Intensity Transformation Research Articles

Distributed fault estimation of nonlinear dynamical systems over sensor networks: a non-fragile approach

PurposeThe purpose of this paper is to investigate the fault estimation issue of nonlinear dynamical systems via distributed sensor networks. Furthermore, based on the communication topology of sensor networks, the nonfragile design strategy considering the gain fluctuation is also adopted for distributed fault estimators.Design/methodology/approachBy means of intensive dynamical model transformation, sufficient conditions with disturbance attenuation performance are established to design desired fault estimator gains with the help of convex optimization.FindingsA novel distributed fault estimation framework for a class of nonlinear dynamical systems is established over a set of distributed sensor networks, where sampled data of sensor nodes via local information exchanges can be used for more efficiency.Originality/valueThe proposed distributed fault estimator gain fluctuations are taken into account for the nonfragile strategy, such that the distributed fault estimators are more applicable for practical sensor networks implementations. In addition, an illustrative example with simulation results are provided to validate the effectiveness and applicableness of the developed distributed fault estimation technique.

Improving ductility and strength of high-entropy alloy [formula omitted] via multi-directional forging and annealing

A dual-phase high-entropy alloy Fe50Mn30Co10Cr10 is treated via multi-directional forging (MDF) and subsequent annealing at 600°C–1000°C. Different microstructures with totally different grain sizes and phase ratios are obtained. The MDF increases yield strength and ultimate tensile strength at the expense of ductility. Via annealing the MDF-processed alloy at 1000°C, the full recrystallized sample yields a excellent combination of high strength and good ductility due to the grain boundary strengthening, transformation-induced plasticity and twinning-induced plasticity. The yield strength, ultimate tensile strength and elongation at failure are 16.2%, 14.2% and 35.3% than those of the as-cast sample. The postmortem characterizations of this annealed sample show strong 〈111〉 texture in the austenite phase along the loading direction and intense martensite transformation with the gradually disappearance of the annealing twins.

Rhythm, noise and action: decoding R.D. Burman’s soundtracks of Bombay cinema

ABSTRACT The sustained use of ‘Western’ style orchestration in Bombay film music can be attributed to the trajectory of two kinds of musical practices, one tethered to the leisure economies developed by the colonial rule from the 19th century onwards, and second, the robust and frequent presence of travelling jazz bands from the early twentieth century. As a period of intense transformation, the decade of the 1940s saw musicians from different parts of the subcontinent move to Bombay to find work in the film industry. This process often involved adapting to new performance contexts, genres and instruments. Studios in the Bombay film industry became fecund spaces where musicians and arrangers trained in Western classical music came in heady contact with the jazz men of Bombay’s nightclubss. Focusing on the late 1960s as another transitional moment, this article traces R.D. Burman’s affective encounters with these ‘mobile musicking bodies.’ Biographies of his key musicians give us detailed accounts of their training and involvement in diverse sites of musical performance, before they arrived in the Bombay film industry. This detour informs my analysis of R.D. Burman and his team’s innovative film scores, underlining vocal effects, side rhythms and inclusion of edgy off-key sounds. Moving away from a song-driven approach, I focus on title tracks, background scores and extended instrumental set-pieces of crime and action genres that are now getting recirculated on the internet by R.D. Burman’s fans. Through a methodology that will combine textual analysis, internet ethnography and close listening, the article will argue that these new soundscapes carried the inscriptions of global music cultures and ‘extra-musical’ noise.

Advancing thermoelectric potential: strontium telluride under compression strain analyzed with HSE hybrid functional and Wannier interpolation

In the present era, the energy sector is undergoing an intense transformation, which encourages numerous research efforts aimed at reducing and reusing energy waste. One of the main areas of focus is thermoelectric energy, where telluride compounds have attracted researchers due to their remarkable ability to convert thermal energy into electrical energy. We focused this study on finding out how well strontium telluride (SrTe) can be used to generate thermoelectric power by testing it under up to 10% compression strain. We have used advanced computational approaches to increase the accuracy of our results, specifically the HSE hybrid functional with the Wannier interpolation method. This method is primarily employed to analyze electronic properties; however, our research extends its utility to investigate thermoelectric characteristics. Our findings provide accurate predictions for both electronic and thermoelectric properties. The above method has successfully achieved a significant improvement of 58% in the electronic band gap value, resulting in a value of 2.83 eV, which closely matches the experimental results. Furthermore, the Figure of Merit 0.95 is obtained, which is close to the ideal range. Both the band gap value and the thermoelectric figure of merit decrease when the compression strain is increased. These findings emphasize the importance of using SrTe under specific conditions. The findings of this work provide motivation for future researchers to investigate the environmental changes in the thermoelectric potential of SrTe.

УПРАВЛЕНИЕ КОМАНДОЙ ВНУТРИКОРПОРАТИВНОГО СТАРТАПА: ПРОЦЕССНОЕ ИССЛЕДОВАНИЕ ДИНАМИКИ РАЗВИТИЯ

Innovative development of the Russian economy is impossible without increasing the efficiency of small innovative enterprises (startups), including those created within companies. The problems of managing internal startups and especially startup teams have been relatively poorly studied by modern science. The high dynamics of startups causes high variability and intensive transformations in team management practices. To create a highper formance startup team, it is necessary to understand the internal logic of change in the parameters of teams and team management. The article studies the dynamics of changes in team characteristics and team management within the startup development process. The research methodology is based on process research and case studies. The work investigates the dynamics of the startup team a cloud gaming service. The startup was organized within one company but was then sold to a large IT corporation. The article examines certain characteristics of the team in their development including management methodologies, team composition, communications, culture, motivation, operational and strategic planning pro cedures.

Application of deep ensemble learning for palm disease detection in smart agriculture

Agriculture has notably become one of the fields experiencing intensive digital transformation. Leveraging state-of-the-art techniques in this domain has provided numerous advantages for agricultural activities. Deep learning (DL) algorithms have proven beneficial in addressing various agricultural challenges. This study presents a comprehensive investigation into applying DL models for palm disease detection and classification in the context of smart agriculture. The research aims to address the limitations observed in previous studies and improve the robustness and generalizability of the results. To achieve this, a two-stage optimization methodology is employed. First, transfer learning and fine-tuning techniques are applied using various pre-trained deep neural network models. The experiments show promising results, with all models achieving high accuracy rates during training and validation. Furthermore, their performance on unseen test data is also assessed to ensure practical applicability. The top-performing models are MobileNetV2 (92.48 %), ResNet (92.42 %), ResNetRS50 (92.30 %), and DenseNet121 (92.01 %). Second, a deep ensemble learning approach is applied to enhance the models' generalization capability further. The best-performing models with different criteria are combined using the ensemble technique, resulting in remarkable improvements in disease detection tasks. DELM1 emerges as the most successful ensemble model, achieving an ROC AUC Score of 99 %. This study demonstrates the effectiveness of deep ensemble learning models in palm disease detection and classification for smart agriculture applications. The findings contribute to advancing disease detection systems and emphasize the potential of ensemble learning. The study provides valuable insights for future research, guiding the application of DL techniques to address critical agricultural challenges and improve crop health monitoring systems. Another contribution is combining various plant diseases and insect pest classes using diverse datasets. A comprehensive classification system is achieved by considering different disease classes and stages within the white scale category, improving the model's robustness.

MOTHER’S GAZE: FAMILY PHOTOGRAPHY AS A WAY TO RE-CLAIM SUBJECTIVITY

I am a mother, photographer and photography researcher. In this article I reflect on the practice of photographing my family with a goal of drawing attention to the role of family photography in re-claiming mother’s agency as subject. By implementing autoethnographic research strategy I analyse photographs and texts shared on my motherhood blog in 2016–2020. An intensive identity transformation takes place upon becoming a mother, which moves the woman’s confidence in herself as a subject with agency. My experience of motherhood was complicated and ambivalent. Yet, whilst photographing my family I create an image of a warm and cosy life. The discrepancy between images and inner experience prompts writing and thereby expanding the meaning of representations through written narrative. By looking for other means to regain subjectivity I review the elements of my photographic experience: the act of photographing, the review of photographs, archiving, sharing on social network in combination with writing. I state that photography allows me to activate my gaze at others and the gaze of others at me, which provides quite a significant sensation of power. The article offers a different perspective on the genre of vernacular family snapshots stressing the therapeutic potential of photography practice.

Upgrading the industrial structure for optimizing water-energy-carbon nexus in regional trade network

To take actions for the SDGs (Goals 6, 7, 9, 12, and 13), the world is undergoing intense industrial transformation and upgrading. However, there has been limited analysis of water-energy-carbon (WEC) nexus within regional trade network to uncover the effects of industrial restructuring. Here, this study explores the trade-related WEC flows in the Yangtze River Delta area (YRD) from 2012 to 2017 by four aspects (spatiotemporal status, sectors, WEC flowing synergies, and environmental-economic trade-off) based on an environmentally extended input-output analysis. The main results show that the resource supply network in the YRD has been optimized, with enhanced synergies of WEC flows. Resource trade in the YRD has shifted from traditional heavy industry (HV Ⅰ) to high-tech manufacturing industry (HV Ⅱ). The share of trade-related WEC in demand of HV Ⅱ among all sectors increased by 10, 5, and 15 percentages, while the share in demand of HV Ⅰ decreased by 15, 10, and 10 percentages during this transition period. This study also discloses an environmental-economic contradiction arising in regional trade: low-carbon and high-value-added economic development in some regions may be premised on relocating environmental resource pressures. Hence, this study could assist policymakers in analyzing sustainable industrial transition models for regional integration clusters and in formulating targeted interregional resource trade policies to alleviate development gaps.

Insights of ecological resilience in Caatinga assemblages – landscape configuration drives Chrysomeloidea (Coleoptera) diversity in a seasonally dry tropical forest

Seasonally Dry Tropical Forests (SDTFs) have long suffered from chronic, intensive and extensive landscape transformations due to human activities, challenging biodiversity conservation in this biome. The Caatinga is the largest Neotropical SDTF, serving as an excellent model to understand how land use changes modulate ecological communities. In this study, we assessed the effects of landscape configuration and composition on the abundance and diversity of Chrysomeloidea in a region of Caatinga. We sampled beetles in 10 landscape units, in which we measured landscape configuration (patch size, edge density) and composition (landscape diversity, patch richness). Hill numbers (q0, q1, q2) were used to analyze the diversities of Chrysomeloidea. A total of 484 individuals belonging to 82 species were collected. Landscape configuration affected Chrysomeloidea assemblages with a positive correlation between edge density and Chrysomeloidea diversity. We provide a new perspective regarding the spatial distribution of Chrysomeloidea in Caatinga and conclude that landscape configuration, but not composition, directly affects Chrysomeloidea assemblages.

Hydroecological limitations of the use of water resources of transboundary rivers of the steppe zone (through the example of the Ural and Tobol Rivers, Russia)

To identify the main types of hydroecological restriction on the use of water resources and their spatial patterns in the Ural and Tobol river basins within the steppe zone.A comprehensive assessment of the water‐environmental situation in the regions of the studied basins studied was carried out on the basis of the calculation of water‐environmental stress – the ratio of water intake and free flow (average long‐term flow minus ecological). To assess the environmental restrictions on water use, data from the State reports, “On the State and Protection of the Environment" were used. Exposure to the risk of flooding of settlements was analysed according to information from the registers of settlements at risk of flooding (flooding). Analysis of the dynamics of channel processes was carried out using Landsat satellite images. For the rivers of the Tobol River basin, an approach based on taking into account the nature of channel transformations in the sectors of the state border of the Russian Federation and the Republic of Kazakhstan was used.As a result of the research, the main types of hydroecological restriction in the transboundary basins of the Ural and Tobol were identified. In particular, the key factor limiting water use is the availability of a guaranteed volume and adequate quality of water resources. Hydrological restrictions associated with the negative impact of water include the risks of flooding of settlements during the passage of spring or summer floods, as well as intensive riverbed transformations (in the Ural River basin).The Ural and Tobol river basins (within the steppe zone) are characterised by the development of a rather complex hydroecological situation in some areas. Taking into account the long cycle of low water content in these rivers, the general hydroecological situation has aggravated in recent decades, the primary problem being that of guaranteed provision of water resources of standard quality. As a result, an urgent task is to develop an algorithm for a comprehensive assessment of hydroecological restrictions on water use and their consequences for the population and economy of the regions of the steppe zone.

Schrödinger's Cat-Parallel experiences: exploring the underlying mechanisms of undergraduates' engagement and perception in online learning.

The emergence of e-learning had an intense, immediate, and disruptive transformation in the education system. While education aims to seek more interactions and learning engagement between teachers and students, it turns out that it takes lots of work to achieve the goal in the online classroom. This study aims to explore the underlying mechanisms and implications that emerge from the influence of the new features of online learning, drawing on students' real-life experiences, to construct a comprehensive theoretical model. From July 2023 to October 2023, 56 undergraduates, including 18 male and 38 female, participated in the data collection process either face-to-face or online. The study constructs a substantive theoretical model by employing the approaches of The Grounded Theory, three level-coding constant comparative method, theoretical sampling, core category distillation and storyline collation. (1) The elements involved in the process of online learning exhibit underlying logical correlations, driven by profound underlying factors, ultimately resulting in a parallel experience akin to Schrödinger's Cat. (2) Online features lead to students' motivation mainly depending on whether they are self-regulated. (3) Teacher-student interactions and self-regulation shape different learning contexts and types by being moderated by internal and external effects. Students had a parallel experience similar to that of Schrödinger's Cat: they were constantly dissatisfied with "rational" learning and "perceptually" satisfied with online learning. The variation in the satisfaction of the three basic psychological needs necessities college students in online learning leads to parallel experiences.

Housing-Resources Spatial Mismatch Investigation of Affordable Housing and Policy Implementation: A Case Study from Hangzhou, China

Intensive spatial transformation and restructuring in China these years has brought the separation of residence-job, so as to residence-public services, which adversely affects people’s access and enjoyment of job and public service resources, especially for the disadvantaged populations with limited choice of residence location and insufficient access to those resources. The residents of affordable housing are among the typical disadvantaged populations under the existing affordable housing policy in China. Residence-job separation of affordable housing residents has been paid much attention in literature, but no specific study has been conducted on the residence-public services separation and the behavioral responses of the residents. Spatial mismatch theory was originally put forward to reveal the adverse labor market outcome brought about by residence-job separation, and nowadays some scholars have tried to extend the residence-job spatial mismatch to residence-other resource spatial mismatch. This research responds to both the dilemma facing by the disadvantaged affordable housing residents and the extension trend of spatial mismatch theory. By applying the spatial mismatch theory and taking several affordable housing communities of Hangzhou as examples, the study explore the problems existing in affordable housing in commuting, employment, public service and residents' behavior response. The results found that the current affordable housing policy has led to an increase in commuting costs, a decrease in employment accessibility and welfare, a decrease in accessibility and satisfaction of public services, and disruptive behavior in the affordable housing market. These problems are mainly caused by remote layout and single supply, unreasonable allocation methods, difficulty in exchanging housing units and inadequate supervision of undesirable behaviors. To alleviate the spatial mismatch between housing and resources in Hangzhou, policy suggestions could be considered from four aspects: housing layout and supply, allocation methods, housing exchange and supervision.

Variations in the oxidation potential of PM2.5 in an old industrial city in China from 2015 to 2018

PM2.5 pollution in China has decreased dramatically, but how its health effects change is not clear. There are 120 old industrial cities in China, where the sources, composition, and health effects of PM2.5 may be significantly different with other cities. Huangshi, an old industrial city in central China, underwent intense green transformations from 2015 to 2018. In this study, we collected ambient PM2.5 samples in 2015 and 2018 at an urban site in Huangshi. The average PM2.5 concentration decreased from 83.44 ± 48.04 μg/m3 in 2015 to 68.03 ± 39.41 μg/m3 in 2018. However, the average volume-normalized dithiothreitol (DTTv) of PM2.5 increased from 1.38 ± 0.45 nmol/min/m3 to 2.14 ± 1.31 nmol/min/m3 and the DTT normalized by particulate mass (DTTm) increased from 20.6 ± 10.1 pmol/min/μg to 40.07 ± 21.9 pmol/min/μg, indicating increased exposure risk and inherent toxicity. The increased toxicity of PM2.5 might be related to the increased trace elements (TEs) concentrations. The positive matrix factorization and multiple linear regression methods were employed to quantify the contributions of emission sources to PM2.5 and DTTv. The results showed that the contribution of coal combustion, industry, and dust to PM2.5 decreased significantly from 2015 to 2018, while that of vehicle emission and secondary sources increased. Despite the decreased fraction of coal combustion and industry sources, their contribution to DTTv increased slightly, which was caused by the increased intrinsic toxicity. The increased intrinsic toxicity was possibly caused by increased TEs, such as Pb, Cu, and V. Besides, the contribution of vehicle emission to DTTv also increased. Overall, these results provide valuable insights into the effectiveness of controlling strategies in reducing particulate health impacts in old industrial cities, and stress the necessity of formulating toxicity-oriented controlling strategies, with special attention to TEs from coal combustion and industry sources as well as vehicle emissions.

An intensity-based self-supervised domain adaptation method for intervertebral disc segmentation in magnetic resonance imaging

Background and objective:Accurate IVD segmentation is crucial for diagnosing and treating spinal conditions. Traditional deep learning methods depend on extensive, annotated datasets, which are hard to acquire. This research proposes an intensity-based self-supervised domain adaptation, using unlabeled multi-domain data to reduce reliance on large annotated datasets.Methods:The study introduces an innovative method using intensity-based self-supervised learning for IVD segmentation in MRI scans. This approach is particularly suited for IVD segmentations due to its ability to effectively capture the subtle intensity variations that are characteristic of spinal structures. The model, a dual-task system, simultaneously segments IVDs and predicts intensity transformations. This intensity-focused method has the advantages of being easy to train and computationally light, making it highly practical in diverse clinical settings. Trained on unlabeled data from multiple domains, the model learns domain-invariant features, adeptly handling intensity variations across different MRI devices and protocols.Results:Testing on three public datasets showed that this model outperforms baseline models trained on single-domain data. It handles domain shifts and achieves higher accuracy in IVD segmentation.Conclusions:This study demonstrates the potential of intensity-based self-supervised domain adaptation for IVD segmentation. It suggests new directions for research in enhancing generalizability across datasets with domain shifts, which can be applied to other medical imaging fields.

Deep Learning-Driven Parameter Adaptation for Underwater Image Restoration

In this paper we propose a learning-based approach to enhance underwater image quality by optimizing parameters and applying intensity transformations. Our methodology involves training a CNN Regression model on diverse underwater images to learn enhancing parameters, followed by applying intensity transformation techniques. In order to evaluate our approach, we conducted experiments using well-known underwater image datasets found in the literature, comprising real-world subaquatic images and we propose a novel underwater image dataset, composed by 276 images from Amazon turbid water rivers. The results demonstrate that our approach achieves an impressive accuracy rate in three different underwater image datasets. This high level of accuracy showcases the robustness and efficiency of our proposed method in restoring underwater images.

The Issue of Provisioning Garrisons of Regular Troops in Southern Western Siberia in Correspondence of Military, Mining, and Civil Authorities of the Region in the mid-18th Century

Intensive transformations in the administrative environment in the South Siberian outskirts during the second third of the 18th century led to the emergence of a special kind of communication, namely, intersectoral. The problem of provisions supply delivery for the regular forces in the south of Western Siberia in the regional and local administrative discourse of military-departmental, mining, and civil authorities in the middle of the 18th century is considered in the paper. The author analyzes the office documentation which was one of the key channels for the implementation and reflection of administrative interactions between various verticals of power in the early Imperial period. Intersectoral communication at the regional level was largely open while at the local level there had been attempts to limit it deliberately. It is shown that the development of a renovated model, algorithms for the procurement and food supply for military teams took place during the official correspondence of 1747–1749, when the structures of the three branches of government had significantly different positions. The circumstances of discussing the food supply issue in the power discourse revealed in the article indicate that there were tangible manifestations of competition between civil and departmental authorities in the regional and local administrative system of the middle of the 18th century.

CONCEPTUAL POLYCOMPONENT MODEL OF AN INNOVATIVE MECHANISM FOR IMPROVING THE COMPETITIVENESS OF AGRO-INDUSTRIAL COMPLEX ENTERPRISES

The modern agricultural sector is going through a period of intense transformation caused by both internal and external factors. In the context of active globalisation, business entities are forced to withstand fierce competition and therefore need to constantly adapt to the environment. This creates an urgent need for agribusiness enterprises to constantly improve their approaches and mechanisms of operation. Continuous adaptation requires flexibility, innovation and strategic thinking. Changes in the economic, political and technological landscape require businesses to respond quickly to new opportunities and challenges to ensure their competitiveness and sustainability. This constant process of adaptation is becoming a prerequisite not only for success, but also for survival in today's global business environment. The purpose of the article is to develop an innovative mechanism for improving the competitiveness of agribusiness enterprises. Methodology. The methodological basis of the study, which objectively reveals and substantiates the problem of increasing the competitiveness of agro-industrial enterprises using the model of the innovation mechanism, is based on such special and general scientific methods as: monographic, logical-theoretical, statistical and economic-mathematical, visualisation, system analysis, neural network modelling, logical generalisation, abstraction and conclusion formation. The information base of the study was formed by the materials of the State Statistics Service of Ukraine, statistical yearbooks, scientific developments of scientists on the defined topic, and financial statements of the studied enterprises. The subject and object basis of the study is the entrepreneurial activity of agricultural enterprises in Vinnytsia Oblast: Agricultural complex "Zelena Dolyna", PJSC "Dashkivtsi", LLC "Selyshchanske", FE "Yavir", FE "IRYNA – O.T". The results of the study have shown that the innovation mechanism, which consists in ensuring the management of innovative development of agribusiness enterprises, involves adjusting the business environment of an economic entity to achieve a cumulative effect from the efficient use of innovative and energy potentials. The paper emphasises that the cumulative effect means that the effect of the interaction of innovation and energy resources exceeds the simple effect of the impact of each of them separately. Practical implications. The authors calculated the indicators of competitiveness of the studied agricultural enterprises of Vinnytsia Oblast; assessed the level of innovation potential of these enterprises; determined the indicators of energy potential. On the basis of the obtained diagnostic results, a fuzzy knowledge base has been formed and a multicomponent decision-making system has been built for various combinations of values of the components of the innovation mechanism.

The second generation of intellectuals in the educational modernization of the city of Santos (1908-1930)

In the late nineteenth and early twentieth centuries, the city of Santos, located on the coast of São Paulo, emerged as an important urban center influenced by the ideals of progress and modernity that accompanied the recent Proclamation of the Republic in Brazil. This period of political transition was marked by intense social, economic, and cultural transformations, reflected in the practices and discourses of the intellectuals who worked in the city. Among these intellectuals, a network formed by Arthur Porchat de Assis, Adolpho Porchat de Assis, Victor de Lamare and Delphino Stockler de Lima stands out, whose work in the modernization of education in Santos between 1908 and 1930 had a significant impact on the city's educational development. This study aims to present results about the role of these intellectuals in the process of modernization of education in Santos during the First Republic. The research was based on a literature review and a survey of periodicals of the time, analyzing the discourses and practices of these subjects. The analysis reveals that education was seen as a fundamental means for the construction of a modern and progressive nation, being used as an instrument for the consolidation of republican ideals and for overcoming the memories of the old monarchical regime. The city of Santos, with its strategic port and an active intellectual elite, has become a stage for debates and initiatives aimed at educational modernization. This network of intellectuals, in particular, played a crucial role in the implementation of educational reforms and the creation of institutions that sought to meet the needs of the population, contributing to the construction of a dualistic educational system, offering one type of education to the ruling class and another type of education to the working class.

Taxonomy of Acute Stroke: Imaging, Processing, and Treatment

Stroke management employs a variety of diagnostic imaging modalities, image processing and analysis methods, and treatment procedures. This work categorizes methods for stroke imaging, image processing and analysis, and treatment, and provides their taxonomies illustrated by a state-of-the-art review. Imaging plays a critical role in stroke management, and the most frequently employed modalities are computed tomography (CT) and magnetic resonance (MR). CT includes unenhanced non-contrast CT as the first-line diagnosis, CT angiography, and CT perfusion. MR is the most complete method to examine stroke patients. MR angiography is useful to evaluate the severity of artery stenosis, vascular occlusion, and collateral flow. Diffusion-weighted imaging is the gold standard for evaluating ischemia. MR perfusion-weighted imaging assesses the penumbra. The stroke image processing methods are divided into non-atlas/template-based and atlas/template-based. The non-atlas/template-based methods are subdivided into intensity and contrast transformations, local segmentation-related, anatomy-guided, global density-guided, and artificial intelligence/deep learning-based. The atlas/template-based methods are subdivided into intensity templates and atlases with three atlas types: anatomy atlases, vascular atlases, and lesion-derived atlases. The treatment procedures for arterial and venous strokes include intravenous and intraarterial thrombolysis and mechanical thrombectomy. This work captures the stateoftheart in stroke management summarized in the form of comprehensive and straightforward taxonomy diagrams. All three introduced taxonomies in diagnostic imaging, image processing and analysis, and treatment are widely illustrated and compared against other state-of-the-art classifications.

Szczecin – A medieval town at the mouth of the river Odra on the southern coast of the Baltic

Szczecin in one of the most important towns in Pomerania region. According to archaeological sources, the oldest Slavic settlement appeared here in the 8th century. Specific conditions prevailing in river mouths have favoured human settlements since prehistory but settlement processes and intensive transformations of the natural environment which accompanied them became very intensive in the Middle Ages. The landscape of the River Odra, which underwent transformations as a result of anthropogenic processes, was shaped primarily in the period of the last 16–15 thousand years. In the literature the problem of reconstructing the topography of the oldest part of today's Szczecin has been addressed. The aim of the article is to present the earliest stages of the formation of the city and the beginnings of the transformation of the natural environment as a result of anthropogenic processes, as well as ways of using natural resources.