bluuebunny/crossref_metadata_2025 huggingface dataset:
ADVANCED TREATMENT IN RHEUMATOID ARTHRITIS. IS IT POSSIBLE TO TAPER THE BIOLOGICAL TREATMENT?
Authors:   Sf. Maria Clinical Hospital, Bucharest, Romania, Cambu Ina ,   Department of Internal Medicine and Rheumatology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania, Nuta Catalina Raluca ,   Sf. Maria Clinical Hospital, Bucharest, Romania,   Department of Internal Medicine and Rheumatology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania, Predeteanu Denisa ,   Sf. Maria Clinical Hospital, Bucharest, Romania,   Department of Internal Medicine and Rheumatology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania,   Research Center of the Pathology and Treatment of Systemic Rheumatic Diseases – RCRD, Bucharest, Romania
Published: September 2021

Rheumatoid arthritis (RA) is a systemic autoimmune disease, leading to synovial hypertrophy and adjacent bone and cartilage destruction. The combined use of biological agents and methotrexate (MTX) has revolutionised the treatment of RA producing significant improvements in clinical, radiographic and functional outcomes. The results of clinical study and experience of the specialities of rheumatology in clinical statement showed the long treatment may be associated with side effects, in addition biological treatment means high cost. The next goal should be remission without the use of biological agents. That’s why new treatment in RA means the tapering or even stopping the biological treatment in patients with RA who reached remission. In association with the new recommendation EULAR in 2013 there are many studies which showed the possibility of tapering or discontinuing the biological therapy in patients in sustained remission.
EVALUATION OF PATIENTS’ AWARENESS REGARDING GLUCOCORTICOIDS SIDE EFFECTS AND AVAILABLE PREVENTION STRATEGIES
Authors:   Carol Davila University of Medicine and Pharmacy, Bucharest, Plaisanu Cristina , Iorgoveanu Vasilia Cristina ,   Department of Internal Medicine and Rheumatology, Sf. Maria Clinical Hospital, Bucharest, Ionescu Ruxandra ,   Carol Davila University of Medicine and Pharmacy, Bucharest,   Department of Internal Medicine and Rheumatology, Sf. Maria Clinical Hospital, Bucharest
Published: September 2021

Glucocorticoids are drugs used in various medical areas, but well known for the myriad of side effects which are still a concern for the medical world. Latest recommendations on this matter aim at improving their management and implementing adequate prevention strategies. This aspect would change patient’s perspective on this treatment, reducing the fear and uncertainty associated with glucocorticoids. Objective. Our study focuses on analysing the level of information that patients hold about glucocorticoids side effects and if the available prevention strategies are known and applied in clinical practice. Material and methods. Study included 85 patients with rheumatic pathology and glucocorticoid therapy for at least 3 months. Study design was prospective observational and consecutive hospitalized patients were recruited, receiving and compiling a specific questionnaire. Results. 85 patients (84.7% women, mean age 54.42 ± 16.54 years) mostly under corticotherapy due to rheumatoid arthritis (44.7%) and systemic lupus erythematosus (23.5%) were recruited. Patients with higher education had the tendency to discontinue treatment (r=0.289, p=0.007). Moreover, reading prospectus has a great influence on treatment compliance (treatment risks significantly correlated with disease duration and glucocorticoid therapy duration (r=0.232; p < 0.032, r=0.252; p <0.024 respectively). Awareness about the risk of osteoporosis correlates with reading the prospectus (r= 0.396; p <0.0001), glucocorticoid treatment duration (r=0.209; p <0.032) and the use of vitamin D supplements (r=0,315; p <0.003). Regarding glucocorticoid administration timetable, we identified two groups – early morning and late evening (44.7% vs. 55.3%), showing a non-uniform treatment schedule. Conclusions. Our study shows an inadequate level of information regarding patient’s awareness on glucocorticoid treatment. Although excellent prevention strategies have been elaborated, there is a need of optimizing their accessibility to our patients.
CARBON DIOXIDE EMISSION FROM DIESEL ENGINE VEHICLES IN INTERMODAL TRANSPORT
Authors: Brzeziński Mariusz , Pyza Dariusz
Published: September 2021

Currently, many logistics operators operate in both domestic and foreign markets using various forms of transport organization. Choosing a corresponding technology and appropriate form of transport has an influence not only delivery time and costs, but also has an impact on the environment as a whole. There is a plethora of public research available in global literature discussing various ways of exploiting transport. On the other hand, there is a lack of complex studies detailing carbon emissions coming from transport activity. Specifically, where a theory of organic fuel combustion in the form of a chemical reaction with oxygen is considered. To fill this gap, we offer an innovative Emission Model of Industrial Sources (EMIS) method. This method makes it possible to determine the amount of CO2 emitted into the atmosphere during various transport methods. It also enables us to estimate, in terms of CO2 output, a threshold where transport of containers via combined mode becomes more favourable for the environment, than road transport. We ran a simulation of our algorithm to create boundary conditions. This let us prepare a regression function of CO2 emission, for intermodal and road transport as a function of various transport distances. The simulation results suggest that our approach may be used by supervisory institutions, which are responsible further developing and utilizing combined transport.
Selection Functions in Astronomical Data Modeling, with the Space Density of White Dwarfs as a Worked Example
Authors: Rix Hans-Walter , Hogg David W. , Boubert Douglas , Brown Anthony G. A. , Casey Andrew , Drimmel Ronald , Everall Andrew , Fouesneau Morgan , Price-Whelan Adrian M.
Published: September 2021

Statistical studies of cataloged object properties are central to astrophysics. But one cannot model those objects’ population properties without the sample’s selection function, the quantitative understanding of which objects could have ended up in such a catalog. As didactic introductions to this topic are scarce in the astrophysical literature, we provide one here, addressing the following questions: What is a selection function? On what arguments
q
should it depend? Over what domain must a selection function be defined? What simplifying approximations can be made? And, how is a selection function used in “modeling”? We argue that volume-complete samples, limited by the faintest objects, reflect a highly suboptimal selection function, needlessly reducing the number of bright and usually rare sample members. We illustrate these points by a worked example: github.com/gaia-unlimited/WD-selection-function, deriving the space density of white dwarfs (WDs) in the Galactic neighborhood as a function of their luminosity and color, Φ0(M

G
, (B − R)) in [mag−2 pc−3]. We construct a sample



of 105 presumed WDs through straightforward selection cuts on the Gaia EDR3 catalog in magnitude, color, and parallax,
q
= (G, (B − R), ϖ). We then combine a simple model for Φ0 with this selection function’s

S



(
q
)

effective survey volume to estimate Φ0(M

G
, (B − R)) precisely and robustly against the detailed choices for

S



(
q
)

. This resulting WD luminosity–color function Φ0(M

G
, (B − R)) differs dramatically from the initial number density distribution in the luminosity−color plane: by orders of magnitude in density and by four magnitudes in density peak location.
The Hot Circumgalactic Medium of the Milky Way: Evidence for Supervirial, Virial, and Subvirial Temperatures; Nonsolar Chemical Composition; and Nonthermal Line Broadening
Authors: Das Sanskriti , Mathur Smita , Gupta Anjali , Krongold Yair
Published: September 2021

For the first time, we present the simultaneous detection and characterization of three distinct phases at >105 K in z = 0 absorption using deep Chandra observations toward Mrk 421. The extraordinarily high signal-to-noise ratio (≥60) of the spectra has allowed us to detect a hot phase of the Milky Way circumgalactic medium (CGM) at

3.2

−
0.5

+
1.5

×

107 K coexisting with a warm-hot phase at 1.5 ± 0.1 × 106 K and a warm phase at 3.0 ± 0.4 × 105 K. The warm-hot phase is at the virial temperature of the Galaxy, and the warm phase may have cooled from the warm-hot phase, but the supervirial hot phase remains a mystery. We find that [C/O] in the warm and warm-hot phases, [Mg/O] in the warm-hot phase, and [Ne/O] in the hot phase are supersolar, and the hot and the warm-hot phases are α-enhanced. Nonthermal line broadening is evident in the warm-hot and the hot phases, and it dominates the total line broadening. Our results indicate that the >105 K CGM is a complex ecosystem. It provides insights on the thermal and chemical history of the Milky Way CGM and theories of galaxy evolution.
KMTNet Nearby Galaxy Survey. III. Deficient Hα Flux in the Extended Disks of Spiral Galaxies
Authors: Byun Woowon , Sheen Yun-Kyeong , Seon Kwang-Il , Ho Luis C. , Lee Joon Hyeop , Jeong Hyunjin , Kim Sang Chul , Park Byeong-Gon , Lee Yongseok , Cha Sang-Mok , Ko Jongwan , Kim Minjin
Published: September 2021

We perform a deep, wide-field imaging survey of nearby galaxies using Hα and broadband filters to investigate the characteristics of star formation in galaxies. Motivated by the finding that star formation rates (SFRs) derived from Hα fluxes in dwarf galaxies are systematically lower than those inferred from far-ultraviolet (FUV) fluxes, we attempt to determine whether the same trend exists in the extended disks of two star-forming galaxies. We perform spatially resolved photometry using grid-shaped apertures to measure the FUV and Hα fluxes of star-forming regions. We also perform spectral energy distribution (SED) fittings using 11 photometric data points (FUV-to-MIR), including data from the literature, to estimate the local properties such as internal attenuation of individual star-forming clumps. Comparing SFRFUV and SFRHα
, which are converted from the Hα and FUV fluxes corrected for the local properties, we find that SFRHα
/SFRFUV tend to decrease as the SFR decreases. We evaluate possible causes of this discrepancy between the two SFRs by restricting parameters in the SED fitting and conclude that deficient Hα fluxes in the extended disks of galaxies are tightly correlated with recent starbursts. The strong and short starburst, which has been rapidly suppressed over the last 10 Myr, seems to induce a significant discrepancy between the SFRHα
and SFRFUV. In addition, the recent bursts in the extended disks of galaxies appear to have occurred azimuth-symmetrically, implying that these were likely triggered by gas accretion or internal processes rather than external perturbation.
Determinant of Smoking Behavior among Elementary Student in Indonesia: A Structure Equation Model
Authors: Haryanto Astrid Novita , Noer Melinda , Kusumayati Agustin , Machmud Rizanda , Hafizurrachman Hafizurrachman , Bachtiar Adang
Published: September 2021

BACKGROUND: Initial smoking exposure may occur during early adolescence (aged 10–12 years old), and it increases overtime. Although several factors for smoking behaviors exist among adolescents, there are few studies address determinant of smoking behavior by adding others variables in theory of plan behavior such as smoking refusal skills, self-regulation, parenting, family function, environment, and culture.

AIM: The aim of this study was, therefore, to evaluate the determinant of smoking behavior among elementary student in Indonesia using a structural equation model.

METHODS: A cross-sectional survey was carried out from June to October 2019 in West Java, Indonesia. For each school, students were selected using a systematic random sampling technique. The study included girls and boys ages 10–12. The consent was obtained by the parent or guardian. Structural equation modeling was used for analysis.

RESULTS: The mean age was 10.56 years (SD = 0.37). About 28.6% of them were currently smoking with aged of first use was 10.02 (SD = 0.19). More than half (56%) of their family were currently smoking too and friend smoking was 41.7%. The final model accounted for 27% and 39% of the variance of intention and smoking behavior, respectively, has both direct and indirect effects through empowerment on self-care behaviors toward pregnancy-related complication.

CONCLUSION: The present study was intended to expand the theory of planned behavior by including additional variables in its model: Smoking refusal skills, self-regulation, parenting, family function, environment, and culture. This study also provides a significant contribute for clinical a practice and policy-maker as a basic data to establish future intervention to promote no tobacco use among elementary student to achieve optimal well-being to prevent a fatal disease.
Assessment of Contralateral Biopsy Technique for Improving Tissue Changes in Patients with Tongue Malignancy
Authors: Alhatab Nawres , Abusanna Muntathar Muhsen , Salih Hydar
Published: September 2021

Background: Oral cancer is one of the most common type of head and neck cancer, with a 5 year survival rate of < 50%. One of the major problems of oral cancer include the late stage of disease at the time of diagnosis. Mirror image biopsy is a new technique that can be used for detection of early changes in the oral mucosa. Aim of the study: To histologically assess the reflect copy biopsy occupied from clinically usual observing mucosa at consistent contralateral  anatomical place to the main lesion in patients identified with tongue squamous cell carcinoma to notice any indication of arena alteration in oral mucosa. Materials and methods: Seven patients diagnosed with squamous cell carcinoma of the tongue underwent reflect copy biopsy from clinically usual observing mucosa at consistent contralateral anatomical place to the main lesion. The reflect copy biopsy example were exposed to histopathological check. Results: of the seven patients included, four were male and three were female, with an age range from 45 years to 64 years (median 54.5 years). One of the biopsies revealed severe dysplasia and six-revealed hyperplasia of the epithelium. Conclusion: Mirror image biopsy is a useful tool to detect the early field changes in oral mucosa in order to prevent further progression to oral cancer.
Clinical Evaluation of the Effect of Implant-Supported and Implant Retained Distal Extension Removable Partial Dentures on the Supporting Structures
Authors: Kotb Ragia Saad Mohamed , Gamal Ahmed Hassan Ahmed , Mohamed Tolba M. Agamy Emad , Fekry Mohamed Gehan
Published: September 2021

Objective: To evaluate and compare the effect of implant supported versus implant retained removable partial denture restoring Kennedy's class I cases on the supporting structures by measuring modified gingival index and probing depth for abutment teeth and implants.
Subjects and Methods: Twelve patients; who had Kennedy class I mandibular partially edentulous ridge extending distal to the first or second premolar,   were selected from the outpatient clinic, Prosthodontics Department, Faculty of Dentistry, Minia University. The patients were classified into two equal groups; according to the implant superstructures either dome shaped abutment or ball and socket attachment.  Each Patient of both groups had two implants in second molar position (one in each side) and received removable partial denture of the same design. Patients were followed up for one year clinically. Group I: Six patients received RPD supported by dome shaped short abutments.  Group II six patients received RPD retained by ball and socket attachments.
Results: Results revealed that, there was no statistically significant difference between the two groups regarding modified gingival index and probing depth around the abutment teeth and implant abutment.
Conclusion:  The use of dome shaped abutment or ball and O-ring attachment have the same effect on gingival index and probing depth around natural abutments and implants in Kennedy class I mandibular situations.
Determinants of Coronary Heart Disease Incidence among Indonesian Hajj Pilgrims Hospitalized in Saudi Arabia in 2019
Authors: Naim Juniarty , Wahiduddin Wahiduddin , Masni Masni , Amiruddin Ridwan , Irwandy Irwandy , Bustan M. Nadjib
Published: September 2021

BACKGROUND: Cardiovascular diseases (CVDs) are the main causes of death worldwide, including in the hajj pilgrims. Coronary heart disease (CHD) is the most common CVDs in Indonesian hajj pilgrims hospitalized in Saudi Arabia.

AIM: This study aimed to determine the determinants of the CHD incidence among Indonesian hajj pilgrims hospitalized in Saudi Arabia in 2019.

METHODS: This study was an observational analytic study with a case–control design. The study was conducted in Makassar using data from the integrated Hajj computerized system in the health sector (siskohatkes) Hajj Health Center (Puskeshaji) in January–June 2021. Cases were pilgrims hospitalized in Saudi Arabia with a diagnosis of CHD, about 186 people, and controls were pilgrims hospitalized with diagnoses other than CVDs. Selection of controls by matching age and sex with a ratio of 1:1. The determinants analyzed included education, high blood pressure, high blood sugar levels, high low-density lipoprotein (LDL) cholesterol levels, excess body mass index (BMI), and smoking. Data analysis was using the STATA program with an odds ratio (OR) test and multiple logistic regression.

RESULTS: The most respondents were 65 years (48.39%), female respondents, about 61.83%. Most respondents’ education was in elementary school, about 31.99%. Multivariate analysis showed that high blood pressure (OR = 2.32, 95% confidence index [CI] = 1.50–3.57), high blood sugar levels (RO = 1.90, 95% CI = 1.06–3.40), high LDL cholesterol levels (RO = 1.82, 95% CI = 1.15–2.88), and excess BMI (RO = 1.73, 95% CI = 1.07–2.68) were risk factors for the CHD incidence. However, education and smoking were not risk factors for CHD.

CONCLUSION: By multiple logistic regression analyzes, the study revealed that the probability of CHD when having those four risk factors was 85.69%.
Data Standards for the Phenology of Plant Specimens
Authors: Pearson Katelin , Ellwood Libby , Gilbert Edward , Guralnick Rob , Macklin James , Nelson Gil , Sweeney Patrick , Stucky Brian , Wieczorek John , Yost Jenn
Published: September 2021

Phenological data (i.e., data on growth and reproductive events of organisms) are increasingly being used to study the effects of climate change, and biodiversity specimens have arisen as important sources of phenological data. However, phenological data are not expressly treated by the Darwin Core standard (Wieczorek et al. 2012), and specimen-based phenological data have been codified and stored in various Darwin Core fields using different vocabularies, making phenological data difficult to access, aggregate, and therefore analyze at scale across data sources. The California Phenology Network, an herbarium digitization collaboration launched in 2018, has harvested phenological data from over 1.4 million angiosperm specimens from California herbaria (Yost et al. 2020). We developed interim standards by which to score and store these data, but further development is needed for adoption of ideal phenological data standards into the Darwin Core. To this end, we are forming a Plant Specimen Phenology Task Group to develop a phenology extension for the Darwin Core standard. We will create fields into which phenological data can be entered and recommend a standardized vocabulary for use in these fields using the Plant Phenology Ontology (Stucky et al. 2018, Brenskelle et al. 2019). We invite all interested parties to become part of this Task Group and thereby contribute to the accesibility and use of these valuable data. In this talk, we will describe the need for plant phenological data standards, current challenges to developing such standards, and outline the next steps of the Task Group toward providing this valuable resource to the data user community.
Detecting Epidemic Diseases Using Sentiment Analysis of Arabic Tweets
Authors: Baker Qanita , Shatnawi Farah , Rawashdeh Saif , Al-Smadi Mohammad , Jararweh Yaser
Published: September 2021

Opinion mining is an important step towards facilitating information in health data. Several studies have demonstrated the possibility of tracking diseases using public tweets. However, most studies were applied to English language tweets. Influenza is currently one of the world's greatest infectious disease challenges. In this study, a new approach is proposed in order to detect Influenza using machine learning techniques from Arabic tweets in Arab countries. This paper is the first study of epidemic diseases based on Arabic language tweets. In this work, we have collected, labeled, filtered and analyzed the influenza-related tweets written in the Arabic language. Several classifiers were used to measure the quality and the performance of the approach, which are: Naive Bayes, Support Vector Machines, Decision Trees, and K-Nearest Neighbor. The classifiers which achieved the best accuracy results for the three experiments were: Naïve Bayes with 89.06%, and K-Nearest Neighbor with 86.43%, respectively.
A Framework for Online Social Network Volatile Data Analysis: A Case for the Fast Fashion Industry
Authors: Hani Anoud , Al-Obeidat Feras , Benkhelifa Elhadj , Adedugbe Oluwasegun
Published: September 2021

Consumer satisfaction is an important part for any business as it has been shown to be a major factor for consumer loyalty. Identifying satisfaction in products is also important as it allows businesses alter production plans based on the level of consumer satisfaction for a product. With consumer satisfaction data being very volatile for some products due to a short requirement period for such products, current consumer satisfaction must be identified within a shorter period before the data becomes obsolete. The fast fashion industry, which is part of the fashion industry, is adopted as a case study in this research. Unlike slow fashion, fast fashion products have short shelf lives and their retailers must be able to react swiftly to consumer demands. This research aims to investigate the effectiveness of current data mining techniques when used to identify consumer satisfaction towards fast fashion products. This is carried out by designing, implementing and testing a software artefact that utilises data mining techniques to obtain, validate and analyse fast fashion social data, sourced from Twitter, to identify consumer satisfaction towards specific product types. In addition, further analysis is carried out using a sentiment scaling method adapted to the characteristics of fast fashion.
Analysing Bias in Political News
Authors: De Arruda Gabriel , Roman Norton , Monteiro Ana
Published: September 2021

Although of paramount importance to all societies, the fact that media can be biased is a troubling thought to many people. The problem, however, is by no means easy to solve, given its high subjectivity, thereby leading to a number of different approaches by researchers. In this work, we addressed media bias according to a tripartite model whereby news can suffer from a combination of selective coverage of issues (Selection Bias), disproportionate attention given to specific subjects (Coverage Bias), and the favouring of one side in a dispute (Statement Bias). To do so, we approached the problem within an outlier detection framework, defining bias as a noticeable deviation from some mainstream behaviour. Results show that, in following this methodology, one can not only identify bias in specific outlets, but also determine how that bias comes about, how strong it is, and the way it interacts with other dimensions, thereby rendering a more complete picture of the phenomenon under inspection.
Ant-Set: A Subset-Oriented Ant Colony Optimization Algorithm for the Set Covering Problem
Authors: Schmitt Murilo Falleiros Lemos , Mulati Mauro , Constantino Ademir , Hernandes Fábio , Hild Tony
Published: September 2021

This paper proposes an algorithm for the set covering problem based on the metaheuristic Ant Colony Optimization (ACO) called Ant-Set, which uses a lineoriented approach and a novelty pheromone manipulation based on the connections between components of the construction graph, while also applying a local search. The algorithm is compared with other ACO-based approaches. The results obtained show the effectiveness of the algorithm and the impact of the pheromone manipulation.
Experimental Evaluation of Three Value Recommendation Methods in Interactive Configuration
Authors: Fargier Hélène , Gimenez Pierre-François , Mengin Jérôme
Published: September 2021

The present work deals with the recommendation of values in interactive configuration, with no prior knowledge about the user, but given a list of products previously configured and bought by other users ("sales histories"). The basic idea is to recommend, for a given variable at a given step of the configuration process, a value that has been chosen by other users in a similar context, where the context is defined by the variables that have already been decided, and the values that the current user has chosen for these variables. From this point, two directions have been explored. The first one is to select a set of similar configurations in the sales history (typically, the k closest ones, using a distance measure) and to compute the best recommendation from this set - this is the line proposed by [Coster et al., 2002]. The second one, that we propose here, is to learn a model from the entire sample as representation of the users' preferences, and to use it to recommend a pertinent value; three families of models are experimented: the Bayesian networks, the naive Bayesian networks and the lexicographic preferences trees.
Solver Requirements for Interactive Configuration
Authors: Falkner Andreas , Haselböck Alois , Krames Gerfried , Schenner Gottfried , Schreiner Herwig , Taupe Richard
Published: September 2021

Interactive configuration includes the user as an essential factor in the configuration process. The two main components of an interactive configurator are a user interface at the front-end and a knowledge representation and reasoning (KRR) framework at the back-end. In this paper we discuss important requirements for the underlying KRR system to support an interactive configuration process. Representative of many reasoning systems and tools used for implementing product configurators, we selected MiniZinc, Choco, Potassco, Picat, CP-SAT solver, and Z3 for evaluation and reviewed them against the identified requirements. We observe that many of those requirements are not well supported by existing stand-alone solvers.
Speaker/Style-Dependent Neural Network Speech Synthesis Based on Speaker/Style Embedding
Authors: Sečujski Milan , Pekar Darko , Suzić Siniša , Smirnov Anton , Nosek Tijana
Published: September 2021

The paper presents a novel architecture and method for training neural networks to produce synthesized speech in a particular voice and speaking style, based on a small quantity of target speaker/style training data. The method is based on neural network embedding, i.e. mapping of discrete variables into continuous vectors in a low-dimensional space, which has been shown to be a very successful universal deep learning technique. In this particular case, different speaker/style combinations are mapped into different points in a low-dimensional space, which enables the network to capture the similarities and differences between speakers and speaking styles more efficiently. The initial model from which speaker/style adaptation was carried out was a multi-speaker/multi-style model based on 8.5 hours of American English speech data which corresponds to 16 different speaker/style combinations. The results of the experiments show that both versions of the obtained system, one using 10 minutes and the other as little as 30 seconds of target data, outperform the state of the art in parametric speaker/style-dependent speech synthesis. This opens a wide range of application of speaker/style dependent speech synthesis based on small quantities of training data, in domains ranging from customer interaction in call centers to robot-assisted medical therapy.
An Ontological Approach to Support Dysfunctional Analysis for Railway Systems Design
Authors: Debbech Sana , Collart-Dutilleul Simon , Bon Philippe
Published: September 2021

Dysfunctional analysis is an essential and demanding task in the early development stages of safety-critical systems (SCSs). Nevertheless, current practices present several drawbacks. Generally, a common dysfunctional analysis conceptualization is missing and it is dependent on safety analysis techniques. Moreover, some safety analysis methods require well-known system behaviors expressed by dynamic models such as sequence diagrams and finite automata. However, the dynamic character of these models increases their susceptibility to changes and then they are not obtainable in the early design stages. Since dysfunctional analysis highly relies on the experience of safety analysts and the feedback (REX) obtained from previous systems development, there is a need to formalize this knowledge domain in a structured way to ensure its future reuse. Furthermore, safety measures derived from this dysfunctional analysis approach must be strongly linked to a goal-oriented perspective and adapted to a specific context. For this purpose, this paper presents a real-world semantics interpretation and conceptualization of dysfunctional analysis related concepts based on the Unified Foundational Ontology (UFO) and well-known standards to avoid ambiguities. The proposed Dysfunctional Analysis Ontology (DAO) aims to provide a systematization of the goal-oriented dysfunctional analysis through a terminological clarification in order to prevent hazards in the first design phases. Then, a DAO formalization is proposed using the Web Ontology Language (OWL). Finally, the DAO pattern is applied to two different real critical scenarios from the railway domain in order to illustrate and evaluate this ontological approach.
The Modified Principal Component Analysis Feature Extraction Method for the Task of Diagnosing Chronic Lymphocytic Leukemia Type B-CLL
Authors: Topolski Mariusz
Published: September 2021

The vast majority of medical problems are characterised by the relatively high spatial dimensionality of the task, which becomes problematic for many classic pattern recognition algorithms due to the well-known phenomenon of the curse of dimensionality. This creates the need to develop methods of space reduction, divided into strategies for the selection and extraction of features. The most commonly used tool of the second group is the PCA, which, unlike selection methods, does not select a subset of the original set of features and performs its mathematical transformation into a less dimensional form. However, natural downside of this algorithm is the fact that class context is not present in supervised learning tasks. This work proposes a feature extraction algorithm using the approach of the pca method, trying not only to reduce the feature space, but also trying to separate the class distributions in the available learning set. The problematic issue of the work was the creation of a method of feature extraction describing the prognosis for a chronic lymphocytic leukemia type B-CLL, which will be at least as good, or even better than when compared to other quality extractions. The purpose of the research was accomplished for binary and three-class cases in the event in which for verification of extraction quality, five algorithms of machine learning were applied. The obtained results were compared with the application of paired samples Wilcoxon test.
Exploring Virtual Reality in the Higher Education Classroom: Using VR to Build Knowledge and Understanding
Authors: Young Gareth , Stehle Sam , Walsh Burcin , Tiri Egess
Published: September 2021

irtual reality (VR), as an informative medium, possesses the potential to engage students with immersive, interactive, and informative experiences. When presented in VR, immersive virtual environments (IVEs) can provide three-dimensional visual simulations that can be used to inform students about concepts in specific contexts that would be near impossible to achieve with more traditional teaching methodologies. It is proposed that existing learning frameworks can benefit from exploring the modalities of interaction that are presently afforded via VR from the experiential perspectives of the students. An evaluation is presented that focused on the appraisal of student experiences of immersive technologies as applied in a higher education context, specifically in the use of VR for the exploration of geomorphology theory by physical geography students. This research supports further development of the immersive learning discipline from three different perspectives. First, an empathy mapping method was applied to visualize student experiences and externalize our observed knowledge of student users for creating a shared understanding of their needs and to aid in lesson planning decision making when using VR in the classroom. Second, student experiences were captured using a technology-focused user experience questionnaire to obtain student attitudes immediately post-task. Finally, to assist teachers with the creation of a student-centered lesson plans that incorporate VR in the classroom, eight heuristic guidelines (focus, provocation, stimulation, collaboration, control, digital life, learner skills, multimodal experience) were developed. It is proposed that these findings can be used to provide support for the use of mixed reality and immersive virtual environments in learning that encompass the challenges faced by students and the interdisciplinary education community at large.
Bite-Sized Virtual Reality Learning Applications: A Pattern-Based Immersive Authoring Environment
Authors: Horst Robin , Naraghi-Taghi-Off Ramtin , Rau Linda , Dorner Ralf
Published: September 2021

Bite-sized learning is a current educational trend in which educators divide content into relatively small, easily comprehensible chunks, called nuggets. In this paper, we introduce an authoring toolkit that relies on VR implementation of nuggets and show that a nugget-based approach is also facilitating the authoring of VR learning content. In particular, we present Immersive Nugget Tiles (IN-Tiles), a novel authoring toolkit aimed at authors who are not experts in VR. With IN-Tiles, manipulating VR nuggets and authoring VR learning content can be directly accomplished within a virtual environment allowing authors to immediately experience the results of their authoring efforts in VR. We discuss the underlying concepts of IN-Tiles, specifically how to visualize VR nuggets in a virtual environment and how to present affordances that support authoring and manipulating VR nuggets. We report the results of a user study where we evaluated the IN-Tiles toolkit and compared it to a conventional 2D authoring environment that also relies on component-based VR. The results support the hypothesis that nugget-based immersive authoring tools are suitable to create bitesized VR applications successfully and that authoring directly in VR has an added value particularly for authors who are no IT specialists.
A Systematic Review of Research about Game-based Learning in Virtual Worlds
Authors: Pellas Nikolaos , Mystakidis Stylianos
Published: September 2021

While a substantial body of literature has well-documented and demonstrated considerable potentials of virtual worlds (VWs) across a variety of learning subjects, little is known today regarding game-based learning (GBL) approaches that can be applied. This systematic literature review presents the current state of knowledge and practice about GBL approaches in VWs from Primary and Secondary (K-12) to Higher education (HE). It provides guidance for instructional designers and scholars by systematically appraising and summarizing the most relevant existing research articles published from 2006 until December 2019. Twenty-eight studies were finally included for a detailed analysis and synthesis during the selection and screening process. The results indicated that GBL in VWs gained popularity from 2014 until 2016. Many studies in K-12 and HE settings were focused on describing and evaluating the appropriateness or the effectiveness of the applied instructional design processes using various game prototypes to disseminate their findings on user experience, usability issues, students' outcomes, and/or learning performance. This study contributes by reviewing how GBL approaches in VWs can potentially benefit students' learning performance, leading to a higher level of satisfaction and dimensions of disciplinary understanding. It also proposes six concrete recommendations guiding game design and development to support learning in VWs.
Finding the Gaps about Uses of Immersive Learning Environments: A Survey of Surveys
Authors: Beck Dennis , Morgado Leonel , Shea Patrick
Published: September 2021

Advancing the field of research in Immersive Learning Environments requires avoiding the pitfalls of previous educational technologies. Studies must consider the actual use of these environments and the context where it occurs, not simply the technocentric perspectives on these environments. This paper provides an overview and analysis of surveys on this topic, in order to map the field and find out which information on actual uses of Immersive Learning Environments are reported, and hence which gaps need to be covered towards a robust, encompassing knowledge on their relationship with learning. Collected accounts of use were clustered via thematic analysis and contrasted with research areas in learning and technology, highlighting the gaps in the field and serving as a blueprint for research agendas on uses of immersive learning environments.
Energy Efficient Composite Metric Based Routing Protocol for Internet of Things
Authors: Natesan Sathishkumar , Krishnan Rajakumar
Published: September 2021

The Routing Protocol for Low Power and Lossy Networks (RPL) is operated by gadgets comprised of many devices of embedded type with limited energy, memory as well as resources that do their process. The improvements in the life of the network and energy conservation are the key challenging features in Low Power and Lossy Networks (LLN). Obviously, the LLN has a key strategic part in routing. The Internet of Things (IoT) device is expected to make the apt choice. In LLN, the poor routing choice leads to traffic congestion, reduction in power as well as packet loss ratio. The task in the proposal analyzes Delay (D), Load (L) and Battery Discharge Index (BDI) pivoted Energy Efficient Composite Metric Routing (EECMR) protocol for LLN. The performance of the work in the proposal is evaluated by the COOJA simulator. It outperforms with respect to Network Lifetime (NL), Delay as well as Packet Delivery Ratio (PDR) contrasted to the routing metrics like Traffic Load (TL), Link Quality (LQ), Residual Energy (RE), RE-Battery Discharge Index (RE-BDI) and Hop Count (HC).
Fuzzy Adaptive Data Packets Control Algorithm for IoT System Protection
Authors: Apiecionek Łukasz , Biedziak Matusz
Published: September 2021

One of huge problem for recent IT systems are attacks on their resources called Distributed Denial of Service attacks. Many servers which are accessible from public network were a victim of such attacks or could be in the future. Unfortunately, there is still no effective method for protecting network servers against source of the attack, while such attack could block network resources for many hours. Existing solutions for protecting networks and IoT systems are using mainly firewalls and IDS/IPS mechanisms, which is not sufficient. This article presents the method minimizing the DDoS attacks. Proposed method provides possibilities for the network administrators to protect their servers and IoT network resources during the attack. The proposed fuzzy adaptive algorithm is using Ordered Fuzzy Numbers for predicting amount of packets which could be passed over the network boarder gateway. Proposed solution will give the opportunity for ordinary users to finish their work when the attack occurs.
Description of four new terrestrial diatom species from Luticola and Microcostatus genera from South Africa
Authors: Rybak Mateusz , Kochman-Kędziora Natalia , Peszek Łukasz
Published: September 2021

The knowledge about terrestrial diatom assemblages in southern Africa is rather limited, despite a long history of diatom research in this area. Terrestrial habitats are places of characteristic diatom floras, dominated by species resistant to desiccation which are able to thrive in conditions of limited water availability. The presented work expands the knowledge about these unique habitats. During the study on terrestrial moss-inhabiting diatoms from Western Cape Province (South Africa), four taxa with a unique set of valve features have been found and described herein as new species, based on light and scanning electron microscopy. These new species are:Luticola microcephalaM. Rybak, Peszek & Kochman-Kędziora,sp. nov.,Luticola asymmetricaM. Rybak, Kochman-Kędziora & Peszek,sp. nov.,Luticola terrestrisKochman-Kędziora, M. Rybak & Peszek,sp. nov.andMicrocostatus meridionalisPeszek, M. Rybak & Kochman-Kędziora,sp. nov.Algal community composition had low species richness (9–15 taxa per sample) and samples were dominated by:Humidophila contenta,Nitzschia brevissimaand Eunotia aff. pseudominor. The three newLuticolaspecies formed numerous populations, exceeding 10% of the share, whereasMicrocostatus meridionalisreached 5.4%. Basic morphological data of associated diatom flora together with detailed micrographs are also provided.
A comparison of collecting methods in relation to the diversity of Collembola in scree habitats
Authors: Jureková Nikola , Raschmanová Natália , Miklisová Dana , Kováč Ľubomír
Published: September 2021

We compared the species composition, relative abundances and life form structure of subterranean Collembola (Hexapoda) captured by two different methods along a depth gradient of five forested scree sites in the Western Carpathians, Slovakia: (1) high-gradient extraction of soil samples, and (2) collection using subterranean traps. Our results showed that the soil samples were more efficient in covering species richness at the majority of the sites. The body size of the captured animals depended remarkably on the sampling method. Extraction was more effective in collecting smaller, less active hemi- and euedaphic forms of Collembola, while collection by subterranean traps favoured both motile ground-dwelling as well as relatively large, active euedaphobionts. Additionally, different trends in the vertical stratification of Collembola life forms and their relative abundances were detected by the two methods. Atmobionts and epigeonts, forming the greater part of the communities in traps compared to soil samples, were distributed along the entire scree profiles, but their relative abundance and species numbers had a strongly decreasing trend with depth. Moreover, motile, large hemi- and euedaphic forms had high relative abundances in traps in the middle and deeper scree levels at three sites. In contrast, in soil samples the hemi- and euedaphobionts with small body size were abundant on the surface of the MSS sites. Thus, soil sampling applied before installation of subterranean traps may serve as an appropriate complementary technique to obtain a more complete pattern of Collembola diversity in forested scree habitats.
The distribution and behavioral characteristics of plateau pikas (Ochotona curzoniae)
Authors: Qiu Jun , Ma Cang , Jia Ying-Hui , Wang Jin-Zhao , Cao Shou-Kai , Li Fang-Fang
Published: September 2021

Plateau pikas (Ochotona curzoniae) are regarded as one of the main causes of the degradation of alpine meadows in the Qinghai-Tibet Plateau (QTP). The population density of plateau pikas is directly related to the degree of grassland damage. In this study, field observation was conducted for one week in the southeastern QTP in August 2019. A random encounter model (REM) was used to estimate the population density of plateau pikas from photographs and videos, and the frequencies of different behaviors were calculated. In addition, the effects of water-source distance and terrain on the distribution of plateau pikas and the frequencies of different pika behaviors under different population densities were explored. The observations and knowledge derived from this study provide a reference for the population control of plateau pikas.
Ce que « se laver » signifie : histoire de pratiques et d’expériences
Authors: Richelle Sophie
Published: September 2021

Tout au long du XX e  siècle, les normes d’hygiène d’ablution totale se répandent dans l’ensemble de la société, mais les salles de bains privatives restent durablement l’apanage des plus aisés. Face au manque d’infrastructures disponibles, les bains publics sont une réponse collective à ces nouvelles nécessités. Parmi eux, les bains-douches des charbonnages, qui font l’objet de cet article, constituent un cas d’étude exceptionnel. Dans une histoire sociale des mines encore à faire, ils sont un observatoire inédit de la construction de nos rapports aux corps, à leur hygiène et à leur propreté, ainsi que des différenciations sociales et genrées qui les traversent dans des sociétés ouvrières en voie de transformation au XX e  siècle.
Comment approcher la trajectoire d’un cluster rural ? Témoignages de la région viticole de Bordeaux
Authors: Leszczyńska Dorota
Published: September 2021

Cet article explore le développement historique de la région des vins de Bordeaux en mobilisant la théorie du cluster. Une méthodologie qualitative et des entretiens ont été utilisés pour mener une étude au sein du cluster. La dynamique de la trajectoire du cluster est appréhendée en s’appuyant sur ses séquences historiques. Les résultats illustrent la manière dont les connaissances incorporées dans un cluster au cours de l’histoire, ainsi que leur transmission à travers les siècles, contribuent au développement longitudinal de la trajectoire du cluster.
La transition numérique des structures œuvrant au service de l’intérêt général peut-elle augmenter leur impact social ?
Authors: Sibieude Thierry , Leclerc Élise
Published: September 2021

Quelles sont les conditions de la maximisation de l’impact, et notamment sa pérennisation, du mécénat de compétence tech au profit des organisations dont la mission relève directement et prioritairement de la gestion du bien commun au service de l’intérêt général ? Telle est la question de recherche que la Fondation Devoteam a posée à l’ESSEC au moment de la mise en place de son programme #TechFor-People, afin de s’assurer de la pertinence de ce programme pour répondre aux besoins sur le long terme des structures de l’ESS (Économie Sociale et Solidaire) en transformation digitale. Afin de répondre à cette problématique l’ESSEC a réalisé une évaluation d’impact social fondée sur les cadres théoriques de la théorie du changement et de la théorie des parties prenantes, avec l’analyse de besoin, une collecte de données qualitatives ex-ante ainsi qu’une collecte de données quantitative ex-ante et ex-post. L’analyse de ces collectes révèle une dichotomie spécifique aux structures de l’ESS utilisant le programme que nous avons catégorisées en Tech Driven d’une part, ou Tech Powered d’autre part, avec des besoins et des conditions de pérennisation spécifiques en fonction de la catégorie qui leur correspond.