bluuebunny/crossref_metadata_2025 huggingface dataset:
176 Does High-Quality Learning Need High-Fidelity Simulation? Experience from Obstetric Theatres Preparing for the First Wave of COVID-19
Authors: Schnieke-Kind Christopher , Wise Arlene , Stevenson Karen , Alexander Nicki , Theodosiou Kate
Published: January 2022

In early 2020, medical teams globally faced the challenge of preparing for an unprecedented clinical situation. As well as the predicated scale and severity of the COVID-19 pandemic clinical teams were generally inexperienced in dealing with an infectious agent of this nature. Simulation, particularly high-fidelity, plays an important role in preparing for novel, high-stakes situations. However, at this time, all clinical departments were simultaneously occupied with such preparation. This placed unprecedented demand on resource-dependant, high-fidelity simulation. Here we share our use of multiple simulation modalities, ranging from low- to high-fidelity, to prepare our multi-disciplinary obstetric theatre team for the arrival of the COVID-19 pandemic.

The aim of the study was to prepare the local team to manage COVID obstetric patients within the theatre environment, particularly in the context of obstetric emergencies. This preparation must take the form of both institutional learning (the creation of a standardized protocol specifically adapted for obstetric theatres) and individual learning (familiarity by individual team members with guidelines and their roles within them).

Multiple modalities of simulation were utilized (

This programme of multiple interlinked simulation modalities allowed the creation of a coherent, comprehensive and practical protocol for the management of COVID patients in obstetric theatres in advance of encountering such patients in reality. This protocol was found to be satisfactory to a group of local subject matter experts prior to the arrival of the pandemic. As management of COVID obstetric patients became more familiar, this protocol was reviewed. It was found that no significant alterations were required, indicating that, despite utilizing only a single, high-fidelity simulation session, the original programme of development had pre-empted many of the practical issues that would otherwise only have been discovered later through real-world practice. Individual learning is more challenging to define, but feedback suggested both a greater familiarity with guidelines by individual learners and was able to identify targets for more specific training (e.g. donning/doffing, definitions of aerosol-generating procedures).

High-fidelity is often viewed as the highest form of simulation for effective learning. However, its undertaking has a high resource cost. Our experience demonstrated that low-fidelity, less resource-demanding modalities provide significant benefits to both individual and institutional learning.
32 Using a Simulation Environment to Assess the Usability of a Novel Medical Device During the Covid-19 Pandemic
Authors: Sa-Couto Carla , Nicolau Abel , de Sousa Carolina , Cruz Nuno
Published: January 2022

It was a recognized challenge of lack of ventilators needed to face COVID-19 worldwide. Although ventilators are sparse, self-inflating manual resuscitators are widely available in-hospital services, providing a rapid response to respiratory depression. Based on this, a device (PNEUMA)

This work describes the use of a simulation environment to test the usability of a novel device to automate self-inflating manual resuscitators.

The usability study was divided into two parts: (1) participants followed a protocol with instructions for assembling and using the system in a non-clinical context (

Usability testing. Left panel – assembly of the system (part I); right panel – use of the system in an immersive clinical simulation environment (part II).

A convenience sample (two MDs and six RNs) from an intensive care unit of a tertiary Portuguese hospital participated in the test. Usability testing showed that the system was easy and timely assembled, with low complexity of use (e.g. not requiring external help). The clinical scenario tested the transition between spontaneous and mechanical ventilation, and ventilatory parameters’ control, using PNEUMA. All participants reported that the controllable parameters (I:E, RR, Vol, PIP, Plat, and PEEP) were relevant and easy to change. Participants suggested the inclusion of patient parameters such as the tidal volume and lung compliance. Participants also suggested improvements, such as the inclusion of pressure alarms and a more user-friendly interface. All participants reported that they would be willing to use the device for emergency use.

The reported study resulted in recommendations and ameliorations of the device, before its use in real settings, in the context of the COVID-19 pandemic. The use of simulation environments for device/systems’ testing provides a timely and standardized approach, enabling a safer clinical practice.
75 No Time To Train? The Use of Simulation to Develop a Pathway and Deliver Training for Emergency Surgery in Maternity During the COVID-19 Pandemic
Authors: Shiels Sally , Choi Desiree , Baxter Linden , Higham Helen
Published: January 2022

The COVID-19 pandemic presented healthcare workers with a challenge to provide safe clinical care while protecting staff and coping with an evolving situation. The use of simulation to devise and test emergency pathways is well recognized in the literature

Recognizing the need to develop a safe pathway, with a limited evidence base, we sought to test the hypothesis that a combination of table-top and

This programme involved three phases: pathway development, safety testing and team training. The initial phase was a simulated table-top scenario of a parturient requiring a Category 1 Caesarean delivery under general anaesthetic. This pathway was then used to create a structured simulation scenario to test its suitability. The debrief sessions for each explored three themes: (1) pathway feasibility; (2) timing and (3) feedback.

The table-top simulation took place on 11 March. Team-specific outcomes highlighted the logistics of early senior escalation and the rationalization of staff and equipment in theatre. We also recognized deficits in the amount and correct use of personal protective equipment (PPE). Staffing levels and limitations in communication were also key findings. The subsequent

The initial phases of the COVID-19 pandemic provided a fertile ground for team consolidation and planning that promoted collaboration in one of the most multi-professional areas of any hospital: the maternity unit. Involvement of all teams meant that deficits in training could be identified early, and changes could be adapted rapidly. The simulations also demonstrated to staff that it was possible to safely deliver a baby within the timeframe. Recognizing that this was not an isolated problem, we shared our resources publicly helping teams in the USA, Laos, Australia and UK to develop their own protocols. Importantly, it improved our response to the second wave.
60 Talking Under Cover: A Virtual Workshop to Improve Communication in PPE
Authors: John Sini
Published: January 2022

Since 15 June 2020, all hospital staff were mandated by the government to wear a facemask in hospital and it looks like they will remain a permanent feature in healthcare for the foreseeable future. There is a significant body of research about the plethora of adverse effects that wearing masks can have on verbal communication

The aim of the study was to develop an interactive virtual workshop aims to improve the verbal communication of healthcare staff whilst wearing Personal Protective Equipment (PPE).

We delivered 14 workshops from March 2021 to May 2021 to 80 participants. First, we discussed the barriers that healthcare workers are up against when they are working in Personal Protective Equipment (PPE) and then speak about vocal anatomy and how speech is created. The workshop then focusses on how to make speech clearer whilst also advising healthcare staff on how to look after their voice. To ensure the workshop is interactive, there are a number of exercises that the participants perform and videos of COVID cardiac arrest simulations are used to discuss the potential speech and communication errors in PPE which could affect patient safety in an emergency. Finally, we also incorporated a patient’s perspective in designing this course. They offered very helpful suggestions regarding verbal and non-verbal communication when communicating with patients in PPE, which are often overlooked by healthcare professionals but immensely valuable to improve patients’ and staff experience.

We invited hospital departments to book on to the virtual training and collected electronic feedback from participants. As a result of this feedback, we hope to be able to provide face-to-face training in the future and incorporate simulation in the workshops so that participants can practice what they have learnt with higher fidelity and we are better able to understand how the added burden of cognitive bandwidth will influence people’s communication.
95 Striving to Thrive: Developing an Innovative Region-Wide Medical Registrar Preparation Simulation-Based Course
Authors: Wheeler Joseph , Kainth Harj , Adjetey Andrea , Morse Richard , Bains Amarpal , Ali Izhar , Hamilton Stuart , Mann Karishma
Published: January 2022

The COVID-19 pandemic has led to disruption and missed educational opportunities for Internal Medicine (IM) Year 2 trainees who shall progress to the second stage of their training in August 2021, stepping up to the medical registrar role. It had become apparent that some of these trainees may not be currently performing at the level expected for this stage of their training and may encounter some difficulties during this transition period.

We were tasked by Health Education England (West Midlands) to design and implement an innovative region-wide medical registrar preparation course, utilizing simulation-based education. The courses required standardized content that could be delivered by either face-to-face or virtual modalities across multiple centres in the region.

Two separate high-fidelity simulation courses were designed to deliver key aspects of the IM training curriculum with a clear focus on the behaviours, attitudes and skills required to perform as a junior medical registrar: ‘Thrive’. A 1-day course designed for trainees who are expected to be able to progress to IM year 3 without any concern. These courses were planned to be run by other regional centres to their local trainees using either a face-to-face or virtual format. ‘Strive’. A 2-day course designed for those trainees who have been identified as needing extra support to be able to progress to IM year 3. These courses were planned to be run via a face-to-face format at our SimWard to trainees from across the region. Course content included a mix of high-fidelity simulation scenarios as well as workshops focussing on key areas for medical registrar preparation as identified by IM trainees:

Leading cardiac arrests

Debriefing

Breaking bad news

Prioritization and delegation

Giving advice

Escalating care

All content was designed and produced in house to then be provided electronically to region-wide centres facilitating standardized delivery, including pre-recorded simulation scenarios to allow virtual delivery. A webinar was held to aid roll out and provide training on course delivery and content to participating centres. Courses were delivered during the spring and summer of 2021. Initial feedback has shown an increase in perceived trainee confidence in dealing with all topic areas at the registrar level and has illustrated that learning has already been utilized in clinical practice. Courses are ongoing until the end of July 2021, after which a full analysis of region-wide impact can be made.
9 Enhanced Recovery After Surgery: Multi-Disciplinary Healthcare Simulation Training for Perioperative Teams
Authors: Khan Omar , Yanny Heba , Salim Mohmad
Published: January 2022

Enhanced recovery after surgery (ERAS) is an evidence-based approach in perioperative care allowing patients to recover more quickly after surgery. The ultimate aim of this programme is to optimize organ function pre-operatively and reduce the stress response from major surgery to aid in early recovery

We aimed to provide structured and interactive simulation (SIM) training for staff involved in the management of colorectal surgery patients on the ERAS programme. Staff included operating department practitioners (ODPs), surgical staff nurses and anaesthetics senior house officers (SHOs). This was based at a small district general hospital (DGH) in the West Midlands.

Staff were given hypothetical post-operative scenarios of commonly encountered surgical problems on the ward. These included hypotensive patients and the management of regional analgesic techniques such as epidurals. Sessions were commenced with a brief and targeted outline of relevant physiology, followed by a series of SIM moulages. A longer period of time was made available at the end of each SIM for debrief.

Staff were more confident after SIM sessions in managing the acutely ill ERAS surgical patient. The multi-disciplinary nature of the scenarios was highly commended. Feedback from staff was encouraging, in particular, about how ‘real’ the scenarios felt. There was also increased awareness about the rationale behind the principles of the ERAS programme and healthcare staff felt it would change their practice. Feedback was measured through a series of pre- and post-SIM questionnaires.

Through a series of SIM sessions and theatre shadowing, we aim to create an ERAS team and ERAS unit at the hospital. SIM will play a major role in addressing the learning objectives of junior medical staff, ODPs and nurses. The long-term goal is to safely manage these patients on a dedicated unit. We aim to create a safe environment where invasive monitoring can be used, and treatments such as vasopressors prescribed under the supervision of anaesthetists. This will ultimately improve patient care and help fulfil the core objectives of the ERAS approach.
171 Safe Patient Transfer: Getting Everyone in on the Acct
Authors: McCauley Peter , Burlacu Crina , Wall Nick , Murphy Anna Marie , Moran Peter , Kinirons Brian , Doherty Dermot , Knapman Karl , Menzie David
Published: January 2022

Optimal patient care frequently requires the safe inter-hospital transfer of critically ill patients for time-sensitive treatments, often outside of normal working hours. Safe transfer requires a multi-disciplinary approach including doctors (typically anaesthesiologists), nurses and paramedics. In a 2018 survey of anaesthesiology trainees in Ireland, 81% agreed that specific training in this area was ‘deficient’ or ‘absent’

Recognizing the lack of formal training, we identified the need for training in the transport of critically ill patients including familiarization with the ambulance environment and common critical transfer scenarios

The ACCT methodology consists of (1) comprehensive Video-Assisted Learning (VAL) material for pre-course completion; (2) on-site face-to-face simulation; (3) an ACCT Train the Trainer (ACCT-TTT) for trainers to subsequently deliver the programme.

The VAL material includes lectures (e.g. transport physiology), clinical skills demonstrations (e.g. transport and ambulance equipment) and simulation (e.g. safe packaging for transfer). There is an accompanying multiple-choice questionnaire (MCQ) to ensure full engagement and testing of core knowledge prior to the on-site component. On-site, small multispecialty delegate groups comprising of doctors, nurses and paramedics rotate through three simulations, allowing for enhanced experiential learning. Two take place in high-fidelity simulation laboratories, and one occurs in a fully operational ambulance. Delegates assume their real work roles and deal with common transport scenarios and adverse incidents. Debriefing focuses on reinforcing prescribed learning objectives. A post-course MCQ is used to validate learning, with feedback forms used for course evaluation. We plan to pilot the course and subsequently conduct ACCT-TTT courses. We aim to implement and expand ACCT nationwide, making it a mandatory component of anaesthesiology training.
COMPARATIVE ANALYSIS AND APPLICABILITY DETERMINATION FOR SEVERAL DLT SOLUTIONS
Authors: Bogdanov A. , Korkhov V. , Shchegoleva N. , Khvatov V. , Zaynalov N. , Kiyamov J. , Dik A. , Faradzhov A.
Published: January 2022

Potential benefits of implementation of distributed ledger technology are widely discussedamong different business actors and governmental structures. Within the last decade, with growingpopularity of blockchain-based payment systems and cryptocurrencies, these discussions considerablysharpened. Therefore, an extensive body of research has emerged on this soil. The goal of this study isto attempt to make a comparative analysis of several existing blockchain-based distributed ledgerplatforms. Besides that, authors overview the most commonly used consensus algorithms and designapproaches, as for any blockchain product, consensus algorithm is a crucial part which determines theperformance of the overall system. Choosing the right algorithm would ensure high reliability andthroughput, while the wrong choice could cause fatal malfunctions for the application. A suitablealgorithm usually should be chosen according to the task in consideration, e.g. Nakamoto-styleprotocols could be considered better for public networks, while multiround voting protocols are moresuitable for private and secure systems. The highest attention is paid to consensus algorithms based onthe solution of the Byzantine Fault Tolerance problem (BFT).
ON DEEP LEARNING FOR OPTION PRICING IN LOCAL VOLATILITY MODELS
Authors: Shorokhov S.
Published: January 2022

We study neural network approximation of the solution to boundary value problem for Black-ScholesMerton partial differential equation for a European call option price, when model volatility is afunction of underlying asset price and time (local volatility model). Strike-price and expiry day of theoption are assumed to be fixed. An approximation to option price in local volatility model is obtainedvia deep learning with deep Galerkin method (DGM), making use of the neural network of specialarchitecture and stochastic gradient descent on a sequence of random time and underlying price points.Architecture of the neural network and the algorithm of its training for option pricing in local volatilitymodels are described in detail. Computational experiment with DGM neural network is performed toevaluate the quality of neural network approximation for hyperbolic sine local volatility model withknown exact closed form option price. The quality of the neural network approximation is estimatedwith mean absolute error, mean squared error and coefficient of determination. The computationalexperiment demonstrates that DGM neural network approximation converges to a European calloption price of the local volatility model with acceptable accuracy.
TRANSFORMER-BASED MODEL FOR THE SEMANTIC PARSING OF ERROR MESSAGES IN DISTRIBUTED COMPUTING SYSTEMS IN HIGH ENERGY PHYSICS
Authors: Grin D. , Grigorieva M.
Published: January 2022

Large-scale computing centers supporting modern scientific experiments store and analyze vast amounts of data. A noticeable number of computing jobs executed within the complex distributed computing environments ends with errors of some kind, and the amount of error log data generated every day complicates manual analysis by human experts. Moreover, traditional methods such as specifying regular expression patterns to automatically group error messages become impractical in a heterogeneous computing environment without a well-defined structure of error messages. ClusterLogs framework for error message clustering was developed to address this challenge. Theframework can discover common patterns in error messages from various sources and group them together. One of the essential results of this process is the clear automated description of the resulting clusters, which will be used for the analysis. In this research, we propose that interpreting error messages as a natural language allows us to use transformer-based deep learning models such as BERT for this task. A model for extracting the relevant part of messages was trained and integrated into ClusterLogs to represent each cluster as a few actionable items, ensuring better interpretation and validation of the results of clustering.
THE ANALYSIS OF THE EDUCATIONAL MEASUREMENT RESULTS, AND ITS PROVIDING AS “SOFTWARE-AS-A- SERVICE” SOLUTION IN ELEARNING
Authors: Lavdina Y. , Gustun O. , Budaragin N. , Leonova N. , Modyaev A.
Published: January 2022

In modern eLearning systems, educational measurements are used both to evaluate the students’ achievements and to control the learning process. However, eLearning systems usually have comparatively trivial embedded features for analyzing measurement results, which are not of considerable interest for sufficient statistical research of the assessment tools quality. To identify the characteristics of assessment materials such as reliability, homogeneity, discriminatory power, validity, and others, researchers are forced to get dump from the database of eLearning system. And then they use third-party software to perform required data processing operations and calculations.This makes it difficult to analyze the measurement results during the measuring itself, for example, in adaptive testing. We propose the approach to organizing and performing measurement results analysis by using the software-as-a-service (SaaS) model for cloud computing. The SaaS user is provided with the set of necessary tools for conducting full-fledged statistical analysis in real time. They also get the access to customizable applications for implementing their own measurement procedures (including adaptive ones).
JIRA PLUGIN FOR THE ALICE INSTANCE
Authors: Kondratyev A. , Bondyakov A.
Published: January 2022

As a bug tracking and project management system, the ALICE experiment uses Jira Software, which provides a wide range of configuration options. Jira also allows one to significantly expand the basic functionality with custom plugins. In this work, the LinkedIssuesHasStatus plugin for the JIRA service of the ALICE experiment is developed and implemented. The plugin returns tickets that link issues in the specified status and that are linked with the specified linking type.
DATA KNOWLEDGE BASE CURRENT STATUS AND OPERATION
Authors: Kotliar V.
Published: January 2022

The Data Knowledge Base (DKB) project aims at knowledge acquisition and metadata integration. Itprovides fast response for a variety of complicated queries, such as summary reports and monitoringtasks (aggregation queries) and multi-system join queries. Such queries are not easy to implement in atimely manner and, obviously, are less efficient than a query to a single system with integrated andpre-processed information would be. This work describes the status of the project as well as itsintegration with the ATLAS Workflow Management and future perspectives.
Current status of the MICC: an overview
Authors: Baginyan A. , Balandin A. , Balashov N. , Dolbilov A. , Gavrish A. , Golunov A. , Gromova N. , Kashunin I. , Korenkov V. , Kutovskiy N. , Mitsyn V. , Pelevanyuk I. , Podgainy D. , Streltsova O. , Strizh T. , Trofimov V. , Vorontsov A. , Voytishin N. , Zuev M.
Published: January 2022

The Multifunctional Information and Computing Complex (MICC) of the Joint Institute for Nuclear Research (JINR) runs Tier-1, which supports the NICA experiments and the LHC CMS experiment, Tier-2, which supports all LHC experiments, as well as the NICA experiments and other HEP experiments with JINR’s participation, cloud computing for neutrino physics experiments (Baikal-GVD, JUNO, DANS, etc.), as well as for the JINR Member States’ clouds, the “Govorun” supercomputer for all JINR programs, as well as for the NICA experiments and research in the field of machine learning and quantum computing. This activity is aimed at ensuring the further development of the network, information and computing infrastructure of JINR for the research and production activities of the Institute and its Member States on the basis of state-of-the-art information technologies in accordance with the JINR Seven-Year Plan of development for 2017-2023. This paper describes the current state of the MICC.
USAGE OF TIME SERIES DATABASES IN THE GRAFANA PLATFORM FOR THE NETIS SERVICE
Authors: Alexandrov E. , Pozo Astigarraga M. , Avolio G.
Published: January 2022

NetIs is a service used to monitor the Data Acquisition network of the ATLAS experiment. The firstversion was developed at CERN in 2010. Over the years, the need to replace NetIs with an improvedservice emerged. Indeed, the effort to maintain NetIs has considerably increased together with the sizeand complexity of the network system; additionally, the Round Robin Database used to store the dataresults in a loss of granularity over time that makes the tool unsuitable for retrieving accurate valuesfrom the past. The graphs produced by NetIs are generated by the backend server and they are quitestatic, though the GUI is familiar to many users. The main idea was to exploit the recent advancementsin time series databases and visualization tools like Grafana in order to present data to the users in amore dynamic way. The Persistent Back-End for the ATLAS Information System, developed inATLAS for permanent storage of operational data, was already integrated with Grafana andsuccessfully collecting network monitoring statistics. Grafana, despite being a very popularvisualization web application, does not support some GUI elements that are used in NetIs such as atree or position of drop-down. Javascript code integrated with Grafana was used to overcome theselimitations.
MULTI-GPU TRAINING AND PARALLEL CPU COMPUTING FOR THE MACHINE LEARNING EXPERIMENTS USING ARIADNE LIBRARY
Authors: Goncharov P. , Nikolskaia A. , Ososkov G. , Rezvaya E. , Rusov D. , Shchavelev E.
Published: January 2022

Modern machine learning (ML) tasks and neural network (NN) architectures require huge amounts ofGPU computational facilities and demand high CPU parallelization for data preprocessing. At thesame time, the Ariadne library, which aims to solve complex high-energy physics tracking tasks withthe help of deep neural networks, lacks multi-GPU training and efficient parallel data preprocessing onthe CPU.In our work, we present our approach for the Multi-GPU training in the Ariadne library. We willpresent efficient data-caching, parallel CPU data preprocessing, generic ML experiment setup forprototyping, training, and inference deep neural network models. Results in terms of speed-up andperformance for the existing neural network approaches are presented with the help of GOVORUNcomputing resources.
VERIFIABLE APPLICATION-LEVEL CHECKPOINT AND RESTART FRAMEWORK FOR PARALLEL COMPUTING
Authors: Gankevich I. , Petriakov I. , Gavrikov A. , Tereshchenko D. , Mozhaiskii G.
Published: January 2022

Fault tolerance of parallel and distributed applications is one of the concerns that becomes topical for large computer clusters and large distributed systems. For a long time the common solution to this problem was checkpoint and restart mechanisms implemented on operating system level, however, they are inefficient for large systems and now application-level checkpoint and restart is considered as a more efficient alternative. In this paper we implement application-level checkpoint and restart manually for the well-known parallel computing benchmarks to evaluate this alternative approach. We measure the overheads introduced by creating and restarting from a checkpoint, and the amount of effort that is needed to implement and verify the correctness of the resulting programme. Based on the results we propose generic framework for application-level checkpointing that simplifies the process and allows to verify that the application gives correct output when restarted from any checkpoint.
OPTIMIZATION OF THE COMPUTATION OF MULTIDIMENSIONAL INTEGRALS FOR ESTIMATING THE MESON LIFETIME
Authors: Goderidze D. , Kalinovsky Yu. , Friesen A.
Published: January 2022

To calculate the lifetime of mesons in hot and dense nuclear matter, it is necessary to computemultidimensional integrals with a complicated integrand function. This work presents an algorithmand methods to calculate such integrals on the basis of the Monte-Carlo method. To optimize thecomputation, the parallel calculation algorithm is implemented in the C++ programming languageusing OpenMP and NVIDIA CUDA technologies. The calculations are performed on nodes withmulticore CPUs and Intel Xeon Phi coprocessors and the Nvidia Tesla K40 accelerator installed withina heterogeneous cluster of the Meshcheryakov Laboratory of Information Technologies, Joint Institutefor Nuclear Research, Dubna. The code is used to calculate the pion lifetime using all possible pionpion scattering modes.
THE DEEP DISTRIBUTED LEARNING IMPLEMENTATIONS WITH A LARGE DATASET ON THE DESKTOP GRID
Authors: Kurochkin I.
Published: January 2022

Machine learning methods and in particular deep neural networks are often used to solve the problemof image classification. There is a trend towards an increase in training data and an increase in the sizeof neural network architectures. The process of training a deep neural network with millions ofparameters can take thousands of hours on modern computing devices. Distributed computing systemscan be used to reduce training time. The wide scalability of grid systems and the ease of connectingnew computational nodes can significantly reduce the training time for deep neural networks. But atthe same time, you should take into account the peculiarities of data exchange between the nodes ofthe desktop grid system. Methods of organizing distributed deep learning are proposed using theexample of the image classification problem. The technique of random formation of a local dataset isproposed. The results of using synchronous and asynchronous approaches to distributed learning areshown
DESIGN AND DEVELOPMENT OF APPLICATION SOFTWARE FOR THE MPD DISTRIBUTED COMPUTING INFRASTRUCTURE
Authors: Moshkin A. , Pelevanyuk I. , Rogachevskiy O.
Published: January 2022

The Multi-Purpose Detector collaboration began using distributed computing for centralized MonteCarlo generation in mid-2019. The DIRAC Interware is used as a platform for the integration ofheterogeneous distributed computing resources. Since then, workflows of job submission, datatransfer, and storage have been designed, tested, and successfully applied. Moreover, the growth ofinterest in access to the computing system from users is observed. One way to provide such access forthe users is to allow them to directly submit jobs to DIRAC. However, direct access to the resourcesimposes a high responsibility on users and must be restricted. For this reason, another approach waschosen, i.e. to design and develop a dedicated application that collects requirements from users andstarts the required number of jobs. Such an approach entails additional effort: elaboration ofrequirements, application design and development. Nevertheless, it allows for greater control over theworkload submitted by other users, reducing possible failures and the inefficient usage of resources.
IMPROVEMENTS OF THE LOOT MODEL FOR PRIMARY VERTEX FINDING BASED ON THE ANALYSIS OF DEVELOPMENT RESULTS
Authors: Rezvaya E. , Goncharov P. , Nefedov Y. , Ososkov G. , Zhemchugov A.
Published: January 2022

The recognition of particle trajectories (tracks) from experimental measurements plays a key role in the reconstruction of events in experimental high-energy physics. Knowledge about the primary vertex of an event can significantly improve the quality of track reconstruction. To solve the problem of primary vertex finding in the BESIII inner tracking detector we applied the LOOT program which is a deep convolutional neural network that processes all event hits at once, like a three-dimensional image. We used mean absolute error to measure the quality of the trained model, but a thorough analysis of the results showed that this metric by itself is inadequate without considering output distributions of the vertex coordinates. Correcting all errors allowed us to propose special corrections to the loss function that gave quite acceptable results. The process of our problem investigation and itsoutcomes are presented.
ANALYSIS OF THE EFFECTIVENESS OF VARIOUS METHODS FOR PARALLELIZING DATA PROCESSING IMPLEMENTED IN THE ROOT PACKAGE
Authors: Solovjeva T.
Published: January 2022

The ROOT software package is currently being upgraded in several ways to improve data processingperformance. This paper will consider several tools implemented in this framework for calculations onmodern heterogeneous computing architectures. PROOF (Parallel ROOT Package Extension) dividescommon work into small chunks, i.e. packets. The size of the first packet used for calibration, theminimum and maximum set size of the packet, the degree of data structuring affect the speed of theirprocessing. When processing large amounts of data, the read and write speed can be crucial. The newasynchronous file merge feature in the TBufferMerger class allows writing data in parallel frommultiple streams to a single output file. Our calculations show a good scalability of the macroexecution time depending on the number of processor cores used.
DATA STORAGE SYSTEMS OF «HYBRILIT» HETEROGENEOUS COMPUTING PLATFORM FOR SCIENTFIC RESEARCH CARRIED OUT IN JINR: FILESYSTEMS AND RAIDS PERFORMANCE RESEARCH
Authors: Kokorev A. , Belyakov D. , Lyubimova M.
Published: January 2022

"HybriLIT" Heterogeneous platform is a part of the Multifunctional Information and ComputingComplex (MICC) of the Laboratory of Information Technologies named after MG Meshcheryakov ofJINR, Dubna. Heterogeneous platform consists of Govorun supercomputer and HybriLIT educationand testing polygon. Data storage and processing system is one of the platform components. It isimplemented using distributed and parallel filesystems (NFS, EOS, Lustre). Platform performancedepends on many factors, including performance of storage and file systems.The best storage performance for wide variety of user jobs may be obtains with optimal filesystemparameters. The number of tests of local filesystems (EXT family and XFS) was carried out. Therewere empirically obtained an optimal parameters o data storage system at which the performance havebeen high results.The new methodology was developed for analyzing the obtained measurements of IOPS (input-outputoperations per second) and Latency (milliseconds) for results evaluations.Various filesystems were analyzed by the developed methodology. The conclusion was drawn aboutof optimal parameters of the investigated filesystems.
MULTITHREADED EVENT SIMULATION IN THE BMNROOT PACKAGE
Authors: Stepanova M. , Driuk A. , Mertz S. , Gertsenberger K. , Nemnugin S.
Published: January 2022

The researches at the NICA accelerator complex (JINR, Joint Institute for Nuclear Research, Dubna) require efficient and fast software implementations of algorithms for modeling and reconstruction of the particle collision events. BmnRoot package developed for the BM@N experiment is based on the ROOT environment, Geant4 and the FairRoot object-oriented framework. BmnRoot includes tools for event simulation, reconstruction and data analysis modules. With the announcement of Geant4MT multithreading support in ROOT and FairRoot, the problem of modifying the BmnRoot code for multithreading simulation appeared. As a result, an event-driven parallelism model has been implemented for event simulation in BmnRoot. The stages of the performed work and the results of testing the implemented multithreaded version are presented.
NEURAL NETWORK APPROACH TO THE PROBLEM OF IMAGE SEGMENTATION FOR MORPHOLOGICAL STUDIES
Authors: Stadnik A. , Streltsova O. , Podgainy D. , Kolesnikоva I. , Butenko Yu. , Nechaevskiy A. , Anikina A. , Gudiev T. , Streltsov A.
Published: January 2022

The report presents the results on the development of the algorithmic block of the Information System(IS) for radiobiological studies, created within a joint project of MLIT and LRB JINR, in terms ofsolving the segmentation problem for morphological research to study the effect of ionizing radiationon biological objects. The problem of automating the morphological analysis of histologicalpreparations is solved in the frames of the project by implementing algorithms based on a neuralnetwork approach and computer vision methods. The results of the investigations will be used in thedevelopment of the algorithmic block of the BIOHLIT information system.
RECONSTRUCTION OF ORDINARY DIFFERENTIAL EQUATIONS FROM IRREGULARLY DISTRIBUTED TIME- SERIES DATA
Authors: Golovkina A. , Kozynchenko V. , Kulabukhova N.
Published: January 2022

The present paper aims to develop a reconstruction method for the right side of a system of ODEs inpolynomial form from sparse and irregularly distributed time-series data. This method doesn’t requireany additional knowledge about the system and has several steps. The scarcity of the data through thetrajectory length is compensated by the artificially generated points using approximatingtrigonometrical polynomials. Then, we get uniformly spread data points with the step conditioned bythe desired accuracy of derivatives approximation in ODEs. This let to further use conventionalreconstruction algorithms described in the literature. We test the proposed method on time series datagenerated from known ODE models in a two-dimensional system. We quantify the accuracy of thereconstruction for the system of ODEs as a function of the amount of data used by the method.Further, we solve the reconstructed system of ODEs and compare the solution to the original timeseries data. The method developed and validated here can now be applied to large data sets forphysical and biological systems for which there is no known system of ODEs.
MIKROPROPAGACIJA I SOMATSKA EMBRIOGENEZA BAGREMA (ROBINIA PSEUDOACACIA L.)
Authors: Pustahija Fatima , Međedović Safer , Čaušević Adisa
Published: January 2022

Početni eksplanti, meristemi pazušnih i apikalnih pupoljaka, Robinia pseudoacacia L. izrezani su iz petogodišnjih stabala i uzgajani na bazalnoj MS podlozi koja sadrži 0,5 mg/1 BA, 20 mg/1 adenin sulfata i 0,02 mg/1 NAA. Umnožavanje nodalnih segmenata testirano je na istoj podlozi i koncentraciji regulatora rasta. Za rizogenezu 0,5 mg/1 IBA je dodato u MS bazalnu podlogu. Korenov sistem je 100% regenerisan. Aklimatizacija kompletnih biljaka bila je efikasna. Somatska embriogeneza skakavca dobivena je iz neembriogenih eksplantata. Suspenzija ćelija kalusa je kultivisana na tečnom MS bazalnom mediju koji sadrži 8 mg/1 2,4D i 0,5 mg/1 BA u prvoj fazi eksperimenta, a zatim na tečnom MS bazalnom mediju koji sadrži 0,3 mg/1 2,4D i 1 mg/1 BA. Embriogene strukture diferencirane u ovoj fazi su prebačene na MS podlogu bez hormona.
RASPROSTRANJENOST HIPOVIRULENTNIH SOJEVA CRYPHONECTRIA PARASITICA (Murr.) Barr, UZROČNIKA RAKA PITOMOG KESTENA, U BOSNI I HERCEGOVINI
Authors: Treštić Tarik , Usčuplić Midhat
Published: January 2022

Pitomi kesten (Castanea sativa Miller) u Bosni i Hercegovini raste samo kao šumska vrsta drveća kojima se upravlja kao izdanačkim šumama. Plod kestena je ovdje sekundarni proizvod i nema odabranih stabala za plodonošenje. Najveća nalazišta kestena su na sjeverozapadu (Cazin), istoku (Bratunac-Srebrenica) i jugu (Konjic-Jablanica), ali ima mnogo malih-raštrkane sastojina ove vrste po cijeloj zemlji. Međutim, areal kestena se smanjuje zbog raka i na pojedinim mjestima kesten se zamjenjuje drugom vrstom drveća. Mnoge sastojine kestena su degradirane i zbog nedostatka šumskouzgojnog tretmana. Cryphonectria parasitica (Murr.) Barr je prvi put pronađen u sjeverozapadnom arealu kestena 1961. godine, uz granicu sa Hrvatskom, pa je očigledno uvezena iz ove zemlje, ali je danas prisutna svuda. Prva pojava hipovirulentnih tipova karcinoma je bila uočena 1980. godine i od tada se težina bolesti usporava na sjeverozapadu u odnosu na južne regije gdje je hipovirulencija široko rasprostranjena i postepeno raste.
UTICAJ HERBIVORA NA REGENERACIJU ŠUMA
Authors: Kunovac Saša
Published: January 2022

Biljojedi i biljni resursi čine sistem u kojem na brzinu regeneracije biljaka utiče gustina životinjskih populacija koje ih jedu. Sa druge strane, biljke dostupne kao izvor hrane određuju brzinu rasta životinjskih populacija. U „normalnim“ ekosistemima gustina biljojeda je određena brojem predatora, a u tom slučaju stanju šumei ostale biljne vrste imaju dovoljno "prostora" za regeneraciju. U suprotnom, u uslovima bez predatora, uticaji biljojeda na regeneraciju šuma mogu biti veoma značajni. Ovaj rad se bavi metodama procjene šteta uzrokovane velikim biljojedima u procesima regeneracije šuma.
NOVA KOMBINACIJA U LEPEZOLISNOG ILI KRIVOCASICNOG GLOGA, Crataegus rhipidophylla Gand. (Rosaceae)
Authors: Janjić Nikola
Published: January 2022

S obzirom na opis i originalni materijal Karla Malog, ukazano je na neophodnost prenošenja varijeteta romiigeri iz Crataegus monogyna Jacq. u C. rhipidophylla Gand., tj. da se napravi nova kombinacija: C. rhipidophylla Gand. var. ronnigeri (K. Maly) Janjić.
PROVENIJENIČNI POKUSI SA ZELENOM DUGLAZIJOM (Pseudotsuga menziesii Mirb. Franco) NA LOKALITETU BLINJE KOD KREŠEVA
Authors: Ballian Dalibor , Mikić Todor , Pintarić Konrad
Published: January 2022

EUFRO program ispitivanja provenijencije duglazije (Pseudotsuga menziesii Mirb. Franco) započeo je u proljeće 1972. godine na poligonu Blinje kod Kreševa. Izmjerene su visine, prečnik, stopa preživljavanja, zapremina srednjeg stabla i ukupna zapremina po hektaru u dobi od 32 godine.

Statistički značajne razlike za navedene karakteristike nisu pronađene. Međutim, što se visine tiče, najbolja se pokazala 1099 provenijencija (Vasco Pine Grove, SAD) sa srednjom visinom od 20,90 m za prednji raspon 1099 provenijencije i prečnikom od 26, 46 m, a za stopu preživljavanja 1100 provenijencija (Grand Ronde Agency, Oregon, SAD) sa stopom od 37,33 biljaka po jednom lokalitetu. Najveću zapreminu srednjeg stabla imala je provenijencija 1099 i iznosila je 0,3796 m3, a najveću zapreminu po hektaru imala je 1036 provenijencija (Albemi, Britanska Kolumbija, Kanada) i iznosila je 442,54 m3/ha.
Optimalne debljinske klase za selekciju proporcionalne zapremine stabla (PPS)
Authors: Čabaravdić Azra
Published: January 2022

Planiranje inventure šuma je uvijek otvoreno za primjenu naprednog naučnog pristupa. Planeri istraživanja nastoje da optimizuju sve aktivnosti u okviru inventure šuma. Optimizacija plana uzorkovanja treba da pokaže smjer daljnjih poboljšanja postojećeg plana odabira stabala, u pogledu odabira stabala na osnovu vjerovatnoće proporcionalne veličini (PPS - Probability Proportional to Size), predviđanju (PPP) ili grešci (PPE) .

Ovaj rad razmatra mogućnost određivanja optimalnog praga za odabir stabla proporcionalnog zapremini stabla. Očekuje se da će primijenjeni postupci pokazati relativnu efikasnost pragova prečnika čije karakteristike mogu zadovoljiti zahtjeve za visokom preciznošću.

Nadalje, ovaj pristup bi se mogao koristiti kao osnova za razvoj složenijih dizajna uzorkovanja.
ŠESTI PRILOG POZNAVANJU NESAMONIKLE DENDROFLORE SARAJEVA I OKOLINE
Authors: Janjić Nikola
Published: January 2022

Šesti prilog je nastavio inventarizaciju uzgojenih dendrovrsta i njihovih oblika u sarajevskoj regiji započetu prije skoro pedeset godina. Procijenjena je prisutnost biljaka, kao i njihova otpornost na lokalne klimatske i druge uslove i dato mišljenje o mogućem uspjehu unošenja u svakom kritičnom slučaju.
ARMILLARIA GLJIVE U CENTRALNOJ BOSNI
Authors: Treštić Tarik , Usčuplić Midhat , Mujezinović Osman , Memišević Mirzeta
Published: January 2022

Armillaria je rod patogena i saprofita. Neke od ovih vrsta uzrokuju bolesti truleži korijena i ponekad veliku smrtnost stabala izloženih faktorima stresa, npr. požari, insekti, imela, zagađenje itd. Armillaria spp. su uobičajene u Bosni i Hercegovini, javljaju se kako u prirodnim šumama tako i na plantažama, ali nema saznanja o tome koja vrsta naseljava određena područja i koja je od njih značajan patogen. Prikazani rad čini prvi korak u istraživanju Armillaria u Bosni i Hercegovini kako bi se identifikovale uobičajene vrste i bolje razumjela njihova uloga u našim šumskim ekosistemima.
GLJIVE PRAŠUMSKIH REZERVATA "RAVNA VALA" NA IGMANU I "TRSTIONICA" PORED KAKNJA - PRVI PRILOG
Authors: Usčuplić Midhat , Treštić Tarik
Published: January 2022

Prezentirani su rezultati istraživanja gljiva prašuma šuma "Ravna vala" na planini Igman kod Sarajeva i "Trstionica" kod Kaknja realizovani u periodu 2001-2003. Ovo je prvi izvještaj na ovu temu koji pokazuje da su prašume šume dobar rezervoar gljiva. Ovdje se mogu naći neke vrlo rijetke vrste.
REZULTATI KALEMLJENJA PITOMOG KESTENA (Castanea sativa Mill.) KULTIVARIMA TIPA "MARON" NA PODRUČJU CAZINA
Authors: Koričić Šefik , Pintarić Konrad
Published: January 2022

Prvo kalemljenje kestena u Bosni i Hercegovini vrši se u Cazinu (sjeverozapadna Bosna) sa raznim sortama kestena "Marón" koje su uvezene iz Italije. U proljeće 2001. osnovan je hektar zasada kestena, sa kalemljenim sadnicama unesenim iz Italije, a 2001. i 2002. godine kalemljeni su neki izdanci u prirodnim izdanačkim šumama kestena. Rezultati dobijeni u zasadu kestena i izdanačkim šumama kestena su obećavajući.
PRILOG POZNAVANJU RASADNIČKE PROIZVODNJE CRNOG BORA (Pinus nigra Arn.)
Authors: Roth Valentin , Dubravac Tomislav
Published: January 2022

UDK 630*232:582.475

U istraživanju je korišteno sjeme crnog bora podrijetlom iz klonske sjemenske plantaže “Prkos” (nije priznata), Uprave šuma Podružnica Gospić, Šumarija Gospić (urod 2001), dorađeno tijekom zime 2001/2002 u trušnici u Šumarskom institutu Jastrebarsko.

Prilikom sjetve u sjemeništu rasadnika, bitna je količina sadnica po jedinici površine (ovisno o vremenu zadržavanja u sjemeništu 1, 2, ili 3 godine), što ovisi o kakvoći sjemena (punoća, čistoća, klijavost i dr.), te o količini posijanog sjemena (kom / m2 ili g / m2) koja je određena formulom na osnovi koje dobivamo potrebnu količinu sjemena za željeni broj biljaka. Za gustoću sjetve, u dosadašnjoj praksi uglavnom su se koristile neke iskustvene norme i načini izračunavanja broja odnosno količine sjemena po m2.

U našim istraživanjima razvidno je kako smo dorađenim sjemenom (do 98% punoće) i manjim brojem sjemenki dobili veći broj biljaka u odnosu na broj istih dobivenih iz manje kvalitetno dorađenog sjemena.

Isto tako, razvidno je kako pri sjetvi na osnovu formule “1” (X = broj sjemenki / m2) dobivamo od 40% do 45% željenog broja biljaka, dok sijanjem količine sjemena po formuli “2” (N = količina sjemena u g / m2), dobivamo 3,5 puta više biljaka crnog bora od željenog broja (željeni br. “V”).

Određenim izmjenama postojećih formula za izračunavanje potrebne količine sjemena za željeni broj biljaka, postigli bismo veću točnost, što je i potvrđeno u ovim istraživanjima sa sjemenom crnog bora.

Ista istraživanja (sa sjemenom – jele i bukve), provodimo u drugim rasadnicima, gdje preliminarni rezultati ukazuju na sličnost s prikazanima u ovome radu, čime bismo potvrdili navedeno.
IZRADA DISPOZICIJE BONITETNIH RAZREDA STANIŠTA JEDNODOBNIH ZASADA CRNOG BORA (Pinus nigra Arn.) NA KARBONATNIM SUPSTRATIMA U BOSNI
Authors: Ibrahimspahić Aida
Published: January 2022

UDK 630*54:582.475(497.6)

Značajne šumovite nepokrivene površine u Bosni i Hercegovini obrađivale su se sastojine smreke, bijelog i crnog bora. U posljednje vrijeme nije uspostavljen znanstveni pristup gospodarenju, pa su u upotrebi inozemne tablice prinosa (Shober, 1975.; Frauendorfer, 1954.). Upotreba tih tablica nije ispravna zbog različitih karakteristika štanda i mnogih drugih čimbenika.

Radi utvrđivanja poreznih osnova za plansko i racionalno gospodarenje ovim sastojinama provedeno je ispitivanje njihovih razvijenih, strukturnih i proizvodnih karakteristika. Prvi zadatak u ovom istraživanju, nakon procjene zemaljskih podataka, je definiranje rasporeda klasa mjesta. Cilj ovog rada je razviti dispoziciju krivulja prosječno visinskih klasa lokaliteta, odnosno relativnih visinskih klasa lokaliteta jednodobnih sastojina crnog bora na karbonatnoj podlozi u Bosni