bluuebunny/crossref_metadata_2025 huggingface dataset:
IRIS – providing a nationally accessible infrastructure for UK science
Authors: de Witt Shaun , Sansum Andrew , Clarke Peter , Lahiff Andrew
Published: November 2020

In many countries around the world, the development of national infrastructures for science either has been implemented or are under serious consideration by governments and funding bodies. Current examples include ARDC in Australia, CANARIE in Canada and MTA Cloud in Hungary. These infrastructures provide access to compute and storage to a wide swathe of user communities and represent a collaboration between users, providers and, in some cases, industry to maximise the impact of the investments made. The UK has embarked on a project called IRIS to develop a sustainable e-infrastructure based on the needs of a diverse set of communities. Building on the success of the UK component of the WLCG and the innovations made, a number of research institutes and universities are working with several research groups to co-design an infrastructure, including support services, which take this to a level applicable to a wider use base. We present the preparatory work leading to the definition of this infrastructure, showing the wide variety of use cases which require to be supported. This leads us to a definition of the hardware and interface requirements needed to meet this diverse set of criteria, and the support posts identified in order to make best use of this facility and sustain it into the future.
Unroutable Traffic: Maintaining Trust and Integrity of the LHC Open Network Environment
Authors: Hoeft Bruno , Ambroj Pérez Samuel , Bergroth Magnus , O’Connor Michael , Cziva Richard
Published: November 2020

This paper explores the methods and results confirming the baseline assumption that LHCONE[1] (Large Hadron Collider Open Network Environment) traffic is science traffic. The LHCONE is a network conceived to support globally distributed collaborative science. LHCONE connects thousands of researchers to Large Hadron Collider (LHC) datasets at hundreds of universities and labs performing analysis within the global collaboration on high-energy physics. It is “Open” to all levels of the LHC as well as a short list of approved non-LHC science collaborations. LHCONE satisfies the need for a high performance global data transfer network of supporting scientific analysis. Even though LHCONE is a closed virtual private network, packets from non-LHCONE sites were found within the network on multiple occasions. This paper describes the findings, discusses the reasons and proposes some ideas on how to prevent “unroutable LHCONE packets” in order to maintain trust and integrity within the network.
Network in Belle II
Authors: Pardi Silvio
Published: November 2020

Belle II has started the Phase 3 data taking with a fully equipped detector. The data flow at the maximum luminosity is expected to be 12PB of data/year and will be analysed by a cutting-edge computing infrastructure spread over 26 Countries. Several of the major computing centres for HEP in Europe, USA and Canada will store the second copy of RAW data. In this scenario, the international network infrastructure for research plays a key role in supporting and orchestrating all the activities of data analysis and replication. The large-scale network data challenge will also take advantage from LHCONE VRF service and the support of network experts of KEKCC, Belle II sites and NREN. The program of major upgrade in 2019 empowered the connection among Japan, Europe and USA over a 100Gb geographic ring. In this work, we summarize the network requirements needed to accomplish all the tasks provided by the Belle II computing model. We also highlight the status of the major network links that support and advance Belle II. Lastly, we present the results of the last Network Data Challenge campaign performed between KEK and the main RAW data centres with the additional usage of the Data Transfer Node service provided by GÉANT.
Towards a NoOps Model for WLCG
Authors: Gardner Robert , Bryant Lincoln , McKee Shawn , Stephen Judith , Vukotic Ilija , Weaver Christopher , Wu Wenjing
Published: November 2020

One of the most costly factors in providing a global computing infrastructure such as the WLCG is the human effort in deployment, integration, and operation of the distributed services supporting collaborative computing, data sharing and delivery, and analysis of extreme scale datasets. Furthermore, the time required to roll out global software updates, introduce new service components, or prototype novel systems requiring coordinated deployments across multiple facilities is often increased by communication latencies, staff availability, and in many cases expertise required for operations of bespoke services. While the WLCG (and distributed systems implemented throughout HEP) is a global service platform, it lacks the capability and flexibility of a modern platform-as-a-service including continuous integration/continuous delivery (CI/CD) methods, development-operations capabilities (DevOps, where developers assume a more direct role in the actual production infrastructure), and automation. Most importantly, tooling which reduces required training, bespoke service expertise, and the operational effort throughout the infrastructure, most notably at the resource endpoints (sites), is entirely absent in the current model. In this paper, we explore ideas and questions around potential NoOps models in this context: what is realistic given organizational policies and constraints? How should operational responsibility be organized across teams and facilities? What are the technical gaps? What are the social and cybersecurity challenges? Conversely what advantages does a NoOps model deliver for innovation and for accelerating the pace of delivery of new services needed for the HL-LHC era? We will describe initial work along these lines in the context of providing a data delivery network supporting IRIS-HEP DOMA R&D.
Cloudscheduler: a VM provisioning system for a distributed compute cloud
Authors: Sobie Randall , Berghaus Frank , Casteels Kevin , Driemel Colson , Ebert Marcus , Galindo Fernando , Leavett-Brown Colin , MacDonell Danika , Paterson Michael , Seuster Rolf , Tolkamp Shaelyn , Weldon Jodie
Published: November 2020

We describe a high-throughput computing system for running jobs on public and private computing clouds using the HTCondor job scheduler and the cloudscheduler VM provisioning service. The distributed cloud computing system is designed to simultaneously use dedicated and opportunistic cloud resources at local and remote locations. It has been used for large scale production particle physics workloads for many years using thousands of cores on three continents. Cloudscheduler has been modernized to take advantage of new software designs, improved operating system capabilities and support packages. The result is a more resilient and scalable system, with expanded capabilities.
Running HTC and HPC applications opportunistically across private, academic and public clouds
Authors: Lahiff Andrew , de Witt Shaun , Caballer Miguel , La Rocca Giuseppe , Pamela Stanislas , Coster David
Published: November 2020

The Fusion Science Demonstrator in the European Open Science Cloud for Research Pilot Project aimed to demonstrate that the fusion community can make use of distributed cloud resources. We developed a platform, Prominence, which enables users to transparently exploit idle cloud resources for running scientific workloads. In addition to standard HTC jobs, HPC jobs such as multi-node MPI are supported. All jobs are run in containers to ensure they will reliably run anywhere and are reproduceable. Cloud infrastructure is invisible to users, as all provisioning, including extensive failure handling, is completely automated. On-premises cloud resources can be utilised and at times of peak demand burst onto external clouds. In addition to the traditional “cloud-bursting” onto a single cloud, Prominence allows for bursting across many clouds in a hierarchical manner. Job requirements are taken into account, so jobs with special requirements, e.g. high memory or access to GPUs, are sent only to appropriate clouds. Here we describe Prominence, its architecture, the challenges of using many clouds opportunistically and report on our experiences with several fusion use cases.
ATLAS Sim@P1 upgrades during long shutdown two
Authors: Berghaus Frank , Brasolin Franco , Di Girolamo Alessandro , Ebert Marcus , Leavett-Brown Colin Roy , Lee Chris , Love Peter , Pozo Astigarraga Eukeni , Scannicchio Diana Alessandra , Schovancova Jaroslava , Seuster Rolf , Sobie Randall
Published: November 2020

The Simulation at Point1 (Sim@P1) project was built in 2013 to take advantage of the ATLAS Trigger and Data Acquisition High Level Trigger (HLT) farm. The HLT farm provides around 100,000 cores, which are critical to ATLAS during data taking. When ATLAS is not recording data, such as the long shutdowns of the LHC, this large compute resource is used to generate and process simulation data for the experiment. At the beginning of the second long shutdown of the large hadron collider, the HLT farm including the Sim@P1 infrastructure was upgraded. Previous papers emphasised the need for simple, reliable, and efficient tools and assessed various options to quickly switch between data acquisition operation and offline processing. In this contribution, we describe the new mechanisms put in place for the opportunistic exploitation of the HLT farm for offline processing and give the results from the first months of operation.
ScienceBox Converging to Kubernetes containers in production for on-premise and hybrid clouds for CERNBox, SWAN, and EOS
Authors: Bocchi Enrico , Canali Luca , Castro Diogo , Kothuri Prasanth , Gonzalez Labrador Hugo , Malawski Maciej , Mościcki Jakub T. , Mrowczynski Piotr
Published: November 2020

Docker containers are the de-facto standard to package, distribute, and run applications on cloud-based infrastructures. Commercial providers and private clouds expand their offer with container orchestration engines, making the management of resources and containerized applications tightly integrated. The Storage Group of CERN IT leverages on container technologies to provide ScienceBox: An integrated software bundle with storage and computing services for general purposes and scientific use. ScienceBox features distributed scalable storage, sync&share functionalities, and a web-based data analysis service, and can be deployed on a single machine or scaled-out across multiple servers. ScienceBox has proven to be helpful in different contexts, from High Energy Physics analysis to education for high schools, and has been successfully deployed on different cloud infrastructure and heterogeneous hardware.
Running ALICE Grid Jobs in Containers A new approach to job execution for the next generation ALICE Grid framework
Authors: Storetvedt Maxim , Betev Latchezar , Helstrup Håvard , Fanebust Hetland Kristin , Kileng Bjarte
Published: November 2020

The new JAliEn (Java ALICE Environment) middleware is a Grid framework designed to satisfy the needs of the ALICE experiment for the LHC Run 3, such as providing a high-performance and high-scalability service to cope with the increased volumes of collected data. This new framework also introduces a split, two-layered job pilot, creating a new approach to how jobs are handled and executed within the Grid. Each layer runs on a separate JVM, with a separate authentication token, allowing for a finer control of permissions and improved isolation of the payload. Having these separate layers also allows for the execution of job payloads within containers. This allows for the further strengthening of isolation and creates a cohesive environment across computing sites, while avoiding the resource overhead associated with traditional virtualisation.

This contribution presents the architecture of the new split job pilot found in JAliEn, and the methods used to achieve the execution of Grid jobs while maintaining reliable communication between layers. Specifically, how this is achieved despite the possibility of a layer being run in a separate container, while retaining isolation and mitigating possible security risks. Furthermore, we discuss how the implementation remains agnostic to the choice of container platform, allowing it to run within popular platforms such as Singularity and Docker.
WLCG Networks: Update on Monitoring and Analytics
Authors: Babik Marian , McKee Shawn , Andrade Pedro , Bockelman Brian Paul , Gardner Robert , Fajardo Hernandez Edgar Mauricio , Martelli Edoardo , Vukotic Ilija , Weitzel Derek , Zvada Marian
Published: November 2020

WLCG relies on the network as a critical part of its infrastructure and therefore needs to guarantee effective network usage and prompt detection and resolution of any network issues including connection failures, congestion and traffic routing. The OSG Networking Area, in partnership with WLCG, is focused on being the primary source of networking information for its partners and constituents. It was established to ensure sites and experiments can better understand and fix networking issues, while providing an analytics platform that aggregates network monitoring data with higher level workload and data transfer services. This has been facilitated by the global network of the perfSONAR instances that have been commissioned and are operated in collaboration with WLCG Network Throughput Working Group. An additional important update is the inclusion of the newly funded NSF project SAND (Service Analytics and Network Diagnosis) which is focusing on network analytics. This paper describes the current state of the network measurement and analytics platform and summarises the activities taken by the working group and our collaborators. This includes the progress being made in providing higher level analytics, alerting and alarming from the rich set of network metrics we are gathering.
Preparing CERN Tier-0 data centres for LHC Run 3
Authors: Bärring Olof
Published: November 2020

Since 2013 CERN’s local data centre combined with a colocation infrastructure at the Wigner data centre in Budapest [1] have been hosting the compute and storage capacity for Worldwide LHC Computing Grid (WLCG) [2] Tier-0. In this paper we will describe how we try to optimize and improve the operation of our local data centre to meet the anticipated increment of the physics compute and storage requirements for Run 3, taking into account two important changes on the way: the end of the co-location contract with Wigner in 2019 and the loan of 2 out of 6 prefabricated compute modules being commissioned by the LHCb experiment [3] for their online computing farm.
Federated User Account Management
Authors: Karasawa Mizuki , Hover John , Misawa Shigeki
Published: November 2020

BNL SDCC (Scientific Data and Computing Center) recently deployed a centralized identity management solution to support Single Sign On (SSO) authentication across multiple IT systems. The system supports federated login access via CILogon and InCommon and multi-factor authentication (MFA) to meet security standards for various application and services such as Jupyterhub / Invenio that are provided to the SDCC user community. CoManage (cloud-based) and FreeIPA / Keycloak (local) are utilized to provided complex authorization for authenticated users. This talk will focus on technical overviews and strategies to tackle the challenges/obstacles in our facility.
Cosmos : A Unified Accounting System both for the HTCondor and Slurm Clusters at IHEP
Authors: Du Ran , Shi Jingyan , Jiang Xiaowei , Zou Jiaheng
Published: November 2020

HTCondor was adopted to manage the High Throughput Computing (HTC) cluster at IHEP in 2016. In 2017 a Slurm cluster was set up to run High Performance Computing (HPC) jobs. To provide accounting services for these two clusters, we implemented a unified accounting system named Cosmos.

Multiple workloads bring different accounting requirements. Briefly speaking, there are four types of jobs to account. First of all, 30 million single-core jobs run in the HTCondor cluster every year. Secondly, Virtual Machine (VM) jobs run in the legacy HTCondor VM cluster. Thirdly, parallel jobs run in the Slurm cluster, and some of these jobs are run on the GPU worker nodes to accelerate computing. Lastly, some selected HTC jobs are migrated from the HTCondor cluster to the Slurm cluster for research purposes.

To satisfy all the mentioned requirements, Cosmos is implemented with four layers: acquisition, integration, statistics and presentation. Details about the issues and solutions of each layer will be presented in the paper. Cosmos has run in production for two years, and the status shows that it is a well-functioning system, also meets the requirements of the HTCondor and Slurm clusters.
The IPPOG Resource Database: Making particle physics outreach & education available worldwide
Authors: Lapka Marzena , Goldfarb Steven
Published: November 2020

The International Particle Physics Outreach Group (IPPOG) is a network of scientists, science educators and communication specialists working across the globe in informal science education and outreach for particle physics. Members initiate, develop and participate in a variety of activities in classrooms, public events, festivals, exhibitions, museums, institute open days, etc. The IPPOG Resource Database was designed to provide a central location hosting written and multimedia material, tools, recipes, and other content to serve these activities. Objects in the database are categorised by language, target audience, age group, media type, and physics topics. Current efforts include porting the database to the new CERN web infrastructure and improving the interface to serve a public audience. We present our efforts to update procurement and categorisation of educational content, in addition to implementation of a redesigned user interface.
New developments for ALICE MasterClasses and the new Particle Therapy MasterClass
Authors: Graczykowski Łukasz , Nowakowski Piotr , Foka Panagiota
Published: November 2020

International MasterClasses (IMC), an outreach activity of the International Particle Physics Outreach Group (IPPOG), has been bringing cuttingedge particle physics research to schoolchildren for over 15 years now. All four LHC experiments participate in the event, including ALICE, the experiment optimised for the study of heavy-ion collisions. Heavy-ion physics is actively contributing to IMC with new developments such as experimental measurements but also applications for society, such as treatment of cancer with ions. In particular, ALICE provides three MC measurements related to the main observables used to characterize the properties of the produced Quark-Gluon Plasma. Historically, those MC measurements were developed independently, inheriting from the first one, by several ALICE groups. Since all of them are based on the ROOT EVE package, a project to integrate them into a common framework was undertaken. ALICE delivers now a single and easy-to-use application, compiled under Linux, MacOS, and, for the first time, Windows. Then, in line with current IPPOG goals to increase the global reach and scope of the IMC programme a newly developed measurement on medical applications of particle physics, the Particle Therapy MasterClass (PTMC) was introduced in the IMC2020 programme. It is a simplified version of matRad, a MATLAB-based toolkit for calculation of dose deposition in the body and allows for planning of radiotherapy using different modalities and highlighting the benefits of treatment with ions.
Delivering a machine learning course on HPC resources
Authors: Bagnasco Stefano , Fronzé Gabriele Gaetano , Legger Federica , Lusso Stefano , Vallero Sara
Published: November 2020

In recent years, proficiency in data science and machine learning (ML) became one of the most requested skills for jobs in both industry and academy. Machine learning algorithms typically require large sets of data to train the models and extensive usage of computing resources, both for training and inference. Especially for deep learning algorithms, training performances can be dramatically improved by exploiting Graphical Processing Units (GPUs). The needed skill set for a data scientist is therefore extremely broad, and ranges from knowledge of ML models to distributed programming on heterogeneous resources. While most of the available training resources focus on ML algorithms and tools such as TensorFlow, we designed a course for doctoral students where model training is tightly coupled with underlying technologies that can be used to dynamically provision resources. Throughout the course, students have access to a dedicated cluster of computing nodes on local premises. A set of libraries and helper functions is provided to execute a parallelized ML task by automatically deploying a Spark driver and several Spark execution nodes as Docker containers. Task scheduling is managed by an orchestration layer (Kubernetes). This solution automates the delivery of the software stack required by a typical ML workflow and enables scalability by allowing the execution of ML tasks, including training, over commodity (i.e. CPUs) or high-performance (i.e. GPUs) resources distributed over different hosts across a network. The adaptation of the same model on OCCAM, the HPC facility at the University of Turin, is currently under development.
Experience Finding MS Project Alternatives at CERN
Authors: Alandes Pradillo Maria , Jones Pete , Seweryn Piotr Jan
Published: November 2020

As of March 2019, CERN is no longer eligible for academic licences of Microsoft products. For this reason, CERN IT started a series of task forces to respond to the evolving requirements of the user community with the goal of reducing as much as possible the need for Microsoft licensed software. This exercise was an opportunity to understand better the user requirements for different types of applications. Here we focus on MS Project, the dominant PCbased project management software, which has been used at CERN for many years. There were over 1,500 installations at CERN when the task force started, with a heterogeneous pool of users in terms of required functionality, area of work and expertise. This paper will present an evaluation of users’ needs and whether they could be fulfilled with cheaper and less advanced solutions for project management and scheduling. Moreover, selected alternatives, their deployment and lessons learned will be described in more detail. Finally, it will present the approach on how to communicate, train and migrate users to the proposed solutions.
The Official Website of the AMS Experiment
Authors: Behlmann Matthew , Konyushikhin Maxim , Pashnin Andrey , Shan Baosong , Wei Jiahui , Xu Yonghuan , Qu Zhaoyi
Published: November 2020

The Alpha Magnetic Spectrometer (AMS-02) is a particle physics experiment installed on board the International Space Station (ISS). It has been operating since May 2011 and is expected to continue through 2028 or beyond. The AMS collaboration seeks to store, manage and present its research results as well as details about the detector and operations. An open-source content management framework is utilized as the platform to build the website. This platform allows management of a variety of information, such as institutes in the collaboration, physics results, publications, academic events, etc. This note discusses the motivation, strategy, infrastructure, web design techniques, custom modules, data sharing plan, and day-to-day operation. The resulting website is located at https://ams02.space.
ATLAS Open Data – Development of a simple-but-real HEP data analysis framework
Authors: Ould-Saada Farid
Published: November 2020

The ATLAS Collaboration at the Large Hadron Collider is releasing a new set of recorded and simulated data samples at a centre-of-mass energy of 13 TeV collected in pp collisions at the LHC. This new dataset was designed after an in-depth review of the usage of the previous release of samples at 8 TeV. That review showed that capacity-building is one of the most important and abundant uses of public ATLAS samples. To fulfil the requirements of the community and at the same time attract new users and use cases, we developed real analysis software based on ROOT in two of the most popular programming languages: C++ and Python. These so-called analysis frameworks are complex enough to reproduce with reasonable accuracy the results -figures and final yields- of published ATLAS Collaboration physics papers, but still light enough to be run on commodity hardware. With the computers that university students and regular classrooms typically have, students can explore LHC data with similar techniques to those used by current ATLAS analysers. We present the development path and the final result of these analysis frameworks, their products and how they are distributed to final users inside and outside the ATLAS community.
Public Engagement - More than just fun
Authors: Corbett Greg , Collier Ian , Palmer Sophy
Published: November 2020

Public Engagement (PE) with science should be more than “fun” for the staff involved. PE should be a strategic aim of any publically funded science organisation to ensure the public develops an understanding and appreciation of their work, its benefits to everyday life and to ensure the next generation is enthused to take up STEM careers. Most scientific organisations do have aims to do this, but very few have significant budgets to deliver this. In a landscape of ever tightening budgets, how can we develop a sustainable culture of PE within these organisations?

UKRI/STFC’s Scientific Computing Department present how we have worked to embed a culture of PE with the department by developing our early career staff members; highlighting the impact PE makes at the departmental and project level; and linking PE to our competency framework.

We will also discuss how our departmental work interacts with and complements STFC’s organisational-wide PE effort, such as making use of a shared evaluation framework that allows us to evaluate our public engagement activities against their goals and make strategic decisions about the programme’s future direction.
CMS strategy for HPC resource exploitation
Authors: Pérez-Calero Yzquierdo Antonio
Published: November 2020

High Energy Physics (HEP) experiments will enter a new era with the start of the HL-LHC program, with computing needs surpassing by large factors the current capacities. Anticipating such scenario, funding agencies from participating countries are encouraging the experimental collaborations to consider the rapidly developing High Performance Computing (HPC) international infrastructures to satisfy at least a fraction of the foreseen HEP processing demands. These HPC systems are highly non-standard facilities, custom-built for use cases largely different from HEP demands, namely the processing of particle collisions (real or simulated) which can be analyzed individually without correlation. The access and utilization of these systems by HEP experiments will not be trivial, given the diversity of configuration and requirements for access among HPC centers, increasing the level of complexity from the HEP experiment integration and operations perspectives. Additionally, while HEP data is residing on a distributed highly-interconnected storage infrastructure, HPC systems are in general not meant for accessing large data volumes residing outside the facility. Finally, the allocation policies to these resources are generally different from the current usage of pledged resources deployed at supporting Grid sites. This report covers the CMS strategy developed to make effective use of HPC resources, involving a closer collaboration between CMS and HPC centers in order to further understand and subsequently overcome the present obstacles. Progress in the necessary technical and operational adaptations being made in CMS computing is described.
Geant Exascale Pilot Project
Authors: Canal Philippe , Sexton-Kennedy Elizabeth , Madsen Jonathan , Jun Soon Yung , Lima Guilherme , Calafiura Paolo , Wang Yunsong , Johnson Seth
Published: November 2020

The upcoming generation of exascale HPC machines will all have most of their computing power provided by GPGPU accelerators. In order to be able to take advantage of this class of machines for HEP Monte Carlo simulations, we started to develop a Geant pilot application as a collaboration between HEP and the Exascale Computing Project. We will use this pilot to study and characterize how the machines’ architecture affects performance. The pilot will encapsulate the minimum set of physics and software framework processes necessary to describe a representative HEP simulation problem. The pilot will then be used to exercise communication, computation, and data access patterns. The project’s main objective is to identify re-engineering opportunities that will increase event throughput by improving single node performance and being able to make efficient use of the next generation of accelerators available in Exascale facilities.
Migrating Engineering Windows HPC applications to Linux HTCondor and Slurm Clusters
Authors: Alandes Pradillo Maria , Høimyr Nils , Llopis Sanmillan Pablo , Tapani Jylhänkangas Markus
Published: November 2020

The CERN IT department has been maintaining different High Performance Computing (HPC) services over the past five years. While the bulk of computing facilities at CERN are running under Linux, a Windows cluster was dedicated for engineering simulations and analysis related to accelerator technology development. The Windows cluster consisted of machines with powerful CPUs, big memory, and a low-latency interconnect. The Linux cluster resources are accessible through HTCondor, and are used for general purpose parallel but single-node type jobs, providing computing power to the CERN experiments and departments for tasks such as physics event reconstruction, data analysis, and simulation. For HPC workloads that require multi-node parallel environments for Message Passing Interface (MPI) based programs, there is another Linux-based HPC service that is comprised of several clusters running under the Slurm batch system, and consist of powerful hardware with low-latency interconnects.

In 2018, it was decided to consolidate compute intensive jobs in Linux to make a better use of the existing resources. Moreover, this was also in line with CERN IT strategy to reduce its dependencies on Microsoft products. This paper focuses on the migration of Ansys [1], COMSOL [2] and CST [3] users from Windows HPC to Linux clusters. Ansys, COMSOL and CST are three engineering applications used at CERN for different domains, like multiphysics simulations and electromagnetic field problems. Users of these applications are in different departments, with different needs and levels of expertise. In most cases, the users have no prior knowledge of Linux. The paper will present the technical strategy to allow the engineering users to submit their simulations to the appropriate Linux cluster, depending on their simulation requirements. We also describe the technical solution to integrate their Windows workstations in order from them to be able to submit to Linux clusters. Finally, we discuss the challenges and lessons learnt during the migration.
Towards a Turnkey Software Stack for HEP Experiments
Authors: Sailer André , Ganis Gerardo , Mato Pere , Petrič Marko , Stewart Graeme A.
Published: November 2020

Future HEP experiments require detailed simulation and advanced reconstruction algorithms to explore the physics reach of their proposed machines and to design, optimise, and study the detector geometry and performance. To synergize the development of the CLIC and FCC software efforts, the CERN EP R&D roadmap proposes the creation of a “Turnkey Software Stack”, which is foreseen to provide all the necessary ingredients, from simulation to analysis, for future experiments; not only CLIC and FCC, but also for proposed Super-tau-charm factories, CEPC, and ILC. The software stack will facilitate writing specific software for experiments ensuring coherency and maximising the re-use of established packages to benefit from existing solutions and community developments, for example, ROOT, Geant4, DD4hep, Gaudi and podio. As a showcase for the software stack, the existing CLIC reconstruction software, written for iLCSoft, is being to be ported to Gaudi. In parallel, the back-end of the LCIO event data model can be replaced by an implementation in podio. These changes will enable the sharing of the algorithms with other users of the software stack.

We will present the current status and plans of the turnkey software stack, with a focus of the adaptation of the CLIC reconstruction chain to Gaudi and podio, and detail the plans for future developments to generalise their applicability to FCC and beyond.
GPU-based reconstruction and data compression at ALICE during LHC Run 3
Authors: Rohr David
Published: November 2020

In LHC Run 3, ALICE will increase the data taking rate significantly to 50 kHz continuous read out of minimum bias Pb-Pb collisions. The reconstruction strategy of the online offline computing upgrade foresees a first synchronous online reconstruction stage during data taking enabling detector calibration, and a posterior calibrated asynchronous reconstruction stage. The significant increase in the data rate poses challenges for online and offline reconstruction as well as for data compression. Compared to Run 2, the online farm must process 50 times more events per second and achieve a higher data compression factor. ALICE will rely on GPUs to perform real time processing and data compression of the Time Projection Chamber (TPC) detector in real time, the biggest contributor to the data rate. With GPUs available in the online farm, we are evaluating their usage also for the full tracking chain during the asynchronous reconstruction for the silicon Inner Tracking System (ITS) and Transition Radiation Detector (TRD). The software is written in a generic way, such that it can also run on processors on the WLCG with the same reconstruction output. We give an overview of the status and the current performance of the reconstruction and the data compression implementations on the GPU for the TPC and for the global reconstruction.
The Evolution of Analysis Models for HL-LHC
Authors: Rizzi Andrea
Published: November 2020

A quick review of how analyses were and are performed at LHC in Run1 and Run2 is proposed. A discussion then follow on how this could scale and what can be improved for Run3 and for High Lumi LHC. Critical items are highlighted and some interesting emerging technologies are discussed.
Échanger et convaincre au niveau international
Authors:   La rédaction Sfen
Published: November 2020

Les institutions internationales du nucléaire ont participé à l’adaptation des filières nationales aux nouvelles conditions d’exploitation du parc nucléaire au coeur de la crise de la Covid-19. L’objectif était de continuer à échanger des informations afin que les mesures de confinement ne soient pas synonymes d’isolement pour les exploitants.
Terahertz accelerator based electron and x-ray sources
Authors: Kärtner Franz X.
Published: November 2020

The generation and use of THz radiation for electron acceleration and manipulation of electron bunches has progressed over the last decade to a level where practical devices for THz guns, acceleration and a wide range of beam manipulations have become possible. Here, we present our progress on generation of single-cycle THz pulses at the two-hundred micro-Joule level to drive advanced acceleration and beam manipulation devices. Specifically, we use pulses centered at 0.3 THz to power a segmented terahertz electron accelerator and manipulator (STEAM) capable of performing multiple high-field operations on the 6D-phase-space of ultrashort electron bunches. Using this STEAM device, we demonstrate record THz-acceleration of >60 keV, streaking with <10 𝑓s resolution, focusing with >2 kT/m strength, compression to ~100 𝑓s as well as real-time switching between these modes of operation. The STEAM device demonstrates the feasibility of THz-based electron accelerators, manipulators and diagnostic tools enabling science beyond current resolution frontiers with transformative impact.
Definition, reasons, and risk factors for mortality of patients listed for liver transplantation – a single-center study
Authors: Peschel Georg , Kraft Ina-Christine , Ilkhtchoui Ramin , Schmid Stephan , Sinner Barbara , Scherer Marcus N , Mueller-Schilling Martina , Weigand Kilian
Published: November 2020

Background In Germany, following the principle “sickest first”, patients awaiting liver transplantation (LTPL) are often transplanted with high MELD score and run the risk that they can no longer be transplanted, getting “too sick for transplant”.

Methods In a retrospective single-center study, we analyzed the mortality of adult patients on the waiting list for LTPL during the years 2014 to 2017. To stratify risk factors, we compared characteristics of deceased and transplanted patients.

Results The main reasons for mortality were sepsis (42.9 %), malignancy (24.3 %) and bleeding (10.0 %). Risk factors for mortality (OR, univariate logistic regression, p < 0.05) were acute on chronic liver failure (ACLF), loss of E-MELD, sepsis, pneumonia, proof of pathogens, candidemia, stay at ICU, multiple organ failure and mechanical ventilation. Multivariate analysis revealed pneumonia (p < 0.001) and high MELD (p = 0.031) as risk factors. Transplantation was more likely in patients with E-MELD. We suggest a Waiting List Mortality Index for Transplantation (WMIT), by dividing deceased patients to transplanted patients to assess mortality. Average WMIT in our cohort was 0.65.

Conclusions Mortality on the waiting list is mainly determined by pneumonia and infections in high-MELD patients. Therefore, patients with ACLF after infections should be prioritized for LTPL. A WMIT might suitably represent waiting list mortality.
Retrospektive Querschnittsstudie von bundesweiten Arzneiverordnungsdaten und vertragsärztlichen Abrechnungsdaten von Morbus Wilson
Authors: Janka Simone-Svea , Bätzing Jörg , Laux Gunter , Holstiege Jakob , Wahler Steffen , Merle Uta , Mehrabi Arianeb , Mohr Isabelle , Weiss Karl Heinz , Mieth Markus
Published: November 2020

Einführung In diesem Beitrag wird die Prävalenz der Erkrankung „Morbus Wilson“ in Deutschland auf der Grundlage von bundesweiten Arzneiverordnungsdaten und vertragsärztlichen Abrechnungsdaten ermittelt und in ein Verhältnis zu der in Deutschland ermittelten Verordnungshäufigkeit gesetzt.

Methodik Für die deskriptive Darstellung der Abrechnungsdaten wird die Datenbank des Zentralinstituts für die kassenärztliche Versorgung (Zi) genutzt. Weiterhin liegen Daten des Statistischen Bundesamts über die stationäre Behandlung vor.

Ergebnisse Auffällig ist die Differenz zwischen den Prävalenzen der therapierten Patienten und der ermittelten gesicherten Diagnosen. Die Prävalenz insgesamt steigt. Die ermittelte Inzidenz und die Betrachtung der Dynamik der Patientenpopulation könnten möglicherweise auf eine hohe Fehldiagnostikrate im ersten Erkrankungsjahr schließen lassen. Nach Datenlage ist die hepatische Verlaufsform die häufigere diagnostizierte Verlaufsform. Die humangenetische Diagnose steigt im Durchschnitt am deutlichsten an.

Schlagwörter Morbus Wilson, Prävalenz, Inzidenz, Trientine, Trientintetrahydrochlorid, D-Penicillamin, Zinkacetat, Zink
Matrix-convex set theory reveals non-classical behavior of quantum magic squares
Authors: Ishimaru Matthew
Published: November 2020

Researchers have disproved a quantum version of the Birkhoff-von Neumann theorem, which relates magic squares to permutation matrices.
Properties and potential applications of reflection focusing and dispersion plane gratings
Authors: Yang Zuhua , Li Pengfei , Fan Quanping , Wei Lai , Chen Yong
Published: November 2020

Plane gratings are widely used as dispersion elements in spectral analysis from the infrared to x-ray regions. This study proposes an optical element, consisting of only a reflection focusing and dispersion plane grating (RFPG) designed for a specific wavelength. A raytracing simulation and a visible light experiment were performed to verify the focusing and wavelength dispersion properties of the proposed RFPG. The raytracing simulation result shows that the designed 635 nm RFPG has a spectral resolution (λ/∆λ) of 423 (linear dispersion = 493.8 eV/m) under specific conditions. Additionally, in the visible light experiment, the spectral resolution of 423 (linear dispersion = 493.8 eV/m) and band range of ±25 nm were obtained at the target wavelength of 635 nm. The experimental results indicate that the proposed optical element, RFPG, exhibits focusing and dispersion properties for a designed wavelength. It is a potential tool for the study of x-ray fluorescence, absorption, and advanced x-ray sources, such as laser wakefield Betatron x-ray sources.
Individual-level correlations of rumen volatile fatty acids with enteric methane emissions for ranking methane yield in sheep fed fresh pasture
Authors: Jonker Arjan , Hickey Sharon , Boma Paul , Woyimo Woju Chernet , Sandoval Edgar , MacLean Sarah , García Rendón Calzada Mariana , Yu Wanjie , Lewis Sarah , Janssen Peter H. , McEwan John C. , Rowe Suzanne
Published: November 2020

Context
Total ruminal volatile fatty acids (VFA) or acetate concentrations were previously found to be moderate correlated proxies to select sheep that are genetically low methane (CH4) emitters. However, this was based on trials, with sheep fed lucerne pellets at a fixed feeding level, which is different from pastoral farming conditions in New Zealand, where the correlated proxy would be applied.

Aim
To determine repeatability and individual-level correlation of rumen VFAs with CH4 emissions in sheep fed ad libitum cut pasture in three and four repeated periods in Experiments 1 and 2 respectively. Sheep in Experiment 1 were also fed lucerne pellets at 2.0 × maintenance-energy requirements in two periods.

Methods
Methane emissions were measured from 96 and 72 animals, in Experiments 1 and 2 respectively, in respiration chambers and rumen samples were collected via oral stomach tubing before morning feeding. Repeatability estimates between periods within feed and experiment serve as an upper threshold for the estimate of heritability and ri estimates are a proxy for genetic correlation.

Key results
Methane (g/day) production and yield (g/kg dry-matter intake) were low to moderately repeatable traits on pasture across periods (0.58 and 0.39 for CH4 production and 0.43 and 0.32 for yield in Experiments 1 and 2 respectively). On pasture, repeatability was generally greater for VFA proportions (0.13–0.32) than for VFA concentrations (0.02–0.24), while the opposite was the case on lucerne pellets. Rumen propionate as a proportion of total VFA had strong negative ri (−0.82 and −0.87) and acetate:propionate ratio (A:P; 0.82 and 0.78) and (acetate + butyrate):(propionate + valerate) ratio (AB:PV; 0.84 and 0.82) had a strong positive ri with CH4 yield in sheep fed cut pasture, while the ri of total ruminal VFA (−0.13 and 0.35) and acetate (−0.08 and 0.38) concentrations with CH4 yield were only moderate and non-significant.

Conclusion
The VFA traits propionate proportion and A:P and AB:PV ratios had strong individual-level correlations with CH4 yield in sheep fed pasture ad libitum, suggesting that they would be useful correlated proxies to rank sheep CH4 yields.
Convergent evolution of sexually dimorphic glands in an amphi-Pacific harvestman family
Authors: Gainett Guilherme , Willemart Rodrigo H. , Giribet Gonzalo , Sharma Prashant P.
Published: November 2020

Sexually dimorphic traits are widespread in animals, and include sex-specific weapons, ornamentation and, although less noticed, glands and associated structures. In arachnids, certain lineages of the order Opiliones exhibit diverse forms of dimorphism in the armature and length of appendages (common in Laniatores), as well as in the presence of sexually dimorphic glands (mostly investigated in Cyphophthalmi), positing harvestmen as promising models to study sexual dimorphism. Whereas the evolution and ecological significance of armature have been the focus of recent attention, sexually dimorphic glands remain understudied in groups other than Cyphophthalmi, despite being widespread in Opiliones. We therefore selected the amphi-Pacific family Zalmoxidae as an ideal taxon to investigate the evolutionary dynamics of this trait. We first describe four new species of Palaeotropical Zalmoxis, including a species with sexually dimorphic glands, and describe the morphology of zalmoxid species with sexually dimorphic glands using scanning electron microscopy. Using a previously assembled six-locus dataset supplemented with new terminals, and applying stochastic character mapping, we infer that sexually dimorphic glands evolved once in the Neotropics and at least four times in the Palaeotropic zalmoxids, revealing the evolutionary lability of this trait.
The moderating impact of maturation on acute neuromuscular and psycho‐physiological responses to simulated soccer activity in academy soccer players
Authors: Salter Jamie , De Ste Croix Mark B.A. , Hughes Jonathan D.
Published: November 2020

Resource constraints complicate load monitoring practices in some academies, which is problematic based on load‐injury associations surrounding periods of rapid non‐linear growth. Limited research has explored relationships between maturation and perceived psycho‐physiological response to activity and associated neuromuscular performance changes. This study aimed to quantify neuromuscular and psycho‐physiological responses to standardised activity and analyse whether dose‐responses were moderated by maturation. Fifty‐seven male soccer players (age: 14.1 ± 0.9 years; stature: 165 ± 10 cm; body mass, 57 ± 9 kg; percentage of predicted adult height 92.7 ± 5%) from two Elite Player Performance Plan (EPPP) academies completed the youth soccer‐specific aerobic fitness test (Y‐SAFT60). Countermovement jump (CMJ), reactive strength index (RSI), absolute (ABS) and relative leg stiffness (REL) were measured pre–post the Y‐SAFT60 with playerload (PL), heart rate (HR), total distance (TDist) and differential ratings of perceived exertion (dRPE) used as markers of load and intensity. A moderation model was employed to analyse interactions of maturation as a continuous variable. Analysis indicated no significant interaction (p <0.05) between maturation and neuromuscular performance but RPE‐Technical demonstrated significant interactions (p = 0.01). Slope analysis indicated four variables (PL, RSI, ABS and REL) that demonstrated significance at various stages of maturation, most notably aligning with peak height velocity (∼87–96% PAH). Tentatively, we propose that maturational developments in the neuromuscular system offer some mechanistic explanation to the varied dose‐responses observed. It is therefore important that maturation is habitually considered within prescription of training programmes and that further empirical studies are completed to determine maturity specific dose‐responses.