bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data mining to detect variables associated with the occupational aspirations of Spanish 15-year-old students
Authors: Expósito-Casas Eva , González-Benito Ana , López-Martín Esther 
Published: June 2022

AbstractThe purpose of this work is to identify contextual variables that help to explain the occupational aspirations of Spanish 15-year-old students. This is done by performing a secondary analysis of the PISA2018 test. Data have been analysed using decision trees introducing the students’ expected occupational status as a dependent variable (DV), and the other items and indicators considered as predictors. The results show that the variables that contributed most to explaining DV were grade repetition, mastery goal orientation, enjoying reading and self-concept of reading. The findings of this exploratory work can be used as a basis for further studies aimed at establishing causal relationships between these variables and students' occupational aspirations.
Multi-band PCA based ear recognition technique
Authors: Zarachoff Matthew Martin , Sheikh-Akbari Akbar , Monekosso Dorothy 
Published: June 2022

AbstractPrincipal Component Analysis (PCA) has been successfully applied to many applications, including ear recognition. This paper presents a Two Dimensional Multi-Band PCA (2D-MBPCA) method, inspired by PCA based techniques for multispectral and hyperspectral images, which have demonstrated significantly higher performance to that of standard PCA. The proposed method divides the input image into a number of images based on the intensity of the pixels. Three different methods are used to calculate the pixel intensity boundaries, called: equal size, histogram, and greedy hill climbing based techniques. Conventional PCA is then applied on the resulting images to extract their eigenvectors, which are used as features. The optimal number of bands was determined using the intersection of number of features and total eigenvector energy. Experimental results on two benchmark ear image datasets demonstrate that the proposed 2D-MBPCA technique significantly outperforms single image PCA by up to 56.41% and the eigenfaces technique by up to 29.62% with respect to matching accuracy on images from two benchmark datasets. Furthermore, it gives very competitive results to those of learning based techniques at a fraction of their computational cost and without a need for training.
A novel image dataset for source camera identification and image based recognition systems
Authors: Bruno Andrea , Capasso Paola , Cattaneo Giuseppe , Petrillo Umberto Ferraro , Improta Riccardo 
Published: June 2022

AbstractMultimodal emotion recognition has attracted a great deal of attention in recent years, with new interesting applications now being considered. One promising application is in the digital image forensics fields where, for example, it gives the possibility to automatically highlight subjects that are in pain, in digital images under examination, by analyzing their facial expressions. However, finding an image that represents a possible crime leaves the problem of identifying the device used to take the image open. Such a problem has been addressed by Source Camera Identification algorithms (SCI, for short). These algorithms analyze some features hidden in a target image to find traces left by the sensor that captured the image. A particularly challenging case is when the candidate source cameras for an image under investigation are of the same manufacturer and model. A fair and universal assessment of these algorithms is only possible if standard datasets are used for their benchmarking. However, our comprehensive analysis has shown that the majority of the datasets proposed so far contain a collection of images taken with different types of cameras, mostly smartphones. We fill this gap by presenting UNISA2020, a novel image dataset that contains a large collection of real-world images taken with multiple conventional digital cameras of the same type. The images in our dataset have been assembled so as to avoid artifacts that could negatively affect the identification process. To validate our dataset, we also performed a comparative experimental analysis to investigate the performance of an SCI reference algorithm when running on our dataset as well as on other SCI standard datasets.
Plasmonic photonic crystal fiber sensor for optical partial discharge detection
Authors: Saber Asmaa M. , Hameed Mohamed Farhat O. , El-Azab Jala , Amer Rabah Y. , Ismail Tawfik , Obayya S. S. A. 
Published: June 2022

AbstractDetection of partial discharge (PD) is vital to reassure the operation reliability of high voltage (HV) electrical power systems. Optical detection methods have been developed in recent years due to their high sensitivity and immunity to electromagnetic interference. In this work, D-shaped photonic crystal fiber sensor based on surface plasmon resonance is reported for optical PD detection in HV equipment. A photochromic spirooxazine dye-doped silica sol–gel is utilized for sensing the UV radiation emitted from the PD. The sol–gel refractive index depends on the radiation intensity which affects the resonance wavelength where coupling occurs between the core and surface plasmon modes. The sensing performance is demonstrated with the help of full vectorial finite element method (FVFEM). The geometrical parameters are studied to maximize the sensor sensitivity where high sensitivity of 2.4 nm/mW.cm−2is achieved. To the best of our knowledge, it is the first time to use a simple design of plasmonic PCF for optical PD detection.
Experimental Study on the Expended Energy on Structural Degradation of Lubricating Greases
Authors: Ahme Leif , Kuhn Erik , Delgado Canto Miguel Ángel 
Published: June 2022

AbstractOne of the keystones of tribological studies is the energetical approach to the lubrication process. In the particular case of lubricating greases, part of the lubrication process's energy dissipates due to a shear-induced structural rearrangement of the 3D network of the thickening agent dispersed in the base oil. This fact confers them a particular consistency, mechanical stability, rheological and tribological behaviour. In this research work, we investigate the mechanical structural degradation induced by shear stress applied in rheological tests (rotational and oscillation mode) and the influence of thickener (type and composition) and base oil on both the degradation process and the expended mechanical energies. For this purpose, lithium, calcium and polyurea-based greases of NLGI grade 2 were used. These greases have been manufactured with a different base oil (mineral, synthetic and vegetable oils) and kinematic viscosity of 48 or 240 mm2/s. Some biogenic greases were also included in this research. The optical microscopy analysis revealed thickener particles-based agglomerates with different shapes and sizes that reduced notably, if not almost completely destroyed, after stress. Due to the thickener particles-based agglomerates distribution, significant differences in the shear-induced frictional energy inside the bulk grease during the shear process were detected. The size of agglomerates depended on both the thickener content and the base oil viscosity and not the type of base oil.
Extraction and separation feasibility of cerium (III) and lanthanum (III) from aqueous solution using modified graphite adsorbent
Authors: Youssef Maha A. , Sami Nesreen M. , Hassan Hisham S. 
Published: June 2022

AbstractGraphite (GR) and graphite/alginate (GRA) composite were synthesized utilizing the thermal annealing technique and used as a new adsorbent material for the selective separation and removal of La(III) and Ce(III) from aqueous solutions. Fourier transform infrared (FTIR) spectroscopy, thermal analysis (DTA, TGA), X-ray diffraction (XRD), surface area, porosity, and scanning electron microscope (SEM) were also used to characterize the generated material. Distinct experiments were performed to test the ability of the GRA to La(III) and Ce(III) removal, which include the effect of pH, shaken time, initial concentration of La(III), and Ce(III) at different temperatures range. After 20 min, both ions have reached equilibrium. The pseudo second-order kinetic model was chosen as one which best fits the experimental evidence and better reflects the chemical sorption process. Adsorption isotherm was studied using the Langmuir, Freundlich, and D-R models. The Langmuir model was used to better fit the results obtained. At 25 °C, Ce(III) and La(III) have maximum monolayer capacities of 200 and 83.3 mg/g, respectively. The sorption was endothermic reaction and spontaneous, as illustrated by the data of thermodynamics studies. GRA has the ability to be used as a novel lanthanide adsorbent material, especially for selective separation between Ce(III) and La(III).
Connecting the Dots in Self-Supervised Learning: A Brief Survey for Beginners
Authors: Fang Peng-Fei , Li Xian , Yan Yang , Zhang Shuai , Kang Qi-Yue , Li Xiao-Fei , Lan Zhen-Zhong 
Published: June 2022

AbstractThe artificial intelligence (AI) community has recently made tremendous progress in developing self-supervised learning (SSL) algorithms that can learn high-quality data representations from massive amounts of unlabeled data. These methods brought great results even to the fields outside of AI. Due to the joint efforts of researchers in various areas, new SSL methods come out daily. However, such a sheer number of publications make it difficult for beginners to see clearly how the subject progresses. This survey bridges this gap by carefully selecting a small portion of papers that we believe are milestones or essential work. We see these researches as the “dots” of SSL and connect them through how they evolve. Hopefully, by viewing the connections of these dots, readers will have a high-level picture of the development of SSL across multiple disciplines including natural language processing, computer vision, graph learning, audio processing, and protein learning.
Incidences of Rhipicephalus (Boophilus) microplus (Canestrini, 1888) Transmitted Pathogens in Cattle in West Africa
Authors: Toure Alassane , Sanogo Moussa , Sghiri Abdelmalek , Sahibi Hamid 
Published: June 2022

Abstract
Context and Purpose
In a context of recent introduction of Rhipicephalus (Boophilus) microplus tick species in West Africa, the purpose of the authors is to estimate incidence density of cattle babesiosis either caused by Babesia bigemina or Babesia bovis, and cattle anaplasmosis. Incidence density represents how quickly a disease or a condition is occurring amongst a group of individuals at risk.

Methods
The longitudinal and prospective study design took place in south, centre, east, west and north of Côte d’Ivoire. Cattle have been followed for 12 months. At the end of each month, each animal has been RT-PCR tested for new infection by Babesia bovis, Babesia bigemina, and PCR–RFLP tested for new infection by Anaplasma marginale.

Results
Findings show for the study area that incidence densities of Babesia bovis, Babesia bigemina and Anaplasma marginale infections in Côte d’Ivoire are, respectively, 15.3 new infections [95% CI 13.1–17.88] per 100 cattle, 32.2 new infections [95% CI 28.5–36.3] per 100 cattle, and 25.9 new infections [95% CI 22.5–29.6] per 100 cattle.

Conclusion
Finally, there is increasing of infection incidence density following the region distance from the coast or elevation.
Evaluation of Ongoing Crisis Intervention Team (CIT) Training for Law Enforcement Using the ECHO Model
Authors: Crisanti Annette S. , Fairfax-Columbo Jaymes , Duran Danielle , Rosenbaum Nils A. , Melendrez Ben , Trujillo Isaac , Earheart Jennifer A. , Tinney Matthew 
Published: June 2022

AbstractCrisis Intervention Team (CIT) training aims to improve law enforcement officers’ (LEOs) ability to safely intervene in calls for service involving individuals with mental illness, as well as to increase LEOs’ ability to link these individuals to mental health services and divert them from the criminal justice system. However, most CIT training is delivered as a stand-alone class, and continuing education in CIT principles and best practices is limited. To address this problem, the Albuquerque Police Department, in partnership with the Department of Psychiatry and Behavioral Sciences at the University of New Mexico, developed CIT ECHO to provide continuing education in CIT best practices. The authors evaluated 113 weekly CIT ECHO sessions targeting LEOs in New Mexico, offered between 2017 and 2020. LEOs electronically completed a post-session survey after each didactic; additionally, a targeted follow-up survey was distributed to LEOs participating in at least three sessions. Surveys measured impact of CIT ECHO on knowledge, self-efficacy, and attitudes towards individuals with mental illness involved in the criminal justice system. After participating in CIT ECHO, LEOs reported increases in knowledge of didactic content and that they felt comfortable applying didactic content on the job. LEOs also evidenced positive attitudinal shifts towards individuals with mental illness and criminal justice involvement. Continuing education in CIT best practices appears to increase LEOs’ knowledge base and comfort in working with individuals with mental illness and criminal justice involvement, as well as results in positive attitudinal shifts towards this population.
Infectious Pepper Mild Mottle Virus and Human Adenoviruses as Viral Indices in Sewage and Water Samples
Authors: Rashed Mohammed Kamal , El-Senousy Waled Morsy , Sayed ElSayed Tarek Abd ElSalam , AlKhazindar Maha 
Published: June 2022

AbstractThe objective of this study was to compare human adenoviruses (HAdVs) genome and infectivity, polyomaviruses (JC and BK) genome (JCPyVs) and (BKPyVs), Pepper Mild Mottle Virus (PMMoV) genome and infectivity, and infectious bacteriophages as viral indices for sewage and water samples. One hundred and forty-four samples were collected from inlets and outlets of water and wastewater treatment plants (WTPs), and WWTPs within Greater Cairo from October 2015 till March 2017. Two methods of viral concentration [Aluminium hydroxide (Al(OH)3) precipitation method and adsorption-elution technique followed by organic flocculation method] were compared to determine which of them was the best method to concentrate viruses from sewage and water. Although samples with only one litre volume were concentrated using Al(OH)3 precipitation method and the same samples with larger volumes (5–20 L) were concentrated using the adsorption-elution technique followed by the organic flocculation method, a non-significant difference was observed between the efficiency of the two methods in all types of samples except for the drinking water samples. Based on the qualitative prevalence of studied viruses in water and wastewater samples, the number of genome copies and infectious units in the same samples, resistance to treatment processes in water and wastewater treatment plants, higher frequency of both adenoviruses and PMMoV genomes as candidate viral indices in treated sewage and drinking water was observed. The problem of having a viral genome as indices of viral pollution is that it does not express the recent viral pollution because of the longer survivability of the viral genome than the infectious units in water and wastewater. Both infectious adenovirus and infectious phiX174 bacteriophage virus showed similar efficiencies as indices for viral pollution in drinking water and treated sewage samples. On the other hand, qualitative detection of infectious PMMoV failed to express efficiently the presence/absence of infectious enteric viruses in drinking water samples. Infectious adenoviruses and infectious bacteriophage phiX174 virus may be better candidates than adenoviruses genome, polyomaviruses genome, and PMMoV genome and infectivity as viral indices for water and wastewater.
On Effective Campus Attack Response: Insights from Agent-Based Simulation for Improving Emergency Information Sharing System Design and Response Strategy
Authors: Beattie Steven , Xi Jing Yang Sunny , Chan Wai Kin Victor 
Published: June 2022

AbstractInformation sharing systems are a critical component of emergency response—especially in campus attack situations that unfold very rapidly. The design of effective information sharing systems is often difficult, however, due to a lack of data on these assault events. This work takes an agent-based approach to simulate three campus emergency information sharing system design alternatives in the context of a college campus knife attack, and incorporates data from on-campus student surveys and parameter tuning experiments. Alternatives are evaluated according to: (1) improved student attack response outcomes; and (2) effective institutional response to the attack. The results confirm that increased awareness supports rapid emergency reporting, but an important gap exists between students’ awareness and their ability to respond effectively, which depends on a number of campus-specific factors. A strong positive impact is seen from safe and efficient information sharing with authorities. This impact depends largely on reporting system implementation qualities, as opposed to campus-specific factors. On a campus in China, WeChat was used as a basis for messaging models. The simulation results show a 9% drop in casualties and a 22% faster police response time from a text-based reporting system using “base” WeChat features instead of traditional phone reporting. Our results also project a 30% drop in casualties and 52% faster police response time using a system designed around a WeChat Mini Program or stand-alone campus emergency reporting app. These outcomes suggest a number of recommendations for improving outdated campus emergency information-sharing systems and response strategies.
Imperceptible black-box waveform-level adversarial attack towards automatic speaker recognition
Authors: Zhang Xingyu , Zhang Xiongwei , Sun Meng , Zou Xia , Chen Kejiang , Yu Nenghai 
Published: June 2022

AbstractAutomatic speaker recognition is an important biometric authentication approach with emerging applications. However, recent research has shown its vulnerability on adversarial attacks. In this paper, we propose a new type of adversarial examples by generating imperceptible adversarial samples for targeted attacks on black-box systems of automatic speaker recognition. Waveform samples are created directly by solving an optimization problem with waveform inputs and outputs, which is more realistic in real-life scenario. Inspired by auditory masking, a regularization term adapting to the energy of speech waveform is proposed for generating imperceptible adversarial perturbations. The optimization problems are subsequently solved by differential evolution algorithm in a black-box manner which does not require any knowledge on the inner configuration of the recognition systems. Experiments conducted on commonly used data sets, LibriSpeech and VoxCeleb, show that the proposed methods have successfully performed targeted attacks on state-of-the-art speaker recognition systems while being imperceptible to human listeners. Given the high SNR and PESQ scores of the yielded adversarial samples, the proposed methods deteriorate less on the quality of the original signals than several recently proposed methods, which justifies the imperceptibility of adversarial samples.
Network loss following the 2016 Presidential Election among LGBTQ+ adults
Authors: Facciani Matthew , McKay Tara 
Published: June 2022

AbstractGrowing levels of political polarization in the United States have been associated with political homogeneity in the personal networks of American adults. The 2016 Presidential Election in the United States was a polarizing event that may have caused further loss of connections to alters who had different politics. Kinship may protect against loss of politically different ties. Additionally, loss of ties with different political views may be particularly pronounced among LGBTQ+ people as they are more likely to be impacted by public policy decisions compared to their heterosexual counterparts. We analyzed two waves of the University of California, Berkeley Social Networks Study's (UCNets) Main Sample and LGBTQ+ Oversample of older adults that occurred in 2015 and 2017, which provided an opportunity to assess alter loss after the 2016 Presidential Election. When evaluating all adults, we found that politically different alters were more likely to reflect kin ties than partner or friend ties. We also found that politically different kin are less likely to be dropped suggesting that kinship acts as a moderating effect of different political views on alter loss. LGBTQ+ respondents were more likely to drop kin alters with different political views than their cisgender heterosexual counterparts. We discuss the implications these results have for political polarization interventions as well as the social networks impact politics can have on LGBTQ+ individuals.
‘I somehow had the Feeling that I did not belong there’—Experiences of Gay and Lesbian Recreational Athletes in German Sports Clubs
Authors: Müller Johannes , Böhlke Nicola 
Published: June 2022

AbstractThere is little empirical research on the sport experiences of gay and lesbian recreational athletes in Germany and their existence and needs within organized, non-professional sports have largely been ignored. Based on twelve in-depth interviews with self-identified male gay and female lesbian adults, this paper explores how queer recreational athletes experience sport in German sports clubs and which particular challenges or discriminatory situations they are confronted with. Findings show that study participants do not experience much discrimination on an explicit level in the sports clubs. Nevertheless, many respondents try to hide their sexuality in the sports context to prevent possible discrimination and questions about their sexuality. After all, it is mainly the discussion about and reduction of their sexuality that is being experienced as problematic. Five main stressors have been identified: (1) the necessity of an outing, (2) the sports club typical mode of communication, (3) the heteronormative pre-structuring of the sports, (4) the feeling of otherness and the assigned special role, (5) the implicit fear of discrimination. The findings point to the need for increased reflection on and reduction of heteronormative structures in German sports clubs.
Quantum neural network autoencoder and classifier applied to an industrial case study
Authors: Mangini Stefano , Marruzzo Alessia , Piantanida Marco , Gerace Dario , Bajoni Daniele , Macchiavello Chiara 
Published: June 2022

AbstractQuantum computing technologies are in the process of moving from academic research to real industrial applications, with the first hints of quantum advantage demonstrated in recent months. In these early practical uses of quantum computers, it is relevant to develop algorithms that are useful for actual industrial processes. In this work, we propose a quantum pipeline, comprising a quantum autoencoder followed by a quantum classifier, which are used to first compress and then label classical data coming from a separator, i.e., a machine used in one of Eni’s Oil Treatment Plants. This work represents one of the first attempts to integrate quantum computing procedures in a real-case scenario of an industrial pipeline, in particular using actual data coming from physical machines, rather than pedagogical data from benchmark datasets.