bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developing a smart fuel using artificial neural network for compression ignition engine fueled with Calophyllum inophyllum diesel blend at various compression ratio
Authors: Venugopal Paramaguru , Kasimani Ramesh , Chinnasamy Suresh 
Published: October 2019

AbstractIn machinery, it is evident that the computing system for self‐automated machinery derives nonlinear and complex equations by comparing the machinery's different input parameters with their corresponding performance output parameters. In order to operate the machinery with good performance and better efficiency, the computing system needs a machine‐learning algorithm. Most recent researchers have concentrated more on self‐driving vehicle, which seems to be lack of developing a strong algorithm for compression ignition (CI) engines to predict the performance and emission output parameter. Thus, this article deals with the prediction of performance and emission characteristics of CI engine fueled with 25% Calophyllum inophyllum and 75% diesel blend (CIB25) at various compression ratios using artificial neural network (ANN). Performance and emission tests were conducted in a single‐cylinder four‐stroke variable‐compression‐ratio CI engine fueled with CIB25 with varying loads and at a constant speed of operation. Experimental investigation indicates that 18:1 compression ratio gives better performance results when CIB25 is used as the fuel. Emission test results show better emission characteristics at 17:1 compression ratio. These results show that some input factors affect the output factors under some set of operating conditions, while some input factors improve them. ANN developed for the CI engine learns how the input factors affect and improve the output factors. Also, developed neural network is found to be satisfactory, and it predicts the output at a regression value of 0.998 with an average error of 1.77% in the case of CIB25.
Binary adsorption of Cu(II) and Ni(II) on Lai'yang bentonite: Kinetics, equilibrium, competition quantitative and mechanisms investigation
Authors: Xiao Fei , Cao Xiao‐qiang , Lyu Xian‐jun , Li Lin , Qiu Jun , Zhang Yan , Wang Peng , Zhang Qing‐jian , Wang Qing‐biao 
Published: October 2019

AbstractIn this study, the competitive adsorption of Cu(II) and Ni(II) adsorption onto bentonite were investigated. The effects of initial adsorbate concentration, pH, contact time, temperature on adsorption and the kinetics, thermodynamic, quantification of adsorption competition and competitive mechanisms have been studied. The results indicated that Cu(II) has a higher affinity than Ni(II) for adsorption on bentonite. But the inhibition effect was not noticeable under alkaline conditions. The Langmuir and pseudo‐second‐order kinetics models can be applied to simulate the isothermal adsorption and adsorption dynamic, respectively. Under a single system/binary system, the maximum adsorption capacity of bentonite for Cu(II) and Ni(II) is 12.76/10.57 and 11.12/9.11 mg/g, respectively. The equilibrium adsorption capacity reduction rate is suitable for quantitative characterization of adsorption competition under any concentration conditions; adsorption competition coefficient is more suitable for low concentration adsorption; although the distribution coefficient is not suitable for quantitative adsorption competition at high concentrations, it can be used to characterize the variation of adsorption competitiveness of Cu(II) at different concentrations. The higher electronegativity, lower first hydrolysis constant and Misono softness, and a better “guest‐host” consistency between Cu(II)O6 and the vacancies in the montmorillonite octahedral sheet make the higher affinity of Cu(II) to bentonite and result in the possible ion exchange between Cu(II) in solution and adsorbed Ni(II). In addition, at high concentrations, Cu(II) and Ni(II) precipitates formed on the surface of montmorillonite may cause remained Cu(II) ions in the solution unable to enter the internal space of the montmorillonite octahedron.
Association of maternal folate status in the second trimester of pregnancy with the risk of gestational diabetes mellitus
Authors: Xie Kaipeng , Xu Pengfei , Fu Ziyi , Gu Xiaohong , Li Hui , Cui Xianwei , You Lianghui , Zhu Lijun , Ji Chenbo , Guo Xirong 
Published: October 2019

AbstractInterest in the high folate status of pregnant women has increased due to its role in the prevention of neural tube defects (NTDs). The effect of increased red blood cell (RBC) folate status during the second trimester of pregnancy on gestational diabetes mellitus (GDM) remains unclear. We measured RBC folate concentrations by competitive protein‐binding assay and obtained clinical information from electronic medical records. Logistic regression analysis was used to explore the associations of RBC folate concentrations with risks of gestational diabetes mellitus (GDM). We further assessed the potential nonlinear relations between continuous log‐transformed RBC folate concentrations and GDM risk by using the restricted cubic splines. We observed high RBC folate concentrations in GDM patients compared to control group [median (interquartile range, IQR), GDM vs. controls: 1,554.03 (1,240.54–1,949.99) vs. 1,478.83 (1,124.60–1,865.71) nmol/L, p = .001]. Notably, high folate concentrations were significantly associated with an increased risk of GDM [RR per 1‐SD increase: 1.16 (1.03, 1.30), p = .012] after adjustment for maternal age, parity, and body mass index (BMI) at enrollment. In the restricted cubic spline model, a test of the null hypothesis of the linear relationship was rejected (p = .001). Our study firstly showed that maternal RBC folate concentrations during the second trimester of pregnancy increase the risk of GDM in a Chinese population. Further randomized clinical trials (RCTs) are warranted to confirm the adverse effect.
Neurochemical regulation of the expression and function of glial fibrillary acidic protein in astrocytes
Authors: Li Dongyang , Liu Xiaoyu , Liu Tianming , Liu Haitao , Tong Li , Jia Shuwei , Wang Yu‐Feng 
Published: October 2019

AbstractGlial fibrillary acidic protein (GFAP), a type III intermediate filament, is a marker of mature astrocytes. The expression of GFAP gene is regulated by many transcription factors (TFs), mainly Janus kinase‐2/signal transducer and activator of transcription 3 cascade and nuclear factor κ‐light‐chain‐enhancer of activated B cell signaling. GFAP expression is also modulated by protein kinase and other signaling molecules that are elicited by neuronal activity and hormones. Abnormal expression of GFAP proteins occurs in neuroinflammation, neurodegeneration, brain edema‐eliciting diseases, traumatic brain injury, psychiatric disorders and others. GFAP, mainly in α‐isoform, is the major component of cytoskeleton and the scaffold of astrocytes, which is essential for the maintenance of astrocytic structure and shape. GFAP also has highly morphological plasticity because of its quick changes in assembling and polymerizing states in response to environmental challenges. This plasticity and its corresponding cellular morphological changes endow astrocytes the functions of physical barrier between adjacent neurons and stabilizer of extracellular environment. Moreover, GFAP colocalizes and even molecularly associates with many functional molecules. This feature allows GFAP to function as a platform for direct interactions between different molecules. Last, GFAP involves transportation and localization of other functional proteins and thus serves as a protein transport guide in astrocytes. This guiding role of GFAP involves an elastic retraction and extension cytoskeletal network that couples with GFAP reassembling, transporting, and membrane protein recycling machinery. This paper reviews our current understanding of the expression and functions of GFAP as well as their regulation.
Graphitic solid core carbon nanorods grown on silica sands using electron cyclotron resonance chemical vapor deposition as a highly efficient and green sorbent for removal of phenol derivatives from water sources
Authors: Mehmanravesh Samira , Farhadi Khalil , Torabian Ali , Hasani Amirhesam 
Published: October 2019

AbstractIn this study, graphitic solid core carbon nanorods (GSCNRs) were, for the first time, anchored to the surface of silica sands through the electron cyclotron resonance chemical vapor deposition method to provide coated silica sands as a new, low‐cost, green, and efficient adsorbent for the removal of organic pollutants such as phenol and 2,4‐dichlorophenol (2,4‐DCP) from aqueous mediums. The characteristics of GSCNRs/SiO2 were confirmed through Fourier‐transform infrared spectroscopy, X‐ray diffraction, and scanning electron microscopy techniques. After the optimization of several parameters, the removal efficiency of phenol and 2,4‐DCP using 1 g of adsorbent amount, the initial concentration of pollutants (10 mg/L phenol and 15 mg/L 2,4‐DCP), a contact time of 10 min (phenol) and 20 min (2,4‐DCP), and pH = 7 were 69 and 89%, respectively. The adsorption isotherm models of Langmuir and Freundlich, as well as pseudo‐first‐order and pseudo‐second‐order kinetic models, were examined under optimal conditions. Eventually, GSCNRs/SiO2 was regenerated five times for the removal of phenol and 2,4‐DCP. The removal efficiency of the tested contaminants from inlet raw water of a water treatment plant using the proposed adsorbent was investigated.
Role of type 2 innate lymphoid cell and its related cytokines in tumor immunity
Authors: Wan Jie , Cai Wei , Wang Huixuan , Cheng Jianjun , Su Zhaoliang , Wang Shengjun , Xu Huaxi 
Published: October 2019

AbstractType 2 innate lymphoid cells (ILC2s) have multiple functions that can respond to allergic diseases, parasite infection, metabolic homeostasis, tissue repair, and adipose metabolism homeostasis. In these diseases, ILC2s can be activated by various inflammatory cytokines released by damaged cells. Activated ILC2s produce different type 2 cytokines, including interleukin (IL)‐4, IL‐5, IL‐9, and IL‐13, which involved in the pathogenesis of many diseases. In recent years, the relationship between ILC2s and tumor diseases has attracted more and more attention. The role of ILC2s in tumor immunity depends on its surface molecules and cytokine context. This review aims to conclude tumorigenic and antitumorigenic roles of ILC2s, and the characters of ILC2s‐related cytokines in tumor diseases to provide a comprehensive overview of the impact of ILC2s in tumor immunity.
Recombinant expression of Aspergillus niger GH10 endo‐xylanase in Pichia pastoris by constructing a double‐plasmid co‐expression system
Authors: Long Lingfeng , Zhang Yunbo , Ren Hongyan , Sun Haiyan , Sun Fubao F , Qin Wensheng 
Published: October 2019

AbstractBACKGROUNDPrevious work has shown that GH10 endo‐xylanase presented better synergistic cooperation with cellulase to achieve effective hydrolysis. However, most currently reported commercial xylanolytic enzymes from Aspergillus niger belong to GH11 and there have been few studies regarding GH10 xylanase. In addition, to increase overall expression of heterologous endo‐xylanase in Pichia pastoris, a double‐plasmid co‐expression method, including the construction of recombinant P. pastoris using one expression vector followed by inserting another vector which targeted to different locus, was introduced.RESULTSA GH10 xylanase gene from A. niger BE‐2 (XynC) was optimized and constitutively expressed in P. pastoris GS115. Compared with the conventional single‐plasmid method, it appeared that the double‐plasmid strategy could considerably increase the XynC yield by ∼33%. To further improve enzyme production, cultivation conditions were optimized at shake‐flask level and then scaled up to a 5‐L bioreactor. Through high cell‐density fermentation, the expression level of GH10 XynC reached 1650 U mL−1. The XynC showed maximum activity at 55 °C and pH 5.0, and exhibited an excellent stability over a wide range of pH from 4.5 to 7.0. The kinetic parameters Km and Vmax values for beechwood xylan were 3.5 mg mL−1 and 2327 U mg−1, respectively.CONCLUSIONThe double‐plasmid co‐expression strategy introduced herein could greatly improve the XynC yield in P. pastoris. The GH10 xylanase from A. niger BE‐2 shared similar reaction conditions with the existing enzymatic hydrolysis, which might be a good candidate to assist cellulases for industrial application. © 2019 Society of Chemical Industry
The influence of grafting process on the optical, geometrical, and structural parameters of nylon‐6 fibers
Authors: Sokkar Taha Z. N. , El‐Bakary Mohammed A. , Sewidan Muhamed A. , Hamza Ahmed. A. 
Published: October 2019

AbstractMach–Zehnder interferometer technique is utilized to study the impact of grafting of the nylon‐6 fibers with poly (methyl methacrylate) (PMMA) polymer on the optical, geometrical, and structural properties. He–Ne laser diffraction technique is applied to study the changes in the fiber thickness of two samples (nylon‐6 blank and nylon‐6 grafted with PMMA) at different positions along the fiber length. The geometrical parameters are investigated by determining the cross‐sectional shape of the two samples. The results of the interferometric and the diffraction techniques show that there is no variation in the thickness of nylon‐6 fiber but variations in the thickness of the grafted nylon‐6 fiber are obvious. The optical and physical properties along the axis of these fibers are characterized by measuring their refractive indices, birefringence, polarizability per unit volume, dielectric constant, surface reflectivity and the refractive index profile. The results show that PMMA polymer changed the optical, geometrical, and structural properties of the nylon‐6 blank fiber. Microinterferograms are given for illustrations.
The scaling of terrestrial striking performance in western ratsnakes (Pantherophis obsoletus)
Authors: Penning David A. , Sawvel Baxter , Moon Brad R. 
Published: October 2019

AbstractIn many organisms, juveniles have performance capabilities that partly offset their disadvantageous sizes. Using high‐speed video recordings and imaging software, we measured the scaling of head morphology, axial morphology, and defensive strike performance ofPantherophis obsoletusacross their ontogeny to understand how size and morphology affect performance. Head measurements were negatively allometric whereas the cross‐sectional area (CSA) of epaxial muscles displayed positive allometry. The greater relative muscle CSA of larger ratsnakes allows them to produce higher forces relative to their mass, and those forces act on a relatively smaller head mass when it is thrust forward during striking. Maximum strike accelerations of 70–273.8 ms−2and velocities of 1.08–3.39 ms−1scaled positively with body mass but differed from the geometric predictions. Velocity scaled with mass0.15and acceleration scaled with mass0.17. Larger snakes struck from greater distances (range = 4.1–26 cm), but all snakes covered the strike distances with similarly short durations (84 ± 3 ms). The negatively allometric head size, isometry of anterior mass, and positively allometric muscle CSA enable largerP. obsoletusto strike with higher velocities and accelerations than smaller individuals. Our results contrast with the scaling of strike performance in an arboreal viper, whose strike distance and velocity were independent of body mass. When strike distance is modulated, all other performance capacities are affected because of the interdependence of acceleration, velocity, duration, and distance.
Extending regular edge‐colorings of complete hypergraphs
Authors: Bahmanian Amin , Haghshenas Sadegheh 
Published: October 2019

AbstractA coloring (partition) of the collection of all ‐subsets of a set is ‐regular if the number of times each element of appears in each color class (all sets of the same color) is the same number . We are interested in finding the conditions under which a given ‐regular coloring of is extendible to an ‐regular coloring of for and . The case was solved by Cruse, and due to its connection to completing partial symmetric latin squares, many related problems are extensively studied in the literature, but very little is known for . The case was solved by Häggkvist and Hellgren, settling a conjecture of Brouwer and Baranyai. The cases and were solved by Rodger and Wantland, and Bahmanian and Newman, respectively. In this paper, we completely settle the cases and .
Gender interactions between vertebral bone mineral density and fat content in the elderly: Assessment using fat–water MRI
Authors: Chen Chiao‐Chi , Liu Yi‐Jui , Lee Shiou‐Ping , Yang Hou‐Ting , Chan Wing P. 
Published: October 2019

BackgroundAdipose tissue is closely related to bone mass, bone quality, and bone fractures, but the connection between fat and bone is complex and gender‐related. Fat–water magnetic resonance imaging (MRI) and MR spectroscopy (MRS) are very useful tools for identifying tissue fat.PurposeTo assess gender interactions between bone mineral density (BMD), bone marrow fat, and body mass index (BMI) in the elderly using fat–water MRI and MRS.Study TypeProspective/cohort.PopulationSixty‐six women and 38 men (mean age, 62.3 years; range, 50–75 years), Asian.Field StrengthA 1.5T MR equipped with a body and spine array coil. STEAM MRS and T2* Dixon were performed.AssessmentVertebral bone marrow fat ratio (MFR), BMI, and BMD were measured. Correlations between these variables and differences in bone density in MFR were assessed between participants, divided into three groups based on bone density.Statistical TestsMultiple regression; Pearson tests; analysis of covariance; analysis of variance.ResultsMultiple regression analysis identified gender, vertebral bone MFR, and BMI as significant predictors of vertebral BMD (P < 0.001). Among the women, vertebral BMD was negatively correlated with vertebral MFR (P = 0.011), but among the men, it was positively correlated with BMI (P = 0.048), although this relationship was confounded by age and MFR. Moreover, vertebral bone marrow fat and BMI were indeed statistically uncorrelated in the elderly (P = 0.357 in women; P = 0.961 in men).Data ConclusionWe found gender interactions between fat and bone in the elderly. Higher bone marrow fat was correlated with lower trabecular BMD in older women but not in men. On the other hand, the positive correlation between BMI and BMD was more pronounced in men than in women.Level of Evidence: 2Technical Efficacy Stage: 2J. Magn. Reson. Imaging 2020;51:1382–1389.
Evaluation of silica from different vendors as the solid support of anion‐exchange chiral stationary phases by means of preferential sorption and liquid chromatography
Authors: Kohout Michal , Hovorka Štěpán , Herciková Jana , Wilk Maciej , Sysel Petr , Izák Pavel , Bartůněk Vilém , von Baeckmann Cornelia , Pícha Jan , Frühauf Peter 
Published: October 2019

AbstractChromatographic performance of a chiral stationary phase is significantly influenced by the employed solid support. Properties of the most commonly used support, silica particles, such as size and size distribution, and pore size are of utmost importance for both superficially porous particles and fully porous particles. In this work, we have focused on evaluation of fully porous particles from three different vendors as solid supports for a brush‐type chiral stationary phase based on 9‐O‐tert‐butylcarbamoyl quinidine. We have prepared corresponding stationary phases under identical experimental conditions and determined the parameters of the modified silica by physisorption measurements and scanning electron microscopy. Enantiorecognition properties of the chiral stationary phases have been studied using preferential sorption experiments. The same material was slurry‐packed into chromatographic columns and the chromatographic properties have been evaluated in liquid chromatography. We show that preferential sorption can provide valuable information about the influence of the pore size and total pore volume on the interaction of analytes of different size with the chirally‐modified silica surface. The data can be used to understand differences observed in chromatographic evaluation of the chiral stationary phases. The combination of preferential sorption and liquid chromatography separation can provide detailed information on new chiral stationary phases.
Optimization of wireless power transfer using artificial neural network: A review
Authors: Ali Azuwa , Mohd Yasin Mohd Najib , Jusoh Muzammil , Ahmad Hambali Nor Azura Malini , Abdul Rahim Siti Rafidah 
Published: October 2019

AbstractWireless power transfer (WPT) is widely explored and applied nowadays because of its simplicity in transferring power without using wire, easy maintenance, and equipment mobility. Due to mobility and compatibility attributes, WPT is utilized in powering biomedical devices, small electronic equipment, wireless sensor, mobile phones, and high voltage applications (eg, electric vehicles). The implementation of artificial neural network (ANN) in WPT has emerged as a powerful/prominent tool for estimating the performance parameters due to its learning and significant features. Such implementation can minimize design complexity and time‐consuming calculations. An early application of ANN employs the information derived from the collectively measured processes for training the ANN algorithm. After a suitable training process, the network output can be considered in place of computationally thorough representations to speed up the result search. To obtain precise result and optimize the parameters in WPT, several popular ANN algorithms have been used by researchers. This review paper highlighted the latest research specifically regarding the implementation of ANN in WPT, which included the types of ANN implemented in WPT, current WPT problem investigation that used ANN, and a comparison between the techniques. Moreover, the challenges and constraints of ANN techniques were elucidated at the end of this paper.
Morphological Identification of Bighead Carp, Silver Carp, and Grass Carp Eggs Using Random Forests Machine Learning Classification
Authors: Camacho Carlos A. , Sullivan Christopher J. , Weber Michael J. , Pierce Clay L. 
Published: October 2019

Abstract
Visual identification of fish eggs is difficult and unreliable due to a lack of information on the morphological egg characteristics of many species. We used random forests machine learning to predict the identity of genetically identified Bighead Carp Hypophthalmichthys nobilis, Grass Carp Ctenopharyngodon idella, and Silver Carp H. molitrix eggs based on egg morphometric and environmental characteristics. Family, genus, and species taxonomic-level random forests models were explored to assess the performance and accuracy of the predictor variables. The egg characteristics of Bighead Carp, Grass Carp, and Silver Carp were similar, and they were difficult to distinguish from one another. When combined into a single invasive carp class, the random forests models were ≥ 97% accurate at identifying invasive carp eggs, with a ≤5% false positive rate. Egg membrane diameter was the most important predictive variable, but the addition of ten other variables resulted in a 98% success rate for identifying invasive carp eggs from 26 other upper Mississippi River basin species. Our results revealed that a combination of morphometric and environmental measurements can be used to identify invasive carp eggs. Similar machine learning approaches could be used to identify the eggs of other fishes. These results will help managers more easily and quickly assess invasive carp reproduction.