bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning Technology Applied to Medical Image Tissue Classification
Authors: Tsai Min-Jen , Tao Yu-Han
Published: October 2022

Medical image classification is a novel technology that presents a new challenge. It is essential that pathological images are automatically and correctly classified to enable doctors to provide precise treatment. Convolutional neural networks have demonstrated their effectiveness in classifying images in deep learning, which may have dozens or hundreds of layers, to illustrate the relationship between them in terms of their different neural network features. Convolutional layers consisting of small kernels take weights as input and guide them through an activation function as output. The main advantage of using convolutional neural networks (CNNs) instead of traditional neural networks is that they reduce the model parameters for greater accuracy. However, many studies have simply been focused on finding the best CNN model and classification results from a single medical image classification. Therefore, we applied a common deep learning network model in an attempt to identify the best model framework by training and validating different model parameters to classify medical images. After conducting experiments on six publicly available databases of pathological images, including colorectal cancer tissue, chest X-rays, common skin lesions, diabetic retinopathy, pediatric chest X-ray, and breast ultrasound image datasets, we were able to confirm that the recognition accuracy of the Inception V3 method was significantly better than that of other existing deep learning models.
Reply to Nduka et al. Comment on “Kehrer et al. Using High-Resolution Ultrasound to Assess Post-Facial Paralysis Synkinesis—Machine Settings and Technical Aspects for Facial Surgeons. Diagnostics 2022, 12, 1650”
Authors: Kehrer Andreas , Prantl Lukas , Knoedler Samuel , Knoedler Leonard
Published: October 2022

We thank Dr. Nduka et al. for this interesting article [...]
Identifying Consumer Mindsets Related to Sugars Consumption in Canadian Adults
Authors: Viana Kátia Danielle Araújo Lourenço , Davidov Sophia , Morello Olivia , Arguello Diana Mariela Puga , Moskowitz Howard , Bellissimo Nick
Published: October 2022

Little is known about the attitudes and perceptions towards dietary sugars in Canadian adults. The objective of this study was to use rule-developing experimentation (RDE) to identify consumer mindsets related to dietary sugars in 18–50-year-old Canadians. Following an isomorphic permuted experimental design, participants (n = 269) each rated a unique set of 24 scenarios, each consisting of a distinct mixture of two to four messages about dietary sugars on a 5-point scale. A regression model was created for each respondent, identifying the value that each respondent attributed to each of the 16 messages. K-means clustering revealed three distinct mindset groups as follows: “Sugars Beliefs” (MS1), “Trend Analysts” (MS2), and “Health Seekers” (MS3). In conclusion, this study found that RDE is a useful methodological approach for evaluating how consumers think about dietary sugars and revealed mindset-specific messages that matter most to people who differ in their attitudes toward sugars.
Content, Quality and Accuracy of Online Nutrition Resources for the Prevention and Treatment of Dementia: A Review of Online Content
Authors: Lee Justine , Nguyen Julie , O’Leary Fiona
Published: October 2022

(1) Background: The internet is a popular information source; however, research evaluating online nutrition-related dementia information is limited. This review characterised content, quality, and accuracy of online dementia-specific nutrition resources for dementia prevention and treatment. (2) Methods: JBI methodology for scoping reviews guided the study. Searches used Google search engine with terms related to dementia and nutrition. Webpages from government, organisational and commercial sources were included; blogs, social media and media sources were excluded. DISCERN tool evaluated content quality; accuracy was assessed against ESPEN and WHO guidelines. Differences in mean DISCERN scores were calculated using ANOVA. (3) Results: 105 webpages from eight countries were included. Webpages were mainly from organisational sources (n = 65) and covered nutrition-related prevention (n = 52) including diet–disease relationships (n = 81). Fewer webpages provided information on dementia related eating issues. The total mean DISCERN score (SD) was 50 ± 8, indicating overall good quality. All government webpages provided accurate information. Commercial webpages had some inaccuracy (ESPEN: 3% mixed, 3% inaccurate; WHO: 3% mixed, 3% inaccurate). (4) Conclusions: Information was of reasonable quality and mostly accurate. Further information on dementia-related eating issues is needed. Future research could address readability, understandability and actionability and examine other sources, such as social media, blogs or forums.
Hearing Their Voices: Self Advocacy Strategies for People with Intellectual Disabilities in South Africa
Authors: Goldberg Cole , Kleintjes Sharon
Published: October 2022

This study investigated strategies for people with intellectual disabilities to self-advocate for inclusion of their priorities in social policy processes in South Africa. Method: Self advocacy strategies were identified through a scoping literature review, a review of self advocacy toolkits and semi structured interviews with people with intellectual disabilities and other stakeholders working at non-governmental and disabled people’s organisations. These data sources were triangulated to identify strategies to upskill and support young adults with intellectual disabilities to share their opinions and perspectives to deepen the diversity of voices engaged in social policy advocacy. Results: Data triangulation identified three core strategies for self advocacy, in person, written strategies and engagement through social media. Discussion: Inclusion of people with intellectual disabilities in civic and political life is crucial, and will only be achieved if self advocates are accepted into the policy-making arena. The cycle of perpetuating exclusion needs to be disrupted, to give people with an intellectual disabilities a say in policy decisions that have an impact on their lives. Conclusion: Adopting strategies which enable the inclusion of the voices of people with intellectual disabilities in civic activities holds potential for diversifying perspectives brought to public participation in policy development and implementation, which is currently primarily the domain of non-disabled citizens.
Racial Distribution of Neighborhood-Level Social Deprivation in a Retrospective Cohort of Prostate Cancer Survivors
Authors: Babatunde Oluwole Adeyemi , Pearce John L. , Jefferson Melanie S. , Frey Lewis J. , Angel Peggi M. , Drake Richard R. , Allen Caitlin G. , Lilly Michael B. , Savage Stephen J. , Hughes Halbert Chanita Hughes
Published: October 2022

Background: A better understanding of neighborhood-level factors’ contribution is needed in order to increase the precision of cancer control interventions that target geographic determinants of cancer health disparities. This study characterized the distribution of neighborhood deprivation in a racially diverse cohort of prostate cancer survivors. Methods: A retrospective cohort of 253 prostate cancer patients who were treated with radical prostatectomy from 2011 to 2019 was established at the Medical University of South Carolina. Individual-level data on clinical variables (e.g., stage, grade) and race were abstracted. Social Deprivation Index (SDI) and Healthcare Professional Shortage (HPS) status was obtained from the Robert Graham Center and assigned to participants based on their residential census tract. Data were analyzed with descriptive statistics and multivariable logistic regression. Results: The cohort of 253 men consisted of 168 white, 81 African American, 1 Hispanic and 3 multiracial men. Approximately 49% of 249 men lived in areas with high SDI (e.g., SDI score of 48 to 98). The mean for SDI was 44.5 (+27.4), and the range was 97 (1–98) for all study participants. African American men had a significantly greater likelihood of living in a socially deprived neighborhood compared to white men (OR = 3.7, 95% C.I. 2.1–6.7, p < 0.01), while men who lived in areas with higher HPS shortage status were significantly more likely to live in a neighborhood that had high SDI compared to men who lived in areas with lower HPS shortages (OR = 4.7, 95% C.I. = 2.1–10.7, p < 0.01). African Americans had a higher likelihood of developing biochemical reoccurrence (OR = 3.7, 95% C.I. = 1.7–8.0) compared with white men. There were no significant association between SDI and clinical characteristics of prostate cancer. Conclusions: This study demonstrates that SDI varies considerably by race among men with prostate cancer treated with radical prostatectomy. Using SDI to understand the social environment could be -particularly useful as part of precision medicine and precision public health approaches and could be used by cancer centers, public health providers, and other health care specialists to inform operational decisions about how to target health promotion and disease prevention efforts in catchment areas and patient populations.
In Vitro Mimicking of Obesity-Induced Biochemical Environment to Study Obesity Impacts on Cells and Tissues
Authors: Ghanemi Abdelaziz , Yoshioka Mayumi , St-Amand Jonny
Published: October 2022

Obesity represents a heavy burden for modern healthcare. The main challenge facing obesity research progress is the unknown underlying pathways, which limits our understanding of the pathogenesis and developing therapies. Obesity induces specific biochemical environments that impact the different cells and tissues. In this piece of writing, we suggest mimicking obesity-induced in vivo biochemical environments including pH, lipids, hormones, cytokines, and glucose within an in vitro environment. The concept is to reproduce such biochemical environments and use them to treat the tissue cultures, explant cultures, and cell cultures of different biological organs. This will allow us to clarify how the obesity-induced biochemistry impacts such biological entities. It would also be important to try different environments, in terms of the compositions and concentrations of the constitutive elements, in order to establish links between the effects (impaired regeneration, cellular inflammation, etc.) and the factors constituting the environment (hormones, cytokines, etc.) as well as to reveal dose-dependent effects. We believe that such approaches will allow us to elucidate obesity mechanisms, optimize animal models, and develop therapies as well as novel tissue engineering applications.
Goblet Cell Carcinoma of the Appendix with Synchronous Adenocarcinoma of the Cecum: Distinct or Related Entities?
Authors: Vincenti Leonardo , Andriola Valeria , Cazzato Gerardo , Colagrande Anna , Fiore Felicia
Published: October 2022

Goblet cell carcinoma (GCC) is a rare primary tumor of the appendix characterized by both epithelial and neuroendocrine components containing goblet cells. While in the past, the GCC has been associated with neuroendocrine tumors, recent studies consider that GCC is closer to adenocarcinoma than a neuroendocrine component. The association between gastro-intestinal (GI) carcinoids and second primary malignancies (SPMs) is widely described in the literature, but there is no reported case of GCC and synchronous adjacent adenocarcinoma of the colon. We describe the first case in the literature, to our knowledge, of synchronous colorectal adenocarcinoma of the cecum and GCC of the appendix that are incidentally discovered in the resected primary cancer specimen. The association between the two neoplasms seems to be not causal and maybe the “paracrine-effect theory” may explain the development of a second tumor close to the primary.
The Role of Novel Motorized Spiral Enteroscopy in the Diagnosis of Cecal Tumors
Authors: Selimagic Amir , Dozic Ada , Husic-Selimovic Azra
Published: October 2022

Small bowel and ileocecal diseases remain a diagnostic and therapeutic challenge, despite the introduction of various modalities for deep enteroscopy. Novel Motorized Spiral Enteroscopy is an innovative technology that uses an overtube with a raised spiral at the distal end to pleat the small intestine. It consumes less time and meets both the diagnostic and therapeutic needs of small bowel diseases. The objective of this article is to highlight the possibility of using NMSE as an alternative technique when a target lesion is inaccessible during conventional colonoscopy or cecal intubation cannot be achieved. We report the case of a 61-year-old man who presented with pain in the right lower abdominal segment, diarrhea, and rapid weight loss for more than 3 months. An initial ultrasound showed a suspicious liver metastasis. Computerized tomography scans showed an extensive ileocecal tumor mass with liver metastasis. The colonoscopy was unsuccessful and incomplete due to dolichocolon and intestinal tortuosity. Later, endoscopy was performed using a Novel Motorized Spiral Enteroscope in a retrograde approach, passing the scope through the anus and colon up to the ileocecal segment, where a tumor biopsy was performed and adenocarcinoma was pathohistologically confirmed.
Tricking the Brain with Leptin to Limit Post Liposuction and Post Bariatric Surgery Weight Regain?
Authors: Ghanemi Abdelaziz , Yoshioka Mayumi , St-Amand Jonny
Published: October 2022

Obesity represents a medical challenge for modern therapists. The main difficulty is that once obesity is established, it is hard to reverse. It is believed that once an increased body weight/adiposity content is reached it becomes the “reference” that energy mechanisms adjust towards keeping. Thus, following a weight loss, such as following liposuction/bariatric surgery, the metabolic balance would target this “reference” that represents the previously reached body weight/adiposity content. On the other hand, medical procedures of liposuction and bariatric surgery reduce the level of the adipocytes-produced hormone leptin. This leptin level reduction leads to an increase in food intake and a decrease in energy expenditure. Therefore, the reduced leptin would be among the signals received by the brain to trigger weight regain via processes aiming to re-establish the pre-liposuction/pre-bariatric surgery body weight or adiposity content. We suggest administering leptin so that the brain does not detect the post- liposuction/post-bariatric surgery weight loss; thus, limiting the signals toward weight regain, leading to a better weight control.
Wind Speed Measurement by an Inexpensive and Lightweight Thermal Anemometer on a Small UAV
Authors: Inoue Jun , Sato Kazutoshi
Published: October 2022

Profiling wind information when using a small unmanned aerial vehicle (sUAV) is vital for atmospheric profiling and monitoring attitude during flight. Wind speed on an sUAV can be measured directly using ultrasonic anemometers or by calculating its attitude control information. The former method requires a relatively large payload for an onboard ultrasonic anemometer, while the latter requires real-time flight log data access, which depends on the UAV manufacturers. This study proposes the feasibility of a small thermal anemometer to measure wind speeds inexpensively using a small commercial quadcopter (DJI Mavic2: M2). A laboratory experiment demonstrated that the horizontal wind speed bias increased linearly with ascending sUAV speed. A smoke experiment during hovering revealed the downward wind bias (1.2 m s−1) at a 12-cm height above the M2 body. Field experiments in the ice-covered ocean demonstrated that the corrected wind speed agreed closely with the shipboard wind data observed by a calibrated ultrasonic anemometer. A dual-mount system comprising thermal anemometers was proposed to measure wind speed and direction.
Aerial Drone Surveys Reveal the Efficacy of a Protected Area Network for Marine Megafauna and the Value of Sea Turtles as Umbrella Species
Authors: Dickson Liam C. D. , Negus Stuart R. B. , Eizaguirre Christophe , Katselidis Kostas A. , Schofield Gail
Published: October 2022

Quantifying the capacity of protected area networks to shield multiple marine megafauna with diverse life histories is complicated, as many species are wide-ranging, requiring varied monitoring approaches. Yet, such information is needed to identify and assess the potential use of umbrella species and to plan how best to enhance conservation strategies. Here, we evaluated the effectiveness of part of the European Natura 2000 protected area network (western Greece) for marine megafauna and whether loggerhead sea turtles are viable umbrella species in this coastal region. We systematically surveyed inside and outside coastal marine protected areas (MPAs) at a regional scale using aerial drones (18,505 animal records) and combined them with distribution data from published datasets (tracking, sightings, strandings) of sea turtles, elasmobranchs, cetaceans and pinnipeds. MPAs covered 56% of the surveyed coastline (~1500 km). There was just a 22% overlap in the distributions of the four groups from aerial drone and other datasets, demonstrating the value of combining different approaches to improve records of coastal area use for effective management. All four taxonomic groups were more likely to be detected inside coastal MPAs than outside, confirming sufficient habitat diversity despite varied life history traits. Coastal habitats frequented by loggerhead turtles during breeding/non-breeding periods combined overlapped with 76% of areas used by the other three groups, supporting their potential use as an umbrella species. In conclusion, this study showed that aerial drones can be readily combined with other monitoring approaches in coastal areas to enhance the management of marine megafauna in protected area networks and to identify the efficacy of umbrella species.
Error Analysis of a PFEM Based on the Euler Semi-Implicit Scheme for the Unsteady MHD Equations
Authors: Shi Kaiwen , Su Haiyan , Feng Xinlong
Published: October 2022

In this article, we mainly consider a first order penalty finite element method (PFEM) for the 2D/3D unsteady incompressible magnetohydrodynamic (MHD) equations. The penalty method applies a penalty term to relax the constraint “∇·u=0”, which allows us to transform the saddle point problem into two smaller problems to solve. The Euler semi-implicit scheme is based on a first order backward difference formula for time discretization and semi-implicit treatments for nonlinear terms. It is worth mentioning that the error estimates of the fully discrete PFEM are rigorously derived, which depend on the penalty parameter ϵ, the time-step size τ, and the mesh size h. Finally, two numerical tests show that our scheme is effective.
Multicriteria Group Decision Making Based on Intuitionistic Normal Cloud and Cloud Distance Entropy
Authors: Li Wei , Lu Yingqi , Fan Chengli , Heng Yong , Zhu Xiaowen
Published: October 2022

The uncertainty of information is an important issue that must be faced when dealing with decision-making problems. Randomness and fuzziness are the two most common types of uncertainty. In this paper, we propose a multicriteria group decision-making method based on intuitionistic normal cloud and cloud distance entropy. First, the backward cloud generation algorithm for intuitionistic normal clouds is designed to transform the intuitionistic fuzzy decision information given by all experts into an intuitionistic normal cloud matrix to avoid the loss and distortion of information. Second, the distance measurement of the cloud model is introduced into the information entropy theory, and the concept of cloud distance entropy is proposed. Then, the distance measurement for intuitionistic normal clouds based on numerical features is defined and its properties are discussed, based on which the criterion weight determination method under intuitionistic normal cloud information is proposed. In addition, the VIKOR method, which integrates group utility and individual regret, is extended to the intuitionistic normal cloud environment, and thus the ranking results of the alternatives are obtained. Finally, the effectiveness and practicality of the proposed method are demonstrated by two numerical examples.
First Request First Service Entanglement Routing Scheme for Quantum Networks
Authors: Li Si-Chen , Tang Bang-Ying , Zhou Han , Yu Hui-Cun , Liu Bo , Yu Wan-Rong , Liu Bo
Published: October 2022

Quantum networks enable many applications beyond the reach of classical networks by supporting the establishment of long-distance entanglement connections, and are already stepped into the entanglement distribution network stage. The entanglement routing with active wavelength multiplexing schemes is urgently required for satisfying the dynamic connection demands of paired users in large-scale quantum networks. In this article, the entanglement distribution network is modeled into a directed graph, where the internal connection loss among all ports within a node is considered for each supported wavelength channel, which is quite different to classical network graphs. Afterwards, we propose a novel first request first service (FRFS) entanglement routing scheme, which performs the modified Dijkstra algorithm to find out the lowest loss path from the entangled photon source to each paired user in order. Evaluation results show that the proposed FRFS entanglement routing scheme can be applied to large-scale and dynamic topology quantum networks.
Quantum Energy Current Induced Coherence in a Spin Chain under Non-Markovian Environments
Authors: Ablimit Arapat , He Run-Hong , Xie Yang-Yang , Wu Lian-Ao , Wang Zhao-Ming
Published: October 2022

We investigate the time-dependent behaviour of the energy current between a quantum spin chain and its surrounding non-Markovian and finite temperature baths, together with its relationship to the coherence dynamics of the system. To be specific, both the system and the baths are assumed to be initially in thermal equilibrium at temperature Ts and Tb, respectively. This model plays a fundamental role in study of quantum system evolution towards thermal equilibrium in an open system. The non-Markovian quantum state diffusion (NMQSD) equation approach is used to calculate the dynamics of the spin chain. The effects of non-Markovianity, temperature difference and system-bath interaction strength on the energy current and the corresponding coherence in cold and warm baths are analyzed, respectively. We show that the strong non-Markovianity, weak system-bath interaction and low temperature difference will help to maintain the system coherence and correspond to a weaker energy current. Interestingly, the warm baths destroy the coherence while the cold baths help to build coherence. Furthermore, the effects of the Dzyaloshinskii–Moriya (DM) interaction and the external magnetic field on the energy current and coherence are analyzed. Both energy current and coherence will change due to the increase of the system energy induced by the DM interaction and magnetic field. Significantly, the minimal coherence corresponds to the critical magnetic field which causes the first order phase transition.
Final-State Condition and Dissipative Quantum Mechanics
Authors: Ho Pei-Ming
Published: October 2022

Unitarity demands that the black-hole final state (what remains inside the event horizon at complete evaporation) must be unique. Assuming a UV theory with infinitely many fields, we propose that the uniqueness of the final state can be achieved via a mechanism analogous to the quantum-mechanical description of dissipation.
Multi-Stage Attentive Network for Motion Deblurring via Binary Cross-Entropy Loss
Authors: Guo Cai , Chen Xinan , Chen Yanhua , Yu Chuying
Published: October 2022

In this paper, we present the multi-stage attentive network (MSAN), an efficient and good generalization performance convolutional neural network (CNN) architecture for motion deblurring. We build a multi-stage encoder–decoder network with self-attention and use the binary cross-entropy loss to train our model. In MSAN, there are two core designs. First, we introduce a new attention-based end-to-end method on top of multi-stage networks, which applies group convolution to the self-attention module, effectively reducing the computing cost and improving the model’s adaptability to different blurred images. Secondly, we propose using binary cross-entropy loss instead of pixel loss to optimize our model to minimize the over-smoothing impact of pixel loss while maintaining a good deblurring effect. We conduct extensive experiments on several deblurring datasets to evaluate the performance of our solution for deblurring. Our MSAN achieves superior performance while also generalizing and compares well with state-of-the-art methods.
A Modal Interpretation of Quantum Spins and Its Application to Freudian Theory
Authors: Battilotti Giulia , Borozan Miloš , Grotto Rosapia Lauro
Published: October 2022

In the present paper, we aim to develop a formal quantum logic theory of the interplay between conscious and unconscious processes of the human mind, a goal that has already been envisaged in quantum cognition; in doing so, we will show how the interplay between formal language and metalanguage allows for characterizing pure quantum states as infinite singletons: in the case of the spin observable, we obtain an equation defining a modality that is then re-interpreted as an abstract projection operator. By including a temporal parameter in the equations and by defining a modal negative operator, we derive an intuitionistic-like negation, for which the non-contradiction law is seen as an equivalent of the quantum uncertainty. Building on the psychoanalytic theory of Bi-Logic by Matte Blanco, we use modalities in interpreting the emergence of conscious representations from an unconscious one, and we demonstrate that this description fits well with Freud’s view of the role of negation in mental processes. Psychoanalysis, where affect plays a prominent role in shaping not only conscious, but also unconscious representations, is therefore seen as a suitable model to expand the domain of quantum cognition to the broader field of affective quantum cognition.
Transfer Entropy Granger Causality between News Indices and Stock Markets in U.S. and Latin America during the COVID-19 Pandemic
Authors: Coronado Semei , Martinez Jose N. , Gualajara Victor , Rojas Omar
Published: October 2022

The relationship between three different groups of COVID-19 news series and stock market volatility for several Latin American countries and the U.S. are analyzed. To confirm the relationship between these series, a maximal overlap discrete wavelet transform (MODWT) was applied to determine the specific periods wherein each pair of series is significantly correlated. To determine if the news series cause Latin American stock markets’ volatility, a one-sided Granger causality test based on transfer entropy (GC-TE) was applied. The results confirm that the U.S. and Latin American stock markets react differently to COVID-19 news. Some of the most statistically significant results were obtained from the reporting case index (RCI), A-COVID index, and uncertainty index, in that order, which are statistically significant for the majority of Latin American stock markets. Altogether, the results suggest these COVID-19 news indices could be used to forecast stock market volatility in the U.S. and Latin America.
Joint Angle Variability Is Altered in Patients with Peripheral Artery Disease after Six Months of Exercise Intervention
Authors: Fallahtafti Farahnaz , Salamifar Zahra , Hassan Mahdi , Rahman Hafizur , Pipinos Iraklis , Myers Sara A.
Published: October 2022

Supervised exercise therapy (SET) is a conservative non-operative treatment strategy for improving walking performance in patients with peripheral artery disease (PAD). Gait variability is altered in patients with PAD, but the effect of SET on gait variability is unknown. Forty-three claudicating patients with PAD underwent gait analysis before and immediately after a 6-month SET program. Nonlinear gait variability was assessed using sample entropy, and the largest Lyapunov exponent of the ankle, knee, and hip joint angle time series. Linear mean and variability of the range of motion time series for these three joint angles were also calculated. Two-factor repeated measure analysis of variance determined the effect of the intervention and joint location on linear and nonlinear dependent variables. After SET, walking regularity decreased, while the stability remained unaffected. Ankle nonlinear variability had increased values compared with the knee and hip joints. Linear measures did not change following SET, except for knee angle, in which the magnitude of variations increased after the intervention. A six-month SET program produced changes in gait variability toward the direction of healthy controls, which indicates that in general, SET improved walking performance in individuals with PAD.
Fault Diagnosis of Rolling Bearings Based on WPE by Wavelet Decomposition and ELM
Authors: Xi Caiping , Gao Zhibo
Published: October 2022

The fault diagnosis classification method based on wavelet decomposition and weighted permutation entropy (WPE) by the extreme learning machine (ELM) is proposed to address the complexity and non-smoothness of rolling bearing vibration signals. The wavelet decomposition based on ‘db3’ is used to decompose the signal into four layers and extract the approximate and detailed components, respectively. Then, the WPE values of the approximate (CA) and detailed (CD) components of each layer are calculated and composed to be the feature vectors, which are finally fed into the extreme learning machine with optimal parameters for classification. The comparative study of the simulations based on WPE and permutation entropy (PE) shows that the classification method of seven kinds of signals of normal bearing signals and six types of fault states (7 mils and 14 mils) based on WPE (CA, CD) with the number of nodes in the hidden layers of ELM determined by the five-fold cross-validation has the best performances, the training accuracy can reach 100%, and the testing accuracy can reach 98.57% with 37 nodes of the hidden layer by ELM. The proposed method using WPE (CA, CD) by ELM provides guidance for the multi-classification of normal bearing signals.
Generalized Solution of Inverse Problem for Ising Connection Matrix on d-Dimensional Hypercubic Lattice
Authors: Kryzhanovsky Boris , Litinskii Leonid
Published: October 2022

We analyze a connection matrix of a d-dimensional Ising system and solve the inverse problem, restoring the constants of interaction between spins, based on the known spectrum of its eigenvalues. When the boundary conditions are periodic, we can account for interactions between spins that are arbitrarily far. In the case of the free boundary conditions, we have to restrict ourselves with interactions between the given spin and the spins of the first d coordination spheres.
Two-Level Finite Element Iterative Algorithm Based on Stabilized Method for the Stationary Incompressible Magnetohydrodynamics
Authors: Tang Qili , Hou Min , Xiao Yajie , Yin Lina
Published: October 2022

In this paper, based on the stabilization technique, the Oseen iterative method and the two-level finite element algorithm are combined to numerically solve the stationary incompressible magnetohydrodynamic (MHD) equations. For the low regularity of the magnetic field, when dealing with the magnetic field sub-problem, the Lagrange multiplier technique is used. The stabilized method is applied to approximate the flow field sub-problem to circumvent the inf-sup condition restrictions. One- and two-level stabilized finite element algorithms are presented, and their stability and convergence analysis is given. The two-level method uses the Oseen iteration to solve the nonlinear MHD equations on a coarse grid of size H, and then employs the linearized correction on a fine grid with grid size h. The error analysis shows that when the grid sizes satisfy h=O(H2), the two-level stabilization method has the same convergence order as the one-level one. However, the former saves more computational cost than the latter one. Finally, through some numerical experiments, it has been verified that our proposed method is effective. The two-level stabilized method takes less than half the time of the one-level one when using the second class Nédélec element to approximate magnetic field, and even takes almost a third of the computing time of the one-level one when adopting the first class Nédélec element.
Multiple Reflections for Classical Particles Moving under the Influence of a Time-Dependent Potential Well
Authors: Graciano Flávio Heleno , da Costa Diogo Ricardo , Leonel Edson D. , de Oliveira Juliano A.
Published: October 2022

We study the dynamics of classical particles confined in a time-dependent potential well. The dynamics of each particle is described by a two-dimensional nonlinear discrete mapping for the variables energy en and phase ϕn of the periodic moving well. We obtain the phase space and show that it contains periodic islands, chaotic sea, and invariant spanning curves. We find the elliptic and hyperbolic fixed points and discuss a numerical method to obtain them. We study the dispersion of the initial conditions after a single iteration. This study allows finding regions where multiple reflections occur. Multiple reflections happen when a particle does not have enough energy to exit the potential well and is trapped inside it, suffering several reflections until it has enough energy to exit. We also show deformations in regions with multiple reflection, but the area remains constant when we change the control parameter NC. Finally, we show some structures that appear in the e0e1 plane by using density plots.
The Relationship between Health-Related Quality of Life, Subjective Scar Estimation, and Activity Performance in Adult Burn Patients 6 and 12 Months after Injury
Authors: Enblom Sara , Sundin Elin , Guné Gerd Edvinsson , Aspling Nona , Huss Fredrik
Published: October 2022

A burn injury affects a person’s health-related quality of life (HRQoL) in different ways and might influence their daily life for months and years afterward. The aim of this study was to examine how activity performance and subjective scar estimation relate to self-rated health and whether this changes in the first year post-burn. Fifty consecutive patients who were scheduled for follow-up at the Burn Center’s outpatient clinic in Uppsala were included. Assessments of HRQoL (EQ-5D), activity performance (DASH), and subjective scar evaluation (POSAS) were conducted at 6 and 12 months post-burn. The results show a statistically significant correlation between self-rated HRQoL and activity performance (p = 0.001) and between self-rated HRQoL and subjective scar estimation (p = 0.000) at 6 but not at 12 months post-burn. A possible explanation of the lack of correlation at one year post-burn might be the patient´s expectations of his or her recovery. In future research, it would be interesting to investigate the long-term correlations between quality of life and activity performance.
Saudi Green Banks and Stock Return Volatility: GLE Algorithm and Neural Network Models
Authors: Assous Hamzeh F.
Published: October 2022

This study investigates the effects of ESG factors on stock return volatility from 2012 to 2020 using linear regression, GLE algorithm, and neural network models. This paper used the ESG factors and main control variables (ROA, EPS, and year) as independent variables. The regression model results showed that both year and E scores significantly positively affected Saudi banks’ stock return volatility. However, the S score and ROA significantly negatively impacted the volatility. The results indicated that the prediction models were more efficient in analysing the volatility and building an accurate prediction model using all independent variables. The results of the GLE algorithm model showed that the level of importance of the variables was sorted from highest to least significant as follows: S score, ROA, E score, and then G score. While the result of the neural network was sorted as ROA, ROE, and EPS, then the E score, S score, and G score factors all had the same minor importance in predicting the stock return volatility. Linear regression and prediction models indicated that the S score was the most crucial variable in predicting stock return volatility. Both policymakers and investors can benefit from our findings.
Student Engagement, Learning Environments and the COVID-19 Pandemic: A Comparison between Psychology and Engineering Undergraduate Students in the UK
Authors: Limniou Maria , Sedghi Naser , Kumari Destiny , Drousiotis Efthyvoulos
Published: October 2022

This study compared student learning engagement from two UK departments exploring their participation in face-to-face and synchronous online learning environments. Overall, 446 undergraduate students from Psychology (soft/non-Science, Technology, Engineering, and Mathematics (STEM) discipline) and Electrical Engineering and Electronics (EEE) (hard/STEM discipline) completed an online questionnaire over the second semester of the 2020–2021 academic year, where the teaching was mainly online. The questionnaire included validated scales regarding teaching and students’ characteristics and an open-ended question regarding the role of learning environments. There was a significant difference between the two learning environments in both departments, with most of the students believing that they were better engaged with their learning process in face-to-face environments (quantitative analysis). Additionally, the thematic analysis of student qualitative responses revealed that online student engagement was influenced by (1) Behaviour, (2) Affective, and (3) Cognitive challenges (i.e., additional workload, lack of communication and distractions in the home environment) and opportunities (i.e., the effective use of study time and online content through interactive learning environments). This study could assist academics, university policymakers, and researchers to understand student engagement alongside learning environments, reconsidering the opportunities and challenges that were gained from online learning due to the COVID-19 pandemic.
Democratising Ethical Regulation and Practice in Educational Research
Authors: Fox Alison , Busher Hugh
Published: October 2022

This paper sets the context for questions covered in the Education Sciences Special Issue: Regulation and Ethical Practice for Educational Research: What are appropriate ethical appraisal and approval practices for particular contexts? How can ethics committees effectively support educational researchers and educational research? To do so, the paper argues for a democratising of ethical regulation and practice in educational research, which includes the decolonization agenda, to break away from enduring power imbalances in knowledge production. A key focus is on the regulation of educational research through ethics committees (whether institutional, regional and/or national) and how this affects research practice. While intended to help researchers to protect and benefit potential research participants, ethics committees themselves can have an important part to play in recognizing and removing barriers to inclusivity, as well as in erecting them, to maximise the benefits of educational research. To overturn the dominance of global North knowledge, for post-colonial research ethics regulation, broader conversations of researcher values and experiences in different parts of the world are needed. This paper explores how ethics committees’ expectations do and could shape researcher decision-making. It presents examples of approaches to ethical appraisal which would support empowerment and participation, not only for gatekeepers and participants but also for the research community, whether experienced researcher, ethics committee member or neophyte researcher. Evidence of ethical research practice which paves the way forward is drawn from a range of contexts to help acknowledge the enduring and wide-ranging impact of colonialism, neo-liberalism and neo-imperialism.
Language Teaching through the Flipped Classroom: A Systematic Review
Authors: Heredia Ponce Hugo , Romero Oliva Manuel Francisco , Romero Claudio Carmen
Published: October 2022

Language teaching is in question for reasons related to methodology. For years now, the focus has been on learning and the search for active methodologies such as the flipped classroom (FC). This methodology was chosen because of its emergent character and because of the advantages and limitations that have arisen after its implementation in the classroom. Hence, the aim of this paper is to determine the level of expansion of the FC approach in language teaching over the last five years. For this purpose, a systematic review was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Two international databases, Web of Science (WOS) and Scopus, were used for the search, until 1 July 2022, using both Spanish and English descriptors: “language learning*”, “flipped classroom,” and “language teaching”. In this process, inclusion and exclusion criteria were established for a sample (N = 181) which resulted in a final selection of 26 articles. It can be seen that the majority of the articles published are between 2021 and 2022, aimed at L2 teaching, specifically English, and also show that they produce motivation in students and improve results in the development of language teaching, among others.
Aspects Influencing the Provision of Internships by Czech Firms to Future Economists during Their Studies
Authors: Berková Kateřina , Březinová Hana , Frendlovská Dagmar , Kubišová Andrea , Krpálek Pavel , Krelová Katarína Krpálková , Melas David
Published: October 2022

Internships have an irreplaceable place in professional education. Theoretical and practical education is being more interconnected and strengthened with emphasis placed on high-quality preparation of graduates for internships. From a scientific point of view, there are contradictions between companies’ attitudes towards the employability of future graduates. Therefore, the main aim of the article is to investigate the interest of Czech companies in providing internships to university students studying economic programs as well as the companies’ willingness to employ these students after graduation. The primary data were obtained from 83 valid questionnaires answered by companies experienced in providing internships to these students. The Mann–Whitney U test was used to determine the differences in the attitudes of companies towards the provision of internships in terms of size and duration of the company’s existence on the market. Correlation relationships between variables were determined using Pearson’s correlation coefficient. It was found that large firms will take on students after graduation for a certain period of time, and this is contrary to small businesses. Students must possess work and soft skills when entering internships. In the given context, there was no connection found between the evaluation of the student’s work performance and the required competencies by the company. Therefore, students can also be assigned to internships in order to meet the setting of the study program or the needs of employers. Moreover, internships need constant care, especially in the area of relationships between a university and an application sphere.
“It’s about Taking the Risk”: Exploring Toddlers’ Risky Play in a Redesigned Outdoor Space
Authors: Little Helen
Published: October 2022

Physically challenging, risky play is a natural part of children’s outdoor play behaviour, yet risky play is often limited by the environmental affordances as well as educators’ reluctance to allow this type of play due to safety concerns. This case study explored the influence of the redesign of the outdoor environment on 18–26-month-old children’s play behaviours and their educators’ attitudes and responses to the children’s risky play. Video recorded observations examined the children’s play behaviours and adult interactions with the children during their usual outdoor play time. Interviews with educators explored their conceptions of risk-taking and attitudes towards the risky elements included in the redesigned space, whilst their attitudes towards children’s risky play and personal risk-taking behaviours were examined using the Tolerance of Risk in Play Scale and Attitudes Towards Risk questionnaire. Findings indicate that despite initial concerns, educators were supportive of the children’s risky play in the new environment and the environment afforded opportunities for diverse play including risky play.
A Follow-Up Review on the Impact of a Participatory Action Research Regarding Outdoor Play and Learning
Authors: Gessiou Georgia
Published: October 2022

The aim of the study is to examine educators’ reflections on their practices and views regarding outdoor play and learning (OPL) and unveil the impact and sustainability of participating in participatory action research (PAR). The study draws back on the findings of a PAR conducted three years ago in two different school units that aimed to support children’s OPL. In the current research, we return to the research field, and with the participating educators we attempt to shed light on their experiences after the formal research came to an end. The research has a socio-cultural perspective on outdoor play and learning with references to participative and active relationships between cultural, social, spatial, and psychological factors. Participating in research where all participants were agents of the change (PAR) enabled the educators to enrich their pedagogical agendas and respect children’s need to play outdoors; it further helped them feel confident and develop competencies in designing outdoor activities. However, the findings unveil the challenges that educators face in creating sustainable outdoor landscapes due to the lack of sufficient supervision and governmental support. The study adds new data regarding the release of sustainable long-term changes both in outdoor pedagogies and settings.
A Pre-Adolescent and Adolescent Clinical Sample Study about Suicidal Ideation, Suicide Attempt, and Self-Harming
Authors: Raffagnato Alessia , Iannattone Sara , Fasolato Rachele , Parolin Elisa , Ravaglia Benedetta , Biscalchin Gaia , Traverso Annalisa , Zanato Silvia , Miscioscia Marina , Gatta Michela
Published: October 2022

Suicide is the second cause of death among adolescents, and nonsuicidal self-injury (NSSI) is one of the main risk factors for suicidal behavior. However, the possible variables specifically associated with suicidal ideation and suicide attempt, as well as the psychopathological characteristics linked to the concomitant presence of suicidal ideation/attempt and NSSI are still under-investigated in youth. The current study aimed to address these issues in a sample of 174 young Italian inpatients (Mage = 14.3 years ± 1.93, 78.2% girls). Sociodemographic and clinical variables were assessed through psycho-diagnostic interviews and ad hoc questionnaires. A binomial logistic regression was performed to identify the predictors of suicidal ideation and suicide attempt. Then, Kruskal–Wallis tests were run to analyze the psychopathological differences between patients with suicidal ideation and suicide attempt considering the coexistence of NSSI. The results highlighted that previous access to child mental health services and general psychopathological problems significantly predicted suicidal ideation, while previous hospitalizations, borderline personality functioning, and affective disorders significantly predicted suicide attempt. In general, inpatients with also NSSI reported higher levels of internalizing, somatic and total problems, impulsiveness, alexithymia, and emotional dysregulation. The clinical implications of our findings in terms of primary and secondary preventive programs are discussed.