This study explored the relationships among teacher-child relationship (TCR), self-regulation (SR), social emotions (SE), and children’s learning of mathematics and vocabulary while considering the influence of gender and age. Two hundred seventy children (boys = 154, girls = 116) aged 3-6 years (Mage = 59.44 months) participated across 18 classes in three preschools. The results from multi-group structural equation modeling (SEM) revealed significant gender differences of TCR when predicting SR and SE. However, no significant gender differences were observed when SR predicted mathematics and vocabulary, or SE predicted these two. SR emerged as the most potent predictor of mathematics for all children. Furthermore, significant age variations were identified in TCR when predicting SR and SE and when SR and SE predicted mathematics and vocabulary. Finally, the research discusses implications for teachers, emphasizing the importance of tailored support for children of different genders and age groups to enhance TCR, SR, and SE.

The polyamide 6 powder was prepared by the liquid phase method, and then mixed with hexagonal boron nitride (h-BN) in a high-pressure homogenizer for micron-level mixing, and finally the composite material is obtained by hot pressing. The thermal conductivity of composites was as high as 1.73 W/(m•K). The results showed that the dispersion of h-BN in the matrix was well and there was no obvious agglomeration in the composite from the scanning electron microscope. Differential scanning calorimetry and X-ray diffraction results showed that h-BN affects the crystalline of polyamide 6 and the thermal stability of the composites was improved. The composite is expected to be used in high thermal conductivity functional plastics.

In the understanding of the molecular interaction between plants and their microbiome, a key point is to identify simplified models of the microbiome including relevant bacterial and fungal partners which could also be effective in plant growth promotion. Here, as proof-of-concept, we aim to identify the possible interactions between symbiotic nitrogen-fixing rhizobia and soil fungi (Trichoderma spp.), hence shed light on synergistic roles rhizospheric fungi could have in the symbiotic nitrogen fixation with host plants. We selected 4 strains of the model rhizobium Sinorhizobium meliloti and 4 Trichoderma species (T. velutinum, T. tomentosum, T. gamsii and T. harzianum). In an experimental scheme of 4 x 4 strains x species combinations, we investigated the rhizobia physiological and transcriptomic responses elicited by fungal spent media, as well as spent media effects on rhizobia-host legume plant (alfalfa, Medicago sativa L.) symbiosis. Fungal spent media had large effects on rhizobia, specific for each fungal species and rhizobial strains combination, indicating a general rhizobia genotype x fungal genotype interaction. Differential expression of a high number of genes was shown in rhizobia strains. Moreover, changes in rhizobia exopolysaccharide and auxin production were identified in response to fungal spent media. Different rhizobium-fungus combinations were also shown to have synergistic effects on alfalfa symbiotic phenotypes. Our results provide a first insight into interactions involving nitrogen-fixing rhizobia and rhizospheric fungi, highlighting the panoply of genes and genotypic interactions (fungus, rhizobium, host plant) which may concur to plant symbiosis.

The extraction of sugarcane planting distribution provides a scientific basis and theoretical support for local sugarcane cultivation management and the prediction of sugarcane yield. Sugarcane predominantly grows in tropical and subtropical regions characterized by cloudy and rainy conditions. Optical satellite remote sensing imagery is greatly affected by cloud and rain interference. In contrast, synthetic aperture radar (SAR) data exhibit strong penetration capabilities, enabling effective imaging in overcast, rainy, and cloudy environments. Focusing on Fusui County, Guangxi Province, China, this research utilizes Sentinel-1 radar data and integrates the phenological features of sugarcane growth. A sugarcane planting distribution extraction model is constructed using a random forest classifier. The results demonstrate that the phenological feature approach based on temporal radar scattering characteristics achieves superior performance in sugarcane identification and extraction. The overall accuracy surpasses 92.18%, with a Kappa coefficient of 0.89. This method exhibits a 4.95% accuracy improvement compared to single-period radar scattering feature methods. Therefore, this radar-based method for extracting sugarcane planting distribution can effectively and accurately extract sugarcane cultivation patterns in regions with complex cloud and rain conditions, such as Guangxi Province. It also serves as a methodological reference for extracting crop planting distributions in cloudy and rainy areas.

The opening of habitats associated with the emergence of C4 grasslands during the Neogene has had a massive influence on the evolution of plant and animal communities. Strikingly, the impacts of grassland expansion on species diversification in Africa, where the largest surface of grasslands and savannas in the world is located, are not well understood. To explore the impact of habitat opening, we investigate the evolution of noctuid stemborers, a group of moths mostly associated with open habitats, and whose diversity is centered in the Afrotropics. We generate a dated molecular phylogeny for ca. 80% of the known stemborer species and assess the role of habitat opening on the evolutionary trajectory of the group through a combination of parametric historical biogeography, ancestral character state estimation, life history traits and habitat-dependent diversification analyses. Our results support an origin of stemborers in Southern and East Africa ca. 20 million years ago (Ma), with range expansions linked to the increased availability of open habitats to act as dispersal corridors, and closed habitats acting as potent barriers to dispersal. Early specialization on open habitats was maintained over time, with shifts towards closed habitats being rare and invariably unidirectional. Analyses of life history traits showed that habitat changes involved specific features likely associated with grassland adaptations, such as variations in larval behavior and color. We compare these findings to those previously inferred for an Afrotropical butterfly group that diversified roughly in parallel with the stemborers but distributed predominantly in closed habitats. Remarkably, these two groups show nearly opposite responses in relation to habitat specialization, whether in terms of biogeographical patterns, or in terms of rates of transition between open and closed habitats. We conclude that habitat opening played a major role in the diversification of Afrotropical lineages through dispersal and adaptation linked to habitat shifts.

Background: Despite cardiovascular benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1RA) in patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD), their utilization remains low globally. This study aimed to evaluate the utilization of SGLT2i and GLP1RA in patients with T2DM and ASCVD, as well as the factors associated with medications in South Korea. Methods: This retrospective study was conducted from 2015 to 2020, using National Patient Sample claims data. The study population included adult patients with confirmed T2DM and ASCVD diagnosed between March 1 and October 31 each year. Demographic and clinical characteristics, and influencing factors were investigated. Results: Among 57,576 study participants, SGLT2i use increased from 1.2 % to 10.51 % during the study period, whereas GLP1RA use increased slightly from 0 % to 1.17 %. Older age, comorbid chronic kidney disease, concurrent use of dipeptidyl peptidase 4 inhibitors (DPP4i), and prescriptions from specific physician specialties negatively influenced SGLT2i use. Conversely, comorbid dyslipidemia, heart failure, concurrent use of sulfonylurea (SU), and prescriptions from cardiologists positively influenced SGLT2i use. For GLP1RA, older age, concurrent DPP4i use, and specific physician specialty were negative factors, whereas female sex, dyslipidemia, insulin, and SU use were positive factors. Conclusions: Despite increasing utilization, 88.35 % of eligible patients remained untreated with SGLT2i and GLP1RA as of 2020. This study highlights the disparities in utilization based on patient characteristics and physician specialties, emphasizing the need to remove barriers and enhance clinical benefits for high-risk patients.

Case report

Title: Low attenuation areas in necrotizing soft tissue infectionAuthors: Masanori Kawataki MD1, Yuta Oda MD2

Global land use land cover (LULC) maps are essential for monitoring forest dynamics and are a useful tool for any spatial planner. An increasing number of institutes are interested in producing such maps, especially with freely available high-resolution imagery and the emergence of new classification techniques. However, these maps should be submitted to an accuracy assessment for more accurate and effective use at the regional, national, and local scales. In this study, two products, the European Space Agency World Cover 2020 (ESA WC2020) and Sentinel-2 10 m Land Use/Land Cover Time Series (ESRI LC2020), were subjected to an accuracy assessment at the local scale, particularly in Talassemtane National Park (TNP). The results showed an overall accuracy of 56.90 % for the ESA product and 83.56% for the ESRI product. Forest cover is the most accurate land cover class for both products. In addition, area-based accuracy was used to adjust each class’s area and evaluate uncertainty. Finally, spatial agreement between the two products was achieved using change detection analysis, which showed a result of 70% at the local level. This work will be used in studies in the TNP area to distinguish between forest and non-forest land, particularly to monitor deforestation.

A document by mohammad hasan namazi. Click on the document to view its contents.

This article investigates the challenges of stabilizing Cable Suspended Parallel Robots (CSPRs) when dealing with uncertainties in models and external disturbances. It presents a novel Robust Adaptive Fractional-Order Sliding Mode Controller (RAFOSMC) designed specifically to handle uncertain nonlinear functional upper bounds that define disturbances and uncertainties. The approach employs stable adaptive laws to determine the unknown coefficients within the perturbation functional upper bounds. Analysis demonstrates that the Fractional-Order Sliding Mode Controller (FOSMC) surpasses traditional Integer-Order Sliding Mode Controllers (IOSMC). FOSMC exhibits advantages such as decreased chattering, swifter convergence toward the intended trajectory during initial movement, and eventual finite-time convergence to the fractional sliding surface. The study also proposes an innovative approximation for the sign function to further minimize chattering. Additionally, for situations where cable states are unavailable, the study introduces a nonlinear observer capable of estimating both cable position and model perturbations. Simulation results and comparisons with recent research support the efficacy of the proposed approaches.

Central apneas are a prevalent yet complex phenomenon, particularly among children. This retrospective study, conducted over a decade (from 2012 to 2022), analyzed central apneas in a cohort of 612 pediatric patients who underwent ventilation at the Sleep Medicine and Long-Term Ventilation Unit of the Bambino Gesù Children’s Hospital in Rome, Italy. Among this group, 67 patients met the inclusion criteria for central apneas. Central apneas often arise within the context of various underlying pathologies, including neurological disorders, genetic syndromes, and brain tumors. We categorized patients into three main groups including patients with “exclusively central apneas”, “predominantly central apneas”, and “predominantly obstructive apneas”. Ventilation modes were diverse, with pressure-controlled ventilation and pressure support being commonly used, reflecting the individualized nature of therapy. The choice of ventilation mode has been influenced by the underlying diagnosis and the severity of central apneas, with pressure support ventilation being the most frequently employed mode. Continuous Positive Airway Pressure was also employed in select cases. A statistically significant reduction (p<0.05) in mean cAHI was observed in patients with multimalformation syndromes, hypoxic-ischemic encephalopathy and Prader-Willi Syndrome. The reduction in mean cAHI was not statistically significant in the case of patients with brain tumors. While non-invasive ventilation was commonly used, invasive mechanical ventilation was selectively employed in more severe cases. The study highlights the need for personalized therapeutic strategies when managing central apneas in pediatric patients.

During the Stelmor air-cooling process, the temperature distribution has a significant impact on the wire loops’ final mechanical properties. The temperature distribution during air-cooling process is accurately solved by establishing three-dimensional model and numerical simulation. The heat transfer coefficient at the high dense region is much smaller than that of wire loops at the low dense region, and changes periodically over time, according to a Computational Fluid Dynamics (CFD) simulation method. It is also found that the heat transfer coefficient on the cross section of the wire loop is very different, with a difference of 70-100 Wm-2K-1. Finally, the finite difference method is used to calculate the mathematical model of the temperature distribution during the Stelmor air-cooling process. Comparing the results with the measurement data, the simulation results and measurement data match up well.

A document by Tahseen Al-kinani. Click on the document to view its contents.

Objective: To outline what is commonly understood, perceived and followed at individual institutions across the country on the subject of Post-Infectious Bronchiolitis Obliterans(PIBO) Methods: A 64-item web-based questionnaire with three sections addressing key domains in PIBO was employed. The questionnaire assessed knowledge points, attitudes and practice essentials which were consolidated and analysed. Results: The questionnaire was completed by 40 paediatricians/sub-specialists across 15 cities in India, and 88% of them were paediatric pulmonologists. The knowledge about disease process, clinical presentation, diagnostic modalities and treatment options were consistent with established literature. The prognosis was thought to be favourable by 75% respondents. Considerable heterogenicity was noted in the choice of first-line drugs, their doses, durations and combinations. Similarly, the time of the institution of second-line medication and drug of choice exhibited discrepancies. Conclusions There is a sizeable ambiguity in treatment practices concerning PIBO. This uncertainty calls for a review and consensus among Indian practitioners.

Objective: To analyze the clinical manifestations, imaging features, and treatment of Mycoplasma pneumoniae pneumonia with pulmonary venous thrombosis (PVT) in children and to improve the understanding of PVT among clinicians. Methods: We retrospectively analyzed a case of refractory mycoplasma pneumoniae pneumonia (RMPP) with PVT and reviewed the related literature. We also summarized the clinical features of the disease and our experience in diagnosing and treating the patient. Results: Our case is a 5-year-old female who was admitted to the hospital for fever and cough that was persistent for ten days before admission. Chest CT of the child showed pneumonia, atelectasis, pleural effusion, and pericardial effusion. After treatment with anti-infection, anti-inflammatory, and immunomodulatory medications, the symptoms of the child improved. Since the chest CT of the child showed atelectasis of the lung, we performed bronchoscopy. Bloody sputum was observed in the trachea, right main bronchus, and the lower bronchioles. Local hemostatic and systemic hemostatic agents were given for five days; however, bloody sputum was still observed during bronchoscopy. Finally, pulmonary vein and left atrium thrombosis were confirmed through chest CTA examination. Thrombi disappeared after anticoagulant therapy with low molecular weight heparin (LMWH) and warfarin, and there was no discomfort in the follow-up for two years. Conclusion: PTV may occur after mycoplasma pneumoniae infection. Early diagnosis and treatment are very important for patient prognosis.

The Internet of Things (IoT) is a new well-structured emerging technology with communication of smart devices using the 5G technology, infrastructures of roads, vehicles, smart cities, traffic systems and user applications. The IoT applications facilitate providing prompt emergency responses, and improved quality of vehicles, and road services, with cost-effective activities in the intelligent transportation systems. According to the growth of 5G technology and complex communications between smart devices and intelligent vehicles, Federated Learning is applied to support privacy and security factors in safety-critical transportation systems using innovative prediction methods in Internet of Vehicle (IoV) environments. Therefore, Federated Learning (FL) approaches can support safety, privacy and security for the sensitive personal information of users and critical aspects of vehicles in intelligent transportation systems and IoV. This comprehensive review paper delves into the innovative integration of blockchain technology with federated learning and the dynamic domain of IoV. It extensively analyzes the primary concepts, methodologies, and challenges associated with the deployment of FL in IoV. This study categorically examines three main types of federated learning approaches vertical, horizontal, and decentralized each tailored to specific IoV communication scenarios like Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Cloud (V2C). The study emphasizes various applications of FL, including cyber-attack detection, data sharing, traffic prediction, and privacy preservation based on critical Quality of Service (QoS) factors. Finally, some main challenges and new open issues are discussed and assessed for federated machine learning approaches in the IoV.

Recombinant adeno-associated virus (rAAV) is a commonly used in vivo gene therapy vector because of its non-pathogenicity, long-term transgene expression, broad tropism, and ability to transduce both dividing and non-dividing cells. However, rAAV vector production via transient transfection of mammalian cells typically yields a low fraction of filled-to-total capsids (~1–30% of total capsids produced). Analysis of our previously developed mechanistic model for rAAV2/5 production attributed these low fill fractions to a poorly coordinated timeline between capsid synthesis and viral DNA replication and the repression of later phase capsid formation by Rep proteins. Here, we extend the model by quantifying the expression dynamics of total Rep proteins and their influence on the key steps of rAAV2/5 production using a multiple dosing transfection of human embryonic kidney 293 (HEK293) cells. We report that the availability of pre-formed empty capsids and viral DNA copies per cell are not limiting to the capsid filling reaction. However, optimal expression of Rep proteins (< 240 ± 13 ag per cell) enables enrichment of the filled capsid population (> 12% of total capsids/cell) upstream. Our analysis suggests increased enrichment of filled capsids via regulating the expression of Rep proteins is possible but at the expense of per cell capsid titer in a triple plasmid transfection. Our study reveals an intrinsic limitation of scaling rAAV2/5 vector genome (vg) production and underscores the need for approaches that allow for regulating the expression of Rep proteins to maximize vg titer per cell upstream.

Introduction The performance of a rapid test was evaluated against two ELISAs as a potentially useful tool to determine exposure to SARS-CoV-2 in low resource settings. A serosurvey was conducted in Kibera informal settlement, Nairobi, Kenya, where low numbers of COVID-19 were recorded during the pandemic. Materials and methods A cross-sectional study was performed in 10 of 14 villages in Kibera informal settlement, Kenya’s largest slum community, in August 2021, before general vaccine roll-out. Participants were age one year and above with no symptoms of COVID-19. Capillary blood samples were tested using the Standard Q COVID-19 IgM/IgG Combo rapid test, Platelia SARS-CoV-2 Total Ab (IgM/IgG/IgA) Assay, and Wantai Total Ab (IgM/IgG/IgA) ELISA for SARS-CoV-2 which served as the reference test. Results Samples were obtained from 438 participants; in 72 samples blood was insufficient for the Platelia ELISA. Specificity of the rapid test and Platelia ELISA were similar (>93%) but sensitivity was low (rapid test 61.3%; Platelia ELISA 83.4%). The Wantai ELISA showed greater positivity (82.6%) than the rapid test (51.8%) and Platelia ELISA (69.7%). Conclusions The Wantai ELISA showed superior performance in this serosurvey. Point-of-care tests for convenient screening for SARS-CoV-2 exposure for surveillance studies need to be developed.

The integration of electric motors into various industrial and automotive applications emphasizes the critical necessity for reliable performance and operational efficiency. The advent of advanced digital technologies offers opportunities for predictive maintenance strategies. Digital Twins (DTs), mathematical models simulating a system's physical behavior in real-time, present a transformative approach to enhance real-time monitoring of critical quantities, which is imperative to improve operational efficiency and minimize downtime. In this paper, we explore the feasibility and efficacy of deploying real-time physics-based DTs for condition monitoring in electric motor applications. Particularly, we focus on employing on-the-edge DTs, implemented on low-power onboard microprocessors, ensuring continuous communication with the physical asset for reliable real-time monitoring. The study applies DT technology to a high-voltage high-density Electric Vehicle (EV) motor, assessing its predictive capabilities in a real-world scenario. Results showcase the potential of DTs in revolutionizing condition monitoring, thereby meeting the evolving operational and maintenance requirements of contemporary electric motor systems.

Objective: This study was carried out to develop an instrument to measure the emotional well-being of mothers in line with the Deck-Chair theory of Jean Ball. Design: Scale development and psychometric testing study. Setting: Turkey Population or Sample: A total of 398 postpartum women were included. Methods: MEWBS was administered to postpartum women being prepared for discharge (n=398). Factor analyses were carried out to determine the construct validity of the scale. Cronbach’s alpha coefficient was used to assess the reliability of the scale. Main Outcome Measures: MEWBS is a valid and reliable scale. Results: KMO value for EFA was found to be 0.806. As a result of the factor analysis that was carried out with the varimax orthogonal rotation technique, three factors explaining 51.825% of the total variance in the measured characteristic (Healthcare and Education, Social Support, and Mother’s Personality and Experiences) were identified. The internal consistency coefficient of the scale revealed that it was highly reliable (Cronbach’s alpha=0.860). It was determined that the scale did not have response bias (Hotelling’s T 2=397.260, p=0.000), and its factors were additive (non-additivity: 0.000). Conclusion: The validity and reliability test results of MEWBS demonstrated that it is a valid and reliable measurement instrument to assess the emotional well-being of postpartum mothers being prepared for discharge. MEWBS can guide healthcare professionals in identifying the emotional well-being of mothers in line with Jean Ball’s deck-chair theory and providing care accordingly. Therefore, healthcare professionals are advised to use MEWBS in their routine practices and assessments of mothers.

Title: Lifestyle Interventions Can Work with Super-Super Obese Patient BMI of 90.5 kg/m2: Case ReportGhadeer Al Ghareeb1, Duoaa Abdoh1, Mustafa Kuffy2, Ayman Afify3.1 Preventive Medicine Consultant, Fellows in Lifestyle Medicine Program, Prince Sultan Military Medical City, Riyadh, Saudi Arabia.2 Consultant Occupational Medicine, Prince Sultan Military Medical City, Riyadh, Saudi Arabia.3 Family Medicine Consultant, Prince Sultan Military Medical City, Riyadh, Saudi Arabia.Key words: Obesity, Weight Loss, Lifestyle, Primary Health Care, Body Mass Index, Liraglutide.Abstract: patients with super-super obesity represent challenges for health care professionals due to high failure rate, morbidity and mortality. This is a report of successful case of a 38-year-old female with a body mass index (BMI) of 90.5 kg/m2 underwent lifestyle modification as initial management approach.

Fake news classification emerged as an exciting topic for machine learning and artificial intelligence researchers. Most of the existing literature on fake news detection is based on the English language. Hence, it needs more usability. Fake news detection in low-resource scare languages is still challenging due to the absence of large annotated datasets and tools. In this work, we propose a large-scale Indian news dataset for the Hindi language. This dataset is constructed by scraping different reliable fact-checking websites. The LDA approach is adopted to assign the category to news statements. Various machine-learning and transfer learning approaches are applied to verify the authenticity of the dataset. Ensemble learning is also applied based on the low false-positive rate of machine-learning classifiers. A multi-modal approach is adopted by combining LSTM with VGG-16 and VGG-19 classifiers. LSTM is used for textual features, while VGG-16 and VGG-19 are applied for image analysis. Our proposed dataset has achieved satisfactory performance.

Objective: We aim to assess which variables are associated with recruitment failure of RCTs, leading to an extension of the study period.. Design: Nationwide cohort study. Setting: A cohort of RCTs supported by the trial centre of the Dutch Consortium of Obstetrics and Gynaecology. Population: We included 83 RCTs that recruited patients between March 1 st 2003 and December 1 st 2023. Main outcome measures: Primary outcome was recruitment target not achieved within six months after the pre-planned recruitment period. Secondary outcomes were recruitment target not achieved within an extension period of at least twelve months and premature termination of the trial. Results: In total, 46 of 83 RCTs (55%) did not achieve their targeted recruitment within the pre-planned study period with a maximal extension period of 6 months. The most relevant indicators for recruitment failure in multivariable risk prediction modelling were presence of a no-treatment arm, a compensation fee of less than 200 euros per included patient, funding of less than 350.000 euros, while a preceding pilot study lowered this risk. Conclusions: We identified that the presence of a no-treatment arm, low funding and a low compensation fee per included patient were the most relevant risk factors for recruitment failure within the pre-planned period, while a preceding pilot study lowered this risk. Awareness of these indicators is important when designing future studies.