History Characteristics Research Articles

List jako świadectwo życia kulturalno-naukowego na przykładzie spuścizny rękopiśmiennej ks. Jana Kudery

Father Jan Kudera, together with Father Emil Szramek and Konstanty Prus, belonged to the first generation of researchers of the Silesian literary regionalism. This paper presents the results of an analysis the correspondence of Fr. Jan Kudera, kept at the Archdiocesan Archives in Katowice. The analysed documents come from 9 fonds of the legacy bearing reference numbers from ZS 515 to ZS 523. The research of a historical and literary character was conducted mainly through content analysis. The letter was treated as a document and at the same time an autonomous statement. Correspondence from the legacy of the priest can be a valuable and unique source of information on cultural and scientific life in Silesia in the years 1922–1939 and about Kudera itself.

Spatial heterogeneity analysis on distribution patterns and underlying determinants of historical rural settlements: a case study in Taihang Baxing

AbstractAs vital carriers of cultural heritage, rural areas are facing the threats of degradation and urbanization during rapid urbanization processes. In recent years, China has formulated and implemented a series of national policies, regulations, and heritage protection lists to safeguard and perpetuate the traditional patterns and historical features of rural heritage. However, these rural heritage listings exhibit significant macro-level distributional imbalances and generally lack consideration of regional characteristics. This study uses the Taihang Baxing (THBX) in China as a case study, initially employing historical local documents and maps as base data. It utilizes the stability in the evolution of Chinese characters to compare historical and contemporary village names, filtering out existing historical rural settlements (HRS) to construct a dataset. Further, a multi-scale geographically weighted regression (MGWR) model is applied to analysis the impacts of natural, economic, and social factors on the concentration of HRS (CHRS). The study reveals that the CHRS in the region is markedly characterized by clustering, with evident spatial heterogeneity in the impacts of various factors. Slope (SLP), total annual precipitation (TP), and potential crop yield (PCY) significantly influence the CHRS globally, while elevation (ELV), distance to ancient path (DAP) and surface runoff (DSR), gross domestic product (GDP), and road density (RD) have significant local impacts. This research offers a methodological framework for HRS data compilation and provides theoretical and methodological references for national and local levels of rural heritage protection, optimization of rural spatial patterns, prediction of rural evolution pathways, and implementation of China’s rural revitalization strategy.

Musculoskeletal mimics for lumbosacral radiculopathy. Part 2: Specific disorders.

Lumbosacral radiculopathy is a common disorder evaluated by the electrodiagnostic medicine (EDX) consultant. Making this task difficult is the abundance of radiculopathy mimics. Peripheral neurologic mimics are common, but musculoskeletal mimics are not rare and may be less familiar to many EDX consultants. Awareness of the most common musculoskeletal mimickers-particularly key historical and physical examination features that can distinguish them from radiculopathies-can lead to an accurate diagnosis for the patient and referring provider. Part 1 of this monograph covered theoretical issues surrounding why radiculopathy mimics occur. This second part reviews the most common musculoskeletal mimics, including facet arthropathy, myofascial pain syndrome, hip pathology, greater trochanteric pain syndrome, piriformis syndrome, sacroiliac joint dysfunction, hamstring pathology, iliotibial band syndrome, and plantar fasciitis. Diagnosis of these musculoskeletal mimickers is complicated by nonspecific physical examination and imaging findings, and diagnostic injections are frequently necessary to confirm the diagnosis. Treatment for most mimickers includes physical therapy, anti-inflammatory medications, guided injections, and other conservative measures, only rarely followed by surgical intervention. EDX consultants can efficiently incorporate a few high-yield maneuvers into their physical examination based on the location of the pain to provide answers to patients presenting with a musculoskeletal mimic of a lumbosacral radiculopathy.

TDOcc: Exploit machine learning and big data in multi-view 3D occupancy prediction

With the advancement of machine learning and big data technologies, BEV(Bird’s Eye View)-based methodologies have recently achieved significant breakthroughs in multi-view 3D occupancy prediction tasks. However, BEV(Bird’s Eye View)-centric 3D occupancy prediction continues to grapple with feature representation and annotation costs when applied to complex open environments. In order to surmount these issues and further propel the evolution of 3D occupancy tasks, this study introduces a novel framework termed TDOcc. By leveraging multi-camera imagery, TDOcc executes 3D semantic occupancy prediction by directly learning from unprocessed 3D spaces, thereby maximizing information retention. TDOcc presents two notable advantages: firstly, it utilizes dense occupancy labels, which not only facilitate robust dense occupancy inference but also enable comprehensive object estimation within the scene. Secondly, the framework synthesizes historical feature information by adeptly aligning past and present features through temporal cues, thereby bolstering the efficacy of the feature fusion module. Additionally, with a view to address the ill-posed nature inherent in camera-based 3D occupancy prediction, we incorporate an enhancement module that operates within the 3D feature space. This module has been meticulously crafted for the training phase to amplify the model’s learning potential. Extensive experiments conducted on the widely recognized nuScenes dataset underscore the efficacy of our proposed approach. Compared to the most recent TPVFormer and OccFormer, our approach has achieved a significant improvement in mean Intersection over Union (mIoU) by 2.0 and 0.8 respectively, and has reached performance comparable to the state-of-the-art LiDAR-based methods.

Based on Deep Learning Model and Flink Streaming Computing Short Term Photovoltaic Power Generation Prediction for Suburban Distribution Network

With the advancement of global energy internet construction, accurate prediction of new energy generation power such as photovoltaic is an important foundation for ensuring the safety and economic working of new power systems. A short-term photovoltaic power generation prediction method for suburban distribution networks based on deep learning model fusion and Flink flow calculation is proposed to address the challenges of complex power grids, diversified disturbance factors, and isolated monitoring points. This method uses Bi directional Long Short Term Memory(BiLSTM) to extract cross sequential nonlinear characteristic of photovoltaic power generation time series data. Compared with standard LSTM, BiLSTM can consider both historical and future information simultaneously, thus extracting richer extracted features from power generation time series data. This method also integrates attention mechanism to capture the importance distribution of historical temporal features for power generation prediction, effectively solving the problem of long-term temporal dependence in standard LSTM models. The Flink streaming computing framework embeds a trained BiLSTM-Attention photovoltaic power generation prediction model, enabling real-time prediction and monitoring analysis of photovoltaic power generation at various monitoring points in the suburban distribution network. This article uses a dataset of a suburban photovoltaic power station for validation, and trains the model with historical power generation data, meteorological factors, weather types, seasons, and other information as inputs. The BiLSTM-Attention fusion model studys the temporal characteristics of power generation, and has high accuracy in predicting short-term photovoltaic power generation in different scenarios. The Flink streaming computing platform can not only process high throughput predicted power data, but also has low time delay.

From Traditional to Postmodern: Architectural Evolution and Implications for Cultural Preservation on Tha Phae Road, Chiang Mai, Thailand

This study examines the architectural heritage of Tha Phae Road in Chiang Mai, Thailand, which reflects the city’s cultural and economic development. The preservation of its historic character and cultural significance is of utmost importance as rapid urbanization and development threaten its potential loss. Using Grounded Theory, the study analyzes non-numerical data, including photographs and site investigations, to identify the area’s four main architectural styles: Modern, Postmodern, Traditional, and Traditional-Colonial, with Modern being the most prevalent. The Compound Annual Growth Rate (CAGR) is used to examine the distribution of styles over an 11-year period, revealing a decline in Traditional and Modern styles and a positive growth rate of Postmodern architecture. To preserve and enhance the area’s visual quality while allowing for new development, the study proposes a Façade Control Guideline and zoning regulations. These guidelines consider criteria such as the history and importance of Tha Phae Road, ensuring that any changes made to the area respect the overall scale and character of the street. This study’s findings have important implications for the development and preservation of Tha Phae Road’s identity and highlight the value of preserving the cultural heritage and visual quality of the area.

THE PHILOSOPHY OF FREEDOM AND ITS LIMITS: UKRAINIAN EXPERIENCE OF DEMOCRATIC DEVELOPMENT

The purpose of this research is a philosophical reflection on the category of freedom in the context of Ukraine’s democratic development, with a focus on its limits in light of current political and social challenges, particularly war and crises. The study analyzes the historical stages of the concept of freedom in Ukraine, the legal and ethical constraints placed on it, and the existential dimension of responsibility tied to individual choice. The research methods include critical analysis of philosophical and political works, synthesis of approaches from different philosophical schools (particularly liberalism and existentialism), comparative analysis of freedom and responsibility concepts, and systematic analysis of the legal and ethical challenges facing modern Ukrainian society. The results of the study reveal that the concept of freedom in Ukraine has specific historical features, related to the ongoing struggle for national independence, and dynamically changes under the influence of external threats and internal political processes. It is determined that the limits of freedom are shaped not only by legal norms but also by ethical and societal factors that actively shape Ukrainian public discourse. Special attention is given to the existential dimension of freedom as responsibility, which manifests in complex moral choices in the context of war. The scientific novelty of the article lies in the combination of historical, legal, and existentialist approaches to understanding freedom in the context of Ukrainian democratic development, providing deeper insights into the relationship between freedom and responsibility during periods of social crises. The theoretical significance of the work lies in expanding the philosophical understanding of the category of freedom within the Ukrainian context, its interaction with legal and ethical norms, which is essential for further research in political philosophy and law.

Unveiling Agricultural Heritage: Mapping Historical Features in Farming Landscapes

ABSTRACT Agricultural heritage represents a unique fusion of natural and cultural elements, encompassing both tangible and intangible aspects that reflect the historical bond between humanity and the land focused on food production. Recognising its significance is vital, as it not only preserves tradition and expertise but also fosters sustainability and environmental resilience. While significant initiatives like Globally Important Agricultural Heritage Systems (GIAHS) are in place to safeguard remarkable agricultural areas with unique heritage values, frameworks for recognising the historic significance of non-outstanding agricultural areas are not sufficiently consolidated. Nonetheless, it is equally important to acknowledge the heritage value of agricultural systems that, while lacking exceptional features, succeed in preserving traditional techniques and processes, thereby conserving cultural landscapes and gastronomic identities. For this reason, this paper introduces a methodology for assessing the time depth of agricultural elements such as roads, livestock routes, agricultural plots, rural buildings and land use using historical cartography. By mapping historically significant features in farming areas, this method might be useful for recognising agricultural heritage and integrate it into spatial decision-making, ensuring the preservation of its cultural and environmental values. The method’s application is presented in a case study of Spain’s floodplains and irrigation areas near Aranjuez (Community of Madrid).

Chronobridge: a novel framework for enhanced temporal and relational reasoning in temporal knowledge graphs

The task of predicting entities and relations in Temporal Knowledge Graph (TKG) extrapolation is crucial and has been studied extensively. Mainstream algorithms, such as Gated Recurrent Unit (GRU) models, primarily focus on encoding historical factual features within TKGs, often neglecting the importance of incorporating entities and relational features during decoding. This bias ultimately leads to loss of detail and inadequate prediction accuracy during the inference process. To address this issue, a novel ChronoBridge framework is proposed that features a dual mechanism of a chronological node encoder and a bridged feature fusion decoder. Specifically, the chronological node encoder employs an advanced recursive neural network with an enhanced GRU in an autoregressive manner to model historical KG sequences, thereby accurately capturing entity changes over time and significantly enhancing the model’s ability to identify and encode temporal patterns of facts across the timeline. Meanwhile, the bridged feature fusion decoder utilizes a new variant of GRU and a multilayer perception mechanism during the prediction phase to extract entity and relation features and fuse them for inference, thereby strengthening the reasoning capabilities of the model for future events. Testing on three standard datasets showed significant improvements, with a 25.21% increase in MRR accuracy and a 39.38% enhancement in relation inference. This advancement not only improves the understanding of temporal evolution in knowledge graphs but also sets a foundation for future research and applications of TKG reasoning.

A secure and efficient data aggregation scheme for cloud–edge collaborative smart meters

Smart meters are part of the Advanced Measurement Infrastructure (AMI) system in the smart grid. It facilitates data transfer between consumers and electricity suppliers (ES). However, the mass deployment of smart meters (SM) brings heavy overhead to grid operation and poses serious privacy threats. To this end, this paper proposes a secure and efficient data aggregation scheme of cloud–edge collaboration smart meters. At first, we standardize the users’ historical electricity load features and use the improved K-Means clustering algorithm to calculate the Euclidean distance between feature vectors to obtain the classification results of users’ load features. On this basis, ES generates relevant parameters to encrypt meter data and protect users’ data privacy based on classification results. The aggregator (Ag) performs the data aggregation, generates the overall signature using the Schnorr aggregation signature method, and sends it to the cloud server (CS). The ES queries the CS to obtain data and parses it to realize the customer billing service. Meanwhile, this paper executes a series of experiments, and the results show that the proposed scheme exhibits significant advantages in privacy protection and system operation efficiency.

Globalisation and competitive strategies of firms in traditional manufacturing sectors of the West Midlands

In the context of globalisation, the sustainability of traditional manufacturing sectors depends on the ability of firms to modernise and diversify. To remain competitive against emerging economies in high-volume and low-technology areas, firms must engage in high-value manufacturing. This paper uses theoretical underpinnings from strategic management and place-based approaches to provide a historical account of competitive strategies of traditional manufacturing firms in the West Midlands region of the UK between 2010 and 2012 where the automotive, ceramics, glass and clothing sectors are examined. The research methodology is based on critical realist philosophy, which emphasizes an in-depth understanding of firm behaviour and acknowledges sensitivity to differences in decision-making. The paper highlights the complexity of competitive behaviour, which is influenced by enabling and constraining factors. While the evidence presented in the paper is from 2010 to 2012, it emphasizes the need for a participatory, farsighted, and proactive policy approach to retain the historic industrial character of the region.

Japan’s experience in organizing and promoting separate accumulation of municipal solid waste (MSW)

The article considers the Japanese system of municipal solid waste management as well as work with the population in the field of environmental education. The roles and responsibilities of the parties in the management of municipal solid waste are analyzed. In Japan, unlike other countries, the state is deeply involved in the process. Sorting and disposal of waste occur at the municipal level due to the historical characteristics of the Japanese society. Extended producer responsibility requires their participation from product development to disposal, and consumers are required to cooperate with them and local authorities by properly disposing solid waste.The regulatory framework in the field of MSW management is built around the Basic Act on Establishing a Sound Material-Cycle Society and the Law for Promotion of Effective Utilization of Resources, which formulates the 3R strategy, aimed at Reducing, Reusing, and Recycling of waste. An analysis of recently adopted documents, the Plastic Resource Circulation Act of 2021 in particular, demonstrates that special emphasis is placed on 2R: waste reduction and reuse, which is successfully achieved thanks to the high level of environmental awareness of Japanese citizens and thoughtful and multifaceted educational work with the population.Over the past decade, Japan has seen a steady reduction of municipal solid waste. However, while remaining one of the world leaders in the field, it is currently faced with a number of difficulties, such as a low recycling rate and a significant volume of incinerated waste. It is concluded that significant progress in this area is impossible without clearer goal setting for the volume of solid waste processing that would meet modern world standards.

Identity of Colonial Architecture Preservation in Thakhek City Center

This paper examines the conservation of colonial architecture in the center of Thakhek, which is a unique and historically significant feature of the city. Researching the historical context, architectural features and cultural values ​​of the buildings in the colonial era in Laos and efforts to conserve and promote them to become urban heritage. The research uses mixed methods, combining documentary research, observation from the field through surveys, measurements and interviews with local stakeholders. The findings reveal the challenges faced in preserving the colonial architecture at Thakhek, including limited resources. This research also highlights the potential benefits of preserving colonial architecture, such as promoting cultural tourism, promoting community pride and contributing to urban regeneration. The study concluded with recommendations to strengthen the preservation of colonial architecture in the center of Thakhek, emphasizing the need for a comprehensive preservation plan, increasing public awareness and cooperation between local stakeholders. This research contributes to the broader discussion on heritage conservation in Southeast Asia, offering insights into the challenges and opportunities of preserving colonial architecture in old urban areas in a context of rapid urban development.

Temporal Variability of Hydroclimatic Extremes: A Case Study of Vhembe, uMgungundlovu, and Lejweleputswa District Municipalities in South Africa

The current study investigated hydroclimatic extremes in Vhembe, Lejweleputswa, and uMgungundlovu District Municipalities based on streamflow data from 21 river gauge stations distributed across the study site for the period spanning 1985–2023. Statistical metrics such as the annual mean and maximum streamflow, as well as trends in annual, maximum, seasonal, and high/low flow, were used to evaluate the historical features of streamflow in each of the three district municipalities. Moreover, the Standardized Streamflow Index (SSI) time series computed from streamflow observations at 3- and 6-month accumulation periods were used to assess hydroclimatic extremes, including drought episodes, proportion of wet/dry years and trends in SSI, drought duration (DD), and drought severity (DS). The results indicate that the three district municipalities have experienced localized and varying degrees of streamflow levels and drought conditions. The uMgungundlovu District Municipality in particular has experienced a significant decline in annual and seasonal streamflow as well as an increase in drought conditions during the 38-year period of analysis. This is supported by the negative trends observed in most of the assessed metrics (e.g., annual, maximum, seasonal, low/high flow, and SSI), whereas DD and DS showed positive trends in all the stations, suggesting an increase in prolonged duration and severity of drought. The Lejweleputswa District Municipality depicted positive trends in most of the assessed metrics, suggesting that streamflow increased, whereas drought decreased in the region over the 38-year period of study. Moreover, the Vhembe District Municipality experienced both negative and positive trends, suggesting localized variations in dry and wet conditions. The results presented in this study contribute towards drought monitoring and management efforts in support of policy- and decision-making that aim to uplift water resources management and planning at local and district municipality levels.

Visual Quality Analysis of Diyarbakır Sur District's Historical Buildings and Surroundings

Historical sites are structures, monuments, or areas that carry the traces of the past and hold significant importance in the collective memory of society. The cultural, historical, and architectural value of historic places is important for visual perception. Visual quality analysis aims to assess the physical condition and appearance of these historic places and to identify their conservation and maintenance needs. This analysis plays an important role in the decisions to be taken for the preservation of the place. The parameters that influence visual quality reflect the preservation and maintenance of the place, the visitor experience, the importance of cultural heritage for conservation, tourism and economy, and social awareness. Visual perception of historic places refers to how people perceive these places and how this perception is associated with the historical, cultural, and architectural features of the place. The visual perception of historic places may vary depending on various factors. The visual perception of historic places is important for their preservation, visitor experience and the continuation of cultural heritage. While a positive visual perception of historic places can make them more valuable and important in society, a negative perception can damage their reputation and make it difficult to preserve them. For this reason, the visual perception of historical places is an important factor that should be taken into account in determining conservation and maintenance strategies and in the promotion of places. In this study, thirty historical places in Diyarbakır Sur District were evaluated by 10 experts according to visual quality parameters. As a result, with the scores obtained in the visual perception of historical places, suggestions were made for the protection of these places, their importance in terms of tourism and the continuation of cultural heritage.

Small Historical Centres and Their Connection with The Landscape: Fragility and Complexity in Italian Contexts

This paper addresses the issues of fragility and complexity of small towns, particularly regarding the Italian case. Results define a possible conjunction between the landscape historical characteristics and the creation of circuits for the usability of smaller centres that can be connected to each other, based on their features. A prototype schedule, including GIS elaboration, is the novel proposal illustrated in the paper: it derives from the investigation carried out within the Working Group of the Italian Ministry of Culture, aimed at defining a Charter for Small Villages. The approach innovativeness consists in the comparison methodology between different landscape units that can also be extended to similar cases, defined on the basis of the involved factors matrix.

Multimodal vehicle trajectory prediction and integrated threat assessment algorithm based on adaptive driving intention

As autonomous driving and connected communication technologies advance swiftly, vehicle trajectory prediction has become increasingly significant. The motion of a vehicle is contingent not only on its historical trajectory but is also subject to the influence of surrounding vehicles, thereby exhibiting intricate social and temporal interdependencies. Furthermore, the inherent randomness and uncertainty in driver behavior render vehicle trajectory prediction inherently multimodal, a factor that is frequently neglected in current research. Against this backdrop, a multimodal vehicle trajectory prediction (MTP) model based on an encoder-decoder architecture is proposed to hierarchically extract historical features of vehicles. The model consists of five key components: temporal feature encoder module, spatial interaction module, spatial-temporal dependence module, driving intention fusion module and multimodal trajectory output module. Experiments on the NGSIM dataset show that the predictive performance of the model has been improved to varying degrees, especially at 3–5 s, where the improvement is more significant. Compared with state-of-the-art models, the Root Mean Square Error (RMSE) error at 5 s time horizon is 3.38 m on NGSIM dataset, which represents a 25 % improvement. To measure the safety of predicted trajectories, we propose a comprehensive threat assessment model that combines collision time (TTC), headway (TH) and time to lateral collision (TLC) metrics based on safe distance theory. This model not only evaluates the longitudinal collision threat in the following state, but also evaluates the lateral collision threat during driving maneuvers in multi lane scenarios, thereby comprehensively improving the safety of vehicle driving. This research also offers new perspectives and insights for the development of autonomous driving.

Reconsideration of educational directions for ensuring the national security of Ukraine

The article emphasises that at the level of the basic National Security Strategy of Ukraine, one of the key directions of ensuring the national security of Ukraine is the development of human capital, including through the prism of modernisation of education. At the same time, the very essence of human capital is not fully disclosed at the level of other programme documents and legislative acts of Ukraine, which causes difficulties in the practical implementation of this direction and the identification of the central executive body responsible for such activities. In view of this, the category of human potential should not be declarative, but actually embodied in the national legislation, with priorities for its development and criteria for its assessment, including in the educational sphere. According to the article, a person in the modern world is faced with a large amount of diverse information, which in the context of the Russian-Ukrainian war is often distorted by enemy propaganda, information operations and cyber attacks. In such circumstances, the importance of the so-called information hygiene increases, which is formed mainly through educational tools, such as trainings, educational courses, programmes, etc. In the course of implementing the educational direction of ensuring national security, the unacceptability of the narratives proposed by enemy propaganda can be guaranteed in the minds of the population by developing human cognitive abilities, as well as forming a comprehensive understanding of historical, state-building processes, political and socio-economic features, the distortion of which is the basis of enemy information and psychological operations. In addition, the emphasis is placed on the fact that the educational component of ensuring the national security of Ukraine is also to promote maximum individualisation of the education process, formation of an individual educational trajectory of an applicant for education, including through artificial intelligence technologies.

MECP2 Variants in Males: More Common than Previously Appreciated

BackgroundTo assess the age and MECP2 variants of recently identified males and set the stage for further study of clinical features in males. MethodsGenetic information on the specific MECP2 variant was acquired from the coordinator (K.F.) of the Parent Group for Males. Data were collected indicating whether these variants were de novo or transmitted from the mother and whether males who appeared to meet the diagnostic criteria for Rett syndrome had mosaicism for the MECP2 variant. ResultsFifty-nine males were identified through the parent group. Their ages ranged from 2 to 28 years, with the median age being 7.0 years and the mean age being 10.8 years. Of these variants, 46 (78.0%) were de novo, nine (15.3%) were maternally inherited, and for four (6.8%) inheritance was not known. Eleven (18.6%) were mosaic, 10 with somatic mosaicism and one with Klinefelter syndrome (47XXY). Together with males reported previously from the US Natural History Study, the total group represents 85 males, of whom 27 are deceased. ConclusionsThese data on males with MECP2 variants are important to caregivers, physicians, and researchers to begin to characterize their historical and clinical features, improve diagnostic recognition and overall care, and accelerate access to therapeutic studies including gene replacement strategies. Equal access to such therapies for males is critical.

Semi-supervised prediction method for time series based on Monte Carlo and time fusion feature attention

Accurate and reliable forecasting of time sequences is a challenging task in cyber–physical systems (CPS). Traditional time series prediction models struggle to provide accurate predictions for diverse types of time series data, especially with missing data due to variations in scale, types, and the complexity of real-world production environments. In this paper, we introduce a hybrid model named Temporal Feature Fusion Attention-based Monte Carlo Semi-supervised Long Short Term Memory (LSTM) network to address this issue. The model encodes the current state and historical information using a current time feature state vector. It then calculates the hidden feature vectors for the time series at different time points (past, present, and future), as well as for the current Monte Carlo filtering sequences. This approach leverages the correlation of time series features, transfers and fuses crucial historical features within the sequence with the optimized sequence feature information from the Monte Carlo algorithm. Our experiments confirm that with 10% of labeled data missing, our proposed method significantly improves the evaluation metric Mean Absolute Percentage Error (MAPE) by 17.827% compared to the baseline LSTM model. Moreover, our method surpasses other state-of-the-art methods across four distinct time series datasets, achieving the best prediction results.