bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical response of masonry structure strengthened with ultra-high performance concrete (UHPC): a comparative analysis for different strengthening tactics
Authors: Jiang Zhimei , Yang Jun , Su Hao
Published: October 2023

Rehabilitation and strengthening of existing masonry structures can improve their safety, prolong life and save economic costs. In this study, a total of eighteen masonry column specimens strengthened by ultra-high performance concrete (UHPC) were fabricated and tested in compression. The effects of strengthening method, strengthening thickness and loading eccentricity were investigated. The failure mode, bearing capacity, strain, ductility, and energy dissipation were discussed in before and after strengthening to evaluate the UHPC strengthening effectiveness. A three-dimensional numerical model established using finite element analysis (FEA) was validated with the experimental results. Results indicated that the brittle failure of masonry columns in compression could be significantly avoided using UHPC strengthening. Among three methods of strengthening, hoop strengthening was the most effective in increasing the ultimate load, ductility, and dissipated energy of masonry columns by 185.81%, 49.09%, and 297.12%, respectively. With the strengthening thickness increased from 0 to 20 and 30 mm, the ultimate bearing capacity of masonry columns was respectively increased by 29.17% and 117.26%, while the corresponding lateral displacement was decreased by 32.44% and 37.24%, respectively. The horizontal buckling of masonry columns can be relieved by UHPC, and the increase in eccentricity did not weaken the contribution of UHPC in strengthened masonry columns. The numerical results were in good agreement with the test results, with errors below 7.6%.
Exploring microbial diversity responses in agricultural fields: a comparative analysis under pesticide stress and non-stress conditions
Authors: Gangola Saurabh , Joshi Samiksha , Bhandari Geeta , Pant Garima , Sharma Anita , Perveen Kahkashan , Bukhari Najat A. , Rani Ranjana
Published: October 2023

Exposure to pesticides changes the microbial community structure in contaminated agricultural fields. To analyze the changes in the native microbial composition qRT-PCR, a metagenomic study was conducted. The qRT-PCR results exhibited that the uncontaminated soil has a higher copy number of 16S rDNA relative to the soil contaminated with pesticide. Metagenome analysis interprets that uncontaminated soil is enriched with proteobacteria in comparison with pesticide-contaminated soil. However, the presence of Actinobacteria, Firmicutes, and Bacteroides was found to be dominant in the pesticide-spiked soil. Additionally, the presence of new phyla such as Chloroflexi, Planctomycetes, and Verrucomicrobia was noted in the pesticide-spiked soil, while Acidobacteria and Crenarchaeota were observed to be extinct. These findings highlight that exposure to pesticides on soil significantly impacts the biological composition of the soil. The abundance of microbial composition under pesticide stress could be of better use for the treatment of biodegradation and bioremediation of pesticides in contaminated environments.
Rapid detection of Mucorales based on recombinase polymerase amplification and real-time PCR
Authors: Xu Rui , Li Dingchen , Zhao Jingya , Zhong Hanying , Chen Hong , Jia Yajing , Chen Fangyan , Han Li
Published: October 2023

Mucormycosis, an invasive fungal disease with severe consequences, poses a significant threat to immunocompromised individuals. However, the timely and accurate identification of Mucorales infection continues to present difficulties. In this study, novel detection techniques utilizing recombinase polymerase amplification (RPA) and quantitative real-time polymerase chain reaction (qPCR) were developed, specifically targeting the mitochondrial rnl gene, in order to address this challenge. The specificity of the RPA and qPCR assay was assessed by adding genomic DNAs extracted from 14 non-targeted strains, as well as human and mouse blood. No false-positive results were observed. Additionally, genomic DNAs from 13 species in five genera of order Mucorales were tested and yielded positive results in both methods. To further evaluate the sensitivity of the assays, DNAs from Rhizopus oryzae, Mucor racemosus, Absidia glauca, Rhizomucor miehei, and Cunninghamella bertholletiae were utilized, with concentrations ranging from 1 ng/μL to 1 fg/μL. The limit of detection (LoD) for the RPA assay was determined to be 1 pg., with the exception of Rhizomucor miehei which had a LoD of 1 ng. The LoD for the qPCR assay varied between 10 fg and 1 pg., depending on the specific species being tested. Sensitivity analysis conducted on simulated clinical samples revealed that the LoD for RPA and qPCR assays were capable of detecting DNA extracted from 103 and 101 colony forming units (CFU) conidia in 200 μL of blood and serum, respectively. Consequently, the real-time RPA and qPCR assays developed in this study exhibited favorable sensitivity and specificity for the diagnosis of mucormycosis.
Tools for classification of growing/non-growing bacterial colonies using laser speckle imaging
Authors: Balmages Ilya , Liepins Janis , Zolins Stivens , Bliznuks Dmitrijs , Broks Renars , Lihacova Ilze , Lihachev Alexey
Published: October 2023

Prior research has indicated the feasibility of assessing growth—associated activity in bacterial colonies through the application of laser speckle imaging techniques. A subpixel correlation method was employed to identify variations in sequential laser speckle images, thereby facilitating the visualization of specific zones indicative of microbial growth within the colony. Such differentiation between active (growing) and inactive (non-growing) bacterial colonies holds considerable implications for medical applications, like bacterial response to certain drugs or antibiotics. The present study substantiates the capability of laser speckle imaging to categorize bacterial colonies as growing or non-growing, a parameter which nonvisible in colonies when observed under white light illumination.
Diversity of antibiotic resistance genes in soils with four different fertilization treatments
Authors: Wang Zhuoran , Zhang Na , Li Chunming , Shao Liang
Published: October 2023

Although the enrichment of resistance genes in soil has been explored in recent years, there are still some key questions to be addressed regarding the variation of ARG composition in soil with different fertilization treatments, such as the core ARGs in soil after different fertilization treatments, the correlation between ARGs and bacterial taxa, etc. For soils after different fertilization treatments, the distribution and combination of ARG in three typical fertilization methods (organic fertilizer alone, chemical fertilizer alone, and conventional fertilizer) and non-fertilized soils were investigated in this study using high-throughput fluorescence quantitative PCR (HT-qPCR) technique. The application of organic fertilizers significantly increased the abundance and quantity of ARGs and their subtypes in the soil compared to the non-fertilized soil, where sul1 was the ARGs specific to organic fertilizers alone and in higher abundance. The conventional fertilizer application also showed significant enrichment of ARGs, which indicated that manure addition often had a more decisive effect on ARGs in soil than chemical fertilizers, and three bacteria, Pseudonocardia, Irregularibacter, and Castllaniella, were the key bacteria affecting ARG changes in soil after fertilization. In addition, nutrient factors and heavy metals also affect the distribution of ARGs in soil and are positively correlated. This paper reveals the possible reasons for the increase in the number of total soil ARGs and their relative abundance under different fertilization treatments, which has positive implications for controlling the transmission of ARGs through the soil-human pathway.
MRI BrainAGE demonstrates increased brain aging in systemic lupus erythematosus patients
Authors: Kuchcinski Grégory , Rumetshofer Theodor , Zervides Kristoffer A. , Lopes Renaud , Gautherot Morgan , Pruvo Jean-Pierre , Bengtsson Anders A. , Hansson Oskar , Jönsen Andreas , Sundgren Pia C. Maly
Published: October 2023

Introduction

Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease affecting multiple organs in the human body, including the central nervous system. Recently, an artificial intelligence method called BrainAGE (Brain Age Gap Estimation), defined as predicted age minus chronological age, has been developed to measure the deviation of brain aging from a healthy population using MRI. Our aim was to evaluate brain aging in SLE patients using a deep-learning BrainAGE model.

Methods

Seventy female patients with a clinical diagnosis of SLE and 24 healthy age-matched control females, were included in this post-hoc analysis of prospectively acquired data. All subjects had previously undergone a 3 T MRI acquisition, a neuropsychological evaluation and a measurement of neurofilament light protein in plasma (NfL). A BrainAGE model with a 3D convolutional neural network architecture, pre-trained on the 3D-T1 images of 1,295 healthy female subjects to predict their chronological age, was applied on the images of SLE patients and controls in order to compute the BrainAGE. SLE patients were divided into 2 groups according to the BrainAGE distribution (high vs. low BrainAGE).

Results

BrainAGE z-score was significantly higher in SLE patients than in controls (+0.6 [±1.1] vs. 0 [±1.0], p = 0.02). In SLE patients, high BrainAGE was associated with longer reaction times (p = 0.02), lower psychomotor speed (p = 0.001) and cognitive flexibility (p = 0.04), as well as with higher NfL after adjusting for age (p = 0.001).

Conclusion

Using a deep-learning BrainAGE model, we provide evidence of increased brain aging in SLE patients, which reflected neuronal damage and cognitive impairment.
Unraveling the parameters and biological mechanisms of CO2 laser therapy for acute pain relief
Authors: Wang Xianggang , Liu Jiaqi , Wang Zhonghan , Guo Chunming , Lan Hongjia , Feng Shibin , Liu He , Gao Xun , Zhang Dongming , Zhu Lintao , Jin Hui , Wang Jincheng
Published: October 2023

Acute pain-related pathology is a significant challenge in clinical practice, and the limitations of traditional pain-relief drugs have made it necessary to explore alternative approaches. Photobiomodulation (PBM) therapy using CO2 laser has emerged as a promising option. In this study, we aimed to identify the optimal parameters of CO2 laser irradiation for acute pain relief through in vivo and in vitro experiments. First, we validated the laser intensity used in this study through bone marrow mesenchymal stem cells (BMSCs) experiments to ensure it will not adversely affect stem cell viability and morphology. Then we conducted a detailed evaluation of the duty cycle and frequency of CO2 laser by the hot plate and formalin test. Results showed a duty cycle of 3% and a frequency of 25 kHz produced the best outcomes. Additionally, we investigated the potential mechanisms underlying the effects of CO2 laser by immunohistochemical staining, and found evidence to suggest that the opioid receptor may be involved in its analgesic effect. In conclusion, this study provides insights into the optimal parameters and underlying mechanisms of CO2 laser therapy for effective pain relief, thereby paving the way for future clinical applications.
The effect of the dietary approaches to stop hypertension diet on total antioxidant capacity, superoxide dismutase, catalase, and body composition in patients with non-alcoholic fatty liver disease: a randomized controlled trial
Authors: Zare Zahra , Hosseinzadeh Mahdieh , Sharuni Fatemeh , Rohani Fatemeh Sadat , Hojjat Hashem , Rahimpour Shahab , Madadizadeh Farzan , Zavar Reza Javad , Wong Alexei , Nadjarzadeh Azadeh
Published: October 2023

Aim

Non-alcoholic fatty liver disease (NAFLD) is a condition characterized by the accumulation of fat in the liver without excessive alcohol consumption. Lifestyle modifications, such as adopting a healthy diet, represent the standard treatment for NAFLD. However, the impact of the Dietary Approaches to Stop Hypertension (DASH) diet on oxidative stress biomarkers in patients with NAFLD remains unclear. Therefore, this study aimed to determine the effect of the DASH diet on total antioxidant capacity (TAC), catalase (CAT), superoxide dismutase (SOD) levels, and body composition in overweight and obese patients with NAFLD.

Methods

A total of 70 overweight and obese patients aged 1870 years were randomly assigned to either the intervention (DASH diet, n = 35) or the control group (control diet, n = 35) for 12 weeks, with both groups following a calorie-restricted diet.

Results

The mean age of participants was 43.1 ± 8.1 years in the DASH group and 45.1 ± 8.6 years in the control group. At the end of the study, a significant difference was observed in the mean TAC and SOD levels between the two groups (p = 0.02). After adjusting for potential confounding factors, such as age, sex, diabetes, smoking, physical activity, and baseline values, the DASH diet maintained its significant effects on TAC and SOD compared to the control diet (p = 0.03). However, there were no significant differences in CAT levels between the two groups. Moreover, a significant reduction in visceral fat (p = 0.01) and a marginally significant decrease in BMI (p = 0.06) were observed in the DASH group compared to the control group after adjusting for potential confounders.

Conclusion

In conclusion, our study showed that following the DASH diet for 12 weeks in overweight and obese patients with NAFLD has beneficial effects on TAC, SOD, and visceral fat. These findings support the use of the DASH diet as a potential therapeutic intervention for the improvement of oxidative biomarkers in patients with NAFLD.

Clinical trial registration

www.irct.ir/, identifier IRCT20170117032026N3.
PCG-net: feature adaptive deep learning for automated head and neck organs-at-risk segmentation
Authors: Luan Shunyao , Wei Changchao , Ding Yi , Xue Xudong , Wei Wei , Yu Xiao , Wang Xiao , Ma Chi , Zhu Benpeng
Published: October 2023

Introduction

Radiation therapy is a common treatment option for Head and Neck Cancer (HNC), where the accurate segmentation of Head and Neck (HN) Organs-AtRisks (OARs) is critical for effective treatment planning. Manual labeling of HN OARs is time-consuming and subjective. Therefore, deep learning segmentation methods have been widely used. However, it is still a challenging task for HN OARs segmentation due to some small-sized OARs such as optic chiasm and optic nerve.

Methods

To address this challenge, we propose a parallel network architecture called PCG-Net, which incorporates both convolutional neural networks (CNN) and a Gate-Axial-Transformer (GAT) to effectively capture local information and global context. Additionally, we employ a cascade graph module (CGM) to enhance feature fusion through message-passing functions and information aggregation strategies. We conducted extensive experiments to evaluate the effectiveness of PCG-Net and its robustness in three different downstream tasks.

Results

The results show that PCG-Net outperforms other methods, improves the accuracy of HN OARs segmentation, which can potentially improve treatment planning for HNC patients.

Discussion

In summary, the PCG-Net model effectively establishes the dependency between local information and global context and employs CGM to enhance feature fusion for accurate segment HN OARs. The results demonstrate the superiority of PCGNet over other methods, making it a promising approach for HNC treatment planning.
Hepatitis B Virus and B-cell lymphoma: evidence, unmet need, clinical impact, and opportunities
Authors: Rosenberg Maya , Poluch Maria , Thomas Colin , Sindaco Paola , Khoo Alan , Porcu Pierluigi
Published: October 2023

Nearly a billion people worldwide are infected with the hepatitis B Virus (HBV) and about a third of them have chronic infection. HBV is an important cause of morbidity and mortality, including acute and chronic hepatitis and hepatocellular carcinoma (HCC). Screening and control of primary HBV infection through vaccination represent a major advance in global public health, but large sections of the world population, in both developed and underdeveloped countries, remain unscreened and unvaccinated. In addition to being a global cause of liver disease, an important role of HBV in lymphoma has also emerged. First, the high risk of HBV reactivation in previously infected patients receiving chemo-immunotherapy necessitates the systematic evaluation of HBV serological status in all non-Hodgkin’s lymphoma (NHL) cases and preemptive antiviral therapy for those who may have chronic or occult HBV infection. Second, HBV has been shown to infect lymphocytes, namely B-cells, and has been associated with a higher risk of developing B-cell lymphoma, most clearly in countries where HBV is endemic. While the risk of HBV reactivation with chemoimmunotherapy in NHL is well known, the role and the impact of HBV as a global lymphoma risk factor and potential oncogenic driver in B-cells are very poorly understood. Here, we review the clinical and scientific evidence supporting an association between HBV and B-cell lymphoma, with a particular focus on diffuse large B-cell lymphoma (DLBCL) and provide an overview of the estimated impact of HBV infection on the biology and clinical course of DLBCL. We also discuss ways to gain a better insight into the unmet need posed by HBV in lymphoma and whether assessing immune responses to HBV, measuring viral loads, and detecting the presence of HBV-encoded proteins in tumor tissue could be integrated into the molecular and clinical risk stratification of patients with DLBCL.
Importance of metabolic and immune profile as a prognostic indicator in patients with diabetic clear cell renal cell carcinoma
Authors: Cheng Xiangyu , Hou Yanlian
Published: October 2023

Background

ccRCC, also known as clear cell renal cell carcinoma, is a cancer that is highly metabolically active and has a strong connection with the immune system. The objective of this research was to investigate the correlation between pathways associated with metabolism, diabetes, immune infiltration, and their impact on the prognosis of ccRCC.

Method

We conducted an extensive examination utilizing ssGSEA, ESTIMATE algorithm, WGCNA, and GSVA for gene set enrichment analysis, gene co-expression network analysis, and gene set variation analysis. An established prognostic model, utilizing immune-related WGCNA findings, was evaluated for its association with clinical characteristics and the tumor microenvironment (TME).

Result

The ssGSEA effectively categorized ccRCC into groups based on low and high metabolism. Strong associations were observed between scores related to metabolism and immune scores, ESTIMATE scores, stromal scores, and gene expression related to HLA. The analysis conducted by WGCNA revealed a module called the ‘yellow module’ that exhibited a significant correlation with the infiltration of immune cells and the survival rates of patients. A risk model was developed, demonstrating reliable predictive performance for patient survival outcomes. The risk model also correlated significantly with immune scores and HLA-related gene expressions, suggesting potential immune evasion mechanisms. The analysis of mutations in TCGA data revealed the mutational patterns of ccRCC, and there was a significant correlation between the risk score and clinical characteristics. The GSVA analysis revealed a notable enrichment of pathways associated with cancer in patients at high risk. Finally, in order to evaluate the role of CX3CL1 in renal cell carcinoma cells, we then performed the cell proliferation assays. The results demonstrated that the over expression of CXCL1 could promote the cell proliferation ability in renal cell carcinoma cells.

Conclusion

Our findings provide a novel perspective on the interactions between diabetes, metabolic pathways, and the immune landscape in ccRCC. The predictive value of the prognostic model established in this research has the potential to guide the development of new therapeutic and prognostic approaches for patients with ccRCC.
Molecular targeted therapy for metastatic colorectal cancer: current and evolving approaches
Authors: Li Furong , Lin Yanping , Li Rong , Shen Xin , Xiang Mengying , Xiong Guangrui , Zhang Ke , Xia Tingrong , Guo Jiangyan , Miao Zhonghui , Liao Yedan , Zhang Xuan , Xie Lin
Published: October 2023

Colorectal cancer (CRC) represents 10% of all cancer types, making it the third leading cause of cancer-related deaths globally. Metastasis is the primary factor causing mortality in CRC patients. Approximately 22% of CRC-related deaths have metastasis present at diagnosis, with approximately 70% of these cases recurring. Recently, with the application of novel targeted drugs, targeted therapy has become the first-line option for individualized and comprehensive treatment of CRC. The management of these patients remains a significant medical challenge. The most prevalent targeted therapies for CRC in clinical practice focus on anti-vascular endothelial growth factor and its receptor, epidermal growth factor receptor (EGFR), and multi-target kinase inhibitors. In the wake of advancements in precision diagnosis and widespread adoption of second-generation sequencing (NGS) technology, rare targets such as BRAF V600E mutation, KRAS mutation, HER2 overexpression/amplification, and MSI-H/dMMR in metastatic colorectal cancer (mCRC) are increasingly being discovered. Simultaneously, new therapeutic drugs targeting these mutations are being actively investigated. This article reviews the progress in clinical research for developing targeted therapeutics for CRC, in light of advances in precision medicine and discovery of new molecular target drugs.
Pharmacogenomics in clinical trials: an overview
Authors: Nogueiras-Álvarez Rita
Published: October 2023

With the trend towards promoting personalised medicine (PM), the application of pharmacogenetics and pharmacogenomics (PGx) is of growing importance. For the purposes of clinical trials, the inclusion of PGx is an additional tool that should be considered for improving our knowledge about the effectiveness and safety of new drugs. A search of available clinical trials containing pharmacogenetic and PGx information was conducted on ClinicalTrials.gov. The results show there has been an increase in the number of trials containing PGx information since the 2000 s, with particular relevance in the areas of Oncology (28.43%) and Mental Health (10.66%). Most of the clinical trials focus on treatment as their primary purpose. In those clinical trials entries where the specific genes considered for study are detailed, the most frequently explored genes are CYP2D6 (especially in Mental Health and Pain), CYP2C9 (in Hematology), CYP2C19 (in Cardiology and Mental Health) and ABCB1 and CYP3A5 (particularly prominent in Transplantation and Cardiology), among others. Researchers and clinicans should be trained in pharmacogenetics and PGx in order to be able to make a proper interpretation of this data, contributing to better prescribing decisions and an improvement in patients’ care, which would lead to the performance of PM.
Application of homotopy perturbation method to solve a nonlinear mathematical model of depletion of forest resources
Authors: Buhe Eerdun , Rafiullah Muhammad , Jabeen Dure , Anjum Naveed
Published: October 2023

Reduction in forest resources due to increasing global warming and population growth is a critical situation the World faces today. As these reserves decrease, it alarms new challenges that require urgent attention. In this paper, we provide a semi-analytical solution to a nonlinear mathematical model that studies the depletion of forest resources due to population growth and its pressure. With the help of the homotopy perturbation method (HPM), we determine an approximate series solution with few perturbation terms, which is one of the essential power of the HPM method. We compare our semi-analytical results with numerical solutions obtained using the Runge-Kutta 4th-order (RK-4) method. Furthermore, we analyze the model’s behaviour and dynamics by changing the parametric coefficients that represent the depletion rate of forest resources and the growth rate of population pressure and present these findings using various graphs.
Evaluating relationships between seed morphological traits and seed dormancy in Chenopodium quinoa Willd.
Authors: McGinty Emma M. , Craine Evan B. , Miller Nathan D. , Ocana-Gallegos Cristina , Spalding Edgar P. , Murphy Kevin M. , Hauvermale Amber L.
Published: October 2023

Introduction

Quinoa is a high-value, nutritious crop that performs well in variable environments, marginal soils, and in diverse crop rotations. Quinoa’s many attributes make it an ideal crop for supporting human health in global communities and economies. To date, quinoa research has largely focused on traits in adult plants important for enhancing plant phenotypic plasticity, abiotic stress, disease resistance, and yield. Fewer studies have evaluated quinoa seed dormancy and suggest that most modern quinoa varieties have weak or no seed dormancy, and a narrow window of seed viability post-harvest. In other crops, diminished seed dormancy is a major risk factor for preharvest sprouting (PHS; germination on the panicle due to rain prior to harvest) and may also pose a similar risk for quinoa.

Methods

This study (1) developed a dormancy screening assay to characterize seed dormancy strength in a large collection of quinoa varieties, (2) investigated if morphological variables including seed coat color, seed coat thickness, seed shape including eccentricity which evaluates the roundness or flatness of a seed, and other agronomic traits like crude protein content and seed moisture, contribute to quinoa seed dormancy, and (3) evaluated the use of a phenetic modeling approach to explore relationships between seed morphology and seed dormancy.

Results

Dormancy screening indicated seed dormancy ranges in quinoa varieties from none to strong dormancy. Further, phenetic modeling approaches indicate that seed coat thickness and eccentricity are important morphological variables that impact quinoa seed dormancy strength.

Conclusions

While dormancy screening and phenetic modeling approaches do not provide a direct solution to preventing PHS in quinoa, they do provide new tools for identifying dormant varieties as well as morphological variables contributing to seed dormancy.
Peer victimization and children’s internet addiction in China: a moderated mediation model
Authors: Zhou Pingyan , Cai Jinping , Cui Jiaxin , Liu Jian , He Wenguang , Zhang Cai , Chen Fumei , Wang Zhe
Published: October 2023

Background

Peer victimization used to be considered as a crucial risk factor for children addicted to the internet. Whereas some victimized ones are function better than would be expected. Variability across individuals indicates that it is necessary to understand how children cope with being bullied and why they do not exhibit maladaptive outcomes.

Objective

We explored the underlying mechanisms by testing whether subjective well-being was a mediator between peer victimization and Internet addiction and whether the mediation effects conditioned on the levels of parent–child relationship (PCR).

Methods

Data were collected from 65, 868 elementary school students in China (Mage = 9.56 years, SD = 0.62, 54.0% male) using four questionnaires.

Results

We found that: (1) subjective well-being can partially mediate the relationship of the two variables; and (2) PCR can moderate direct path and second half of the intermediary process. These moderating effects were stronger for children with higher PCR vs. lower PCR, as a strong PCR can help children to deal with intense emotions and to access effective resources to obtain support.

Conclusion

This study deepens our understanding of how peer victimization leads to internet addiction, identifies a supportive PCR as a crucial factor that strengthens the resilience of child victims, and highlights the value of focusing on improving the relationship between parents and children in intervening internet addiction related to peer victimization.
Neuromyths and knowledge about intellectual giftedness in a highly educated multilingual country
Authors: Schmitt Anna , Wollschläger Rachel , Blanchette Sarrasin Jérémie , Masson Steve , Fischbach Antoine , Schiltz Christine
Published: October 2023

Introduction

Understanding brain functioning and intellectual giftedness can be challenging and give rise to various misconceptions. Nonetheless, there seems to be a widespread fascination and appetite for these subjects among the lay public and diverse professionals. The present study is the first to investigate general knowledge about the brain, neuromyths and knowledge about giftedness in a highly multilingual and educated country.

Methods

Starting from and extending two seminal studies on neuromyths, several novel statements on intellectual giftedness have been included in order to explore knowledge and misconceptions concerning giftedness. Our sample (N = 200) was composed of Luxembourgish education professionals, including students in educational science and cognitive psychology, thus allowing to analyze responses in general and according to training and professional profiles. Specifically, Group 1 consisted of teachers and futures teachers (n = 152). Group 2 consisted of other education professionals and psychology students (n = 48).

Results

Despite the size and the unbalanced distribution of the sample, our findings indicate a good level of general knowledge about the brain and learning (71.3% of correct responses in average) which does, however, not preclude the presence of the typically observed original neuromyths. Thus, we replicate the classical finding that misconceptions on Learning Styles (70% of error rate) and the Multiple Intelligence Theory (71.5% of error rate) are the most represented, both in (future and in-service) teachers and other education professionals. Moreover, the present sample also revealed a high presence of misconceptions on intellectual giftedness.

Discussion

Limitations and future directions are discussed.
Assessment of malaria prevention knowledge, attitude, and practice and associated factors among households living in rural malaria-endemic areas in the Afar Pastoral Region of Ethiopia
Authors: Addis Desalegne , Gebeyehu Wondmeneh Temesgen
Published: October 2023

Background

Malaria morbidity has reduced significantly in most regions of Ethiopia, but it is still a serious issue in the northeast, particularly in the Afar region.

Objective

The study aimed to evaluate household heads' knowledge, attitudes, and practices toward malaria prevention and its associated factors in rural Ada'ar woreda district in the Afar region.

Methods

A community-based cross-sectional study was conducted among 422 households living in Ada'ar woreda district. A systematic sampling technique was used to select households. A pre-tested, structured questionnaire was used to interview randomly selected adult household heads. Frequency and percentage were computed. Logistic regression was used to determine the association between independent and dependent variables. Statistical significance was considered to be a p-value <0.05.

Results

Nearly two-thirds (64.2%) of household heads had good knowledge of malaria prevention, and 46.9% had a positive attitude toward it. About 17.3 and 56.9% of study participants had good malaria prevention practices and good healthcare seeking behaviors, respectively. Illiterate (AOR = 2.62, 95% CI: 1.49–4.63) and low-income (AOR = 2.6, 95% CI: 1.2–5.6) participants were more likely to have poor knowledge of malaria prevention (malaria signs and symptoms, malaria transmissions, and malaria prevention methods). Married participants (AOR = 2.52, 95% CI: 1.02–6.29) and illiterates (AOR = 2.83, 95% CI: 1.69–4.73) had negative attitudes toward malaria prevention. Household heads with poor knowledge of malaria prevention had 85% higher rates of practicing poor malaria prevention methods (regular bed nets used; AOR = 1.85, 95% CI: 1.2–2.8). Young adults (18–25 years) were more likely to have poor healthcare seeking behaviors (AOR = 3.5, 95% CI: 1.73–7.1), while pastoralists had a lower likelihood (AOR = 0.46, 95% CI: 0.28–0.8).

Conclusion

Knowledge, attitude, and practices toward malaria prevention remain a problem in malaria-endemic rural areas of the Afar region of Ethiopia. There is a need for the implementation of interventions that will focus on increasing knowledge of malaria prevention and encouraging positive attitudes toward it, as well as promoting regular bed net usage and healthcare seeking behaviors.
Absence of abnormal vascular changes on prenatal imaging aids in differentiating simple uterine scar dehiscence from placenta accreta spectrum: a case series
Authors: Adu-Bredu Theophilus K. , Owusu Yaw Gyanteh , Owusu-Bempah Atta , Collins Sally L.
Published: October 2023

Accurate prenatal discrimination between a simple, non-adherent uterine scar dehiscence with an underlying placenta and the severe end of the placenta accreta spectrum is problematic as the two can appear similar on prenatal imaging. This may lead to the false diagnosis of placenta accreta spectrum resulting obstetric anxiety, overtreatment and potential iatrogenic morbidity. Despite potential similarities in the etiology, the manifestation and management of these two conditions is very different. The prenatal sonographic features of seven confirmed cases of simple uterine scar dehiscence with an underlying placenta previa were examined. The common sonographic features found for scar dehiscence was a thinned myometrium (<1 mm) overlying a generally homogenous placenta and a placental bulge. There was absence of lacunae and features of hypervascularity including bridging vessels. Our findings suggest accurate discrimination between a simple scar dehiscence with the placenta underlying it and placenta accreta spectrum can be made on prenatal ultrasound if the placenta is carefully examined for the vascular features unique to PAS.
Neural Network-Enhanced Fault Diagnosis of Robot Joints
Authors: Zhang Yifan , Zhu Quanmin
Published: October 2023

Industrial robots play an indispensable role in flexible production lines, and the faults caused by degradation of equipment, motors, mechanical system joints, and even task diversity affect the efficiency of production lines and product quality. Aiming to achieve high-precision multiple size of fault diagnosis of robotic arms, this study presents a back propagation (BP) multiclassification neural network-based method for robotic arm fault diagnosis by taking feature fusion of position, attitude and acceleration of UR10 robotic arm end-effector to establish the database for neural network training. The new algorithm achieves an accuracy above 95% for fault diagnosis of each joint, and a diagnostic accuracy of up to 0.1 degree. It should be noted that the fault diagnosis algorithm can detect faults effectively in time, while avoiding complex mathematical operations.
Interactive Effects of Inorganic–Organic Compounds on Passivation of Cadmium in Weakly Alkaline Soil
Authors: Tong Fei , Huang Qin , Liu Lizhu , Fan Guangping , Shi Gaoling , Lu Xin , Gao Yan
Published: October 2023

The availability of cadmium (Cd) in soils is an important factor affecting the safe production of crops. The application of certain soil amendments could reduce the soil Cd availability via the passivation of Cd. However, the passivation of Cd in alkaline soils is limited. Thus, different inorganic and organic amendments and their compound treatments were selected as passivators for reducing the Cd availability in a weakly alkaline farmland soil. The effects of different single and compound amendments on the soil pH and Cd availability, as well as the interactions between inorganic and organic components in immobilizing Cd, were evaluated. The results showed that the inorganic–organic compound amendments can considerably improve the Cd passivation efficiency in the weakly alkaline soil. Moreover, the inorganic and organic components in the compound amendments exerted different synergistic effects in Cd passivation. The manganese dioxide-based compound amendments showed the most remarkable synergistic effects, while the calcium–magnesium–phosphate fertilizer-based compound amendments displayed the weakest synergistic effects. The underlying mechanisms regarding the synergistic effects may be that the compound amendments enhanced the adsorption/specific adsorption, co-precipitation, and surface complexation of Cd in the alkaline soil. A more balanced recommendation for Cd immobilization in the weakly alkaline soil may be manganese dioxide-based compound amendments, given the synergistic effects and Cd immobilization capabilities of various compound materials. This study may provide a theoretical foundation for the passivation remediation of alkaline Cd-contaminated farmland soils by using inorganic–organic compound amendments.
Effects of Lyophilized Açaí (Euterpe oleracea) Supplementation on Oxidative Damage and Intestinal Histology in Juvenile Shrimp Penaeus vannamei Reared in Biofloc Systems
Authors: Colombo Grecica Mariana , Marreiro Gomes Robson Matheus , Muñoz Buitrago Sonia Astrid , Buitrago Ramírez Juan Rafael , de Sousa Araujo Alan Carvalho , Silva Oliveira Fernando Pablo , Pedrosa Virgínia Fonseca , Romano Luís Alberto , Tesser Marcelo , Wasielesky Wilson , Monserrat José María
Published: October 2023

The objective of this was to evaluate the ability of bioflocs to assimilate and transfer antioxidant compounds present in açaí Euterpe oleracea to juvenile Penaeus vannamei shrimp grown in a biofloc system. Juvenile shrimp were distributed into four treatment groups (control, 5, 20, and 80 mg açaí L−1), containing 31 shrimps/tank (90 L), and cultivated for 30 days. Every 24 h throughout the experimental period, the respective açaí concentrations were added directly to the cultivation water. The bioflocs and hepatopancreas lost their antioxidant capacity with increasing concentrations of açaí; however, lipid damage was mitigated after treatment with 20 mg of açaí L−1 (p < 0.05). The application of 20 mg açaí L−1 increased the mean height and area of the middle intestinal microvilli (p < 0.05). Mortality and protein and lipid damage in shrimp muscle increased with daily administration of 80 mg açaí L−1 (p < 0.05). It is concluded that the bioflocs were able to assimilate the antioxidants present in açaí and transfer them to the shrimp, and the administration of 20 mg açaí L−1 presented the best performance, demonstrating the possibility of its application in the cultivation of P. vannamei in a biofloc system.
Comparison of Oral Microbial Composition and Determinants Encoding Antimicrobial Resistance in Dogs and Their Owners
Authors: Šakarnytė Laura , Šiugždinienė Rita , Žymantienė Judita , Ruzauskas Modestas
Published: October 2023

Consolidated studies on animal, human, and environmental health have become very important for understanding emerging zoonotic diseases and the spread of antimicrobial resistance (AMR). The aim of this study was to analyse the oral microbiomes of healthy dogs and their owners, including determinants of AMR. Shotgun metagenomic sequencing detected 299 bacterial species in pets and their owners, from which 70 species were carried by dogs and 229 species by humans. Results demonstrated a unique microbial composition of dogs and their owners. At an order level, Bacteroidales were the most prevalent oral microbiota of dogs with significantly lower prevalence in their owners where Actinomycetales and Lactobacillales predominated. Porphyromonas and Corynebacterium were the most prevalent genera in dogs, whereas Streptococcus and Actinomyces were in animal owners. The resistances to macrolides, tetracyclines, lincosamides and Cfx family A class broad-spectrum β-lactamase were detected in both animal and human microbiomes. Resistance determinants to amphenicols, aminoglycosides, sulphonamides, and quaternary ammonium compounds were detected exceptionally in dogs. In conclusion, the study demonstrated different bacterial composition in oral microbiomes of healthy dogs without clinical signs of periodontal disease and their owners. Due to the low numbers of the samples tested, further investigations with an increased number of samples should be performed.
Implementation of the HHL Algorithm for Solving the Poisson Equation on Quantum Simulators
Authors: Daribayev Beimbet , Mukhanbet Aksultan , Imankulov Timur
Published: October 2023

The Poisson equation is a fundamental equation of mathematical physics that describes the potential distribution in static fields. Solving the Poisson equation on a grid is computationally intensive and can be challenging for large grids. In recent years, quantum computing has emerged as a potential approach to solving the Poisson equation more efficiently. This article uses quantum algorithms, particularly the Harrow–Hassidim–Lloyd (HHL) algorithm, to solve the 2D Poisson equation. This algorithm can solve systems of equations faster than classical algorithms when the matrix A is sparse. The main idea is to use a quantum algorithm to transform the state vector encoding the solution of a system of equations into a superposition of states corresponding to the significant components of this solution. This superposition is measured to obtain the solution of the system of equations. The article also presents the materials and methods used to solve the Poisson equation using the HHL algorithm and provides a quantum circuit diagram. The results demonstrate the low error rate of the quantum algorithm when solving the Poisson equation.
Online Machine Learning and Surrogate-Model-Based Optimization for Improved Production Processes Using a Cognitive Architecture
Authors: Hinterleitner Alexander , Schulz Richard , Hans Lukas , Subbotin Aleksandr , Barthel Nils , Pütz Noah , Rosellen Martin , Bartz-Beielstein Thomas , Geng Christoph , Priss Phillip
Published: October 2023

Cyber-Physical Systems (CPS) play an essential role in today’s production processes, leveraging Artificial Intelligence (AI) to enhance operations such as optimization, anomaly detection, and predictive maintenance. This article reviews a cognitive architecture for Artificial Intelligence, which has been developed to establish a standard framework for integrating AI solutions into existing production processes. Given that machines in these processes continuously generate large streams of data, Online Machine Learning (OML) is identified as a crucial extension to the existing architecture. To substantiate this claim, real-world experiments using a slitting machine are conducted, to compare the performance of OML to traditional Batch Machine Learning. The assessment of contemporary OML algorithms using a real production system is a fundamental innovation in this research. The evaluations clearly indicate that OML adds significant value to CPS, and it is strongly recommended as an extension of related architectures, such as the cognitive architecture for AI discussed in this article. Additionally, surrogate-model-based optimization is employed, to determine the optimal hyperparameter settings for the corresponding OML algorithms, aiming to achieve peak performance in their respective tasks.
A Computational Study of Polymer Solutions Flow Regimes during Oil Recovery from a Fractured Model
Authors: Guzei Dmitriy , Skorobogatova Angelica , Ivanova Sofia , Minakov Andrey
Published: October 2023

Increasing the efficiency of hydrocarbon field development is an important issue. One of the methods for increasing oil recovery is the injection of aqueous solutions of polymers. Although this method has been known and used for quite some time, further systematic research is needed to further improve its effectiveness. In this work, systematic computational studies of the features of oil displacement by aqueous polymer solutions from a naturally fractured structure were carried out. Direct numerical modeling of a two-phase immiscible flow in the process of displacing oil from a natural fracture structure using solutions of anionic polymers based on polyacrylamide was carried out. Aqueous solutions of three different polymers were considered, the concentrations of which varied from 0 to 0.1%, and the molecular weights were from 10 to 20 mln c.u. The rheological properties of polymers and their wetting characteristics have been previously studied in laboratory experiments. A distinctive feature of the polymers considered was the non-Newtonian nature of their aqueous solutions even at low concentrations. To take these processes into account, the computational technique has been extended to the case of non-Newtonian rheology for immiscible two-phase flow in one of the media. During numerical simulations, the effect of the concentration of polymers, their molecular weight, and charging density on the flow regimes in a fractured reservoir have been investigated systematically at various crude oil viscosities. It has been shown that the use of a 0.1% aqueous solution of polyacrymalide can increase the oil-recovery factor by 1.8 times. It has been established that, with an increase in the molecular weight and surface charge density of the polymer, the efficiency of its use for enhancing oil recovery increases. With an increase in the viscosity of the displaced oil, the effect of using the injection of the considered polymers also increases. The data obtained in this work can be used to further improve polymer-flooding technologies for oil fields.
Artificial Intelligence Component of the FERODATA AI Engine to Optimize the Assignment of Rail Freight Locomotive Drivers
Authors: Brezulianu Adrian , Geman Oana , Popa Iolanda Valentina
Published: October 2023

The optimization of locomotive drivers’ scheduling in rail freight transportation comes as a necessity for minimizing economic expenses and training investments. The Ferodata AI engine, an artificial intelligence (AI)/machine learning (ML) software module, developed by our team, has integrated a supervised random forest model that automatically assigns conductors to freight transportation orders based on the data about locomotive driver’s tiredness score, distance of the driver to the departure point of a transportation order, driver availability, and circulation history. The model proposed by us obtained very good performance metrics on the train set (accuracy: 95%, AUC: 0.9905) and reasonably good and encouraging performance on the test set (accuracy: 84%, AUC: 0.8357). After rigorous testing and validation on external and larger datasets, the automated optimization of locomotive driver assignments could bring operational efficiency, cost savings, regulatory compliance, and improved safety to scheduled rail freight transports.