Reviewerly/exHarmony huggingface dataset:
Spatiotemporal assessment of multi-sourced groundwater salinization in a coastal aquifer (Rhodope, Northern Greece)

&amp;lt;p&amp;gt;The coastal aquifer of the Rhodope region (NE Greece) is a complex groundwater system impacted by various processes that increase groundwater salinization (seawater intrusion, trapped saline lenses, geothermal fluid impact, irrigation return). In the context of the MEDSAL Project (www.medsal.net), a thorough study of its hydrogeochemical characteristics was performed to assess the spatiotemporal variations of groundwater salinization and identify the dynamics of the phenomenon.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To this aim, we used a combination of tools, including multivariate statistics analysis (MVSA) and hydrogeochemical modelling, to decipher the mechanism(s) of groundwater salinization and their evolution in time and space.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Results from Hierarchical Cluster Analysis (HCA) classified water samples into four (4) diverse groups and seven (7) subgroups that denote different hydrogeochemical and salinization phases. The different processes that control hydrogeochemistry were further assessed using R-mode factor analysis. The outcomes outlined three (3) factors that supplemented the HCA. The dominant factor is related to the cascading processes of salinization, and the secondary factors are related to anthropogenic contamination (N surplus due to agricultural activities) and the impact from the substrate (water-rock interaction).&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Hydrogeochemical modelling further supported assessments and provided an overview of the spatiotemporal variability of factors and processes affecting groundwater chemistry. A set of saturation indices of key minerals related to the dominant processes identified by the MVSA were calculated and interpolated to capture the spatiotemporal dynamics. Results facilitated the development of a more representative conceptual model about salinization and the key hydrogeochemical processes affecting water quality in the area.&amp;lt;/p&amp;gt;
“SOLET”, A SELF-ORGANISED LEARNING ENVIRONMENT FOR TEACHERS ABOUT CRITICAL DIGITAL LITERACIES: PROPOSAL AND VALIDATION

J. Raffaghelli 1, D. Español-Fernández1, M. Romero-Carbonell 1, T. Romeu-Fontanillas 1, M. Lakkala 2, A. Roffi 3, A. Gouseti 4 1Open University of Catalonia (SPAIN) 2University of Helsinki (FINLAND) 3University of Florence (ITALY) 4University of Hull (UNITED KINGDOM)
GOOD PRACTICES IN DIGITALIZATION OF LITERARY INHERITANCE IN THE REPUBLIC OF BULGARIA

N. Tomova, D. Boyadzieva, N. Ninova, I. IlievaUniversity of Library Studies and Information Technologies (BULGARIA)
Starting an MLS in the Midst of a Pandemic, or How to Survive, Adapt, and Overcome Program Fatigue

In this essay, the 2020–21 SMLG officers emphasize the importance of building a community of students and emerging professionals in the field of music librarianship under difficult circumstances. Due to the COVID-19 virus, the incoming MLS Music Specialization cohort at Indiana University had to quickly adapt to a year of online classes. With only half of the incoming students physically in Bloomington, it was difficult to begin learning the trifecta of hands-on library skills: public services, technical services, and archival work. Additionally, it was daunting and challenging to get to know everyone in the program due to the physical restrictions. However, the Students of Music Librarianship Group, or SMLG, was able to help alleviate these challenges by organizing virtual check-ins, casual hangouts, and professional development sessions where students could meet other music librarians to discuss unique aspects of their jobs. The authors also discuss how, despite this crisis, they have continued to build the necessary skills to succeed in our chosen profession and offer recommendations for how degree programs like theirs might adapt in the future.
The creation and control of structured light with digital micro-mirror devices

Structured light has become topical of late, allowing custom optical fields to be tailored in all degrees of freedom, and finding applications that include optical trapping and tweezing, microscopy, communications and even quantum protocols. Commonly, the light is tailored in its spatial degrees of freedom for arbitrary polarization, amplitude and phase control, executed on spatial light modulators. This invited talk will outline the role of digital micro-mirror devices (DMDs) in the creation, control and detection of structured light fields, covering fundamentals for “getting started” to the state-of-the-art in real-time control with high speed and fidelity. The talk will cover topics ranging from lasers to single photons, highlighting the versatility of the DMD toolkit.
An Improved Small Target Detection Method Based on YOLOv4

In order to improve the efficiency and accuracy of small target detection in current traffic flow, this research proposes an improved YOLOv4 framework and applies it to small target detection task.A new small target-friendly 4-fold down-sampling residual is added between the second and third residual blocks of CSP Darknet-53 block to improve the detection accuracy of small target.The novel YOLOv4 model is optimized by above strategy.Compared with the original network, the modified framework can significantly improve the recall rate and average detection accuracy of small target.
Data Mining Method under Model-Driven Architecture (MDA)

With the development of university information technology, how to mine and visually analyze the data of the existing separated information system will become an important research topic. The current university information system is a combination of some proprietary business systems characterized by poor data separation and storage and data analysis power. In addition, the data mining methods based on cloud computing will make customers gradually lose the ability to control the data. Because of the above problems, this paper proposes a university data mining method based on the MDA idea by constructing a data analysis and visualization framework, including multidimensional data modeling, data extraction, and data display based on visualization technology. The framework makes full use of the design idea of MDA and models multidimensional data, data extraction, and data display, respectively. The multidimensional data model module, data extraction module, and data visualization module provide efficient solutions for data analysis and visualization in universities.
Autonomous ground vehicle for physically impaired: A solution rather than luxury

The aspect of autonomous vehicles has majorly been associated with luxury in the previous years, but seldom is its importance in the arena of medical crisis and to help the physically-impaired realized. The aspect of physically impaired is not alone concerned with those who are quadriplegic or completely paralysed but even those who at their later stage of life have lost their muscle strength to an extent that they cannot support their locomotion even by the means of a mechanical wheelchair. Our paper is majorly concerned about the aspect of creating an autonomous ground vehicle and deploying the same in the healthcare field. The paper also describes the complete process of creating a ground vehicle capable of autonomous GPS navigation and dynamic obstacle avoidance capabilities. The project shall also include the concepts of traffic light recognition and lane detection to make the vehicle a little road-ready. Another important parameter that we want to include in our project is to make our vehicle dependent on renewable sources of energy or on sources like piezoelectric sensors. This might increase the initial cost of the vehicle but shall be highly successful in reducing the expenditure in terms of operational expenditure by saving the costs of investment in highly expensive chemical batteries from time to time. Thus, the amalgamation of all the important aspects such as autonomic abilities to navigate, elevated by self-avoidance of unprecedented obstacles and self-path planning techniques can lead to the development of a nearly-infallible AGV. Ready for its road-mission or even indoor-mission as and well needed.
Comparative survey on the ways of access to managerial information

The main objective of the paper was a comparative investigation of acquiring management data by the managers of the Tehran Universities Central Library&#x0027;s (TUCL) which are under the supervision of the Ministry of Science, Research, and Technology (MSRT) &#x0026; the Ministry of Health and Medical Education (MHME) located in Tehran in different managerial levels of these libraries. The comparative survey method is used in the current study and to collect data, researcher-made questionnaires were employed. The data were analyzed in two levels using Minitab software. Findings of the research suggested that middle managers mainly preferred to utilize the workers&#x0027; reports and operational managers used the internet as their informational resources. Regarding applying the information both preferred planning most and authoring and research, least. Middle managers and operational managers&#x0027; main priority to get information was to contact experts and surf on the internet, respectively and their last priority was using the personal library. Regarding communication methods, both groups mainly preferred phone most and attending conferences last. In addition to guiding information science experts, the results of the current study can give insights to the designers and experts of the management information systems (MISs) in designing user-friendly systems.
Seismic Monitoring of Novaya Zemlya:&amp;#160;Progress, Challenges, and Prospects

&amp;lt;p&amp;gt;The permanent seismic stations of the European Arctic maintain a detection threshold of around magnitude 2 for events on and around Novaya Zemlya. Events above magnitude 3 are clearly observed by multiple stations at regional and far-regional distances and, with improved traveltime models, can be located with high accuracy. The monitoring capability for smaller magnitude events is dominated by the small aperture seismic arrays ARCES and SPITS. We review the properties of Novaya Zemlya seismic signals on key stations and discuss how empirical signal processing may enhance detection and interpretation of future events in the region. We present a joint probabilistic location for 21 low magnitude events between 1986 and 2020 in which the joint probability distribution for all events simultaneously exploits both constraints on earlier events from stations no longer in operation and constraints on newer events from more recently deployed stations. Advances in signal processing, enhanced exploitation of archive data, new permanent stations, and comparative multiple event analysis will all contribute both to a more robust and sensitive detection capability and higher confidence in signal interpretation.&amp;lt;/p&amp;gt;
Face Super-Resolution Using Recurrent Generative Adversarial Network

Theface super-resolution (SR) networks based on deep learning have more advanced performance than traditional SR algorithms. However, facial key components are difficult to reconstruct because the adjacent pixels have great change. Moreover, most face SR networks only focus on the performance and ignore the number of parameters. To solve the above problems, we propose the face super-resolution network using recurrent generative adversarial network (FSRRGAN). The generator is the face SR recurrent generator (FSRRG) with dense iterative up-down sampling blocks as the basic unit. It can reduce the number of parameters and effectively improve the reconstruction performance combined with the relativistic average patch discriminator (RAPD). We use the facial perceptual similarity distance (FPSD) loss to replace the traditional perceptual loss. The experimental results show that our network has excellent performance both qualitatively and quantitatively on 4x and 8x face reconstruction.
Using raft as consensus algorithm for blockchain application of roaming services for mobile network

In the past few years blockchain became the new trending technology, it is expected to spread as internet in the 80s, Blockchain technology, using a consensus algorithm, is a cryptographic record that cannot be changed by repetitive sequence hashing and failure tolerance. Decentralization, persistency, anonymity, and audibility is the key characteristics of the blockchain. These characteristics encourage many industries to be interested in blockchain adoption in their IT systems. The consensus is one of the critical problems in the blockchain; these consensus algorithms play a critical role in maintaining the safety and efficiency of the blockchain. Unless transactions are pending, the Raft Consensus will not mint blocks. The raft can lead to significant storage savings, particularly if the transaction load is low because zero transactions are not minted in empty blocks. The performance of a blockchain that implements raft as a consensus algorithm has been evaluated through the simulation of roaming services for mobile network operators (MNOs) application. Performance evaluation to determine how quickly the network accepts blockchain transactions are reported. The result indicated that the proposed mechanism increase the throughput of transaction significantly.
The ambivalence of the Eternity and the Coming in Christian mysticism as a cryptomystical subtext of philosophical thought

It is proved that the superrationality of Christian mystical experience qualitatively differs from the superrationality of other mystical traditions. In addition to the superrationality of Eternity as an invariant of all sacred traditions, Christian experience is superrational in the aspect of the Coming state of adoration, which is a task, not a given. This aspect is unique as an attribute of Christian mystical experience only. In the aspect of Eternity, mystical unity with the God is understood in metaphors of rotation, fusion and dissolution. In the aspect of the Coming, unity with the God is understood in the metaphors of “doing”: co-work and synergy with the God. If rational thinking, like culture as a whole, is cryptomythologic and cryptomystical, then the cryptomysticism of thought that grows on the basis of the Christian archetype has its specifics. The result of the irremovable two-vectorness of the Eternity and Сoming of Christian archetype is the fluctuations of rational culture, which were not generated by any other sacred tradition. The apophatic mystery of the Eternity and the Сoming breaks down into two opposite poles in philosophical thought. One pole is associated with the phenomenological tradition of transcendental rotation, the other – with the utopian tradition.
Ex Libris

Free AccessEx LibrisDr. Christine Wenona HoffmannDr. Christine Wenona HoffmannSearch for more papers by this authorPublished Online:Mar 2022https://doi.org/10.13109/path.2022.111.3.128SectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail About Previous article FiguresReferencesRelatedDetails Download book coverVolume 111Issue 3March 2022 ISSN: 0720-6259eISSN: 2197-0831HistoryPublished online:March 2022 PDF download
A generic optical metrology platform for AR/VR

Optical metrology provides direct feedback for AR/VR/MR design verification and manufacturability evaluation by imitating the human eye’s optical properties of resolution, color sensitivity and uniformity over large FOVs, self-adaption to focus location, brightness and contrast. This paper defines a generic, standardized optical metrology platform to efficiently integrate various optical metrology instruments into the platform’s global coordinate system by utilizing a specially designed active-optical calibration target to precisely map the optical entrance pupil of any optical metrology instrument and device under test (DUT) to a common reference point, providing effective data correlation. The platform can easily accommodate common AR/VR/MR optical metrology equipment for measurements of: MTF/contrast, color and brightness, virtual distance, angular FOV, and binocular alignment error; to provide a unified metrology platform for optical measurements.
Seismological characterization of dynamics parameter of the Hunga Tonga explosion from teleseismic waves

&amp;lt;p&amp;gt;Most of the largest volcanic activity in the world occurs in remote places as deep oceans or poorly monitored oceanic islands. Thus, our capacity of monitoring volcanoes is limited to remote sensing and global geophysical observations. However, the rapid estimation of volcanic eruption parameters is needed for scientific understanding of the eruptive process and rapid hazard estimation. We first a method to rapidly identify large volcanic explosions, based on analysis of seismic data. The method automatically detects and locate long period (0.01-0.03Hz) signals associated with physical processes close to the Earth surface, by analyzing surface waves recorded at global seismic stations. With this methodology, we promptly detect the January 15, 2022 Hunga Tonga eruption, among many other signals associated with known and unknown processes. We further use the waves generate by the Hunga Tonga volcanic explosion and estimate important first-order parameters of the eruption (Force spectrum, impulse). We then relate the estimated parameters with the volcanic explosivity index (VEI). Our estimate of VEI~6, indicate how the Hunga Tonga eruption is among the largest volcanic activity ever recorded with modern geophysical instrumentation, and can provide new insights about the physics of large volcanoes.&amp;lt;/p&amp;gt;
Establishment of intersection traffic flow prediction model based on random characteristics of cloud model

In the problem of traffic flow prediction at traffic intersections, this paper tries to predict traffic flow based on the random characteristics of cloud model. Establish the cloud model of traffic flow through the mapping relationship between qualitative and quantitative. To establish a new prediction mechanism between adjacent intersections to predict future traffic trends. Provide dynamic optimization support for intersection traffic signal timing scheme to evacuate traffic congestion as soon as possible.
Exploring Item Bank Stability through Live and Simulated Datasets

LanguageCert manages the construction of its tests, exams and assessments using a sophisticated item banking system which contains large amounts of test material that is described, inter alia, in terms of content characteristics such as macroskills, grammatical and lexical features and measurement characteristics such as Rasch difficulty estimates and fit statistics. In order to produce content and difficulty equivalent test forms, it is vital that the items in any LanguageCert bank manifest stable measurement characteristics. The current paper is one of two linked studies exploring the stability of one of the item banks developed by LanguageCert [Note 1]. This particular bank has been used as an adaptive test bank and comprises 820 calibrated items. It has been administered to over 13,000 test takers, each of whom have taken approximately 60 items. The purpose of these two exploratory studies is to examine the stability of this adaptive test item bank from both statistical and operational perspectives. The study compares test taker performance in the live dataset with over 13,000 test takers (where each test taker takes approximately 60 items) with a simulated ‘full’ dataset generated using model-based imputation. Simulation regression lines showed a good match and Rasch fit statistics were also good: thus indicating that items comprising the adaptive item bank are of high quality both in terms of content and statistical stability. Potential future stability was confirmed by results obtained from a Bayesian ANOVA. As mentioned above, such item bank stability is important when item banks are used for multiple purposes, in this context for adaptive testing and the construction of linear tests. The current study therefore lays the ground work for a follow-up study where the utility of this adaptive test item bank is verified by the construction, administration and analysis of a number of linear tests.
Eruption forecasting at Strokkur geyser, Iceland: An application of Permutation Entropy

&amp;lt;p&amp;gt;A volcanic eruption is usually preceded by increased seismic activity resulting from magma propagation. Although these precursors can be detected by a modern seismometer, it is still a challenge to answer whether they will be followed by an actual eruption and when the eruption will occur after precursors are detected. The time between the start of volcanic unrest and the actual eruption is crucial. Therefore, there is a need for an assessment tool that is applicable in real-time. Permutation Entropy (PE) has been recently suggested to be a promising tool for the prediction of volcanic eruptions. It is a robust yet simple tool to quantify the complexity of time series. We aim to find out whether there is a distinct feature in the temporal variation of PE that is useful for eruption forecasting. We performed several synthetic tests to understand how PE works and how to choose the optimum input parameters for a signal with certain properties. We then applied this knowledge to calculate PE of seismic data that recorded eruptions of Strokkur geyser, Iceland on the 10&amp;lt;sup&amp;gt;th&amp;lt;/sup&amp;gt; of June 2018. 78 eruptions occurred within five hours of observation. We used this fast-repeating process to check if the eruptions cause a repetitive pattern of PE. The input parameters used for PE calculation are a window length of 1 second, an embedding dimension of 5, and a delay time of 0.067 seconds. Our results show a distinct, repeating pattern of the PE that is consistent with the phases in the eruptive cycle of Strokkur as described by Eibl et al. (2021). The PE drops in the stage of bubble accumulation at depth, then undergoes repeated increasing and decreasing patterns during regular bubble collapses at depth in the conduit, and finally continuously increases as a precursor towards the time of eruption on the surface. The average duration of this precursor to the eruption is about 10 seconds.&amp;lt;/p&amp;gt;