Publications
Timely evaluation of cardioembolic stroke (CES) caused by atrial fibrillation is critical from the point of view of the possibility of prescribing effective secondary prevention with oral anticoagulants. Insular lesion is considered as a promising neuroimaging marker of CES.
Objective: to analyze the role of insular cortex lesions using magnetic resonance imaging (MRI) of the brain as a potential neuroimaging marker of the pathogenetic subtype of ischemic stroke (IS).
Patients and methods. 225 patients in the acute period of IS were examined. Depending on the stroke etiology, patients were divided into three groups: cryptogenic stroke (CS; n=99), CES (n=45), and non-CES (n=81). All patients underwent an MRI of the brain to analyze the insular cortex lesions. In 57 patients, foci of cerebral infarction were additionally marked manually on axial slices of diffusion-weighted MRI using the Anatomist software. The calculated MRI characteristics of foci for CES and non-CES groups were used to construct a decision tree in the WEKA 3.6 package. Echocardiographic markers of atrial cardiopathy were assessed in all patients – the left atrium (LA) emptying fraction and LA function index; in 68 patients, the concentration of serum NT-proBNP was also assessed.
Results and discussion. The insula was affected in 12% of patients: most often in CES (33%), significantly less often in CS and non-CES (6 and 7.4%, respectively), without significant differences between the latter groups. The presence of insula lesion in relation to CES has a sensitivity of 33% and a specificity of 93% (p=0.002); odds ratio 6.25; 95% confidence interval 2.22–17.63. In most patients, the posterior insular cortex was involved in the pathological process. Isolated insular infarction occurred in only one patient with CES, while the involvement of the insula and adjacent zone, and the combination of insular infarction with territorial infarction, were observed more often. The group of patients with insular lesions was distinguished by the predominance of women, greater severity of stroke at admission, less deficit at discharge, larger LA diameter, lower LA emptying fraction, and functional index. CES was four times more common in the insular lesion group, while CS was two times more common in those without insular lesions. Insula involvement identifies three out of five CES patients according to the decision tree. Further analysis of the total lesion volume can locate almost all remaining patients with CES: they are characterized by the indicator >12 sm3.
Conclusion. Insular lesions allow reliable differentiation of patients with CES and non-CES and can be considered a potential marker of the cardioembolic subtype of IS, which requires further investigation.
Currently, there is a trend for companies to participate in Demand Response (DR) market, which requires them to reduce energy consumption during peak hours. Underground mining enterprises (UEM) are energy-intensive and for them participation in such programs is especially relevant. The main consumer of electricity at UEM is the ventilation system, mainly the main fan unit (MFU). The article presents the DR service architecture at UEM, in which the basis for reducing power consumption at a given time is the prediction of the required performance of the MFU. Decrease in MFU performance can be planned (for example, during lowering and lifting of workers along he ventilation shaft) and unplanned. The paper presents the architecture of the DR service and considers the case of a possible unscheduled decrease in the MFU capacity based on the results of modeling the air distribution between the shafts in the digital twin with a predicted change in the parameters of the outside air entering the UEM. In the case of enabling such reduction, the energy management platform will be able to reduce the power consumption at a given time.
This paper considers scientific and applied aspects of algorithmic and software design for cyber-physical systems (CPS) of buildings. A CPS of a building is a basic element of IT architecture within SmartCity approach. It represents a set of devices, which control life support systems integrated into a premise, means of communication, and the computing resources necessary for user services. In a building’s CPS, all equipment and subsystems are combined into a single ecosystem to improve comfort and security, as well as reduce operating costs and resource savings. The paper investigates requirements for building’s CPS software. The groups of design patterns are presented, which in practice significantly reduce the time for programming and configuring the building’s CPS elements and increase interoperability of developed information applications. CPS algorithms are considered in context of Internet of Things.
The need for accurate balancing in electricity markets and a larger integration of renewable sources ofelectricity require accurate forecasts of electricity loads in residential buildings. In this paper, we considerthe problem of short-term (one-day ahead) forecasting of the electricity-load consumption in residentialbuildings. In order to generate such forecasts, historical electricity consumption data are used, presentedin the form of a time series with a fixed time step. Initially, we review standard forecasting methodologiesincluding naive persistence models, auto-regressive-based models (e.g., AR and SARIMA), and the tripleexponential smoothing Holt-Winters (HW) model. We then introduce three forecasting models, namelyi) the Persistence-based Auto-regressive (PAR) model, ii) the Seasonal Persistence-based Regressive (SPR)model, and iii) the Seasonal Persistence-based Neural Network (SPNN) model. Given that the accuracy ofa forecasting model may vary during the year, and the fact that models may differ with respect to theirtraining times, we also investigate different variations of ensemble models (i.e., mixtures of the previ-ously considered models) and adaptive model switching strategies. Finally, we demonstrate through sim-ulations the forecasting accuracy of all considered forecasting models validated on real-world datagenerated from four residential buildings. Through an extensive series of evaluation tests, it is shown thatthe proposed SPR forecasting model can attain approximately a 7% forecast error reduction over standardtechniques (e.g., SARIMA and HW). Furthermore, when models have not been sufficiently trained, ensem-ble models based on a weighted average forecaster can provide approximately a further 4% forecast errorreduction.
This book constitutes the proceedings of the 16th International Conference on Formal Concept Analysis, ICFCA 2021, held in Strasbourg, France, in June/July 2021.
The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 32 submissions. The book also contains four invited contributions in full paper length.
The research part of this volume is divided in five different sections. First, "Theory" contains compiled works that discuss advances on theoretical aspects of FCA. Second, the section "Rules" consists of contributions devoted to implications and association rules. The third section "Methods and Applications" is composed of results that are concerned with new algorithms and their applications. "Exploration and Visualization" introduces different approaches to data exploration.
Background and Purpose Despite the continuing efforts in multimodal assessment of the motor system after stroke, conclusive findings on the complementarity of functional and structural metrics of the corticospinal tract (CST) integrity and the role of the contralesional hemisphere are still missing. The aim of this work was to find the best combination of the motor system parameters, allowing classification of patients into three predefined groups of upper limb motor recovery.
Methods 35 chronic ischemic stroke patients (47 [26–66] y.o., 29 [6–58] months post-stroke) with only supratentorial lesion and unilateral upper extremity weakness were enrolled. Patients were divided into three groups depending on the upper limb motor recovery. Non-parametric statistical tests and regression analysis were used to investigate the relationships among structural and functional motor system parameters, probed by diffusion tensor imaging (DTI) and transcranial magnetic stimulation (TMS). In addition, stratification rules were tested, using a decision tree classifier to identify parameters explaining motor recovery.
Results Fractional anisotropy (FA) ratio in the internal capsule (IC) and absence/presence of motor evoked potentials (MEPs), were equally discriminative of the worst motor outcome group (96% accuracy). MEP presence diverged for two investigated hand muscles. Concurrently, for the three recovery groups’ classification, the best parameter combination was: IC FA ratio and Fréchet distance between the contralesional and ipsilesional CST FA profiles (91% accuracy). No other metrics had any additional value for patients’ classification.
Conclusions This study demonstrates that IC FA ratio and MEPs absence are equally important markers for poor recovery. Importantly, we found that MEPs should be controlled in more than one hand muscle. Finally, we show that better separation between different motor recovery groups may be achieved when considering the whole CST FA profile.
This paper examines people's willingness to separate collection of plastic waste. The study is based on a questionnaire survey of Perm residents and visitors, the data were analyzed using econometric methods. We identified key factors that determine the ecological behavior of people - the importance for a person of the benefits that he carries for the environment, the willingness to devote personal time to measures to protect it and awareness of the environmental harm of plastic waste. On average, all things being equal, an individual's awareness of the environmental hazards of plastic leads to increase the probability of his participation in the separate collection of plastic by 11.78%. On average, all things being equal, the proximity of containers for separate collection of plastic waste increases the probability that a person will participate in the separate collection of plastic by 45.57%. It should be noted that the probability of participation in a separate collection is lower for men than for women, all things being equal. Also, all things being equal, the probability of participation in the separate collection of plastic increases with age by 0.3%.
The paper presents the results of the data analysis conducted at Bereznyaki Mine-2 of Uralkali in summer and winter (during the air pre-treatment period). The findings show that when mine air heaters are operating thermal drop of ventilation pressure appears in air supply shafts. It causes “airlocks” in the shafts – a phenomenon that nearly stops the airflow in one of the shafts while increasing dramatically the airflow in the other (others) air intake shafts. As a result, mine air heaters in the shafts may stop running which provokes freezing of the mine shaft shoring. The analysis of mine ventilation modes performed in summer and winter determined the factors affecting the occurrence of “airlocks” in the air supply shafts during air pre-treatment.
The article considers the architecture of the ventilation control system for underground mining enterprises, equipped with a digital twin with online functions such as simulation modeling and predictive analytics. The system is focused on the main fan unit (MFU) control taking into account changing parameters of external air supplied to mine shafts. In contrast to the existing ones, the proposed method of control takes into account the influence of these parameters on changes in the total volume of natural draught, on which the total volume of air supplied to the mine (mine) depends. It is known that ventilation systems of such enterprises consume from 30 to 50% of all electricity consumed for the mining process. In this regard, the proposed control models can be used to optimize energy costs and energy savings in ventilation. The Internet of things (IoT) InfluxData of stack TICK is offered for the realization. The offered architecture of cyber-physical system (CPS) consists of four subsystems: physical object subsystem, network and computing infrastructure IoT, digital twin, user interface. Architecture of CPS provides data processing from energy meters, control controllers and sensors of air environment parameters, implemented in blocks of on-line and off-line calculations. The digital twin of the ventilation system is made with the use of a time series database and a database of attributes that store information on changes in equipment parameters by time, air indicators, performance indicators, statistics on accidents and fan runtime, CPS characteristics, etc. CPS of the given architecture means connection of additional data sources, providing calculations of rational volumes of air delivery taking into account safety norms and requirements of energy efficiency.
Studies over the past decade demonstrate the high potential of diff usion-weighted MRI (dMRI) as a modern technique for non-invasive quantitative assessment of the microstructural integrity of the white matter of the brain, which allows predicting some aspects of the rehabilitation potential. Purpose of the study: to calculate the threshold values of fractional anisotropy (FA) of some cerebral tracts, which are informative in determining various aspects of the rehabilitation potential in the acute period of ischemic stroke. Patients and methods. We examined 100 patients with ischemic stroke and 10 persons without stroke and cognitive impairment. All patients underwent dMRI and clinical assessment of indicators of rehabilitation potential at discharge. Results. The NIHSS at discharge is associated with the size of infarction, the FA of the anterior, posterior leg and knee of the internal capsule, the superior longitudinal, cingular and inferior fronto-occipital bundles. Similar associations were noted for the Rivermead mobility index and the Rankin scale. The function of the hand according to the Frenchay scale is associated with the size of the lesion, FA of the anterior leg of the internal capsule, superior longitudinal, inferior fronto-occipital and cingular bundles. The MoCA is interrelated only with the size of the infarction and the FA of the anterior leg of the internal capsule, the Berg scale — with the size of the lesion and the FA of the upper longitudinal bundle, the FIM scale — with the FA of the upper longitudinal, inferior fronto-occipital and cingular bundles. The threshold values of FA of the cerebral tracts which are most informative in determining various aspects of the rehabilitation potential in the acute period of ischemic stroke were determined. Conclusion. The quantitative assessment of the FA of the main projection and associative tracts is informative in relation to the determination of the rehabilitation potential in the acute period of ischemic stroke.
Research considers the task of developing analytical software for IoT platforms with the purpose of subsequent creation of energy consumption control devices and systems on their basis on the example of HVAC with dynamic optimization. The analysis of platform technologies used to create energy consumption control solutions is presented; classes of horizontally-oriented and vertically-oriented platforms are highlighted and characterized. Analysis of the platforms allowed to identify the requirements for the functions and to construct a multi-layered architecture of the target vertically-oriented IoT platform, most suitable for the development of the system of dynamic optimization of the energy management process of HVAC. The problem statement of dynamic energy consumption control on the example of ventilation and the strategy of approximation of energy cost function by means of predictive models is presented. The activity of the proposed analytical models in HVAC control loops is illustrated in a time diagram. The use of the model as a service is proposed to dynamically optimize energy consumption and consequently energy costs The publication was prepared within the framework of the Academic Fund Program at the HSE University in 2020 – 2021 (grant № 21-04-039).
Due to economic instability there has been an increase in demand for unallocated metal accounts offered by Russian commercial banks since April 2020. Although opening unallocated metal accounts gives banks an opportunity to expand the range of their products, diversify income, attract new clients and retain old ones, most Russian banks do not provide such services. For those, it is important to understand the determinants of bid-ask spreads (the difference between the quoted metal bid and ask prices), since the demand for unallocated metal accounts and the bank’s income from this service depend on the bid-ask spread. The purpose of this paper is to investigate the main determinants of quoted bid-ask spreads on unallocated metal accounts in commercial banks. Multiple regression models are applied for the period from October 2017 to May 2020. There are very few articles on the determinants of quoted bid-ask spreads on unallocated metal accounts; for this reason the paper is based on the results of studies of bid-ask spreads in other markets. Based on recent theoretical results, which indicate that bid-ask spreads depend on price volatility, we confirm this hypothesis on unallocated metal accounts. Moreover, we reveal that banks’ assets and the share of state participation influence bid-ask spreads on unallocated metal accounts in commercial banks. It is also proven that bid-ask spreads for unallocated metal accounts in gold are, on average, lower than those for palladium, platinum and silver.
The development of application software for cyber-physical systems of buildings involves the widespread use of Internet of Things (IoT) integration platforms. In practice, the flexible functionality of IoT platforms often leads to additional costs for software enhancement of existing and connection of new units, in particular digital twins. The paper proposes a technological solution for the implementation of a digital twin of the ventilation process in the IoT control loop of heating, ventilation and air conditioning (HVAC) systems for buildings and industrial facilities. The implementation and execution of the digital twin in the form of a dynamic simulation model in the object-oriented modelling language Modelica in the OpenModelica environment is considered. The IoT platform InfluxData, based on the TICK stack, is considered as an example of an integration environment. It is a horizontally-oriented IoT platform that contains the mechanism for collecting data from devices and the InfluxDB time-series database for storing metrics. To integrate simulation models on Modelica with InfluxDB, an OMPython server is proposed. In this case, the integration scripts are executed in the Python language, which as a result extends the traditional capabilities of the IoT platform significantly to the level of a digitally twinned control system. This HVAC control involves adapting control loops by taking into account the dynamics of the air distribution process over the ventilation network, evaluating and compensating for process inertia. The publication was prepared within the framework of the Academic Fund Program at the HSE University in 2020–2021 (grant № 21-04-039).
Background
In patients with psychotic disorders, sleep spindles are reduced, supporting the hypothesis that the thalamus and glutamate receptors play a crucial etio-pathophysiological role, whose underlying mechanisms remain unknown. We hypothesized that a reduced function of NMDA receptors is involved in the spindle deficit observed in schizophrenia.
Methods
An electrophysiological multisite cell-to-network exploration was used to investigate, in pentobarbital-sedated rats, the effects of a single psychotomimetic dose of the NMDA glutamate receptor antagonist ketamine in the sensorimotor and associative/cognitive thalamocortical (TC) systems.
Results
Under the control condition, spontaneously-occurring spindles (intra-frequency: 10–16 waves/s) and delta-frequency (1–4 Hz) oscillations were recorded in the frontoparietal cortical EEG, in thalamic extracellular recordings, in dual juxtacellularly recorded GABAergic thalamic reticular nucleus (TRN) and glutamatergic TC neurons, and in intracellularly recorded TC neurons. The TRN cells rhythmically exhibited robust high-frequency bursts of action potentials (7 to 15 APs at 200–700 Hz). A single administration of low-dose ketamine fleetingly reduced TC spindles and delta oscillations, amplified ongoing gamma-(30–80 Hz) and higher-frequency oscillations, and switched the firing pattern of both TC and TRN neurons from a burst mode to a single AP mode. Furthermore, ketamine strengthened the gamma-frequency band TRN-TC connectivity. The antipsychotic clozapine consistently prevented the ketamine effects on spindles, delta- and gamma−/higher-frequency TC oscillations.
Conclusion
The present findings support the hypothesis that NMDA receptor hypofunction is involved in the reduction in sleep spindles and delta oscillations. The ketamine-induced swift conversion of ongoing TC-TRN activities may have involved at least both the ascending reticular activating system and the corticothalamic pathway.
In this work we analyze the business attractiveness of cities from the franchise point of view. We select factors that theoretically influence attractiveness of the city in terms and show how to estimate them. We suggest some classical machine learning algorithms (ordinary least squares regression, elastic net, support vector regression, and random forest). We show results of empirical study and discuss what factors are the most important in the case.