bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of innovative digital technologies in transformation of Agricultural and Industrial Complex
Authors: Strizhakova E A , Nazarova Yu N , Zayats O A , Zadorozhneva Yu V , Shumakova R I 
Published: July 2020

Abstract
The conditions of the digital economy development are studied in the article taking into account the application of innovative technologies. The authors considered features and the role of their influence on the digital transformation of the Agricultural and Industrial Complex. The review of the main government programs to intensify the industry development by using digital technologies is presented here.
The assessment of gait features according to the data of a portable acceleration sensor in an intelligent monitoring system
Authors: Dorofeev N V , Grecheneva A V 
Published: July 2020

Abstract
The article is devoted to assessing the possibility of identifying individual characteristics of a person’s gait according to the data of one accelerometric sensor, as well as the possibility of assessing impaired functioning of the musculoskeletal system with subsequent use in intelligent expert systems based on neural network algorithms. The article notes the prospects of using dynamic measurements to improve the effectiveness of orthopedic diagnostics. The prospects of using accelerometry along with complex medical motion capture systems are noted. The results of distinguishing characteristic gait indicators among a group of subjects according to one accelerometer sensor, as well as an assessment of the distribution structure of the articular angle when walking, are described. As subjects, people with impaired functioning of the musculoskeletal system and people without disorders are involved. The results obtained are in good agreement with the data of goniometric control systems built on the basis of several sensors. Thus, the results of the research show the possibility of obtaining a detailed picture of gait. The results obtained will allow us to form a preliminary structure of the neural network and evaluate its coefficients with the further development of automated control and monitoring systems based on existing portable wearable devices (phone, watch).
Development of Telecommunication System Units in Parallel Neural Network Basis
Authors: Smirnov A A , Sakhnyuk P A 
Published: July 2020

Abstract
The article suggests the integration of a neural network as a parallel element base in a telecommunication system. In this case, the ability to learn or adapt to external conditions is applied as the main advantage. For telecommunication systems in conditions when it is possible, this ability will improve noise immunity, reliability, operability, etc. The article considers an example of the integration of a neural network into a discrete matched signal filter. It is noted that the use of parallel mathematical methods in signal processing leads to the maximum effect of increasing the quality parameters of such telecommunication elements.
Simulator of the navigation equipped with LIDAR of the mobile robot based on the neural network
Authors: Faizullin R V 
Published: July 2020

Abstract
The paper considers the issue of using the robot simulators equipped with LIDAR (Light Detection and Ranging). The simulator application allows decreasing the experiment costs, their time and risks or negative aftereffects of accidents, but, at the same time, the simulated environment should identical to the real one. In practice, the simulated environment can have differences and there comes the issue of estimating the robot ability to adapt to new conditions. Neural networks are used to teach the robots, due to which the robots reach the target in the shortest or the fastest way, at the same time, there should be no accident/collision. The initial series represents the multiple time series. To teach the neural networks to control the robots, the paper proposes to introduce the additional index in the form of the minimal distance to the nearest object in the actual time moment. The approach novelty in using the new penalty function for teaching the neural network is the speed index of approaching the nearest object/obstacle. The neural networks were taught on the maps without dynamic objects, but tested in the conditions when several mobile robots were used on the map, thus, they became the dynamic obstacles for each other. The accident risk for robots without the proposed penalty function during testing was 4.5% against 0.3% - with the penalty function.
Anthropomorphic manipulator master-slave teleoperation using 3D depth sensor and color camera
Authors: Petrenko V I , Tebueva F B , Gurchinskiy M M , Svistunov N Yu , Nestulya A K 
Published: July 2020

Abstract
The article proposes a method for anthropomorphic manipulator teleoperation based on data processing using depth and color cameras of the Kinect controller. Processing data with Kinect allows to determine the coordinates of the nodal points of the operator’s body, which, after recalculation, can be used to generate control signals for the manipulator. The article describes the algorithm and the mathematical apparatus for determining the angles of the operator’s arm joints in real time. The proposed method can be used to control the joints of the manipulator of an anthropomorphic robot, and can also be adapted to control manipulators with a kinematic structure different from the structure of human arm, or to implement other control methods such as gesture control.
Cognitive modeling of the development of complex managed systems
Authors: Baidakov A N , Nazarenko A V , Babkina O N 
Published: July 2020

Abstract
The purpose of this research is to form a set of methodological provisions related to the use of cognitive modeling in the management of complex systems in conditions of high dynamism of studied processes. The rapid development of information and analytical tools provides new opportunities for applying cognitive modeling to a wider range of systems. The methodological basis of the study is the system methodology and its direct implementation is based on the system sequence “mission – goal – functions - structure – behavior – result”. Cognitive modeling in the management of complex systems takes into account their hierarchical structure, which entails the hierarchy of the corresponding models, which is directly reflected in the generated models or considered when building local models for systems of a certain hierarchy level. Complex systems also determine the complexity of the models that represent them. Therefore, the paper proposes stratification of the modeling process and its results on five levels: the representation model, the understanding model, the interaction model, the management model and the behavior model. The dynamics of simulated systems and their external environment assumes an iterative (cyclic) nature of cognitive modeling. The paper presents a structural cognitive model of managing the functioning and development of complex systems as its result.
Lattice thermal conductivity of NaCoO2 and LiCoO2 intercalation materials studied by hybrid density functional theory
Authors: Mattila Nina , Karttunen Antti J 
Published: July 2020

Abstract
We have studied the lattice dynamics and lattice thermal conductivity of NaCoO2 intercalation material with first-principles hybrid density functional methods. The lattice thermal conductivity has been obtained using linearized Boltzmann transport theory and the contributions to the lattice thermal conductivity have been analyzed in detail. The results obtained for NaCoO2 have been systematically compared with LiCoO2 to shed light on the effect of the alkali metal atom. The room-temperature in-plane lattice thermal conductivities within relaxation time approximation are 78 Wm−1K−1 and 46 Wm−1K−1 for NaCoO2 and LiCoO2, respectively. The respective room-temperature cross-plane lattice-thermal conductivities are 25.0Wm−1K−1 and 6.6 Wm−1K−1. The predicted lattice thermal conductivities for fully alkali-occupied single crystals are clearly larger in comparison to the experimental values obtained for single-crystal NaCoO2 and polycrystalline LiCoO2. Analysis of the lattice thermal conductivity reveals that the differences between NaCoO2 and LiCoO2 can be explained by significantly shorter phonon lifetimes in LiCoO2.
Impacts of COVID-19 response actions on air quality in China
Authors: Marlier Miriam E , Xing Jia , Zhu Yifang , Wang Shuxiao 
Published: July 2020

Abstract
An outbreak of the novel coronavirus (COVID-19) was first reported in Wuhan, Hubei Province, China in December 2019. In late January 2020, the Chinese government implemented strict quarantine measures across Hubei Province and other parts of the country to limit the transmission of COVID-19. An effect of these quarantine measures was the reduction in economic activity and associated emissions that contribute to air pollution. In this study, we quantify the spatial extent and magnitude of changes in air pollution concentrations across China by comparing complementary satellite, ground-based, and modeled data from the first two months of 2019 and 2020. We find a 48% reduction in satellite-derived average fine particulate matter (PM2.5) concentrations in eastern China during a three-week period after the Lunar New Year (LNY) in 2020 compared to 2019, which follows significant declines in the pre-LNY period. We also observe a 49% and 11% decline in post-LNY satellite tropospheric column concentrations of nitrogen dioxide (NO2) and sulfur dioxide (SO2). These satellite-based results are in general agreement with data collected from ground monitoring stations across the country, which show a decline in post-LNY PM2.5, NO2, and SO2 concentrations. Our modeling analysis suggests that these observed air quality improvements are driven primarily by the reduction in NO2 emissions, which indicate reductions in transportation and industrial pollution sources during COVID-19, but unfavorable meteorological conditions weaken the role of emissions reduction. Finally, we estimate a reduction by 5%, 14%, and 18% of days in the post-LNY period for 2020 that exceed national PM2.5 air quality targets for the entire country, eastern China, and Hubei Province. As more information becomes available on population characteristics and air pollution exposure patterns, this analysis can be extended to quantify human health related impacts to sudden changes in air pollution in China and other locations around the world.
Incidence Correction Factors for Moderate and Severe Acute Child Malnutrition From 2 Longitudinal Cohorts in Mali and Burkina Faso
Authors: Barba Francisco M , Huybregts Lieven , Leroy Jef L 
Published: July 2020

Abstract
Child acute malnutrition (AM) is an important cause of child mortality. Accurately estimating its burden requires cumulative incidence data from longitudinal studies, which are rarely available in low-income settings. In the absence of such data, the AM burden is approximated using prevalence estimates from cross-sectional surveys and the incidence correction factor $K$, obtained from the few available cohorts that measured AM. We estimated $K$ factors for severe acute malnutrition (SAM) and moderate acute malnutrition (MAM) from AM incidence and prevalence using representative cross-sectional baseline and longitudinal data from 2 cluster-randomized controlled trials (Innovative Approaches for the Prevention of Childhood Malnutrition—PROMIS) conducted between 2014 and 2017 in Burkina Faso and Mali. We compared K estimates using complete (weight-for-length z score, mid-upper arm circumference (MUAC), and edema) and partial (MUAC, edema) definitions of SAM and MAM. $K$ estimates for SAM were 9.4 and 5.7 in Burkina Faso and in Mali, respectively; K estimates for MAM were 4.7 in Burkina Faso and 5.1 in Mali. The MUAC and edema–based definition of AM did not lead to different $K$ estimates. Our results suggest that $K$ can be reliably estimated when only MUAC and edema-based data are available. Additional studies, however, are required to confirm this finding in different settings.
Evaluation of Risks of Bias in Addiction Medicine Randomized Controlled Trials
Authors: Wayant Cole , Tritz Daniel , Horn Jarryd , Crow Matt , Vassar Matt 
Published: July 2020

Abstract

Aims
Perhaps the most important step when designing and conducting randomized controlled trials (RCTs) in addiction is to put methodological safeguards in place to minimize the likelihood for bias to affect trial outcomes. In this study, we applied the revised Cochrane risk of bias tool (ROB 2) to RCTs of drug, alcohol or tobacco interventions.

Methods
We searched for trials published in 15 addiction medicine journals over a 7-year period. Our primary endpoint is the risk of bias of included studies. We conducted a sensitivity analysis of publicly funded trials.

Results
Overall, included RCTs were most often at high risk of bias per our judgments (244/487, 50.1%). However, significant proportions of included RCTs were at low risk of bias (123/487, 25.3%) or some concerns for bias (120/497, 24.6%). RCTs with behavioral modification interventions (19/44, 43.2%) and alcohol interventions (80/150, 53.3%) had the highest proportion of high-risk judgments. In a sensitivity analysis of publicly funded RCTs), 195/386 (50.5%) were at high risk of bias.

Conclusions
Approximately half of included drug, alcohol or tobacco RCTs in our sample were judged to be at high risk of bias with the most common reason being a lack of proper blinding or proper description of blinding. Key action items to reduce bias in future addiction RCTs include adequate randomization, blinding and inclusion of a trial registry number and protocol.
Pathogenetic profiling of COVID-19 and SARS-like viruses
Authors: Nain Zulkar , Rana Humayan Kabir , Liò Pietro , Islam Sheikh Mohammed Shariful , Summers Matthew A , Moni Mohammad Ali 
Published: July 2020

AbstractThe novel coronavirus (2019-nCoV) has recently emerged, causing COVID-19 outbreaks and significant societal/global disruption. Importantly, COVID-19 infection resembles SARS-like complications. However, the lack of knowledge about the underlying genetic mechanisms of COVID-19 warrants the development of prospective control measures. In this study, we employed whole-genome alignment and digital DNA–DNA hybridization analyses to assess genomic linkage between 2019-nCoV and other coronaviruses. To understand the pathogenetic behavior of 2019-nCoV, we compared gene expression datasets of viral infections closest to 2019-nCoV with four COVID-19 clinical presentations followed by functional enrichment of shared dysregulated genes. Potential chemical antagonists were also identified using protein–chemical interaction analysis. Based on phylogram analysis, the 2019-nCoV was found genetically closest to SARS-CoVs. In addition, we identified 562 upregulated and 738 downregulated genes (adj. P ≤ 0.05) with SARS-CoV infection. Among the dysregulated genes, SARS-CoV shared ≤19 upregulated and ≤22 downregulated genes with each of different COVID-19 complications. Notably, upregulation of BCL6 and PFKFB3 genes was common to SARS-CoV, pneumonia and severe acute respiratory syndrome, while they shared CRIP2, NSG1 and TNFRSF21 genes in downregulation. Besides, 14 genes were common to different SARS-CoV comorbidities that might influence COVID-19 disease. We also observed similarities in pathways that can lead to COVID-19 and SARS-CoV diseases. Finally, protein–chemical interactions suggest cyclosporine, resveratrol and quercetin as promising drug candidates against COVID-19 as well as other SARS-like viral infections. The pathogenetic analyses, along with identified biomarkers, signaling pathways and chemical antagonists, could prove useful for novel drug development in the fight against the current global 2019-nCoV pandemic.
qSNE: quadratic rate t-SNE optimizer with automatic parameter tuning for large datasets
Authors: Häkkinen Antti , Koiranen Juha , Casado Julia , Kaipio Katja , Lehtonen Oskari , Petrucci Eleonora , Hynninen Johanna , Hietanen Sakari , Carpén Olli , Pasquini Luca , Biffoni Mauro , Lehtonen Rainer , Hautaniemi Sampsa 
Published: July 2020

Abstract

Motivation
Non-parametric dimensionality reduction techniques, such as t-distributed stochastic neighbor embedding (t-SNE), are the most frequently used methods in the exploratory analysis of single-cell datasets. Current implementations scale poorly to massive datasets and often require downsampling or interpolative approximations, which can leave less-frequent populations undiscovered and much information unexploited.

Results
We implemented a fast t-SNE package, qSNE, which uses a quasi-Newton optimizer, allowing quadratic convergence rate and automatic perplexity (level of detail) optimizer. Our results show that these improvements make qSNE significantly faster than regular t-SNE packages and enables full analysis of large datasets, such as mass cytometry data, without downsampling.

Availability and implementation
Source code and documentation are openly available at https://bitbucket.org/anthakki/qsne/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Tick-borne Pathogens Detected in the Blood of Immunosuppressed Norwegian Patients Living in a Tick-endemic Area
Authors: Quarsten Hanne , Salte Tore , Lorentzen Åslaug R , Hansen Inger J W , Hamre Runar , Forselv Kristine J N , Øines Øivind , Wennerås Christine , Noraas Sølvi 
Published: July 2020

Abstract

Background
The knowledge regarding the occurrence and the clinical implications of tick-borne infections in immunosuppressed patients living in tick-endemic areas is limited.

Methods
Adult patients with autoimmune conditions requiring immunosuppressive treatment such as infliximab and rituximab were invited to participate in the study when they attended the hospital for treatment and/or control of the disease. Whole-blood samples were analyzed by real-time polymerase chain reaction for Borrelia burgdorferi sensu lato, Borrelia miyamotoi, Anaplasma phagocytophilum, Rickettsia spp., Candidatus Neoehrlichia mikurensis, and Babesia spp.

Results
The occurrence of tick-borne pathogens in the blood of patients (n = 163) with autoimmune conditions requiring immunosuppressive treatment was evaluated. Pathogen DNA was detected in 8.6% (14/163) of the patients. The predominant pathogen was Ca. Neoehrlichia mikurensis (12/14), which was carried in the blood of infected patients for 10–59 days until treatment with doxycycline. B. burgdorferi s.l. and Rickettsia spp. were detected in 1 patient each. The B. burgdorferi–infected patient presented with fever, whereas the remaining patients were judged to have subclinical infections. B. miyamotoi, A. phagocytophilum, and Babesia spp. were not detected in any patient.

Conclusions
Patients treated with biologicals and living in a tick-endemic area seem to have a high risk of contracting Ca. Neoehrlichia mikurensis infection, which, if left untreated, could result in thromboembolic complications.
FAIR digital objects in environmental and life sciences should comprise workflow operation design data and method information for repeatability of study setups and reproducibility of results
Authors: Harjes Janno , Link Anton , Weibulat Tanja , Triebel Dagmar , Rambold Gerhard 
Published: July 2020

Abstract
Repeatability of study setups and reproducibility of research results by underlying data are major requirements in science. Until now, abstract models for describing the structural logic of studies in environmental sciences are lacking and tools for data management are insufficient. Mandatory for repeatability and reproducibility is the use of sophisticated data management solutions going beyond data file sharing. Particularly, it implies maintenance of coherent data along workflows. Design data concern elements from elementary domains of operations being transformation, measurement and transaction. Operation design elements and method information are specified for each consecutive workflow segment from field to laboratory campaigns. The strict linkage of operation design element values, operation values and objects is essential. For enabling coherence of corresponding objects along consecutive workflow segments, the assignment of unique identifiers and the specification of their relations are mandatory. The abstract model presented here addresses these aspects, and the software DiversityDescriptions (DWB-DD) facilitates the management of thusly connected digital data objects and structures. DWB-DD allows for an individual specification of operation design elements and their linking to objects. Two workflow design use cases, one for DNA barcoding and another for cultivation of fungal isolates, are given. To publish those structured data, standard schema mapping and XML-provision of digital objects are essential. Schemas useful for this mapping include the Ecological Markup Language, the Schema for Meta-omics Data of Collection Objects and the Standard for Structured Descriptive Data. Data pipelines with DWB-DD include the mapping and conversion between schemas and functions for data publishing and archiving according to the Open Archival Information System standard. The setting allows for repeatability of study setups, reproducibility of study results and for supporting work groups to structure and maintain their data from the beginning of a study. The theory of ‘FAIR++’ digital objects is introduced.
Myocarditis in Crohn’s disease: a case report
Authors: McGrath-Cadell Lucy , Bart Nicole K , Lin Linda , Ghaly Simon , Holloway Cameron J 
Published: July 2020

Abstract

Background
Mobile valvular masses are often considered pathognomonic for infective endocarditis. We present a case of a young patient with mobile valvular masses in the context of myocarditis likely secondary to active ileal Crohn’s disease. Cardiac magnetic resonance (CMR) imaging was crucial in diagnosing and monitoring our patient.

Case summary
A 27-year-old woman presented with pleuritic chest pain, dyspnoea, and a 3-day history of fevers. She also reported a 2-month history of intermittent visual loss in her right eye. She had a history of histologically proven ileal Crohn’s disease, diagnosed 5 months prior. She was haemodynamically unstable on presentation. Abnormalities on a transthoracic echocardiogram necessitated a transoesophageal echocardiogram. After blood cultures were sent, the patient was commenced on empirical treatment for infective endocarditis with gentamicin and flucloxacillin. Eight days after her initial presentation, all blood cultures remained negative and she was changed to empirical treatment for culture negative endocarditis with ceftriaxone and vancomycin, according to local protocol. Despite 8 days of treatment for infective endocarditis she remained febrile. A CMR was organized on Day 9 and this showed myocarditis, which changed the treatment paradigm. She responded swiftly to steroids and anti-coagulation.

Discussion
In this case, echo-dense valvular lesions are not pathognomonic for infective endocarditis and a careful diagnostic process involving multi-modality imaging, including CMR, occurred to arrive at a diagnosis of myocarditis likely secondary to Crohn’s disease.