bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating the effective conductivity for ellipse-inclusion model with Kapitza thermal resistance
Authors: Nguyen Van-Luat
Published: August 2021

The ellipse assemblage model with imperfect interface has quite complex microstructure, that can be considered an extension of the circle assemblage model with imperfect interfaces. The paper introduces an approximate method for computing the effective conductivity of isotropic composites with imperfect interfaces in two-dimensional space. Based on the coated-ellipse assemblage model and the equivalent inclusion approximation, one can determine the effective thermal conductivity of the composites. The polarization approximation is given in an explicit form (PEK) and this method will be applied to calculate the effective conductivity of the composite with Kapitza thermal resistance model. The PEK result will have compared with the Fast Fourier Transform (FFT) simulation and Hashin-strikman bounds (HS).
CHEP 2021: Preface to the Proceedings
Authors: Biscarat Catherine , Campana Simone , Hegner Benedikt , Roiser Stefan , Rovelli Chiara I. , Stewart Graeme A.
Published: August 2021

The 25th International Conference on Computing in High Energy and Nuclear Physics (CHEP), organised by CERN, took place as a virtual event from 17–21 May 2021. The conference attracted 1144 registered participants from 46 different countries. There were 207 scientific presentations made over the 5 days of the conference. These were divided between 30 long talks and 2 keynotes, which were presented in plenary sessions; and 175 short talks, which were presented in parallel sessions.
The Phoenix event display framework
Authors: Moyse Edward , Ali Fawad , Cortina Emilio , Bianchi Riccardo Maria , Couturier Ben
Published: August 2021

Visualising HEP experiment event data and geometry is vital for physicists trying to debug their reconstruction software, their detector geometry or their physics analysis, and also for outreach and publicity purposes. Traditionally experiments used in-house applications that required installation (often as part of a much larger experiment specific framework). In recent years, web-based event/geometry displays have started to appear, dramatically lowering the entry barrier to use, but which typically are still per-experiment. The Phoenix framework is an extensible, experiment-agnostic framework for event and geometry visualisation.
A proposal for Open Access data and tools multi-user deployment using ATLAS Open Data for Education
Authors: Sánchez Pineda Arturo , Guerrieri Giovanni ,   on behalf of ATLAS Software and Computing
Published: August 2021

The deployment of analysis pipelines has been tightly related and conditioned to the scientific facility’s computer infrastructure or academic institution where it is carried on. Nowadays, Software as a Service (SaaS) and Infrastructure as a Service (IaaS) have reshaped the industry of data handling, analysis, storage, and sharing. The sector of science does not escape those changes. This situation is particularly true in multinational collaborations, where distributed resources allow researchers to deploy data analysis in diverse computational ecosystems. This project explores how the current multi-cloud (e.g., SaaS + IaaS) approach can be adapted to modest scenarios where analysis pipelines can be deployed using containers and virtual machines containing analysis tools and protocols. This approach aims to replicate sophisticated computer facilities in places with fewer resources like small universities, start-ups, and even individuals who want to learn and contribute to this and other sciences and its replicability. It is desired to explore the development of multi-cloud-compatible tools in physics analysis and operations monitoring using ATLAS experimental and simulated data, adding the Big Data component that the High Energy Physics field has by nature.
dCache: Inter-disciplinary storage system
Authors: Mkrtchyan Tigran , Chitrapu Krishnaveni , Garonne Vincent , Litvintsev Dmitry , Meyer Svenja , Millar Paul , Morschel Lea , Rossi Albert , Sahakyan Marina
Published: August 2021

The dCache project provides open-source software deployed internationally to satisfy ever more demanding storage requirements. Its multifaceted approach provides an integrated way of supporting different use-cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters and long term data persistence on a tertiary storage. Though it was originally developed for the HEP experiments, today it is used by various scientific communities, including astrophysics, biomed, life science, which have their specific requirements. In this paper we describe some of the new requirements as well as demonstrate how dCache developers are addressing them.
The Cherenkov Telescope Array production system proto-type for large-scale data processing and simulations
Authors: Arrabito Luisa , Bregeon Johan , Maeght Patrick , Sanguillon Michèle ,   for the CTA Consortium, Tsaregorodtsev Andrei ,   for the DIRAC Consortium
Published: August 2021

The Cherenkov Telescope Array (CTA) is the next-generation instrument in the very-high energy gamma ray astronomy domain. It will consist of tens of Cherenkov telescopes deployed in 2 arrays at La Palma (Spain) and Paranal (ESO, Chile) respectively. Currently under construction, CTA will start operations around 2023 for a duration of about 30 years. During operations CTA is expected to produce about 2 PB of raw data per year plus 5-20 PB of Monte Carlo data. The global data volume to be managed by the CTA archive, including all versions and copies, is of the order of 100 PB with a smooth growing profile. The associated processing needs are also very high, of the order of hundreds of millions of CPU HS06 hours per year. In order to optimize the instrument design and study its performances, during the preparatory phase (2010-2017) and the current construction phase, the CTA consortium has run massive Monte Carlo productions on the EGI grid infrastructure. In order to handle these productions and the future data processing, we have developed a production system based on the DIRAC framework. The current system is the result of several years of hardware infrastructure upgrades, software development and integration of different services like CVMFS and FTS. In this paper we present the current status of the CTA production system and its exploitation during the latest large-scale Monte Carlo campaigns.
The ESCAPE Data Lake: The machinery behind testing, monitoring and supporting a unified federated storage infrastructure of the exabyte-scale
Authors: Dona Rizart , Di Maria Riccardo ,   on behalf of the ESCAPE project
Published: August 2021

The EU-funded ESCAPE project aims at enabling a prototype federated storage infrastructure, a Data Lake, that would handle data on the exabyte-scale, address the FAIR data management principles and provide science projects a unified scalable data management solution for accessing and analyzing large volumes of scientific data. In this respect, data transfer and management technologies such as Rucio, FTS and GFAL are employed along with monitoring enabling solutions such as Grafana, Elasticsearch and perf- SONAR. This paper presents and describes the technical details behind the machinery of testing and monitoring of the Data Lake – this includes continuous automated functional testing, network monitoring and development of insightful visualizations that reflect the current state of the system. Topics that are also addressed include the integration with the CRIC information system as well as the initial support for token based authentication / authorization by using OpenID Connect. The current architecture of these components is provided and future enhancements are discussed.
Coffea-casa: an analysis facility prototype
Authors: Adamec Matous , Attebury Garhan , Bloom Kenneth , Bockelman Brian , Lundstedt Carl , Shadura Oksana , Thiltges John
Published: August 2021

Data analysis in HEP has often relied on batch systems and event loops; users are given a non-interactive interface to computing resources and consider data event-by-event. The “Coffea-casa” prototype analysis facility is an effort to provide users with alternate mechanisms to access computing resources and enable new programming paradigms. Instead of the command-line interface and asynchronous batch access, a notebook-based web interface and interactive computing is provided. Instead of writing event loops, the columnbased Coffea library is used.

In this paper, we describe the architectural components of the facility, the services offered to end users, and how it integrates into a larger ecosystem for data access and authentication.
Exploring the virtues of XRootD5: Declarative API
Authors: Simon Michal , Hanushevsky Andrew
Published: August 2021

Across the years, being the backbone of numerous data management solutions used within the WLCG collaboration, the XRootD framework and protocol became one of the most important building blocks for storage solutions in the High Energy Physics (HEP) community. The latest big milestone for the project, release 5, introduced multitude of architectural improvements and functional enhancements, including the new client side declarative API, which is the main focus of this study. In this contribution, we give an overview of the new client API and we discuss its motivation and its positive impact on overall software quality (coupling, cohesion), readability and composability.
Training and Serving ML workloads with Kubeflow at CERN
Authors: Golubovic Dejan , Rocha Ricardo
Published: August 2021

Machine Learning (ML) has been growing in popularity in multiple areas and groups at CERN, covering fast simulation, tracking, anomaly detection, among many others. We describe a new service available at CERN, based on Kubeflow and managing the full ML lifecycle: data preparation and interactive analysis, large scale distributed model training and model serving. We cover specific features available for hyper-parameter tuning and model metadata management, as well as infrastructure details to integrate accelerators and external resources. We also present results and a cost evaluation from scaling out a popular ML use case using public cloud resources, achieving close to linear scaling when using a large number of GPUs.
Laurelin: Java-native ROOT I/O for Apache Spark
Authors: Melo Andrew , Shadura Oksana ,   for the CMS Collaboration
Published: August 2021

Apache Spark[1] is one of the predominant frameworks in the big data space, providing a fully-functional query processing engine, vendor support for hardware accelerators, and performant integrations with scientific computing libraries. One difficulty in adopting conventional big data frameworks to HEP workflows is the lack of support for the ROOT file format in these frameworks. Laurelin[6] implements ROOT I/O with a pure Java library, with no bindings to the C++ ROOT[2] implementation, and is readily installable via standard Java packaging tools. It provides a performant interface enabling Spark to read (and soon write) ROOT TTrees, enabling users to process these data without a pre-processing phase converting to an intermediate format.
Accelerating GAN training using highly parallel hardware on public cloud
Authors: Cardoso Renato , Golubovic Dejan , Peluaga Lozada Ignacio , Rocha Ricardo , Fernandes João , Vallecorsa Sofia
Published: August 2021

With the increasing number of Machine and Deep Learning applications in High Energy Physics, easy access to dedicated infrastructure represents a requirement for fast and efficient R&D. This work explores different types of cloud services to train a Generative Adversarial Network (GAN) in a parallel environment, using Tensorflow data parallel strategy. More specifically, we parallelize the training process on multiple GPUs and Google Tensor Processing Units (TPU) and we compare two algorithms: the TensorFlow built-in logic and a custom loop, optimised to have higher control of the elements assigned to each GPU worker or TPU core. The quality of the generated data is compared to Monte Carlo simulation. Linear speed-up of the training process is obtained, while retaining most of the performance in terms of physics results. Additionally, we benchmark the aforementioned approaches, at scale, over multiple GPU nodes, deploying the training process on different public cloud providers, seeking for overall efficiency and cost-effectiveness. The combination of data science, cloud deployment options and associated economics allows to burst out heterogeneously, exploring the full potential of cloud-based services.
Towards a realistic track reconstruction algorithm based on graph neural networks for the HL-LHC
Authors: Biscarat Catherine , Caillou Sylvain , Rougier Charline , Stark Jan , Zahreddine Jad
Published: August 2021

The physics reach of the HL-LHC will be limited by how efficiently the experiments can use the available computing resources, i.e. affordable software and computing are essential. The development of novel methods for charged particle reconstruction at the HL-LHC incorporating machine learning techniques or based entirely on machine learning is a vibrant area of research. In the past two years, algorithms for track pattern recognition based on graph neural networks (GNNs) have emerged as a particularly promising approach. Previous work mainly aimed at establishing proof of principle. In the present document we describe new algorithms that can handle complex realistic detectors. The new algorithms are implemented in ACTS, a common framework for tracking software. This work aims at implementing a realistic GNN-based algorithm that can be deployed in an HL-LHC experiment.
Accelerating End-to-End Deep Learning for Particle Reconstruction using CMS open data
Authors: Andrews Michael , Burkle Bjorn , Chaudhari Shravan , Di Croce Davide , Gleyzer Sergei , Heintz Ulrich , Narain Meenakshi , Paulini Manfred , Usai Emanuele
Published: August 2021

Machine learning algorithms are gaining ground in high energy physics for applications in particle and event identification, physics analysis, detector reconstruction, simulation and trigger. Currently, most data-analysis tasks at LHC experiments benefit from the use of machine learning. Incorporating these computational tools in the experimental framework presents new challenges. This paper reports on the implementation of the end-to-end deep learning with the CMS software framework and the scaling of the end-to-end deep learning with multiple GPUs. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation for particle and event identification. We demonstrate the end-to-end implementation on a top quark benchmark and perform studies with various hardware architectures including single and multiple GPUs and Google TPU.
Reframing Jet Physics with New Computational Methods
Authors: Cranmer Kyle , Drnevich Matthew , Macaluso Sebastian , Pappadopulo Duccio
Published: August 2021

We reframe common tasks in jet physics in probabilistic terms, including jet reconstruction, Monte Carlo tuning, matrix element – parton shower matching for large jet multiplicity, and efficient event generation of jets in complex, signal-like regions of phase space. We also introduce Ginkgo, a simplified, generative model for jets, that facilitates research into these tasks with techniques from statistics, machine learning, and combinatorial optimization. We also review some of the recent research in this direction that has been enabled with Ginkgo. We show how probabilistic programming can be used to efficiently sample the showering process, how a novel trellis algorithm can be used to efficiently marginalize over the enormous number of clustering histories for the same observed particles, and how the dynamic programming and reinforcement learning can be used to find the maximum likelihood clusterinng in this enormous search space. This work builds bridges with work in hierarchical clustering, statistics, combinatorial optmization, and reinforcement learning.
ALICE Run 3 Analysis Framework
Authors: Alkin Anton , Eulisse Giulio , Grosse-Oetringhaus Jan Fiete , Hristov Peter , Kabus Maja
Published: August 2021

In LHC Run 3 the ALICE Collaboration will have to cope with an increase of lead-lead collision data of two orders of magnitude compared to the Run 1 and 2 data-taking periods. The Online-Offline (O2) software framework has been developed to allow for distributed and efficient processing of this unprecedented amount of data. Its design, which is based on a message-passing back end, required the development of a dedicated Analysis Framework that uses the columnar data format provided by Apache Arrow. The O2 Analysis Framework provides a user-friendly high-level interface and hides the complexity of the underlying distributed framework. It allows the users to access and manipulate the data in the new format both in the traditional “event loop” and a declarative approach using bulk processing operations based on Arrow’s Gandiva sub-project. Building on the well-tested system of analysis trains developed by ALICE in Run 1 and 2, the AliHyperloop infrastructure is being developed. It provides a fast and intuitive user interface for running demanding analysis workflows in the GRID environment and on the dedicated Analysis Facility. In this document, we report on the current state and ongoing developments of the Analysis Framework and of AliHyperloop, highlighting the design choices and the benefits of the new system.
FuncADL: Functional Analysis Description Language
Authors: Proffitt Mason , Watts Gordon
Published: August 2021

The traditional approach in HEP analysis software is to loop over every event and every object via the ROOT framework. This method follows an imperative paradigm, in which the code is tied to the storage format and steps of execution. A more desirable strategy would be to implement a declarative language, such that the storage medium and execution are not included in the abstraction model. This will become increasingly important to managing the large dataset collected by the LHC and the HL-LHC. A new analysis description language (ADL) inspired by functional programming, FuncADL, was developed using Python as a host language. The expressiveness of this language was tested by implementing example analysis tasks designed to benchmark the functionality of ADLs. Many simple selections are expressible in a declarative way with FuncADL, which can be used as an interface to retrieve filtered data. Some limitations were identified, but the design of the language allows for future extensions to add missing features. FuncADL is part of a suite of analysis software tools being developed by the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP). These tools will be available to develop highly scalable physics analyses for the LHC.
Streaming Readout of the CLAS12 Forward Tagger Using TriDAS and JANA2
Authors: Ameli Fabrizio , Battaglieri Marco , Bondí Mariangela , Celentano Andrea , Boyarinov Sergey , Brei Nathan , Chiarusi Tommaso , De Vita Raffaella , Fanelli Cristiano , Gyurjyan Vardan , Lawrence David , Musico Paolo , Pellegrino Carmelo , Raydo Ben , Vallarino Simone
Published: August 2021

An effort is underway to develop streaming readout data acquisition system for the CLAS12 detector in Jefferson Lab’s experimental Hall-B. Successful beam tests were performed in the spring and summer of 2020 using a 10GeV electron beam from Jefferson Lab’s CEBAF accelerator. The prototype system combined elements of the TriDAS and CODA data acquisition systems with the JANA2 analysis/reconstruction framework. This successfully merged components that included an FPGA stream source, a distributed hit processing system, and software plugins that allowed offline analysis written in C++ to be used for online event filtering. Details of the system design and performance are presented.
Progress in developing a hybrid deep learning algorithm for identifying and locating primary vertices
Authors: Akar Simon , Atluri Gowtham , Boettcher Thomas , Peters Michael , Schreiner Henry , Sokoloff Michael , Stahl Marian , Tepe William , Weisser Constantin , Williams Mike
Published: August 2021

The locations of proton-proton collision points in LHC experiments are called primary vertices (PVs). Preliminary results of a hybrid deep learning algorithm for identifying and locating these, targeting the Run 3 incarnation of LHCb, have been described at conferences in 2019 and 2020. In the past year we have made significant progress in a variety of related areas. Using two newer Kernel Density Estimators (KDEs) as input feature sets improves the fidelity of the models, as does using full LHCb simulation rather than the “toy Monte Carlo” originally (and still) used to develop models. We have also built a deep learning model to calculate the KDEs from track information. Connecting a tracks-to-KDE model to a KDE-to-hists model used to find PVs provides a proof-of-concept that a single deep learning model can use track information to find PVs with high efficiency and high fidelity. We have studied a variety of models systematically to understand how variations in their architectures affect performance. While the studies reported here are specific to the LHCb geometry and operating conditions, the results suggest that the same approach could be used by the ATLAS and CMS experiments.
Usage of GPUs in ALICE Online and Offline processing during LHC Run 3
Authors: Rohr David
Published: August 2021

ALICE will significantly increase its Pb–Pb data taking rate from the 1 kHz of triggered readout in Run 2 to 50 kHz of continuous readout for LHC Run 3. Updated tracking detectors are installed for Run 3 and a new twophase computing strategy is employed. In the first synchronous phase during the data taking, the raw data is compressed for storage to an on-site disk buffer and the required data for the detector calibration is collected. In the second asynchronous phase the compressed raw data is reprocessed using the final calibration to produce the final reconstruction output. Traditional CPUs are unable to cope with the huge data rate and processing demands of the synchronous phase, therefore ALICE employs GPUs to speed up the processing. Since the online computing farm performs a part of the asynchronous processing when there is no beam in the LHC, ALICE plans to use the GPUs also for this second phase. This paper gives an overview of the GPU processing in the synchronous phase, the full system test to validate the reference GPU architecture, and the prospects for the GPU usage in the asynchronous phase.
Sakrumfrakturen – Fragilitätsfrakturen
Authors: Pieroh Philipp , Fakler Johannes K.M. , Heyde Christoph-Eckhard , Nowak Tobias E. , Rommens Pol M. , Wagner Daniel
Published: August 2021

Fragilitätsfrakturen des Sakrums (FFS) sind eine neue Herausforderung für Becken- und Wirbelsäulenchirurgen mit einem deutlichen Anstieg der Fallzahlen über die letzten Jahre. Die unspezifische Klinik und oftmals unauffällige Röntgenbilder unterstreichen die Notwendigkeit der Computertomografie (CT) als Primärdiagnostik, um auch nicht-dislozierte Frakturen zu detektieren. Spezifische Klassifikationen für FFS existieren nicht, jedoch wurden die FFS in der fragility fractures of the pelvis (FFP) Klassifikation abgebildet. Hier werden (nicht-) dislozierte unilaterale und bilaterale Frakturen von bilateralen dislozierten Frakturen mit horizontaler Kommunikation unterschieden. Unabhängig der Therapie (konservativ/operativ) sollte eine Osteoporosediagnostik und -therapie erfolgen. Nicht-dislozierte Frakturen können konservativ behandelt werden, dabei gilt es jedoch eine suffiziente Analgesie und ausreichende Mobilisation zu gewährleisten, ggf. mit der Erstellung spezifischer Belastungsprotokolle. Ebenfalls ist die Therapie mit (rekombinantem) Parathormon erfolgsversprechend. Bei anhaltender Immobilisation und/oder Schmerzen muss bei nicht-dislozierten Frakturen eine operative Therapie empfohlen werden. Aufgrund der hohen Rate der Frakturprogression (bis zu 30%) sowie allgemeinen Versagensrate der konservativen Therapie (ca. 18%) bei FFS sollte eine engmaschige Kontrolle erfolgen. Dislozierte Frakturen sollten operativ behandelt werden, wobei hier perkutane Verfahren vorzuziehen sind.
Central Serous Chorioretinopathy – an Overview
Authors: Berger Lieselotte , Bühler Virginie , Yzer Suzanne
Published: August 2021

Central serous chorioretinopathy (CSCR) is characterised by retinal serous detachment usually localised in the macular region. CSCR predominantly affects men between 30 and 50 years of age. Traditional classification differentiates between acute (duration shorter than 4 to 6 months) and chronic disease (duration longer than 4 to 6 months). The pathogenesis is multifactorial and current thinking assumes the presence of localised choroidal hyperpermeability with subsequent secondary changes in the retinal pigment epithelium (RPE). The symptoms of acute CSCR include central blurred vision, often with deterioration in visual acuity. Optical coherence tomography (OCT) reveals subretinal fluid (SRF) and/or single retinal pigment epithelial detachments. Fluorescein angiography (FA) usually shows a leaking point with absent or only minor RPE changes in the acute phase and indocyanine green angiography (ICG) highlights circumscribed areas of thickened and hyperpermeable choroid.
Acute cases may show spontaneous resolution of SRF, but may also recur and/or become chronic. After the initial diagnosis, spontaneous remission is seen in about 70 to 80% of cases, with a recurrence rate of about 50%. Due to the favourable spontaneous course, it is recommended to wait for 4 to 6 months after the first symptoms manifest. Steroid therapy is considered as a major risk factor. Chronic cases are characterised by slow deterioration in visual acuity with reduced contrast and colour perception. There are extensive RPE changes, with secondary degenerative changes of the photoreceptors. The disease can by complicated by choroidal neovascularisation (CNV), especially in elderly patients. The literature lists a number of treatments: The leakage point (visible in the FA) can be treated by focal laser therapy, either micropulse laser or, if sufficiently distant from the fovea, by argon laser coagulation. Randomised trials in chronic CSCR demonstrated good outcomes
with photodynamic therapy. With observation periods ranging from 3 to 6 months, several case series reports found improvement after systemic administration of mineralocorticoid receptor antagonists, carbonic anhydrase inhibitors or non-steroidal anti-inflammatory drugs. In the presence of secondary CNV, anti-VEGF treatment should be initiated. It is unclear whether the combination with PDT might be useful.
Rectal Administration of Ibuprofen: Comparison of Enema and
Suppository Form
Authors: Prasaja Budi , Harahap Yahdiana , Sandra Monika , Iskandar Irene , Lusthom Windy , Cahyaningsih Prawitasari
Published: August 2021

Ibuprofen is a widely used and well-tolerated analgesic and antipyretic. It is
desirable to have a formulation with a rapid rate of absorption because it is
required for rapid pain relief and temperature reduction. Previous studies have
described the pharmacokinetic profiles of ibuprofen suppository and the mean
peak times of ibuprofen suppository were around 1.8 hours, indicating a
slower rate of absorption. The aim of this study is to compare the
pharmacokinetic parameters of rectal administration of ibuprofen between enema
and suppository form in order to provide evidence for the faster absorption
rates of ibuprofen enema. This study was a phase-1 clinical study, open-label,
randomized and two-way crossover with one-week washout period comparing the
absorption profile of equal dose of ibuprofen administered rectally in two
treatment phases: ibuprofen suppository and enema. Blood samples were collected
post dose for pharmacokinetic analyses. Tmax was analyzed using a
Wilcoxon matched paired test. A standard ANOVA model, appropriate for
bioequivalence studies was used and ratios of 90% confidence intervals
were calculated. This study showed that Tmax for ibuprofen enema was
less than half that of ibuprofen suppository (median 40 min vs.
90 min, respectively; p-value=0.0003). Cmax
and AUC0–12 for ibuprofen enema were bioequivalent to
ibuprofen suppository, as the ratio of
test/reference=104.52%, 90% CI
93.41–116.95% and the ratio of
test/reference=98.12%, 90%CI
93.34–103.16%, respectively, which fell within
80–125% bioequivalence limit. The overall extent of absorption
was similar to the both, which were all well tolerated. In terms of
Tmax, Ibuprofen enema was absorbed twice as quickly as from
ibuprofen suppository. Therefore it is expected that an ibuprofen enema may
provide faster onset of analgesic and antipyretic benefit.
Caring for Cancer Patients during Corona Pandemic—(COVID-19)—A Narrative Review
Authors: Pratapa Sree Karthik , Acharya Sourya , Mamidipalli Sai Spoorthy , Andhale Amol
Published: August 2021

Background Coronavirus disease 2019, the third pandemic of 21st century which has brought the whole world under panic, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a zoonotic beta coronavirus sharing phylogenetic, genomic similarities with SARS virus and Middle East Respiratory Syndrome virus.

Specific Concerns Cancer patients are at double the risk than normal patients since these patients are at immunocompromised state. WHO guidelines advice the patients to plan only emergency hospital visits only till the pandemic persists. Should meet patient/visitors in a well-ventilated room or outdoors and maintain at least 2 m distance between the visitor/patients. It also encourages the patient to refill the prescribed medications in well advance and to stay physically active, if possible.

Discussion The World Health Organizations’ isolate, trace, test, treat policy needs to be followed to protect these high-risk patients from this global pandemic.]
Compression Screw Fixation of Lunate Fracture: Case Report and Review of the Literature
Authors: Qureshi Hassan A. , Tadisina Kashyap Komarraju , Frojo Gianfranco , Xu Kyle Y. , Kraemer Bruce A.
Published: August 2021

Background Isolated traumatic lunate fractures without other surgical carpal bone or ligamentous injuries are extremely rare, with few published reports available to guide management. Lunate fracture management is controversial, and depends on concurrent injuries of adjacent carpal bones, ligaments, risk of ischemia, and displacement.

Case Description A 48-year-old right hand dominant man suffered a crush injury to the left hand caught between a forklift and a metal shelf. Radiographs and computed tomography imaging of the left hand and wrist were significant for a displaced Teisen IV fracture of the lunate. A dorsal ligament sparing approach was utilized to access, reduce, and fixate the fracture using a headless compression screw. After immobilization and rehab, at 9 months after initial injury, the patient was back to work on full duty without restriction and pleased with the results of his treatment.

Literature Review A literature review of lunate fracture compression screw fixation was performed and revealed a total of three reports indicating successful treatment of fractures, with patients returning to full activity.

Clinical Relevance Lunate fractures are rare, often missed, and treating these injuries can be challenging, particularly in the setting of acute trauma. Based on our limited experience, we believe that open reduction and internal fixation of isolated Teisen IV lunate fractures with a headless compression screw is a viable treatment modality with satisfactory outcomes.
Water-resistive and wearable triboelectric nanogenerators based on polyurethane/polyester textiles fabricated utilizing a planarization layer
Authors: Jeon Young Pyo , Lee Hak Ji , Yoo Young Joon , Yoo Keon-Ho , Park Sang Yoon , Kim Tae Whan
Published: August 2021

We report a water-resistive and wearable triboelectric nanogenerator on a polyurethane/polyester textile substrate with a planarization layer. The power generation and reliability of the triboelectric nanogenerators (TENGs) fabricated utilizing a resin planarization layer were significantly enhanced in comparison with those of TENGs without the resin planarization layer. The planarization layer was deposited on the polyurethane/polyester textile substrate by using spin coating and ultraviolet curing to improve its surface properties and polarity. The output voltages and currents of TENGs based on a resin planarization layer on a polyurethane/polyester substrate were measured in the vertical contact-separation mode by using a counter unit containing Al electrodes and a polyimide friction layer. The TENGs exhibited a peak potential of over 30 V, which is about three times larger than that of the devices without such a planarization layer, and the corresponding maximum power density was 3.16 mW/m2. Furthermore, the results of endurance and water resistance tests carried out on the TENGs with a resin planarization layer on a textile substrate showed that such devices were suitable for use in applications in which the device must be worn.
Defects in multilayer MoS2 grown by pulsed laser deposition and their impact on electronic structure
Authors: Sharona H.
Published: August 2021

Defect morphology plays a crucial role in determining the properties of the system and can harness new functionalities. One of the widely studied layered materials is semiconducting molybdenum disulfide (MoS2) with interesting electronic, optical, and spin-valley properties strongly dependent on the stacking order. The defects on this material are extensively studied but limited to individual layers. Here, we provide a systematic study of a defect in a multi-layer MoS2 sample grown by pulsed laser deposition using transmission electron microscopy in cross-sectional form and first-principles calculation to explore their electronic properties. The various dislocations in the system, such as ripple, kink, peak, and edge dislocation, change the inter-layer distance. The observed inversion domain boundaries introduce 3R stacking in the system with deviation from straight layer nature. These stacking defects add richness to existing defect structures and open new opportunities for novel device applications beyond a single-layer limit.
N95 respirator mask breathing leads to excessive carbon dioxide inhalation and reduced heat transfer in a human nasal cavity
Authors: Salati Hana , Khamooshi Mehrdad , Vahaji Sara , Christo Farid C. , Fletcher David F. , Inthavong Kiao
Published: August 2021

Face masks and respirators are used to filter inhaled air, which may contain airborne droplets and high particulate matter (PM) concentrations. The respirators act as a barrier to the inhaled and exhaled air, which may change the nasal airflow characteristics and air-conditioning function of the nose. This study aims to investigate the nasal airflow dynamics during respiration with and without an N95 respirator driven by airflow through the nasal cavity to assess the effect of the respirator on breathing conditions during respiration. To achieve the objective of this study, transient computational fluid dynamics simulations have been utilized. The nasal geometry was reconstructed from high-resolution Computed Tomography scans of a healthy 25-year-old female subject. The species transport method was used to analyze the airflow, temperature, carbon dioxide (CO2), moisture content (H2O), and temperature distribution within the nasal cavity with and without an N95 respirator during eight consecutive respiration cycles with a tidal volume of 500 ml. The results demonstrated that a respirator caused excessive CO2 inhalation by approximately 7× greater per breath compared with normal breathing. Furthermore, heat and mass transfer in the nasal cavity was reduced, which influences the perception of nasal patency. It is suggested that wearers of high-efficiency masks that have minimal porosity and low air exchange for CO2 regulation should consider the amount of time they wear the mask.
Sperm cryopreservation in the Burmese python
Authors: Young Carly , Ravida Nicole , Rochford Michael , Mazzotti Frank , Curtis Michelle , Durrant Barbara
Published: August 2021

Burmese pythons Python bivittatus captured in the Florida Everglades as part of an invasive species monitoring program served as a model for the development of sperm cryopreservation protocols for endangered snakes. Spermatozoa were collected from the vas deferens and initial motility, plasma membrane integrity and acrosome integrity were recorded before cryopreservation. Spermatozoa were extended in TES and Tris (TEST) yolk buffer with glycerol (GLY) or dimethyl sulfoxide (DMSO) concentrations of 8%, 12% or 16%, or combinations of GLY and DMSO with final concentrations of 4%:4%, 6%:6% or 8%:8%, and frozen at a rate of 0.3°C min−1. Sperm frozen in combinations of GLY and DMSO exhibited greater post-thaw motility and plasma membrane integrity than those frozen in GLY or DMSO alone. All DMSO and GLY:DMSO treatments preserved a greater proportion of intact acrosomes than GLY alone. To determine the best overall cryopreservation protocol for this species, a sperm quality index was calculated, giving equal weight to each of the three measured indicators of cryosurvival. This analysis revealed that Burmese python spermatozoa frozen in 6% GLY:6% DMSO or 4% GLY:4% DMSO exhibited the highest post-thaw viability. This study represents the first comparative, comprehensive attempt to develop a sperm cryopreservation protocol for any snake species.
Sperm cryopreservation in an Australian skink (
Authors: Hobbs Rebecca J. , Upton Rose , Keogh Leesa , James Karen , Baxter-Gilbert James , Whiting Martin J.
Published: August 2021

Assisted reproductive technologies for population and genetic management for threatened herpetofauna have grown substantially in the past decade. Here we describe experiments to optimise sperm cryopreservation in a model squamate, the eastern water skink Eulamprus quoyii. Small, concentrated volumes of highly motile spermatozoa were reliably collected from adult male E. quoyii by non-lethal ventral massage. Samples were used to: (1) test whether protein-rich diluents, namely Beltsville poultry semen extender (BPSE) and TES and Tris (TEST) yolk buffer (TYB), improve post-thaw quality metrics compared with Dulbecco’s phosphate-buffered saline (DPBS); and (2) compare the efficacy of these diluents in combination with either 1.35 M glycerol or 1.35 M dimethyl sulfoxide (DMSO) at two freezing rates, fast (approximately –20°C min−1) versus slow (–6°C min−1). Glycerol and DMSO performed equally well in preserving spermatozoa under slow freezing rates. Under these conditions, the use of the complex diluents BPSE and TYB significantly improved post-thaw total motility compared with DPBS. Complex interactions occurred between cryodiluent type, cryoprotectant and freezing rate when testing fast versus slow freezing rates among treatment groups. Under slow freezing rates, DMSO was better at preserving membrane integrity and motility, regardless of diluent type, but successful fast freezing required complex diluents to support motility and membrane integrity, which has implications for implementation in a field setting.
Replication across space and time must be weak in the social and environmental sciences
Authors: Goodchild Michael F. , Li Wenwen
Published: August 2021

Replicability takes on special meaning when researching phenomena that are embedded in space and time, including phenomena distributed on the surface and near surface of the Earth. Two principles, spatial dependence and spatial heterogeneity, are generally characteristic of such phenomena. Various practices have evolved in dealing with spatial heterogeneity, including the use of place-based models. We review the rapidly emerging applications of artificial intelligence to phenomena distributed in space and time and speculate on how the principle of spatial heterogeneity might be addressed. We introduce a concept of weak replicability and discuss possible approaches to its measurement.
On randomly changing conformity bias in cultural transmission
Authors: Denton Kaleda K. , Liberman Uri , Feldman Marcus W.
Published: August 2021

Significance

Animals, from humans toDrosophila, display conformity and anticonformity. Population dynamics under (anti)conformity may explain emergent properties of groups including fads, norms, and collective behavior. Although empirical evidence suggests that a population’s level of conformity can vary over time, most mathematical models have not included time-varying conformity coefficients. To potentially improve applicability to real-world systems, we allow conformity coefficients, numbers of sampled “role models,” and weak selection to vary stochastically in an established conformity model. Novel dynamics are possible, including simultaneous stochastic local stability of monomorphisms and polymorphism. Interpreting real-world population differences in terms of (anti)conformity may therefore not be straightforward. Under some conditions, however, the deterministic model provides a useful approximation to the stochastic model.
Magnetotransport properties of Fe substituted Ca3CoMnO6
Authors: Thankachen Nisha , Sengunthar Poornima , Patel Shivangi S , Pandya Rutvi J , Joshi U S
Published: August 2021

Ca3CoMnO6, a quasi-1D Ising chain at low temperature offers rich fundamental physics and applications. We have studied the dielectric and magnetoelectric coupling in Fe doped Ca3CoMnO6 (CCMO) bulk ceramics prepared by co-precipitation technique. Single phase hexagonal crystal structure having R-3C space group was confirmed by x-ray diffraction. Extremely low currents were observed up to 20% Fe doping. Doping dependence of magnetoresistance (MR) revealed both positive and negative MR, with anomalously high MR values beyond 3000% in diluted Fe doped CCMO; whereas the higher doping of Fe was found to result in negative MR due to enhanced magnetostriction effects. The dielectric study was carried out for a range of 20 Hz to 10 MHz. The negative value of the colossal magnetodielectric induced in the Fe doped samples can be attributed to the magnetostriction effect along with interfacial Maxwell-Wagner polarization.
Efficient and versatile toolbox for analysis of time-tagged measurements
Authors: Lin Z. , Schweickert L. , Gyger S. , Jöns K.D. , Zwiller V.
Published: August 2021

Acquisition and analysis of time-tagged events is a ubiquitous tool in scientific and industrial applications. With increasing time resolution, number of input channels, and acquired events, the amount of data can be overwhelming for standard processing techniques. We developed the Extensible Time-tag Analyzer (ETA), a powerful and versatile, yet easy to use software to efficiently analyze and display time-tagged data. Our tool allows for flexible extraction of correlation from time-tagged data beyond start-stop measurements that were traditionally used. A combination of state diagrams and simple code snippets allows for analysis of arbitrary complexity while keeping computational efficiency high.
Drainage canal impacts on smoke aerosol emissions for Indonesian peatland and non-peatland fires
Authors: Lu Xiaoman , Zhang Xiaoyang , Li Fangjun , Gao Lun , Graham Laura , Vetrita Yenni , Saharjo Bambang H , Cochrane Mark A
Published: August 2021

Indonesia has experienced frequent fires due to the lowering of groundwater levels caused by drainage via extensive canal networks for agricultural development since the 1970s. However, the impact of canals on fire emissions is still poorly understood. Here we investigate canal impacts on smoke aerosol emissions for Indonesian peatland and non-peatland fires by quantifying the resulting changes of smoke aerosol emission coefficient (Ce) that represents total aerosol emissions released from per unit of fire radiative energy. First, we quantified the impacts of canal drainage and backfilling on water table depth (WTD) variations using field data and then expanded such impacts from field to regional scales by correlating field WTD to satellite terrestrial water storage (TWS) anomalies from Gravity Recovery and Climate Experiment. Second, we estimated Ce from fire radiative power and smoke-aerosol emission rates based on Moderate Resolution Imaging Spectroradiometer active fire and multi-angle implementation of atmospheric correction aerosol products. Finally, we evaluated the Ce variation with TWS anomalies. The results indicate: (a) Ce is larger in peatland fires than in non-peatland fires; (b) Ce increases significantly as TWS anomalies decrease for both peatland and non-peatland fires; and (c) Ce changes at nearly twice the rate in peatland for a given TWS anomaly range as in non-peatland. These phenomena likely result from the different fuel types and combustion phases prevalent under different moisture conditions. These findings support the Indonesian government’s recent peatland restoration policies and pave the way for improved estimation of tropical biomass burning emissions.
Computation in a general physical setting
Authors: Gilligan-Lee Ciarán M
Published: August 2021

The computational abilities of theories within the generalised probabilistic theory framework has been the subject of much recent study. Such investigations aim to gain an understanding of the possible connections between physical principles and computation. Moreover, comparing and contrasting the computational properties of quantum theory with other operationally-sensible theories could shed light on the strengths and limitations of quantum computation. This paper reviews and extends some of these results, deriving new bounds on the computational ability of theories satisfying n-local tomography, and theories in which states are represented as generalised superpositions. It moreover provides a refined version of the conjecture that a quantum computer can simulate the computation in any theory within a certain sub-class of generalised probabilistic theories with at most polynomial overhead. The paper ends by describing an important relation between this conjecture and delegated computation, similar to the relation between quantum non-locality and device-independent cryptography.
Traceable functional characterization of surface topography with angular-resolved scattering light measurement
Authors: Eifler Matthias , Brodmann Boris , Hansen Poul Erik , Seewig Jörg
Published: August 2021

Among other functional characteristics, tribological properties of workpieces are directly associated with the microstructures on their surface. Thus, a precise, reliable, and traceable acquisition of these microstructures is required to evaluate characteristics of wear, friction, and lubrication on the surface. One suitable method is the angular-resolved scattering light (ARS) measurement that is a very robust measuring technique and can be used for in-process quality monitoring. It is very insensitive to vibrations due to measuring the angular distribution and not the distance between the instrument and workpiece. The instrument provides interesting capabilities for the monitoring of functionally relevant processes as small changes in the surface texture can be detected reliably. The traceability of the measuring principle is challenging as the measurements have to be connected to the basic unit of length. We propose calibration artifacts (material measures) that are manufactured with ultra-precision turning and can be applied for the calibration and verification of the ARS instrument. The design of the material measures is based on a simulation model for the ARS instrument and aims at predefined Aq-values (see the guideline VDA 2009). By using a scattering reference measuring device that is traceable via the power spectral density the traceability of the process is ensured. Results of comparison measurements between multiple ARS instruments show the reproducibility of the measured Aq-values and the practical abilities of the approach for calibration and performance verification.