Historical Time Research Articles

Refining Travel Suggestions using Python

In the era of personalized travel experiences, the need for intelligent and adaptive planning tools is paramount. This is developed using Python, harnesses the power of machine learning to analyse traveller preferences and patterns, offering customized destination suggestions. The core of this study is to demonstrate how machine learning can transform traditional travel planning into a more efficient, personalized experience. By integrating user data and preferences, the system proposes itineraries that not only align with individual interests but also enhance the overall travel experience. This details the development process, the machine learning techniques employed, and the efficacy of Python in creating a dynamic and responsive travel planning website. The goal is to enhance the user experience in planning trips by providing optimizing destination suggestions, considering factors like historical preferences, budget constraints, and time availability.

Geohazard features of the Tyrrhenian Calabria

ABSTRACT This paper accompanies the Maps of Geohazard features of the Cilento and the Calabro-Tyrrhenian continental margin in the southern Tyrrhenian Sea (Italy). The main geohazard-related features were derived from extensive seafloor mapping through the collection of high-resolution multibeam data acquired during several oceanographic cruises. They encompass many fluids seepage features, fault scarps, landslides scars, gullies, channels, and canyons. Hazards related to coastal landslides and shelf-indenting canyons are very high in these sectors (especially in southern Calabria) due to active seismicity coupled with rapid uplift, high sedimentation rates and narrow or totally absent continental shelf, thus promoting a direct connection between steep slopes and coastal areas. In this setting, mass-wasting features can directly impact coastal or submarine infrastructures or indirectly create local tsunami waves, as observed in historical times. Moreover, this physiographic setting of the margin facilitates the transfer of marine litter toward deep-sea areas.

Возможные миры художественного текста: когнитивно-семантический аспект репрезентации времени (на материале романа В.В. Орлова «Альтист Данилов»)

This article studies the temporal organization of a literary text from the standpoint of a cognitive semantic approach. Literary time is considered in close connection with the meanings that form the semantic space of a text. The correlation of events within which literary time is manifested shows the direction of literary time, which, in its turn, participates in the formation of thinkable worlds. The study aimed to determine and describe the features of the construction of thinkable worlds within the literary time semantically marked in a literary text. The practical significance of the research lies in identifying and describing the principles of structuring possible worlds by means of their temporal coordinates, representing a synthesis of a hero’s physical and psychological time, with the inclusion of markers of historical time in the semantic space of a literary text. The author studied V.V. Orlov’s novel Danilov, the Violist using the inductive-deductive and comparative methods, cognitive and semantic analysis, as well as philological interpretation. A conclusion is drawn that literary time in this novel is of great importance for the organization of thinkable worlds. Its most frequent markers are segodnya (‘today’) and teper’ (‘now’), lexicalizing the cognitive and semantic features of a world which reminds the reader of objective reality, albeit distant in historical time, as well as of a fantasy world, whose properties are unreal. Orlov creates a synthesis of the hero’s physical and psychological time, which can also include historical time (in that case, the reader’s background knowledge is involved, making it possible to correctly decode precedent phenomena). The semantics of literary time in the novel is hierarchical and systemic: textual representatives manifest both universal ideas about time and author’s individual variability in the perception of chronological intervals, which affects the emotional sphere of the reader.

OSL dating of very young aeolian sediments of NW Spain to assess dune erosion and accretion periods

Optically stimulated luminescence (OSL) ages of young coastal dune ridges have allowed getting more knowledge on the deposition, erosion and evolution of coastal dune systems in Northern Europe during historical times. However, there is a lack of knowledge of the evolution of the same systems in SW Europe. The studies published in the last years about fossil dunes in NW Spain have allowed the reconstruction of the coastal evolution of this area from the Marine Isotopic Stage (MIS 8) until the Middle Holocene. However, there is still a poor knowledge for the Late Holocene and namely the last centuries. Dating young sediments is challenging due to the low signal to noise ratio of the natural OSL signal and because young samples are very sensitive to thermal transfer or partial bleaching of the luminescence signal during transport. In the last century, erosion and accretion events are better known because remote sensing methods allowed to model some coastal dune systems. However, OSL dating has also been particularly useful in NW Europe to get a better knowledge on the coastal dune evolution. In this work, seven samples from dune ridges and a climbing dune of a coastal system in Playa de Trece (NW Spain) were dated by OSL, as they record the last accretion events occurred in the last two centuries, and above all the 20th Century. For assessing the ages we have compared the results from both parametric central age models and Bayesian statistic using R package BayLum.

Technological progress in Russian military sports suits: the history of the use of materials and fabrics from the end of the 19th century to the beginning of the 21st century

The subject of the study is technology in military sports suits of Russian military personnel. The object of the study is the progress in the production technologies of military sports suits. The author examines in detail the history of the use of various materials and fabrics for the production of military sports suits, from the end of the 19th century to the beginning of the 21st century. Special attention is paid to the analysis of the properties of various materials. The author shows that fabrics with high strength, wear resistance and good breathability are most suitable for military sports suits of Russian servicemen. The fabrics used for the production of military uniforms must meet a number of requirements. At the same time, such properties of fabrics as crease, drapery, hydroscopicity, dust capacity, heat-shielding properties, shrinkage, thread shedding, thread expansion in seams, sliding should be taken into account. The main research methods were theoretical methods – the method of analysis, generalization, systematization, classification of literary sources on the research topic. The novelty of the research consists in a comprehensive analysis of the basic properties, characteristics and requirements for fabrics used for the manufacture of military suits. A retrospective analysis and comparison of costumes from different eras were carried out. The main conclusion of the study is that from the end of the 19th century to the 21st century, the use of fabrics for military clothing has undergone significant changes. It is shown that at the end of the 19th century, military clothing was mainly made from natural fabrics such as cotton, wool and linen. With the advent of synthetic fibers in the 20th century, fabrics became more durable, lightweight, quick-drying and resistant to external factors. In the 21st century, with the development of fabric production technologies for military clothing, special mixtures of natural and synthetic fibers, as well as membrane materials, began to be used to provide high protection, comfort and functionality for military personnel. The author's special contribution to the study is the generalization of the results of various studies, the comparison of the main characteristics of fabrics used in various historical times with modern fabrics and materials.

Identifying archived insect bulk samples using DNA metabarcoding: A case study using the long‐term Rothamsted Insect Survey

AbstractInsect populations are declining in many parts of the world, but a lack of long‐term monitoring data is impeding our ability to understand and mitigate the causes of insect biodiversity loss. Whilst high‐throughput sequencing (HTS) approaches, such as DNA metabarcoding, have the potential to revolutionize insect biomonitoring through rapid scalable identification, it is unclear to what extent HTS can be applied to long‐term stored insect samples. Archived insect samples could inform forecasting and provide valuable information regarding past changes to biodiversity. Here, we assess the efficacy of DNA metabarcoding to identify archived samples from the longest passive monitoring scheme in the United Kingdom: the Rothamsted Insect Survey (RIS). With a focus on aphids as the target taxa of a national network of suction‐traps, we analyze a 16‐year time‐series of stored samples (2003–2018) using DNA metabarcoding from one of the RIS suction traps as an exemplar. We achieved this by using a non‐destructive DNA extraction protocol, ensuring the integrity of archival samples for further studies. We compared the identities of aphids determined by both metabarcoding (as inferred amplicon sequence variants [ASVs]) and morphological identification and found that metabarcoding detected most genera with varying success (mean > 76%). When comparing the two methods objectively (i.e., including taxa not detected morphologically), however, congruence decreased (51%). We show that minimum sequence copy thresholds can minimize metabarcoding false positives, but at the expense of introducing false negatives, highlighting the need for careful data curation. Detectability of taxa identified morphologically and similarity between the two methods did not significantly vary over time, demonstrating the viability of metabarcoding for screening archival samples. We discuss the advantages and challenges of metabarcoding for insect biomonitoring, particularly from archival samples, including improvements to sample handling, processing, and archiving. We highlight the wider potential of HTS approaches for stored samples from insect monitoring schemes, unlocking the immense potential of global historical time series.

Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti

Abstract. Haiti, a Caribbean country, is highly vulnerable to hydroclimatic hazards due to heavy rainfall, which is partly linked to tropical cyclones. Additionally, its steep slopes generate flash floods, particularly in small catchments. Moreover, the hydrology of this region remains poorly understood and understudied. Unfortunately, there is no accessible database for the scientific community to use in this country. To fill this gap, hydroclimatic data were collected to create the first historical database in Haiti. This database, called Simbi (guardian of rivers, freshwater, and rain in Haitian mythology), includes 156 monthly rainfall series over the period 1905–2005, 59 daily rainfall series over the period 1920–1940, 70 daily streamflow series, and 23 monthly temperature series, not necessarily continuous, over the period 1920–1940. It also provides simulated streamflow series over the period 1920–1940 using the GR2M and GR4J rainfall–runoff models for 24 catchments and 49 attributes covering a wide range of topographic, climatic, geological, land use, hydrogeological, and hydrological signature indices. Simbi is the first open-access hydro-meteorological dataset for Haiti and will contribute to a better knowledge of hydrological risk in Haiti. Several sources of uncertainty associated with Simbi are acknowledged, including data quality (historical data), digitisation of paper archives, identification of relevant rain gauges, and rainfall–runoff models. It is important to consider these uncertainties when using Simbi. The database will be regularly updated to include additional historical data that will be digitised in the future. It will thus contribute toward better knowledge of the hydrology of Haitian catchments and will enable the implementation of various hydrological calculations useful for designing structures or flow forecasting. Simbi is an open-access database and is available for download at https://doi.org/10.23708/02POK6 (Bathelemy et al., 2023).

Research on E-Commerce Retail Demand Forecasting Based on SARIMA Model and K-means Clustering Algorithm

With the rapid development of e-commerce, precise demand forecasting and efficient inventory management have become essential for the success and profitability of retail businesses. This study focuses on demand forecasting for e-commerce retailers using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model and the K-means clustering algorithm. The research utilizes a dataset containing 1996 time series of sales data from various products, merchants, and warehouses, aiming to predict demand changes for the next 15 days. The study initially evaluates three models—Linear Regression (LR), Autoregressive Integrated Moving Average (ARIMA), and SARIMA—by fitting them to historical sales data to forecast future demand. The SARIMA model is identified as the most effective through rigorous evaluation using 1-mWAPE (mean weighted absolute percentage error) and RMSE (root mean square error) metrics. To enhance homogeneity within demand categories, the K-means clustering method is applied to divide products into four distinct groups, further refining the forecasting process.The paper also addresses the challenge of integrating new sequences into the dataset by leveraging clustering results to classify sequences and using cosine similarity to identify analogous historical time series. These matched sequences serve as the basis for demand prediction using the established SARIMA model. The findings highlight the robustness of the SARIMA model in capturing trends and seasonality, providing a reliable framework for e-commerce demand forecasting that can significantly impact inventory strategies and operational efficiency.

Forecast of coal consumption in salt lake enterprises based on temporal gated recurrent unit network with squeeze-and-excitation attention

Accurate coal consumption forecasting is key to improving energy supply efficiency and strategic planning. However, current forecasting methods mainly emphasize temporal variations, ignoring key influencing factors such as seasonality and environmental changes. In addition, the complex structure of neural networks complicates the selection of ideal hyperparameters. To address these issues, this study proposes a novel squeezing-and-excitation temporal gated recurrent unit (SE-TGRU) method. By incorporating squeezing-and-excitation attention modules, this method autonomously assesses the relative significance of diverse historical time points, unveiling their correlations to capture essential information about coal consumption. Notably, a novel reverse learning-based dwarf mongoose optimization (RL-DMO) algorithm is devised to comprehensively analyze data within a specified time window. This augmentation enhances the ability of the model to discern data anomalies with heightened sensitivity, enabling corresponding adjustments during the training process. Finally, the efficacy of the proposed method in coal consumption forecasting is verified through extensive experimentation using actual data sourced from the procurement department of a salt lake enterprise. The experimental results demonstrate that the proposed method exhibits an 11 % improvement in the R-squared (R2) indicator and an 18 % reduction in the root mean square error (RMSE) compared to the baseline method.

The Revelations of Blessed Angela — the problem of authorship of visions

The book "Revelations of Blessed Angela" ("The Phenomenon of the gifts of the Almighty sent down in the Spirit of Blessed Mother Angela of Foligno", hereinafter — "Revelations...") as a historical source attracts very little attention in Russian literature, and in Western literature all research is focused around the religious component of revelations, the cult of the personality of God. Angela and the questions of finding the unknown and mystical in her visions. For some, bl. Angela is a real saint, for others she is a woman who suffered from hysteria, and all her visions are the fruit of a sick fantasy.The work analyzed the first two parts of the book "Revelations..." by bl. Angela, which are key to understanding the teaching. The experience described in the chapters on visions is closely related to the problem of authorship. Solving the issue of authorship may provide an opportunity to take a fresh look at historical time and similar works. It is proposed to consider the book as evidence of an attempt to create a cult of the holy new formation, which turned out to be very successful: under the developed doctrine of salvation, the life of the saint was compiled, who directly accepted divine revelations, fully confirming the views of certain groups of spirituals in the Franciscan order.

Next step in Monachacantiana (Montagu, 1803) phylogeography: northern French and Dutch populations (Eupulmonata, Stylommatophora, Hygromiidae).

Features of shell and genitalia as well as nucleotide sequences of selected mitochondrial and nuclear genes of specimens of Monachacantiana from ten northern French and two Dutch populations were compared with the same features of British and Italian populations. They were found to be very similar to populations previously identified as belonging to the CAN-1 lineage of M.cantiana. This confirms previous suggestions that M.cantiana was introduced to western Europe (England, France and the Netherlands) in historical times.

Historical charcoal production as a factor in soil cover heterogeneity in a fluvioglacial landscape − A case study from northern Poland

Although in situ wood thermal processing, as a common practice in European forests in historical times, has been confirmed in many studies, the environmental implications of that process remain poorly explored. In this study, we focused on evaluating the impact of that process on forest vegetation and soil cover heterogeneity in a fluvioglacial landscape dominated by Brunic Arenosols. This study covered three 70–95-year-old stands of Scots pine in northern Poland. Three soil profiles, including from the relict charcoal hearth (RCH), from the surrounding ditch and a control, were examined from each stand, as well as associated vegetation. The studies showed that 19th century charcoal production platforms were overgrown with 20–60% fewer plant species than control stands. The effect on soils varied according to their characteristics. The presence of anthropogenic horizons consisting of a mixture of burnt soil material, ashes, charcoal particles, and other products of wood pyrolysis was the most distinguishing feature of RCH soils classified as Spolic Technosols (Arenic, Dystric, Pyric, Protospodic, Transportic). Typically, these horizons were characterised by lower bulk density, and higher porosity, as well as higher contents of total organic carbon, nitrogen, and exchange cations than the control soils. The differences between the RCH and control soils were highlighted by a comparison between the pools of the components in a soil column (pedon). Clear tendencies were not recorded for pH, the phosphorus content and stocks, the forms of iron and aluminium, the saturation of the soil sorption complex with bases or the trophic index. This may be due to the long-term neutralising effect of forest vegetation, dominated by Scots pine. Moreover, the results of our study may indicate the problem of toxicity of the RCH soils, which should be undertaken, considering the utilitarian importance of the issue.

Let us move forward: Comment on “are generations a useful concept?”

Generational labels (e.g., Millennials and Baby Boomers) are widely used in daily life to represent the unique characteristics of groups of people. However, the existence of generational differences remains contentious. In their focal paper, Costanza et al. (2023) critically reviewed the literature on generational differences and proposed two future research directions: the social constructionist and lifespan development perspectives. In this commentary, we aimed to extend the proposed directions for future research on generational differences by integrating the two perspectives into one theoretical framework. Future research should investigate how proximal social relationships (e.g., intergenerational relations) and distal social norms (e.g., age norms) change over historical time and whether these historical changes shape individuals' development and aging. The theoretical framework that integrates the two proposed research directions may stimulate research on generational differences to progress beyond the concept of generations.

Co-occurrence order-preserving pattern mining with keypoint alignment for time series

Recently, order-preserving pattern (OPP) mining has been proposed to discover some patterns, which can be seen as trend changes in time series. Although existing OPP mining algorithms have achieved satisfactory performance, they discover all frequent patterns. However, in some cases, users focus on a particular trend and its associated trends. To efficiently discover trend information related to a specific prefix pattern, this paper addresses the issue of co-occurrence OPP mining (COP) and proposes an algorithm named COP-Miner to discover COPs from historical time series. COP-Miner consists of three parts: extracting keypoints, preparation stage, and iteratively calculating supports and mining frequent COPs. Extracting keypoints is used to obtain local extreme points of patterns and time series. The preparation stage is designed to prepare for the first round of mining, which contains four steps: obtaining the suffix OPP of the keypoint sub-time series, calculating the occurrences of the suffix OPP, verifying the occurrences of the keypoint sub-time series, and calculating the occurrences of all fusion patterns of the keypoint sub-time series. To further improve the efficiency of support calculation, we propose a support calculation method with an ending strategy that uses the occurrences of prefix and suffix patterns to calculate the occurrences of superpatterns. Experimental results indicate that COP-Miner outperforms the other competing algorithms in running time and scalability. Moreover, COPs with keypoint alignment yield better prediction performance.

Geochemical Evolution in Historical Time of Thermal Mineral Springs at Campetti Southwest (Veii, Central Italy) through Geoarcheological Investigation

A multidisciplinary study, involving hydrogeological, geochemical, and mineralogical analyses, was conducted to define the evolution of thermal mineral springs in the Sabatini Volcanic District (SVD) (Central Italy) in a historic period. The outcomes were integrated with the archeological findings to improve the knowledge of the evolution of Veii, a settlement established since the Iron Age and later expanded by Etruscans and Romans. During the archeological excavations, water-related buildings were identified, especially at the Campetti Southwest site in the Veii settlement. Votive inscriptions also suggest the presence of buildings linked to sacred waters, even if a clear definition of the source and type of water is missing. In the SVD, some low-flow thermal mineral springs are present as a result of the mixing of thermal and CO2-rich groundwater from the deep carbonate aquifer and the cold, shallow volcanic aquifer. Mineralogical and chemical analyses characterized the travertine and Fe-hydroxide deposits on Roman tanks and walls in Campetti Southwest and in a nearby ancient Roman bath along the Valchetta River. These deposits showed different relative concentrations of sedimentary and volcanic-related elements, testifying a geochemical evolution of the groundwater mixing and the presence of a paleothermal mineral spring in Campetti Southwest.

History and Humor

Arguably, Monty Python’s The Life of Brian is one of the most controversial interpretations of Christ’s story, due to the Pythons’ shrewd, satirical sense of humor and the film’s mockery of the historical public’s admiration and obsession with messianic figures. This paper takes a similar stance to scholars who argue, however, that the film is not blasphemous—it does not mock Christ himself. The argument hinges on the distinction between Christ and Brian. In separating Christ and Brian into two figures, the film operates on another level, allowing viewers to experience the rise of a messianic figure through Brian as well as introducing them to the historical context. Therefore, though ostensibly not about Christ, The Life of Brian provides insight into the historical time period of Christ and can be beneficial for those interested in furthering their understanding of Christ’s story.

Spatiotemporal Patterns in the Urban Heat Island Effect of Several Contemporary and Historical Chinese “Stove Cities”

Various cities in China have been identified as “stove cities” either in contemporary or historical times, exposing residents to extremely high temperatures. Existing studies on the heat island effect in stove cities are not representative nationwide. The outdated nature of these studies also significantly diminishes the relevance of their findings. Thus, reassessing the urban heat island (UHI) effect of stove cities is necessary in the context of global climate change and urbanization. This study focuses on seven symbolic and geographically distributed stove cities in China, including Nanjing, Chongqing, Wuhan, Fuzhou, Beijing, Xi’an, and Turpan. Using land surface temperature (LST) data, this study investigates the summer heat island effect from 2013 to 2023 and analyzes changes in the spatial distribution of the heat island effect. This paper utilizes impervious surface data and urban clustering algorithms to define urban and suburban areas. It then examines the evolution and spatial distribution of surface urban heat island intensity (SUHII) over time. Incorporating urbanization variables like population density and urban area, the study analyzes the main factors affecting the heat island effect from 2013 to 2018. We find that all cities continuously expand, with the annual average heat island effect intensifying over the years. With the exception of Beijing, the summer heat island or cool island effects in the remaining six cities show an overall intensification trend. From 2013 to 2018, SUHII has been primarily related to urban expansion and planning layout, with minimal impact from factors such as population density.

Robust multi-scale time series prediction for building carbon emissions with explainable deep learning

Accurate prediction dramatically enhances the effectiveness of carbon emission control, making it a valuable tool for achieving decarbonization goals. In this work, we propose a robust explainable encoder-decoder deep learning method for predicting multi-scale short-term carbon emissions and feature importance analysis to predict buildings’ emission patterns accurately. In the encoder, the initial inputs are transformed into a sequence to capture the time series and spatial information, where the model predicts the building emissions with an attention mechanism in the decoder. The hybrid model is trained and validated with a multi-scale dataset collected from a university. Results reveal that (1) After considering the buildings’ interactions, the R2 values regarding individual building emissions predictions are 0.943, 0.938, 0.941, and 0.943, respectively, climbing to 0.952, 0.943, 0.943, and 0.950. (2) Benefiting from the proposed model’s structure, the constructed model can accurately predict the community’s emissions with the R2 equal to 0.952 and keep excellent robustness after adding the white Gaussian noise data with all R2 are above 0.919. (3) The historical hourly emissions, outdoor humidity and time of day are considered the most essential factors responsible for the building emissions. The novelty of this work lies in the multi-scale building emissions prediction that is conducted by the developed hybrid model simultaneously considering the impact of environmental factors and building interactions, allowing us to expand the model’s application scenarios and provide valuable references for decarbonization decision-making.

Historical Time and Acceleration. A Constitutive Bond

Abstract This manuscript addresses the link between the concept of ‘historical time’ and the thesis of the acceleration of history and society in constitutive terms. ‘Historical time’ is used as concept mainly from the eighteenth century and corresponds to a way of understanding the contemporary world as a moment in which a ‘chronology’ of time and, along with it, the appearance of a temporalized history itself, take place. Different temporal schemes support this transition: a pass from synchronicity to diachrony, the transition from iteration to the ‘event’, circularity to the linearity. In what follows, I propose to observe some implications and articulations of the ‘historical time’ and ‘social acceleration’ theses, advancing the hypothesis that they are both connected and mutual dependent.

HWWI Commodity Price Index: A Technical Documentation of the 2023 Revision

Abstract The HWWI Commodity Price Index, which aims at reflecting price developments of raw materials imported by highly industrialized countries, dates back to the 1950s. This paper explains the calculation of the index at the example of its latest revision, which became effective on 1st September 2023. While the index and its subindices are still calculated for OECD and European Momentary Union countries at four different frequencies (annual, monthly, quarterly and daily) for two different currencies (USD, EUR), it now additionally includes index values for several weighting periods (long-term: 2012–2021, pre-crisis: 2017–2019 and crisis years: 2020–2021), for individual countries and for different perspectives (daily revised, real-time and historical time series). The paper also provides detailed information on the employed methodology and the input data (commodities, import data, prices) used to calculate the weights and the index values. Although the revision is not without effect on the resulting index values, especially throughout the crises periods, the correlation between the initial and the revised index remains very high.