Miracle-dz/UniFAR-FTUs huggingface dataset:
An Investigation of the Relationship between the Parents' Math Literacy Self-Efficacy and Their Math Anxieties

Mathematics anxiety can be defined as negative feelings towards mathematics and mathematical operations in general. Math anxiety is seen in many students, and even in parents. In fact, parents' own anxiety regarding mathematics may lead to their children experiencing angst over the subject as well. This can be a problem considering parents are considered one of the basic components of education and have important responsibilities to guide the education process of their children. Mathematical literacy is one of the research topics that have come into prominence in recent years due to PISA. Consequently, the purpose of this study is to determine the relationship between the parents' mathematical literacy self-efficacy and mathematics anxieties. Additionally, through examining the participation of parents in mathematic teaching during the COVID-19 pandemic, it is hoped to better understand their views and methodologies. All participants in this study are parents themselves. The study is designed with an explanatory sequential design among mixed method research designs. The grade in which the students are educated does not make any difference in the self-efficacy and anxiety perceptions of the parents regarding their mathematics literacy. Also, the parents' mathematical literacy self-efficacy and anxiety levels were high. [Paper presented at International Congress of Educational Research (13th, Hatay, Turkey, Sep 3-6, 2020). ]
Clinical Significance of Preoperative Hematological Parameters in Patients with D2-Resected, Node-Positive Stomach Cancer

The purpose of the present study was to investigate the clinical significance of preoperative hematological parameters in patients with advanced stomach cancer, and to explore who might benefit from adjuvant concurrent chemoradiotherapy (CCRT) compared to chemotherapy alone. Among 1032 patients with node-positive stomach cancer who had a confirmed diagnosis after complete D2 resection, and who received adjuvant chemotherapy alone or CCRT, a total of 692 patients was selected using propensity score matching. Among absolute neutrophil count, absolute lymphocyte count (ALC), absolute monocyte count (AMC), platelet count, neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and platelet-to-lymphocyte ratio, AMC was the most relevant prognostic factor for overall survival and recurrence-free survival (hazard ratio (HR) 1.674, 95% confidence interval (CI) 1.180–2.376; HR 1.908, 95% CI 1.650–2.695, respectively). In a subgroup with a high ALC, patients treated with adjuvant CCRT had a favorable recurrence-free survival (HR 0.620, 95% CI 0.393–0.980) compared to those treated with chemotherapy alone. Further study is needed to confirm our findings and to develop tailored adjuvant treatment.
Comparator product issues for biowaiver implementation: the case of Fluconazole

The aim of this work was to assess if the commercially available Fluconazole drug products (Reference, Generic and Similar) would meet the biowaiver criteria from Food and Drug Administration (FDA) and Brazilian Agency for Health Surveillance (ANVISA) agencies. All formulations were evaluated considering the dissolution profile carried out in Simulated Gastric Fluid (SGF) pH 1.2, Acetate Buffer (AB) pH 4.5 and Simulated Intestinal Fluid (SIF) pH 6.8. The results demonstrated that all formulations fulfilled the 85% of drug dissolved at 30 min criterion in SGF pH 1.2. However, in AB pH 4.5 and SIF pH 6.8, some formulations, including the comparator, did not achieve this dissolution percentage. The discrepant dissolution profiles also failed the ƒ2 similarity factor analysis, since none of the formulations showed values between 50 and 100 in the three dissolution media. Comparative dissolution profiles were not similar, considering that the main issues concerning the dissolution were evidenced for the comparator product. Hence, a revision in the regulatory norms in order to establish criteria to switch the comparator could result in an increased application of drugs based on biowaiver criteria.
Leadership practices and sustained lesson study

ABSTRACT Background The continual improvement of teaching and learning is vital for schools in order to meet the rapid changes in the world around us. Lesson study is considered a valuable professional development approach in that regard. It is focused on teachers collaboratively studying live classroom lessons. Sustaining lesson study, by making its core components part of the school’s organisational routines, can help schools continually and systematically to improve student learning and teaching. However, despite the value of this approach, sustaining lesson study turns out to be complex. Leadership seems to play a crucial role therein, but the question is: how? Purpose The study aimed to gain in-depth insight into what leadership looks like in schools that sustained lesson study. Method A case study design was used to investigate leadership in two secondary schools. We conducted over 300 hours of observations through immersion within practice, collected school policy documents, and interviewed the school leadership. Data were analysed qualitatively. Findings The analysis identified that both schools carried out various leadership practices for sustained lesson study. For leadership at schools that aim for sustained lesson study, it seems important to schedule lesson study, to be available, to have knowledge about lesson study and to appoint a lesson study coordinator. Whether and how leadership practices were carried out seemed to depend on the school’s context – for instance, by the policy reasons for working with lesson study. As such, it is important to examine the school and its leadership in context when considering sustainability. Conclusion Through immersion within practice, specific and real-life examples of leadership were identified. This study’s insights could help school leadership to sustain lesson study in their schools.
Spiritual Activity as an Effort to Cope with Depression during the COVID-19 Pandemic in Indonesia

Spiritual activity is used to be associated with better mental health, particularly in the face of stress. At the beginning of the COVID-19 pandemic, numerous new regulations, including quarantine, restrictions on mobility, and physical distancing, triggered stress throughout society. The objective of the study is to explore the relationship of spiritual activities at each level of depression in Indonesia in the early stages of the COVID-19 pandemic (2-4 May 2020). The cross-sectional research was administered online in 34 provinces in Indonesia, involving 2189 respondents aged 15 years old and over and social media users. The researchers employed a structured questionnaire to examine demographic characteristics and coping activities and measured depressive symptoms using the Patient Health Questionnaire (PHQ-9). Multivariate results presented that the spiritual activities are able to decrease the risk of depression at every depression level (mild, moderate, and severe) after being controlled by gender and marital status. The values for each level, which are mild, moderate, and severe, were OR=0.332 (95% CI 0.19-0.60; p-value=0.000), OR=0.198 (95% CI 0.09-0.43; p-value=0.000), and OR=0.234 (95% CI 0.08-0.64; p-value=0.005), respectively. Good spiritual activities during an infectious disease outbreak are efficient to support some individuals in reducing the risk of depression, particularly in Indonesia.
Impaired social decision‐making in males with methamphetamine use disorder

Individuals with methamphetamine use disorder (MUD) commonly exhibit socially problematic behaviours. Investigating the prosocial decision‐making of individuals with MUD could enable a better understanding of their impaired social functioning and help improve their social relationships. We conducted two studies to examine the performance of individuals with MUD and healthy controls on a modified dictator game. In Study 1, 55 male individuals with MUD and 34 healthy male participants made a series of choices between two pairs of monetary prizes for themselves and for others. In Study 2, 62 male individuals with MUD and 31 healthy male participants made the same choices as in Study 1 after a brief exposure to methamphetamine‐related pictures. In both studies, we consistently found a context dependency of decreased prosociality in individuals with MUD. That is, individuals with MUD made fewer prosocial choices than healthy individuals in disadvantageous contexts (but not advantageous contexts). The results of the computational model suggested that the lower prosociality of individuals with MUD in disadvantageous contexts could be attributed to the lower weight placed on others' benefits. Moreover, when exposed to methamphetamine‐related pictures, individuals with MUD showed less caution and slower encoding/motor speed than healthy individuals, and individuals with MUD with a longer history of methamphetamine use tended to respond less cautiously. Our findings provide evidence that in disadvantageous contexts, individuals with MUD show reduced prosociality and less consideration of others' benefits. Identifying the origin of the alterations in prosocial decision‐making has implications for diagnosis and treatment.
Role and Contribution of Knowledge Management to Development the Competitiveness in Hotel Industry

Knowledge represents a strategic resource of economic and social development today. It is the basis on which businesses can build sustainable operations and gain competitive advantages. Knowledge management (KM) has been embraced by businesses, particularly in the production and service sectors. However, the hotel industry has still not implemented knowledge management-focused activities to their extent. The introduction of a knowledge management strategy in the Egyptian hotel industry is taking place at a very slow pace. There is a growing awareness within the hotel industry of the need to undertake Knowledge management activities, develop a knowledge management strategy and the importance of human resources. Among researchers and managers, there is constant debate concerning the way knowledge management activities. A 54 questionnaire survey sample was selected and its size corresponded to the part of ten hotels in Cairo to determine their level of Knowledge Management and the extent to which Knowledge Management activities and strategies contribute to the development of a hotel’s competitive ability. The empirical research shows that the hotel industry agrees with the fact that a developed Knowledge Management strategy and the implementation of Knowledge Management-focused activities significantly contribute to the achievement of hotels objectives and goals such as increasing productivity, developing employees, improving business efficiency and customer relation, improving human resource management and creating the environment that encourages innovations and consequently to the successful business performance. Successful business performance of hotels will help in gaining competitive advantages in the local, regional, and global markets.
Detection and classification of skin diseases with ensembles of deep learning networks in medical imaging

Skin disorders are a serious worldwide public health issue that affects a large number of individuals. In recent years, with the fast advancement of technology and the use of different data mining approaches, treatment of skin predictive classification has really become highly predictive as well as accurate. As a result, the type of machine learning approaches capable of efficiently differentiating skin condition categorization is essential. So far, no one machine learning approach has outperformed the others in terms of skin disease prediction. In this research, we introduce a new method that combines two separate data mining approaches into a single unit, as well as an ensemble approach that combines both data mining techniques into a single group. We explore different data mining strategies to categorize the skin condition using an informative Dermatology publicly accessible dataset ISIC2019 images, and then apply an ensemble deep learning method. Furthermore, the presented ensemble technique, which is based on machine and deep learning, was tested on Dermatology datasets and was able to categorize skin disorders into seven categories.
Impact of the COVID-19 Pandemic on the Work Engagement of UK Active Employees

The objective of this investigation was to describe the work engagement perceived by UK workers during the COVID-19 pandemic. A descriptive cross-sectional study was conducted. The sample included 1085 participants, aged 18 years and older, living in the UK during the COVID-19 pandemic, who were active workers. Data were collected using an online questionnaire and the UWES-9. They were analysed using descriptive statistics, a t-test for equality of means or ANOVA, and the Chi-squared Automatic Interaction Detection method. The mean value in the UWES-9 was 3.46 (SD = 1.11). Participants with lower satisfaction (21.8%) gave significantly low or very low UWES-9 scores in 58.5% of the cases. Greater work engagement was obtained with more resources and less conflict, risk, and stress. In cases where there had been contact with COVID-19, this was associated with slightly lower levels of work engagement. These results could motivate and guide companies to adopt risk prevention measures and protocols to return to normal working conditions after the initial crisis phase of the pandemic.
Stilbocrea banihashemiana sp. nov. a New Fungal Pathogen Causing Stem Cankers and Twig Dieback of Fruit Trees

Stem cankers and twig dieback were the most serious disease of fig (Ficus carica) and loquat (Eriobotrya japonica) noticed in a survey of fruit tree orchards in the Fars Province, Iran. Isolates of Bionectriaceae were consistently recovered from symptomatic fig and loquat trees. Phylogenetic analyses of multiple nuclear loci, internal transcribed spacer regions (ITS) of rDNA, RNA polymerase II subunit 2 (rpb2), and translation elongation factor 1-α (tef1), combined with morphological observations, revealed that isolates could be referred to a still unknown taxon, which was formally described as Stilbocrea banihashemiana sp. nov. Phylogenetically, isolates from fig and loquat trees clustered in a well-supported monophyletic group within the Stilbocrea clade of Bionectriaceae, closely related to S. walteri. Stilbocrea banihashemiana sp. nov. was characterized by the lack of stilbella-like asexual structure in both natural substrates and pure cultures and produced two morphologically distinct types of conidia, globose and cylindrical, formed on short and long simple phialides. In pathogenicity tests, S. banihashemiana sp. nov. induced stem cankers in both fig and loquat, wood discoloration in fig and twig dieback in loquat. Pathogenicity tests also showed that the potential host range of this novel pathogen includes other economically relevant horticultural trees.
QoS-Aware Cost Minimization Strategy for AMI Applications in Smart Grid Using Cloud Computing

Cloud computing coupled with Internet of Things technology provides a wide range of cloud services such as memory, storage, computational processing, network bandwidth, and database application to the end users on demand over the Internet. More specifically, cloud computing provides efficient services such as “pay as per usage”. However, Utility providers in Smart Grid are facing challenges in the design and implementation of such architecture in order to minimize the cost of underlying hardware, software, and network services. In Smart Grid, smart meters generate a large volume of different traffics, due to which efficient utilization of available resources such as buffer, storage, limited processing, and bandwidth is required in a cost-effective manner in the underlying network infrastructure. In such context, this article introduces a QoS-aware Hybrid Queue Scheduling (HQS) model that can be seen over the IoT-based network integrated with cloud environment for different advanced metering infrastructure (AMI) application traffic, which have different QoS levels in the Smart Grid network. The proposed optimization model supports, classifies, and prioritizes the AMI application traffic. The main objective is to reduce the cost of buffer, processing power, and network bandwidth utilized by AMI applications in the cloud environment. For this, we developed a simulation model in the CloudSim simulator that uses a simple mathematical model in order to achieve the objective function. During the simulations, the effects of various numbers of cloudlets on the cost of virtual machine resources such as RAM, CPU processing, and available bandwidth have been investigated in cloud computing. The obtained simulation results exhibited that our proposed model successfully competes with the previous schemes in terms of minimizing the processing, memory, and bandwidth cost by a significant margin. Moreover, the simulation results confirmed that the proposed optimization model behaves as expected and is realistic for AMI application traffic in the Smart Grid network using cloud computing.
Online Tuning of Control Parameters for Off-Road Mobile Robots: Novel Deterministic and Neural Network-Based Approaches

This article addresses the problem of online adaptation of control parameters, dedicated to a path tracking problem in off-road conditions. Two approaches are offered to modify the tuning gain of a previously developed adaptive and predictive control law. The first approach is a deterministic method based on dynamic equations of the system, allowing the adaptation of the settling distance with respect to robot capabilities depending on grip conditions and velocity. The second strategy uses a neural network trained with a covariance matrix adaptation evolution strategy (CMA-ES) algorithm to optimize the robot’s behavior with respect to an objective (obj) function. Each approach uses as input dynamic parameters, estimated from sliding angles and cornering stiffness observers. Both methods are described and compared to results obtained when using constant parameters to identify their respective strengths and weaknesses. They have been implemented and tested in real conditions on an off-road mobile robot with varying terrain and trajectories. An in-depth analysis of the proposed techniques is done, and further insights are obtained in the context of gain tuning for steering controllers in dynamic environments. The performance and transferability of these methods are demonstrated as well as their robustness to changes in terrain properties. As a result, tracking errors are reduced while preserving the stability and explainability of the control architecture.
Left atrial appendage thrombus in patients referred to electrical cardioversion for typical atrial flutter

Introduction: Patients with atrial flutter (AFL) are at risk of stroke; however, the stratification of stroke risk is difficult. It remains unknown whether left atrial appendage thrombus (LAAT) in AFL patients on chronic oral anticoagulation (OAC) contributes significantly to that risk. Aim of the research: To assess the prevalence and predictors of LAAT, and its role in the prediction of mortality, stroke, and systemic thromboembolic events among consecutive AFL patients on OAC admitted for electrical cardioversion. Material and methods: This was a prospective, single-centre cohort study. The participants underwent transoesophageal echocardiography before electrical cardioversion. A total of 69 patients were enrolled. The primary outcome was the presence of LAAT. All participants were followed up for 12 months to evaluate the incidence of systemic thromboembolic events, stroke, and death. Results: Despite uninterrupted OAC, irrespective of the anticoagulant agent type, LAAT was present in 10.1% of patients referred for cardioversion due to typical AFL of > 48-hour duration. The significant predictor of LAAT was prior stroke/ transient ischaemic attack/thromboembolic event (OR = 14.75; 95% CI: 2.17–108.33). No deaths, strokes, or systemic throm- boembolic events occurred during the follow-up period. Conclusions: The predictive role of LAAT in relation to mortality, stroke, and systemic thromboembolic events among pa- tients with AFL and chronic oral anticoagulation remains unclear.
This paper is included in the Proceedings of the Eighteenth Symposium on Usable Privacy and Security (SOUPS 2022)

Intelligent voice assistants may soon become proactive, offering suggestions without being directly invoked. Such behavior increases privacy risks, since proactive operation requires continuous monitoring of conversations. To mitigate this problem, our study proposes and evaluates one potential privacy control, in which the assistant requests permission for the information it wishes to use immediately after hearing it. To ﬁnd out how people would react to runtime permission requests, we recruited 23 pairs of participants to hold conversations while receiving ambient suggestions from a proactive assistant, which we simulated in real time using the Wizard of Oz technique. The interactive sessions featured different modes and designs of runtime permission requests and were followed by in-depth interviews about people’s preferences and concerns. Most participants were excited about the devices despite their continuous listening, but wanted control over the assistant’s actions and their own data. They generally prioritized an interruption-free experience above more ﬁne-grained control over what the device would hear.