bluuebunny/crossref_metadata_2025 huggingface dataset:
Physics Performance of the ATLAS GNN4ITk Track Reconstruction Chain
Authors: Caillou Sylvain , Calafiura Paolo , Ju Xiangyang , Murnane Daniel , Pham Tuan , Rougier Charline , Stark Jan , Vallier Alexis
Published: May 2024

Particle tracking is vital for the ATLAS physics programs. To cope with the increased number of particles in the High Luminosity LHC, ATLAS is building a new all-silicon Inner Tracker (ITk), consisting of a Pixel and a Strip subdetector. At the same time, ATLAS is developing new track reconstruction algorithms that can operate in the HL-LHC dense environment. A track reconstruction algorithm needs to solve two problems: track finding for building track candidates and track fitting for obtaining track parameters of those track candidates. Previously, we developed GNN4ITk, a track-finding algorithm based on a Graph Neural Network (GNN), and achieved good track-finding performance under realistic HL-LHC conditions. Our GNN pipeline relied only on the 3D spacepoint positions. This work introduces heterogeneous GNN models to fully exploit the subdetector-dependent features of ITk data, improving the performance of our GNN4ITk pipeline. In addition, we interfaced our pipeline to the standard ATLAS track-fitting algorithm and data model. With that, the GNN4ITk pipeline produces full-fledged track candidates that can be used for any downstream analyses and compared with the other track reconstruction algorithms.
RenderCore – a new WebGPU-based rendering engine for ROOT-EVE
Authors: Bohak Ciril , Kovalskyi Dmytro , Linev Sergey , Mrak Tadel Alja , Strban Sebastien , Tadel Matevž , Yagil Avi
Published: May 2024

ROOT-Eve (REve), the new generation of the ROOT event-display module, uses a web server-client model to guarantee exact data translation from the experiments’ data analysis frameworks to users’ browsers. Data is then displayed in various views, including high-precision 2D and 3D graphics views, currently driven by THREE.js rendering engine based on WebGL technology. RenderCore, a computer graphics research-oriented rendering engine, has been integrated into REve to optimize rendering performance and enable the use of state-of-the-art techniques for object highlighting and object selection. It also allowed for the implementation of optimized instanced rendering through the usage of custom shaders and rendering pipeline modifications. To further the impact of this investment and ensure the long-term viability of REve, RenderCore is being refactored on top of WebGPU, the next-generation GPU interface for browsers that supports compute shaders, storage textures and introduces significant improvements in GPU utilization. This has led to optimization of in-terchange data formats, decreased server-client traffic, and improved offloading of data visualization algorithms to the GPU. FireworksWeb, a physics analysis-oriented event display of the CMS experiment, is used to demonstrate the results, focusing on high-granularity calorimeters and targeting high data-volume events of heavy-ion collisions and High-Luminosity LHC. The next steps and directions are also discussed.
Towards a distributed heterogeneous task scheduler for the ATLAS offline software framework
Authors: Calafiura Paolo , Esseiva Julien , Ju Xiangyang , Leggett Charles , Stanislaus Beojan , Tsulaia Vakho
Published: May 2024

With the increased data volumes expected to be delivered by the HLLHC, it becomes critical for the ATLAS experiment to maximize the utilization of available computing resources ranging from conventional GRID clusters to supercomputers and cloud computing platforms. To run its data processing applications on these resources, the ATLAS software framework must be capable of efficiently executing data processing tasks in heterogeneous distributed computing environments. Today, using the Gaudi Avalanche Scheduler, whose implementation is based on Intel TBB, we can efficiently schedule Athena algorithms to multiple threads within a single compute node. We aim to develop a new framework scheduler capable of supporting distributed heterogeneous environments, based on technologies like HPX or Ray. After the initial evaluation phase of these technologies, we began the development of a prototype distributed task scheduler for the Athena framework. This contribution describes this prototype scheduler and the preliminary results of performance studies within ATLAS data processing applications.
DIRAC current, upcoming and planned capabilities and technologies
Authors: Stagni Federico , Boyer Alexandre , Tsaregorodtsev Andrei , Lytovchenko Andrii , Sailer André , Haen Christophe , Burr Christopher , Bauer Daniela , Fayer Simon , Martyniak Janusz , Serfon Cédric
Published: May 2024

DIRAC is the interware for building and operating large scale distributed computing systems. It is adopted by multiple collaborations from various scientific domains for implementing their computing models. DIRAC provides a framework and a rich set of ready-to-use services for Workload, Data and Production Management tasks of small, medium and large scientific communities having different computing requirements. The base functionality can be easily extended by custom components supporting community specific workflows. DIRAC is at the same time an aging project, and a new DiracX project is taking shape for replacing DIRAC in the long term. This contribution will highlight DIRAC’s current, upcoming and planned capabilities and technologies, and how the transition to DiracX will take place. Examples include, but are not limited to, adoption of security tokens and interactions with Identity Provider services, integration of Clouds and High Performance Computers, interface with Rucio, improved monitoring and deployment procedures.
The Second-Factor Authentication System at CERN
Authors: Ahmad Adeel , Aguado Corman Asier , Short Hannah , Valsan Liviu , Fava Maria , Tedesco Paolo , Lopienski Sebastian , Lueders Stefan , Brillault Vincent
Published: May 2024

In 2022, CERN ran its annual simulated phishing campaign in which 2000 users gave away their passwords. In a real phishing incident, this would have meant 2000 compromised accounts, unless they were protected by Two-Factor Authentication (2FA). In the same year, CERN introduced 2FA for accounts with access to critical services. The new login flow requires users to always authenticate with a 2FA token, either with Time-based one-time password (TOTP) or WebAuthn. This introduces a significant security improvement for the individual and for the laboratory. The previous flow enforced 2FA to access a small number of applications. In this paper, we will discuss the rationale behind the 2FA deployment, as well as the technical setup of 2FA in the CERN Single Sign-On system, Keycloak. The paper will give a detailed overview of the architecture for this new 2FA flow and compare how it differs from the legacy 2FA system which was in place since 2019. We share statistics on how users are responding to this change in the login flow, and the actions we have taken to improve the user experience. Finally, we briefly describe our custom extensions to Keycloak for specific use cases, which include adding roles in the user token, overriding the default Keycloak session, and modifying the user login flow.
JIRIAF: JLAB Integrated Research Infrastructure Across Facilities
Authors: Vardan Gyurjyan , Christopher Larrieu , Graham Heyes , David Lawrence
Published: May 2024

The JIRIAF project aims to combine geographically diverse computing facilities into an integrated science infrastructure. This project starts by dynamically evaluating temporarily unallocated or idled compute resources from multiple providers. These resources are integrated to handle additional workloads without affecting local running jobs. This paper describes our approach to launch best-effort batch tasks that exploit these underutilized resources. Our system measures the real-time behavior of jobs running on a machine and learns to distinguish typical performance from outliers. Unsupervised ML techniques are used to analyze hardware-level performance measures, followed by a real-time crosscorrelation analysis to determine which applications cause performance degradation. We then facilitate bad behavior by throttling these processes. We demonstrate that problematic performance interference can be detected and acted on, which makes it possible to continue to share resources between applications and simultaneously maintain high utilization levels in a computing cluster. For a case study, we relocated the CLAS12 data processing workflow to a remote data processing facility, preventing file migration and temporal data persistency.
The CMS monitoring applications for LHC Run 3
Authors: Jashal Brij Kishor , Kuznetsov Valentin , Legger Federica , Uzunoglu Ceyhun
Published: May 2024

Data taking at the Large Hadron Collider (LHC) at CERN restarted in 2022. The CMS experiment relies on a distributed computing infrastructure based on WLCG (Worldwide LHC Computing Grid) to support the LHC Run 3 physics program. The CMS computing infrastructure is highly heterogeneous and relies on a set of centrally provided services, such as distributed workload management and data management, and computing resources hosted at almost 150 sites worldwide. Smooth data taking and processing requires all computing subsystems to be fully operational, and available computing and storage resources need to be continuously monitored. During the long shutdown between LHC Run 2 and Run 3, the CMS monitoring infrastructure has undergone major changes to increase the coverage of monitored applications and services, while becoming more sustainable and easier to operate and maintain. The used technologies are based on open-source solutions, either provided by the CERN IT department through the MONIT infrastructure, or managed by the CMS monitoring team. Monitoring applications for distributed workload management, submission infrastructure based on HTCondor, distributed data management, facilities have been ported from mostly custom-built applications to use common data flow and visualization services. Data are mostly stored in non-SQL databases and storage technologies such as ElasticSearch, VictoriaMetrics, Prometheus, InfluxDB and HDFS, and accessed either via programmatic APIs, Apache Spark or Sqoop jobs, or visualized preferentially using Grafana. Most CMS monitoring applications are deployed on Kubernetes clusters to minimize maintenance operations. In this contribution we present the full stack of CMS monitoring services and show how we leveraged the use of common technologies to cover a variety of monitoring applications and cope with the computing challenges of LHC Run 3.
The Ligo-Virgo-KAGRA Computing Infrastructure for Gravitational-wave Research
Authors: Bagnasco Stefano
Published: May 2024

The LIGO, VIRGO and KAGRA Gravitational-wave (GW) observatories are getting ready for their fourth observational period, O4, scheduled to begin in March 2023, with improved sensitivities and thus higher event rates. GW-related computing has both large commonalities with HEP computing, particularly in the domain of offline data processing and analysis, and important differences, for example in the fact that the amount of raw data doesn’t grow much with the instrument sensitivity, or the need to timely generate and distribute “event candidate alerts” to EM and neutrino observatories, thus making gravitational multi-messenger astronomy possible. Data from the interferometers are exchanged between collaborations both for low-latency and offline processing; in recent years, the three collaborations designed and built a common distributed computing infrastructure to prepare for a growing computing demand, and to reduce the maintenance burden of legacy custom-made tools, by increasingly adopting tools and architectures originally developed in the context of HEP computing. So, for example, HTCondor is used for workflow management, Rucio for many data management needs, CVMFS for code and data distribution, and more. We will present GW computing use cases and report about the architecture of the computing infrastructure as will be used during O4, as well as some planned upgrades for the subsequent observing run O5.
An Intelligent Data Analysis System for Biological Macromolecule Crystallography
Authors: Sun Hao-Kai , Hu Yu , Geng Zhi , Gao Zengqiang , Zhang Xin , Ding Wei
Published: May 2024

In this work, we design and implement a user-friendly, AIempowered, auto-pipelining data analysis system for biological macromolecule crystallography. It consists of four modules, (1) data reduction that generates reference reﬂection ﬁles from X-ray diﬀraction images, (2) structure prediction via database-querying or AlphaFold/OpenFold real-time prediction, (3) molecular replacement and (4) module building and reﬁnement. This data analysis system, currently at Work-In-Progress stage, is based on and developed for High Energy Photon Source initially, aiming at automatic, intelligent, and higheﬃciency software and will be open-source for academic research.
Polyglot Jet Finding
Authors: Stewart Graeme Andrew , Gras Philippe , Hegner Benedikt , Krasnopolski Atell
Published: May 2024

The evaluation of new computing languages for a large community, like HEP, involves comparison of many aspects of the languages’ behaviour, ecosystem and interactions with other languages. In this paper we compare a number of languages using a common, yet non-trivial, HEP algorithm: the anti-
kT clustering algorithm used for jet finding. We compare specifically the algorithm implemented in Python (pure Python and accelerated with numpy and numba), and Julia, with respect to the reference implementation in C++, from Fastjet. As well as the speed of the implementation we describe the ergonomics of the language for the coder, as well as the efforts required to achieve the best performance, which can directly impact on code readability and sustainability.
Data Management Package for the novel data delivery system, ServiceX, and Applications to various physics analysis workflows
Authors: Choi KyungEon , Onyisi Peter
Published: May 2024

Recent developments of HEP software allow novel approaches to physics analysis workflows. The novel data delivery system, ServiceX, can be very effective when accessing a fraction of large datasets at remote grid sites. ServiceX can deliver user-selected columns with filtering and run at scale. We introduce the ServiceX data management package, ServiceX DataBinder, for easy manipulations of ServiceX delivery requests and delivered data using a single configuration file. We show various practical use cases within analysis pipelines that range from a data delivery of a few columns for machine learning study to a data delivery for full-scale physics analysis.
First implementation and results of the Analysis Grand Challenge with a fully Pythonic RDataFrame
Authors: Padulano Vincenzo Eduardo , Guiraud Enrico , Falko Andrii , Gazzarrini Elena , Garcia Garcia Enrique , Gosein Domenic
Published: May 2024

The growing amount of data generated by the LHC requires a shift in how HEP analysis tasks are approached. Efforts to address this computational challenge have led to the rise of a middle-man software layer, a mixture of simple, effective APIs and fast execution engines underneath. Having common, open and reproducible analysis benchmarks proves beneficial in the development of these modern tools. One such benchmark is provided by the Analysis Grand Challenge (AGC), which represents a specification for realistic analysis pipelines. This contribution presents the first AGC implementation that leverages ROOT RDataFrame, a powerful, modern and scalable execution engine for the HENP use cases. The different steps of the benchmarks are written with a composable, flexible and fully Pythonic API. RDataFrame can then transparently run the computations on all the cores of a machine or on multiple nodes thanks to automatic dataset splitting and transparent workload distribution. The portability of this implementation is shown by running on various resources, from managed facilities to open cloud platforms for research, showing usage of interactive and distributed environments.
Integration of the Barcelona Supercomputing Center for CMS computing: Towards large scale production
Authors: Acosta-Silva C. , Delgado Peris A. , Flix Molina J. , Hernández J.M. , Pérez-Calero Yzquierdo A. , Pineda Sánchez E. , Villalonga Domínguez I.
Published: May 2024

The CMS experiment is working to integrate an increasing number of High Performance Computing (HPC) resources into its distributed computing infrastructure. The case of the Barcelona Supercomputing Center (BSC) is particularly challenging as severe network restrictions prevent the use of CMS standard computing solutions. The CIEMAT CMS group has performed significant work in order to overcome these constraints and make BSC resources available to CMS. The developments include adapting the workload management tools, replicating the CMS software repository to BSC storage, providing an alternative access to detector conditions data, and setting up a service to transfer produced output data to a nearby storage facility. In this work, we discuss the current status of this integration activity and present recent developments, such as a front-end service to improve slot usage efficiency and an enhanced transfer service that supports the staging of input data for workflows at BSC. Moreover, significant efforts have been devoted to improving the scalability of the deployed solution, automating its operation, and simplifying the matchmaking of CMS workflows that are suitable for execution at BSC.
Lifecycle Management, Business Continuity and Disaster Recovery Planning for the LHCb Experiment Control System Infrastructure
Authors: Cifra Pierfrancesco , Sborzacchi Francesco , Neufeld Niko , Cardoso Luis Granado
Published: May 2024

LHCb (Large Hadron Collider beauty) is one of the four large particle physics experiments aimed at studying differences between particles and anti-particles and very rare decays in the charm and beauty sector of the standard model at the LHC. The Experiment Control System (ECS) is in charge of the configuration, control, and monitoring of the various subdetectors as well as all areas of the online system, and it is built on top of hundreds of Linux virtual machines (VM) running on a Red Hat Enterprise Virtualisation cluster. For such a mission-critical project, it is essential to keep the system operational; it is not possible to run the LHCb’s Data Acquisition without the ECS, and a failure would likely mean the loss of valuable data. In the event of a disruptive fault, it is important to recover as quickly as possible in order to restore normal operations. In addition, the VM’s lifecycle management is a complex task that needs to be simplified, automated, and validated in all of its aspects, with a particular focus on deployment, provisioning, and monitoring. The paper describes the LHCb’s approach to this challenge, including the methods, solutions, technology, and architecture adopted. We also show limitations and problems encountered, and we present the results of tests performed.
Monitoring CERN Windows Infrastructure using Open Source products
Authors: Martín Zamora Pablo , Kalliafas Michalis
Published: May 2024

More than 500 servers are actively managed by the Windows infrastructure team on the CERN site. They run critical services for the laboratory, from controlling some of the accelerator systems to directory services, storage, and databases. Visibility of the state of these servers at all times is critical for smooth operation of their services. This paper describes the implementation of an open-source ecosystem based on icinga2, focused on how to monitor Windows-based services, and the technical choices and configurations that were made to transparently deploy and manage an opensource monitoring infrastructure in the organization.
Sustainability in HEP Computing
Authors: Walker Rodney
Published: May 2024

The European energy crisis during 2022 prompted many computing facilities to take urgent electricity saving measures. In part voluntary, in response to EU and national appeals, but also to keep within a flat energy budget, as the electricity price rose. We review some of these measures and, as the situation normalizes, take a longer view on how the flexibility of high throughput computing can best contribute to the net-zero energy transition. We discuss carbon intensity estimation of workloads, automatically powering down nodes during low-demand periods, CPU frequency modulation to track variable electricity tariffs or renewable generation throughout the day and potential spin-down disk storage solutions.
AI4EIC Hackathon: PID with the ePIC dRICH
Authors: Fanelli Cristiano , Giroux James , McSpadden Diana , Rajput Kishansingh , Suresh Karthik , Cisbani Evaristo , Deconinck Wouter , Walter Eric , Bressan Andrea , Diefenthaler Markus , Horn Tanja , Wenaus Torre
Published: May 2024

The inaugural AI4EIC Hackathon unfolded as a high-point satellite event during the second AI4EIC Workshop at William & Mary. The workshop itself boasted over two hundred participants in a hybrid format and delved into the myriad applications of Artificial Intelligence and Machine Learning (AI/ML) for the Electron-Ion Collider (EIC). This workshop aimed to catalyze advancements in AI/ML with applications ranging from advancements in accelerator and detector technologies—highlighted by the ongoing work on the ePIC detector and potential development of a second detector for the EIC—to data analytics, reconstruction, and particle identification, as well as the synergies between theoretical and experimental research. Complementing the technical agenda was an enriched educational outreach program that featured tutorials from leading AI/ML experts representing academia, national laboratories, and industry. The hackathon, held on the final day, showcased international participation with ten teams from around the globe. Each team, comprising up to four members, focused on the dual-radiator Ring Imaging Cherenkov (dRICH) detector, an integral part of the particle identification (PID) system in ePIC. The data for the hackathon were generated using the ePIC software suite. While the hackathon presented questions of increasing complexity, its challenges were designed with deliberate simplifications to serve as a preliminary step toward the integration of machine learning and deep learning techniques in PID with the dRICH detector. This article encapsulates the key findings and insights gained from this unique experience.
Involving the new generations in Fermilab endeavors
Authors: Mambelli Marco , Donati Simone , Bellettini Giorgio , Barzi Emanuela
Published: May 2024

Since 1984 the Italian groups of the Istituto Nazionale di Fisica Nucleare (INFN) and Italian Universities, collaborating with the DOE laboratory of Fermilab (US) have been running a two-month summer training program for Italian university students. While in the first year the program involved only four physics students of the University of Pisa, in the following years it was extended to engineering students. This extension was very successful and the engineering students have been since then extremely well accepted by the Fermilab Technical, Accelerator, and Scientific Computing Division groups. Over the many years of its existence, this program has proven to be the most effective way to engage new students in Fermilab endeavors. Many students have extended their collaboration with Fermilab with their Master’s Thesis and PhD. Since 2004 the program has been supported in part by DOE in the frame of an exchange agreement with INFN. Over its almost 40 years of history, the program has grown in scope and size and has involved more than 550 Italian students from more than 20 Italian Universities, Several Institutes of Research, including ASI and INAF in Italy, and the ISSNAF Foundation in the US, have provided additional financial support. Since the program does not exclude appropriately selected non-Italian students, a handful of students from European and non-European Universities were also accepted over the years. Each intern is supervised by a Fermilab Mentor responsible for performing the training program. Training programs spanned from Tevatron, CMS, Muon (g-2), Mu2e, and Short Baseline Neutrino Experiments and DUNE design and experimental data analysis, development of particle detectors (silicon trackers, calorimeters, drift chambers, neutrino and dark matter detectors), design of electronic and accelerator components, development of infrastructures and software for exascale data handling, research on superconductive elements and on accelerating cavities, and theory of particle accelerators. Since 2010, within an extended program supported by the Italian Space Agency and the Italian National Institute of Astrophysics, a total of 30 students in physics, astrophysics, and engineering have been hosted for two months in the summer at US space science Research Institutes and laboratories. In 2015 the University of Pisa included these programs within its educational programs. Accordingly, Summer School students are enrolled at the University of Pisa for the duration of the internship and are identified and ensured as such. At the end of the internship, the students are required to write summary reports on their achievements. After positive evaluation by a University Examining Board, interns are acknowledged credits for their Diploma Supplement. The program was canceled in 2020 and 2021 due to the pandemic but restarted successfully in 2022. We believe this program can be taken as a model and easily adopted by interested institutions.
Support for experiments at INFN-T1
Authors: Pellegrino Carmelo , Cesini Daniele , Fornari Federico , Lattanzio Daniele , Morganti Lucia , Pascolini Alessandro , Rendina Andrea
Published: May 2024

The Italian WLCG Tier-1 located in Bologna and managed by INFN-CNAF has a long tradition in supporting several research communities in the fields of High-Energy Physics, Astroparticle Physics, Gravitational Waves, Nuclear Physics and others, to which provides computing resources in the form of batch computing, both HPC, HTC and Cloud, and storage. Although the LHC experiments at CERN represent the main users of the Tier-1 resources, an increasing number of communities and experiments are also being supported in all of their computing activities. Due to this demanding user base, an efficient support system is needed in order to assure a smooth and appropriate exploitation of the computing infrastructure. In this framework, such a role is played by the Tier-1 User Support group, which acts as the entry point for services, support requests, and problem reports. The group makes use of multiple systems to meet the different needs and specificities of the supported experiments. Moreover, the group continuously maintains detailed knowledge base in the form of an on-line user guide and develops tools to advertise specific information about the services available to the communities in a form that is easy to access and use. The communication channels are represented by ticketing systems and also by mailing lists used for a more direct communication, allowing to promptly notify maintenance interventions, downtimes and more in general all the new features and services provided by the center. In this paper, the ticketing systems, tools, platforms and services that User Support offers, and the internal organization of the department will be described. Future workflow plans in view of the DATACLOUD project, which will require an increasing effort, will also be presented.
Controlling Quality for a Physics-Driven Generative Models and Auxiliary Regression Approach
Authors: Rogachev Alexander , Ratnikov Fedor
Published: May 2024

High energy physics experiments heavily rely on the results of MC simulation of data used to extract physics results. However, the detailed simulation often requires tremendous amount of computation resources.

Using Generative Adversarial Networks and other deep learning generative techniques can drastically speed up the computationally heavy simulations like a simulation of the calorimeter response. To be useful, such models are required to satisfy quality metrics which are driven by a specific physics properties of generated objects rather than by a regular ML image-like quality metrics.

The auxiliary regression extension to the GAN-based fast simulation demonstrated improvements of the physics quality for generated objects. This approach introduces physics metrics to a Discriminator path of the model thus allows direct discriminating of objects with poorly reproduced properties.

In this paper we discuss the auxiliary regression GAN approach to physicsbased fast simulation and concentrate on requirements to the quality of the auxiliary regressor to provide a necessary precision of the generative models built on top of this regressor.
The Neutron-Gamma Pulse Shape Discrimination of CLLB Detector
Authors: Song Ruiqiang , Peng Shuo , Tong Yufeng , Wu Qi , Qian Sen , Wang Zhigang , Han Jifeng
Published: May 2024

Cs2LiLaBr6: Ce (CLLB) scintillator with the size of Φ 21mm × 25 mm coupled with PMT was used to detect neutron and gamma rays. The pulse shape discrimination (PSD) of neutrons and gamma rays by charge comparison method, the neutrons and gamma rays from AmBe source and fast neutron beam can be separated with figure-of-merit (FOM) values of 0.9 and 1.3, respectively. However, some neutron and gamma rays are difficult to distinguish, so new algorithms need to be investigated to improve the PSD performance of neutron and gamma. Artificial neural networks (ANN) have a very good image recognition capability, thus the ANN model was constructed to discriminate the waveforms of neutron and gamma rays. After ANN model training, the neutron and gamma signals of the CLLB detector were recognized with an accuracy of 98%, and the FOM value of the ANN method was calculated to be 19.4. This result is much higher than the charge comparison method, indicating better discrimination between neutrons and gamma rays with the ANN method.
Suppressing Beam Background and Fake Photons at Belle II using Machine Learning
Authors: Cheema Priyanka
Published: May 2024

The Belle II experiment situated at the SuperKEKB energyasymmetric e+
e− collider began operation in 2019. It has since recorded half of the data collected by its predecessor, and reached a world record instantaneous luminosity of 4.7 × 1034 cm-2s-1. For distinguishing decays with missing energy from background events at Belle II, the residual calorimeter energy measured by the electromagnetic calorimeter is an important quantity. Ideally, calorimeter clusters due to beam backgrounds and fake photons should be excluded when the residual calorimeter energy is calculated, so identifying them during the analysis process is key. We present two new boosted decision tree classifiers that have been trained to identify such clusters at Belle II and distinguish them from real photons originating from collision events at the interaction point. We provide results from their application to the B → D*ℓν decay mode, and show that the distribution of residual calorimeter energy for signal events is significantly improved.
What Machine Learning Can Do for Focusing Aerogel Detectors
Authors: Shipilov Foma , Barnyakov Alexander , Bobrovnikov Vladimir , Kononov Sergey , Ratnikov Fedor
Published: May 2024

Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARICH). The specifics of detector location make proper cooling difficult, therefore a significant number of ambient background hits are captured. They must be mitigated to reduce the data flow and improve particle velocity resolution. In this work we present several approaches to filtering signal hits, inspired by machine learning techniques from computer vision.
IceCube experience using XRootD-based Origins with GPU workflows in PNRP
Authors: Schultz David , Sfiligoi Igor , Riedel Benedikt , Andrijauskas Fabio , Weitzel Derek , Würthwein Frank
Published: May 2024

The IceCube Neutrino Observatory is a cubic kilometer neutrino telescope located at the geographic South Pole. Understanding detector systematic effects is a continuous process. This requires the Monte Carlo simulation to be updated periodically to quantify potential changes and improvements in science results with more detailed modeling of the systematic effects. IceCube’s largest systematic effect comes from the optical properties of the ice the detector is embedded in. Over the last few years there have been considerable improvements in the understanding of the ice, which require a significant processing campaign to update the simulation. IceCube normally stores the results in a central storage system at the University of Wisconsin–Madison, but it ran out of disk space in 2022. The Prototype National Research Platform (PNRP) project thus offered to provide both GPU compute and storage capacity to IceCube in support of this activity. The storage access was provided via XRootD-based OSDF Origins, a first for IceCube computing. We report on the overall experience using PNRP resources, with both successes and pain points.
Towards High-Performance AI4NP Applications on Modern GPU Platforms
Authors: Mei Xinxin , Brei Nathan , Lawrence David
Published: May 2024

The evolution of modern heterogeneous accelerators, such as GPUs, has significantly advanced the landscape of artificial intelligence (AI). There is a notable surge to adopt AI within the nuclear physics domain (AI4NP). While most AI4NP studies focus on feasibility analysis, our attention is directed towards evaluating their performance on contemporary GPUs that integrate tensor cores. We first benchmark the throughput of hyperparameterized multi-layer perceptron (MLP) models. We then examine the performance of an AI4NP application: Hydra. We assess the performance gain and accuracy loss caused by the tensor cores for low-precision floating-point operations. Our experiments encompass the PyTorch and TensorFlow Keras frameworks on NVIDIA’s T4 and A100 GPUs. We explore the behavior of different GPU hardware platforms and AI software tools. This study can be a valuable resource for guiding the performance optimization of larger-scale deployments of AI4NP applications.
Precise Quantum Angle Generator Designed for Noisy Quantum Devices
Authors: Rehm Florian , Vallecorsa Sofia , Borras Kerstin , Krücker Dirk , Grossi Michele , Varo Valle
Published: May 2024

The Quantum Angle Generator (QAG) is a cutting-edge quantum machine learning model designed to generate precise images on current Noise Intermediate Scale Quantum devices. It utilizes variational quantum circuits and incorporates the MERA-upsampling architecture, achieving exceptional accuracy. The study demonstrates the QAG model’s ability to learn hardware noise behavior, with stable results in the presence of simulated quantum hardware noise up to 1.5% during inference and 3% during training. However, deploying the noiseless trained model on real quantum hardware reduces accuracy. Training the model directly on hardware allows it to learn the underlying noise behavior, maintaining precision comparable to the noisy simulator. The QAG model’s noise robustness and accuracy make it suitable for analyzing simulated calorimeter shower images used in high-energy physics simulations at CERN’s Large Hadron Collider.
A method of fluorescence molecular tomographic reconstruction via the second-order sensitivity matrix
Authors: Zou Wei , Wang Jiajun
Published: May 2024

Fluorescence molecular tomographic (FMT) reconstruction is commonly solved based on the Jacobian matrix, which is a first-order sensitivity matrix. Basically, using the second-order derivatives for iterative reconstruction can help improve the performance of convergence. In this paper, a reconstruction method of FMT based on the reduction of the second-order sensitivity matrix is proposed. In addition, the strategy of detectors rotation is combined into the inverse reconstruction to further improve the reconstruction quality. The reconstructed results demonstrate that the proposed method accelerates the reconstruction with high precision of inverse solutions.
Experimental investigations and numerical simulations of lattice structures obtained by additive manufacturing
Authors: Remadi Amina , Chatti Sami , Belaid Dhekra
Published: May 2024

In this study, both experimental and numerical investigations are carried out on samples fabricated by additive manufacturing (AM). The determination of stress distribution in parts obtained by AM, even for simple tensile test, is complicated because it is largely influenced by many manufacturing parameters as the adopted infill pattern, the infill orientation and the infill density. Firstly, the material parameters of the fused filament PLA and tensile specimens made by the AM with an infill grid pattern with density of 100% are experimentally determined. Then, the effect of the infill orientation with an infill density of 40% on the tensile stress state is experimentally and numerically investigated. By synthesizing these results, a comprehensive understanding of stress distribution in AM-produced components is achieved. The obtained anisotropic mechanical parameters are used to simulate compression of a flat-ring part.
Cysts of the jaws and how to make their diagnoses under a microscope: a need for a better communication between clinicians and pathologists
Authors: Strokov Svyat , Cardot-Leccia Nathalie , Raybaud Hélène , Latrèche Sarah , Guillou Estelle , Khenissa Nouha , Ponchet Yves , Voha Christine
Published: May 2024

Introduction: Cysts of the jaws constitute an heterogenous group of lesions occurring in the maxillofacial region. Their diagnosis is challenging and necessitating a meticulous correlation of clinical, radiological, and pathological features. Pathologists often face numerous difficulties stemming from inadequate clinical and radiological information, along with limited samples. Nevertheless, clinicians are not always aware of the pathologist's concerns, making difficult to know exactly which pertinent clinical information they should deliver in their request form. The objective of this article is to illustrate the microscopic diagnostic pitfalls associated with cystic lesions of the jaws and enhance communication between oral surgeons and oral pathologist. Corpus: This section starts by examining the essential clinical and radiological data necessary for a precise pathological diagnosis. Subsequently, we discuss about the differential diagnosis of jaw cystic lesions, categorizing them into five distinct subsets based on their microscopic features, particularly their histological lining. For each subset, we engage in a detailed discussion concerning the primary diagnostic challenges and their implications for treatment decisions. Conclusion: Pathologist and clinicians are not irreconcilables: improved communication, rooted in a mutual understanding of each other's concerns, leads to optimizing the diagnosis and subsequently the treatment of jaw cysts.
Sialolipoma: a rare case of a hamartoma in the floor of the mouth
Authors: Zayed Ali Sh. , Falih Mohammed Oday , Qas Marrogy Hanan Amanuel
Published: May 2024

Sialolipomas are rare benign mature mesenchymal lipomatous proliferations that present in a wide age range. These tumors are involved in both major and minor salivary glands, and most of them are almost only seen in adults when the minor salivary glands are involved. In this article, it underlines the occurrence of a rare case of sialolipoma that manifests as a swelling in the floor of the mouth of a 53 year old female patient and interferes with speech, mastication, and tongue movement.
Slip ratio control based on adaptive fuzzy sliding mode for vehicle with an electromechanical brake system
Authors: Zhang Houzhong , Zhang Chengyin , Xu Lin , Jia Zicong
Published: May 2024

The development of vehicle intelligence has driven the evolution of brake-by-wire systems, with electromechanical braking (EMB) emerging as a crucial development in intelligent vehicle braking. To enhance the braking safety of EMB-equipped vehicles, this paper proposes a slip ratio control method based on adaptive fuzzy sliding mode control (AFSMC) to more effectively achieve wheel slip ratio tracking during braking. The approach involves establishing the mathematical model of the planetary gear-type EMB system and the vehicle’s longitudinal dynamics model. Additionally, a hierarchical collaborative control strategy is introduced, where the bottom layer employs the EMB clamping force control algorithm based on cascaded proportional-integral (PI), and the top layer integrates AFSMC to regulate the slip ratio. The simulation results, validated using the joint simulation platform of Simulink and Carsim under various conditions, illustrate that the AFSMC, compared to the conventional sliding mode controller (SMC), attains more precise control of wheel slip ratio while mitigating the chattering phenomenon. These findings suggest the potential of AFSMC for practical engineering applications.
Adjunctive bevacizumab therapy in an equine corneal stromal invasive
squamous cell carcinoma with a 53-months follow-up
Authors: Blohm Klaas-Ole , Nell Barbara
Published: May 2024

A 17-year-old Appaloosa mare was referred for evaluation of presumed refractory
keratitis of the left eye. Gross examination revealed ocular discomfort and
corneal neovascularization with a nasal focal opacification affecting
approximately 40% of the corneal surface. On ophthalmic examination, extensive
subepithelial to mid-stromal vascular branching accompanied by a homogeneous
white, dense opacification, which affected up to 80% of the total corneal
thickness, were apparent. Signs of concurrent uveitis were absent. Deep-stromal
lamellar keratectomy with a conjunctival pedicle graft was performed under
general anesthesia. Histopathology confirmed a poorly differentiated corneal
stromal invasive squamous cell carcinoma (SI-SCC) with neoplastic cell extension
to the surgical margins. Postoperatively, 4 topical mitomycin C 0.04%
chemotherapy cycles combined with oral firocoxib therapy were initiated. Seven
months after surgery, regrowth of the SI-SCC was clinically suspected. A total
volume of 1 ml bevacizumab 2.5% was administered in the standing sedated horse
via 3 mid-stromal corneal injections. Four weeks later, intrastromal bevacizumab
injections (ISBIs) were repeated, however, this time the solution was injected
directly into the main corneal vessel branches.

Seven weeks after the second ISBIs, the left eye was comfortable and significant
remission of corneal vascularization and opacity was recognized. No recurrence
has been noted for a follow-up period of more than 53 months.

Equine SI-SCC usually has a very poor prognosis for globe maintenance. To the
authors’ knowledge this is the first report of well-tolerated intrastromal
antivascular endothelial growth factor adjunctive therapy with bevazicumab 2.5%
and SI-SCC resolution after a multimodal treatment approach.
Individueller Konzentrationsverlauf von Progesteron und Östradiol-17β
im Blut bei Stuten während des Zyklus
Authors: Laufkötter Sara , Längerer Lina , Wehrend Axel
Published: May 2024

Gegenstand und Ziel Die Studie stellt den individuellen Verlauf der
Konzentrationen von Östradiol-17ß und Progesteron im Blut von Stuten über einen
Zyklus dar, um auf physiologische individuelle Unterschiede zwischen einzelnen
Tieren hinzuweisen und Interpretationshilfen von Hormonwerten zu geben.

Material und Methoden An 7 Stuten wurde über den Zyklusverlauf die
Konzentrationen an Progesteron und Östradiol-17ß bestimmt. Eine Stute wurde
aufgrund eines vom physiologischen Zyklus abweichenden Verlaufs aus der
Beurteilung ausgeschlossen. Zusätzlich wurden die Ovarien täglich sonografisch
untersucht, um die Hormonwerte morphologischen Veränderungen auf den Ovarien
zuordnen zu können.

Ergebnisse Teilweise zeigen Stuten erhebliche individuelle Unterschiede in
ihren Hormonverläufen, die sich auch von den veröffentlichten Vergleichswerten
in der Literatur unterscheiden. So zeigten 2 Stuten zum Zeitpunkt der Ovulation
einen Progesteronwert oberhalb des Basalniveaus. Die postovulatorischen
Progesteronverläufe der Stuten zeigen deutliche Schwankungen, was die Angabe von
Referenzwerten in den verschiedenen Abschnitten der Gelbkörperphase erschwert.
Die Länge der Plateauphasen beträgt im Durchschnitt 12,3±1,5 Tage. Die Stute mit
der Doppelovulation zeigte die höchsten Progesteronkonzentrationen.

Schussfolgerung Die Messung von Plasmaprogesteronwerten bei Stuten sollten
nur im Zusammenhang mit weiteren Untersuchungsergebnissen interpretiert werden.
Die sehr starken Schwankungen der Östradiol-17ß-Konzentrationen machen es
fraglich, ob die Bestimmung dieses Hormonwertes einen diagnostischen Nutzen
hat.

Klinische Relevanz Bei der Interpretation von Steroidhormonwerten im
ingraviden Zyklus einer Stute sind die individuellen Verläufe zu beachten, die
teilweise deutlich von den veröffentlichten Referenzwerten abweichen.
Diagnose und Therapie eines persistierenden Ductus arteriosus: Eine
retrospektive Evaluation bei 17 Katzen
Authors: Masche Anja , Breit Peter , Höpfner Robert , Schmerbach Kay
Published: May 2024

Gegenstand und Ziel Ziel der Studie war die Darstellung des Signalements,
der klinischen Merkmale und echokardiographischen Ergebnisse von Katzen, die
wegen eines persistierenden Ductus arteriosus (PDA) behandelt wurden sowie der
kurz- bis mittelfristigen Ergebnisse nach erfolgreicher Ligatur des PDA.

Material und Methoden Die Studie ist eine retrospektive Untersuchung von
17 Katzen mit einem PDA über einen Zeitraum von 10 Jahren. Die Diagnosestellung
PDA erfolgte mittels transthorakaler Echokardiografie. Es wurden 13 Katzen
chirurgisch mittels Thorakotomie und Ligatur des PDA versorgt.

Ergebnisse Bei allen Katzen wurde ein Herzgeräusch festgestellt, welches
sich größtenteils mit einer Lautstärke von Grad 4 bis 6 zeigte (15/17 Katzen;
88,2%). Ein kontinuierliches Herzgeräusch trat häufiger auf (10/17 Katzen;
58,9%) als ein systolisches (7/17 Katzen; 41,1%). Echokardiografisch zeigten
sich bei der Mehrheit der Katzen der linksventrikuläre enddiastolische
Durchmesser (LVIDd) sowie der linksventrikuläre endsystolische Durchmesser
(LVIDs) deutlich über den Referenzwerten. Der Durchmesser des PDA (gemessen an
der breitesten Stelle des Gefäßes) lag im Mittel bei 3,4 mm±1,08 mm und die
mediane maximale Durchflussgeschwindigkeit bei 5,06 m/sek (2,6m/sek–6,4m/sek).
Bei allen chirurgisch versorgten Katzen wurde die Operation erfolgreich
abgeschlossen und alle Katzen wurden nach anschließender stationärer Therapie
entlassen. Bei einer Katze kam es perioperativ zu einer Blutung aus dem PDA, die
gestillt werden konnte. Diese Katze zeigte postoperativ einen Restshunt, welcher
in einer Kontrollechokardiografie 3 Monate später nicht mehr dargestellt werden
konnte. Sechs Katzen konnten über einen längeren Zeitraum verfolgt werden.

Schlussfolgerungen Mit einer postoperativen Überlebensrate von 100% liegt
in dieser Studie eine sehr gute chirurgische Prognose vor.

Klinische Relevanz Die chirurgische Behandlung des PDA ist bei Tieren ohne
fortgeschrittene Herzveränderungen kurativ. Erste Hinweise kann die Auskultation
eines Herzgeräusches geben. Zwar ist die erste klinische Diagnostik mit der
Auskultation einfach und sollte bei jeder Erstvorstellung bereits im jungen
Alter erfolgen, jedoch muss bedacht werden, dass nicht jede Katze mit PDA ein
kontinuierliches Herzgeräusch zeigen muss. Hierbei sollten vor allem die
klinischen Symptome berücksichtigt werden.