bluuebunny/crossref_metadata_2025_split huggingface dataset:
Konsep dan Praktik Literasi Informasi Untuk Mahasiswa: Kasus Mahasiswa Pekerja Paruh Waktu di UPT Perpustakaan UIN Walisongo
Authors: Ulumi Bahrul 
Published: April 2021

This article reveals the pratice of information literacy done by students writing final project and working as part time workers at main library. It employs qualitattive approach which is considered the appropriate method to explore how these students implement their information skills to takle their final duties. The research shows that they partially comprehend the concept of information since they actively took part only in library orientation, as a result, they just a bit know about the concept of information ethics, although they are able to correctly finish their final works.
Practical Machine-Learning Applications in Well-Drilling Operations
Authors: Olukoga T. A. , Feng Y. 
Published: April 2021

Summary
There is a great deal of interest in the oil and gas industry (OGI) in seeking ways to implement machine learning (ML) to provide valuable insights for increased profitability. With buzzwords such as data analytics, ML, artificial intelligence (AI), and so forth, the curiosity of typical drilling practitioners and researchers is piqued. While a few review papers summarize the application of ML in the OGI, such as Noshi and Schubert (2018), they only provide simple summaries of ML applications without detailed and practical steps that benefit OGI practitioners interested in incorporating ML into their workflow. This paper addresses this gap by systematically reviewing a variety of recent publications to identify the problems posed by oil and gas practitioners and researchers in drilling operations. Analyses are also performed to determine which algorithms are most widely used and in which area of oilwell-drilling operations these algorithms are being used. Deep dives are performed into representative case studies that use ML techniques to address the challenges of oilwell drilling. This study summarizes what ML techniques are used to resolve the challenges faced, and what input parameters are needed for these ML algorithms. The optimal size of the data set necessary is included, and in some cases where to obtain the data set for efficient implementation is also included. Thus, we break down the ML workflow into the three phases commonly used in the input/process/output model. Simplifying the ML applications into this model is expected to help define the appropriate tools to be used for different problems. In this work, data on the required input, appropriate ML method, and the desired output are extracted from representative case studies in the literature of the last decade. The results show that artificial neural networks (ANNs), support vector machines (SVMs), and regression are the most used ML algorithms in drilling, accounting for 18, 17, and 13%, respectively, of all the cases analyzed in this paper. Of the representative case studies, 60% implemented these and other ML techniques to predict the rate of penetration (ROP), differential pipe sticking (DPS), drillstring vibration, or other drilling events. Prediction of rheological properties of drilling fluids and estimation of the formation properties was performed in 22% of the publications reviewed. Some other aspects of drilling in which ML was applied were well planning (5%), pressure management (3%), and well placement (3%). From the results, the top ML algorithms used in the drilling industry are versatile algorithms that are easily applicable in almost any situation. The presentation of the ML workflow in different aspects of drilling is expected to help both drilling practitioners and researchers. Several step-by-step guidelines available in the publications reviewed here will guide the implementation of these algorithms in the resolution of drilling challenges.
Group 14 Metallafluorenes as Sensitive Luminescent Probes of Surfactants in Aqueous Solution
Authors: Spikes Helena J. , Jarrett-Noland Shelby J. , Germann Stephan M. , Braddock-Wilking Janet , Dupureur Cynthia M. 
Published: April 2021

Abstract
Sila- and germafluorenes containing alkynyl(aryl) substituents at the 2,7- position are strongly emissive with high quantum yields in organic solvents. Provided they are sufficiently soluble in water, their hydrophobic structures have the potential for many biological and industrial applications in the detection and characterization of lipophilic structures. To that end, the emission behaviors of previously synthesized 2,7- bis[alkynyl(biphenyl)]-9,9-diphenylsilafluorene (1), 2,7- bis[alkynyl(methoxynaphthyl)]-9,9-diphenylgermafluorene (2), 2,7- bis[alkynyl(p-tolyl)]-9,9-diphenylsilafluorene (3), and 2,7- bis[alkynyl(m-fluorophenyl)]-9,9-diphenylsilafluorene (4) were characterized in aqueous solution and in the presence of various surfactants. Despite a high degree of hydrophobicity, all of these metallafluorenes (MFs) are soluble in aqueous solution at low micromolar concentrations and luminesce in a common aqueous buffer. Further, the 2,7 substituent makes the emission behavior tunable (up to 20 nm). Fold emission enhancements in the presence of various surfactants are highest toward Triton X-100 and CTAB (ranging from 5–25 fold) and are lowest for the anionic surfactants SDS and SDBS. These enhancements are competitive with existing probes of surfactants. Quantum yields in buffer range from 0.11 to 0.34, competitive with many common fluorophores in biological use. Strikingly, MF quantum yields in the presence of TX-100 and CTAB approach 100% quantum efficiency. MF anisotropies are dramatically increased only in the presence of TX-100, CTAB, and CHAPS. Coupled with the above data, this suggests that MFs associate with neutral and charged surfactant aggregates. Interactions with the anionic surfactants are weaker and/or leave MFs solvent exposed. These properties make metallafluorenes competitive probes for surfactants and their properties and behaviors, and thus could also have important biological applications.
WITHDRAWN: A Novel Axis HIF1A/miR-1271-5p/lncRNA PTTG3P/YAP1 Contributes to Colorectal Cancer Progression and Relates to an Immune-suppressing Microenvironment
Authors: zheng yang , zhang ke , liu yiyang , xie longfei , ge jinnian , wang yue , zhao guohua 
Published: April 2021

Abstract
Background Pseudogene has emerged as key regulators of important biological processes involved in human cancers. However, the PTTG3P biological function in colorectal cancer (CRC) needs further to be clarified. Methods qRT-PCR was adopted to measure the PTTG3P expression in different cell line and CRC tissues. Cellular localization of PTTG3P was detected by subcellular fractionation assay. In vitro and in vivo experiments were carried out to explore the bioeffect of PTTG3P in CRC cells. Chromatin immunoprecipitation (ChIP), luciferase assay and RIP were explored to certify the direct binding of PTTG3P and microRNA. Results PTTG3P was upregulated in CRC and closely related to poor prognosis. Through gain and loss of function approaches, PTTG3P facilitated proliferation and glycolysis through YAP1, and glycolysis inhibitor (2-DG,3-BG) and LDHA knockdown could rescue cell proliferation and tumorigenesis. Mechanically, miR-1271-5p modulates PTTG3P expression and miR-1271-5p mimics could recover the PTTG3P function. Also HIF1A increased PTTG3P expression in both normoxia and hypoxia conditions by ameliorating miR-1271-5p expression. In addition, silencing PTTG3P decreases the level of inflammatory cytokines TNF-α, IL-1β and IL-6, and low PTTG3P expression relates with CD8+ T, NK and TFH cells infiltration. Conclusions Our findings verified the oncogenic function of PTTG3P in assisting the cell proliferation and glycolysis, demonstrating the pivotal roles of HIF1A/miR-1271-5p/lncRNA PTTG3P/YAP1 in CRC progression, which proposes a novel approach for clinical treatment.
Emotion Categorization from Faces of People with Sunglasses and Facemasks
Authors: Shehu Harisu Abdullahi , Browne Will , Eisenbarth Hedwig 
Published: April 2021

Abstract
Emotional information is considered to convey much meaning in communication. Hence, artificial emotion categorization methods are being developed to meet the increasing demand to introduce intelligent systems, such as robots, into shared workspaces. Deep learning algorithms have demonstrated limited competency in categorizing images from posed datasets with the main features of the face being visible. However, the use of sunglasses and facemasks is common in our daily lives, especially with the outbreak of communicable diseases such as the recent coronavirus. Anecdotally, partial coverings of the face reduces the effectiveness of human communication, so would this have hampering effects on computer vision, and if so, would the different emotion categories be affected equally? Here, we use a modern deep learning algorithm (i.e. VGG19) to categorize emotion from faces of people obscured with simulated sunglasses and facemasks. We found that face coverings obscure emotion categorization by up to 74%, whereby emotion categories are affected differently by different coverings, e.g. clear mouth coverings have little effect in categorizing happiness, but sadness is affected badly. While an overall accuracy of up to 97% has been achieved with nothing added to the face, the achieved accuracy decreases in all other cases when the face is obscured. Notably, clear visors have only a small effect across all emotions, where the classifier achieved an accuracy of up to 89.0% compared to other types of facemasks in which the achieved accuracy is less than 36%.
Assessing the Influence of Sea Surface Temperature and Arctic Sea Ice Cover on the Uncertainty in the Northern Winter Future Climate Projections
Authors: Cheung Ho Nam , Keenlyside Noel , Koenigk Torben , Yang Shuting , Tian Tian , Xu Zhiqing , Gao Yongqi , Ogawa Fumiaki , Omrani Nour-Eddine , Qiao Shaobo , Zhou Wen 
Published: April 2021

Abstract
We investigate the uncertainty (i.e., inter-model spread) in future projections of the northern winter climate, based on the forced response in the CMIP5 RCP8.5 scenario. The uncertainty in the forced response of sea level pressure (SLP) is large in the North Pacific, the North Atlantic, and the Arctic. A major part of these uncertainties (31%) is marked by a pattern with a center in the northeastern Pacific and a dipole over the northeastern Atlantic that we label as the Pacific–Atlantic SLP uncertainty pattern (PAΔSLP). To better understand the nature of PAΔSLP, the associated sea surface temperature (SST) and Arctic sea ice cover (SIC) perturbation patterns are prescribed in experiments with two atmospheric models (AGCMs): CAM4 and IFS.The AGCM experiments indicate more robust SLP response over the North Pacific driven by the SST perturbation, which is associated with the tropical-midlatitude interaction and the Rossby wavetrain. The North Atlantic SLP response is better explained by the joint effect of SST and SIC perturbations, which is partly related to the Rossby wavetrain from the Pacific and the air–sea interactions over the North Atlantic. However, these responses shift westward relative to PAΔSLP, where in CAM4 it is related to the low-frequency transient eddy forcing. The magnitude of these responses in the two AGCMs is largely different. Thus, constraining only the SST and SIC projections might not alone help constrain future climate projections. We should investigate the role of other factors in these uncertainties, such as the atmosphere–SST–SIC coupled dynamics.
Chalcogenide As Inorganic Transport Layer in Perovskite Solar Cell
Authors: kumar Atul 
Published: April 2021

Abstract
Fill factor (FF) deficit and stability is a primary concern with the perovskite solar cell. Resistance values and band alignment at junction interface in perovskite are causing low fill factor. Moisture sensitivity of methylammonium lead halide perovskite is causing a stability issue. We tried to solve these issues by using inorganic hole transport layer (HTL). FF is sensitive to the band offset values. We study the band alignment/band offset effect at the Perovskite /HTL junction. Inorganic material replacing Spiro-MeOTAD can enhance the stability of the device by providing an insulation from ambient. Our simulation study shows that the earth abundant p-type chalcogenide materials of SnS as HTL in perovskite is comparable to Spiro-MeOTAD efficiency.
The Combined Use of SEM-EDX, Raman, ATR-FTIR and Visible Reflectance Techniques for the Characterisation of Roman Wall Painting Fragments From Monte D’Oro Area (Rome): An Insight onto Red, Yellow and Pink Shades.
Authors: Guglielmi Vittoria , Andreoli Martina , Comite Valeria , Baroni Anna , Fermo Paola 
Published: April 2021

Abstract
The aim of this work has been the identification of the painter’s materials employed in the wall’s decoration of some destroyed building dating approximately between the first century B.C. and the first century A.D. This research originates from a previously started joined archaeological and analytical investigation concerning a really varied group of findings that resulted from an excavation performed by Soprintendenza Archeologica in the area of Monte d'Oro in Rome. The focus of this study progression has been directed to a numerous selection of monochrome red, pink, and yellow pigmented fragments. The analyses were performed by means of scanning electron microscopy energy dispersive X-ray spectroscopy (SEM-EDX) combined to Raman and Fourier transform infrared (FTIR) spectroscopies; visible reflectance measurements have also been carried out in order to evaluate its appliance in such a kind of archaeological studies. Most attention has been given to the assessment of the performances of non-destructive techniques, precisely the ones achieved by portable Raman and visible reflectance instrumentation, above all to test their diagnostic capabilities. In addition to the expected and well-known pigments such as cinnabar, red ochre, hematite for the reds and yellow ochre for the yellows, the study highlighted a diffuse use of mixed colours and/or overlapped painted layers and confirmed in some cases the presence of gildings. Among the mixtures of pigments, the most singular outcome concerns the pink fragment revealing the possible application of bone white, which, based on of the known literature, seems to be rather uncommon as pigment in Roman wall decorations.
WITHDRAWN: Gene Based ­­­­Markers in Marker-Assisted Selection to Screen Tomato Genotypes Resistant to Fusarium Wilt, Late Blight, Verticillium Wilt, Leaf Mold, Bacterial Spot and Bacterial Speck
Authors: Mahfouze Heba , Mahfouze Sherin 
Published: April 2021

Abstract
The tomato crop is exposed to serious losses due to infection with several diseases and pests, which threaten tomato production in Egypt and worldwide. Therefore, selecting the tomato germplasm resistant or tolerant to a specific pathogen by molecular markers closely linked to resistance loci is a desirable goal of this study. In this work, seven co-dominant markers targeting six resistance genes (I-1, Ve, Ph3, Cf-9/Cf-4, Rx4, and Pto) for six main diseases [ fusarium wilt (Fusarium oxysporum f. sp. lycopersici), verticillium wilt (Verticillium dahliae and V. alboatrum), late blight (Phytophthora infestans), leaf mold (Cladosporium fulvum), bacterial spot (Xanthomonas campestris pv. vesicatoria) and bacterial speck (Pseudomonas syringae pv. tomato)], respectively were determined. Theses molecular markers differentiated among 19 tomato genotypes resistant (homozygote/heterozygote) and susceptible (homozygote) to the pathogens. Therefore, this study supplied us with novel tomato lines with resistance to multiple diseases, and their pyramiding inside domesticated tomato cultivars are suggested to apply in the tomato breeding programs of resistance against fungal and bacterial diseases.
Monopulse Estimation of Unknown Polarization for Conformal Phased Array with Arbitrarily Oriented Dipoles
Authors: Deng Yuhao , Xie Julan , He Zishu , Li Jun 
Published: April 2021

Abstract
In this paper, a novel monopulse estimator is proposed to surmount obstacles caused by unknown polarized pattern and the difference among each dipole orientation. Polarized pattern often alters the phased array response and we could hardly recover it if we known nothing about polarized parameters. The sum and difference beamforming of conformal phased array is affected due to the difference among each dipole orientation. Therefore the conventional monopulse estimator is dumped in this circumstance. The method proposed in this paper is a remarkable estimator based on maximum likelihood methodology. In this method, polarized parameters are considered as a part of desired signal and the least-squares solution of desired signal is obtained. With the desired signal solution, the likelihood function with respect to direction is derived at first. Then from the above, Jacobian and Hessian matrix of likelihood function is deduced. The boresight is considered as the initial direction value and the estimator of desired signal direction is obtained by Newton's formula. Finally, the polarized parameters are estimated by least-squares method using the direction estimator. The root-mean-square error (RMSE) of angle estimation is acceptable when prior polarized information is completely unknown. Polarized parameters are estimated by similar technique after we find out azimuth and elevation. Our research fills a gap of monopulse estimation with arbitrary polarization and diverse dipole arrangement.
Difficulty Intubating a Double-Lumen Tube due to a Tracheal Bronchus: A Case Report
Authors: Wang Wenzhu , Li Ji , Liu Jian , Song Chengwei , Zhang ya-nan 
Published: April 2021

Abstract
Background: Intubation difficulties, hypoxemia, inability to perform a one-lung ventilation, and high airway pressure often occur during double-lumen tube intubation. Tracheal bronchus is a very rare and difficult to find reason. We present a case of tracheal bronchus accidentally discovered during double-lumen tube intubation in a patient undergoing thoracic surgery. We are the first one to summarize the one-lung ventilation strategy for patients with tracheal bronchus. Case Presentation: A 53-year-old man underwent a scheduled thoracoscopic left upper lobectomy. After two unsuccessful attempts to pass the right-sided double-lumen tube through the right mainstem bronchus, fiberoptic bronchoscopy revealed an aberrant tracheal bronchus with an incidence of 0.1%–3%. Finally we used a left-sided DLT to ventilate the right lung. The patient had no airway complications and was discharged 7 days after the operation.Conclusions: This case serves to remind us that preoperative visits must be thorough and careful. Although a computed tomography chest examination was performed before surgery, we just looked at the inspection report and did not look at the images. We also reviewed relevant literature and summarized the one-lung ventilation strategies for patients with tracheal bronchus. For left-lung ventilation, either a left-sided double-lumen tube or a combination of a bronchial blocker and Fogarty artery embolization catheter can be used. For right-lung ventilation, a bronchial blocker or a left-sided double-lumen tube is a good choice.
DMWAS: Deep &amp; Machine learning omics Wide Association Study &amp; Feature set Optimization by Clustering &amp; Univariate Association for Biomarkers Discovery as Tested on GTEx Pilot Dataset for Death due to Heart-Attack
Authors: Singh Abhishek N 
Published: April 2021

Abstract
Univariate and multivariate methods for association of the genomic variations with the end-or-endo phenotype have been widely used for genome wide association studies. In addition to encoding the SNPs, we advocate usage of clustering as a novel method to encode the structural variations, SVs, in genomes, such as the deletions and insertions polymorphism (DIPs), Copy Number Variations (CNVs), translocation, inversion, etc., that can be used as an independent feature variable value for downstream computation by artificial intelligence methods to predict the endo-or-end phenotype. We introduce a clustering based encoding scheme for structural variations and omics based analysis. We conducted a complete all genomic variants association with the phenotype using deep learning and other machine learning techniques, though other methods such as genetic algorithm can also be applied. Applying this encoding of SVs and one-hot encoding of SNPs on GTEx V7 pilot DNA variation dataset, we were able to get high accuracy using various methods of DMWAS, and particularly found logistic regression to work the best for death due to heart-attack (MHHRTATT) phenotype. The genomic variants acting as feature sets were then arranged in descending order of power of impact on the disease or trait phenotype, which we call optimization and that also uses top univariate association into account. Variant Id P1_M_061510_3_402_P at chromosome 3 & position 192063195 was found to be most highly associated to MHHRTATT. We present here the top ten optimized genomic variant feature set for the MHHRTATT phenotypic cause of death.
Numerical modeling of reinforcement forces in geosynthetic reinforced soil slopes
Authors: Djeffal Houcine , Belkacemi Smain , Boumezrane Djamalddine 
Published: April 2021

Abstract
Reinforced soil slopes are widely used in civil engineering for slope protection for their vast advantages. The paper reports the details of numerical models used to predict the factors affecting force distribution in the reinforcement layers of reinforced slope-instrumented structures. However, the failure mechanism of reinforced slopes has not been fully studied. The stability analysis of reinforced slopes is conducted in this paper based on the limit equilibrium method. Furthermore, the effects of the target factor of safety and the soil friction angle of the reinforcement layers on the reinforcement force distribution are investigated. The research results indicate that the above parameters have great effects on the maximum reinforcement force and the reinforcement force distribution of the reinforced slope. Based on the analysis of computation results, the reinforcement mechanism is analyzed and the optimum design scheme of the reinforced slope is recommended. The results can be used as a guideline for the determination of the required reinforcement forces.