bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thresholds for post‐wildfire debris flows: Insights from the Pinal Fire, Arizona, USA
Authors: Raymond Carissa A. , McGuire Luke A. , Youberg Ann M. , Staley Dennis M. , Kean Jason W. 
Published: December 2019

AbstractWildfire significantly alters the hydrologic properties of a burned area, leading to increases in overland flow, erosion, and the potential for runoff‐generated debris flows. The initiation of debris flows in recently burned areas is well characterized by rainfall intensity‐duration (ID) thresholds. However, there is currently a paucity of data quantifying the rainfall intensities required to trigger post‐wildfire debris flows, which limits our understanding of how and why rainfall ID thresholds vary in different climatic and geologic settings. In this study, we monitored debris‐flow activity following the Pinal Fire in central Arizona, which differs from both a climatic and hydrogeomorphic perspective from other regions in the western United States where ID thresholds for post‐wildfire debris flows are well established, namely the Transverse Ranges of southern California. Since the peak rainfall intensity within a rainstorm may exceed the rainfall intensity required to trigger a debris flow, the development of robust rainfall ID thresholds requires knowledge of the timing of debris flows within rainstorms. Existing post‐wildfire debris‐flow studies in Arizona only constrain the peak rainfall intensity within debris‐flow‐producing storms, which may far exceed the intensity that actually triggered the observed debris flow. In this study, we used pressure transducers within five burned drainage basins to constrain the timing of debris flows within rainstorms. Rainfall ID thresholds derived here from triggering rainfall intensities are, on average, 22 mm h−1 lower than ID thresholds derived under the assumption that the triggering intensity is equal to the maximum rainfall intensity recorded during a rainstorm. We then use a hydrologic model to demonstrate that the magnitude of the 15‐min rainfall ID threshold at the Pinal Fire site is associated with the rainfall intensity required to exceed a recently proposed dimensionless discharge threshold for debris‐flow initiation. Model results further suggest that previously observed differences in regional ID thresholds between Arizona and the San Gabriel Mountains of southern California may be attributed, in large part, to differences in the hydraulic properties of burned soils. © 2019 John Wiley & Sons, Ltd.
Edge computing and power control in NOMA‐enabled cognitive radio networks
Authors: Cheng Yuxia , Liu Zhanjun , Chen Qianbin , Liang Chengchao 
Published: December 2019

AbstractDue to the limited computation resources of mobile devices in cognitive radio networks, the secondary users in the network can suffer from long executing time, which is not acceptable for latency‐sensitive and computation‐intensive tasks. To tackle this issue, this paper proposes to reduce the task computing latency for secondary networks by offloading the tasks to edge servers through leveraging mobile edge computing (MEC) that is emerging as a promising technology to augment the computation capacity of mobile devices. Specifically, under the conditions that the interference caused by secondary users is tolerable to primary user and within the available computation resources of the MEC server, the primary user and secondary users both can offload tasks to the MEC server through nonorthogonal multiple access. Thus, we jointly formulate the offloading decision and power control as an optimization problem, aiming at minimizing the overall computing latency for secondary networks. To overcome the computational complexity caused by the nonconvexity of the original problem, we transform the original problem to a solvable problem and decouple the transformed problem into the separate offloading decision and power control. An iterative algorithm is proposed based on block coordinate decent method to achieve the near‐optimal solution. Simulation results show that under the same parameters, such as the number of primary users, maximum transmit power, computational capability of the MEC server and the computational capability of the secondary users, the proposed NOMA‐enabled computation offloading scheme can effectively reduce the overall computing latency for the secondary network and improve the percentage of offloading secondary users than those of OMA‐enabled.
Analytic vision on fog computing for effective load balancing in smart grids
Authors: Rani Shalli 
Published: December 2019

AbstractThe Internet of Things generates a massive amount of data through sensors and other physical devices, which cause latency and delay in processing time and response time of smart grid (SG) services. To increase the efficiency of SGs, cloud computing provides a pay‐per model approach to transmit the collected data and enhances the scalability and functionality of end devices. Moreover, in load balancing (LB), resource utilization, and distribution mechanism, milliseconds also make an effect where delays or jitters are not acceptable. Fog computing, an extension of cloud provides computing, networking, storage, communication at the edge of the network, and has overcome the existing challenges of SGs. In this article, a new hybrid model on the highly virtualized platform is proposed. Three algorithms for LB: throttled, round robin, and particle swarm optimization, are analyzed and compared. Moreover, this article also highlights some cost minimization and effective utilization approaches to distribute resources efficiently to provide services in SGs with respect to LB algorithms.
Forecasting with unbalanced panel data
Authors: Baltagi Badi H. , Liu Long 
Published: December 2019

AbstractThis paper derives the best linear unbiased prediction (BLUP) for an unbalanced panel data model. Starting with a simple error component regression model with unbalanced panel data and random effects, it generalizes the BLUP derived by Taub (Journal of Econometrics, 1979, 10, 103–108) to unbalanced panels. Next it derives the BLUP for an unequally spaced panel data model with serial correlation of the AR(1) type in the remainder disturbances considered by Baltagi and Wu (Econometric Theory, 1999, 15, 814–823). This in turn extends the BLUP for a panel data model with AR(1) type remainder disturbances derived by Baltagi and Li (Journal of Forecasting, 1992, 11, 561–567) from the balanced to the unequally spaced panel data case. The derivations are easily implemented and reduce to tractable expressions using an extension of the Fuller and Battese (Journal of Econometrics, 1974, 2, 67–78) transformation from the balanced to the unbalanced panel data case.
Extraction, purification, characterization, anticoagulant activity, and anticoagulant mechanism of polysaccharides from the heads of Hypomesus olidus
Authors: Zhang Xuan , Ma Xin‐Tong , Xu Yu , Jiang Guo‐Chuan , Zhang Jia‐Lin , Liu Xue‐Jun , Yan Xiao‐Hui 
Published: December 2019

AbstractThe aim of this work was to extract, isolate, and purify polysaccharides from the heads of Hypomesus olidus and to evaluate their anticoagulant activities and anticoagulant mechanisms. Response surface methodology was used to optimize the extraction conditions for ultrasonic‐assisted extraction of polysaccharides from the heads of Hypomesus olidus. The optimal extraction conditions consisted of ultrasonic power of 275 W, ultrasonic time of 50 min, and solid–liquid ratio of 5 ml/g, giving the yield of crude polysaccharides (GYT) of 7.73 ± 0.042%. Three polysaccharide fractions, GYT‐1, GYT‐2, and GYT‐3 were purified from GYT by using DEAE‐cellulose‐52 column and Sephadex G‐100 column for anticoagulant activities. The results showed that two doses (2 and 4 mg/ml) of GYT‐1 and GYT‐3 could significantly prolong (p < .01) in partial thromboplastin time (APTT) (2.19 and 2.37 times, 2.22 and 2.44 times, respectively) and thrombin time (TT) (2.39 and 2.46 times, 2.44 and 2.80 times, respectively) compared with normal control. In particular, GYT‐3 had stronger anticoagulant activity than GYT‐1, and it was composed of arabinose, fructose, glucose, and lactose with molar ratios of 0.595:1: 2.026:0.273. However, GYT‐2 had no anticoagulant activity (p > .05). In addition, anticoagulation mechanism of polysaccharides from the heads of Hypomesus olidus (GYT‐3) was evaluated. The results showed that the anticoagulant activity of GYT‐3 was based on their binding with antithrombin AT‐III. And the inhibitory effects of GYT‐3 on factor IIa and Xa were related to the concentration of AT‐III in plasma. This study may provide a new and promising anticoagulant drug.
Restructuring of contralateral gray matter volume associated with cognition in patients with unilateral temporal lobe glioma before and after surgery
Authors: Hu Guanjie , Hu Xinhua , Yang Kun , Liu Dongming , Xue Chen , Liu Yong , Xiao Chaoyong , Zou Yuanjie , Liu Hongyi , Chen Jiu 
Published: December 2019

AbstractGlioma can cause variable alterations to the structure and function of the brain. However, there is a paucity of studies on the gray matter (GM) volume alterations in the brain region opposite the temporal glioma before and after surgery. Therefore, the present study was initiated to investigate the alternation in contralateral homotopic GM volume in patients with unilateral temporal lobe glioma and further, assess the relationship between GM volume alternations with cognition. Eight left temporal lobe glioma patients (LTPs), nine right temporal lobe glioma patients (RTPs), and 28 demographically matched healthy controls (HCs) were included. Using voxel‐based morphometry method, alternations in the contralateral homotopic GM volume in patients with unilateral temporal lobe glioma was determined. Furthermore, the correlation analysis was performed to explore the relationship between cognitive function and altered GM volume. In the preoperative analysis, compared to HCs, LTPs exhibited increased GM volume in right inferior temporal gyrus and right temporal pole (superior temporal gyrus), and, RTPs presented increased GM volume in left inferior temporal gyrus. In the postoperative analysis, compared to HCs, RTPs presented increased GM volume in left middle temporal gyrus. Furthermore, the increased GM volume was significantly positively correlated with the memory test but negatively correlated with the visuospatial test. This study preliminarily confirmed that there were compensatory changes in the GM volume in the contralateral temporal lobe in unilateral temporal lobe glioma patients. Furthermore, alterations of GM volume may be a mechanism for cognitive function compensation.
Pseudomonas aeruginosa‐mannose sensitive hemagglutinin injection therapy for the treatment of chyle fistula following neck dissection
Authors: Chen Qiang , Zou Xiuhe , Ma Yu , Liu Feng , Wei Tao , Li Zhihui , Gong Rixiang , Zhu Jingqiang 
Published: December 2019

AbstractBackgroundThe efficacy of Pseudomonas aeruginosa‐mannose sensitive hemagglutinin (PA‐MSHA) injection therapy in the treatment of chyle fistula following neck dissection is unclear.MethodsThis prospective study enrolled 26 patients who developed chyle fistula after neck dissection. Patients were divided into high‐output (>500 mL) and low‐output groups (≤500 mL) and were initially treated conservatively for 5 days in the high‐output group or 7 days in the low‐output group. When conservative treatment failed, topical PA‐MSHA therapy was applied.ResultsTwelve of 26 patients were cured with conservative treatment, and the remaining 14 patients were all successfully resolved by PA‐MSHA therapy. Chyle fistula got resolved in the low‐output and high‐output groups after the initiation of therapy were at a median 1 days and 6 days, respectively. Among them, 12 (85.7%) patients experienced fever and 11 (78.6%) patients experienced neck pain.ConclusionsTopical PA‐MSHA injection therapy could effectively manage chyle fistula following neck dissection.
Anhydrous Conditions Enable the Catalyst‐Free Carboxylation of Aromatic Alkynes with CO2 under Mild Conditions
Authors: Toniolo Davide , Bobbink Felix D. , Dyson Paul J. , Mazzanti Marinella 
Published: December 2019

AbstractThe direct carboxylation of aromatic alkynes with CO2, a cheap and widely available C1 source, is the most attractive method for the synthesis of carboxylic acids. Here we show that direct carboxylation of terminal alkynes can be simply performed in near‐quantitative yield in four hours with anhydrous Cs2CO3 under mild conditions without need of a metal catalyst.
Convolutional neural network in the detection of lung carcinoma using transfer learning approach
Authors: Lakshmi D. , Thanaraj K. Palani , Arunmozhi M. 
Published: December 2019

AbstractBackgroundLung carcinoma is the leading cause of 1.76 million deaths worldwide. GLOBOCAN 2018 report says lung cancer occupies the first position in terms of incidence and mortality rate. Reasons include limited access to timely diagnosis and treatment.ObjectiveThis research work presents the viability of using convolutional neural network (CNN) for lung carcinoma detection. The proposed network automatically detects the lung carcinomas tissues through transfer learning without the difficulty of specifying features for image classification.Subjects and methodsThe study involves lung CT images of 12 male and 4 female subjects, aging between 35 and 77 years. These images are obtained in Bitmap image format with a resolution of 512 × 512. Two cases namely healthy and carcinoma are taken for study. Carcinoma cases include poorly differentiated carcinoma, moderately differentiated carcinoma. The training data consists of 800 lung CT slices, validation set consists of 100 CT images, and test data consist of 100 images, respectively.ResultsExperimental results demonstrate the VGG16 and VGG 19 network implementation with the area under the receiver operating characteristics of 0.930 and 0.90, respectively. VGG19 compete well with a sensitivity and specificity of 80% and 100% compared to VGG16 with 98% and 88%, respectively.ConclusionHence, the implementation of VGG16 and VGG19 with good accuracy proves that CNN used for lung carcinoma detection leading to timely diagnosis and treatment may decrease the mortality rate.
Decoding visual network‐related dynamic functional connectivity for eyes‐open and eyes‐closed using machine learning
Authors: Wang Xun‐Heng , Jiao Yun , Li Lihua 
Published: December 2019

AbstractEyes‐open (EO) and eyes‐closed (EC) are the two experimental conditions during resting state functional magnetic resonance imaging (fMRI) scan sessions. However, the dynamic neural mechanisms of EO/EC based on intrinsic connectivity networks (ICNs) remains largely unexplored. This paper aimed to decode the dynamic internetwork neural mechanisms for EO/EC using data mining and to identify EO/EC resting state fMRI scans based on machine learning. To achieve these goals, the two states were analyzed using the discriminative models, resulting in total accuracy of 85.87%, a sensitivity of 91.3%, and a specificity of 80.43%. In addition, the discriminative features discovered using data mining were related to previous findings. In summary, we applied visual network‐related inter‐ICN features to decode the neural mechanisms of EO/EC. The reproducible results suggested that visual network‐related inter‐ICN dynamic features could be beneficial for decoding visual attentions, and had potential as neuroimaging‐markers to identify EO/EC resting state fMRI scans.
MicroRNA‐mediated suppression of P‐glycoprotein by quantum dots in lung cancer cells
Authors: Sun Yimin , Zhang Jie , Yin Huancai , Yin Jian 
Published: December 2019

AbstractThe interactions between adenosine triphosphate‐binding cassette (ABC) transporters and nano‐sized materials are attracting increasing attention, due to their great potential in overcoming the multidrug resistance (MDR) phenomena in cancer treatment. However, the inner mechanisms involved in the interactions are largely unknown. In this study, two commercial quantum dots (QDs), CdSe/ZnS‐MPA and CdSe/ZnS‐GSH, were tested for their interactions with P‐glycoprotein (P‐gp), as well as the relating mechanisms in lung cancer (A549) cells. Both QDs significantly suppressed the gene and protein expressions of P‐gp in A549 cells. To explain this, the gene expressions of nine relating microRNAs (miRNAs) were evaluated. The results indicated a shared up‐regulation of miR‐34b and miR‐185 by both QDs. Furthermore, mimics and inhibitors of miR‐34b and miR‐185 significantly enhanced and suppressed the gene and protein expressions of P‐gp, respectively, confirming the modulatory function of these two miRNAs on P‐gp. Interestingly, expressions of both miRNAs were suppressed during treatment with Cd2+ and doxorubicin, which induced the expression of P‐gp, indicating the universality of these miRNAs‐related mechanisms. Thus, as miR‐34b and miR‐185 participated in the suppression of P‐gp functions in A549 cells they could be interesting targets for the treatment of lung cancer.
Quantitative structure–property relationship models to predict thermodynamic properties of some mono and polycyclic aromatic hydrocarbons using genetic algorithm‐multiple linear regression
Authors: Dialamehpour Fatemeh , Shafiei Fatemeh 
Published: December 2019

AbstractPolycyclic aromatic hydrocarbons (PAHs) are a class of diverse organic compounds. Quantitative structure–property relationship (QSPR) models are used for modeling and predicting the thermodynamic properties of 45 monocyclic aromatic hydrocarbons (MAHs) and PAHs. Thermodynamic properties of PAHs such as heat capacity (C
v; J mol−1 K−1), thermal energy (Eth; kJ mol−1), and entropy (S; J mol−1 K−1) are calculated at the HF level of theory and 6‐311G *basis sets using the Gaussian 09 program. A set of molecular descriptors is calculated for selected compounds using the software Dragon. The genetic algorithm (GA) and backward stepwise multiple linear regression (MLR) techniques are used to obtain suitable QSPR models. The predictive ability of the models is checked using several criteria for internal and external model validation. The results show that three descriptors (Uindex, nAT, HTe) can be efficiently used for estimating S, one descriptor (HTe) for modeling Eth, and also one descriptor (Uindex) for predicting C
v of the considered compounds. The results and discussion lead to the conclusion that the models established by GA‐MLR have good correlation of the thermodynamic properties, which means QSPR models can be efficiently used for predicting the above‐mentioned properties and designing new molecules of MAHs and PAHs.
Is variation in tail vertebral morphology linked to habitat use in chameleons?
Authors: Luger Allison M. , Ollevier Anouk , De Kegel Barbara , Herrel Anthony , Adriaens Dominique 
Published: December 2019

AbstractChameleons (Chamaeleonidae) are known for their arboreal lifestyle, in which they make use of their prehensile tail. Yet, some species have a more terrestrial lifestyle, such as Brookesia and Rieppeleon species, as well as some chameleons of the genera Chamaeleo and Bradypodion. The main goal of this study was to identify the key anatomical features of the tail vertebral morphology associated with prehensile capacity. Both interspecific and intra‐individual variation in skeletal tail morphology was investigated. For this, a 3D‐shape analysis was performed on vertebral morphology using μCT‐images of different species of prehensile and nonprehensile tailed chameleons. A difference in overall tail size and caudal vertebral morphology does exist between prehensile and nonprehensile taxa. Nonprehensile tailed species have a shorter tail with fewer vertebrae, a generally shorter neural spine and shorter transverse processes that are positioned more anteriorly (with respect to the vertebral center). The longer tails of prehensile species have more vertebrae as well as an increased length of the processes, likely providing a greater area for muscle attachment. At the intra‐individual level, regional variation is observed with more robust proximal tail vertebrae having longer processes. The distal part has relatively longer vertebrae with shorter processes. Although longer, the small size and high number of the distal vertebrae allows the tail to coil around perches.
Recognition of the gluconeogenic enzyme, Pck1, via the Gid4 E3 ligase: An in silico perspective
Authors: Ismail Alaa M. , Elfiky Abdo A. , Elshemey Wael M. 
Published: December 2019

AbstractGluconeogenesis, the reverse process of glycolysis, is a favorable mechanism at conditions of glucose deprivation. Pck1 is a rate‐limiting gluconeogenic enzyme, where its deficiency or mutation contributes to serious clinical situations as neonatal hypoglycemia and liver failure. A recent report confirms that Pck1 is a target for proteasomal degradation through its proline residue at the penultimate position, recognized by Gid4 E3 ligase, but with a lack of informative structural details. In this study, we delineate the localized sequence motif, degron, that specifically interact with Gid4 ligase and unravel the binding mode of Pck1 to the Gid4 ligase by using molecular docking and molecular dynamics. The peptide/protein docking HPEPDOCK web server along with molecular dynamic simulations are applied to demonstrate the binding mode and interactions of a Pck1 wild type (SPSK) and mutant (K4V) with the recently solved structure of Gid4 ligase. Results unveil a distinct binding mode of the mutated peptide compared with the wild type despite having comparable binding affinities to Gid4. Moreover, the four‐residue peptide is found insufficient for Gid4 binding, while the seven‐residue peptide suffices for binding to Gid4. The amino acids S134, K135, and N137 in the loop L1 (between β1 and β2) of the Gid4 are essential for the stabilization of the seven‐residue peptide in the binding site of the ligase. The presence of Val4 instead of Lys4 smashes the H‐bonds that are formed between Lys4 and Gid4 in the wild type peptide, making the peptide prone to bind with the other side of the binding pocket (L4 loop of Gid4). The dynamics of Gid4 L3 loop is affected dramatically once K4V mutant Pck1 peptide is introduced. This opens the door to explore the mutation effects on the binding mode and smooth the path to target protein degradation by design competitive and non‐competitive inhibitors.
Climate regionalization in Bolivia: A combination of non‐hierarchical and consensus clustering analyses based on precipitation and temperature
Authors: Abadi Azar M. , Rowe Clinton M. , Andrade Marcos 
Published: December 2019

AbstractClimate regionalization is an inseparable part of many climate change and environmental studies. Delineating climatologically homogeneous regions enhances the utility of such studies and reduces the biases due to the uncertainties associated with climate model outputs at individual grid points which both lead to better understanding of the atmospheric mechanisms affecting a region's climate. Throughout time, researchers and statisticians have developed different methods to perform regionalization in which the techniques are highly dependent on the nature and accessibility of the data. This research aims to divide Bolivia into smaller, coherent climate subdivisions. To achieve this goal, we first apply the non‐hierarchical k‐means clustering method to climatologies of monthly accumulated precipitation and monthly average temperature separately using a gridded observation dataset for Bolivia spanning from 1979 to 2010. The clustering is performed on the two variables separately to avoid arbitrary attribute scaling and information redundancy as well as to gain a better understanding of these individual variables across Bolivia. Consensus clustering then finds the categorical intersection of the two independent clusters to create homogeneous climate regions. Results from this study show that Bolivia can be divided into 10 climatically distinguishable subdivisions largely explicable by topography and latitude, which are the key climate control factors in the region.