Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of family relations and school environment on aggressive behavior of school age students

Background: Family and school conditions have been reliably connected to aggression issues in adolescence. Aim: Assessing effect of family relations and school environment on aggressive behavior of school age students, exploring the difference between adolescence aggressive behavior in relation to teaching environment and family relation. Design: A descriptive, cross-sectional design was utilized. Setting: The study was conducted at two randomly selected preparatory governmental schools affiliated to Al-Sayeda Zeinab educational directorate, Cairo, Egypt. Sample: A purposive sample of 180 adolescents in selected preparatory schools was included in the study. Tools: Five tools were used, 1) Socio-demographic data sheet for students, 2) Socio-demographic data sheet for parents, 3) Aggressive Behavior Scale, 4) Brief Family Relationship Scale and 5) School Climate Scale. Results: Showed that there were “statistical significant differences” between father and mother educational characteristics and methods of home punishment. Also, there was a significant statistical relationship between family relations and aggressive behavior of children. Conclusion: A significant statistical relationship between family relations and aggressive behavior of children. Also, a significant statistical relationship was found between school environment and aggressive behavior of children. Also, a significant statistical relationship was revealed between aggressive behavior of children and socio-demographic characteristics of their parents. Recommendations: Psycho-educational programs about impulsivity, aggression, family relations will be important to increase students and parents’ awareness about behavioral competencies and challenges.
Situating service work in action: A review and a pragmatist agenda for analysing interactive service work

Research on interactive service work has paid close attention to how organizations and frontline employees deal with the inherent complexity of the customer– employee–employer triangle. This raises questions about the agency of interactive service workers with respect to the indeterminacy of service interactions. Our meta-narrative review finds that the theorization of worker agency in service interactions remains underdeveloped in the two dominant research streams of mainstream management and labour process theory studies. Implicitly or explicitly, these streams either subsume agency under managerial prescription or view it through the binary polar of control and resistance. There has been less focus on service workers’ efforts to overcome practical difficulties in everyday service interactions. To address this lacuna, we offer a conceptual framework that draws on a less prominent, third research stream, which we label pragmatist. This stream includes scholarship largely unfamiliar to the international English-speaking community, published mainly in French and German academic jour-nals. We propose three contributions in this paper. First, we contribute to the interactive service work literature by mapping the theoretical plurality within and beyond the English-speaking community. Second, we problematize established streams of research by articulating the intellectual axes of the field; this allows us to present a new research area to account for the concrete dynamics of service interaction and to capture frontline employee agency. Third, we propose a pragmatist research framework coupled with a future research agenda more attentive to the embeddedness and materiality of frontline workers’ situated actions. This way, we address the indeterminacy of interactive situations.
Fatigue damage detection from imbalanced inspection data of Lamb wave

The core of structural health monitoring is to provide a real-time monitoring, inspection, and damage detection of structures. As one of the most promising technology to structural health monitoring, the Lamb wave method has attracted interest because it is sensitive to small-scale damage with a long detection range. However, in many real-world structural health monitoring applications, the nature of the problem implies structures work under normal condition in most of its operating phases; therefore, classes of data collected are not equally represented. The predictive capability of damage detection algorithms may significantly be impaired by class imbalance. This article presents a damage detection method using imbalanced inspection data which is collected through Lamb wave detection. Aiming at maximizing detection accuracy, an improved synthetic minority over-sampling technique using three-point triangle (triangle synthetic minority over-sampling technique) is proposed to conduct the over-sampling procedure and increase the number of minority samples. The iterative-partitioning filter is employed to remove the noisy examples which may be introduced by triangle synthetic minority over-sampling technique. Three conventional classification methods, namely, support vector machine, decision tree, and k-nearest neighbor, are used to perform the damage detection. A fatigue crack detection test using Lamb wave is performed to demonstrate the overall procedure of the proposed method. Three damage sensitive features, namely, normalized amplitude, correlation coefficient, and normalized energy, are extracted from signals as datasets. A cross-validation is performed to verify the performance of the proposed method for crack size identification.
Effect of Temperature and Surface Roughness on the Tribological Behavior of Electric Motor Greases for Hybrid Bearing Materials

Greased bearings in electric motors (EMs) are subject to a wide range of operational requirements and corresponding micro-environments. Consequently, greases must function effectively in these conditions. Here, the tribological performance of four market-available EM greases was characterized by measuring friction and wear of silicon nitride sliding on hardened 52100 steel. The EM greases evaluated had similar viscosity grades but different combinations of polyurea or lithium thickener with mineral or synthetic base oil. Measurements were performed at a range of temperature and surface roughness conditions to capture behavior in multiple lubrication regimes. Results enabled direct comparison of market-available products across different application-relevant metrics, and the analysis methods developed can be used as a baseline for future studies of EM grease performance.
Cognitive Deficits in School Going Children with Attention Deficit Hyperactivity Disorder

Cognitive impairment has been found to be accompanying Attention deficit hyperactivity disorder in several studies. Cognitive abilities are key to healthy and proper functioning for any human and that’s why cognitive deficits creates various types of problems in persons with cognitive impairment. The present study aimed at studying the cognitive deficits in school going children with ADHD.A cross sectional study was designed for studying the cognitive deficits in school going children with ADHD. Thirty school going children with ADHD were selected by using purposive sampling technique. DT-ADHD was used for screening purpose. All of the 30 children were assessed on Malin’s Intelligence Scale for Indian Children (MISIC), Colour cancellation test, Children Colour Trail Test and Wisconsin Card Sorting Test. Statistical analysis of the findings was done by using SPSS. 20. The result showed that the school going children with ADHD performed poorly on subtests of MISIC, Wisconsin Card Sorting Test, Colour cancellation test and Children Colour Trail Test suggesting deficit in attention, concentration, in the speed of attention, in sequencing, mental flexibility, working memory, problem in shifting and maintaining set, problem in forming abstract concepts. The present study showed that the school going children with ADHD had significant cognitive deficits.
Breast Cancer-Related Apps in Google Play and App Store: Evaluate of Their Functionality and Quality

Aim: This study aimed to evaluate the functionality and quality of breast cancer-related apps which can be accessed from Turkey. Methods: The research covers 707 mobile applications, which were searched using the keywords "cancer", "oncology" and "breast cancer" in Google and App store stores between January and June 2019. The quality of apps was assessed with the user version of the Mobile App Rating Scale (MARS). Results: Mobile applications focus on communication, education and treatment order / plan categories. The average MARS quality score for applications in all of the two stores was determined as 3.42. According to the average score of the scale sub-dimensions; It was seen that they were ranked as functionality, aesthetics, information quality and participation. MARS scale sub-groups were listed as functionality, aesthetics, knowledge quality, and participation. Conclusion: e-Health is a subject that has just started to be used actively in health. Although basic information about breast cancer was used, information on prevention, early diagnosis and precautions was relatively limited and was not personalized. Support from healthcare professionals and further efforts should be made to develop evidence-based breast cancer knowledge and innovative technology and applications regarding cancer. Implications for practice: e-Health technologies are a good tool in breast cancer, but appear to lack evidence-based content and individual specific areas such as age and education level.
Phishing email strategies: Understanding cybercriminals' strategies of crafting phishing emails

It is a known fact that cybercriminals often manipulate people to steal sensitive information. However, there has been a lack of research in investigating cybercriminals' strategies and the evolution of strategies when crafting phishing emails to entice people to perform a variety of malicious tasks such as clicking on fraudulent links. This study uses a combination of Natural Language Processing (NLP), topic modeling, and clustering techniques to analyze and evaluate the persuasive techniques/strategies, which cybercriminals use when crafting fraudulent emails. Our experimental results revealed the efficacy of using these techniques in understanding cybercriminals' mindset as well as how certain aspects of these techniques maintained consistency despite the evolution of the strategy from early Nigerian scams to more modern phishing emails. The findings of our study indicate that the most common technique/strategy used by cybercriminals is a combination of creating a sense of urgency while promising a reward. Moreover, despite the evolution of technology, cybercriminals are still effectively using the same persuasive techniques. Based on our findings, we provided several recommendations to improve anti‐phishing software and awareness and training programs.
Revisiting Label Smoothing Regularization with Knowledge Distillation

Label Smoothing Regularization (LSR) is a widely used tool to generalize classification models by replacing the one-hot ground truth with smoothed labels. Recent research on LSR has increasingly focused on the correlation between the LSR and Knowledge Distillation (KD), which transfers the knowledge from a teacher model to a lightweight student model by penalizing their output’s Kullback–Leibler-divergence. Based on this observation, a Teacher-free Knowledge Distillation (Tf-KD) method was proposed in previous work. Instead of a real teacher model, a handcrafted distribution similar to LSR was used to guide the student learning. Tf-KD is a promising substitute for LSR except for its hard-to-tune and model-dependent hyperparameters. This paper develops a new teacher-free framework LSR-OS-TC, which decomposes the Tf-KD method into two components: model Output Smoothing (OS) and Teacher Correction (TC). Firstly, the LSR-OS extends the LSR method to the KD regime and applies a softer temperature to the model output softmax layer. Output smoothing is critical for stabilizing the KD hyperparameters among different models. Secondly, in the TC part, a larger proportion is assigned to the uniform distribution teacher’s right class to provide a more informative teacher. The two-component method was evaluated exhaustively on the image (dataset CIFAR-100, CIFAR-10, and CINIC-10) and audio (dataset GTZAN) classification tasks. The results showed that LSR-OS can improve LSR performance independently with no extra computational cost, especially on several deep neural networks where LSR is ineffective. The further training boost by the TC component showed the effectiveness of our two-component strategy. Overall, LSR-OS-TC is a practical substitution of LSR that can be tuned on one model and directly applied to other models compared to the original Tf-KD method.
Model simulations of chemical effects of sprites in relation with observed HO2 enhancements over sprite-producing thunderstorms

Abstract. Recently, measurements by the Superconducting Submillimeter-Wave Limb Emission Sounder (SMILES) satellite instrument have been presented which indicate an increase in mesospheric HO2 above sprite-producing thunderstorms. The aim of this paper is to compare these observations to model simulations of chemical sprite effects. A plasma chemistry model in combination with a vertical transport module was used to simulate the impact of a streamer discharge in the altitude range 70–80 km, corresponding to one of the observed sprite events. Additionally, a horizontal transport and dispersion model was used to simulate advection and expansion of the sprite air masses. The model simulations predict a production of hydrogen radicals mainly due to reactions of proton hydrates formed after the electrical discharge. The net effect is a conversion of water molecules into H+OH. This leads to increasing HO2 concentrations a few hours after the electric breakdown. Due to the modelled long-lasting increase in HO2 after a sprite discharge, an accumulation of HO2 produced by several sprites appears possible. However, the number of sprites needed to explain the observed HO2 enhancements is unrealistically large. At least for the lower measurement tangent heights, the production mechanism of HO2 predicted by the model might contribute to the observed enhancements.
Levels of Maternal Serum Alpha-fetoprotein and Beta Human Chorionic Gonadotropin in HIV Seropositive Pregnant Women Attending Antenatal Care at Nnamdi Azikiwe University Teaching Hospital Nnewi, Nigeria

HIV infection remains a worrisome pandemic especially in developing countries like Nigeria, with an increasing number of infected women becoming pregnant, with added risk of pregnancy complications such as intrauterine fetal death, neural tube defects, and vertical transmissions. Hence this study assessed the levels of maternal serum alpha-fetoprotein (MSAFP) and beta human chorionic gonadotropin (β-hCG) in HIV seropositive pregnant women, and their implication Original Research Article Udeogu et al.; JAMMR, 33(12): 32-38, 2021; Article no.JAMMR. 58661 33 for maternal and fetal health. A total of 86 patients were recruited for the study from the Antenatal Clinic of Nnamdi Azikiwe University Teaching Hospital (NAUTH) Nnewi. Forty three were HIV seropositive (Test group), and forty three were HIV seronegative (Control group). Maternal serum alpha-fetoprotein and beta human chorionic gonadotropin levels were assayed by Enzyme Linked Immunosorbent Assay. The results showed that MSAFP levels (3.14±2.80 ng/ml) were significantly lower (P < .05) in HIV infected pregnant women when compared to HIV uninfected pregnant women (4.75±3.68 ng/ml). There was no significant difference in the levels of β-hCG (217.88±63.85mIU/mL) in the test group (P = 0.629) as compared to controls (223.75±47.71 mIU/mL). In the test group, increased CD4 counts were significantly associated with increased MSAFP and β-hCG levels in a positive fashion (P < .05). Increase in Gestational age was also significantly associated with increased β-hCG levels (P < .05). The measurements of MSAFP and β-hCG levels may be used alongside CD4 count in the assessment of maternal and fetal wellbeing. Human Immunodeficiency Virus by reducing the levels of MSAFP in HIV infected pregnant women increases the likelihood of pregnancy complications such as intrauterine fetal death.
FastPacket: Towards Pre-trained Packets Embedding based on FastText for next-generation NIDS

New Attacks are increasingly used by attackers every day but many of them are not detected by Intrusion Detection Systems as most IDS ignore raw packet information and only care about some basic statistical information extracted from PCAP files. Using networking programs to extract fixed statistical features from packets is good, but may not enough to detect nowadays challenges. We think that it is time to utilize big data and deep learning for automatic dynamic feature extraction from packets. It is time to get inspired by deep learning pre-trained models in computer vision and natural language processing, so security deep learning solutions will have its pre-trained models on big datasets to be used in future researches. In this paper, we proposed a new approach for embedding packets based on character-level embeddings, inspired by FastText success on text data. We called this approach FastPacket. Results are measured on subsets of CIC-IDS-2017 dataset, but we expect promising results on big data pre-trained models. We suggest building pre-trained FastPacket on MAWI big dataset and make it available to community, similar to FastText. To be able to outperform currently used NIDS, to start a new era of packet-level NIDS that can better detect complex attacks
Focus Within or On Others: The Impact of Reviewers' Attentional Focus on Review Helpfulness

When reviewers write online reviews, they differ in the focus of their attention: some focus on their own experiences, whereas some direct their attention to others—prospective consumers who may read the reviews in the future. This paper explores how, why, and when reviewers’ attentional focus can influence the helpfulness evaluation of reviews beyond the impact of substantive review content. Drawing on the attentional focus and persuasion literatures, we develop a theoretical model proposing that reviewers’ attentional focus may influence consumers’ perception of review helpfulness through opposing processes, and that its overall effect is contingent on the review’s two-sidedness. Results of one archival analysis and five controlled experiments provide consistent support for our hypotheses. This work challenges the predominant view of the positive impact of other-focus (vs. self-focus), explores the interpersonal impact of a reviewer’s attentional focus on prospective consumers who are total strangers, and reveals an important, context-specific boundary condition.
Involvement of Antioxidant Defenses and NF-κB/ERK Signaling in Anti-Inflammatory Effects of Pterostilbene, a Natural Analogue of Resveratrol

Pterostilbene (PTE), a natural stilbenoid occurring in grapes and berries, is recognized as a dimethylated analogue of resveratrol. This compound shows numerous notable pharmacological activities, including antiaging, anticancer, antidiabetes, antioxidant, and neuroprotection. This study investigates the anti-inflammatory properties of PTE in macrophage cells (RAW 264.7) against the lipoteichoic acid (LTA) stimulation. The expression of inflammatory tumor necrosis factor (TNF-α), interleukin-1β (IL-1 β), and inducible nitric oxide synthase (iNOS) and the content of nitric oxide (NO) were detected in LTA-induced cells. In addition, a Western blot assay was used to detect mitogen-activated protein kinases: extracellular signal-regulated kinase (ERK)1/2, p38 MAPK, and c-Jun N-terminal kinase (JNK). The phosphorylation of IκB and p65 and translocation of nuclear factor kappa B (NF-κB) were assessed by Western blot and immuno-fluorescence staining. The results showed that PTE significantly attenuated NO production and TNF-α, IL-1 β, and iNOS expression in LTA stimulated cells. Among the activation of ERK, JNK, and p38 in cells treated with LTA, PTE at higher concentration had only inhibited ERK activation. However, PTE blocked IκB phosphorylation, phosphorylation and nuclear translocation of p65NF-κB. Fascinatingly, PTE enhanced antioxidant defense molecules as verified by the enhanced heme oxygenase-1 (HO-1) expression, catalase (CAT) antioxidant enzyme, and non-enzymatic antioxidant, and reduced glutathione (GSH) in LTA-induced RAW 264.7 cells. These results suggest that PTE exerts an anti-inflammatory property via attenuating NF-κB/ERK signaling pathways as well as enriching antioxidant defense mechanisms.
Cyclopentadienyl iron dicarbonyl (CpFe(CO)2) derivatives as apoptosis-inducing agents

Iron has been found to serve multiple purposes besides being an oxygen carrier. Of particular note is the generation of deleterious free radicals which can lead to the formation of tumours. However, in this work, we have found that cyclopentadienyl iron carbonyl complexes CpFe(CO)2X (X = halide, NCS, BF4− and CpFe(CO)2) can induce apoptosis in breast cancer and HeLa cell lines. Normal cells are however unaffected. A detailed study on CpFe(CO)2I shows that the complex is metabolic-stable and easily permeable across a lipid barrier. Preliminary investigations into the mode of action suggest that a Fenton-type reaction caused by CpFe(CO)2 complexes may be related to cell death.
Scale‐dependent maximum reinforcement percentage in reinforced concrete beams

The Cohesive/Overlapping Crack Model is able to describe the transition between cracking and crushing failures occurring in reinforced concrete beams by increasing beam depth and/or steel percentage. Within this Nonlinear Fracture Mechanics model, the tensile and compressive ultimate behaviors of the concrete matrix are modeled through two different process zones that advance independently one of another. Moreover, this model is able to investigate local mechanical instabilities occurring in the structural behavior of reinforced concrete structures: tensile snap‐back and snap‐through, which are due to concrete cracking or steel fracture, and the compressive snap‐back occurring at the end of the plastic plateau, which is generated by the unstable growth of the crushing zone. In this context, the application of the Cohesive/Overlapping Crack Model highlights that the ductility, which is represented by the plastic rotation capacity of a reinforced concrete element subjected to bending, decreases as reinforcement percentage and/or beam depth increase. Thus, a scale‐dependent maximum reinforcement percentage beyond which concrete crushing occurs prior to steel yielding is demonstrated to exist. In particular, the maximum steel percentage results to be inversely proportional to h0.25, h being the beam depth. In this way, a rational and quantitative definition of over‐reinforcement is provided as a steel percentage depending on the beam depth.