bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Revenue Forecasting Model of Automobile Manufacturing Enterprises Combining Public Opinion Data and Financial Data: A Case Study of Chinese Automobile Manufacturing Enterprises
Authors: Du Yu , Wei Kaiyue , Li Xinyue , Liu Huilu
Published: July 2023

The automobile manufacturing industry is currently in an important period of transformation and upgrading. Scientific and accurate revenue forecasting model can help automobile manufacturing companies to carry out reasonable business planning, but also can help industry investors and other automobile market participants to understand the business situation. However, revenues of automobile manufacturing companies often show a non-linear dynamic fluctuation trend. To address the aforementioned issues, this research proposes a quarterly revenue prediction model for automobile manufacturing companies based on the machine learning and deep learning algorithm. The overall model is divided into two parts. The first part is based on the random forest and SARIMA algorithm to establish the quarterly sales forecasting model for the automotive industry. The forecasting performance of the model is significantly better than that of the SARIMA model alone. And the performance is better when SARIMA uses dynamic forecasting than when SARIMA uses static forecasting. In the second part, this paper transforms the collected opinion text into data representing the positive degree of opinion sentiment, and builds a model based on the CNN algorithm using the predicted value of automobile industry sales obtained in the first part along with other feature variables. The RMSE and MAE of this prediction model are significantly lower than those of the two benchmark models, so the model proposed in this paper has a better performance on the task of predicting the revenue of automobile manufacturing companies, and the prediction performance of the model is better than that of the model without the introduction of public opinion data.
Transcription directionality is licensed by Integrator at active human promoters
Authors: Lai Fan , Dang Yunkun , Yang Jiao , Li Jiangyang , Miao Langxi , Gao Xu , Sun Wenhao , Shuo Linghu , Ren Guiping , Peng Bangya , Chen Shunkai , Liu Zhongqi , Wang Bo , Dong Ao , Huang Duo , Yuan Jinrong
Published: July 2023

A universal characteristic of eukaryotic transcription is that the promoter recruits RNAPII to produce both precursor mRNAs (pre-mRNAs) and short unstable promoter upstream transcripts (PROMPTs) toward the opposite direction. However, how the transcription machinery senses the correct direction to produce pre-mRNAs is largely unknown. Here, through multiple acute auxin-inducible degradation (AID) systems, we show that rapid depletion of a RNAPII-binding protein complex, Integrator, results in robust PROMPTsaccumulation throughout the genome. Interestingly, the accumulation of PROMPTs is compensated by the reduction of pre-mRNA transcripts in actively transcribed genes. Consistently, Integrator depletion alters the distribution of polymerase between the sense and antisense direction, which is marked by an increased RNAPII-CTD Tyr1 phosphorylation (Tyr1P) level at PROMPT regions and a refrained Ser2 phosphorylation (Ser2P) level at transcription start sites (TSSs). Mechanistically, the endonuclease activity of Integrator is critical to suppress PROMPTs production in a sequence-independent manner. During this step, the endonuclease activity can be inhibited by the U1 signal on nascent antisense transcripts through the recognition of the U1 snRNA-Integrator which relies on the U1-Integrator axis to govern the direction of gene transcription.
Carbon storages and sequestration potentials of Sulula Mofa Forest Northern Ethiopia: Implications of managing forests for climate change mitigation
Authors: Yimer Hussen , Mammo Siraj
Published: July 2023

Forests provides various services and particularly, playing an incredibly greater role in balancing the global carbon balance and mitigating climate change by sequestering CO2 and storing organic carbon from the atmosphere. The overall objective of this study was intended to investigate the Carbon stock and CO2 sequestered potentials, along altitudinal, slope and aspect gradients of woody species of Sulula Mofa Forest, Northern Ethiopia. Systematic sampling technique was used to collect data from the three carbon pools. A total of 42 sample plots with size 400m2 for Tree pool, small plots with a size of 1m2 for Litter pool and Soil data collected from five sub-plots within each major plot and a diameter of > 5cm and at the depth up to 30cm land surface. DBH of woody species were measured in each major sampling plot at DBH ≥ 1.3m & the diameter at DBH ≥ 5cm. The biomass of woody species was estimated using the non destructive allometric equation, while appropriate laboratory procedures were used in the analysis of litter and soil biomass. A total of 54 woody plant species categorized into 50 genera and 33 families were recorded and identified. The total carbon stock and CO2 sequestration potentials of the woody species were estimated to 1121.14 t/ha & 4114.59 t/ha respectively, of which tree pools (658.55), Soil pools (315.88) and Litter pools (146.71). In the study forest, 92.59% of carbon stored and CO2e sequestered were contributed by the following ten woody tree species of the study forest; Ficus sur, Juniperus procera, Cupressus lusitanica, Eucalyptus globulus, Acacia abyssinica, Croton macrostachys, Erythrina abyssinica, Olea europaea subsp. cuspidata, Cordia africana and Pteroloblum stellautm with their descending order. Plots in the south and west part of the forest had more species diversity, greater carbon stocks and CO2 sequestration potentials. Plots at the middle and upper altitudes assessed had more species diversity. It can be concluded that the study forest contributes high carbon stock, better sequestration potential and plays a role in climate change mitigation. Thus, we suggests that, stakeholders should adopt effective forest conservation measures and get benefit from the bio-carbon fund from their activity (CDM of the Kyoto Protocol); as financial incentives to improve foresters’ Livelihoods.
Local Mitigation of Higher-Order Ionospheric Effects in DFMC SBAS and System Performance Evaluation
Authors: Sophan Somkit , Supnithi Pornchai , Myint Lin M. M. , Saito Susumu , Hozumi Kornyanat , Nishioka Michi
Published: July 2023

Dual-Frequency Muti-Constellation (DFMC) Satellite-Based Augmentation System (SBAS) is a new SBAS standard for aeronautical navigation systems. It supports aircraft navigation from the enroute to approach phases via the L1 and L5 frequencies (1575.42 and 1176.45 MHz). Although the ionosphere-free (IF) combination in the DFMC SBAS operation removes the first-order ionospheric delays in the pseudorange measurement, remaining terms including the satellite-clock offset errors and higher-order ionospheric (HOI) delays are still unaccounted for. The DFMC SBAS accuracy and integrity can be affected by the HOI effects, especially during severe ionospheric disturbances. In this work, we present the local DFMC SBAS corrections with and without the mitigation of HOI delays. We first estimate the HOI delay terms using the received pseudorange followed by separate satellite and receiver bias estimations based on the minimum sum-variance technique. The integrity terms can then be obtained. The performances of DFMC SBAS using GNSS data (GPS, Galileo, and QZSS) are evaluated using obtained GNSS data at stations in Thailand on the ionospheric quiet and disturbed days. The results show that with the HOI mitigation, the vertical positioning errors (VPE) on the quiet and disturbed days can be improved by 12% and 9%, whereas the vertical protection levels (VPL) are improved by 16% and 21%, respectively. In addition, we perform a preliminary assessment of DFMC SBAS based on the International Civil Aviation Organization (ICAO) requirements of two categories: LPV-200 and CAT-I showing promising results.
Selection and validation of reference genes suitable for gene expression analysis by Reverse Transcription Quantitative Real-Time PCR in Acinetobacter baumannii
Authors: Ferraz Lúcio Fábio Caldas , de Oliveira Paloma Aparecida Alves , Baboghlian Juliana , Ramos Clarissa Orandina Aparecida , Mançano Alquiandra Stefani Ferreira , Porcari Andréia , Girardello Raquel
Published: July 2023

Acinetobacter baumannii is a Gram-negative bacterium considered an emerging multi-drug-resistant pathogen. Furthermore, this bacterium can survive in extreme environmental conditions, which makes it a frequent cause of nosocomial infection outbreaks. Gene expression analyses by Reverse Transcription Quantitative Real-Time PCR (RT-qPCR) depend on a reference gene, also called an endogenous gene, which is used to normalize the generated data and thus ensure an accurate analysis with minimal errors. Currently, gene expression analyses in A. baumannii are compromised, as there are no reports in the literature describing the identification of validated reference genes for use in RT-qPCR analyses. For this reason, we selected twelve candidate reference genes of A. baumannii and assessed their expression profile under different experimental and culture conditions. The expression stability of the candidate genes was evaluated by using statistical algorithms such as BestKeeper, GeNorm, NormFinder, Delta CT, and RefFinder, in order to identify the most suitable candidate reference genes for RT-qPCR analyses. The statistical analyses indicated rpoB, rpoD, and fabD genes as the most adequate to ensure accurate normalization of RT-qPCR data in A. baumannii. The accuracy of the proposed reference genes was validated by using them to normalize the expression of the ompA gene, encoding the outer membrane protein A, in A. baumannii sensible and resistant to the antibiotic polymyxin. The present work provides suitable reference genes for precise RT-qPCR data normalization on future gene expression studies with A. baumannii.
SFC-SMOTE: A sample filtering clustering oversampling algorithm for imbalanced clinical diagnostic data
Authors: Xu Zhaozhao , Yang Fangyuan , Wang Hong , Sun Junding , Wang Shuihua , Zhang Yudong
Published: July 2023

Background: Medical data mining is an important research direction in the data mining field and has always been a research hotspot in the computer and medical fields for many years. Data mining algorithms usually assume that the sample distribution of data is balanced and the misclassification cost is equal. However, due to the characteristics of medical research, there are serious sample imbalances in the clinical diagnostic data collected, which leads to poor classification effects of data mining algorithms.
Methods: For the problem of sample imbalance in clinical diagnosis data, this paper proposes a sample filtering clustering oversampling algorithm (SFC SMOTE). Firstly, the k-means algorithm is used to group the clinical diagnosis data so that the similarity of the samples within the group is high while the similarity of the samples between the groups is low. Then, the sample filtering strategy is used to identify and filter the "noisy samples" in the minority and the majority and merge the filtered samples of the two classes according to the original class of the samples. Finally, the dynamic rate strategy is set according to the original two-class sample numbers, and the minority and majority samples are dynamically synthesized to restore the original structure of the data.
Results: Experimental results show that the three classification algorithms have the best classification effect on the dataset sampled by the SFC SMOTE algorithm. Among them, the average Sensitivity, Specificity and MCC of Random forest are 92.48%, 92.07% and 84.57%, respectively, which are significantly better than the existing algorithms. In addition, the Wilcoxon and Friedman test results show that the SFC SMOTE algorithm is significantly better than the existing algorithms.
Conclusion: The classification effect of the three classification algorithms has been significantly improved after all sampling algorithms. In addition, the oversampling algorithm is significantly better than the clustering oversampling algorithm. More importantly, no matter which classification algorithm is used, the classification effect of the dataset sampled by the SFC SMOTE algorithm is better.
HOP Count Based Energy Efficient Cluster Head Selection Using Leveling and Sectoring
Authors: Nazeer Mohd
Published: July 2023

WSN are mostly deployed in sensitive location where battery replacement is impossible, which lead to implementation of an energy efficient protocol to extend network life time. In unsupervised machine learning, clustering based hierarchical routing protocols the dissemination of energy occurs mostly due to local communication and cluster head selection, roles of the nodes are changed as cluster member or cluster head to solve fusion and localization problem and manage energy dissemination and increasing the network life time. Nodes can communicate with each other directly or indirectly manner. In this paper the proposed LS-LEACH algorithm solved the problem of optimized cluster head selection by using leveling and sectoring protocol. In LS-LEACH the deployment area is divided into levels and sectors, and selection of the cluster head is done by using hop count matrix. LS-LEACH has been evaluated by performing simulation in OMNET + + simulator and equated with existing EERMS algorithm by considering different metric such as last node death, first node death and network life time. The proposed algorithm can be utilized in various smart IoT based application for optimal cluster head selection.
Accurate felt-tip pen brands classification based on a convolutional neural network using data augmentation
Authors: Huang Jiadong , Wang Xiaobin , Zhang Guangteng , Yang Lei
Published: July 2023

Ink analysis played an important role in document examination, but the limited dataset made it difficult for many algorithms to distinguish inks accurately. This paper aimed to evaluate the feasibility of two data augmentation(DA) methods, Gaussian noise data augmentation (GNDA) and extended multiplicative signal augmentation (EMSA), for the classification of felt-tip pen ink brands. Four brands of felt-tip pens were analysed using FTIR spectroscopy. Five classification models were used, convolutional neural network (CNN), K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and partial least squares discriminant analysis (PLS-DA). The results showed that the datasets generated by GNDA and EMSA are similar to the original datasets and have some diversity. The EMSA method had optimal classification results when combined with CNN, with classification accuracy (ACC), precision (PRE), recall (REC) and F1 score reaching 99.86%, 99.87%, 99.86%, 99.86%, and 99.86%, compared with GNDA-CNN method(ACC = 80.90%, PRE = 87.34%, REC = 81.62%, F1 score = 79.23%). This study shows that when raw spectral data is small, DA methods can be combined with neural network models to identify ink brands effectively.
Lightweight Joint Loss 2D Pose Estimation Network Based onCM-RTMPose
Authors: Cao Zherui , Xue Tao , Zhou Qianming
Published: July 2023

Human pose estimation tasks often need to be deployed on edge devices. While existing humanpose estimation networks can achieve good accuracy, their complex network structure leads to slowinference speed, which is not suitable for real-time tasks. At the same time, the large model structureis not conducive to model deployment. To address this issue, increasingly lightweight networks havebeen proposed in recent years, but existing lightweight networks have a certain gap in model accuracycompared to traditional pose estimation networks. We enhance the feature extraction and keypointrefinement capabilities of the model by adding spatial attention mechanism and using the transformermodule Meta3D, which is more suitable for pose estimation tasks. We trained a lightweight networkCM-RTMpose on the COCO dataset, which achieved an AP value of 69.8%, surpassing most existinglightweight pose estimation networks. To demonstrate the effectiveness of our method, we conductedcorresponding ablation experiments on the COCO and OCHuman datasets. The experiments showedthat our method achieved an AP value of 66.1% on the OCHuman dataset, surpassing the baseline network.
Investigation on Barium Zirconate Nanocomposite for Dielectric Properties
Authors: Sivakumar Seenivasan
Published: July 2023

The barium zirconate (BaZrO3) Perovskite is of interest for various fields of applications. It has high corrosion resistance with respect to molten phases formed during the synthesis of copper-oxide-based super conducting single crystal. In the present investigation, ZrO2and BaZrO3were prepared by co-precipitation method. The samples were characterized by powder X-ray diffraction, FT-IR spectra and EDAX-shows the elemental analysis of the specimens. ZrO2and BaZrO3SEM micrograph of the ZrO2and BaZrO3shows the morphological structure of both of the samples it resembles a nano cluster of spherical particles like a flower. Most of the particles arranged like an agglomerates. The Photoluminescence spectra indicates the blue emission at zirconate. The red emission region is shifted of barium. The high ion exchange ability and redox moment must make it useful in many catalystic processes and also it made the material is useful for the flurosense lamp and flat panel displays. The dielectric constant and dielectric loss were determined as a function of frequency at 1 MHz. It is found to be 63.56 forzirconia and 78.24 for barium zirconate. Due to its high dielectric constant value barium zirconate may be useful in case of ferroelectric applications.
A Review of the Informal Economy Driving Forces and Policy Measures against it: An Analysis of Six EU Countries
Authors: Schneider Friedrich , Asllani Alban
Published: July 2023

This study provides estimates of the size and development of the shadow economy in the countries of the European Union (EU) plus the United Kingdom from 2003 to 2022 using a MIMIC approach. The focus of the study is to provide an analysis of the main factors that drive economic agents to enter shadow economy activities. Our results show that the size of the shadow economy has declined markedly between 2003 and 2021 for almost all countries of the EU including the UK. Our results indicate that the average size of the shadow economy in 27 EU countries plus the UK has decreased from 22.6% of GDP in 2003 to 17.3% in 2022. However, our results also reveal that the size of the shadow economy increased slightly in most EU countries as a result of the direct or indirect impact of the Coronavirus pandemic from 2020 onward. Our analysis and results reveal that weak institutional quality, ineffective government institutions, complex and burdensome tax and regulatory systems, the lack of strong legal systems, and pervasive corruption are the main determinants of economic informality in most countries of the EU. Moreover, the study reviews and elaborates on the main driving forces and the policy measures implemented to reduce the shadow economy with an exclusive focus on six EU countries (Germany, Austria, Denmark, Greece, Italy and Romania).
JEL Classification: O5, C39, C51, C82, H11, H26, U17.
Identification of six genes associated with COVID-19-related Circadian rhythm dysfunction by integrated bioinformatic analysis
Authors: Xu Yanfeng , Zhang Mingyu , Wang Guanyun , Yang Jigang
Published: July 2023

Patients with coronavirus disease 2019 (COVID-19) might cause long-term burden of insomnia, while the common pathogenic mechanisms are not elucidated. The gene expression profiles of COVID-19 patients and healthy controls were retrieved from the GEO database, while gene set related with circadian rhythm were obtained from Genecards database. 76 shared genes were screened and mainly enriched in cell cycle, cell division and cell proliferation, and 6 hub genes were found out including CCNA2, CCNB1, CDK1, CHEK1, MKI67 and TOP2A, with positive correlation to plasma cells. In the TF-gene regulatory network, NFYA, NFIC, MEF2A and FOXC1 showed high connectivity with hub genes. This study identified six hub genes and might provide new insights into pathogenic mechanisms and novel clinical management strategies.
Twin-boundary engineering boosted undercoordinated active sites for scalable conversion of CO2 to ethylene
Authors: Voiry Damien , Zhang Yang , Lyu Pengbo , Petit Eddy , WU Huali , Wang Wensen , Ma Jingyuan , Wang Ying , Zhang Xiaolin , Salameh Chrystelle , Qi Kun
Published: July 2023

The development of highly selective and energy efficient technologies for electrochemical CO2 reduction combined with renewable energy sources holds great promise for advancing the field of sustainable chemistry. The engineering of copper-based electrodes provides a pathway for the conversion of CO2 into high-value multicarbon products (C2+). However, the ambiguous determination of the intrinsic CO2 activity and the maximization of the density of exposed active sites have severely limited the use of Cu for the realization of practical electrocatalytic devices. Here, we report a scalable strategy to obtain a high density of undercoordinated sites by maximizing the exposure of twin-boundary active sites using a direct chronoamperometric pulse method. Our numerical investigations predicted that twin-boundaries modulate the adsorption behavior of *CO on the Cu surface, which acts as a key intermediate species associated with the production of multicarbon species. We investigated the consequence of twin-boundary density on dendric Cu catalysts (TB-Cu) by combining transmission electron microscopy, in-situ Raman and X-ray photoelectron spectroscopy with detailed electrochemical measurements. A linear relationship between the Faradaic efficiency of the C2+ product and the presence of under-coordinated sites was observed, which allowed to directly quantify the contribution of the twin-boundary in Cu-based catalysts on the CO2RR properties and the formation of multicarbon products. Using a membrane electrode assembly electrolyzer, the high twin-boundary density Cu electrodes achieve a maximum Faradaic efficiency of 73.2 % for C2+ product formation and a full cell energy efficiency of 20.2 % at a specific current density of 303.6 mA cm-2. The TB-Cu was implemented in a 25 cm2 MEA electrolyzer and demonstrated selectivity of over 62 % for 70 hours together with current retention of 88.4 % at the applied potential of -3.80 V. The catalysts and electrolyzer were further coupled to an InGaP/GaAs/Ge triple-junction solar cell to demonstrate a solar-to-fuel (STF) conversion efficiency of 8.33 %. This work opens new avenues for the design of an undercoordinated Cu-based catalyst for the realization of solar-driven fuel production.
Exogenous systemin peptide treatment in olive alters Bactrocera oleae (Diptera, Tephritidae) oviposition preference
Authors: Sánchez Luiza , Cunha Ana E. , Rodrigues Nuno , Pereira José Alberto , Baptista Paula
Published: July 2023

The olive fruit fly, Bactrocera oleae (Rossi), is a key pest of the olive crop, whose control relies mostly on the use of insecticides. Plant peptides may represent a more environmentally-friendly tool to manage olive fly, due to their recognized role to activate and/or prime plant defence responses against pests. In this work, behavioural experiments (no-choice and two-choice) and analysis of volatile compounds were carried out in order to evaluate the impact of the exogenous application of the peptide systemin to olive tree on olive fly infestation, and to elucidate its mode of action to prime plant defence. The treatment of olive branches with 10 nM systemin showed to confer protection against olive fly, by reducing significantly the ovipositions (up to 3.0-fold) and the number of infested fruits (up to 2.9-fold) when compared to not-treated branches. This protective effect was even detected in neighbouring not-treated branches, suggesting the ability of systemin to trigger plant-to-plant communication. The deterrent activity of the primed olives was associated with the emission of the volatiles 2-ethyl-1-hexanol, 4-tert-butylcyclohexyl acetate and 1,2,3-trimethyl-benzene, which were negatively correlated with oviposition and fly infestation. Systemin also showed to trigger the biosynthesis of specific volatiles (esters) in olives in response to fly attacks. Overall, the observed protection conferred by systemin against olive fly is likely due to the emission of specific volatiles that can act as a defence and/or as signalling molecules to upregulate the plant defence response. Thus, systemin represents a novel and useful tool to manage olive fruit fly.
On surface of Apollonius
Authors: Végh Attila
Published: July 2023

Apollonius defined the circle as the set of points that have a given ratio $\mu$ of distances from two given points, where $\mu\not=1$. Generally, consider two $0$-symmetric, bounded, convex bodies $K$ and $K'$, which define two norms, whose unit balls are $K$ and $K'$. The surface of Apollonius is the set of points equidistant from centers of bodies $K$ and $K'$ with respect to these norms. We prove that the surface of Apollonius of two ellipsoids is a quadratic surface and we examine when this surface becomes a sphere.
Mathematics Subject Classification (2010). Primary 51N20, 52A20; Secondary 51N10, 52A10.
Optimization on Manifold Injection in DI Diesel Engine Fuelled with Acetylene
Authors: Sonachalam M , Manieniyan V , Senthilkumar R , Sıngh J Anıx Joel
Published: July 2023

Researchers proved that implementing new combustion technology and optimizing fuel quantity results in a significant reduction in conventional fossil fuel usage as well as emission levels. One of the low temperature combustion technologies is the Reactivity Controlled Compression Ignition combustion strategy, which is used to lower the overall combustion temperature and provide better control over the combustion. This study focuses on Reactivity Controlled Compression Ignition combustion technology, which is fueled by conventional diesel fuel as a high reactivity fuel injected through the injector and acetylene gas as a low reactivity fuel injected through the modified inlet manifold along with air to the cylinder. The modified engine setup was carried out for performance, emission and combustion tests under different load conditions, as well as different mass flow rate of acetylene gas as a low reactivity fuel which is injected along with air. The flow field of the low reactivity fuel at the inlet manifold is analyzed using the Computational Fluid Dynamics principle, which is used to select the optimum flow rate to improve combustion quality. According to the simulation results, the optimized flow rate of acetylene is 3 Liters Per Minute, and according to the experimentation, at 3 Liters Per Minutes acetylene injection, the brake thermal efficiency is improved by about 3.7%, and emissions such as Carbon Monoxide, Hydro Carbon, smoke intensity, and Oxides of Nitrogen are reduced by about 35%, 17%, 10%, and 21%, respectively.
Deep embedding clustering based on residual autoencoder
Authors: Li Mengli , Cao Chao , Li Chungui , Yang Shuhong
Published: July 2023

Clustering algorithm is one of the most widely used and influential analysis techniques. With the introduction of deep learning, deep embedding clustering algorithm has been developed rapidly and achieved good results. Much depends on the potential expression captured by the autoencoder network. Therefore, the quality of the potential expression directly determines the performance of the algorithm. In view of this, researchers have proposed many improvements. Although the performance has been slightly improved, they all have one shortcoming, that is, too much emphasis is placed on the original data reconstruction ability during the process of feature expression, which greatly limits the further expression of potential features according to specific clustering tasks. Moreover, there is a large amount of noise in the original data, so blindly emphasizing reconstruction will only backfire. Hence, we innovatively propose a deep embedding clustering algorithm based on residual autoencoder (DECRA) after in-depth research. Specifically, a novel autoencoder network with residual structure is proposed and introduced into deep embedded clustering tasks. The network introduces an adaptive weight layer in feature representation z, which can make it have good robustness, generalization for specific tasks, and adaptive learning of better feature embeddings according to category classification. In this paper, the reasons for the validity of this structure are explained theoretically, and comprehensive experiments on five benchmark datasets including various types show that the clustering performance of the DECRA is very competitive and significantly superior to the most advanced methods.
Investigation of functionalized magnetic graphene oxide using glycine and hexamethylenediamine ligands to remove Pb 2+ from aqueous solutions
Authors: Zarei Mahmoud , Rostamzadeh Paria , Asgari Elham , Hosseinzadeh Mehdi
Published: July 2023

This work is reserved to the synthesis, characteristics, and evaluation of the adsorption efficiency of nanocomposite-based adsorbents based on functionalized magnetic graphene oxide. The chemical structure and bond formation, crystal structure, and pollutant absorption by the adsorbent were characterized by Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, and atomic absorption spectroscopy respectively. The optimization process was analyzed using CCD and RSM, taking into account four independent variables including adsorbent mass, initial pH solution, agitation time and Pb2+ concentration. A comparative analysis was carried out on functionalized magnetic graphene oxide samples with HMDA and Gly regarding Pb2+ removal. Investigating the kinetic and isotherm studies toward the adsorbent and its resumption in successive sorption and desorption cycles, it was observed that the adsorption processes follow second-order kinetics and Freundlich isotherm; thermodynamic studies, including Gibbs free energy changes, enthalpy, and entropy changes, show that the absorption process is spontaneous and exothermic. The maximum adsorption rate obtained have been found as 86% and 98.38% respectively for as-synthesized and functionalized adsorbent by Gly and HMDA with operational parameters including adsorbent mass (5–25 mg), initial solution pH (2–10), agitation time (5–45 min), and initial Pb2+ concentration (5–25 mg.L− 1), Therefore, the HMDA functionalized nanocomposite was realized to be an acceptable adsorbent for pb2+ from an aqueous solution.
Multiomics reveals the role of macrophage-vascular endothelial cell interactions in the hepatoblastoma tumor microenvironment
Authors: Zhu Qian , Xie Yuwei , Qiu Kang , Wu Tingting , Zhang Peng , Sun Xinxin , Wang Hongli , Ji Ming , Hao Xiwei , Zhu Chengzhan
Published: July 2023

Background
Hepatoblastoma is a common tumor in childhood, characterized by immature histology and diverse cell lineages. The purpose of this study is to identify the genes that are abnormally expressed in hepatoblastoma, and to explore and verify the targets of intercellular communication that affect the tumor immune microenvironment.
Methods
Through comprehensive analysis of gene expression from GSE133039 and GSE180664 data sets, the differentially expressed genes in cancer tissues and adjacent tissues were obtained. GO and KEGG enrichment analysis is used to predict the biological function and signal transduction pathway of differential expression gene enrichment. Use cytoscape to build PPI network to filter hubgene; Construct correlation analysis of immune cell infiltration to infer the correlation between immune cells. Combined with single-cell transcriptome data, further reveal the relationship between cells and signal targets of cell communication.
Results
58 differentially expressed genes with high expression and 94 differentially expressed genes with low expression were obtained from the two data sets of hepatoblastoma. They were mainly involved in the signal transduction related to metastasis. PPI network screened 50 hubgenes. The correlation analysis of immune cell infiltration of different genes showed that macrophages were significantly correlated with endothelial cells. Combined with the analysis of single-cell transcriptome data, hepatoblastoma was divided into 11 cell subpopulations, and 16 genes in hubgene were expressed in different cell subpopulations, in which LFNG was highly expressed in macrophages and monocytes, which served as the target of intercellular communication to promote the development of hepatoblastoma.
Conclusion
In this study, we identified the genes that were abnormally expressed in hepatoblastoma, and affected the cellular communication of hepatoblastoma through LFNG target, thus affecting the progress of tumor. Therefore, LFNG may become a therapeutic target for hepatoblastoma.
Home Range, Site Fidelity, and Movements of the Timber Rattlesnake (Crotalus horridus) in West-Central Illinois
Authors: Eckert Scott A. , Jesper Andrew C.
Published: July 2023

Understanding the home range of reptiles is important to their conservation and recovery efforts. Despite numerous home range studies for the imperiled timber rattlesnake (Crotalus horridus), only a single study has been undertaken in the central midwestern United States. We report on the home range size, site fidelity, and movements of this species in west-central Illinois. Using VHF telemetry, we located 29 C. horridus (13 female, 16 male) every 1.3 days over a 5-year period for 51 years ofrecords of the species' locations and movements. We calculated annual home ranges for each snake per year using 99%, 95%, and 50% isopleths derived from Brownian Bridge utilization distributions, and we also report 100% minimum convex polygons for comparison with other studies. We examined the effects of sex, mass, SVL, and year on home range sizes and reportedon movement metrics as well as home range fidelity using both UDOI and BA statistics. The homerange sizes for male and non-gravid C. horridus were 56.91 Ha (CI = 41.04-72.77) and 20.22 (CI = 3.81-36.62) for 95% BBMM; 7.56 Ha (CI = 5.47-9.65) and 2.36 Ha (CI = 0.19-4.53) for 50% BBMM; and 80.03 Ha (CI = 50.95-109.11) and 30.80 Ha (CI = 1.55-60.06) for MCP. The estimated daily distance traveled was significantly greater for males (mean = 57.25 m/day, CI=49.06-65.43) than females (mean = 27.55 m/day, CI = 18.99-36.12). Similarly, maximum displacement distances from hibernacula were significantly greater for males (mean = 2.03 km, CI = 1.57-2.48) than females (mean = 1.29 km, CI = 0.85-1.73], and on average, males were located further from their hibernacula throughout the entirety of their active season. We calculated habitat fidelity using 11 snakes that were tracked over multiple years. The mean BBMM overlap using Bhattacharyya's Affinity (BA) for all snakes at the 99%, 95%, and 50% isopleths was 0.46 (SE=0.03), 0.38 (SE=0.03), and 0.08 (SE=0.02), respectively. The mean BBMM overlap for all snakes using the Utilization Distribution Overlap Index (UDOI) at the 99%, 95%, and 50% isopleths was 0.78 (SE=0.13), 0.41 (SE=0.03), and 0.09 (0.02), respectively. Our results are largely consistent with those of other studies in terms of home range sizes and theinfluence of sex on those home ranges and distances traveled. The species also exhibits strong site fidelity with snakes generally using the same habitats each summer. Particularly interesting was the tendency for snakes to disperse from specific hibernacula in the same general direction to the same general areas. We propose some possible reasons for this dispersal pattern.
Effectiveness of Endoscopic Screening in Reducing Esophageal Cancer Mortality: A Nested Case-control Study
Authors: LU Youhua , Qi Yuantao , MA Siqi , YANG Jia , ZHAO Li , ZHAO Deli , MA Guifeng , ZHANG Nan , MA Anning , WANG Jialin
Published: July 2023

Purpose To evaluate the effectiveness of endoscopic screening in reducing esophageal cancer mortality within a high-incidence area.
Methods A nested case-control study was conducted based on the Upper Gastrointestinal Cancer Screening Program of Feicheng City. Based on the screening population cohort, individuals who were newly diagnosed with esophageal cancer from September 2006 to December 2016 and died of esophageal cancer before December 2018 as case subjects. Each case matched 4 controls (Subjects who were alive on the date of death of the corresponding case) based on age, gender and screening village. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated via conditional logistic analysis.
Results This study included 345 cases (270 men and 75 women) and 1380 matched controls (1,080 men and 300 women). Compared with individuals who were never screened, the total ORs was 0.52(CI 0.39-0.70) for participants, the OR of screened subjects 40 to 49 years old was 0.34 (CI 0.17-0.67), and the OR for dying from esophageal cancer among individuals who were diagnosed 2 to 4 years was 0.30 (CI 0.17-0.53).
Conclusions Participating in endoscopic screening could reduce the risk of death from esophageal cancer by 48%. The screening effect was related to the age of screening and the period from the screening to the date of diagnosis.
Development and validation of a machine learning model for bone metastasis in prostate cancer: Based on inflammatory and nutritional indicators
Authors: Jin Tongtong , An Jingjing , Wu Wangjian , Wang Chao , Zhou Fenghai
Published: July 2023

Purpose
Application of machine learning in bone metastasis of prostate cancer based on inflammation and nutritional indicators.
Methods
Retrospective analysis the clinical data of patients with prostate cancer initially diagnosed in the Department of Urology of Gansu Provincial People's Hospital from June 2017 to June 2022. Logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) are used to jointly screened the model features. The filtered features are incorporated into algorithms including LR, random forest (RF), extreme gradient boosting (XGBoost), naive nayes (NB), k-nearest neighbor (KNN), and decision tree (DT), to develop prostate cancer bone metastasis models.
Results
A total of 404 patients were finally screened. Gleason score, T stage, N stage, PSA and ALP were used as features for modeling. The average AUC of the 5-fold cross-validation for each machine learning model in the training set is: LR (AUC = 0.9054), RF (AUC = 0.9032), NB (AUC = 0.8961), KNN (AUC = 0.8704), DT (AUC = 0.8526), XGBoost (AUC = 0.8066). The AUC of each machine learning model in the test set is KNN (AUC = 0.9390, 95%CI: 0.8760 ~ 1), RF (AUC = 0.9290, 95%CI: 0.8718 ~ 0.9861), NB (AUC = 0.9268, 95%CI: 0.8615 ~ 0.9920), LR (AUC = 0.9212, 95%CI: 0.8506 ~ 0.9917), XGBoost (AUC = 0.8292, 95%CI: 0.7442 ~ 0.9141), DT (AUC = 0.8057, 95%CI: 0.7100 ~ 0.9014). A comprehensive evaluation of the DeLong test among different models and each evaluation metric shows that KNN is the best machine learning model in the study.
Conclusion
A bone metastasis model of prostate cancer was established, and it was observed that indicators such as inflammation and nutrition had a weak correlation with bone metastasis.
Investigating alcohol consumption in China via Wastewater-based Epidemiology
Authors: Yao Yan , Wang Jingya , Zhong Yuling , Chen Wenyu , Rao Yulan , Su Mengxiang , Di Bin
Published: July 2023

Alcohol abuse and addiction remain priority public health issues worldwide. Accurate estimation of alcohol prevalence is increasingly challenging due to the time-consuming and labor-intensive nature of traditional survey methods. This study examined alcohol consumption in major cities of China via Wastewater-based epidemiology(WBE) and compared WBE estimates with other data sources. A simple and valid ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed for the determination of two alcohol metabolites, ethyl glucuronide (EtG) and ethyl sulfate (EtS) in wastewater. The optimized method was applied to 62 sewage samples collected from wastewater treatment plants (WWTPs) in 31 provincial capital cities across China in the fourth quarter of 2020. The methodology established in this study was validated with the lower limit of quantification (LLOQ) up to 0.1 µg/L, good linearity in the range of 0.1–50 µg/L, intra-day and inter-day precision less than 5.58% and 5.55%, respectively, and the recoveries of the extracts were higher than 97.14%. The consumption range of alcohol estimated via WBE was 1.23 ~ 18.18 mL ethanol/person /day (EPD) in the capital cities of China. There was a significant difference in alcohol consumption among cities and WBE estimates of alcohol consumption were lower than WHO survey results and higher than foreign countries. The investigation of alcohol consumption based on WBE is very potential, which can complement objective information for estimating the consumption of alcohol.
The Ethanol-Producing Enterocloster bolteae and Limosilactobacillus fermentum are enriched in Nonalcoholic steatohepatitis
Authors: MBAYE Babacar , WASFY Reham MAGDY , BORENTAIN Patrick , TIDJANI Maryam , MOTTOLA Giovanna , BOSSI Vincent , CAPUTO Aurelia , RAOULT Didier , GEROLAMI Rene , MILLION Matthieu
Published: July 2023

Background: Non-alcoholic steatohepatitis (NASH) has become a major public health issue. In fact, it is one of the leading causes of disturbed liver function and liver transplantation worldwide. Its link with the intestinal microbiota is still topical, and the production of endogenous ethanol following dysbiosis of the microbiota - one of the mechanisms linked to the disease - has been shown in several studies. In this study, we analyzed stool samples from 41 NASH patients and 24 healthy controls using culturomics and 16S rRNA targeted metagenomics to identify the microbial profile associated with each group. Fecal ethanol concentration was also determined for all samples.
Results: We identified 358 different bacterial species using the culturomics approach distributed into 11 phyla and 143 genera. With a significant difference, 12 appeared significantly more frequently in the NASH group and 4 more frequently in the control group. Finegoldia magna was the most detected in NASH patients (10/14 (71%)), and 2 ethanol producing strains: Limosilactobacillus fermentum and Enterocloster bolteae.
Metagenomics shows an enrichment of Lactobacillus and Streptococcus and a microbial profile identical to that of the culture. With regard to the species, there was an elevated frequency of ethanol-producing bacteria in NASH patients, and the concentration of ethanol was also higher in the stools of NASH patients compared to healthy controls (bilateral Mann-Whitney test, p=value 0.0145). However, compared with metagenomics, only the culture showed enrichment of Enterocloster bolteae in NASH patients.
Conclusions: Culturomics and metagenomics are complementary methods for exploring the microbiota. Our results suggest that enrichment of ethanol-producing bacteria in NASH patients may play an instrumental role in the pathogenesis of the disease.
Patient-derived ex vivo cell culture growth dynamics predict recurrence probability in patients with atypical and anaplastic meningiomas
Authors: Bissolo Marco , Masalha Waseem , Scheffler Pierre , Steiert Christine , Sankowski Roman , Beck Jürgen , Schnell Oliver , Heiland Dieter Henrik , Grauvogel Jürgen
Published: July 2023

Purpose
The prediction of recurrence in meningiomas is limited by the lack of ex vivo meningioma models. By introducing a novel patient-derived ex vivo cell culture model, we aimed to utilize cell growth dynamics to predict recurrence patterns.
Methods
Tissue samples were collected from patients who underwent meningioma resection at our department between April 2021 and November 2021 immediately after tissue harvesting. After establishing a novel cell culture procedure in a modified DMEM medium, histopathological analysis, and immunohistochemistry were performed. Population doubling time and cell growth rate were measured during the 38-day observational period. The mean clinical follow-up was 18 months. Clinical and radiological examinations were conducted before surgery and three and 15 months after tumor resection.
Results
A patient-derived ex vivo cell culture model was successfully established for 21 of 29 samples of central nervous system-World Health Organization (WHO) grade 1–3 meningiomas. The population doubling time and two-week ex vivo model survival differed significantly among malignancy grades (p = 0.010). Viability at the second week of culture correlated with WHO grade (p = 0.024). A positive population doubling time at the second week and a population doubling time of < 200 hours were correlated with relapsing disease within 15 months (p = 0.013).
Conclusion
As early as the end of the second week of cell culture, growth dynamics may provide prognosis data for atypical and anaplastic meningiomas. Further studies of cell growth patterns may support therapeutic decisions in patients with meningiomas when molecular analysis cannot be performed.
Contribution of wastewater irrigated vegetables to the prevalence of soil- transmitted helminth infection among female farmers in Addis Ababa, Ethiopia
Authors: Gurmassa Bethelhem kinfu , Gari Sirak Robele , Solomon Ephrem Tefera , Goodson Michaela L. , Walsh Claire L. , Dessie Bitwe K. , Alemu Bezatu Mengistie
Published: July 2023

Background
Many farmers in and around Addis Ababa city rely on untreated wastewater for irrigation due to a growing population and limited access to reliable agricultural water sources. However, data on STH contamination of irrigated vegetables and farmer risk are scanty. This study aimed to determine the prevalence of STH in vegetables and female farmer stool samples in Ethiopia, as well as the association between helminths in vegetables and female farmers' stool.
Methods
A cross-sectional study was conducted between November 2021 and February 2022 to investigate the prevalence of helminths in vegetable samples and stool samples of female wastewater irrigated vegetable growers. A stratified random sampling technique was employed to select farming households. The sample size for each district was set by a proportionate allocation to the total number of homes. Two hundred fifty-two composite samples and 101 stool samples from the wastewater-irrigated farm were collected and analyzed. A questionnaire was utilized to collect qualitative data, while vegetable samples were used to obtain quantitative data. Stata version 14.0 was used to process the data. Using Poisson regression, the relationship between helminths in vegetable samples and farmer health was studied. Statistical significance was set at p-value < 0.05.
Result
STH were found in 67.5% of the vegetables and 20.8% of the female farmers' stools. Significant concentrations of Ascaris lumbricoides (vegetable 48.4% and stool 9.9%) were identified in all analyzed samples, followed by hookworm (vegetable 13.1% and stool 8.9%) and Trichuris trichiura (vegetable 5.9% and stool 2%). The presence of helminths in wastewater-irrigated vegetables and the level of infection in exposed farmers had a statistically significant positive association (p < 0.05).
Conclusion
Vegetables grown with wastewater irrigation are contaminated with STH, which could be a source of infections for farmers. Therefore, in addition to reducing occupational exposure, risk reduction programs should target households that have no knowledge how to prevent the spread of helminths.