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Real-time, accurate, and robust localisation is critical for autonomous vehicles (AVs) to achieve safe, efficient driving, whilst real-time performance is essential for AVs to achieve their current position in time for decision making. To date, no review paper has quantitatively compared the real-time performance between different localisation techniques based on various hardware platforms and programming languages and analysed the relations among localisation methodologies, real-time performance and accuracy. Therefore, this paper discusses state-of-the-art localisation techniques and analyses their localisation performance in AV application. For further analysis, this paper firstly proposes a localisation algorithm operations capability (LAOC)-based equivalent comparison method to compare the relative computational complexity of different localisation techniques; then, it comprehensively discusses the relations among methodologies, computational complexity, and accuracy. Analysis results show that the computational complexity of localisation approaches differs by a maximum of about 〖10〗^7 times, whilst accuracy varies by about 100 times. Vision- and multi-sensor fusion-based localisation techniques have about 2–5 times potential for improving accuracy compared with lidar-based localisation. Lidar- and vision-based localisation can reduce computational complexity by improving image registration method efficiency. Multi-sensor fusionbased localisation can achieve better real-time performance compared with lidar- and vision-based localisation because each standalone sensor does not need to develop a complex algorithm to achieve its best localisation potential. Vehicle-to-everything (V2X) technology can improve positioning robustness. Finally, results show that the fusion technique combined with V2X has considerable potential for achieving a cost-efficient localisation solution for AVs.

Inspired by allosteric regulation of natural molecules, we present a rational design scheme to build synthetic nucleic acid allosteric nanodevices. The clearly specified conformational states of switches obtained from systematic screening and analyses make the ON-OFF transition clear-cut and quantification ready. Under the rational design scheme, we have developed a series of DNA switches with triplex-forming oligos as allosteric modulators and implemented designated allosteric transitions, allosteric coregulation, and reaction pathway control. In conjunction with toehold-mediated strand displacement, our design scheme has also been applied to synthetic nucleic acid computing including a set of logic operations and complex algorithm.

In this letter, we consider a problem of throughput optimum channel switching for channel access by a secondary user in multichannel Cognitive Radio Networks in which there is a delay involved in switching from one channel to another. We consider an imperfect sensing model that takes into account false alarm and detection probabilities. We show that the problem can be posed in the framework of Partially Observable Markov Decision Process (POMDP), and obtain an average throughput optimal policy for which we provide structural results. Also, we propose a low complex algorithm ASTUTE for channel access based on one stage reward. We compare the performance of the optimum policy with ASTUTE . Our results show that the average throughput performance of ASTUTE is very close to that of the optimal solution.

The aim of the work was to justify the algorithm of outpatient drug therapy in patients with COVID-19, based on the principle of «Multi-hit» Approach. The algorithm is based on the published results of clinical studies and observations, authors’ own practical experience in the use and management of more than 4 thousand patients diagnosed with COVID-19 of varying severity during the 2020 pandemic. The article substantiates a complex algorithm for the treatment of outpatients with COVID-19, which includes etiotropic, pathogenetic, and symptomatic components of therapy with different mechanisms of action. The described approach is the 1st stage (outpatient) of a complex algorithm for managing patients with COVID-19. It has been successfully implemented in the system of outpatient care for patients with novel coronavirus infections in several leading medical institutions in Russia. The authors believe that the developed algorithm for providing outpatient drug therapy for COVID-19, based on the principle of multiple exposure, may be useful in real clinical practice of managing patients with coronavirus infection.

We present a simple greedy algorithm to construct the prefer-same de Bruijn sequence and prove that it is equivalent to the more complex algorithm first stated by Eldert et al. without proof (Eldert et al., 1958 [3] ), and later by Fredricksen (Fredricksen, 1982 [5] ). Then we prove that the resulting sequence has the lexicographically largest run-length representation among all de Bruijn sequences. Furthermore, we prove that the sequence resulting from a prefer-opposite greedy construction has the lexicographically smallest run-length representation among all de Bruijn sequences.

Recommendation: In the treatment of progressive collapsing foot deformity (PCFD), the combination of bone shape, soft tissue failure, and host factors create a complex algorithm that may confound choices for operative treatment. Realignment and balancing are primary goals. There was consensus that preservation of joint motion is preferred when possible. This choice needs to be balanced with the need for performing joint-sacrificing procedures such as fusions to obtain and maintain correction. In addition, a patient’s age and health status such as body mass index is important to consider. Although preservation of motion is important, it is secondary to a stable and properly aligned foot. Level of Evidence: Level V, consensus, expert opinion.

The life cycle of most complex engineering systems is greatly a function of maintenance. Generally, most maintenance operation usually requires the removal of failed part. Disassembly sequence planning is an optimization program that seeks to identify the optimal sequence for the removal of the failed part. Most studies in this area usually, use single constraint matrix while implementing varied complex algorithm to identify the optimal sequence that saves time associated with carrying out maintenance operation. The used of single constraint matrix typically has the drawback of computer higher storage requirement as well as time consumption. To address this problem, this study proposes Multi-Level Constraint Matrix Ant Colony Algorithm (MLCMACA). MLCMACA efficiency was validated using complex aircraft landing gear systems in comparison with genetic algorithms. The result shows MLCMACA superior performance from the perspective of reduced search time and faster tracking of optimal disassembly sequence. Hence is recommended for handling of disassembly sequence planning problems.

Lung cancer is a major global public health problem, yet the disease is highly stigmatized, which impairs the opportunities to get optimal treatment for these patients. Globally, as well as locally in Mexico, lung cancer is the main cause of cancer-related deaths. Despite this, it is the only one among the five deadliest cancers in Mexico which is not covered by Popular Health Insurance. Lung cancer treatment is a complex algorithm, which requires fully trained personnel to assess each patient in order to determine standard-of-care therapy based on several factors associated with the molecular profile of the tumor, as well as patient characteristics and their financial capabilities. Coupled to this, in the recent decade, several breakthrough therapies have been launched, shifting the outlook for certain patient subgroups. However, none of these novel therapies are currently available to patients who have public-based health insurance. In this paper, we review the inequities present in the Mexican health system and highlight the importance of addressing these opportunities.El cáncer de pulmón es un problema de salud pública a nivel global. Sin embargo, la enfermedad conlleva un gran nivel de estigma que disminuye las posibilidades de obtener un tratamiento óptimo para estos pacientes. El cáncer de pulmón es la causa principal de muertes relacionadas con cáncer, tanto en el mundo como localmente en México. A pesar de esto, en la lista de las cinco neoplasias con mayor mortalidad en México, el cáncer de pulmón es la única que no se encuentra cubierta por parte del Seguro Popular. El tratamiento del cáncer de pulmón es un algoritmo complejo, el cual requiere personal altamente calificado para la valoración de cada paciente y la determinación del estándar-de-cuidado, dependiendo de varios factores relacionados tanto con el perfil molecular del tumor como con las características del paciente y sus posibilidades económicas. Aunado a esto, en la década en curso ha surgido una gran cantidad de nuevas posibilidades terapéuticas que cambian el pronóstico de ciertos subgrupos de pacientes. Sin embargo, estas terapias no están disponibles para pacientes que se encuentran asegurados por parte del sistema público de salud en México. En este trabajo se revisaron las inequidades que se presentan en el sistema de salud en México y se recalcó la importancia de actuar sobre estas áreas de oportunidad.

Background: fever of unknown origin is one of the diagnoses more difficult in our area, because it involves monitoring of a complex algorithm of several procedures to establish its cause and con frequently takes too long before any explanation. Therefore, the objective is to get to your diagnosis etiologic and to do a particular series of steps.Objective: to describe the most frequent causes of classical fever of unknown origin in the hospital setting and make a simplified diagnostic search algorithm for this pathology.Methods: a case-series study of 85 patients admitted to the Hospital Obispo Polanco with a diagnosis of fever of unknown origin conducted from 2013 to 2018 in the therapeutic services except for pediatrics and surgery units. The study variables included age, sex, complementary studies (variables from humoral, microbiological and biopsies), results obtained, diagnosis of each patient, treatment.Results: of all patients, 23 (27 %) had infections, of which 14 (16 %) of respiratory focus, 6 (7 %) of urinary focus, 2 (2 %) of abdominal focus and 1 (1 %) of the skin focus. Seven patients (8 %) had neoplasms, three of which (3 %) of respiratory origin, three of digestive tract (3 %) and one of prostatic origin (1 %). In four patients (5 %) were diagnosed of the rheumatic diseases. In 51 (60 %) patients not be could diagnose any cause of fever of unknown origin.Conclusions: the first cause of fever of unknown origin is diseases of unknown etiology with 60 % (51 cases) without being able to identify the clear focus. Among the known etiologies, the most private pathology is infectious bacterial diseases of the respiratory and urinary tracts (27 % — 23 patients). The third place is occupied by oncological diseases with a predominance of malignant pulmonary neoplasms (8 % — 7 patients). Rheumatological diseases occupy the last place and, in this study, accounted for only 5 % (4 patients).

The non-linear complex algorithm is applied to the nuclear security where the non-zero sum quantifications of the game theory is applied for simulations. In the results, the values are described as the integers, because the Boolean values are calculated in the modeling. There are several interested factors as Nuclear Fuel, Safety System, Security System, Operator, and Government. In the simulations, the positive values show the possibility of terror incidents which are obtained as dynamical manner in the Boolean numbers of 1.0 or −1.0. The cumulative values show the five nuclear security factors are summed up. For the aging effect, the graph gives the highest value as 18 at 715th month. The analysis of payoff graph shows the result of the payoff of each factor where there are meeting points around 360th month and 450th month. Therefore, the possibility of the terrorism increases as time goes on.

The article presents a complex algorithm for digital image segmentation and classification of visual objects. The classification of segmentation methods is given and the principles of clustering are revealed. It is noted that the main method of data clustering can be divided into hierarchical and sectional clustering, edge segmentation classification is edge-based segmentation, this type of segmentation usually uses edge detection or edge concept. The principles of implementation of the segmentation algorithm by region / region are determined. It is emphasized that the basis of the segmentation algorithm by region / area is the assumption that neighboring pixels within one area have a similar value, the general procedure is to compare one pixel with neighbors. It is emphasized that if the similarity criterion is met, the pixel can be set as belonging to the cluster as one or more of its neighbors, the choice of similarity criterion is important, and the results are affected by the presence of noise. The types of segmentation algorithm by region / region are described the algorithm of growing region and block segmentation. It is noted that the first performs image segmentation by examining adjacent pixels of a set of points and determines whether pixels could be classified into a cluster of the main point or not, and the second is analogous to the first with the difference that there is no need to select point criteria, points are generated automatically. The stages of algorithms for implementing each of the described approaches to segmentation and their advantages and disadvantages are presented. A complex algorithm of digital image segmentation is formed, which is presented in the form of a block diagram. It is emphasized that an alternative approach to improving the accuracy of recognition is to use information about the structure of relationships between categories of regions / objects. The directions of further researches which are based on software development of complex algorithm are outlined.

This paper attempts to find the best-suited model for real-time sentiment analysis of tweets. A lot of research is being done on Twitter data and sentiment analysis, but all of them analyze the pre-existing datasets. This causes many problems as Twitter data is mostly dependent on time, location, topic, trends, etc., and the same trained model cannot be used for real-time analysis. Another problem is that a complex algorithm will take a lot of time, and some tweets can be missed. For example, we need to create a model to track tweets to predict terrorist attacks. A model like this should be fast so that we do not miss even a single tweet. Many other factors like traffic and the language of the tweet should also be kept in mind. This type of model cannot be trained on pre-existing datasets. In this paper, tweets are extracted from Twitter in real time and stored in a dataset. Feature extraction and NLP models are applied to the data, and then, machine learning models are run through the data. Support vector machine with bag of words provided the best results, whereas logistic regression with bag of words was the fastest.

The paper aims to present the reconstructive surgical approach in the case of a patient with complex soft tissue lesions of the calf. The patient was the victim of a road accident resulting in the fracture of the right tibia for which screw-plate osteosynthesis was performed. The chosen therapeutic solution was represented by covering the soft tissue defects using a complex algorithm that involved the use of a reverse sural flap associated with a medial hemisoleus muscle flap and a split-thickness skin graft. Considering functional recovery and the degree of patient satisfaction, the result of the therapeutic conduct was appreciated as very good. The association of the reverse sural flap with the medial hemisoleus flap can be a solution for solving complex cases with multiple soft tissue defects located in the middle and lower third of the calf.

Multi-reservoir systems exploitation is known as one of the most important problems in optimizing water resources. The present study aims to improve the differential evolution (DE) algorithm, promoting the contraction performance and reflection operators, by merging in the shuffled complex evolutionary (SCE). In order to use the SCE algorithm for complex water resource problems, SCE-DE algorithm was developed as well. The performed algorithm was evaluated by solving a difficult mathematical function problem using SCE and SCE-DE methods as a benchmark. The results illustrate that SCE-DE method represents a higher speed in converging to the optimum response and is closer to the absolute optimum. Moreover, the mentioned algorithms were performed for solving the optimization problems of multi-reservoir systems, and the obtained results were compared with the LP absolute response. The obtained data represent a difference of 0.009% between the response of objective function in the SCE-DE method and the LP response. However, the response of objective function of SCE differs 1.84% from that of the LP. Comparing the present observations and the other studies, the proposed algorithm has revealed a much closer optimum response to the LP response. Therefore, we recommend SCE-DE for solving complex problem of water resources.

The complexity and intensity of reforms over several decades in the United States of America led to large-scale systemic reform and shifted superintendent roles from emphasis on management tasks to pivotal actions in the complex algorithm for managing and leading change initiatives. National commissions, task force reports, and nationwide research on the American superintendency informed need for changes in school-district leadership. This article provides a scholarly and objective analysis of issues surrounding five roles superintendents assume and the emergent need for district-level team leadership to address successfully diverse and complex challenges in contemporary education.

In order to mitigate the adverse impacts of climate change, adaptive operating rules (AOR) are generally derived using an ensemble of General Circulation Models (GCMs). Up to date, most of related literatures only focus on one fold of the following issues concerning the derivation of AOR using the GCMs ensemble, including: (1) consideration of different scenario weighing methods, or (2) analysis of different positions to locate scenario weights. And less concern is given to the latter compared with the former. However, few studies identify the relationship between (1) and (2) in the derivation of AOR based on the GCMs ensemble. In this study, we attempt to investigate where to use Equal and REA scenario weights in the derivation of reservoir operating rules under climate change. Equal weights (EW) and unequal weights based on the reliability ensemble average (REA) method are used in two positions: (I) the optimization objective of the reservoir operation model, which is to maximize the weighted average hydropower generation for all future scenarios; and (II) the incorporation of GCMs ensemble climate projections into the weighted climate conditions, and then it is input into the reservoir operation model with the objective of maximizing annual hydropower generation. Four AORs, including EW-AOR(I), REA-AOR(I), EW-AOR(II) and REA-AOR(II), are derived, and their optimized parameters are obtained by the simulation-based optimization (SBO) method with the Complex algorithm. The case study in the Jinxi Reservoir in China indicates that REA-AOR(I) outperforms the other three operation schemes, and EW-AOR(II) performs better than REA-AOR(II). Therefore, equal weights are preferably used to incorporate climate conditions, while unequal weights based on REA method can improve the performance of the reservoir operation model. Generally, REA-AOR(I) and EW-AOR(II) are suggested for adaptive reservoir management under climate change.

International audience; In this paper, we study the advice complexity of the online bin packing problem. In this well-studied setting, the online algorithm is supplemented with some additional information concerning the input. We improve upon both known upper and lower bounds of online algorithms for this problem. On the positive side, we first provide a relatively simple algorithm that achieves a competitive ratio arbitrarily close to 1.5, using constant-size advice. Our result implies that 16 bits of advice suffice to obtain a competitive ratio better than any online algorithm without advice, thus improving the previously known bound of O(log(n)) bits required to attain this performance. In addition, we introduce a more complex algorithm that still requires only constant-size advice, and which is below 1.5-competitive, namely has competitive ratio arbitrarily close to 1.47012. This is the currently best performance of any online bin packing algorithm with sublinear advice. On the negative side, we extend a construction due to Boyar et al. [10] so as to show that no online algorithm with sub-linear advice can be 7/6-competitive, which improves upon the known lower bound of 9/8.

The examination and complex treatment of 86 patients with phlegmon of the parotid-chewing area were carried out. Based on clinical data, modern laboratory and instrumental (invasive measurement of tissue pressure), significant prognostic criteria were revealed, an algorithm for evaluating the effectiveness of treatment was developed. Adequate choice of classification characteristics, as well as further application of differential treatment tactics in the patients of the main group of observations, further confirmed that the individual substantiation of the therapeutic algorithm allows to improve the results of treatment. Obtained 90.9% good results of treatment of patients with phlegmon of parotid-chewing area, with 6.8% of satisfactory outcomes and only 2.3% of unsatisfactory results, allow to recommend the developed technologies protected by 2 patents of the Russian Federation in clinical practice.

Introduction. In the process of determining the value of real estate, the analysis of the real estate market is often purely formal. We have to admit the absence of a fully-fledged section on the analysis of the real estate market in the national standards, as well as the lack of awareness of many appraisers with the conceptual foundations of this methodology. Such situation caused the fact that the section of evaluation report on the market analysis is not organized as part of the research algorithm; consequently, it is not connected with other sections and the report in general. The cost is calculated by one or several standard approaches: cost, revenue, comparative. As a result of coordinating the evaluation results obtained by different methodological approaches, only one digital value is obtained. On its basis, it is necessary to draw conclusions about the value of the object of valuation in the market, its investment attractiveness, and the efficiency of its management system. Purpose. The article aims to develop theoretical and methodological provisions and practical recommendations for constructing a model of market pricing. Results. The differences between individual and mass valuation of real estate have been determined. The essence of the methodology of constructing a model of market pricing has been revealed. A complex algorithm for constructing a model of market pricing has been developed.

This study proposes a novel approach, namely, skin flow complex algorithm (SFCA), to decompose the molecular skin surface into topological disks. The main contributions of SFCA include providing a simple decomposition and fast calculation of the molecular skin surface. Unlike most existing works which partition the molecular skin surface into sphere and hyperboloid patches, SFCA partitions the molecular skin surface into triangular quadratic patches and rectangular quadratic patches. Each quadratic patch is proven to be a topological disk and rendered by a rational Bézier patch. The skin surface is constructed by assembling all rational Bézier patches. Experimental results show that the SFCA is more efficient than most existing algorithms, and produces a triangulation of molecular skin surface which is decomposable, deformable, smooth, watertight and feature-preserved.

The main goal of the paper was to develop algorithms and methods for computation of basic sums, the mathematical objects of great importance in computational materials science having applications to description of the representative volume element (RVE) and to the effective properties of 2D composites. The previously used algorithm had the exponential complexity. We propose a linearly complex algorithm. All the presented algorithms can be easily implemented in modern scientific computing packages, while maintaining both efficient calculations and a high level of abstraction. The proposed approach is applied to derivation of a polynomial approximation of the effective conductivity formula for 2D random material with non-overlapping circular inclusions with normally distributed radii. The obtained formulas are applied to the optimal packing problem of disks on the plane.

Background: Cancer care delivered in an academic setting or by providers with higher volume has been associated with improved overall survival (OS) in selected surgical and medical scenarios, including the care of patients with multiple myeloma (MM). Most studies have limited their focus to OS, and have used a simple count of similar patients as a proxy measure for disease-specific expertise. Few studies have assessed whether treatment by an oncologist that specializes in a specific patient's cancer results in better quality care and outcomes. This latter focus may be particularly important for MM management, for which the approval of newer immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs), coupled with 1st-line PI-IMiD combinations, stem cell transplant (SCT) & maintenance therapy (MT) among fit patients, have expanded options, complexity and therapy lines. In this study, we constructed a measure reflecting oncologist sub-specialization in treatment of hematologic malignancies and examined associations between that dimension, academic care setting, and various aspects of active MM therapy as well as OS. Methods: We selected adults with a MM diagnosis between 07/07-12/15 from the SEER-Medicare linked database. We required continuous Medicare Parts A and B enrollment and no HMO/PPO coverage from 12 months prior to diagnosis (1 month prior for Part D) through death or end of study (12/16) and MM therapy initiation w/in 12 months post diagnosis. Outcomes including 1st treatment line PI-IMiD combination, SCT, MT, and 2nd, 3rd, and 4th treatment lines were constructed by applying a complex algorithm to claims-based indicators for oral and IV drugs and receipt dates. Provider setting was assigned as academic and/or NCI designated cancer center (NCI-CC), other hospital (other teaching or non-teaching), or community (non-hospital), based on claims from the most recent hematologist or oncologist evaluation and management visit prior to 1st line initiation. The percentage of each oncologist's patient panel diagnosed with a hematologic malignancy (HEME%) was calculated for each 3-year period, using a pooled sample of 11 major cancer sites (reported in SEER-Medicare) for the denominator; HEME% was linked back to each patient based on the oncologist of record at the visit prior to 1st line initiation. Bivariate analyses and multivariable regressions tested for associations with treatment (logistic regression) and OS (Cox proportional hazards models). Regressions controlled for demographics, health status, and diagnosis year. Results: The cohort (n=4932) was 14% Black, and 51% age ≥75 years [Table 1]. Care setting was 14.5% academic/NCI-CC, 22.4% other hospital, and 63.0% community; community setting decreased from 72.4 to 57.8% during the observation period (2007 to 2015). Mean HEME% (31% overall) was higher for academic/NCI-CC (51%), where there was a bimodal distribution with peaks at 25% and 85-90% (Figure 1). Mean HEME% was 27% at both other hospital and community practices, with a peak at 25%. 1st treatment line PI-IMiD combinations, MT after PI-IMiD, and SCT were received by 21%, 53%, and 4%, respectively. 2nd, 3rd, and 4th treatment lines were received by 55%, 31% and 18% respectively. After adjustment, higher HEME% was associated with increased likelihood of receiving a PI-IMiD combination and SCT during 1st line, receiving 3rd line (all at p Conclusion: Using a novel measure of oncologist sub-specialization in hematologic malignancies, we found strong positive associations with receipt of 1st line PI-IMiD combination therapy and ongoing treatment lines in a Medicare insured population with MM. In contrast to HEME%, care setting was less likely to be associated with treatment in our multivariable models. The bimodal distribution of HEME% within academic centers is consistent with academic acquisition of community oncology practices. Future research should consider the role of oncologist sub-specialization in other cancers and with additional outcomes, including patient care experience and cost of care. Disclosures Davidoff: Amgen: Consultancy; AbbVie: Consultancy; Celgene: Research Funding. Neparidze:Janssen: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other: Diagnostic committee member ; Sanofi: Membership on an entity's Board of Directors or advisory committees, Other: Advisory board; GlaxoSmithKline: Research Funding. Podoltsev:Jazz Pharmaceuticals: Research Funding; Sunesis Pharmaceuticals: Research Funding; Astex Pharmaceuticals: Research Funding; Samus Therapeutics: Research Funding; AI Therapeutics: Research Funding; Genentech: Research Funding; Arog Pharmaceuticals: Research Funding; Kartos Therapeutics: Research Funding; Incyte: Consultancy, Honoraria; Blueprint Medicines: Consultancy, Honoraria; Agios Pharmaceuticals: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Alexion: Consultancy, Honoraria; Daiichi Sankyo: Research Funding; Astellas Pharma: Research Funding; Boehringer Ingelheim: Research Funding; CTI biopharma: Consultancy, Honoraria, Research Funding; Bristol-Myers Squib: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria. Wang:Celgene/BMS: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Zeidan:Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Acceleron: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Cardinal Health: Consultancy, Honoraria; Taiho: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; BeyondSpring: Consultancy, Honoraria; Cardiff Oncology: Consultancy, Honoraria, Other; Takeda: Consultancy, Honoraria, Research Funding; Ionis: Consultancy, Honoraria; Epizyme: Consultancy, Honoraria; Leukemia and Lymphoma Society: Other; CCITLA: Other; Astex: Research Funding; MedImmune/Astrazeneca: Research Funding; Trovagene: Consultancy, Honoraria, Research Funding; Aprea: Research Funding; Agios: Consultancy, Honoraria; ADC Therapeutics: Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Celgene / BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Otsuka: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding. Huntington:DTRM: Research Funding; Novartis: Consultancy; AbbVie: Consultancy; Astrazeneca: Honoraria; Bayer: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Genentech: Consultancy; Pharmacyclics: Honoraria; TG Therapeutics: Research Funding.

Stochastic subspace identification uses the frequency stability graph as the judgment standard of recognition results, and the introduction of clustering algorithm makes the automatic recognition of stability graph possible. At present, the clustering algorithm generally has subjective input parameter selection, complex algorithm theory and human intervention. The characteristic of stability chart is that the physical mode density is large, while the false mode density is small. DBSCAN clustering is a density based clustering algorithm, which can identify any shape of the class. According to the characteristics of the stability diagram, this paper proposes an automated operational modal analysis algorithm based on DBSCAN clustering, which is applied to the benchmark model of Z24 bridge in Switzerland. The results show that the method is feasible in the automated operational modal analysis of bridge structures.

The article shows complex algorithm for locating geoacoustic events. Location algorithms problems are considered and methods for their solution are proposed. The requirement list is suggested for the developed algorithm, and the complex algorithm key stages are formulated.

In recent years, power companies have been looking for intelligent electricity distribution networks, so as to employ an intelligent level of networking based on deployment of Distributed Generation (DG) and switching equipment entailing the ability to send and receive data and run commands. This level of intelligent development also covers network automation, enhancing reliability and economic exploitation of all available resources within the network at normal and faulty modes. This study proposed an acceptable level of intelligent development based on traditional non-restructured electricity distribution networks. At the next stage, it adopted a complex algorithm to present a method for operation of the network under normal and faulty circumstances with the aim of further cost savings and enhancement of reliability. Simulations carried out on part of the distribution network of Ilam based on actual data through Digsilent yielded satisfactory results.

To develop a complex algorithm for autosomal recessive ataxia (ARA) diagnosis applicable for Russian patients with degenerative ataxias.48 patients with of presumably degenerative ataxias were examined. Clinical evaluation was performed with the use of the SARA and ICARS scales (for ataxia) and MoCA (cognitive functions), and a set of laboratory tests was carried out, including electromyography, brain MRI, and DNA analysis of mutations responsible for Friedreich's disease and spinocerebellar ataxias (SCAs) types 1, 2, 3, 6 and 17. 28 patients underwent mutation screening using a multigenic MPS panel.8 patients (16.7%) with non-hereditary causes of ataxia were identified: cerebellar alcoholic degeneration (n = 6) and multiple system atrophy of cerebellar type (n = 2); 3 patients (6.3%) with genetic ataxias were identified using routine DNA tests, such as with SCA type 1, 2 and 17, and 9 (18.8%) patients with Friedreich's disease. The MPS panel enabled molecular diagnosis of ARA in 8 patients (28.6%): ataxia-telangiectasia (n = 2), SANDO syndrome (n = 2), ataxia with oculomotor apraxia type 2 (n = 1), SCAR10 (n = 1), SCAR16 (n = 1), and atypical form of neuroaxonal dystrophy (n = 1). The diagnosis was not established in 20 patients.We have proposed an appropriate algorithm for degenerative ataxia diagnosis which is recommended to be used when examining patients with sporadic and autosomal recessive cases of the disorders with dyscoordination of movements.Цель исследования. Разработка комплексного алгоритма диагностики аутосомно-рецессивных атаксий, применимого для выборки российских пациентов с атаксиями дегенеративного генеза. Материал и методы. Обследованы 48 пациентов с атаксией предположительно дегенеративного генеза. Проведены клиническая оценка по шкале для обследования и оценки атаксии (SARA), международной объединенной шкале оценки атаксии (ICARS), а для скрининга когнитивных нарушений применяли Монреальскую шкалу оценки когнитивных функций (MoCA), а также комплекс лабораторных и инструментальных исследований, включающий электромиографию, МРТ головного мозга, ДНК-анализ на болезнь Фридрейха и аутосомно-доминантные спиноцеребеллярные атаксии 1, 2, 3, 6 и 17-го типа. У 28 пациентов выполнен мутационный скрининг с использованием таргетной мультигенной MPS-панели. Результаты. Выявлены 8 (16,7%) пациентов с ненаследственными причинами атаксии - алкогольной мозжечковой дегенерацией (n=6) и мозжечковым вариантом мультисистемной атрофии (n=2), а также 12 пациентов с генетическими атаксиями, диагностируемыми при рутинном мутационном скрининге, - 3 (6,3%) пациента со спиноцеребеллярными атаксиями 1, 2 и 17-го типа и 9 (18,8%) пациентов с болезнью Фридрейха. С использованием MPS-панели молекулярный диагноз аутосомно-рецессивных атаксий установлен у 8 (28,6%) пациентов: атаксия-телеангиэктазия (n=2), синдром SANDO (n=2), атаксия с окуломоторной апраксией 2-го типа (n=1), SCAR10 (n=1), SCAR16 (n=1), атипичная форма нейроаксональной дистрофии (n=1). Окончательный диагноз не был установлен у 20 пациентов. Заключение. Для дифференциальной диагностики дегенеративных атаксий нами предложен комплексный диагностический алгоритм, который может быть рекомендован для обследования пациентов со спорадическими и аутосомно-рецессивными случаями заболеваний с нарушением координации движений.

The paper is devoted to the investigation of web pages classification algorithms for protection against inappropriate information on the Internet. The approach for combining of classification algorithms based on different aspects of the source data and different machine learning methods is proposed. The experiments results of this approach application for website classification is presented.

The rise of imaging in medical field has boost the progress of new imaging method and modality that safer, cheaper, and faster. Electrical Impedance Tomography (EIT) is one of imaging modalities that provides safe medical imaging through non ionizing method. The downside of the EIT method is the complex algorithm needed to produce imaging result and low resolution. This study is aimed to provide a simple EIT imaging system that are easily used and developed. The proposed system designed in this study is a MatlabTM and Arduino based imaging system, which are then tested under several observation object scenario. The imaging results that are produced by the system are able to represent the varying observational objects structure. Impedance measurement method that is implemented in the proposed system is a two-point technique using 8 electrodes and 16 electrodes with a frequency of 50 kHz. The main observation object of this system is an acrylic cup filled with tap water that has a TDS (Total Dissolved Solids) of 300 ppm. The proposed EIT imaging system is considered as a simple construction that is able to recognize two different objects according to its different impedance values.

Background: Qigong has a long-term application by integration of mind, breath and body to prevent and cure diseases. Researches show that qigong practice could adjust anxiety, the mechanism may found on brain and heart functions. Currently there are limitations on qigong's anxiety-release mechanism study between mind and body, and existing studies lack of evidence on electrophysiology research. Our objective to analyse qigong's anxiety-release effect and mechanism. Methods: A two-arm randomized clinical trial with 144 qigong naïve anxiety subjects without cerebral or cardiovascular diseases or other severe syndromes will be allocated to either a body and breath regulation group (n = 72) or a body regulation group (n = 72). Participants will conduct three-circle post standing qigong exercise 5 times per week for 8 weeks, while the three-circle post standing qigong combined with abdominal breath regulation (TCPSQ-BR) group will combined with abdominal breath regulation. The primary outcome will be the Self-Rating Anxiety Scale (SAS), and the secondary outcome will be complexity-based measures of heart rate and electroencephalogram (EEG) signals assessed at baseline and 8 weeks. Multiscale entropy analysis will be used as measure of complexity. Conclusion: This study will be investigate the effects of qigong's anxiety-release by SAS, and will analyze the coordinates of EEG and heart rate variability (HRV) signals before and after three-circle post standing qigong (TCPSQ) practice, and to analyse their synergies by complex signal process method. Ethics and trail registration: The protocol was approved by the institutional review boards of Beijing University of Chinese Medicine (2018BZHYLL0109). This study was registered with the “Chinese Clinical Trail Registry” in the WHO Registry Network (ChiCTR-Bon-17010840).

This paper presents an ultra-wide band (UWB) based hardware prototype model to study a novel image extract algorithm (IEa). The IEa is a less complex algorithm proposed to solve the issue which ari...

This research will present different simulations to observe the final impact of a war between the U.S. and Iran and its impact on the world oil prices behavior. The main objective of this paper is to evaluate different levels of war intensity and oil prices behavior from a multidimensional perspective. This simulator evaluates different scenarios of war and oil market prices behavior through the construction of a complex algorithm and multidimensional coordinate spaces. This new simulator is entitled "The War Oil Crisis Simulator (WOC-Simulator)". The objective of the WOC-Simulator is to offer policy-makers and researchers a new analytical tool to study the impact of war on oil prices. The WOC-Simulator, in effect, is a simple and applicable scheme. Finally, this research shows the results obtained in the application of WOC-Simulator in different war scenarios between the U.S. and Iran. The period of study is from 1980 to 2025 and the reason to select this short period is to observe the constant armed tensions that always exist between the U.S. and Iran respectively.

The paper reviews key challenges faced by Russian construction companies while entering the international markets. International construction company ratings demonstrate that the amount of work performed by Russian companies is several times less than the ones performed by international contractors. At the same time the world level companies successfully work overseas. Instead of waiting for beneficial investment climate changes, Russian companies must shift the focus from national market towards foreign expansion and extending operations abroad. That would allow extension of foreign operations and positive changes in the system of values and mentality of Russian contractors. © 2019 Published under licence by IOP Publishing Ltd. The authors would like to express their deepest gratitude to the Russian Foundation for Basic Research (RFBR) for the support of the research within the project No. 17-22-07001 "The complex algorithm of culture-based regeneration of minor industrial cities in the context of agglomeration processes in Russia and Europe".

Molecular cytopathology is a rapidly evolving field of cytopathology that provides biological information about the response to personalised therapy and about the prognosis of neoplasms diagnosed on cytological samples. Biomarkers such as circulating tumour cells and circulating tumour DNA are increasingly being evaluated in blood and in other body fluids. Such liquid biopsies are non-invasive, repeatable, and feasible also in patients with severe comorbidities. However, liquid biopsy may be challenging due to a low concentration of biomarkers. In such cases, biomarkers can be detected with highly sensitive molecular techniques, which in turn should be validated and integrated in a complex algorithm that includes tissue-based molecular assessments. The aim of this review is to provide the cytopathologist with practical information that is relevant to daily practice, particularly regarding the emerging role of circulating tumour cells in the field of predictive molecular pathology.

The paper presents the results of estimating image distortions inherent for compression algorithms based on the complex implementation of wavelet coding taking into account the tradeoff between the degree of compression and the transmission of texture. Estimations of the level of distortion of image contours are given depending on the detail and texture characteristics on large areas of the image with a smooth brightness variation. The choice of test images containing low-contrast textures with different levels of medium brightness is justified. As a measure of the distortion between the original and the decoded image, the ratio of the peak value of the signal to the average noise value at the boundary of the contours of objects in the image is selected. The boundaries were detected by a gradient method. Compression factors are calculated for varying the thresholds of the restriction of the spectral components at different levels of the wavelet decomposition. A variant of the frequency-dependent restriction of the spectral components is proposed, which is determined for each of the subbands. Appropriate values of the compression ratio for the coding method based on the prediction of bit planes for a given set of images are presented.

Представлено біомеханічну модель скелета людини. Розроблено комплексний алгоритм оцінки кінематичних параметрів руху людини для одного інерціального вимірювального модуля. Описано формування коректуючих сигналів для комплексного алгоритму. Виконано аналітичну оцінку рівня випадкової похибки розрахунку швидкості та переміщення на основі біомеханічної моделі. Досліджено вплив корекційних сигналів на точність алгоритму. Показано ефективність роботи алгоритму.

The article is dedicated to evaluating quality of medical care of children. Improvement of this parameter and public health indicators is the key goal of a healthcare system of any country at the moment. The authors analyzed different systems of evaluating quality of medical care of children and demonstrated their benefits and drawbacks. The article presents a complex algorithm of evaluating quality of medical care developed by the authors; it involves structural, procedural and effective components of this term and corresponds with a complex model of simultaneous control organization on the professional level as well as on the regulatory level with due regard to the degree of specialist/patient interaction.

This paper presents inexpensive methods whereby the vehicle side-slip angle can be measured accurately at low speeds on any terrain using cameras. Most commercial side-slip angle sensor systems and estimation techniques rely on smooth terrain and high vehicle speeds, typically above 20 km/h, to provide accurate measurements. However, during certain in-situ tyre and vehicle testing on off-road conditions, the vehicle may be travelling at speeds slower than required for current sensors and estimation techniques to provide sufficiently accurate results. Terramechanics tests are typical case in point. Three algorithms capable of determining the side-slip angle from overlapping images are presented. The first is a simple fast planar method. The second is a more complex algorithm which can extract not only the side-slip angle but also its rotational velocities and scaled translational velocities. The last uses a calibrated stereo-rig to obtain all rotations and translational movement in world coordinates. The last two methods are aimed more at rough terrain applications, where the terrain induces motion components other than typical predominant yaw-plane motion. The study however found no discernible difference in measured side-slip angle of the methods. The system allows for accurate measurement at low and higher speeds depending on camera speed and lighting.

The most important performance parameters in cyclone design are the pressure drop and collection efficiency. In general, the best designs provide relatively high efficiency with a low pressure drop. In this study, the multi-objective optimization of cyclones operating with a low particle loading (15 g/m3) and small particle diameter (5 μm to 15 μm) is performed using the COMPLEX algorithm, a constrained derivative-free optimization method. The objective function is formulated to maximize the collection efficiency with a maximum pressure drop restriction. All objective function evaluations are carried out by CFD simulation with the code CYCLO-EE5 based on the Eulerian multi-fluid concept. An optimized design cyclone is obtained applying the proposed methodology in a feasible time (≈ 15 days of computational effort). Also, in comparison with the Stairmand and Lapple cyclones the collection efficiency was 3.5% and 9.2% higher and the pressure drop was 6.3% and 11.4% lower, respectively. The increase in the collection efficiency with lower pressure drop was due to the displacement of the tangential velocity peak toward the wall and an increase in the tangential velocity near the wall.

Seafood allergy is a hypersensitive disorder with increasing prevalence worldwide. Effective and accurate diagnostic workup for seafood allergy is essential for clinicians and patients. Parvalbumin and tropomyosin are the most common fish and shellfish allergens, respectively. The diagnosis of seafood allergies is complicated by cross-reactivity among fish allergens and between shellfish allergens and other arthropods. Current clinical diagnosis of seafood allergy is a complex algorithm that includes clinical assessment, skin prick test, specific IgE measurement, and oral food challenges. Emerging diagnostic strategies, such as component-resolved diagnosis (CRD), which uses single allergenic components for assessment of epitope specific IgE, can provide critical information in predicting individualized sensitization patterns and risk of severe allergic reactions. Further understanding of the molecular identities and characteristics of seafood allergens can advance the development of CRD and lead to more precise diagnosis and improved clinical management of seafood allergies.