bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Observational Study of Adjunctive Artisanal Cannabidiol Use by Adults with Treatment Resistant Epilepsies: Behavioral and Urinalysis Data
Authors: Brett Barbara , Conroy Matthieu , Doshi Hardik , Lowe Matthew X. , Kalcheff-Korn Sasha , Jackson Heather 
Published: August 2023

AbstractBackground For approximately 30% of people with epilepsy, seizures are not well-controlled by antiepileptic drugs. This condition, called treatment resistant epilepsy (TRE), is associated with increased morbidity and mortality, and substantially impacts the quality of life of both the individual and their family. Non-responsiveness to AEDs leads many people with TRE to seek alternative therapies, such as cannabinoid-based medication, particularly cannabidiol (CBD), with or without medical or professional advice. This is due in part to widespread reporting in the media on the benefits of CBD for seizures in some forms of epilepsy. Methods Ten adults with TRE, opting to add CBD to their existing treatment regime, participated in this prospective, observational, longitudinal study. We hypothesized that adjunctive CBD use would positively impact participants’ quality of life and psychological well-being. Participants were followed for a period of approximately six months – for approximately one month prior to the initiation of CBD use and approximately five months after. At three time points, participants provided urine samples and completed behavioral questionnaires that assessed quality of life, anxiety/depression, and adverse events. Results Analyses showed a statistically significant improvement in quality of life, a statistically significant decrease in anxiety symptoms, and a statistically significant decrease in the experience of adverse events over time (p < 0.05). Urinalysis revealed the majority of participants had no CBD/metabolites in their system at the beginning of the study, and confirmed the presence of CBD/metabolites in participants’ urine after CBD was added to their treatment regime. Conclusion These results suggest that adjunctive use of artisanal CBD may be beneficial for the behavioral and psychological symptoms of TRE and may improve medication tolerability.
RNA-seq Parent-of-Origin Classification with Machine Learning applied to Alignment Features
Authors: Miller Jason R , Adjeroh Donald A 
Published: August 2023

Abstract
Background
Parent-of-origin allele-specific gene expression (ASE) can be detected in interspecies hybrids by virtue of RNA sequence variants between the parental haplotypes. ASE is detectable by differential expression analysis (DEA) applied to the counts of RNA-seq read pairs aligned to parental references, but aligners do not always choose the correct parental reference.
Results
We used public data from four species pairs that are known to hybridize. For each pair, we obtained RNA-seq read pairs from both species and measured our ability to assign each read to its proper species by comparing reads to the transcriptome or genome references. We tested four software packages that assign each read pair to a reference position and found that they often favored the incorrect species reference. To address this problem, we introduce a post process that extracts alignment features and trains a random forest classifier to choose the better alignment. On each dataset tested, our machine-learning post-processor achieved higher accuracy than the aligner by itself at choosing the correct species per RNA-seq read pair.
Conclusions
For the parent-of-origin classification of RNA-seq, machine learning can improve the accuracy of alignment-based methods. This approach should be useful for enhancing ASE detection in interspecies hybrids. We believe this is the first application of machine learning to this problem domain.
A novel dual-component radar signals modulation recognition method based CNN-ST
Authors: Wan Chenxia , Zhang Qinghui 
Published: August 2023

Abstract

This paper presents a randomly overlapping dual-component radar signals recognition method based on a convolutional neural network-swin transformer (CNN-ST) under different signal-to-noise ratio (SNR), for improving the lower recognition performance and the higher computational costs of the conventional methods. To enhance the feature representation ability and decrease the loss of the detailed features of dual-component radar signals under different SNR, the swin transformer is adopted and integrated into the designed CNN model. An inverted residual structure and lightweight depthwise convolutions are used to maintain the powerful representational ability. The results show that the dual-component radar signals recognition accuracy of the proposed CNN-ST is up to 82.58% at -8 dB, which shows the better recognition performance of the CNN-ST over others. The dual-component radar signals recognition accuracies under different SNR are all more than 88%, which verified that the CNN-ST achieves better recognition accuracy under different SNR. The recognition performance of 2FSK-EQFM, 2FSK-LFM, 2FSK-NS, EQFM-LFM, EQFM-NS, and LFM-NS are up to 94.44%, 93.33%, 88.89%, 95.56%, 87.78%, and 94.44% at SNR of -8 dB, respectively. This work offers essential guidance in enhancing dual-component radar signals recognition under different SNR and promoting actual applications.
A Novel Defect Detection Method for Gear System Based on EEWT and DELM
Authors: Huang Xuebin , Liu Hongbing , Chen Fangyuan , Ye Bingcheng 
Published: August 2023

Abstract
Gear system is the one of the most important components of station wagon, so it is very important to study the defect detection method for gear system of station wagon. Defect detection for gear system of station wagon by extensive empirical wavelet decomposition and deep extreme learning machine is proposed in this paper. As the features the time-frequency image based on extensive empirical wavelet decomposition (EEWT) are clearer than those of empirical wavelet decomposition (EWT), EEWT is used to decompose the vibration signals of gear system of station wagon, and create the time-frequency images of the vibration signals of gear system of station wagon. Deep extreme learning machine (DELM) is formed by stacking multi-layer extreme learning auto-encoders, so it can extract higher-level features and has higher classification and recognition accuracy than traditional ELM, thus, DELM is used to defect detection for gear system of station wagon. The experimental results demonstrates that the defect detection accuracy of EEWT-DELM is higher than EWT-DELM,EWT-ELM, and traditional ELM, and EEWT-DELM is suitable for defect detection of gear system of station wagon.
Optimizing Reinforced Concrete Structures: A Comparative Investigation of Diverse Wire Mesh Configurations
Authors: Mebrahtom Misgina , Fissha Yewuhalashet , Ali Mujahid , Gebretsadik Angesom , Kide Yemane , Nguse Zaid , Gebrehiwot Zemicael 
Published: August 2023

Abstract
The current study use varied steel wire meshes in lightweight concrete to investigate the effects on mechanical properties in lightweight aggregate concrete (LWAC). There were three types of steel wire mesh used: hexagonal (chicken) wire mesh, welded square wire mesh, and expanded metal mesh in various layers and orientations in LWAC. Several mechanical properties such as flexural strength (FS), compressive strength (CS), and energy absorption (EA) were investigated. A total of 45 prisms specimens with dimension of 100x100x500mm ( width x depth x length) was casted for FS, 33 cube specimens were prepared for CS 150x150x150mm, whereas 45 specimens were costed for EA tests with a dimension of 400x300x75mm (LxWxH) respectively for 14 days of curing. The experimental results shows that the wire mesh as an additional reinforcement in the beam, enhanced the flexural behavior of the beam by distributing the forces along the section. The increment of the flexural resistance of the reinforced concrete due to the addition of one layer of chicken wire mesh, welded square wire mesh, and expanded metal mesh is 52.96%, 23.76%, and 22.2% respectively. The flexural strength in one-layer hexagonal wire mesh shows the highest FS which is 29.49MPa compared to the rest of the layers. However, the lowest FS were found in the wire mesh with one layer in all three meshes (hexagonal, welded, and expanded). There is a gradual decrease in the CS of concrete incorporating LWAC by increasing the layers of the hexagonal, welded, and expended wire mesh. The highest CS were found in the hexagonal wire mesh with one layer that is 36.56MPa. There is no such variation in the CS of combination of all three types of meshes and were found 29.79MPa. The highest energy was recorded in the expanded and chicken wire mesh with three layers before the ultimate failure that 1108.7 and 1425.6 Joul whereas, for welded square wire mesh, the highest energy absorption (752.3Joul) were found in the combination of three layer. For the first layer of hexagonal wire mesh reinforced concrete, the energy absorption was increased by 82.81% before crack whereas, it increases 88.34% before ultimate failure. Finally, it was concluded and recommended that hexagonal wire mesh outperforms than welded and expanded wire meshes.
Extra-facet puncture PVP in the treatment of osteoporotic vertebral compression fractures
Authors: Zheng Huo-Liang , Li Bo , Jiang Qin-Yu , Jiang Lei-Sheng , Zheng Xin-Feng , Jiang Sheng-Dan 
Published: August 2023

Abstract

PURPOSE To assess the safety and efficacy of the extra-facet puncture technique applied in unilateral percutaneous vertebroplasty (PVP) for treating osteoporotic vertebral compression fractures (OVCFs). METHODS Demographics (age, gender, body mass index and underlying diseases) were recorded for analyzing. VAS (Visual analogue scale) and ODI (Oswestry Disability Index) scores as well as their corresponding MCID (minimal clinically important difference) were used to evaluate clinical outcomes. The segmental kyphotic angle, the vertebral compression ratio and bone cement distribution pattern were evaluated by the plain radiographs. The facet joint violation (FJV) was defined by the postoperative computed tomography (CT) scan. Binary logistic regression analysis was performed to investigate relationships between multiple risk factors and residual back pain. RESULTS VAS and ODI scores in both traditional puncture group and extra-facet puncture group were significantly decreased after PVP surgery (p<0.05). However, no significant difference was observed between the two groups according to VAS and ODI scores. The proportion of patients achieving MCID of VAS and ODI scores was higher in extra-facet puncture group as compared to traditional puncture group within a month (p<0.05). Finally, multivariate logistic regression analysis showed that FJV (odds ratio [OR]: 16.38, p<0.001) and unilateral bone cement distribution (OR: 5.576, p = 0.020) were significant predictors of residual back pain after PVP surgery. CONCLUSIONS Extra-facet puncture percutaneous vertebroplasty can decrease the risk of FJV and it also has the advantage of more satisfied bone cement distribution.
SAR1B contributes to progression of lung cancer via enhancing cell proliferation and migration
Authors: Wen Huanshun , Zhang Jin , Liang Chaoyang 
Published: August 2023

Abstract
Lung cancer remains the leading cause of cancer-related deaths worldwide with increasing incidence. Secretion associated ras related GTPase 1B (SAR1B) encode a protein that responsible for protein transport from the endoplasmic reticulum to the Golgi apparatus. However, the exact involvement of SAR1B in lung cancer is not yet fully understood. In this study, clinical human lung cancer tissues and normal para-carcinoma tissues were analysed to identify the expression of SAR1B. We additionally evaluated the impact of SAR1B on malignant features of lung cancer cells both in vitro and in vivo by developing stable knockdown cell models for SAR1B. Our results revealed that SAR1B was highly expressed in lung cancer tissues, particularly in those that had advanced stages of the lung cancer, as compared with normal para-carcinoma tissues. Concomitantly, overexpression of SAR1Bwas associated with a shorter survival for patients with lung cancer. Moreover, SAR1B knockdown was shown to have a significant impact on suppressing the proliferation and migration of lung cancer cells, while promoting cell apoptosis. Our in vivoexperiments further confirmed the the indispensable role of SAR1B on tumorigenesis. In conclusion, these results demonstrated the promoting role of SAR1B in proliferation and migration of lung cancer cells. SAR1B shows promise as a novel biomarker for lung cancer progression and has potential for use as a therapeutic target for patients with lung cancer.
Timing of Global Surface Water Transitions Reveals Anthropogenic Dominance of Recent Growth in Water Extent
Authors: Nagel Gustavo , Darby Stephen , Leyland Julian 
Published: August 2023

Abstract

The extent of coastal and inland surface water resources is constantly varying in response to complex interrelated processes, driven by natural and anthropogenic factors. Recent advance in satellite technology and cloud computing have enabled global-scale monitoring of the changing occurrence and extent of these surface water resources. However, until now, no previous study has sought to estimate the timing of these surface water changes at the global-scale. Here we introduce the first global-scale identification of the year when water advanced or receded within a given pixel, using a 38-year Landsat time series. Our methods focus exclusively on persistent changes in water features, filtering out seasonal or short-lived fluctuations. We use the new algorithm to map the timing of water advance and/or recession events globally, encompassing both inland water bodies and coastal dynamics. Additionally, the timing of water transitions enabled the identification of the primary drivers behind these changes. As a result, we identified that most of the large-scale water change events are related to human influence, such as damming, infrastructure failures and even conflicts. These combined factors contributed to a global shift, with accumulated water advancing surpassing water receding over time.
Circular RNA hsa_circ_0078767 regulates ferroptosis in lung cancer cells through miR-330-3p/p53 axis
Authors: Chen Ting , Jiang Hua , Lu Lin , Ye Lijuan , Hou Fei , Peng Xiaoqi , Wang Yinghui , Cai Haolin , Zheng Xihua 
Published: August 2023

Abstract
Circular RNAs (circRNAs) have been proved have a major impact on tumorigenesis. Whereas, the specific regulation of circRNAs during lung cancer progression is still need further investigation. Here, we found hsa_circ_0078767 was lowly expressed in lung cancer. Through CCK-8, colony formation, EdU staining, and flow cytometer apoptosis assays. We found that up-regulation of hsa_circ_0078767 repressed lung cancer cells proliferation and facilitated cell apoptosis in vitro and in vivo. Furthermore, we identified the regulatory function of hsa_circ_0078767 on ferroptosis during the malignant development of lung cancer. Elevated iron, Fe2+, and ROS levels was found in hsa_circ_0078767 overexpressed lung cancer cells. Ferroptosis activator erastin reduces the cell viability, and the hsa_circ_0078767 overexpression reinforced erastin-induced inhibitory effect on lung cancer cells. Mechanically, hsa_circ_0078767 sponged miR-330-3p to affect p53 expression. Up-regulation of miR-330-3p and knockdown of p53 reversed the role of hsa_circ_0078767 overexpression on lung cancer cells. Taken together, hsa_circ_0078767 may be a new research highlights for inhibiting lung cancer by promoting ferroptosis in lung cancer cells.
Fire prediction using Machine Learning Algorithms based on the confusion matrix
Authors: Adil Korchi , Ahmed Abatal , Essaid Mohamed 
Published: August 2023

Abstract
In an earlier article, we outlined the process of developing a Machine Learning project that is often complex to establish, and that the problem must be broken down into several stages to facilitate its resolution [1]. We were able to identify 5 steps that we think are the most important to tackle such a project. These 5 steps are : the definition of the problem, the preparation of the data, the choice of the right algorithms, the optimization of the results and the presentation of the final results. In this manuscript, we will propose the application of different ways of evaluating classification models through an algorithm that predicts whether there is a fire in a given location or not. We are conscious that this problem is difficult to solve, especially when we have to predict the latter when there is none, do not predict when there is really one, or not predict when there is none. The method of this study will show how to choose the right algorithm and how to Evaluate it. The experiment shows promising results obtained thanks to the classification model algorithm and confusion matrix which provide fire detection accuracy around 92.71%.
Barriers to the father-adolescent sexual communication: Findings from a cross-sectional study in Iran
Authors: Nabavi Hadiseh Sadat , Ganji Jila , Mohammadpour Reza Ali , Hamidi Fatemeh , Shahhosseini Zohreh 
Published: August 2023

Abstract
Background
Most studies on parent-adolescent sexual communication have been conducted on mothers, whilst fathers' participation in this issue has not been adequately addressed. Hence, this study aimed to determine the barriers to sexual communication between fathers and adolescents.
Methods
This cross-sectional study was performed on 196 parents of adolescents aged 15 to 19 from August 2020 to January 2021 in northern Iran. A socio-demographic medical information form, the parent-adolescent sexual communication barriers questionnaire, and the sexual communication topics between parents and adolescents were used to gather information. A logistic regression test was administered using SPSS-26 to determine the barriers to sexual communication.
Results
The prevalence of father-girl sexual communication (51.1%) was lower than that of father-boy sexual communication (55.8%). The most frequent barriers to fathers' sexual communication with both genders were the adolescent's embarrassment and the possibility of provoking their curiosity about sex. The logistic regressions showed that adolescents' embarrassment and conveying not trusting them and approving of them having sex were barriers to father-adolescent sexual communication. Conversely, adolescents asking more private questions were positive predictors of father-adolescent sexual conversation.
Conclusion
Father-adolescent communication is one of the most critical aspects of parenting, though not an easy one. There is a need to develop appropriate interventions for empowering fathers to communicate with their adolescents about various sexual issues.
Integrative Analysis of Gene Expression Profiles of Substantia Nigra Identifies Potential Diagnosis Biomarkers in Parkinson's disease
Authors: Huang Junming , Li Bowen , Wei Huangwei , Li Chengxin , Liu Chao , Mi Hua , Chen Shaohua 
Published: August 2023

Abstract
Background
Parkinson's disease (PD) is a progressive neurodegenerative disease whose etiology is attributed to development of Lewy bodies and degeneration of dopaminergic neurons in the substantia nigra (SN). Currently, there are no definitive diagnostic indicators for PD. In this study, we aimed to identify potential diagnostic biomarkers for PD and analyzed the impact of immune cell infiltrations on disease pathogenesis.
Method
The PD expression profile data for human SN tissue, GSE7621, GSE20141, GSE20159, GSE20163 and GSE20164 were downloaded from the Gene Expression Omnibus database for use in the training model. After normalization and merging, we identified differentially expressed genes (DEGs) using the Robust rank aggregation strategy. Simultaneously, DEGs after batch correction were identified. Gene interactions were determined through Venn Diagram analysis. Functional analyses and protein-protein interaction networks were used to the identify hub genes, which were visualized through Cytoscape. A Lasso Cox regression model was employed to identify the potential diagnostic genes. The GSE20292 dataset was used for validation. The proportion of infiltrating immune cells in the samples were determined via the CIBERSORT method.
Results
Sixty-two DEGs were screened in this study. They were found to be enriched in nerve conduction, dopamine (DA) metabolism, and DA biosynthesis Gene Ontology terms. The protein-protein interaction (PPI) network and Lasso Cox regression analysis revealed seven potential diagnostic genes that were subsequently validated in peripheral blood samples obtained from healthy control (HC) and PD patients, as well as in the GSE20292 dataset. The results revealed the exceptional sensitivity and specificity of these genes in PD diagnosis and monitoring. Moreover, PD patients exhibited a higher number of plasma cells, compared to HC individuals.
Conclusion
The SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1 are potential diagnostic biomarkers for PD. Our findings also reveal the essential roles of immune cell infiltration in both disease onset and trajectory.
Comparison of weighting methods of multi-criteria decision analysis (MCDA) in evaluation of flood hazard index
Authors: Esmaili Reza , Karipour Seydeh Atefeh 
Published: August 2023

AbstractPreparing a map of flood hazard susceptibility is an important step in flood risk management. Therefore, it is necessary to use methods that reduce errors and increase accuracy in identifying flood hazard areas. This study was conducted with the aim of preparing a map of the flood hazard index (FHI) and evaluating subjective and objective multi-criteria decision analysis (MCDA) weighting methods. Talar basin on the north of Iran has been investigated as a case study for this research. Seven flood-influencing factors including elevation, slope, flow accumulation, distance from the river, rainfall intensity, land cover, and geology were used to create a flood hazard map. The weighting of these factors has been performed by Analytical Hierarchy Process (AHP), sensitivity analysis of AHP (AHPS), Shannon Entropy (SE), and Entropy-AHP. The maps created with the data of past floods were validated with ROC and Kappa index methods. The results showed that the FHI-SE method was more accurate than other methods with an accuracy value of 0.979. FHI-SEA, FHIS, and FHI methods were placed in the next priorities, respectively. Based on the SE method, the factors of distance from the river, elevation, and slope respectively have obtained the highest weight value in creating the flood hazard index map. Different classifications of distance from river variables separately for mountains and plains can reduce the overestimation of flood hazard areas in mountainous areas. The objective weighting method has provided more accuracy than the subjective weighting method such as AHP.