Reviewerly/exHarmony huggingface dataset:
Enhancement-fusion feature pyramid network for object detection

Scale variation is one of the challenges of object detection. Most state-of-the-art object detectors depend on feature pyramid networks (FPN) for multiscale learning to deal with this problem, in which feature fusion is an essential operation. However, feature fusion does not sufficiently address the difficulty of the detection task. This paper presents an enhancement-fusion feature pyramid network (EFPN) to obtain reliable object representations for object detectors. Specifically, it contains a feature enhancement module (FEM) and a bottom-up path module (BPM). The FEM is used to eliminate the negative impact of the uneven distribution of object scales on the model performance. Then, a BPM is proposed to address the fusion inconsistency in the FPN. Additionally, an attention module (Ac) is added to eliminate the information loss in the bottom-up aggregation process. EFPN is evaluated by combining it with state-of-the-art detection methods. Extensive experimental results on two datasets MS-COCO and VOC2007 demonstrate the effectiveness of the proposed method.
Diffusion processes in minor normal faulting seismic sequences monitored by the Alto Tiberina Near Fault Observatory (Northern Apennines, Italy)

The analysis of microseismicity has a fundamental role in understanding earthquakes, giving insights on the long- and short-term driving forces and processes preparing and generating the seismicity occurrence and its evolution in space and time.Recent advances in detection and location algorithms, paired with dense seismic networks, and supported by higher computing capacity, allow dramatic increase in the quality and quantity of low magnitude earthquakes recorded resulting in high resolution earthquakes catalogs in terms of both location attributes and completeness.Such catalogs enable us to analyze small magnitude (M&lt;4) sequences having the advantage of a high frequency of occurrence, with unprecedented resolution in illuminating minor (few kilometers of extent) fault systems and seismicity patterns.We present a detailed analysis of two seismic sequences occurred within an extensional sector of the Northern Apennines between 2010 and 2014: the Citt&amp;#224; di Castello and Pietralunga sequences (maximum magnitude &amp;#8804; 3.6). The area is within the Alto Tiberina Near Fault Observatory (TABOO-NFO), a multidisciplinary monitoring infrastructure dedicated to the investigation of the fault slip behavior of this very low angle normal fault.The very high microseismic activity, the availability of a dense network and a complex tectonic setting involving shallow (H2O) and deep (CO2) fluids circulation, result in an ideal location to apply modern detection and analysis techniques to study microseismicity in detail.We build the high-resolution catalog starting from the raw waveforms recorded by a seismic network composed of ~60 stations covering an area of 80x80km and applying a deep learning phase picker. The events are located with a probabilistic nonlinear algorithm and finally relocated with the double differences algorithm after undergoing a quality selection based on location parameters. The resulting catalog for these sequences counts 6 times the number of events documented in previously available standard catalogs.The spatiotemporal distribution of events shows different characteristics, ranging from foreshock-mainshock-aftershock to more swarm-like patterns but almost all these patterns are compatible with pore-pressure diffusion (1 &amp;#8722; 2m2s-1) processes and exhibiting along-strike migration. These are very similar behavior with respect to the ones observed during the larger extensional sequences occurred in the Apennines in recent years.The case of fluid driven seismicity is coherent with the seismotectonic setting of the area showing large CO2 degassing phenomena and the presence of geologic formations prone to develop fluids overpressure. The comparison of the spatial distribution of events with a three-dimensional deterministic seismostratigraphic model based on different (non-seismic) geophysical data, highlights in fact a ubiquitous involvement of the Triassic Evaporites as hosting lithology, indicating a strong mechanical control and corroborating their seismogenic role.
Tracing of evolution of carbonatite and silicate melts of the Belo-Ziminsky alkaline-ultrabasic carbonatite massif by mineralogy and geochemistry

The Belo-Ziminsky alkaline-ultrabasic carbonatite massif contain dolomite, and calcite ankerite carbonatites essential part , syenites, melteigites and iolites cut by aillikite dikes of several generations (Ashchepkov et al., 2020; Doroshkevich et al., 2014-2021 etc). We analyzed&amp;#160; &gt;4000 mineral grains by electron microscope in all types of rocks and &gt;230 grains by&amp;#160; LA ICP MA&amp;#160; All rocks of the massif are derived from one type of mantle melt that was close to aillikite and formed at a level of &gt;5 GPa in the mantle.According to the nature of the PGE spectra &amp;#8211;&amp;#160; and by serpentinized xenoliths in aillikites, this melt drained metasomatized enriched peorvskites and hydrogenated mantle and was initially very rich in HFSE. Above, at the level of the crust and the upper part of the mantle, the melt began to separate under liquation. In the lower and middle crust, several (3) magmatic chambers were probably formed sequentially, which separated various carbonate and silicate melts, and from dolomite to ankerite melts, judging by the slope, the number of grains in the source decreased, that is, the melts became less deep and more fractionated.These trends are reflected both in the composition of pyroxenes from aillikites&amp;#160; and in the PTX diagram . All this led to significant variations in rocks and their rare-earth spectra of all rocks&amp;#160;
Hamtajoo: A Persian Plagiarism Checker for Academic Manuscripts

In recent years, due to the high availability of electronic documents through the Web, the plagiarism has become a serious challenge, especially among scholars. Various plagiarism detection systems have been developed to prevent text re-use and to confront plagiarism. Although it is almost easy to detect duplicate text in academic manuscripts, finding patterns of text re-use that has been semantically changed is of great importance. Another important issue is to deal with less resourced languages, which there are low volume of text for training purposes and also low performance in tools for NLP applications. In this paper, we introduce Hamtajoo, a Persian plagiarism detection system for academic manuscripts. Moreover, we describe the overall structure of the system along with the algorithms used in each stage. In order to evaluate the performance of the proposed system, we used a plagiarism detection corpus comply with the PAN standards.
Improving Low-Resource NMT with Parser Generated Syntactic Phrases

Recently, neural machine translation (NMT) has become highly successful achieving state-of-the-art results on many resource-rich language pairs. However, it fails when there is a lack of sufficiently large amount of parallel corpora for a domain and/or language pair. In this paper, we propose an effective method for NMT under a low-resource scenario. The model operates by augmenting the original training data with the examples extracted from the parse trees of the target-side sentences. It provides important evidences to the model as these phrases are relatively smaller and linguistically correct. Our experiment on the benchmark WMT14 dataset shows an improvement of 3.28 BLEU and 3.41 METEOR score for Hindi to English translation. Evaluation on the same language pair with relatively much smaller datasets of judicial and health domains also show the similar trends with significant performance improvement in terms of BLEU (15.63 for judicial and 15.97 for health) and METEOR (14.30 for judicial and 15.93 for health).
Exogenous and Endogenous Factors Leading to OSS Vulnerability: Study on Version Dependency Network

Pursuant to many open-source software (OSS) vulnerability incidents, various research institutes and firms have attempted to either identify the most commonly used OSS components, and examine for potential vulnerabilities and possible investments, or produce tools to detect OSS vulnerabilities by thorough inspection. Although these firms aim to identify vulnerabilities as many as possible, but produce too many alarms, and many false alarms. At the same time, one of the major assumptions in various importance and security studies is that packages keep same dependencies over time, i.e., all dependencies are calculated without considering version information, however this is a wrong assumption, for instance when the gem package “spruz” is scored highly risky, because it depended on previous versions of some popular packages, “json_pure”. Having included version dependency, “spruz” would not have scored high importance. Therefore, it is important to investigate package version vulnerability rather than project vulnerability, also discuss research questions as 1) what factors could lead to package vulnerability? Also knowing these factors, can one narrow down vulnerability search? For this purpose, we build a version dependency network combining various sources; on the other hand, we collect vulnerabilities from different repositories. We investigate the impact of network exposure and other exogenous and endogenous factors such as contributors count, open issues count, version age and number of forks on latest package version vulnerability.
CARS - Catalog of Relative Seismic Locations of 1981-2018 Italian Seismicity

The Istituto Nazionale di Geofisica e Vulcanologia (INGV) monitors the Italian peninsula seismicity&amp;#160;by using the data recorded by the Italian National Seismic Network (RSN) together with the ones gathered by other permanent regional networks (PRN). Earthquakes are real-time located by the INGV surveillance system and manually revised by the Italian Seismic Bulletin (BSI) group analysts.Starting from a catalog composed by homogeneous absolute locations (CLASS; Latorre et al., 2023), obtained by using a 3D regional-scale velocity model, we generated a catalog of relative seismic locations (CARS) of about 310,000 events occurred in Italy during 1981-2018.We inverted absolute P- and S- waves arrival times derived from data collected by RSN plus PRN for the period 1981-2008 and only by RSN for 2009-2018 to apply the double-difference relocation algorithm (Waldhauser and Ellsworth, 2000).For the second period, we combined the absolute travel times with relative ones obtained by waveforms cross-correlations analysis performed on pairs of similar events.&amp;#160;The time domain cross&amp;#8208;correlation method proposed by Schaff et al., 2004 and Schaff &amp; Waldhauser, 2005 was applied to seismograms of all pairs of events separated by 10 km or less and recorded at common stations. Seismograms were filtered in the 1&amp;#8211;15 Hz frequency range using a four pole, zero phase band&amp;#8208;pass Butterworth filter. The correlation measurements were performed on 1.0 s long window for P- and S-waves. We collected a total of ~17 million P- and ~23 million S-wave delay times, retaining all measurements with correlation coefficients greater than 0.7.1D velocity models characterising 18 different (geologically, seismically and tectonically homogeneous) Italian macroareas (after Pastori et al. B2-2019-2021, Wp1-task4) were used in the location procedure.To cope with the memory limits (15,000 events with less than 200 readings) of the HypoDD code so to use it in a steady operational mode, we first subdivided the study region in the 18 macroareas related to the velocity models, then we additional discretize each in 100x100km2 cells, overlapped by the 80% in longitude and latitude. We repeatedly produced hypocentral locations of the same events that we merged by computing a final weighted mean location.We present the double-difference catalog of Italian seismicity, allowing to depict alignments clearer with respect to the starting catalog (CLASS), to be related to seismogenic faults and/or to regional structures along the whole Italian peninsula.
Teaching groundwater flow modelling using cloud-hosted Jupyter notebooks and FloPy

&amp;lt;p&amp;gt;Numerical modelling of groundwater flow is a challenging subject for both educators and learners. It requires fundamental insight in hydrogeology, mathematics and computer science. In addition, students need to learn to work with software developed for experts, which is far less user-friendly than the software they are familiar with. Many students will need extensive support to install, use and manage the software. One of the key challenges of teaching software-intensive subjects is the risk of teaching the software rather than the subject. To properly prepare students for further study and their future career they need to understand the modelling process rather than interface of a particular software.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;In this presentation we want to share our experience of using FloPy models in cloud-hosted (Google Colab) Jupyter notebooks for teaching groundwater flow modelling. FloPy is a Python library for constructing, running and post-processing MODFLOW groundwater flow models. Models are constructed by describing their properties using Python code. We use Jupyter notebooks to write, store and run the models. These notebooks provide a flexible environment, in which students can combine model code with documentation, results, notes and images. We use Google Colab which is a free service that hosts these notebooks online, so that students can work on the notebook using any computer with an internet connection.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;Teaching the class using FloPy and Colab yields several benefits compared to the approaches we used before, where students installed software with a graphical user interface (GUI) on their personal computers. Moving to a cloud-based environment has removed several technical barriers. There is no need to install any software and students need only a basic computer and internet access, reducing barriers to entry. Both FloPy and Google Colab are freely available, allowing students to use them outside the classroom as well. Students initially struggle with using Python as most of them have no programming experience. To overcome this, we give a basic introduction to Python and frequent exercises for students to practice.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;The combination of FloPy and Jupyter notebooks also offers benefits to learning. The approach is more transparent than GUI-based modelling tools. The entire model is defined within the notebook, providing students with a clear narrative describing each step of the modelling process. This allows students to develop a deeper understanding of the numerical modelling process. This promotes problem-solving and critical thinking. The cloud-hosted models can easily be shared, promoting cooperation between students and making it easier for the lecturer to help students diagnose and solve problems. In addition to groundwater flow modelling. this combination of tools allows students to develop valuable skills in programming and data analysis that are applicable to a wide range of geoscience careers.&amp;lt;/p&amp;gt;
Swift Search An open-source search engine

Businesses nowadays collect a huge amount of information. To search classified data in an efficient and streamlined manner, every organization will require a Search Engine that can be integrated into their websites and search through their data. To increase the productivity of searching the content with a modern, flexible site search experience, we are proposing a Search Engine that can help the organization to search efficiently. In this paper, we propose Swift Search which is an open-source search engine, with no additional cost involved. The search time is tested on an open-source tool called Meilisearch, which gives a promising level of performance.
Sentiment analysis of the Algerian social movement inception

Purpose This study provides an overview of the application of sentiment analysis (SA) in exploring social movements (SMs). It also compares different models for a SA task of Algerian Arabic tweets related to early days of the Algerian SM, called Hirak. Design/methodology/approach Related tweets were retrieved using relevant hashtags followed by multiple data cleaning procedures. Foundational machine learning methods such as Naive Bayes, Support Vector Machine, Logistic Regression (LR) and Decision Tree were implemented. For each classifier, two feature extraction techniques were used and compared, namely Bag of Words and Term Frequency–Inverse Document Frequency. Moreover, three fine-tuned pretrained transformers AraBERT and DziriBERT and the multilingual transformer XLM-R were used for the comparison. Findings The findings of this paper emphasize the vital role social media played during the Hirak. Results revealed that most individuals had a positive attitude toward the Hirak. Moreover, the presented experiments provided important insights into the possible use of both basic machine learning and transfer learning models to analyze SA of Algerian text datasets. When comparing machine learning models with transformers in terms of accuracy, precision, recall and F 1-score, the results are fairly similar, with LR outperforming all models with a 68 per cent accuracy rate. Originality/value At the time of writing, the Algerian SM was not thoroughly investigated or discussed in the Computer Science literature. This analysis makes a limited but unique contribution to understanding the Algerian Hirak using artificial intelligence. This study proposes what it considers to be a unique basis for comprehending this event with the goal of generating a foundation for future studies by comparing different SA techniques on a low-resource language.
Ordinalysis: Interpretability of multidimensional ordinal data

Ordinalysis is a software that enables dimension reduction, visualization and quantitative ordinality analysis of ordinal data. It is provided as a standalone executable file with a video tutorial. Applications of the software are shown on an ordinal synthetic dataset, ordinal real feature spaces and an ordinal image dataset. Ordinalysis allows the detection of violations of ordinality, the selection of the dimension reduction to preserve ordinality best or the demonstration of existing semantic ordinality in a set of raw data.
Dynamics of demand for sci-tech information by the national science and education sector at the current stage: The view from the library reading rooms

The factors influencing the demand for sci-tech information by the national science and by researchers, in particular, are discussed. The historical analysis demonstrate that the completeness of collection development with domestic publications increases the researchers’ demand. The collection use also depends on funding national science and, correspondingly, on the scope of research and scientific studies, and number of researchers. The dynamics of science is reflected not only in the penetration of collection entries and number of journal publications, but also by the publications dynamics within the given subject scope in the given time period.
The strategy for academic library development: From plans to implementation

The strategy of university library as an instrument of library management is discussed. The main vectors of library development are analyzed; external and internal factors to affect implementation are discussed.
Updating the national standard GOST R 7.0.49 «The systems of standards in information, librarianship and publishing. The State rubricator of sci-tech information. The structure, rules of application and maintenance»: The methodological aspects of structural and functional organization of the Rubricator

The main divisions of the standard GOST R 7.0.49 are discussed; key uses of the State Rubricator of Sci-tech Information (SRSTI) are examined, the methodological guidelines for the Rubricator are analyzed. The descriptions and sample links used in SRSTI are reviewed. The paper is prepared within the framework of the Government Order No. 1021070112681-2-1.2.1; 5.8.3 (FNEG-2022-0006).
The importance of presenting the Russian journal archives in open scientific space

In the current context of information risks of losing access to commercial international information resources, the problem of intensive development of Russian academic journals is of particular importance. One of the unsolved problems includes extremely low presence and visibility of journals’ archives in the digital information space. At the same time, the presence of electronic archives of journals plays essential role in authority of scientific serials, their bibliometric indices and ranks, enhancement of domestic and international readership, as well as the engagement of new authors. Possible approaches to preparing and presenting metadata in open access are discussed as the case study of «Geologiya i Geofizika» journal. Special attention is paid to the important role of academic libraries in digital archiving.
Architecture and construction within the context of cultural and recreational activities in CSTL C&amp;A

The types of target user groups of the sci-tech library, their needs, and conditions for their attending cultural events in the library, are explored. Different types of activities oriented on these user groups, are characterized. Themes, formats of presentation, and the most interesting and popular events are discussed. The paper is prepared within the framework of the Government Order No. 9101000.99.0.BB83AA0000 for 2022.
Word cloud analysis of<i>Family Practice</i>. Does the journal fulfil its editorial policy?

Journal Article Word cloud analysis of Family Practice. Does the journal fulfil its editorial policy? Get access Robert L Atenstaedt Robert L Atenstaedt Public Health Department, Betsi Cadwaladr University Health Board & Glyndwr University, Abergele Hospital, Llanfair Road, Abergele LL22 8DP, United Kingdom Corresponding author: Betsi Cadwaladr University Health Board, Abergele Hospital, Llanfair Road, Abergele LL22 8DP, United Kingdom. E-mail: Robert.Atenstaedt@wales.nhs.uk https://orcid.org/0000-0002-0963-9244 Search for other works by this author on: Oxford Academic PubMed Google Scholar Family Practice, cmad020, https://doi.org/10.1093/fampra/cmad020 Published: 28 February 2023