bluuebunny/crossref_metadata_2025 huggingface dataset:
The role of water in the formation of crystal structures: a case study of valnemulin hydrochloride
Authors: Li Shuyu , Wang Ting , Huang Xin , Zhou Lina , Chen Mingyu , Liu Wanying , Zhang Xiunan , Dong Yuyuan , Hao Hongxun
Published: November 2020

Water molecules play a key role in the formation of crystalline state valnemulin hydrochloride.
Complete equations of state for PETN and its products from atomistic simulations
Authors: Sergeev Oleg V. , Mukhanov Andrei E. , Murzov Semen A. , Yanilkin Aleksey V.
Published: November 2020

Complete equations of state for PETN and the products of its thermal decomposition are obtained using DFT and ReaxFF simulations.
Cryogenic ion trap vibrational spectroscopy of the microhydrated sulfate dianions SO42−(H2O)3−8
Authors: Knorke Harald , Li Huiyan , Warneke Jonas , Liu Zhi-Feng , Asmis Knut R.
Published: November 2020

Infrared photodissociation spectra of microhydrated sulfate dianions with three to eight water molecules are presented over a broad spectral range that covers intramolecular solvent and solute modes as well as intermolecular librational modes.
Accelerating atomistic simulations with piecewise machine-learned ab Initio potentials at a classical force field-like cost
Authors: Zhang Yaolong , Hu Ce , Jiang Bin
Published: November 2020

Combining piecewise switching functions with embedded atom neural networks to accelerate atomistic simulations with ab initio accuracy.
Facile synthesis of a novel nitrogen-doped carbon dot adorned zinc oxide composite for photodegradation of methylene blue
Authors: Atchudan Raji , Edison Thomas Nesakumar Jebakumar Immanuel , Mani Shanmugam , Perumal Suguna , Vinodh Rajangam , Thirunavukkarasu Somanathan , Lee Yong Rok
Published: November 2020

Nitrogen-doped carbon dot decorated zinc oxide nanoparticles were successfully fabricated by an economical wet-impregnation method and used as a photocatalyst for the degradation of aqueous methylene blue dye under UV-light at room temperature.
Polymerization inspired synthesis of MnO@carbon nanowires with long cycling stability for lithium ion battery anodes: growth mechanism and electrochemical performance
Authors: Zhou Fang , Li Shuangfu , Han Kai , Li Yajuan , Liu You-Nian
Published: November 2020

MnO@carbon (MnO@C) nanowires are synthesized via the polymerization inspired in situ growth of [Mn–NTA] (NTA = nitrilotriacetic acid) precursor nanowires with a subsequent heat treatment process.
Improving the charge transport of the ternary blend active layer for efficient semitransparent organic solar cells
Authors: Yin Pan , Yin Zhigang , Ma Yunlong , Zheng Qingdong
Published: November 2020

With the aid of a suitable third component acceptor material, the best-performance semitransparent organic solar cell shows an outstanding efficiency of 13.49% at an average visible transmittance of 22.58%.
Environmentally benign decarboxylative N-, O-, and S-acetylations and acylations
Authors: Ghosh Santanu , Purkait Anisha , Jana Chandan K.
Published: November 2020

A general method for N-, O- and S-acetylation and acylation using Meldrum's acid and its derivatives has been developed.
Temperature-responsive collagen–PNIPAAm conjugate: preparation and fibrillogenesis
Authors: Zhang Juntao , Deng Fen , Liu Wei , Huang Yaozhi , Tu Xiao , Kou Huizhi , He Lang , Wei Benmei , Xu Chengzhi , Wang Haibo
Published: November 2020

A collagen–PNIPAAm conjugate is prepared using the “grafting from” method under mild conditions, and fibrillogenesis was realized by the induction of natural collagen.
Research advances in integrated theranostic probes for tumor fluorescence visualization and treatment
Authors: Xing Jie , Gong Qiuyu , Akakuru Ozioma Udochukwu , Liu Chuang , Zou Ruifen , Wu Aiguo
Published: November 2020

Fuorescent theranostic probes have developed rapidly in the field of precision medicine with their distinctive merit. This review, we described the design strategy and function of fluorescence-based probes in tumor visualization and treatment.
Optical control of ferroelectric switching and multifunctional devices based on van der Waals ferroelectric semiconductors
Authors: Xu Kai , Jiang Wei , Gao Xueshi , Zhao Zijing , Low Tony , Zhu Wenjuan
Published: November 2020

Combining the electrical and optical control of the polarization, we demonstrate multifunctional devices based on van der Waals ferroelectric In2Se3, which can serve as a logic switch, photodetector, electronic memory, and photonic memory concurrently.
A Dy6-cluster-basedfcu-MOF with efficient separation of C2H2/C2H4and selective adsorption of benzene
Authors: Li Yong-Zhi , Wang Hai-Hua , Wang Gang-Ding , Hou Lei , Wang Yao-Yu , Zhu Zhonghua
Published: November 2020

A stable Dy-MOF was constructed based on hexanuclear clusters, and contains F-decorated pores and reveals separation performance for C2H2/CH4, C2H4/CH4and C2H2/C2H4and selective adsorption of benzene/cyclohexane and benzene/toluene.
Preparation and modification of cellulose sponge and application of oil/water separation
Authors: Meng Xu , Dong Yanyan , Zhao Yajun , Liang Liping
Published: November 2020

This work presents a facile preparation and modification of cellulose sponge with hydrophobic/oleophilic surface wetting properties.
Time dependence of electrical characteristics during the charge decay from a single gold nanoparticle on silicon
Authors: Abbas Yawar , Rezk Ayman , Saadat Irfan , Nayfeh Ammar , Rezeq Moh'd
Published: November 2020

In this work, we investigate the time dependence of trapped charge in isolated gold nanoparticles (Au-NPS) dispersed on n-Si substrates, based on the electrical characteristics of nano metal–semiconductor junctions.
Supramolecular strategies in artificial photosynthesis
Authors: Keijer Tom , Bouwens Tessel , Hessels Joeri , Reek Joost N. H.
Published: November 2020

This review describes supramolecular strategies for optimization and integration of components needed for the fundamentals of artificial photosynthesis: light harvesting, charge-separation and catalysis, which are relevant for solar-to-fuel devices.
Sugar-alcohol@ZIF nanocomposites display suppressed phase-change temperatures
Authors: Hackl Lukas , Hsu Chih-Hao , Gordon Madeleine P. , Chou Kelly , Ma Canghai , Kolaczkowski Matthew , Anderson Christopher L. , Liu Yi-Sheng , Guo Jinghua , Ercius Peter , Urban Jeffrey J.
Published: November 2020

The synthesis and characterization of phase change materials infused into metal–organic framework crystals to demonstrate high latent heats with suppressed phase change temperatures.
Porphyrin based metal–organic framework films: nucleation and growth
Authors: Zhou Zhenyu , Mukherjee Soumya , Warnan Julien , Li Weijin , Wannapaiboon Suttipong , Hou Shujin , Rodewald Katia , Rieger Bernhard , Weidler Peter G. , Wöll Christof , Fischer Roland A.
Published: November 2020

This study demonstrates the pros and cons of different methods in the fabrication of functional porphyrin based MOF films, potentially offering critical reference points for the preparation of next-generation functional MOF thin films in general.
A sensitive fluorescent probe for β-galactosidase activity detection and application in ovarian tumor imaging
Authors: Fan Fang , Zhang Li , Zhou Xinguang , Mu Fangya , Shi Guoyue
Published: November 2020

A sensitive fluorescent probe for β-galactosidase activity detection in vivo and near-infrared imaging of ovarian tumors by detecting β-gal.
The application of Ni and Cu-MOFs as highly efficient catalysts for visible light-driven tetracycline degradation and hydrogen production
Authors: Shang Qigao , Liu Nannan , You Dan , Cheng Qingrong , Liao Guiying , Pan Zhiquan
Published: November 2020

The application of Ni and Cu-MOFs as highly efficient catalysts for visible light-driven TC degradation and hydrogen production.
Successful Implicit Vocabulary Intervention for Three Cantonese-Speaking Toddlers: A Replicated Single-Case Design
Authors: S.-Y. Ng Christine , Stokes Stephanie F. , Alt Mary
Published: November 2020

Purpose

We report on a replicated single-case design study that measured the feasibility of an expressive vocabulary intervention for three Cantonese-speaking toddlers with small expressive lexicons relative to their age. The aim was to assess the cross-cultural and cross-linguistic feasibility of an intervention method developed for English-speaking children.

Method

A nonconcurrent multiple-baseline design was used with four baseline data points and 16 intervention sessions per participant. The intervention design incorporated implicit learning principles, high treatment dosage, and control of the phonological neighborhood density of the stimuli. The children (24–39 months) attended 7–9 weeks of twice weekly input-based treatment in which no explicit verbal production was required from the child. Each target word was provided as input a minimum of 64 times in at least two intervention sessions. Treatment feasibility was measured by comparison of how many of the target and control words the child produced across the intervention period, and parent-reported expressive vocabulary checklists were completed for comparison of pre- and postintervention child spoken vocabulary size. An omnibus effect size for the treatment effect of the number of target and control words produced across time was calculated using Kendall's Tau.

Results

There was a significant treatment effect for target words learned in intervention relative to baselines, and all children produced significantly more target than control words across the intervention period. The effect of phonological neighborhood density on expressive word production could not be evaluated because two of the three children learned all target words.

Conclusion

The results provide cross-cultural evidence of the feasibility of a model of intervention that incorporated a high-dosage, cross-situational statistical learning paradigm to teach spoken word production to children with small expressive lexicons.
Analysis of Language Errors in Speakers Who Are Bilingual Under Quiet and Background Noise Conditions
Authors: Barbosa Bruna A. , Coles-White D'Jaris , Regal Darah , Kijai Jimmy
Published: November 2020

Purpose

This study discusses the ways in which the presence of background noise may adversely affect bilingual students' ability to repeat speech, specifically, whether the presence of background noise increases lexical, grammatical, omission, and other errors on the AzBio Sentence Test.

Method

Participants consisted of 15 monolingual English (first language) speakers and 41 bilingual (second language [L2]) speakers from Spanish, Portuguese, and Korean language groups, ranging from students who learned English after the age of 4 years to adulthood. Participants completed the AzBio Sentence Test in both quiet and background noise environments. A language analysis was conducted, and errors were classified under categories of lexical, grammatical, omissions, and other.

Results

The results of this study show that L2 speakers made more lexical, grammatical, omissions, and other errors than first language speakers on the AzBio Sentence Test. In background noise, all bilingual language groups made more errors than monolinguals. Portuguese speakers notably made more omissions than other language groups. This study also shows that participants who were introduced to English at a younger age made fewer errors.

Conclusions

In conclusion, our results corroborate previous research, indicating that bilingual speakers have more difficulty accurately interpreting speech in the presence of background noise. These findings have implications for classroom instruction considering the statistically higher percentage of omissions made by L2 speakers.
Developing Cultural Competence From a Funds of Knowledge Framework: Ethnographic Interviewing Revisited
Authors: Jenkins Kimberly , Rojas Raúl
Published: November 2020

Purpose

This article discusses the clinical utility of ethnographic interviewing as an approach for capitalizing on the life knowledge and skills of a broad range of individuals, with varied cultural backgrounds, during clinical practice. An overview of ethnographic interviewing procedures, a description of the
Funds of Knowledge
framework, and its application are presented.

Conclusions

As the ethnic and racial composition of the general population in the United States shifts, speech-language pathologists and audiologists can expect this to be reflected in the ethno-racial profiles of the clients and families they serve. To continue to deliver the highest quality of speech, language, and/or hearing services, it will become increasingly important for clinicians to engage in ongoing practices that develop and expand their competence and understanding of the cultural and linguistic needs and values of each client and family. This article proposes that ethnographic interviewing, grounded in a
Funds of Knowledge
framework, offers a means for clinicians to discover the knowledge and resources that clients and families have acquired through their everyday life experiences. Notably, it is suggested that, when viewed as valuable assets, such experiences can significantly contribute to the delivery of culturally competent clinical services and potentially help decrease biases in clinical decision making.
Fast and Efficient Entropy Compression of ALICE Data using ANS Coding
Authors: Lettrich Michael
Published: November 2020

In LHC Run 3, the upgraded ALICE detector will record 50 kHz Pb-Pb collisions using continuous readout. The resulting stream of raw data to be inspected increases to ~ 1 TB/s a hundredfold increase over Run 2 must be processed with a set of lossy and lossless compression and data reduction techniques to decrease the data rate to storage to 90 GB/s without affecting the physics.

This contribution focuses on lossless entropy coding for ALICE Run 3 data which is the final component in the compression stage. We analyze data from the ALICE TPC and point out the challenges imposed by the non-standard data with a patchy distribution and symbol sizes of up to 25 Bit. We then explain why rANS, a variant of Asymmetric Numeral System coders is suitable for compressing this data effectively. Finally we present first compression performance numbers and bandwidth measurements obtained from a prototype implementation and give an outlook for future developments.
DUNE DAQ R&D integration in ProtoDUNE Single-Phase at CERN
Authors: Sipos Roland
Published: November 2020

The DAQ system of ProtoDUNE-SP successfully proved its design principles and met the requirements of the beam run of 2018. The technical design of the DAQ system for the DUNE experiment has major differences compared to the prototype due to different requirements placed on the detector, as well as a radically different location of operation. The single-phase prototype at CERN is a major integration facility for R&D aspects of the DUNE DAQ system. The facility allows for the exploration of additional data processing capabilities and optimization of the FELIX system, which is the chosen TPC readout solution for the DUNE single-phase detectors. One of the fundamental differences from the prototype is that the DUNE DAQ relies on self-triggering. Therefore, real-time processing of the data stream for hit and trigger primitive finding is essential for the requirement of continuous readout. The supernova burst trigger requires a large and fast buffering technique, where 3D XPoint persistent memory solutions are evaluated and integrated. In order to maximize resource utilization of the FELIX hosting servers, the elimination of the 100 Gb network communication stack is desired. This implies the design and development of a single-host application layer, which is a fundamental element of the self-triggering chain. This paper discusses the evaluation and integration of these developments for the DUNE DAQ, in the ProtoDUNE environment.
DAQling: an open-source data acquisition framework
Authors: Boretto Marco , Brylinski Wojciech , Lehmann Miotto Giovanna , Gamberini Enrico , Sipos Roland , Sonesten Viktor Vilhelm
Published: November 2020

The Data AcQuisition (DAQ) software for most applications in high energy physics is composed of common building blocks, such as a networking layer, plug-in loading, configuration, and process management. These are often re-invented and developed from scratch for each project or experiment around specific needs. In some cases, time and available resources can be limited and make development requirements difficult or impossible to meet. Moved by these premises, our team developed an open-source lightweight C++ software framework called DAQling, to be used as the core for the DAQ systems of small and medium-sized experiments and collaborations. The framework offers a complete DAQ ecosystem, including a communication layer based on the widespread ZeroMQ messaging library, configuration management based on the JSON format, control of distributed applications, extendable operational monitoring with web-based visualisation, and a set of generic utilities. The framework comes with minimal dependencies, and provides automated host and build environment setup based on the Ansible automation tool. Finally, the end-user code is wrapped in so-called “Modules”, that can be loaded at configuration time, and implement specific roles. Several collaborations already chose DAQling as the core for their DAQ systems, such as FASER, RD51, and NA61/SHINE. We will present the framework and project-specific implementations and experiences.
AliECS: a New Experiment Control System for the ALICE Experiment
Authors: Mrnjavac Teo , Alexopoulos Konstantinos , Chibante Barroso Vasco , Raduta George
Published: November 2020

The ALICE Experiment at CERN’s Large Hadron Collider (LHC) is undertaking a major upgrade during LHC Long Shutdown 2 in 2019-2021, which includes a new computing system called O2 (Online-Offline). To ensure the efficient operation of the upgraded experiment and of its newly designed computing system, a reliable, high performance, and automated experiment control system is being developed. The ALICE Experiment Control System (AliECS) is a distributed system based on state of the art cluster management and microservices that have recently emerged in the distributed computing ecosystem. Such technologies will allow the ALICE collaboration to benefit from a vibrant and innovating open source community. This communication describes the AliECS architecture. It provides an in-depth overview of the system’s components, features, and design elements, as well as its performance. It also reports on the experience with AliECS as part of ALICE Run 3 detector commissioning setups.
The Heavy Photon Search (HPS) Software Environment
Authors: Graf Norman
Published: November 2020

The Heavy Photon Search (HPS) is an experiment at the Thomas Jefferson National Accelerator Facility (JLab) designed to search for a hidden sector photon (A’) in fixed-target electro-production. It uses a silicon microstrip tracking and vertexing detector placed inside a dipole magnet to measure charged particle trajectories and a fast lead-tungstate crystal calorimeter located just downstream of the magnet to provide a trigger and to identify electromagnetic showers. The HPS experiment uses both invariant mass and secondary vertex signatures to search for the A’. The experimental collaboration is small and quite heterogeneous: it is composed of members of the nuclear physics as well as particle physics communities, from universities and national labs from around the US and Europe. Enabling such a disparate group to concentrate on the physics aspects of the experiment required that the software be easy to install and use, and having such limited manpower meant that existing solutions had to be exploited.

HPS has successfully completed two engineering runs and completed its first physics run in the summer of 2019. We begin with an overview of the physics goals of the experiment followed by a short description of the detector design. We then describe the software tools used to design the detector layout and simulate the expected detector performance. Event reconstruction involving track, cluster and vertex finding and fitting for both simulated and real data was, to first order, adopted from existing software originally developed for Linear Collider studies. Bringing it all together into a cohesive whole involved the use of multiple software solutions with common interfaces.
Status of JUNO Simulation Software
Authors: Deng Ziyan
Published: November 2020

The JUNO (Jiangmen Underground Neutrino Observatory) experiment is a multi-purpose neutrino experiment designed to determine the neutrino mass hierarchy and precisely measure oscillation parameters. It will be composed of a 20k ton liquid scintillator (LS) central detector equipped with about 18000 20-inch photon-multipliers (PMTs) and 25000 3-inch PMTs, a water Cherenkov detector with about 2000 20-inch PMTs, and a top tracker. Monte-Carlo simulation is a fundamental tool for optimizing the detector design, tuning reconstruction algorithms, and performing physics study. The status of JUNO simulation software will be presented, including generator interface, detector geometry, physics processes, MC truth, pull-mode electronic simulation.
Evolution of the ROOT Tree I/O
Authors: Blomer Jakob , Canal Philippe , Naumann Axel , Piparo Danilo
Published: November 2020

The ROOT TTree data format encodes hundreds of petabytes of High Energy and Nuclear Physics events. Its columnar layout drives rapid analyses, as only those parts (“branches”) that are really used in a given analysis need to be read from storage. Its unique feature is the seamless C++ integration, which allows users to directly store their event classes without explicitly defining data schemas. In this contribution, we present the status and plans of the future ROOT 7 event I/O. Along with the ROOT 7 interface modernization, we aim for robust, where possible compile-time safe C++ interfaces to read and write event data. On the performance side, we show first benchmarks using ROOT’s new experimental I/O subsystem that combines the best of TTrees with recent advances in columnar data formats. A core ingredient is a strong separation of the high-level logical data layout (C++ classes) from the low-level physical data layout (storage backed nested vectors of simple types). We show how the new, optimized physical data layout speeds up serialization and deserialization and facilitates parallel, vectorized and bulk operations. This lets ROOT I/O run optimally on the upcoming ultra-fast NVRAM storage devices, as well as file-less storage systems such as object stores.
Efficient Iterative Calibration on the Grid using iLCDirac
Authors: Viazlo Oleksandr , Sailer André
Published: November 2020

Software tools for detector optimization studies for future experiments need to be efficient and reliable. One important ingredient of the detector design optimization concerns the calorimeter system. Every change of the calorimeter configuration requires a new set of overall calibration parameters which in turn requires a new calorimeter calibration to be done. An efficient way to perform calorimeter calibration is therefore essential in any detector optimization tool set. In this contribution, we present the implementation of a calibration system in iLCDirac, which is an extension of the DIRAC grid interware. Our approach provides more direct control over the grid resources to reduce overhead of file download and job initialisation, and provides more flexibility during the calibration process. The service controls the whole chain of a calibration procedure, collects results from finished iterations and redistributes new input parameters among worker nodes. A dedicated agent monitors the health of running jobs and resubmits them if needed. Each calibration has an up-to-date backup which can be used for recovery in case of any disruption in the operation of the service. As a use case, we will present a study of optimization of the calorimetry system of the CLD detector concept for FCC-ee, which has been adopted from the CLICdet detector model. The detector has been simulated with the DD4hep package and calorimetry performance has been studied with the particle flow package PandoraPFA.
Lightweight site federation for CMS support
Authors: Acosta-Silva C. , Delgado Peris A. , Flix J. , Guerrero J. M. , Hernández J. M. , Pérez-Calero Yzquierdo A. , Rodriguez Calonge F. J. , Gómez-Pulgar J.
Published: November 2020

There is a general trend in WLCG towards the federation of resources, aiming for increased simplicity, efficiency, flexibility, and availability. Although general VO-agnostic federation of resources between two independent and autonomous resource centres may prove arduous, a considerable amount of flexibility in resource sharing can be achieved in the context of a single WLCG VO, with a relatively simple approach. We have demonstrated this for PIC and CIEMAT, the Spanish Tier-1 and Tier-2 sites for CMS, by making use of the existing CMS xrootd federation infrastructure and profiting from the common CE/batch technology used by the two centres. This work describes how compute slots are shared between the two sites, so that the capacity of one site can be dynamically increased with idle execution slots from the remote site, and how data can be efficiently accessed irrespective of its location. Our contribution includes measurements for diverse CMS workflows comparing performances between local and remote execution, and can also be regarded as a benchmark to explore future potential scenarios, where storage resources would be concentrated in a reduced number of sites.
Automated and Distributed Monte Carlo Generation for GlueX
Authors: Britton Thomas
Published: November 2020

MCwrapper is a set of systems that manages the entire Monte Carlo production workflow for GlueX and provides standards for how that Monte Carlo is produced. MCwrapper was designed to be able to utilize a variety of batch systems in a way that is relatively transparent to the user, thus enabling users to quickly and easily produce valid simulated data at home institutions worldwide. Additionally, MCwrapper supports an autonomous system that takes user’s project submissions via a custom web application. The system then atomizes the project into individual jobs, matches these jobs to resources, and monitors the jobs status. The entire system is managed by a database which tracks almost all facets of the systems from user submissions to the individual jobs themselves. Users can interact with their submitted projects online via a dashboard or, in the case of testing failure, can modify their project requests from a link contained in an automated email. Beginning in 2018 the GlueX Collaboration began to utilize the Open Science Grid (OSG) to handle a bulk of simulation tasks; these tasks are currently being performed on the OSG automatically via MCwrapper. This talk will outline the entire system of MCwrapper, its use cases, and the unique challenges facing the system.
Using Graph Databases
Authors: Hřivnáč Julius
Published: November 2020

Data in High Energy Physics (HEP) usually consist of complext complex data structures stored in relational databases and files with internal schema. Such architecture exhibits many shortcomings, which could be fixed by migrating into Graph Database storage.

The paper describes basic principles of the Graph Database together with an overview of existing standards and implementations. The usefulness and usability are demonstrated using the concrete example of the Event Index of the ATLAS experiment at LHC in two approaches as the full storage (all data are in the Graph Database) and meta-storage (a layer of schema-less graph-like data implemented on top of more traditional storage). The usability, the interfaces with the surrounding framework and the performance of those solutions are discussed. The possible more general usefulness for generic experiments’ storage is also discussed.
OSiRIS: A Distributed Storage and Networking Project Update
Authors: McKee Shawn , Meekhof Benjeman , Kissel Ezra , Keen Andrew , Merz Kenneth M. , Thompson Micheal
Published: November 2020

We report on the status of the OSiRIS project (NSF Award #1541335, UM, IU, MSU and WSU) after its fourth year. OSiRIS is delivering a distributed Ceph storage infrastructure coupled together with software-defined networking to support multiple science domains across Michigan’s three largest research universities as well as the Van Andel Institute. The project’s goal is to provide a single scalable, distributed storage infrastructure that allows researchers at each campus to work collaboratively with other researchers across campus or across institutions. The NSF CC*DNI DIBBs program which funded OSiRIS is seeking solutions to the challenges of multi-institutional collaborations involving large amounts of data and we are exploring the creative use of Ceph and networking to address those challenges. We will present details on the current status of the project and its various science domain users and use-cases. In the presentation we will cover the various design choices, configuration and the tuning and operational challenges we have encountered in providing a multiinstitutional Ceph deployment interconnected by a monitored, programmable network fabric. We will conclude with our plans for the final year of the project and its longer term outlook.
CDFS: A high-efficiency Data Access System for Storage Federations
Authors: Fu Shiyuan , Xu Qi , Cheng Yaodong , Chen Gang
Published: November 2020

High energy physics (HEP) experiments, such as LHAASO, produce a large amount of data, which is usually stored and processed on distributed sites. Nowadays, the distributed data management system faces some challenges such as global file namespace, efficient data access and storage. Focusing on those problems, this paper proposed a cross-domain data access file system (CDFS), applying data deduplication and compression as the storage-optimized engine, aiming at dynamically building an aggregate view of multiple distributed storages and accessing data in a fast and efficient way. The test based on the raw data of LHAASO experiment showed that the CDFS could present a unique repository based on distributed sites in LHAASO. And the storage-optimized engine reduces the storage consumption of the raw data by more than 50%.
Mapping Datasets to Object Storage System
Authors: Chu Xiaowei Aaron , LeFevre Jeff , Montana Aldrin , Robinson Dana , Koziol Quincey , Alvaro Peter , Maltzahn Carlos
Published: November 2020

Access libraries such as ROOT[1] and HDF5[2] allow users to interact with datasets using high level abstractions, like coordinate systems and associated slicing operations. Unfortunately, the implementations of access libraries are based on outdated assumptions about storage systems interfaces and are generally unable to fully benefit from modern fast storage devices. For example, access libraries often implement buffering and data layout that assume that large, single-threaded sequential access patterns are causing less overall latency than small parallel random access: while this is true for spinning media, it is not true for flash media. The situation is getting worse with rapidly evolving storage devices such as non-volatile memory and ever larger datasets. This project explores distributed dataset mapping infrastructures that can integrate and scale out existing access libraries using Ceph’s extensible object model, avoiding re-implementation or even modifications of these access libraries as much as possible. These programmable storage extensions coupled with our distributed dataset mapping techniques enable: 1) access library operations to be offloaded to storage system servers, 2) the independent evolution of access libraries and storage systems and 3) fully leveraging of the existing load balancing, elasticity, and failure management of distributed storage systems like Ceph. They also create more opportunities to conduct storage server-local optimizations specific to storage servers. For example, storage servers might include local key/value stores combined with chunk stores that require different optimizations than a local file system. As storage servers evolve to support new storage devices like non-volatile memory, these server-local optimizations can be implemented while minimizing disruptions to applications. We will report progress on the means by which distributed dataset mapping can be abstracted over particular access libraries, including access libraries for ROOT data, and how we address some of the challenges revolving around data partitioning and composability of access operations.
Chopin Management System: improving Windows infrastructure monitoring and management
Authors: Pacuszka Marta , Bukowiec Sebastian , Puentes Esteban , Metral Guillaume
Published: November 2020

CERN Windows server infrastructure consists of about 650 servers. The management and maintenance is often a challenging task as the data to be monitored is disparate and has to be collected from various sources. Currently, alarms are collected from the Microsoft System Center Operation Manager (SCOM) and many administrative actions are triggered through e-mails sent by various systems or scripts.

The objective of the Chopin Management System project is to maximize automation and facilitate the management of the infrastructure. The current status of the infrastructure, including essential health checks, is centralized and presented through a dashboard. The system collects information necessary for managing the infrastructure in the real-time, such as hardware configuration or Windows updates, and reacts to any change or failure instantly. As part of the system design, big data streaming technologies are employed in order to assure the scalability and fault-tolerance of the service, should the number of servers drastically grow. Server events are aggregated and processed in real-time through the use of these technologies, ensuring quick response to possible failures. This paper presents details of the architecture and design decisions taken in order to achieve a modern, maintainable and extensible system for Windows Server Infrastructure management at CERN.
LArSoft and Future Framework Directions at Fermilab
Authors: Knoepfel Kyle
Published: November 2020

The diversity of the scientific goals across HEP experiments necessitates unique bodies of software tailored for achieving particular physics results. The challenge, however, is to identify the software that must be unique, and the code that is unnecessarily duplicated, which results in wasted effort and inhibits code maintainability.

Fermilab has a history of supporting and developing software projects that are shared among HEP experiments. Fermilab’s scientific computing division currently expends effort in maintaining and developing the LArSoft toolkit, used by liquid argon TPC experiments, as well as the event-processing framework technologies used by LArSoft, CMS, DUNE, and the majority of Fermilab-hosted experiments. As computing needs for DUNE and the HL-LHC become clearer, the computing models are being rethought. Presented here are Fermilab’s plans for addressing the evolving software landscape as it relates to LArSoft and the data-processing frameworks, specifically as it relates to the DUNE experiment.
NANOAOD: a new compact event data format in CMS
Authors: Ehatäht Karl
Published: November 2020

The CMS Collaboration has recently commissioned a new compact data format, named NANOAOD, reducing the per-event storage space requirement to about 1-2 kB. This represents a factor 20 reduction in storage space compared to the MINIAOD data format used previously for physics analysis at CMS. We envisage that the information stored in the NANOAOD data format is sufficient to support the majority of CMS physics analyses. NANOAOD also facilitates the dissemination of analysis methods and the automation of standard workflows for deriving conditions and object calibrations. The latest developments of this project will be presented.
Minimal 4D Composite Higgs Models Under Current LHC Constraints
Authors: Carragher Ethan , Murnane Daniel , Stangl Peter , Su Wei , White Martin , Williams Anthony G.
Published: November 2020

We present preliminary results of the first convergent global fits of several minimal composite Higgs models. Our fits are performed using the differential evolution optimisation package Diver. A variety of physical constraints are taken into account, including a wide range of exclusion bounds on heavy resonance production from Run 2 of the LHC. As a by-product of the fits, we analyse the collider phenomenology of the lightest new up-type and downtype resonances in the viable regions of our models, finding some low-mass resonances that can be probed in future collider searches.
High-dimensional data visualisation with the grand tour
Authors: Laa Ursula
Published: November 2020

In physics we often encounter high-dimensional data, in the form of multivariate measurements or of models with multiple free parameters. The information encoded is increasingly explored using machine learning, but is not typically explored visually. The barrier tends to be visualising beyond 3D, but systematic approaches for this exist in the statistics literature. I use examples from particle and astrophysics to show how we can use the “grand tour” for such multidimensional visualisations, for example to explore grouping in high dimension and for visual identification of multivariate outliers. I then discuss the idea of projection pursuit, i.e. searching the high-dimensional space for “interesting” low dimensional projections, and illustrate how we can detect complex associations between multiple parameters.
Lepton identification in Belle II using observables from the electromagnetic calorimeter and precision trackers
Authors: Milesi Marco , Tan Justin , Urquijo Phillip
Published: November 2020

We present a major overhaul to lepton identification for the Belle II experiment, based on a novel multi-variate classification algorithm. Boosted decision trees are trained combining measurements from the electromagnetic calorimeter (ECL) and the tracking system. The chosen observables are sensitive to the different physics that governs interactions of hadrons, electrons and muons with the calorimeter crystals. Dedicated classifiers are used in various detector regions and lepton momentum ranges. The tree output is eventually combined with classifiers that rely upon independent measurements from other sub-detectors. Using simulation, the performance of the new algorithm is compared against the method used for analysis of the 2018 Belle II data, namely a likelihood discriminator based on the ratio of energy measured in the ECL over the momentum measured by the trackers. In the low momentum region, we largely improve the lepton-pion separation power, decreasing misidentification probability by a factor of 10 for electrons, and 2 for muons at fixed identification efficiency.
Physics Inspired Deep Neural Networks for Top Quark Reconstruction
Authors: Greif Kevin , Lannon Kevin
Published: November 2020

Deep neural networks (DNNs) have been applied to the fields of computer vision and natural language processing with great success in recent years. The success of these applications has hinged on the development of specialized DNN architectures that take advantage of specific characteristics of the problem to be solved, namely convolutional neural networks for computer vision and recurrent neural networks for natural language processing. This research explores whether a neural network architecture specific to the task of identifying t → Wb decays in particle collision data yields better performance than a generic, fully-connected DNN. Although applied here to resolved top quark decays, this approach is inspired by an DNN technique for tagging boosted top quarks, which consists of defining custom neural network layers known as the combination and Lorentz layers. These layers encode knowledge of relativistic kinematics applied to combinations of particles, and the output of these specialized layers can then be fed into a fully connected neural network to learn tasks such as classification. This research compares the performance of these physics inspired networks to that of a generic, fully-connected DNN, to see if there is any advantage in terms of classification performance, size of the network, or ease of training.
The computational challenge of lattice chiral symmetry - Is it worth the expense?
Authors: Virgili Adam , Kamleh Waseem , Leinweber Derek
Published: November 2020

The origin of the low-lying position of the Roper resonance in the nucleon energy spectrum has been the subject of significant interest for many years, including several investigations using lattice QCD. It has been claimed that chiral symmetry plays an important role in our understanding of this resonance. We present results from our systematic examination of the potential role of chiral symmetry in the low-lying nucleon spectrum through the direct comparison of the clover and overlap fermion actions. After a brief summary of the background motivation, we specify the computational details of the study and outline our comparison methodologies. We do not find any evidence supporting the claim that chiral symmetry plays a significant role in understanding the Roper resonance on the lattice.
Setup and commissioning of a high-throughput analysis cluster
Authors: Caspart René , Fischer Max , Giffels Manuel , von Cube Ralf Florian , Heidecker Christoph , Kuehn Eileen , Quast Günter , Heiss Andreas , Petzold Andreas
Published: November 2020

Current and future end-user analyses and workflows in High Energy Physics demand the processing of growing amounts of data. This plays a major role when looking at the demands in the context of the High-Luminosity-LHC. In order to keep the processing time and turn-around cycles as low as possible analysis clusters optimized with respect to these demands can be used. Since hyper converged servers offer a good combination of compute power and local storage, they form the ideal basis for these clusters. In this contribution we report on the setup and commissioning of a dedicated analysis cluster setup at Karlsruhe Institute of Technology. This cluster was designed for use cases demanding high data-throughput. Based on hyper converged servers this cluster offers 500 job slots and 1 PB of local storage. Combined with the 100 Gb network connection between the servers and a 200 Gb uplink to the Tier-1 storage, the cluster can sustain a data-throughput of 1 PB per day. In addition, the local storage provided by the hyper converged worker nodes can be used as cache space. This allows employing of caching approaches on the cluster, thereby enabling a more efficient usage of the disk space. In previous contributions this concept has been shown to lead to an expected speedup of 2 to 4 compared to conventional setups.
Readying CERN for connected device era
Authors: Sierra Rodrigo , Odziemczyk Hubert
Published: November 2020

Whether you consider “IoT” as a real thing or a buzzword, there’s no doubt that connected devices, data analysis and automation are transforming industry. CERN is no exception: a network of LoRa-based radiation monitors has recently been deployed and there is a growing interest in the advantages connected devices could bring—to accelerator operations just as much as to building management. Connected devices bring risks as well as advantages, however, and the last thing any business needs is an unsafe, uncoordinated and unmanaged sensor environment. To support the deployment of the LoRa-based radiation sensors, CERN has established both a Low Power Wireless Area Network (LPWAN) to complement the existing wired and wireless networks and a service infrastructure to manage the provisioning, orchestration, data transfer, security and operation for connected devices.
Dynamic integration of distributed, Cloud-based HPC and HTC resources using JSON Web Tokens and the INDIGO IAM Service
Authors: Spiga Danele , Dal Pra Stefano , Salomoni Davide , Ceccanti Andrea , Alfieri Roberto
Published: November 2020

In the past couple of years, we have been actively developing the Dynamic On-Demand Analysis Service (DODAS) as an enabling technology to deploy container-based clusters over hybrid, private or public, Cloud infrastructures with almost zero effort. DODAS is particularly suitable for harvesting opportunistic computing resources; this is why several scientific communities already integrated their computing use cases into DODAS-instantiated clusters, automating the instantiation, management and federation of HTCondor batch systems. The increasing demand, availability and utilization of HPC resources by and for multidisciplinary user communities, often mandates the possibility to transparently integrate, manage and mix HTC and HPC resources. In this paper, we discuss our experience extending and using DODAS to connect HPC and HTC resources in the context of a distributed Italian regional infrastructure involving multiple sites and communities. In this use case, DODAS automatically generates HTCondor batch system on-demand. Moreover it dynamically and transparently federates sites that may also include HPC resources managed by SLURM; DODAS allows user workloads to make opportunistic and automated use of both HPC and HTC resources, thus effectively maximizing and optimizing resource utilization. We also report on our experience of using and federating HTCondor batch systems exploiting the JSON Web Token capabilities introduced in recent HTCondor versions, replacing the traditional X509 certificates in the whole chain of workload authorization. In this respect we also report on how we integrated HTCondor using OAuth with the INDIGO IAM service.
The DODAS Experience on the EGI Federated Cloud
Authors: Spiga Daniele , Fernandez Enol , Spinoso Vincenzo , Ciangottini Diego , Tracolli Mirco , Donvito Giacinto , Antonacci Marica , Salomoni Davide , Ceccanti Andrea , Cristina Duma Doina , Gaido Luciano
Published: November 2020

The EGI Cloud Compute service offers a multi-cloud IaaS federation that brings together research clouds as a scalable computing platform for research accessible with OpenID Connect Federated Identity. The federation is not limited to single sign-on, it also introduces features to facilitate the portability of applications across providers: i) a common VM image catalogue VM image replication to ensure these images will be available at providers whenever needed; ii) a GraphQL information discovery API to understand the capacities and capabilities available at each provider; and iii) integration with orchestration tools (such as Infrastructure Manager) to abstract the federation and facilitate using heterogeneous providers. EGI also monitors the correct function of every provider and collects usage information across all the infrastructure. DODAS (Dynamic On Demand Analysis Service) is an open-source Platform-as-a-Service tool, which allows to deploy software applications over heterogeneous and hybrid clouds. DODAS is one of the so-called Thematic Services of the EOSC-hub project and it instantiates on-demand container-based clusters offering a high level of abstraction to users, allowing to exploit distributed cloud infrastructures with a very limited knowledge of the underlying technologies.This work presents a comprehensive overview of DODAS integration with EGI Cloud Federation, reporting the experience of the integration with CMS Experiment submission infrastructure system.