Temporal Point Of View Research Articles

Soil Salinity Inversion Based on a Stacking Integrated Learning Algorithm

Soil salinization is an essential risk factor for agricultural development and food security, and obtaining regional soil salinity information more reliably remains a priority problem to be solved. To improve the accuracy of soil salinity inversion, this study focuses on the Manas River Basin oasis area, the largest oasis farming area in Xinjiang, as the study area and proposes a new soil salinity inversion model based on stacked integrated learning algorithms. Firstly, we selected four machine learning regression models, namely, random forest (RF), back propagation neural network, support vector regression, and convolutional neural network, for performance evaluation. Based on the model performance, we selected the more effective RF and BPNN as the basic regression models and further constructed a stacking integrated learning model. This stacking integration learning model improved the prediction accuracy by training a secondary model to fuse the prediction results of these two basic models as new features. We compared and analyzed the stacking integrated learning model with four single machine learning regression models. Findings indicated that the stacking integrated learning regression model fitted better and had good stability; on the test set, the stacking integrated learning regression model showed a relative increase of 8.2% in R2, a relative decrease of 14.0% in RMSE, and a relative increase of 6.5% in RPD when compared to the RF model, which was the single most effective machine learning regression model, and the stacking model was able to achieve soil salinity inversion more accurately. The soil salinity in the oasis areas of the Manas River Basin tended to decrease from north to south from 2016 to 2020 from a spatial point of view, and it was reduced in April from a temporal point of view. The percentage of pixels with a high soil salinity content of 2.75–2.80 g kg−1 in the study area had decreased by 19.6% in April 2020 compared to April 2016. The innovatively constructed stacking integrated learning regression model improved the accuracy of soil salinity estimation on the basis of the superior results obtained in the training of the single optimal machine learning regression model. As a consequence, this model can provide technological backup for fast monitoring and inversion of soil salinity as well as prevention and containment of salinization.

The Story of Czech Anarchism: Ideas and Practices of Czech Libertarians, 1883‐1930

The rich history of Czech anarchism is not well-known internationally. The movement was comprised of thousands of proletarians (especially Northern Bohemian miners) and some important poets. It ended in a surprising and original way with the formation of an anarchist political party in 1914. This led to participation in national governments between 1918 and 1922. To explain the dynamics, the article narrates five separate stories of the Czech anarchism. After a summary recounting the development of the Czech anarchist movement from a temporal and spatial point of view, it examines ideas about the individual and society, organisational forms and organisations, and, finally, the national question, gender, and direct action.

Hemchandra Goswami’s Beloved’s Letter and William Shakespeare’s Sonnet 116: A Comparative Analysis

Hemchandra Goswami (1872-1928), representing a vibrant voice- being one amongst the Romantic-trio of Jonaki Era of Assamese literary world establishing a new spirit and William Shakespeare (1564-1616), the greatest dramatist and poet of the Elizabethan Age of British literary world predicate ample scope to investigate exploring various literary aspects though belonging to diverse world spatially and temporally. So, here in this research paper it is endeavoured to make a comparative analysis of the two poets considering chiefly the dominant thematic aspect of love along with stylistic aspects characterizing the poetic world of both the poets like style and form with reference to the two specific poems Hemchandra Goswami’s Priyotomar chithi translated as The Beloved’s Letter and Shakespeare’s Sonnet 116. The passion of love emanates from human heart as spontaneous expression and therefore its literary manifestation is very obvious in any genre of literature-whether it is poetry, novel, drama, short story or any other. The theme of love has a universal appeal- from temporal point of view, this theme is found in the creations of any age as well as its prominence in the creations of all literary manifestations irrespective of space such as in British, American, Indian, Assamese etc. Moreover, Hemchandra Goswami’s The Beloved’s Letter is regarded as the first Assamese sonnet and Shakespeare’s sonnets have always been widely acclaimed and acknowledged as the classic creation. So, understanding of the two sonnets belonging to diverse space and time would be an impelling force to negotiate the ideas impartially and scientifically which may have a substantial bearing on the existing knowledge. Thus, this paper is an attempt to make a comparative analysis of these two literary stalwarts exploring the literary realm of Hemchandra Goswami and William Shakespeare particularly taking into account The Beloved’s Letter by Hemchandra Goswami and Sonnet 116 by William Shakespeare.

Weakly Supervised Monocular 3D Object Detection by Spatial-Temporal View Consistency.

Monocular 3D object detection plays a crucial role In the field of self-driving cars, estimating the size and location of objects solely based on input images. However, a notable disparity exists between the training and inference of 3D object detectors. This discrepancy arises because during inference, monocular 3D detectors depend solely on images captured by cameras; while during training, these methods require 3D ground truths labeled on point cloud data, which is obtained using specialized devices like LiDAR. This discrepancy creates a break in the data loop, preventing the feedback data from production cars from being utilized to enhance the robustness of the detectors. To address this issue and establish a connection in the data loop, we present a weakly-supervised solution that trains monocular 3D object detectors solely using 2D labels, eliminating the requirement for 3D ground truths. Our approach considers two view consistency: spatial and temporal view consistency, which play a crucial role in regulating the prediction of 3D bounding boxes. Spatial view consistency is achieved by employing projection and multi-view consistency techniques to guide the optimization of the target's location and size. We leverage temporal viewpoint consistency to provide temporal multi-view image pairs, and we further introduce temporal movement consistency to tackle the challenge of dynamic scenes. With only 2D ground truths, our method achieves comparable performance to fully supervised methods. Additionally, our method can be employed as a pre-training method and achieves significant improvement when fine-tuned with a small proportion of fully supervised labels.

THE SPECIFICITY OF THE FUNCTIONING OF POLYPHONIC ELEMENTS AT THE NARRATIVE LEVEL OF MODERN NOVEL (ON THE EXAMPLE OF THE WORKS OF E. VODOLAZKIN, M. SHISHKIN, V. SHAROV)

THE SPECIFICITY OF THE FUNCTIONING OF POLYPHONIC ELEMENTS AT THE NARRATIVE LEVEL OF MODERN NOVEL (ON THE EXAMPLE OF THE WORKS OF E. VODOLAZKIN, M. SHISHKIN, V. SHAROV)

Golden ratio and self-similarity in swimming: breast-stroke and the back-stroke.

Dynamics-on-graph concepts and generalized finite-length Fibonacci sequences have been used to characterize, from a temporal point of view, both human walking & running at a comfortable speed and front-crawl & butterfly swimming strokes at a middle/long distance pace. Such sequences, in which the golden ratio plays a crucial role to describe self-similar patterns, have been found to be subtly experimentally exhibited by healthy (but not pathological) walking subjects and elite swimmers, in terms of durations of gait/stroke-subphases with a clear physical meaning. Corresponding quantitative indices have been able to unveil the resulting hidden time-harmonic and self-similar structures. In this study, we meaningfully extend such latest findings to the remaining two swimming strokes, namely, the breast-stroke and the back-stroke: breast-stroke, just like butterfly swimming, is highly technical and involves the complex coordination of the arm and leg actions, while back-stroke is definitely similar to front-crawl swimming. An experimental validation with reference to international-level swimmers is included.

Real estate prices and land use regulations: Evidence from the Law of Heights in Bogotá

Between 2015 and 2017, the Law of Heights (Policy-562) regulated areas of urban renewal in specific locations of Bogotá (Colombia). Using a novel dataset based on detailed information at the block level between 2008 and 2017, we study whether this policy affected real estate prices. Our empirical strategy compares the price per square meter before and after Policy-562 in treated blocks and in control blocks with similar pre-treatment traits. Results show that prices increased more in treated blocks than in the rest of the city. We also provide evidence that results are heterogeneous from a temporal, land use and strata point of view.

Spatiotemporal Characterization of Cassiopeia A

Analyzing the X-ray data of supernova remnants (SNRs) is among the most challenging tasks in current X-ray astronomy because SNRs are both spatially extended and variable over time. We developed the strategy to track the time-series properties of all the parts constituting a diffuse structure by introducing the free-form image-registration technique based on B-spline and demonstrated the methodology using the Chandra data of Cassiopeia A. We successfully extracted the spatial distribution map of the time variability of continuum luminosity. To our knowledge, this is the first comprehensive characterization of such a dynamic diffuse target both in spatial and temporal viewpoints. We found that each of the four clusters derived by applying k-means algorithm to the extracted light curves has a clear physical meaning distinct from other clusters, which shows that our method is not a mere technique for automation but capable of capturing the underlying physics.

Time-space variations in the East African Rift magmatism: the role of different mantle domains

The East African Rift System (EARS) is the classic example of an active continental rift where extensional tectonics and lithospheric thinning have been closely associated to the generation of large volumes of magmas and represents the environment with the largest range of erupted magma types all over the world. The geochemical signature of erupted magmas testifies the involvement of different mantle domains and depths (i.e., subcontinental lithosphere, asthenosphere and deeper mantle sources). Our aim is to investigate the variable contribution of different mantle domains in the genesis of the EARS magmas through space and time, considering not only the geochemical signature of erupted magmas but also the geochemical message of mantle xenoliths. The main goal is to provide a large-scale view of the common process driving the origin of magmas in the EARS beyond the local peculiarities linked to specific settings. To this aim, we screened an exhaustive geochemical database of basalts and mantle xenoliths from the EARS, and we report original trace element and Sr-Nd isotope data of new samples collected from the Main Ethiopian Rift and Turkana depression. The data were subdivided according to spatial and temporal criteria. From a spatial point of view, the samples were ascribed to five groups, namely: Afar, Ethiopia, Turkana, Eastern Branch, and Western Branch; from a temporal point of view, the magmatic activity of the EARS was subdivided into three main temporal intervals: 45-25 Ma, 25-10 Ma and 10-0 Ma. The geochemical and radiogenic isotope (Sr, Nd, Pb) signature of the selected basalts denotes the variable contributions of a mantle plume, a more depleted asthenospheric mantle (DMM), and different SubContinental Lithospheric Mantle (SCLM) domains, depending on their temporal and spatial distribution. The geochemistry of the selected basalts shows a marked correspondence with the compositional heterogeneity of mantle xenoliths, whose isotopic systematics (Sm-Nd, Re-Os) indicates the formation of the local SCLM in the Archean and during the Pan-African orogeny. Both SCLM domains contributed significantly to magma genesis in the Western Branch (whose signature points towards a contribution of the Pan-African lithosphere) and Eastern Branch (which is also affected by Archean SCLM domains) magmas. The contribution of the SCLM generally increases with time, possibly related to an increase of the geothermal gradient in response to the arrival and flattening of the plume head at the base of the lithosphere and later extension, thinning and shallower melting. Our interpretation supports a pivotal role of the different SCLM domains in magma genesis that is able to fully explain the large compositional heterogeneity of the EARS basalts and represents a reasonable alternative to the putative presence of multiple mantle plumes or a heterogeneous mantle upwelling.

Towards a unified eco-evolutionary framework for fisheries management: Coupling advances in next-generation sequencing with species distribution modelling

The establishment of high-throughput sequencing technologies and subsequent large-scale genomic datasets has flourished across fields of fundamental biological sciences. The introduction of genomic resources in fisheries management has been proposed from multiple angles, ranging from an accurate re-definition of geographical limitations of stocks and connectivity, identification of fine-scale stock structure linked to locally adapted sub-populations, or even the integration with individual-based biophysical models to explore life history strategies. While those clearly enhance our perception of patterns at the light of a spatial scale, temporal depth and consequently forecasting ability might be compromised as an analytical trade-off. Here, we present a framework to reinforce our understanding of stock dynamics by adding also a temporal point of view. We propose to integrate genomic information on temporal projections of species distributions computed by Species Distribution Models (SDMs). SDMs have the potential to project the current and future distribution ranges of a given species from relevant environmental predictors. These projections serve as tools to inform about range expansions and contractions of fish stocks and suggest either suitable locations or local extirpations that may arise in the future. However, SDMs assume that the whole population respond homogenously to the range of environmental conditions. Here, we conceptualize a framework that leverages a conventional Bayesian joint-SDM approach with the incorporation of genomic data. We propose that introducing genomic information at the basis of a joint-SDM will explore the range of suitable habitats where stocks could thrive in the future as a function of their current evolutionary potential.

Prediction of the flame kernel growth rate in spark ignition engine fueled with natural gas, hydrogen and mixtures

The knowledge of combustion duration is a key tool in the development of engines, specially nowadays for engines adapted to new fuels with low C/H ratio such as natural gas and hydrogen. This work is aimed to develop a correlation that predicts the duration of the first phase of combustion until the process becomes turbulent in a SI engine. The flame kernel radius when this transition occurs, Rtr, is the study variable.To determine this variable from the experimental pressure records, a flame kernel growth predictive model is used. The predictive model is adjusted to the experimental data, determining the most appropriate Rtr value.The pressure records of 500 consecutive cycles of 48 test points have been processed. The averaged values of Rtr of each test point have been correlated with the characteristic parameters of the process: turbulence and properties of the fuel–air mixtures. Finally, Rtr and integral length scale ratio is correlated with Damköhler number.A wide range of operating conditions have been studied, reaching the novel conclusion that it is possible to analyze the kernel growth phenomenon from a spatial point of view rather than from a temporal point of view, as had been studied in many previous works.The developed correlation can be used in combustion predictive modeling to support SI engine design. Other practical conclusion from the work, that can be used in SI engine development, is that decreasing the integral length scale reduces the time of the first phase of combustion.

Use of the Copernicus Atmosphere Monitoring Service policy products to evaluate the contribution of EU cities to their pollution

In this paper we compute and analyse the ‘cities contribution to their own pollution’, based on the ‘Source Contribution to EU cities’ policy product from the ‘Copernicus Atmosphere Monitoring Service’. The analysis focuses on 38 EU cities, analyzing how the ‘cities contribution’ changes from a temporal and spatial perspective. A comparison with state-of-the-art similar analysis is also provided. Results show that city contributions (for yearly aggregated values) largely change spatially (that is to say city by city) with values ranging from 5% to 54% for PM2.5 and from 24% to 81% for NO2. We also highlight how local contributions are affected by meteorology. From a temporal point of view, the variability is even higher between seasonal and/or daily city contributions. All these results stress the complexity of finding the right balance between local and national/international emission reduction policies and the challenge of applying measures at the right time, to increase their efficiency. • We analyse the ‘cities contribution to their own pollution’. • Data comes from the ‘Copernicus Atmosphere Monitoring Service’. • The analysis focuses on 38 EU cities. • Results show large spatial and temporal variability of ‘cities contribution’. • Results show It is complex to find the right balance between local and higher level policies.

Online Assessment: A Case Study of Ecole Normale Superieure, Moulay Ismail University

In the digital age, the use of technology is gradually being imposed in all institutions of higher education in Morocco. Without pretending to replace face-to-face teaching, distance learning is less expensive, flexible and accessible if discussed from a temporal and spatial point of view. It allows for the achievement of objectives that could not be achieved without technology. The numerous pedagogical and technical challenges that our training system should face are becoming more and more important and complex; and so are the speculations. In the era of massiveness and lifelong learning, distance learning favors a greater level of autonomy and productivity in the learning process, which is becoming increasingly distant from the teaching process. However, it should be noted that distance learning is still in the experimental stage and has not yet been adopted as a training modality that would meet the new needs of learners and a new audience that is not to benefit from face-to-face training. If this is the case of distance learning, what could be said about online assessment then? In this article, the focus is going to be put on this latter through the experience of the Ecole Normale Superieure of Meknes with the online assessment during the COVID-19 pandemic. A study was conducted at the level of the institution using both a qualitative survey addressed to the professors and a qualitative exploration addressed to the students with the aim of reflecting on the process of the online evaluation. The research findings refer to a deficiency in this area and call for the implementation of training systems to be used, not just in the case of Emergency Remote Teaching.

Natural Hydrogen: A New Source of Carbon-Free and Renewable Energy That Can Compete With Hydrocarbons

Natural Hydrogen: A New Source of Carbon-Free and Renewable Energy That Can Compete With Hydrocarbons

A new large-sized species of Chelonoidis (Testudinidae) without gibbosities from the middle Miocene of Aguada Escondida (NW Chubut, Patagonia, Argentina).

Previously, only one small-sized species of Testudinidae (Chelonoidis gringorum) was named from Lower-Middle Miocene of Central Patagonia. In this short article, we describe a new large Testudinidae, here named Chelonoidis meridiana sp. nov. This large new species (carapace up to 80 cm) differs from other large species of the southern South American fossil record by the absence of gibbosities on neural and costal carapacial bones, a short and wide entoplastron with a humeropectoral sulcus that was placed well behind its posterior end, and pectoral scutes that are medially longer, approximately one-third of the medial length of the hyoplastra. The discovery of this new species in the Middle Miocene increases the raw turtle diversity in Chubut, permitting to reduce the gap between the raw and phylogenetic diversity previously proposed. This occurrence is also important from both a temporal and geographic point of view. It permits fixing the presence of large-sized tortoises in the continent since ~15 million years ago (Middle Miocene). This occurrence predates all other large and giant tortoises from Argentina and South America and it is older than the giant Chelonoidis from the Langhian-Tortonian of Colombia. This is also the southernmost occurrence of a large-sized testudinid in the world.

Fourth grade students’ computational thinking in pair programming with Scratch: A holistic case analysis

This article explores a new but expanding research topic: primary school students’ computational thinking (CT) in the context of programming in pairs. The data comprises four fourth-grade student dyads using Scratch, a block-based programming tool, for two open-ended creative programming sessions. We sought insight into how the dyads put four intertwined CT dimensions – planning; iteration; collaboration, social interactions, and remixing; and debugging – into practice. To examine these dimensions, the data was analysed systematically in three overlapping layers: what happens on the computer screen (design events), who uses the computer (computer control), and what kind of talk is occurring (talk). The temporal viewpoint in the multi-layered analysis revealed and enriched holistic understanding of key computational and social factors, such as initial project planning methods, programming tendencies, and pair programming roles that essentially shaped the dyads’ design processes. Next to opportunities for more focal research in CT education, the results provide especially evidence-based pedagogical knowledge for supporting students’ open-ended programming in the classroom. In particular, concrete suggestions for supporting open-ended project planning, balancing between self-directed design and instructional support during programming, and promoting shared design processes in pair programming are provided based on the findings.

Evolution of Transaction Pattern in Ethereum: A Temporal Graph Perspective

Ethereum is one of the most popular blockchain systems that support more than half a million transactions every day and foster miscellaneous decentralized applications with its Turing-complete smart contract machine. Whereas it remains mysterious what the transaction pattern of Ethereum is and how it evolves over time. In this article, we study the evolutionary behavior of Ethereum transactions from a temporal graph point of view. We first develop a data analytic platform to collect external transactions associated with users as well as internal transactions initiated by smart contracts. Three types of temporal graphs, user-to-user, contract-to-contract, and user-contract graphs, are constructed according to trading relationships and are segmented with an appropriate time window. We observe a strong correlation between the size of the user-to-user transaction graph and the average Ether price in a time window, while no evidence of such linkage is shown at the average degree, average edge weights, and average triplet closure duration. The macroscopic and microscopic burstiness of Ethereum transactions are validated. We analyze the Gini indexes of the transaction graphs and the user wealth in which Ethereum is found to be very unfair since the very beginning, in a sense, “the rich is already very rich.”

A latent feature oriented dictionary learning method for closed-loop process monitoring

Industrial cyber–physical system (ICPS), by its powerful computing, communication, precise control and remote operation functions, has become the mainstream of modern industrial process. The observed variables of the closed-loop process in ICPS are subject to the degradation of equipment and other factors, resulting in exhibiting a stationary/nonstationary mixture feature and dynamic feature. Moreover, due to the frequent change of working conditions in the closed-loop process, the traditional open-loop process monitoring method always triggers false alarms, which will impose a negative impact on the safety and trustworthiness of ICPS. Therefore, for the closed-loop process in ICPS, a latent feature oriented dictionary learning (LFDL) method is proposed, which realizes the precise separation of latent features of raw data through three stages. First, closed-loop process variables are separated into stationary and nonstationary variables to mine the local information spatially. Then, from the temporal viewpoint, the static and dynamic features were extracted for stationary and nonstationary variables on the basis of the slow feature analysis method and cointegration analysis for local monitoring. Finally, the global monitoring results are obtained by utilizing the dictionary learning method to fuse respectively the local monitoring results of the static and dynamic features. Since the proposed method has taken the feature of the close-loop process from temporal and spatial viewpoints simultaneously, it can distinguish the normal change of operating conditions and actual faults accurately. Extensive experiments including the three-phase flow, the Tennessee Eastman process and an industrial roasting process are conducted to demonstrate the feasibility and effectiveness of the proposed method.

Regional well-being in Romania: assessment after a decade of EU accession

PurposeThis paper aims to study through a comprehensive set of socioeconomic indicators the regional level of well-being achieved in Romania, and monitor the improvements and disparities in well-being after a decade of accession to the European Union.Design/methodology/approachA dashboard of 20 socioeconomic indicators for measuring nine dimensions of well-being for Romanian counties is proposed. Using the Adjusted Mazziotta-Pareto method are built composite indicators, which allow us to assess the trend of overall welfare scores for each county. The data are collected at the county level, for 42 counties, and each year from 2006 to 2017, from administrative sources.FindingsThe overall well-being index has an increasing trend for all counties, but the growth rate varies from one county to another. The economic factors, geographic location and share of the urban population matter. For most counties, the evolution of well-being scores is below that recorded at the country level. Romania has registered significant improvements in health, housing, income and access to public utilities dimensions. The counties are ranked by level of well-being. Some empirical measures suggest a slight tendency of socioeconomic disparities to increase over time.Originality/valueThe paper attempts to fill some gaps in measuring the level and disparities of welfare in a fast-growing emerging economy. The Romanian regional context is to a lesser extent explored in a multidimensional approach, from spatial and temporal points of view.

Thelazia callipaeda in Slovakia - From sporadic cases to endemic areas.

Spirurid nematode Thelazia callipaeda, transmitted by the fruit fly Phortica variegata, is a causative agent of an ocular parasitic disease called also canine thelaziosis. Dogs, cats, and wild canids are considered the primary definitive hosts for the parasite, but humans may also serve as aberrant definitive hosts. For long decades the geographic range of T. callipaeda was strictly limited to the territory of Asia, but after the year 2000, the parasite began to spread rapidly through Europe. The first autochthonous infections of dogs and foxes in Slovakia were recorded in 2016. In the present study, the results of a whole-area surveillance for canine thelaziosis are reported. Altogether, 142 cases of infection caused by T. callipaeda were diagnosed by veterinarians in dogs between 2016 and the first quarter of 2021, and two cases of feline thelaziosis were recorded. The majority of the dogs showed mild ocular signs manifested by conjunctivitis; 8.5% of them suffered from more serious mucopurulent discharge, and in two dogs corneal ulceration was recorded. The screening revealed increasing trends in the occurrence of canine thelaziosis from both a temporal and spatial point of view and unambiguously confirms the endemic status of T. callipaeda in Slovakia with the prospect of its further expansion.