bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental analysis on hardness and compression strength of Al6061 reinforced by silicon carbide hybrid composite using bagasse fly-ash and aloe vera ash
Authors: Demisie Leul Fenta , Rengiah Robinson Gnanadurai , Takele Tayachew Nega , Ayalew Yewondwosen Gizat , Berihun Ermias Aswossie 
Published: August 2024

Abstract

The demand for low-density composite materials utilized for structural applications and automobile body parts, resulting in high stiffness-to-weight and strength-to-weight ratios initiated the production of this composite material. The objective of this work is to produce and assess Al6061 Silicon carbide and inexpensive reinforcements of Aloe vera and Bagasse ash. The hardness and compression strength characteristics of the composite, by altering the wt. % of reinforcements were assessed and contrasted. The stir-casting method was used to create this hybrid composite at 700°C. The parameters used to produce this hybrid composite were the composition of reinforcements, powder mixing ratio, and stirring the slurry as done at 600 rpm for 10 minutes. Eight sets of composites were prepared by varying the percentage of Silicon carbide, Bagasse ash, and Aloe vera ash. The prepared composite, compressive strength tests using (ASTM standard D 695) and micro hardness tests (ASTM E18-15 standard) were carried out. The result shows that the compression strength rose with the growth of the bagasse ash and aloe vera ash contents. The highest compression strength of Al6061-10 wt. % SiC, 10 wt. % bagasse ash, and 11 wt. % Aloe vera ash hybrid composite is 376.3 MPa. Al6061-10wt.%SiC-9wt.% bagasse ash – 9wt.% Aloe vera ash and Al6061-10wt.%SiC-10wt.% bagasse ash – 11wt.% Aloe vera ash provided the highest hardness values, measuring 91.16 HV and 91.6 HV, respectively. The hybrid composite's hardness value rose from a single reinforced Al6061/SiC composite by 16.27%. It is determined that the hardness and compression strength of Al6061 composite materials are significantly increased by the addition of bagasse and aloe vera ashes.
Short Term Efficacy of Biological Treatment for Moderate-to-Severe Plaque Psoriasis: A Systematic Review and Network Meta-Analysis
Authors: Ismail Omar , Jaber Kamel , Jaber Yazan , Froukh Ubada , Younis Ahmad , Albdour Karam , Momani Yazan , Almaani Noor 
Published: August 2024

Abstract

Background
Psoriasis is a chronic inflammatory disease that is debilitating, particularly in its more severe forms. Multiple systemic therapies are used in moderate-to-severe psoriasis, but the development of biological interventions has revolutionized its management and improved its outcomes.
Aim
To compare the effectiveness and safety of the different biological interventions approved for use in moderate-to-severe plaque psoriasis.
Methods
Multiple databases were searched for relevant articles and a prospectively planned network meta-analysis was conducted on randomized controlled trials that assessed biological treatments in moderate-to-severe psoriasis.
Results
The search yielded 84 trials that encompassed 39798 patients. Infliximab 5mg/kg had the highest probability of achieving 75% reduction on PASI scale in comparison to placebo (RR = 18.76, 95%CI = [12.31; 28.57], high certainty), while Ixekizumab 80mg and Brodalumab 210mg had the highest probability in achieving PASI90 and PASI100 (37.81, [28.57; 50.03] and 81.04, [26.16; 251.01], respectively, with moderate certainty) On the other hand, Risankizumab 150mg and Ustekinumab 90mg were the only regimens with significantly less withdrawal rates due to adverse events (0.41, [0.18 To 0.96], and 0.57, [0.35 To 0.91], respectively with High certainty) compared to placebo.
Conclusion
Anti-IL17 and Infliximab were among the most effective in ameliorating the symptoms of psoriasis, however, anti-IL17 were better in achieving full or almost full improvement on the PASI scale. Real life decision-making is not so clear-cut and should remain patient centered, taking into consideration factors such as safety, comorbidities, biologic naivety, dosing preferences and insurance considerations.
Intrinsic strain of defect sites steering chlorination reaction for water purification
Authors: Sijin Zuo , yinqiao Zhang , Mohan Chen , Xuanyu He , Erzhuo Zhao , Hao Liang , Jingge Shang , Kai Liu , Jianqiu Chen , Zhou Minghua 
Published: August 2024

Abstract

Carbon nanotube (CT)–based chemical technologies particular in heterogenous advanced oxidation processes (AOPs) used for water purification, have been exploited over the several decades. Many strategies of CT modification have been exploited to improve the catalytic performance in the remediation processes. However, the strain fields of intrinsic defect sites on CT steering AOPs (such as chlorination) have never been reported. Here we for the first time explored the strained defect sites steering chlorination process onto high–efficient and green abatement of 2,4–dichlorophenol. Characterizations and theory analysis unveil that the strained defect sites with the elongated sp2 hybridized C–C bond displaying the larger spin–lattice relaxation boost electronic reactivity with chlorine molecules via the initial Yeager–type adsorption. As a result, the amounts and catalogs of reactive species in our chlorination are tunable on demand, such as the ratio of high–selectivity ClO• ranging from 38.8% in pure defects–based system to 87.5% in strain dominated process, which result in generating the harmless intermediates and even deep mineralization of organic. Thus, this work highlights the vital role of the strain fields on steering chlorination reaction for greener water purification even beyond.
Pan-Cancer TCGA Analysis Reveals the Potential Involvement of Lamin B2 in Dysregulating Chromosome Segregation in Human Cancer
Authors: Kundu Subhadip , Jit Bimal Prasad , Sharma Ashok 
Published: August 2024

Abstract

Lamins are fibrous proteins present just beneath the inner nuclear membrane and play a crucial role in shaping the genomic architecture. Several studies have reported the association of lamins with disease conditions such as cancer. Despite significant progress, the prognostic significance and underlying molecular targets of B-type lamins, especially lamin B2 in pan-cancer, have not been well studied. In this study, we have explored through bioinformatic analysis the potential functions of lamin B2 in driving cancer and its prognostic significance across pan-cancer TCGA datasets. Our results indicate the overexpression of lamin B2 in multiple human cancers, which is also correlated with poor overall and disease-free survival. Besides this, higher lamin B2 is associated with CD4+ Th1 and Th2 cell infiltration. We have identified 9 lamin B2 interacting proteins that are co-expressed with lamin B2 in cancerous conditions and, together with lamin B1, regulate cytokinesis and cell division pathways. Furthermore, we have identified specific molecular targets and independent functions of lamin B2 in dysregulating chromosome segregation and mRNA binding in multiple cancers. Our study, for the first time, has demonstrated the potential functions of lamin B2 and its prognostic significance across different cancers.
Ruptured AAA: Bridging the Gap Between International Guidelines and Local Clinical Realities
Authors: Hassan Summer , Frost Taylor , Bourchier Russell 
Published: August 2024

Abstract

Background: Treatment of asymptomatic Abdominal Aortic Aneurysms (AAA) presents a clinical challenge, balancing rupture risk, patient comorbidities, and intervention-related complications. International guidelines recommend intervention for specific AAA size thresholds, but these are based on historical trials with limited female representation. We aimed to analyse disease characteristics, AAA size at rupture, and intervention outcomes in patients with ruptured AAA from 2009 to 2023 to bridge the gap between guidelines and local realities.
Methods: This single-centre retrospective cohort study analysed electronic health records of patients diagnosed with ruptured AAA, assessing demographics, risk factors, comorbidities, clinical presentation, radiological characteristics, and outcomes.
Results: Of 164 patients (41 females, 123 males, median age 73.5), 93.3% presented with abdominal or back pain. The median AAA size at rupture was 8.0 cm in males and 7.6 cm in females. No significant correlations were found between demographic characteristics, risk factors, AAA size, repair modality, and outcomes. Trends show a decline in AAA prevalence and rupture rates, aligning with global health initiatives. Post-intervention survival rates at 30 days were 70.7%, and at 2 years, 65.9%.
Conclusion: Evolving AAA trends and improved post-intervention survival rates suggest a critical reassessment of existing intervention recommendations. Adjusting intervention thresholds to larger sizes may be warranted to optimize the risk-benefit ratio.
Introducing new Link Prediction Measures and an Evaluation Metric
Authors: Javan Abolfazl , Moeini Ali , Ghodousian Amin 
Published: August 2024

Abstract

Link prediction plays a critical role in network analysis as it tackles the task of predicting missing or future connections within a given network. A wide array of link prediction measures has been proposed to estimate the likelihood of link existence between nodes, aiming to uncover hidden relationships and anticipate the formation of new connections. This task holds particular significance in various domains, including social networks, biological networks, transportation networks, and recommender systems. Nonetheless, evaluating the effectiveness of these measures poses challenges, encompassing both the measures themselves and the employed evaluation metrics. This article offers a comprehensive overview of the existing link prediction measures, shedding light on their limitations and addressing the associated challenges in evaluating their efficacy. Moreover, we propose enhancements to overcome these challenges, entailing modifications to existing measures and the introduction of novel evaluation metrics. By tackling these issues head-on, our objective is to enhance the accuracy and reliability of link prediction in network analysis.
Study on the Optimized Layout of CO₂ Emission Devices from the Perspective of Greenhouse Flow Field Dynamics
Authors: WANG Binnan , Shang Tingyi 
Published: August 2024

Abstract

In the rapid development of modern agricultural technology, greenhouse facilities have become an important cornerstone of agricultural production, with increasingly wide applications and significant implications for improving agricultural production efficiency and crop quality. However, in practical applications, especially during the morning to noon period, due to the gradual increase of solar radiation, the photosynthesis activity of plants in the greenhouse also intensifies, resulting in a significant increase in carbon dioxide consumption. This phenomenon not only reduces the carbon dioxide concentration in the greenhouse, but also limits the efficiency of photosynthesis to a certain extent, thereby adversely affecting the growth of greenhouse crops and ultimately potentially affecting the economic benefits of agricultural crops. To address this challenge, this study introduces carbon dioxide release devices as a solution, and through simulation methods, comparatively analyzes the impact of carbon dioxide release devices placed in different positions on the carbon dioxide concentration distribution in the greenhouse. Through precise data collection and processing, this study aims to determine the optimal placement position of carbon dioxide release devices to achieve the optimization of airflow distribution inside the greenhouse and improve the utilization efficiency of carbon dioxide.
Historical marine ecology using non-traditional data sources reveals the impact of local and global processes over half a century
Authors: Turnbull John W. , Booth D. J. , Vergés Adriana , Clark Graeme 
Published: August 2024

Abstract

Human impacts on earth span centuries, yet scientific studies cover a fraction of this time. Historical records and citizen scientist data are a useful resource for the long-term studies needed to understand and respond to pressures on nature, yet their quality and validity have been challenged. To explore how such non-traditional sources can be used to understand historical ecological change, we studied a site (Shiprock) with long-term citizen science activity in the Sydney, Australia region. We analysed approximately 6000 taxonomic records and reports revealing substantial ecological changes between 1965 and 2020, including the local disappearance of some fish and invertebrate species and declines in the abundance of many taxa including kelp. We found indications of potential range extensions more frequently from the north than the south, consistent with patterns expected from the global processes of climate change. We compared the relative advantages and limitations of the two main citizen science data collection modes: structured surveys and opportunistic presence records. Structured surveys provided broadly scientifically useful ecological information including species richness, populations, community structure and temporal change. Opportunistic data had the potential to provide long-term retrospective community information and species presence, but were limited in the ability to provide species absence, biomass, populations, community structure and coverage of remote areas. Our study allowed the development of scientifically- and managerially-relevant insights encompassing foundation, threatened, protected and invasive species, community shifts and the impacts of local and global processes over historical timescales.
A Multi-Layer Heterogeneous Task Scheduling Strategy in UAVs-assisted MEC Networks
Authors: Pang ShanChen , Zhu XiaoRan , Gui Haiyuan , Zhang Yanxiang 
Published: August 2024

Abstract

This paper studies the task scheduling problem in the multiple unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) system. In order to reflect the complexity and diversity of the system, we propose a multi-layer heterogeneous task scheduling strategy. The strategy allows system model to simulate arrival and service of tasks by applying heterogeneous M/M/1, M/M/c, and M/M/c/K classical queues. In order to better evaluate the proposed strategy, we obtain various performance measures. By trading off delay and energy consumption, a single-objective optimization problem with constraints is formulated. Then we introduce the penalty function method to transform the problem into a single-objective optimization problem without any constraints, and propose a hierarchical heterogeneous task scheduling optimization (HHTSO) algorithm to optimize the formulated problem. Theoretical analysis and simulation results show that the proposed algorithm is more effective in ensuring low delay and low energy consumption.
Transforming de novo peptide sequencing by explainable AI
Authors: Wang Yu , Liang Zhendong , Ling Tianze , Chang Cheng , Yang Tingpeng , Xie Linhai , He Yonghong 
Published: August 2024

Abstract

De novo peptide sequencing is crucial for identifying novel proteins, yet its broader application is constrained by the lack of a robust quality control system. In response, we developed a transformer-based model, π-xNovo, that accurately predicts peptides. By analyzing the model's attention matrix, we elucidated the contribution of spectral peaks to amino acid predictions, thus making de novo sequencing results explainable. Leveraging these insights, we designed a quality control system, π-xNovo-QC, which distinguishes peptide predictions with an accuracy exceeding 80% and a sensitivity above 90%. Applying this system to a large-scale deep human proteome dataset resulted in the identification of 1,931,761 additional peptides, marking a 137% increase over traditional database search results. These newly identified peptides with high confidence facilitated a 17.9% increase in protein identification, a 23.59% increase in the detection of single amino acid polymorphism events, and a 20.02% increase in exon-skipping splicing events. The deployment of this explainable AI system holds significant potential for expanding the application of de novo peptide sequencing, particularly in exploring the darker matter of the entire proteome universe.
Driving analysis and prediction of COD based on frequency division
Authors: Li Mei , Chen Kexing , Wang Deke , Xu Rui 
Published: August 2024

Abstract

COD (Chemical Oxygen Demand) is an important indicator to measure organic pollution of water body. To strengthen in-depth analysis and prediction of COD, a new method was proposed in this paper. A frequency division method, Variational Mode Decomposition (VMD) was used to complete time domain decomposition of COD data before model simulation. The original data was separated into five signals with different frequency bands, IMF1, IMF2, IMF3, IMF4 and IMF5, with which the influence of meteorological factors and water quality factors on COD were explored. The long-term COD content is mainly driven by nutrient factors phosphorus and nitrogen, while the immediate fluctuation characteristics exhibit relatively stability. Random Forest, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) were used to predict COD with the original data and the signal data processed by VMD. It is found that frequency division can improve simulation stability and accuracy of GRU and LSTM more significantly than Random Forest. VMD-GRU and VMD-LSTM models can be used reliably for COD analyzation and prediction in Chengdu area.
Feasibility of novel bigels prepared by beeswax and basil seed mucilage for 3D printing approach
Authors: Jasemi Mohammad mehdi , Noshad Mohammad , Jooyandeh Hossein , Mehdizadeh Saman Abdanan , Behbahani Behrooz Alizadeh 
Published: August 2024

Abstract

In this research, a series of bigels were prepared by incorporating a beeswax-based oleogel and basil seed mucilage- based hydrogels in different ratios. The effect of several oleogel/hydrogel combinations on the physical features and 3D printing capability of the resulting bigels was evaluated. FTIR results of several bigels showed significant variations between 3500-3300 cm-1 (hydroxyl groups) and 1150-990 cm-1 (stretching of C-O and C-O-C bonds). The bigels displayed a shear-thinning characteristic and demonstrated enhanced mechanical properties, such as apparent viscosity, storage modulus, and firmness compared to both pure oleogel and pure hydrogel. According to the thermogravimetric analysis (TGA) results, the weight loss in bigel formulations was faster compared to hydrogels. Bigels with an oleogel/hydrogel ratio of 70:30 exhibited favorable mechanical properties suitable for 3D printing. The findings of this research demonstrate that it is possible to produce 3D printable bigels by blending beeswax (organogelators) with basil seed mucilage (hydrogelator). Furthermore, the characteristics and printing capabilities of these bigels can be customized by adusting the ratios of oleogel to hydrogel.
Screening and identification of key genes between high-grade and low-grade serous ovarian carcinomas using integrated bioinformatics
Authors: Zhang Liwei , Pan Zhenglan , Song Weiguo , Wang Wenyan , Fu Liutao , Li Jun , He Runhua , Wang Qingyuan , Wang Yue , Zhang Shenghua , Shan Wenjun , Wei Bing , Fu Juanjuan 
Published: August 2024

Abstract

Epithelial ovarian cancer (EOC) is one of the most aggressive tumors in women. The most common pathological type of EOC is high-grade serous carcinoma (HGSC), which is often diagnosed at an advanced stage. Low-grade serous carcinoma (LGSC) is estimated to account for 10% of all serous carcinomas. Previous studies have demonstrated that molecular and clinical characteristics differences are apparent between these two subtypes of EOC. The objective of this study was to screen and identify key genes between HGSC and LGSC, and to explore potential molecular mechanisms in the pathogenesis of EOC. The microarray datasets GSE27651 and GSE14001, with a total of 23 LGSC tissue samples and 32 HGSC tissue samples, were obtained from the Gene Expression Omnibus (GEO). The differentially-expressed genes (DEGs) were selected out through the “affy” and “limma” package in R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction (PPI) analysis of DEGs was carried out through the Cytoscape software. Finally, survival analysis of some key geneswas conducted using the Kaplan Meier Plotter Online Tool. A total of 357 DEGs were found in HGSC, of which 181 were up regulated and 176 were down regulated. GO functional enrichment analysis showed that the DEGs were mainly associated with nucleus, cell proliferation and protein binding. KEGG pathway analysis showed that these genes were enriched in the PI3K-Akt signaling pathway, pathways in cancer, the p53 signaling pathway, cell cycle, microRNAs in cancer. Twelve hub genes (TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1, BUB1, RRM2 and PBK) were screened out from PPI network. The mRNA expression of TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1, BUB1, RRM2, and PBK were significantly increased in tumor tissues. The protein expression of TOP2A, CDK1, CCNB1, MAD2L1, KIF11, CCNB2, TTK, AURKA, RACGAP1 and PBK were distinctly higher in serous ovarian cancer tissues than non-serous ovarian cancer tissues detected by immunohistochemical staining. Survival analysis showed that TOP2A, CCNB1, KIF11, AURKA, and BUB1 were significantly associated with clinical survival outcome. In addition, there is a significant correlation between the expression levels of twelve hub-genes and immune cell infiltration in serous ovarian cancer. In summary, the present study identified DEGs and hub genes by two GEO datasets mining, which might offer new insights into the molecular mechanisms of these two subtypes of EOC and provide some prognostic biomarkers for the treatment of EOC.
Transfer printing micro-assembly of silicon photonic crystal cavity arrays: beating the fabrication tolerance limit
Authors: bommer sean , Panuski Christopher , Guilhabert Benoit , Xia Zhongyi , Smith Jack , Dawson Martin , Englund Dirk , Strain Michael 
Published: August 2024

Abstract

Photonic crystal cavities (PhCCs) can confine optical fields in ultra-small volumes, enabling efficient light-matter interactions for quantum and non-linear optics, sensing and all-optical signal processing. The inherent nanometric tolerances of micro-fabrication platforms can induce cavity resonant wavelength shifts two-orders of magnitude larger than cavity linewidths, prohibiting fabrication of arrays of nominally identical devices. We address this device variability by fabricating PhCCs as releasable pixels that can be transferred from their native substrate to a receiver where ordered micro-assembly can overcome the inherent fabrication variance. We demonstrate the measurement, binning and transfer of 119 PhCCs in a single session, producing spatially ordered arrays of PhCCs, sorted by resonant wavelength. Furthermore, the rapid in-situ measurement of the devices enables measurements of the PhCCs dynamic response to the print process for the first time, showing plastic and elastic effects in the seconds to hours range.