bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic Multiwell Assessment of Flow-Related Petrophysical Properties of Tight-Gas Sandstones Based on the Physics of Mud-Filtrate Invasion
Authors: Bennis M. , Torres-Verdín C. 
Published: March 2023

Summary
Petrophysical interpretation of borehole geophysical measurements in the presence of deep mud-filtrate invasion remains a challenge in formation evaluation. Traditional interpretation methods often assume a piston-like radial resistivity model to estimate the radial length of invasion, resistivities in the flushed and virgin zones, and the corresponding fluid saturations from apparent resistivity logs. Such assumptions often introduce notable inaccuracies, especially when the radial distribution of formation resistivity exhibits a deep and smooth radial front. Numerical simulation of mud-filtrate invasion and well logs combined with inversion methods can improve the estimation accuracy of petrophysical properties from borehole geophysical measurements affected by the presence of mud-filtrate invasion.
We develop a new method to quantify water saturation in the virgin zone, residual hydrocarbon saturation, and permeability from borehole geophysical measurements. This method combines the numerical simulation of well logs with the physics of mud-filtrate invasion to quantify the effect of petrophysical properties and drilling parameters on nuclear and resistivity logs. Our approach explicitly considers the different volumes of investigation associated with the borehole geophysical measurements included in the interpretation. The new method is successfully applied to a tight-gas sandstone formation invaded with water-base mud (WBM). Petrophysical properties were estimated in three closely spaced vertical wells that exhibited different invasion conditions (i.e., different times of invasion and different overbalance pressures). Available rock-core laboratory measurements were used to calibrate the petrophysical models and obtain realistic spatial distributions of petrophysical properties around the borehole. This approach assumes that initial water saturation is equal to irreducible water saturation. Based on the calibrated petrophysical models, thousands of invasion conditions were numerically simulated for a wide range of petrophysical properties, including porosity and permeability. Based on the large data set of numerical simulations, analytical and machine-learning (ML) models were combined to infer unknown rock properties in each well. Mean-absolute-percent errors (MAPE) of the analytical and ML models for the estimation of water saturation in the virgin zone are 5% and 2%, respectively, while the MAPE of the analytical models for the estimation of residual hydrocarbon saturation is 10%. Synthetic and field examples are examined to benchmark the successful application and verification of the new interpretation method. Estimates of water saturation in the virgin zone using the new method are in good agreement with core-based models.
Investigating the genetic determination of clutch traits in Chinese local chicken breed
Authors: Wang Jie , Liu Zhansheng , Cao Dingguo , Liu Jie , Li Fuwei , Han Heguo , Han Haixia , Lei Qiuxia , Liu Wei , Li Dapeng , Wang Jianxia , Zhou Yan 
Published: March 2023

Abstract

Background:Egg-laying rate is the trait with the highest economic weight in breeding programs for laying hens. Egg-laying rate is associated with a clutch, which is defined as consecutive days of oviposition. Clutch traits can be used to describe the individual laying pattern and has been considered as a trait for selection. However, little is known about the uniformity of clutch traits.Methods:In this study, after estimating the genetic parameters for age at first egg (afe), body weight at first egg (bwfe), longest clutch until 52 week of age (maxC), the first week when the longest clutch starts (fwlCs), the last week of longest clutch ends (lwlCe), number of clutches (numC), the longest number of days without egg-laying until 52 week of age (lndwel), we identified single nucleotide polymorphisms (SNPs) and potential candidate genes associated with clutch traits in Laiwu Black chicken (a native Chinese breed). The restricted maximum likelihood (REML)method was employed for estimation of genetic parameters of clutch pattern in 399 Laiwu Black hens, using the GCTA software.Results:The results showed that SNP-based heritability estimates of clutch traits ranged from 0.06 to 0.59. A genome-wide association study (GWAS) was performed based on a mixed linear model (MLM) implemented in the EMMAX software. Genotyping data were obtained from whole genome re-sequencing data (399 individuals were re-sequenced at 7× coverage). After quality control, a total of 10,810,544 SNPs remained to be analyzed. The GWAS results revealed that 401 significant SNPs responsible for clutch traits were scattered on chicken chromosomes 1-14, 17-19, 21-25, 28 and Z. Among the annotated genes, neural EGFL like 2 (NELL2), SET And MYND domain containing 3 (SMYD3), and phospholipase D1 (PLCL1)were the most promising candidates for clutch traits in Laiwu Black chicken.Conclusion:The clutch traits showed moderate to high heritability, and the GWAS results identified an array of genes associated with the clutch traits. The findings of this study provide critical insight into the genetic basis of clutch traits.
Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next breeding cycles
Authors: Fritsche-Neto Roberto , Sabadin Felipe , doVale Julio César , Souza Pedro Henrique , Borges Karina Lima Reis , Crossa Jose , Garbuglio Deoclécio Domingos 
Published: March 2023

Abstract
Plant breeders widely use recurrent selection schemes to increase the frequency of favorable alleles for quantitative traits in a population. Although simultaneous selection is complex because it involves several traits combined with selection cycles, the use of selection indexes (SI) is applied to increase the chance of success of the breeding program. Despite many indices are available in the literature, therefore, simulations can help breeders to determine which selection index can be better adjusted considering the selection goals, the intensity, and the genetic correlation among traits over breeding cycles. In this context, we estimated the realized genetic gains in a tropical maize haploid inducer population after two cycles of recurrent selection, using external testers and optimizing the simultaneous selection for this breeding population in the long-term via stochastic simulations. Furthermore, we proposed a new approach to optimize the initial weights by applying Smith-Hazel method to maximize the genetic gains for all traits in a balanced way. Overall, the estimated gains in real induction rate were about 63% per cycle, improving the population performance from 0.8 to 2.8%. Moreover, our results confirm that the traditional Smith-Hazel approach outperformed other methods for long-term response to selection. Finally, recurrent selection with external testers is a suitable method to improve the haploid induction rate in tropical maize populations.
An Optimized Approach For Detection and Classification of Spam Email’s Using Ensemble Methods
Authors: Fatima Rubab , Sadiq Muhammad , Ullah Saleem , Ahmed Gulnaz , Mahmood Saqib 
Published: March 2023

Abstract

Since the advent of email services, spam emails are a major concern because users’ security depends on the classification of emails as ham or spam. It’s a malware attack that has been used for spear phishing, whaling, clone phishing, website forgery, and other harmful activities. However, various ensemble Machine Learning (ML) algorithms used for the detection and filtering of spam emails have been less explored. In this research, we offer a ML based optimized algorithm for detecting spam emails that have been enhanced using Hyper-parameter tuning approaches. The proposed approach uses two feature extraction modules, namely Count-Vectorizer and TFIDF-Vectorizer that provide the most effective classification results when we applied them to three different publicly available email data sets: Ling Spam, UCI SMS Spam, and Proposed dataset. Moreover, to extend the performance of classifiers we used various ML methods such as Naive Bayes (NB), Logistic Regression (LR), Extra Tree, Stochastic Gradient Descent (SGD), XG-Boost, Support Vector Machine (SVM), Random Forest (RF), Multi Layer Perception (MLP), and parameter optimization approaches such as Manual search, Random search, Grid search, and Genetic algorithm. For all three data sets, the SGD outperformed other algorithms. All of the other ensembles (Extra Tree, RF), linear models (LR, Linear-SVC), and MLP performed admirably, with relatively high precision, recall, accuracies and F1-Score.
Social innovation for regenerative buildings: Insights from Austria.
Authors: Hirschberg Rebekka , Ruderer Jomo , Röck Martin 
Published: March 2023

Abstract
Decarbonizing the construction and operation of buildings is essential in achieving sustainable development and mitigating the climate and ecosystem crisis. While considerable progress has been made to reduce energy and emissions from building operation, from a whole life cycle perspective, current building practices still struggle to provide housing within planetary boundaries. Beyond technological innovation, strategies are needed to reduce building-related environmental impacts while ensuring adequate spaces for a regenerative and distributive circular economy. Social innovation is needed to support the implementation of sustainable development goals and reduce emissions in the building sector. This article investigates pioneering building projects from Austria and the various social innovation strategies they successfully deploy to enable alternative model of regenerative spatial production. The strategies include co-creation and participatory design processes, crowd-based financing and co-ownership, as well as dedication to sharing and circularity. The study analyzes three building case studies that showcase successful social innovation in housing. The case studies are situated in different spatial contexts, including reactivating the countryside, revitalizing newly developed neighborhoods, and bringing new life to abandoned buildings. Despite the potential benefits of social innovation, this study finds that current real estate market hardly supports the development and realization of alternative housing models. In response, innovative models of housing are often driven by the initiative of the inhabitants and supported by dedicated individuals in local governance and public service. This study provides insights and guidance on how social innovation strategies can support alternative housing projects and which governance, financing, and ownership models may enable the implementation of regenerative buildings at scale.
Flexible Wearable Microstrip Patch Antenna based on Graded Dielectric Substrate Profile for Wireless Applications
Authors: Singh Rashwinder , Kaur Ranjit , Singh Charanjit 
Published: March 2023

Abstract
The aim of this paper is to investigate the possibilities of designing and fabricating a highly efficient and flexible wearable microstrip patch antenna operating at resonant frequency of 2.45 GHz. Copper Foil Tape (CFT) is used as a conducting medium in designing the patch and ground of antenna. While for designing the substrate, a graded profile based structures are made by combining two non-conducting fabrics i.e. Fleece-Curtain Cotton and Fleece-Polyester. The dielectric constant of these fabrics is measured with the help of ring resonator method. The proposed design models are simulated using CST simulator. To ensure the human body safety from antenna radiations in case of wearable applications, Specific Absorption Rate (SAR) is calculated on the simulated designs. Further some bending analysis of proposed antennas is also performed to ensure their applicability on different body parts like wrist, arm. Finally the proposed designs are fabricated and measured results are obtained using Agilent N5247A: A.09.90.02 VNA. TRL technique is used to calibrate the VNA with 3.5 SMA calibration kit.Simulated and measured results show good matching with each other in terms of resonant frequency, return loss, bandwidth and gain. The antenna designed using fleece-curtain cotton substrate achieved maximum bandwidth of 990 MHz, 2.22 dB gain and -34.99 dB value of S11 parameter. Voltage Standing Wave Ratio (VSWR) for all five antennas is less than 2. Hence the proposed antenna is a suitable candidate for wearable wireless applications.
Trends in Organic Farming Research in India (2002-2021): An assessment
Authors: Bankar Ravindra S. , Lihitkar Shalini R. 
Published: March 2023

Abstract

A scientometric analysis is conducted to study the research productivity and trend dynamics of organic farming research in India covering the period of 20 years (2001–2021). The study aims at the science mapping that aimed to summarize research activity and its essential aspects. The scientometric analysis outlines the year-wise research growth pattern, prolific authors and their productivity, major contributing journal outlets, major contributing institutions, and countries along with keywords occurrences for trend dynamics of the organic farming research in India. The is sourced from the web of science core collection database. The most productive year span is 2017–2021 (44.76% of the total paper published). The research growth pattern shows a gradual increase in research during the two decades. Research Articles are the most published form of research output. A total of 20.11% of international co-authorship is observed in organic farming research. ICAR-based source-Indian Journal of Agricultural Science is the major contributing source to organic farming research. The study has the potential to benchmark the organic farming research in India to play a significant catalytic role for further research in the field of organic farming.
Classification of second harmonic generation effect in magnetic materials
Authors: Xiao Rui-Chun , Shao Ding-Fu , Gan Wei , Wang Huan-Wen , Han Hui , Sheng Zhigao , Zhang Changjin , Jiang Hua , Li Hui 
Published: March 2023

Abstract
Studying of the relationship between magnetism and second harmonic generation effect (SHG) is not only a fundamental topic in condensed matter physics, but also has practical significance in experiments. In this work, we construct a complete and exclusive classification of SHG effect in magnetic materials, which offers a straightforward approach to inspect this intriguing connection and reveals the symmetries and origins of SHG. First, we study the symmetries of SHG tensors in all magnetic point groups with isomorphic group method, then we propose a comprehensive classification of SHG effect containing seven types by considering the symmetries of the magnetic phases and the corresponding parent phases. A tensor dictionary containing SHG and linear magneto-optic effect (LMO) is created, and a SHG database of magnetic materials is also established. Particularly, we find an anomalous SHG effect which is even and contributed by magnetism merely through our classification. Besides, the classification is conducive to the determination of magnetic structures via SHG.
In vitro evaluation of (S)-2-amino-3-[3-(2-18F-fluoroethoxy)-4-iodophenyl]-2-methylpropanoic acid (18F-FIMP) as a positron emission tomography probe for imaging amino acid transporters
Authors: Nozaki Satoshi , Nakatani Yuka , Mawatari Aya , Hume William Ewan , Doi Hisashi , Watanabe Yasuyoshi 
Published: March 2023

Abstract
Background
(S)-2-amino-3-[3-(2-18F-fluoroethoxy)-4-iodophenyl]-2-methylpropanoic acid (18F-FIMP) as a promising PET probe for imaging the tumor-specific L-type amino acid transporter (LAT) 1. Our previous study revealed that 18F-FIMP had a higher affinity for LAT1 than for LAT2 abundantly expressed even in normal cells. 18F-FIMP showed high accumulation in LAT1-positive tumor tissues and low accumulation in inflamed lesions in tumor-bearing mice. However, the affinity of 18F-FIMP for other amino acid transporters was not determined yet. Here, we aimed to determine whether 18F-FIMP has affinity for other tumor-related amino acid transporters, such as sodium- and chloride-dependent neutral and basic amino acid transporter B(0+) (ATB0,+), alanine serine cysteine transporter 2 (ASCT2), and cystine/glutamate transporter (xCT).
Procedures
Cells overexpressing LAT1, ATB0,+, ASCT2, or xCT were established by the transfection of expression vectors for LAT1, ATB0,+, ASCT2, or xCT. Protein expression levels were determined by western blot and immunofluorescent analyses. Transport function was evaluated by a cell-based uptake assay using 18F-FIMP and 14C-labeled amino acids as substrates.
Results
Intense signals were observed only for expression vector-transfected cells on western blot and immunofluorescent analyses. These signals were strongly reduced by gene-specific small interfering ribonucleic acid treatment. The uptake values for each 14C-labeled substrate were significantly higher in the transfected cells than in the mock-transfected cells, and were significantly inhibited by the corresponding specific inhibitors. The 18F-FIMP uptake values were significantly higher in the LAT1- and ATB0,+-overexpressing cells than in the corresponding mock cells, but no such increase was seen in the ASCT2- or xCT-overexpressing cells. These 18F-FIMP uptake values were significantly decreased by the specific inhibitors for LAT1- and ATB0,+.
Conclusions
We demonstrated that 18F-FIMP has affinity not only for LAT1, but also for ATB0,+. Our results may be helpful for understanding the mechanisms of the whole-body distribution and tumor accumulation of 18F-FIMP.
Identification of prognostic m 6 A modification patterns and score system in melanoma patients
Authors: Liu Zichuan , Chen Peijie , Ouyang Si , Xiong Kaixin , Wang Qian , Zhou Min , Wang Yao 
Published: March 2023

Abstract
Background
N6-methyladenosine (m6A) is the most common modification on RNAs and LncRNAs. It plays an important role in cancer stem cell differentiation, T cell differentiation, and immune homeostasis. In this study, we explored the potential roles of m6A modification of RNA in melanoma and investigated the immune cell infiltration in tumor microenvironment in diverse m6Aclusters and different m6Ascore groups.
Methods
The gene expression data and corresponding clinical information of melanoma patients were downloaded from TCGA and GEO databases (GSE65904). A consensus clustering algorithm determined m6A modification patterns based on 14 m6A regulators. Gene set variation analysis (GSVA) explored the biological process and single sample gene set enrichment analyses (ssGSEA) quantified the relative abundance of each immune cell infiltration. m6A-related differentially expressed genes (DEGs) were identified based on three patterns found among patients. An m6A-related gene signature (m6Ascore) was constructed based on genes with significant prognostic value using the principal component analysis algorithm.
Results
Three m6A modification patterns were identified based on 14 m6A regulators, named as m6Aclusters A-C. The prognosis of m6Acluster A was more favorable than m6Aclusters B and C, and it was more closely associated with immune regulation. After screening 4430 DEGs, three m6A modification genomic phenotypes were identified based on 845 prognostic DEGs. To quantify the m6A modification patterns of individual tumor, an m6Ascore was constructed, and patients were classified into high and low m6Ascore groups. The low m6Ascore group, which had a favorable prognosis, was more relevant to immunology. The expression of PD-L1 was higher and the immunophenoscore (IPS) revealed stronger response to immunotherapy in the low m6Ascore group.
Conclusions
This study identified three m6A modification patterns with different immune characteristics in melanoma patients and constructed an m6Ascore system to predict prognosis and immunogenicity of patients, which is conducive to clinical prognosis judgment and individual treatment.
The relationship between abnormal myocardial alterations and glycemic control validated by cardiac magnetic resonance in a pig model of diabetes mellitus
Authors: Zhang Lu , Guo Ying-kun , Yang Zhi-gang , Jiang Li , Yan Wei-feng , Xu Hua-yan 
Published: March 2023

Abstract
Aims
To investigate the relationship between hemoglobin (HbAlc) and abnormal myocardial alterations as determined by cardiac magnetic resonance (CMR) T1 mapping and feature tracking in a pig model of diabetes mellitus (DM).
Methods
Eight DM models were successfully established and were divided into two groups based on their HbAlc median value (high HbAlc ≥ 6.07%, n = 5; low HbAlc < 6.07%, n = 3). As controls, five healthy age-matched pigs were used. Over the diabetic course of 16 months, CMR cine, T1 mapping, and late enhancement gadolinium (LGE) were performed. Afterward, three pigs were then sacrificed and stained with masson trichrome and advanced glycation end products (AGEs) from control, high, and low HbAlc groups, respectively.
Results
Diabetes and control groups did not differ in terms of left ventricular ejection fraction (p = 0.784) and showed no evidence of LGE. However, when compared to controls, pigs with high HbAlc had higher native T1 and ECV as well as lower longitudinal strain and strain rate (all p < 0.05). Furthermore, HbAlc correlated well with native T1, ECV, longitudinal strain, and diastolic strain rate (R2 = 0.470 to 0.849, all p < 0.05). Histological staining showed more significant deposition of myocardial interstitial fibrosis and AGEs in the pig with high HbAlc than in the other two pigs.
Conclusions
High HbAlc was associated with increased myocardial native T1 and ECV and decreased longitudinal myocardial deformation in DM pigs.
Construction waste resource utilization and energy consumption calculation based on Internet of things
Authors: Chang Fuhua , Wang Dan 
Published: March 2023

Abstract
With the development of urbanization, the city has entered the stage of improving the quality of the stock, and the number of urban demolition has increased, resulting in the generation of construction waste and great pressure on the environment. The discharge of construction waste threatens the sustainable development of urban environment. And because large public buildings have high energy consumption and high emissions, it is urgent to establish an effective energy consumption measurement system. In the past, the calculation method for energy consumption was relatively single, which could not effectively manage energy consumption. This paper discusses how to use construction waste scientifically based on the Internet of things, and using advanced measurement technology to monitor and analyze building energy consumption is an effective way to solve this problem. Based on this, this paper constructs a building energy consumption measurement system through the Internet of things technology. By using BP linear neural network model to predict, the system effectively improves the prediction accuracy and makes it close to the actual value. The system is mainly based on the collection terminal, the centralized data terminal and the data management terminal, and then builds a communication bridge between the terminals through the Internet of things and the Internet. The response time of energy consumption monitoring and management is relatively short, and the response speed of power control management and energy consumption management analysis is relatively fast, which can effectively measure the energy consumption of buildings. In addition, this paper also makes a brief analysis of the recycling of construction waste, and puts forward the corresponding strategic analysis of resource utilization. This paper designs an effective energy consumption measurement system by introducing the Internet of things technology into the building field.