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The public education system shifted towards one centered on information technology due to the COVID-19 epidemic. Hence, in recent years, online learning has emerged as a substantial curriculum component at several educational institutions in Sri Lanka. The present investigation explores the pedagogical practices in Sri Lankan government universities in the new normal via a qualitative approach by interviewing eight instructors in eight public universities. The findings revealed that the pedagogy has shifted to an online context with the pandemic, and the education system continuously applies online teaching, assessment, and evaluation techniques. Teachers and students initially encountered various issues in the new normal, including technical difficulties, economic conditions, and a lack of available resources for integrating IT into the education pedagogy. Hence, current practices should continue facilitating digital infrastructure and blended approaches for better outcomes. The authors recommend that policymakers and authorities take high responsibility for building an effective IT-based strategy. It is vital to train educators and encourage them to fully utilize the recent movement towards online instruction by supplying all the necessary technological skills. Training educators and encouraging them to utilize the recent movement towards online instruction entirely is vital by supplying all the necessary technological skills. The government should provide essential infrastructure and facilities to institutions while working toward creating a welcoming atmosphere within universities. Giving encouragement and financial aid to students is critical to alleviating student pressures while transitioning to online learning methods. Policymakers must consider the significance of the human component and realize that technology alone cannot solve every problem. The present transition in the educational system demands implementing a strategic framework to identify the strengths and address the shortcomings.

BackgroundSchizophrenia (SZ) is characterized by abnormalities in self-representation, including a disturbed sense of agency (SoA). The continuous processing of sensory information concerning the internal state of the body (interoception) is argued to be fundamental to neural representations of the self. We, therefore, tested if aberrant interoception underpins disturbances in SoA in SZ, focusing on cardiac interoceptive signaling.MethodsForty-two SZ and 29 non-clinical participants (healthy controls; HC) performed an intentional binding task to measure SoA during concurrent heartbeat recording. The effect of cardiac interoceptive signals on SoA was measured by the difference in intentional binding effect during systole and diastole. This measure was standardized based on the overall intentional binding effect to control for non-cardiac factors, and then compared between SZ and HC.ResultsOur study revealed a significant difference between SZ and HC groups, with opposite effects of cardiac systole on SoA. Specifically, cardiac systole disrupted SoA in SZ, contrasting with the enhanced SoA in HC. Across the SZ group, the extent to which SoA was disrupted by cardiac systole correlated significantly with a clinical proxy for symptom instability, namely the number of hospital admissions for hallucinations and delusions. Furthermore, the disruption was particularly observed in patients with severe hallucinations.ConclusionsThis study revealed a disturbance in the impact of cardiac interoceptive signals on an implicit index of SoA in schizophrenia. This supports the notion that pathophysiological disruption of the central integration of interoceptive information increases vulnerability to disturbances in self-representation and the associated expression of schizophrenic symptoms.

Summary: Background: Global cyclical outbreaks of human enterovirus infections has positioned human enterovirus A71 (EV-A71) as a neurotropic virus of clinical importance. However, there remains a scarcity of internationally approved antivirals and vaccines. Methods: In pursuit of repurposing drugs for combating human enteroviruses, we employed a comprehensive pharmacophore- and molecular docking-based virtual screen targeting EV-A71 capsid protein VP1-4, 3C protease, and 3D polymerase proteins. Among 15 shortlisted ligand candidates, we dissected the inhibitory mechanism of Tanomastat in cell-based studies and evaluated its in vivo efficacy in an EV-A71-infected murine model. Findings: We demonstrated that Tanomastat exerts dose-dependent inhibition on EV-A71 replication, with comparable efficacy profiles in enterovirus species A, B, C, and D in vitro. Time-course studies suggested that Tanomastat predominantly disrupts early process(es) of the EV-A71 replication cycle. Mechanistically, live virus particle tracking and docking predictions revealed that Tanomastat specifically impedes viral capsid dissociation, potentially via VP1 hydrophobic pocket binding. Bypassing its inhibition on entry stages, we utilized EV-A71 replication-competent, 3Dpol replication-defective, and bicistronic IRES reporter replicons to show that Tanomastat also inhibits viral RNA replication, but not viral IRES translation. We further showed that orally administered Tanomastat achieved 85% protective therapeutic effect and alleviated clinical symptoms in EV-A71-infected neonatal mice. Interpretation: Our study establishes Tanomastat as a broad-spectrum anti-enterovirus candidate with promising pre-clinical efficacy, warranting further testing for potential therapeutic application. Funding: MOE Tier 2 grants (MOE-T2EP30221-0005, R571-000-068-592, R571-000-076-515, R571-000-074-733) and A∗STAR Biomedical Research Council (BMRC).

Objective Identify the proportion of patients referred with putative functional seizures (FS) that were subsequently re-diagnosed as epileptic seizures (ES), or an alternative diagnosis, following video telemetry EEG (VTEEG). In addition, describe the characteristics of those seizures.Methods The VTEEG reports from patients admitted to the Chalfont Centre for Epilepsy between 2019 and 2022 were reviewed. Pre-VTEEG and post-VTEEG diagnoses were compared to identify whether a diagnostic revision was made from suspected FS to ES or another diagnosis. Diagnostic revision cases were then grouped into cohorts with associated features and reviewed to characterise and describe FS mimics.Results 444 VTEEG reports where patients had habitual events were identified. 4.7% of patients were referred with FS and were subsequently diagnosed with ES or another diagnosis. In this group, several cohorts could be identified including frontal lobe epileptic seizures, ES with functional overlay, insular or temporal lobe epileptic seizures associated with autonomic or marked experiential peri-ictal symptoms, and individuals who had both ES and FS but whose ES were revealed on medication withdrawal.Conclusion In patients referred to a tertiary epilepsy unit, a small minority of cases had seizures diagnosed as functional and reclassified as epileptic or an alternative diagnosis. It is clinically important to be aware of these FS mimics.

Introduction Functional neurological disorder (FND) is a common cause of referral to neurology services. FND has been shown to lead to significant healthcare resource use and is associated with significant disability, comorbidity and distress. This leads to substantial direct, indirect and intangible costs to the patient and society.Methods We recruited consecutive patients with FND referred to a tertiary FND specialist clinic. We assessed health and social care resource use in the 6 months preceding their consultation through a modified version of the Client Service Receipt Inventory in the form of a postal questionnaire. The total cost was estimated by combining the number and frequency of health resource use with standard national unit costs. We also assessed indirect costs such as informal care and loss of income.Results We collected data on 118 subjects. Patients with comorbid anxiety or depression had higher costs in the preceding 6 months, as did patients who had a longer duration of FND symptoms. Indirect costs were higher than the already substantial direct costs and a large proportion of patients with FND were receiving government support.Conclusion This study highlights the high cost of FND to both patients and health systems. Adequate reform of the patient pathway and reorganisation of services to make diagnoses and initiate treatment more quickly would likely reduce these costs.

IntroductionInfective Endocarditis (IE) is a rare, life-threatening infection of the endocardium with multisystem effects. Culprit microorganisms derived from different niches circulate through the bloodstream and attach to the endocardium, particularly the heart valves. This study aimed to investigate culprit microorganisms among a cross-sectional cohort of IE patients, their associated factors, and to explore the potential relationship to the oral microbiome.MethodsIn this observational study, we undertook a cross-sectional analysis of 392 medical records from patients diagnosed with IE. The primary outcome of this study was to analyse the association between the IE culprit microorganisms and the underlying anatomical types of IE (native valve (NVE), prosthetic valve (PVE), or cardiac device-related (CDE)). Secondary outcomes encompassed a comparative analysis of additional factors, including: the treatment approaches for IE, and the categorisation of blood cultures, extending to both genus and species levels. Additionally, we cross-referenced and compared the species-level identification of IE bacteraemia outcome measures with data from the expanded Human Oral Microbiome Database (eHOMD).ResultsA culprit microorganism was identified in 299 (76.28%) case participants. Staphylococcal infections were the most common (p

This paper explores the “triangulation approach” in social science research methods. Triangulation is an emerging method specifically in qualitative and multi-method studies. Researchers in the social sciences have increased their use of the triangulation approach recently due to the merits of this approach, especially to conduct in-depth studies through multiple inquiries. Simultaneously, this method has criticism and misconceptions among social researchers in terms of what it is, how it can be used, and the credibility of the findings when used. Therefore, this paper analyses in depth what triangulation is, the types of triangulations and how they can be applied in the social sciences.

The rising awareness of nutritional values has led to an increase in the popularity of meat-based diets. Hence, to ensure public health, industries and consumers are focusing more on the quality and freshness of this food. Authentic meat quality assessment methods can indeed be exorbitant and catastrophic. Furthermore, it is subjective and reliant on the knowledge of specialists. Fully automated computer-aided diagnosis systems are required to eradicate the variability among experts. However, evaluating the quality of meat automatically is challenging. Deep convolutional neural networks have shown a tremendous improvement in meat quality assessment. This research intends to utilize an ensemble framework of shallow convolutional neural networks for assessing the quality and freshness of the meat. Two compact CNN architectures (ConvNet-18 and ConvNet-24) are developed, and the efficacy of the models are evaluated using two publicly available databases. Experimental findings reveal that the ConvNet-18 outperforms other state-of-the models in classifying fresh and spoiled meat with an overall accuracy of 99.4%, whereas ConvNet-24 shows a better outcome in categorizing the meat based on its freshness. This model yields an accuracy of 96.6%, which is much better compared with standard models. Furthermore, the suggested models effectively detect the quality and freshness of the meat with less complexity than the existing state-of-the art techniques.

Positive-sense RNA viruses modify intracellular calcium stores, endoplasmic reticulum and Golgi apparatus (Golgi) to generate membranous replication organelles known as viral factories. Viral factories provide a conducive and substantial enclave for essential virus replication via concentrating necessary cellular factors and viral proteins in proximity. Here, we identified the vital role of a broad-spectrum antiviral, peruvoside in limiting the formation of viral factories. Mechanistically, we revealed the pleiotropic cellular effect of Src and PLC kinase signaling via cyclin-dependent kinase 1 signaling leads to Golgi-specific brefeldin A-resistance guanine nucleotide exchange factor 1 (GBF1) phosphorylation and Golgi vesiculation by peruvoside treatment. The ramification of GBF1 phosphorylation fosters GBF1 deprivation consequentially activating downstream antiviral signaling by dampening viral factories formation. Further investigation showed signaling of ERK1/2 pathway via cyclin-dependent kinase 1 activation leading to GBF1 phosphorylation at Threonine 1337 (T1337). We also showed 100% of protection in peruvoside-treated mouse model with a significant reduction in viral titre and without measurable cytotoxicity in serum. These findings highlight the importance of dissecting the broad-spectrum antiviral therapeutics mechanism and pave the way for consideration of peruvoside, host-directed antivirals for positive-sense RNA virus-mediated disease, in the interim where no vaccine is available.

Iron oxides (hematite, Fe2O3, and magnetite, Fe3O4), previously used as electron mediators in the galvanic system with zero-valent aluminum (ZVAl), have been shown to recover Au upon cementation in Au–Cu ammoniacal thiosulfate media selectively, and this warrants further investigation. This research is focused on investigating the role of the semiconductive properties of metal oxides by performing a cementation experiment by mixing 0.15 g of electron mediators (Fe3O4, Fe2O3, TiO2 (anatase and rutile)) and 0.15 g of zero-valent aluminum powder as an electron donor in various electrochemical experiments. The results revealed that upon the cementation experiment, synthetic Fe2O3 and Fe3O4 were consistently able to selectively recover Au at around 90% and Cu at around 20%. Compared to activated carbon (AC), TiO2, in anatase and rutile forms, obtained selective recovery of gold, but the recovery was utterly insignificant compared to that of iron oxides, obtaining an average of 93% Au and 63% Cu recovery. The electrochemical and surface analysis supports the results obtained upon the cementation process, where TiO2, upon cyclic voltammetry (CV), obtained two reduction peaks centered at −1.0 V and −0.5 V assigned to reducing Au and Cu ions, respectively. Furthermore, various electrochemical impedance spectroscopic analyses revealed that the flat band potential obtained in the Mott–Schottky plot is around −1.0 V and −0.2 V for iron oxides and titanium oxides, respectively, suggesting that the electrons travel from semiconductor interface to electrolyte interface, and electrons are accessible only to Au ions in the electrolyte interface (reduction band edge around −1.0 V). The determination of this selective cementation mechanism is one of a kind. It has been proposed that the semiconductive properties of Fe2O3, Fe3O4, and, by configuring their relative energy band diagram, the travel of electrons from the iron oxide–electrolyte interface facilitate the selective cementation towards Au(S2O3)23+ ions in gold–copper ammoniacal thiosulfate solutions.

Virus genome recoding is an attenuation method that confers genetically stable attenuation by rewriting a virus genome with numerous silent mutations. Prior flavivirus genome recoding attempts utilised codon deoptimisation approaches. However, these codon deoptimisation approaches act in a species dependent manner and were unable to confer flavivirus attenuation in mosquito cells or in mosquito animal models. To overcome these limitations, we performed flavivirus genome recoding using the contrary approach of codon optimisation. The genomes of flaviviruses such as dengue virus type 2 (DENV2) and Zika virus (ZIKV) contain functional RNA elements that regulate viral replication. We hypothesised that flavivirus genome recoding by codon optimisation would introduce silent mutations that disrupt these RNA elements, leading to decreased replication efficiency and attenuation. We chose DENV2 and ZIKV as representative flaviviruses and recoded them by codon optimising their genomes for human expression. Our study confirms that this recoding approach of codon optimisation does translate into reduced replication efficiency in mammalian, human, and mosquito cells as well as in vivo attenuation in both mice and mosquitoes. In silico modelling and RNA SHAPE analysis confirmed that DENV2 recoding resulted in the extensive disruption of genomic structural elements. Serial passaging of recoded DENV2 resulted in the emergence of rescue or adaptation mutations, but no reversion mutations. These rescue mutations were unable to rescue the delayed replication kinetics and in vivo attenuation of recoded DENV2, demonstrating that recoding confers genetically stable attenuation. Therefore, our recoding approach is a reliable attenuation method with potential applications for developing flavivirus vaccines.

In appearance-based gait analysis studies, Gait Energy Images (GEI) have been shown to be an effective tool for human identification and gait pathology detection. In addition, model-based studies found kinematic and spatio-temporal features to be useful for gait recognition and Autism Spectrum Disorder (ASD) classification. Adapting the GEI to focus on the strong ASD features would improve the early screening of ASD by allowing the use of powerful appearance-based classifiers such as Convolutional Neural Networks (CNN). This paper introduces an enhanced GEI, by averaging images from a video sequence to produce a single image but by retention of a person’s joint positions only, instead of the full body silhouettes. Depth is encoded into the binary images before they are averaged using colour mapping, a technique used in the Chrono-Gait Image. The Joint Energy Image (JEI) therefore embeds both the temporal and depth information of the joints into a 2D image. The image was preprocessed using Principal Component Analysis before being applied to a Multi-Layer Perceptron, and a Random Forest classifier. The JEI was also applied to a CNN directly and accuracy was improved when using a Test Time Augmentation (TTA) measure. The CNN achieved a TTA accuracy of 95.56% when trained on a primary dataset of 100 subjects (50 with ASD and 50 that are typically developed), and 80% TTA accuracy on a secondary dataset of 20 subjects (10 ASD and 10 typically developed) across multiple tests.

Summary: Background: RNA viruses account for many human diseases and pandemic events but are often not targetable by traditional therapeutics modalities. Here, we demonstrate that adeno-associated virus (AAV) -delivered CRISPR-Cas13 directly targets and eliminates the positive-strand EV-A71 RNA virus in cells and infected mice. Methods: We developed a Cas13gRNAtor bioinformatics pipeline to design CRISPR guide RNAs (gRNAs) that cleave conserved viral sequences across the virus phylogeny and developed an AAV-CRISPR-Cas13 therapeutics using in vitro viral plaque assay and in vivo EV-A71 lethally-infected mouse model. Findings: We show that treatment with a pool of AAV-CRISPR-Cas13-gRNAs designed using the bioinformatics pipeline effectively blocks viral replication and reduces viral titers in cells by >99.99%. We further demonstrate that AAV-CRISPR-Cas13-gRNAs prophylactically and therapeutically inhibited viral replication in infected mouse tissues and prevented death in a lethally challenged EV-A71-infected mouse model. Interpretation: Our results show that the bioinformatics pipeline designs efficient CRISPR-Cas13 gRNAs for direct viral RNA targeting to reduce viral loads. Additionally, this new antiviral AAV-CRISPR-Cas13 modality represents an effective direct-acting prophylactic and therapeutic agent against lethal RNA viral infections. Funding: Agency for Science, Technology and Research (A∗STAR) Assured Research Budget, A∗STAR Central Research Fund UIBR SC18/21-1089UI, A∗STAR Industrial Alignment Fund Pre-Positioning (IAF-PP) grant H17/01/a0/012, MOE Tier 2 2017 (MOE2017-T2-1-078; MOE-T2EP30221-0005), and NUHSRO/2020/050/RO5+5/NUHS-COVID/4.

In Civil Engineering field, the compressive strength of concrete is a key parameter to design concrete structures and evaluate existing structures. Conventionally the measurement of the strength requires a considerable amount of time (∼28 days) and cost. Thus, this paper comprehensively reviews the literature on strength prediction models focusing on the prediction mechanism and its prediction precision. The literature demonstrates that various techniques including mathematics and statistics, analytical, numerical, computational, homogenization and multi-scale model have been employed to develop a model. An analytical model which simply correlates compressive strength and strength influencing factors was first introduced based on a statistical analysis of experimental data and the ideology of concrete technology. With the advancement of concrete technology, those analytical models fail to account for the complexity of strength affecting factors and compute less accurate results. Although Machine Learning (ML) techniques have proven superior accuracy for estimating the mixture proportions and mechanical properties of novel concrete with complex cementitious material, the prediction mechanism is being ‘black box’ which limits its wide application. Since the microstructure of hydrated cement paste was identified as a strength controlling factor in concrete, several models have been developed simulating the hydration of cementitious materials and thus bridging between nano and macro properties such as compressive strength and young’s modulus of concrete. Even though those microstructural models give comparable results with experimental data, various assumptions and hypotheses were considered during the model development. In addition, some of the models could not directly correlate the macro properties of concrete. The review presented in this paper is strong evidence of the need for a powerful model which realistically predicts the mechanical properties of concrete incorporating fundamental physics and chemistry, thermodynamic consideration, bonding and packing arrangement between particles.

Abstract Interoception, the sense of the internal physiological state of the body, theoretically underpins aspects of self-representation. Experimental studies link feelings of body ownership to interoceptive perception, yet few studies have tested for association between the sense of agency and interoceptive processing. Here, we combined an intentional binding paradigm with cardiac measures of interoceptive processing (behavioural performance on a heartbeat discrimination task, and effects of timing within the cardiac cycle) in twenty-six non-clinical participants as an exploratory study. We found performance accuracy on the heartbeat discrimination task correlated positively with the intentional binding effect, an index of sense of agency (β = 0.832, p = 0.005), even after controlling for effects of age, sex, educational level, heart rate, heart rate variability and time accuracy. The intentional binding effect was enhanced during cardiac systole (compared to diastole) in individuals with greater heartbeat discrimination accuracy (β = 0.640, p = 0.047). These findings support the proposal that interoception contributes to mechanisms underlying the emergence of sense of agency.

Globally, higher education institutions are increasingly digitising their operations. A bustling and expanding ecosystem of digital platforms in higher education includes online teaching and research, decision-making using learning and business analytics, and building "smart" campuses. Universities do not digitalise on their own but depend on proprietary digital platforms. This study focuses on how digitalisation impacts higher education institutes in Sri Lanka. This study used a methodology based on a qualitative survey, and the research used personal interviews to collect the required data. The research findings disclosed that although all stakeholders within the higher education institutes had to adapt to forced digitalisation, most were not ready to accept it as the main element defining current-day higher education. Higher education institutes, students, and teachers are the mainly affected parties in the forced digitalisation because of Covid-19. The main factors influencing these parties were inadequate digital literacy, poor financial capabilities, and lack of basic requirements for a digitalised learning environment. However, even with minimum resources, learning is underway in almost all higher education institutes, but it resulted in a digital divide, primarily impacting students and their learning abilities.

Purpose: Values and emotions conveyed via stories may show the contrasts and similarities between people's life experiences. Personal experiences must be shared to be understood, which may aid in forming connections and support networks. Design/Method/Approach (only for empirical papers): This study used a secondary research strategy. Findings: Throughout this study, the author makes the case that narrative is critical to effective organisational management and leadership. However, meaningful and creative in developing qualitative research in management, the growth of story methods has resulted in a lack of consistency in the field. Practical implications: Although the literature acknowledges the significant emotional and psychological advantages associated with using storytelling in studies, there has been no evidence of a link between improving human adaptability and using storytelling in research. Throughout this study, the author makes the case that narrative is critical to effective organisational management and leadership. Although essential and creative in developing qualitative management research, the growth of storey methods has resulted in a lack of consistency in the field. Originality/Value: This paper addresses the application of storytelling to organisation management and how storytelling is used as a tool for qualitative research. Research limitations: The research was primarily focused on secondary research and, therefore, could be limited to previous research findings.

Background and Aims: Various pulsed field ablation (PFA) systems are currently being developed. Recently, a novel CE-approved circular array PFA catheter (PulseSelect™ PFA System, Medtronic, Minneapolis, MN, USA) was introduced. Data on this commercially available system are sparse. The aim was to elucidate real-world data assessing the feasibility, safety, and acute efficacy of pulmonary vein isolation (PVI) and ablation beyond PVI with this novel ablation system. Methods: Consecutive patients with paroxysmal and persistent atrial fibrillation (AF) undergoing first-time ablation with the circular PFA catheter were enrolled in this study. In patients with persistent AF and left atrial (LA) enlargement (LA area > 20 cm2), additional left atrial roof ablation (LARA) was performed. Those with concomitant typical atrial flutter received adjunctive cavo-tricuspid isthmus (CTI) ablation. Results: A total of 100 AF patients were included (29% female, 50% persistent AF). Of these, 33 patients (33%) underwent adjunctive LARA, 1 patient (1%) received posterior wall isolation, and 6 patients (6%) required additional CTI ablation. The skin-to-skin procedural time averaged 66.3 ± 13.8 min, while the fluoroscopy time and dose area product were 13.7 ± 4.7 min and 6.8 ± 4.9 Gycm2, respectively. Acute PVI was achieved in 100% of pulmonary veins. A bidirectional conduction block of the LARA and CTI lines was confirmed in all patients, and no major adverse events were reported. Conclusions: These real-world data demonstrate the feasibility, safety, and acute efficacy of PVI and ablation beyond PVI using a novel circular array PFA catheter in patients with atrial fibrillation and flutter. The system can easily be integrated with standard PVI workflows. Further and larger studies are warranted to assess the clinical long-term effectiveness and safety of this PFA system. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia (SZ) is characterized by abnormalities in self-representation, including a disturbed sense of agency (SoA). The continuous processing of sensory information concerning the internal state of the body (interoception) is argued to be fundamental to neural representations of the self. We, therefore, tested if aberrant interoception underpins disturbances in SoA in SZ, focusing on cardiac interoceptive signaling. Methods: Forty-two SZ and 29 non-clinical participants (healthy controls; HC) performed an intentional binding task to measure SoA during concurrent heartbeat recording. The effect of cardiac interoceptive signals on SoA was measured by the difference in intentional binding effect during systole and diastole. This measure was standardized based on the overall intentional binding effect to control for non-cardiac factors, and then compared between SZ and HC. Results: Our study revealed a significant difference between SZ and HC groups, with opposite effects of cardiac systole on SoA. Specifically, cardiac systole disrupted SoA in SZ, contrasting with the enhanced SoA in HC. Across the SZ group, the extent to which SoA was disrupted by cardiac systole correlated significantly with a clinical proxy for symptom instability, namely the number of hospital admissions for hallucinations and delusions. Furthermore, the disruption was particularly observed in patients with severe hallucinations. Conclusions: This study revealed a disturbance in the impact of cardiac interoceptive signals on an implicit index of SoA in schizophrenia. This supports the notion that pathophysiological disruption of the central integration of interoceptive information increases vulnerability to disturbances in self-representation and the associated expression of schizophrenic symptoms. [ABSTRACT FROM AUTHOR]

Objective: Functional seizures (FS) look like epileptic seizures but are characterized by a lack of epileptic activity in the brain. Approximately one in five referrals to epilepsy clinics are diagnosed with this condition. FS are diagnosed by recording a seizure using video‐electroencephalography (EEG), from which an expert inspects the semiology and the EEG. However, this method can be expensive and inaccessible and can present significant patient burden. No single biomarker has been found to diagnose FS. However, the current limitations in FS diagnosis could be improved with machine learning to classify signal features extracted from EEG, thus providing a potentially very useful aid to clinicians. Methods: The current study has investigated the use of seizure‐free EEG signals with machine learning to identify subjects with FS from those with epilepsy. The dataset included interictal and preictal EEG recordings from 48 subjects with FS (mean age = 34.76 ± 10.55 years, 14 males) and 29 subjects with epilepsy (mean age = 38.95 ± 13.93 years, 18 males) from which various statistical, temporal, and spectral features from the five EEG frequency bands were extracted then analyzed with threshold accuracy, five machine learning classifiers, and two feature importance approaches. Results: The highest classification accuracy reported from thresholding was 60.67%. However, the temporal features were the best performing, with the highest balanced accuracy reported by the machine learning models: 95.71% with all frequency bands combined and a support vector machine classifier. Significance: Machine learning was much more effective than using individual features and could be a powerful aid in FS diagnosis. Furthermore, combining the frequency bands improved the accuracy of the classifiers in most cases, and the lowest performing EEG bands were consistently delta and gamma. [ABSTRACT FROM AUTHOR]

Background: Social media platforms have become increasingly influential channels for discussing various aspects of children's health, including dietary habits and food choices. This research explores the impact of social media on childhood dietary habits regarding the foods children consume by analyzing published findings about online videos and other social media platforms. Methods: From a pool of 9646 articles available on Google Scholar, Science Direct, Web of Science, and ProQuest, 25 were selected for inclusion in this systematic literature review after meeting the qualifying criteria. The screened papers contained clinical studies, cross-sectional studies, and editorials published in English. Results: A review of these articles revealed that individuals' communication with friends via social media significantly enhanced their comprehension of conversations related to weight management. The results of this research inform efforts to combat poor diets and promote overall well-being among children at an earlier stage when personal interactions are likely limited. To promote the healthy growth of children, it is essential that the videos they engage with offer them appropriate guidance on maintaining a nutritious diet. Ultimately, this research provides insights into how social media creates environments conducive to the well-being of children. Conclusions: As a result, social media can serve as a valuable resource to help mitigate the prevalence of obesity in this vulnerable population. [ABSTRACT FROM AUTHOR]