bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analyzing the effect of data preprocessing techniques using machine learning algorithms on the diagnosis of COVID‐19
Authors: Erol Gizemnur , Uzbaş Betül , Yücelbaş Cüneyt , Yücelbaş Şule 
Published: October 2022

SummaryReal‐time polymerase chain reaction (RT‐PCR) known as the swab test is a diagnostic test that can diagnose COVID‐19 disease through respiratory samples in the laboratory. Due to the rapid spread of the coronavirus around the world, the RT‐PCR test has become insufficient to get fast results. For this reason, the need for diagnostic methods to fill this gap has arisen and machine learning studies have started in this area. On the other hand, studying medical data is a challenging area because the data it contains is inconsistent, incomplete, difficult to scale, and very large. Additionally, some poor clinical decisions, irrelevant parameters, and limited medical data adversely affect the accuracy of studies performed. Therefore, considering the availability of datasets containing COVID‐19 blood parameters, which are less in number than other medical datasets today, it is aimed to improve these existing datasets. In this direction, to obtain more consistent results in COVID‐19 machine learning studies, the effect of data preprocessing techniques on the classification of COVID‐19 data was investigated in this study. In this study primarily, encoding categorical feature and feature scaling processes were applied to the dataset with 15 features that contain blood data of 279 patients, including gender and age information. Then, the missingness of the dataset was eliminated by using both K‐nearest neighbor algorithm (KNN) and chain equations multiple value assignment (MICE) methods. Data balancing has been done with synthetic minority oversampling technique (SMOTE), which is a data balancing method. The effect of data preprocessing techniques on ensemble learning algorithms bagging, AdaBoost, random forest and on popular classifier algorithms KNN classifier, support vector machine, logistic regression, artificial neural network, and decision tree classifiers have been analyzed. The highest accuracies obtained with the bagging classifier were 83.42% and 83.74% with KNN and MICE imputations by applying SMOTE, respectively. On the other hand, the highest accuracy ratio reached with the same classifier without SMOTE was 83.91% for the KNN imputation. In conclusion, certain data preprocessing techniques are examined comparatively and the effect of these data preprocessing techniques on success is presented and the importance of the right combination of data preprocessing to achieve success has been demonstrated by experimental studies.
Web information mining and semantic analysis in heterogeneous unstructured text data using enhanced latent Dirichlet allocation
Authors: Venugopal Madamanchi , Sharma Virendra K. , Sharma Kalpana 
Published: October 2022

SummaryInformation mining and semantic analysis have gained significant attention over recent years to obtain appropriate information from unstructured data. Several approaches have been introduced for web information mining. However, the expected accuracy is not reached by these approaches. Therefore, hybrid fuzzy clustering and enhanced latent Dirichlet allocation (ELDA) are proposed for the accuracy increment in this work. The information clustering process is performed using the hybrid fuzzy clustering algorithm called fuzzy‐C‐medoids optimized using improved whale algorithm. The clustering procedure entails grouping data points into more similar clusters than data points from other clusters. Finally, the context of the text is recognized by analyzing the semantic information with ELDA, which offers a suitable index for accurate and fast data extraction. PYTHON tool is used to develop the proposed web mining model, and the simulation analysis of the proposed model is carried out using the BibTex dataset and compared with baseline models. The performance of the proposed method is evaluated using purity, normalized mutual information, accuracy, and precision metrics. Also, it is compared with different existing algorithms. Thus, the analysis of the results proved that the proposed approach achieves better outcomes than the existing approaches.
Signal and Noise: Proton Pump Inhibitors and the Risk of Dementia?
Authors: Friesen Kevin J. , Falk Jamie , Chateau Dan , Kuo I. Fan , Bugden Shawn 
Published: October 2022

The association between proton pump inhibitor (PPI) use and dementia remains controversial. This cohort study re‐examines this issue, addressing shortcomings identified in previous publications using a population‐based and a high‐dimension propensity‐score matched cohort to follow patients for up to 22 years. Cox regression models using baseline characteristics, a lag period, and time‐varying variables were used to examine the risk of dementia by cumulative PPI exposure. High‐dose PPI users (> 180 days of use) had significantly higher risk of dementia in crude Cox models. After adjustment for medical diagnoses and prescription drug use, these associations disappeared. Among high‐dose users starting PPI therapy between 46 and 55 years old, the unadjusted hazard ratio (HR) was 1.55 (95% confidence interval (CI) 1.14, 2.10); the adjusted hazard ratio (aHR) was 1.10 (95% CI 0.80, 1.51). For high‐dose users starting therapy between 56 and 65 years, HR = 1.22 (95% CI1.03, 1.44); aHR = 0.99 (95% CI 0.83, 1.17). High‐dose users between the ages of 66 and 75 years had no association with the risk of dementia. The use of lag models or time‐varying parameters similarly found some association with dementia in crude, but not multivariable Cox models. Although high‐dose PPI users were more likely to develop dementia, they were more likely to be diagnosed with dementia risk factors, such as diabetes and cardiovascular disease, which are risk factors for dementia. Controlling for these conditions using multivariable models or a propensity‐score matched cohort eliminated this association.
Drug testing for mitragynine and kratom: Analytical challenges and medico‐legal considerations
Authors: Helander Anders , Rylski Alexia 
Published: October 2022

AbstractMitragyna speciosa, known as kratom, is a tropical tree native to Southeast Asia that has long been used to increase energy and in traditional medicine. Kratom leaves contain several indole alkaloids including mitragynine, mitraciliatine, speciogynine, and speciociliatine, which have the same molecular formula and connectivity, but different spatial arrangements (i.e., diastereomers). A routine liquid‐chromatographic–high‐resolution mass‐spectrometric (LC‐HRMS) multi‐analyte method for addictive and herbal drugs in urine did not separate mitragynine from speciogynine and speciociliatine. Separation and individual measurement of the four diastereomers was possible with an improved LC method. All diastereomers were detected in 29 patient urine samples who tested positive for mitragynine with the routine method, albeit at variable absolute amounts and relative proportions. The presence of all diastereomers rather than individual substances indicated that they originated from the intake of kratom (i.e., plant material). Speciociliatine dominated in most samples (66%), whereas mitragynine and mitraciliatine were the highest in 17% each. A kratom product (powdered plant material) marketed in Sweden contained all diastereomers with mitragynine showing the highest level. In Sweden, there are signs of an increasing use of kratom in society, based on the results from drug testing, the number of poisons center consultations on intoxications, and customs seizure statistics. Because there may be health risks associated with kratom use, including dependence, serious adverse reactions, and death, analytical methods should be able to identify and quantify all diastereomers. In Sweden, this is important from a legal perspective, as only mitragynine is classified, whereas the other three diastereomers, and kratom (plant material), are not.
Multiple genetic sources facilitate the northward range expansion of an intertidal oyster along China's coast
Authors: Hu Li‐Sha , Dong Yun‐Wei 
Published: October 2022

AbstractCoastal artificial structures on the former mudflats provide available habitats for the rocky intertidal species which can establish new populations in these emerging habitats over their former distribution range limits. As a former southern species, the oyster Crassostrea sikamea has become a pioneer and rapidly invaded the artificial shorelines in northern China. We used a seascape genomics approach to investigate the population structure and genetic sources of C. sikamea on the coastal artificial structures, which is crucial for understanding the genetic mechanisms driving species distribution range expansion and invasion pathway of intertidal species. Five C. sikamea populations, including two artificial substrate populations (WGZ and ZAP), one oyster reef population (LS), and two natural rocky shore populations (ZS and XM), were measured using single nucleotide polymorphism (SNPs) obtained from double digest restriction‐site associated DNA sequencing (ddRAD‐Seq). Redundancy analyses (RDA) were implemented for investigating the relationship between local temperature variables and the temperature adaptability of C. sikamea. Genetic diversity, direction and strength of gene flow, and population structure all revealed that the LS and ZS populations were the genetic sources for the oyster populations on the emerging northern coastal artificial structures. Results of RDA showed that there were different adaptive potentials for northern and southern populations to local temperature variables and the oyster reef population which frequently suffers from heat stress owned high heat adaptability. The ZS population as a genetic source nearby the Yangtze River estuary provided mass larvae for the northern populations, and the other genetic source, the heat‐tolerant LS population, in the oyster reef played an important role in the post‐settlement success by providing preadapted genotypes. These results highlight the importance of multiple sources with divergent adaptative capabilities for biological invasion, and also emphasize the importance of the oyster reef in coastal biodiversity and conservation.
Gharial (Gavialis gangeticus, Gmelin, 1789) abundance in the Rapti River, Chitwan National Park, Nepal
Authors: Yadav Ramesh Kumar , Lamichhane Saneer , Thanet Dol Raj , Rayamajhi Trishna , Bhattarai Santosh , Bashyal Ashish , Lamichhane Babu Ram 
Published: October 2022

AbstractGharial (Gavialis gangeticus) is a Critically Endangered crocodilian species whose abundance in Nepalese rivers is low due to the threat they face. We estimated gharial abundance in the Rapti River, one of the major rivers in Chitwan National Park (CNP) holding the largest numbers of gharials in Nepal. The Rapti River, running across the CNP, was divided into 18 segments, each measuring ~4 km, and gharials were counted directly with three replicates. Gharial count data were analyzed using an N‐mixture model (negative binomial) and the overall occupancy of gharials was estimated using a single season occupancy model. Covariate effects were also investigated on gharial abundance. Our findings revealed that the Rapti River is home to 150 gharials (119–181), with a mean abundance of 8.3 (SD = 3.45) across each segment. The presence of humans and square of Rapti River depth were the significant covariates that had a negative and positive impact on gharial abundance, respectively. Similarly, the number of sandbank present influenced the detection probability of gharials. Our study shows that gharial population estimation can be improved using the N‐mixture model. The overall gharial occupancy estimated using single season occupancy model was 0.84 (SD = 0.08), with a detection probability of 0.37 (SD = 0.02). The management authority should concentrate on segments to minimize human disturbance (e.g., fishing, washing clothes, extraction of riverbed materials). If the gharial population in this river declines, their population in central Nepal will be threatened. Hence, we suggest designating the Rapti River section that passes across the CNP as a “no extraction zone.”
Design of a database‐driven soft‐sensor and its application to a control system
Authors: Kinoshita Takuya , Kano Haruka , Yamamoto Toru 
Published: October 2022

AbstractIn industries, it is difficult to measure physical quantities such as product quality. In order to estimate it, soft sensors have been proposed. In recent years, the Just‐In‐Time (JIT) method has attracted attention. According to this method, the output is estimated by extracting data from the database similar to the current situation. On the other hand, a database‐driven control system has been proposed in which the JIT is equipped with a learning algorithm. This method calculates the control parameters using a database and has the scheme to learn the control parameters to minimize the control error. This paper proposes a new design method for soft sensors which uses a database‐driven approach. Specifically, this paper proposes a method to improve the estimation accuracy without modifying the stored past data by introducing a new modifiercinto the learning algorithm. Furthermore, a control system is designed in which the estimated value using the soft sensor is fed back.
MEMS Rogowski coil current sensor with spiral return coil
Authors: Watanabe Yoshiyuki , Kato Mutsuto , Yahagi Toru , Murayama Hiroki , Yamada Naoya , Yoshida Kenichi , Maehara Kenichi , Fukuda Yusuke , Sashida Kazuyuki , Ikeda Katsuya , Ikeda Kosuke , Takemori Toshiyuki 
Published: October 2022

AbstractWe have developed a MEMS Rogowski coil current sensor with spiral return coil. The Rogowski coil is formed on a silicon substrate clockwise and counterclockwise from the edges, for current detection and external magnetic noise compensation (device size 10 × 10 × 0.3 mm3, spiral coil 135 turns, via diameter 100 μm). When the slew rate (di/dt) was kept constant at 10 A/μs, and the current was changed by 5 A up to 40 A, MEMS Rogowski coil could detect current linearly. When the slew rate was changed by 10 A/μs up to 100 A/μs, it was found that the MEMS Rogowski coil could detect current almost linearly following the reference sensor. Hence, external noise compensation by the return coil has been confirmed.
Morphological markers of chromosomal instability in bone marrow aspiration and trephine biopsy of acute leukemia and myelodysplastic syndrome
Authors: Khairwa Anju , Kotru Mrinalini , Dewan Pooja , Narang Shiva 
Published: October 2022

AbstractThe role of chromosomal instability (CI) in oncogenesis is very well described in solid tumours, but there are a lack of studies on haematology malignancy, especially with multiple morphological markers. The study aims to analyze seven morphological markers of CI‐ chromatin bridges (CB), multipolar mitosis (MPM), nuclear budding (NB), micronuclei (MN), nuclear heterogeneity (NH), laggards, chromatin strings (CS) in bone marrow aspirate (BMA) and biopsy of acute leukaemia (AL), and myelodysplastic syndrome (MDS). It is a retrospective cross‐sectional analytical study where BMA and biopsy were reviewed for CI markers. We compared CI markers in five categories. CI markers were further correlated with clinical manifestations and outcomes of patients. The study included 54 samples of 37 patients. Overall, the median (IQR) of markers were as follows: MN 3.5 (1,7), NB 5 (1,18), MPM 1 (0,4), CB 1(0,2), Laggards 0 (0,1), and CS 2.5 (0,6). NH was noted in 65.4% of samples. All CI markers except laggards were significantly increased in B‐ALL, AML, and MDS compared to other categories. Many CI markers were significantly raised with a few clinical features. The MN, MPM, Laggard, and NH markers were significantly increased in the dead patients compared to those who survived. The study, one of the first to analyze multiple CI markers, revealed that the CI markers were significantly increased in AL and MDS patients and significantly associated with clinical manifestations and outcomes. Morphology markers of CI are valuable and cost‐effective in diagnostic strategy, type of malignancies, and assessing prognosis.
A 3D peridynamic fluid–solid coupling damage model of hydraulic fracture propagation
Authors: Li Yalong , Hu Zhiming , Qiu Zhipeng , Qiu Yafeng 
Published: October 2022

AbstractPeridynamics provides a new model and method for describing material failure and fracture development. In this study, a three‐dimensional peridynamic fluid–solid coupling model of hydraulic fracture propagation was established. The model considered the effective stress and transverse isotropic characteristics of shale and was used to simulate the propagation of the hydraulic fracturing of bedding shale. The damage evolution influence on the fracture propagation behavior, as well as the interactions between the fractures and bedding, were investigated through a simulation. The damage evolution had discontinuous characteristics. In addition to the incomplete damage zone adjacent to the complete damage zone, there were nonadjacent and incomplete damage zones. The fracture and propagation of hydraulic fractures followed the same trends of damage evolution. Moreover, the simulation and related experimental results confirmed the existence of a large amount of mesodamage in the region far from the fracture, and the concept of “remote damage” in hydraulic fracturing was proposed. Finally, the damage evolution of the propagating fractures and bedding was simulated. The simulation showed that bedding hinders the propagation of main fractures in the height direction but promotes the complexity of fracture propagation. Overall, this study provides a new theoretical understanding and research ideas for an in‐depth understanding of hydraulic fracture geometry and the accurate calculation of Stimulated Reservoir Volume.
Boosted backtracking search optimization with information exchange for photovoltaic system evaluation
Authors: Weng Xuemeng , Liu Yun , Heidari Ali Asghar , Cai Zhennao , Lin Haiping , Chen Huiling , Liang Guoxi , Alsufyani Abdulmajeed , Bourouis Sami 
Published: October 2022

AbstractThe determination of photovoltaic (PV) parameters is of great importance for the reliability of solar system operation, continuity of the load power consumption, and control management of the energy source. Therefore, this study proposes an advanced backtracking search optimization algorithm (BSA) equipped with teaching and learning‐based optimization (TLBO), named TLBOBSA, to accurately simulate the PV model. During the evaluation of the proposed algorithm, the concept of teaching from TLBO is introduced into the BSA to guide optimal individuals, thus improving the convergence rate of the algorithm. The learning behavior among individuals in the student phase of TLBO facilitates interindividual learning and provides beneficial information for its evolution, which is introduced into the BSA to ensure the diversity of the population. The comprehensive test results of different PV module models in different environmental conditions show that the proposed algorithm is more advantageous for parameter extraction than other existing algorithms. This can be seen in the simulation experiments of two commercial PV models, where the simulated current is consistent with the measured current at each measured voltage. This demonstrates that the proposed TLBOBSA is an accurate and reliable tool for evaluating unknown parameters of PV models.
Geochronological and geochemical constraints on the petrogenesis of alkali granites from the Makrohar Granulite Belt: Evidence for Mesoproterozoic extensional regime in the eastern Central Indian Shield
Authors: Yadav Bhupendra S. , Ahmad Talat , Bhutani Rajneesh , Kaulina Tatiana , Bayanova Tamara 
Published: October 2022

The Chotanagpur Gneissic Complex (CGC) is characterized by the Makrohar Granulite Belt (MGB) at its north‐western margin parallel to Son‐Narmada lineaments. The MGB exhibits a typical association of mantle‐derived mafic tholeiitic and alkaline rocks along with the felsic units. The zircon U–Pb data on the intrusive granite gneiss from this association define a crystallization age of 1,498 ± 38 Ma, representing a widespread Mesoproterozoic within‐plate magmatic event in CGC synchronous with the breakup of the Columbia Supercontinent. These granite gneisses have an alkaline affinity and are metaluminous in character. They exhibit many of the geochemical characteristics of anorogenic (A‐type) magmas, including enrichment of incompatible trace elements, like Zr, Hf, Nb, Y, Ga, and rare earth elements (REE), but low in Ba and Sr as well as high FeOt/(FeOt + MgO) (~0.98) values and Ga/Al (~3.92) ratios. They show less fractionated REE patterns, characterized by relatively enriched LREE and flat HREE with negative Eu anomaly, and have high Zr‐saturation temperatures (~955°C). Considering their field characteristics and all the geochemical and isotopic features, we conclude that they were derived from melting the lower crust metasomatized by mantle‐derived alkali‐rich fluids due to asthenospheric upwelling.
Geochemistry of the Neoarchean Dodguni carbonates of Chitradurga greenstone belt, Dharwar Craton, India: Implications on depositional environment
Authors: Khelen Chanu Arubam , Manikyamba Chakravadhanula , Subramanyam Konduri Srinivasa Visweswara , Raza Waseem , Reddy Gangula Harshitha 
Published: October 2022

The carbonates of the Dodguni area of the Chitradurga greenstone belt, Dharwar Craton, India were studied to understand the Archean diagenetic and palaeo‐depositional conditions using carbon and oxygen isotopes along with whole‐rock geochemistry. These carbonates show significant variation in δ13C and δ18O (−1.73‰ Vienna Peedee Belemnite [VPDB] to −0.45‰ VPDB and δ18O vary from −13.51‰ VPDB to −8.46‰ VPDB, respectively). The rare earth element (REE) + Y (rare earth elements and yttrium) of the studied carbonate rocks exhibit flat and uniform patterns (PrSN/YbSN = 0.4–1), slight positive La, Eu and Gd anomalies (CeSN/CeSN* = 0.8–0.9; EuSN/EuSN* = 0.7–1.4 and GdSN/GdSN* = 2–2.3, respectively) with slight positive Ce anomalies (PrSN/PrSN* = 0.84–0.86) and superchondritic Y/Ho ratios (Y/Ho = 29–45; chondritic Y/Ho = 28). Their negative δ13C (−1.75‰ to −0.45‰) values are attributed to the influence of higher bio‐productivity during their deposition and oxidation of organic carbon. The geochemical and isotopic systematics suggest that the Dodguni limestones are not affected by the diagenetic and metamorphic processes and record the REE geochemistry of the ancient seawater in which they were precipitated. The comprehensive geochemical including the isotopic studies of the Archean carbonate rocks of the Dharwar Craton, indicate their deposition in shallow marine conditions, precipitation in high temperatures with significant hydrothermal input under the influence of high bio‐productivity, thereby providing valuable constraints on the palaeoceanography and geochemical evolution of the Archean sea.