bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carbon Storage Dynamics and its Economic Values in Tropical Moist Afromontane Forests, South-West Ethiopia
Authors: Tadese Semegnew , Soromessa Teshome , Aneseyee Abreham Berta , Gebeyehu Getaneh , Noszczyk Tomasz , Kindu Mengistie 
Published: February 2023

Abstract
Forest plays an important role in the global carbon cycle by sequestering carbon dioxide and thereby mitigating climate change. In this study, an attempt has been made to investigate the effects of land use/land cover (LULC) change (1989–2017) on carbon stock and its economic values in tropical moist Afromontane forests of the Majang Forest Biosphere Reserve (MFBR), south –west Ethiopia. Systematic sampling was conducted to collect biomass and soil data from 140 plots in MFBR. The soil data were collected from grassland and farmland. InVEST modelling was employed to investigate the spatial and temporal distribution of carbon stocks. Global Voluntary Market Price (GVMP) and Tropical Economics of Ecosystems and Biodiversity (TEEB) analysis was performed to estimate economic values (EV) of carbon stock dynamics. Correlation analysis was also employed to identify the relationship between environmental and anthropogenic impacts on carbon stocks. The results indicated that the above-ground biomass and soil organic carbon stocks were higher than the other remaining carbon pools in MFBR. The total carbon stock (32.59 Mt ha–1) in 2017 was lower than 1989 (34.76 Mt ha–1). The EV of carbon stock in 2017 was lower than in 1989. Elevation, slope, and harvesting index are important environmental and disturbance factors resulting in major differences in carbon stock among study sites in MFBR. The correlation analysis for elevation showed a positive relationship with soil carbon stocks (r = 0.39) and aboveground biomass (r = 0.08), while a negative relationship was found for slope (r = –0.04) and harvesting index (r = –0.21). This calls for urgent attention to implement successful conservation and sustainable use of forest resources in biosphere reserves.
Nitrogen-Enriched Organic fertilizer (NEO) elevates nitrification rates shortly after application but has no lasting effect on nitrification in agricultural soils
Authors: Mousavi Hesam , Solberg Svein Øivind , Cottis Thomas , Dörsch Peter 
Published: February 2023

AbstractIn times of growing population, scarcity of arable land, and increasing use of synthetic nitrogen, new sustainable fertilizers are needed to enhance the resilience of global agri-food systems. Nitrogen-Enriched Organic fertilizer (NEO) is an example of a potentially sustainable fertilizer. Dinitrogen (N2) is captured from the air by a plasma process and mixed as nitrate (NO3−) and nitrite (NO2−) with animal slurries or other liquid organic fertilizers. This process strongly acidifies the slurry, which, together with the resulting high NO2−content, may result in toxic inorganic or organic N compounds. Here we test the effect of NEO produced from cattle slurry and biogas digestate on soil nitrification, i.e., the conversion of NH4+to NO2−and NO3−mediated by aerobic autotrophic bacteria and archaea. We compared potential nitrification rates by laboratory incubation in soil samples from two trials (cereal and grass) fertilized with NEO and other fertilizers for two consecutive years. We also studied the immediate nitrification response to NEO in 73-hour bottle incubations. In agitated soil slurries, NEO strongly stimulated nitrification rates irrespective of feedstock (more than 2-fold), exceeding rates in ammonium controls. In loosely placed soil, a similar pattern was found, but this time ammonium chloride also resulted in high nitrification rates. By contrast, differences in nitrification rates between field-fertilized soil samples were minimal and negligible. Therefore, we conclude that despite the intense stimulation of nitrification by NEO right after application to soil, NEO has no long-lasting effects on nitrification under field conditions. This implies that NEO does not impose adverse effects on soil nitrifier communities.
WITHDRAWN: Evaluation of Surface Roughness and Color Changes of Restorative Materials Used with Different Polishing Procedures in Pediatric Dentistry
Authors: PEKER Oyku , BOLGUL Behiye 
Published: February 2023

Abstract
Aim: It was aimed to evaluate the color stability and surface roughness properties of 4 different restorative materials used in pediatric dentistry clinics as a result of 4 different polishing procedures.
Background and Design: A total of 128 samples, 32 from each restorative material, were prepared by placing each material in 6 mm diameter, 2 mm high polyethylene molds to be polished with 4 different polishing procedures (n=8). Then, color stability and surface roughness measurements of the samples were made. Hysitron TI 950 TriboIndenter device was used for surface roughness test measurements. A spectrophotometer device was used to determine the color stability. Then the samples were kept in the coke solution for 1 week and then the final color measurements were made.
Results:The lowest roughness values ​​were surveyed in G-aenial restorative material polished with Super-Snap material, and the highest roughness values ​​were surveyed in Equia material polished with Identoflex material. When all materials were evaluated, the least color change values ​​were determined in G-aenial material polished with Super-Snap, and the most color change values ​​were detected in Equia material polished with Identoflex. It was observed that the relationship between surface roughness and color change is statistically significant.
Conclusion: The lowest color change and surface roughness values were observed in the G-aenial material polished with Super-Snap. For clinically more successful results, it has been understood that the most appropriate polishing procedure should be chosen based on the restorative material used.
Associations between health factors and food insecurity. A multidimensional analysis with fuzzy set approach
Authors: Flores Lucio 
Published: February 2023

Abstract
Background: Food insecurity, which is one of many factors to consider when studying loss of health, is an important problem in Mexico and many countries around the world. Much insight may be gained into how population health in Mexico is affected by studying these factors.
Methods: Two multidimensional indices were calculated, the first was the multidimensional health index, constructed using 6 factors: excess weight, diabetes, high blood pressure, symptoms of depression, kidney problems and heart problems, and the second was the food insecurity index with three levels, mild, moderate, and severe food insecurity. The multidimensional health index is constructed with the use of fuzzy sets, through the National Health and Nutrition Survey (ENSANUT 2018-19 - for its acronym in Spanish) in Mexico.
Results: The results show a close relationship between these indices and elucidate a specific profile of individuals in which there is a higher prevalence of health loss in relation to severe food insecurity.
Conclusions: This study aims to elucidate the current state of health of the population in Mexico using the most up-to-date data provided by the autonomous public body for statistics and geography to build a multidimensional panorama, as well as the close relationship between food security and the loss of health.
Study of catalytic properties of pristine and Au-modified BaTiO3(001) through DFT calculations for CO hydrogenation
Authors: Comparán-Padilla Víctor E. , Cruz María Teresa Romero-de la , García-Díaz Reyes , Pérez-Camacho Odilia 
Published: February 2023

Abstract
Context.
BaTiO3 is one of the most important ferroelectric oxides in the electronic applications. Also, it has attractive properties for catalysis that could be used for reducing the contamination levels especially carbon monoxide, CO. CO is one of the main gaseous pollutants generally released from the combustion of fossil fuel. In this work, the catalytic properties of pristine and Au-modified BaTiO3 perovskite for CO hydrogenation are studied. The CO adsorption and hydrogenation on pristine BaTiO3 leads to formaldehyde synthesis as the most stable product through two possible routes. Further hydrogenation stages are less probable. On Au-modified BaTiO3 formaldehyde is the principal product too but Au adatom induces selectivity making just one reaction route as the most stable. After BaTiO3 modification with Au unpaired electrons were generated. These unpaired electrons increased the adatom reactivity. According to the obtained results, pristine and Au-modified BaTiO3 can adsorb and hydrogenate CO generating formaldehyde as the principal product. BaTiO3 modifications with Au increases the reactivity and selectivity of the perovskite in the CO hydrogenation reactions.
Methods.
The study was performed through ab initio calculations using the periodic Density Functional Theory (DFT) as implemented in Quantum ESPRESSO. DFT calculations were carried out using the Plane Wave self-consistent field (PWscf). Spin density was considered for systems with unpaired electrons. Plane wave basis set was used to represent the electron states. Vanderbilt pseudopotentials with nonlinear core correction were used to model the interaction of ionic cores and valence electrons. Exchange-correlation energies were treated within the generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerhof (PBE) parameterization.
Estimating The Volume Of Civil Construction Materials By Machine Learning Models
Authors: Pham Vu Hong Son , Nguyen Ngo Luan 
Published: February 2023

Abstract
Previous construction project cost models, especially in the project initiation phase, often mainly focused on estimating the total project cost without taking into account their constituent aspects such as materials, labor, machineries and equipment. Therefore, building a material quantity estimation model will have a positive impact on improving the accuracy of the total project cost. There have been many studies related to this issue, but there are few studies on building a model to estimate the quantity of materials for civil projects with reinforced concrete structures and they use specialized software (which is difficult to access for many subjects in the construction industry). The founding of many machines learning software, especially Weka software, helps to model with powerful algorithms with high reliability. In this study, suitable machine learning models will be proposed for estimating the quantity of materials as: concrete, formwork, steel of the components: foundation, column, beam and floor. Suitable machine learning models will be suggested to rank for each different model.
Analysis of Thaumatotibia leucotreta (Lepidoptera; Tortricidae: Olethreutinae) mitochondrial genomes reveal opportunistic host range expansion towards rose
Authors: de Vossenberg Bart T.L.H. van , Noort Tom H. van , Hooiveld-Knoppers Sanne H.Z. , Gouw Lucas van der , Mertens Jan E.J. , Loomans Antoon J.M. 
Published: February 2023

Abstract
Background
The false codling moth (FCM), Thaumatotibia leucotreta (Meyrick, 1913), is a significant pest of various important economic crops and is a EU quarantine pest. In the last decade the pest has been described on rose. In this study we determined whether this shift occurred within specific FCM populations across the Ethiopian zoogeographic region or whether the species opportunistically switches to this novel host as it presents itself. To achieve this we assessed the genetic diversity of complete mitogenomes of T. leucotreta specimens intercepted at import and analysed potential linkages with geographical origin and host species.
Results
Genomic, geographical and host information were integrated in a T. leucotreta Nextstrain build which contains 95 complete mitogenomes generated from material intercepted at import between January 2013 and December 2018. Samples represented seven sub-Saharan countries and mitogenomic sequences grouped in six main clades.
Discussion
If host strains of FCM would exist, specialization from a single haplotype towards the novel host is expected. Instead, we find specimens intercepted on rose in all six clades. Absence of linkage between genotype and host suggests opportunistic expansion to the new host crop. This underlines risks of introducing new crop species to an area as the effect of pests already present on the new crop might be unpredictable with current knowledge.
On-farm Production &amp; Bio-efficacy Study of ‘Baif Elixer’ Biofertilizer on Momordica Charantia
Authors: Sawane Rutuja , Shinde Suryakant , Shinde Manisha 
Published: February 2023

Abstract
Today’s agriculture sector requires reducing dependency on chemical fertilizers and increasing the use of bio-based formulations for implementing organic farming practices. In organic farming, the role of bio-fertilizers, bio-pesticides, and growth stimulants is crucial, but the availability of bio-based products in larger quantities always remains a constraint. Hence the purpose of this study is to formulate a microbial-based bio-fertilizer formulation ‘BAIF ELIXER’ & evaluation of its bio efficacy infield trials. Six types of microbial cultures, potential as N2 fixers, phosphate solubilizers, and bio stimulants from BAIF Development Research Foundation were cultivated in a 200 L fermenter and used to develop a BAIF ELIXER bio-fertilizer formulation. The final count of 1X109 CFU/ml was used to develop an on-farm liquid bio-fertilizer BAIF ELIXER formulation. To study its bio-efficacy, seed and on-farm treatment were conducted on Momordica charantia on 900 plants planted in a 0.13 hector area for each treatment in Research Farm, Pune. During the field experiment, plant growth and yield were recorded for 7 consecutive harvests at four days intervals. BAIF ELIXER on-farm treatment produces the highest yield of 997 kg at the 7th harvest. Both seed and on-farm treatment give higher yield as compared to control plots. As a result, the crops can be produced organically with the combined application of biofertilizer for sustainable crop development. The study will help to understand the role of beneficial microbes in agriculture in improving organic farming practices.
Identification and analysis of DNA methylation inflammation related key genes in intracerebral hemorrhage
Authors: Xu Sanpeng , Wu Qiong , Li Ping 
Published: February 2023

Abstract
Background: Inflammation and DNA methylation have been reported to play key roles in intracerebral hemorrhage (ICH). The proposed study intended to investigate new diagnostic biomarkers associated with inflammation and DNA methylation through comprehensive bioinformatics approaches.
Methods: GSE179759 and GSE125512 were sourced via the Gene Expression Omnibus (GEO) database, and 3222 inflammation-related genes (IFRGs) were downloaded from the Molecular Signatures Database (MSigDB). Key differentially expressed methylation-regulated and inflammation-related genes (DE-MIRGs) were achieved by overlapping methylation-regulated differentially expressed genes (MeDEGs) between ICH patients and control samples, module genes from Weighted Correlation Network Analysis (WGCNA), and the IFRGs. The functional annotation of DE-MIRGswas performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) resources. A protein-protein interaction (PPI) network was further constructed to clarify the interrelationships between the different DE-MIRGs. The key genes were categorized by Least Absolute Shrinkage Selection Operator (LASSO), and support vector machine recursive feature elimination (SVM-RFE), and subsequently performed Gene Set Enrichment Analysis (GSEA).
Results: A number of 22 DE-MIRGs were acquired among 451 MeDEGs, 3222 IFRGs and 302 module genes, and they were mainly enriched in GO terms of wound healing, blood coagulation and hemostasis; KEGG pathways of PI3K-AKT signaling pathway, Focal adhesion, and Regulation of actin cytoskeleton. A PPI network with 22 nodes and 87 edges was constructed based on the 22 DE-MIRGs, and 11 of them were selected for the following key gene selection. Moreover, 2 key genes (SELP and S100A4) were obtained according to LASSO and SVM-RFE. Finally, SELP was mainly enriched in Cell morphogenesis involved in differentiation, Cytoplasm translation, and Actin binding of GO terms, and the KEGG pathway including Edocytosis, Focal adhesion, and Platelet activation. S100A4 was major enriched in GO terms including Mitochondrial inner membrane, Mitochondrial respirasome, and Lysosomal membrane; Oxidative phosphorylation, Regulation of actin cytoskeleton, and Chemical carcinogensis-reactive oxygen species in KEGG pathways.
Conclusion: 22 DE-MIRGs were identified associated with inflammation and DNA methylation between ICH patients and normal controls, and 2 key genes (SELP and S100A4) were obtained and regarded as the biomarker for ICH, which could provide the research foundation for the further pathological mechanism investigation of ICH.
Carbon dots from natural‐product: applications as adsorbent and Sensing of Fe 3+ Ions
Authors: Shahraki Hesam Salimi , Ahmad Anees , Qurtulen Qurtulen , Gupta Sugandhi , Meraj Uzma 
Published: February 2023

Abstract
Freshwater contamination is a significant concern due to the increasing pollution by industrial activities. Dyes have a wide range of uses and are introduced at different stages of manufacture, raising the risk of unwanted human and environmental contact. Consequently, the demand for an effective method for removing dyes has become more important than before. In this context, Carbon dots have been synthesized by the green synthesis method from Coriander leaves (C-CDs) and used as a prospective adsorbent to remove (MB) methylene blue dye from aqueous solution. The as-synthesized C-CDs are characterized by HR-TEM, XRD, XPS, FTIR, Zeta potential, UV-visible, and Photoluminescence (PL). Effects of different controlling parameters such as adsorbent dosage, pH, contact time, and initial MB dye concentration were investigated. The highest adsorption efficiency (82.6%) and maximum adsorption capacity (96.05 mg/g) of MB were obtained at optimum conditions (303 K). The adsorption isotherm data could be fitted well by Freundlich model, and the experimental data fitted to the Pseudo-Second-Order kinetic model. It is worth noting that C-CDs exhibited excellent sensitivity and high fluorescence quenching effect on Fe3+ ions.
Alteration of PBMC transcriptome profile after interaction with multipotent mesenchymal stromal cells under “physiological” hypoxia
Authors: AN Gornostaeva , PI Bobyleva , ER Andreeva , Sh Gogiya B , LB Buravkova 
Published: February 2023

Abstract
Multipotent mesenchymal stromal cells (MSCs) have demonstrated a pronounced immunosuppressive activity, the manifestation of which depends on the microenvironmental factors, including O2 level. Here we examined the effects of MSCs on transcriptomic profile of allogeneic phytohemagglutinin-stimulated peripheral blood mononuclear cells (PBMCs) after interaction at ambient (20%) or “physiological” hypoxia (5%) O2. As revealed with microarray analysis, PBMC transcriptome at 20% O2 was more affected, which was manifested as differential expression of more than 300 genes, whereas under 5% O2 only 220 genes were changed. Most of genes at 20% O2 were downregulated, while at hypoxia most of genes were upregulated. Altered gene patterns were only partly overlapped at different O2 levels. A set of altered genes at hypoxia only was of particular interest. According Gene Ontology a part of above genes was responsible for adhesion, cell communication, and immune response. At both oxygen concentrations, MSCs demonstrated effective immunosuppression manifested as attenuation of T cell activation and proliferation as well as anti-inflammatory shift of cytokine profile. Thus, at a “physiological” hypoxia MSC immunosuppression is executed with greater efficacy, since the same result has been achieved through a change in the expression of a fewer genes.
Global stability to a chemotaxis-May-Nowak model with exposed state
Authors: Zhang Qingshan , Li Erhui 
Published: February 2023

Abstract
Note: Please see pdf for full abstract with equations.
This paper deals with the Neumann initial-boundary value problem for the chemotaxis-May-Nowak model with exposed state for virus dynamics
ut = Δu − χ∇ · (u∇v) + κ − d1u − βuw,
zt = Δz + βuw − (d2 + c)z,
vt = Δv + cz − d3v,
wt = Δw + kv − d4w
in a smooth bounded domain Ω ⊂ Rn (n ≥ 1). Here χ ∈ R and κ, β, c, k, di (i = 1, 2, 3, 4) are positive constants. We prove that for sufficiently smooth initial data the problem possesses a unique global classical solution which is uniformly bounded with small size of |χ|. Moreover, the large time behavior of the obtained solution is investigated with respect to the basic reproduction number as a threshold.
Mathematics Subject Classification (2010). 35A09, 35B40, 35K51, 92C17.
Non-Fungible Token Fraud: Studying security issues and improvements for NFTmarketplaces using hashing techniques
Authors: Lee Puiyue , Abubakar Mwrwan , Lo Owen , Pitropakis Nikolaos , Buchanan William J 
Published: February 2023

Abstract
In recent years, interest in Non Fungible Tokens (NFTs) has soared and the NFT market has experienced significant growth. Built upon blockchain technology, the tokens represent a unique offering, a rarity, due to its attributes of immutability, trust, transparency, auditability and anonymity. These unique tokens are highly appealing and sought after by investors and traders, since ownership rights, provenance and authenticity are publicly available. As a result, NFTs can be applied in a wide range of contexts and sectors. One such sector is in the digital art market, where sales of NFTs skyrocketed during 2021, thereby generating a multibillion dollar ecosystem. However, due to the fast-changing evolution of NFTs, the increase in demand for the tokens, high returns and lack of regulation, fraud has become commonplace and many security issues have arisen in the ecosystem. In this paper, we explore some of these security issues. Furthermore, by investigating Interplanetary File System (IPFS) and hashing techniques, namely cryptographic and perceptual image hashing, in more detail, proof of concept (PoC) models were built to aid in the identification and combat of NFT fraud.
Intelligent solid waste classification system using combination of image processing and machine learning models
Authors: Abu-Qdais Hani , Shatnawi Nawras , AL-Alamie Esra’a 
Published: February 2023

Abstract
Solid waste is a major issue in all countries around the world. Solid waste classification and segregation prior to reuse, recycling or recovery is an important step toward sustainable waste management. Traditional manual sorting of solid waste is a labour intensive process that may pose health risks to the workers. Currently, automated classification of solid waste using machine learning techniques are widely applied. This study is aiming to develop an automated waste classification model by testing traditional and deep machine learning models. To achieve that, both open (Trashnet) and generated datasets were used in the model training and testing. The study results showed relatively low prediction capability of the traditional machine learning models like Random Forest (RF) and Support Vector Machine (SVM) as compared to the deep machine learning Convolutional Neural Network (CNN). The testing of the three models on a combined data set of Trashnet with local garbage data set resulted in accuracy of 62.5% for SVM, 72.0% for RF and 92.7% for CNN. JONET deep learning model has been developed using a combination of pre-trained base model (DenseNet 201) with a new architicture that contains a fully connected layer in the classification stage with 1024 neurons. The model is capable to identify six classes of solid waste items with various accuracies. When tested on the Trashnet, the accuracy was 96.06%, while testing on the local garbage dataset gave an accuracy of 94.40%. JONET has been tested also on multi object images which gave an acceptable prediction accuracy.