bluuebunny/crossref_metadata_2025_split huggingface dataset:
Flavonoid extract of saffron by‐product alleviates hyperuricemia via inhibiting xanthine oxidase and modulating gut microbiota
Authors: Chen Na , Wang Ran , Li Hua , Wang Weihao , Wang Lan , Yin Xiaojie , Yao Rongmei , Yang Bin 
Published: August 2022

AbstractHyperuricemia was associated with the overproduction or inadequate excretion of uric acid, while its association with gut microbiota has emerged although few studies were focused on it. Previously, we have reported a flavonoid extract from saffron floral bio‐residues lowered uric acid in potassium oxonate‐induced hyperuricemic mice. In this study, the impacts of the flavonoid extract on potassium oxonate‐induced hyperuricemic rats were evaluated through its effects on serum, renal, intestinal uric acid, and xanthine oxidase activity. At the same time, the microbial and metabolic features of the flavonoid extract against hyperuricemia were explored using 16S rRNA sequencing techniques and serum metabolomics, respectively. According to the results, the flavonoid extract lowered serum and intestinal uric acid levels in hyperuricemic rats without kidney damage. On the one hand, it inhibited serum and liver xanthine oxidase activities and down‐regulated the expression of hepatic xanthine oxidase. On the other hand, it ameliorated the hyperuricemia‐associated gut microbiota dysbiosis and alleviated the disturbance of serum metabolome, especially of lipid and amino acid metabolites. The results suggested that the flavonoid extract of saffron floral bio‐residues exerts a potent antihyperuricemia effect by inhibiting xanthine oxidase to decrease uric acid production and modulating gut microbiota related to host metabolism.
A rapid and sensitive ultra‐performance liquid chromatography tandem mass spectrometry method for determination of anlotinib in plasma and dried blood spots: Method development, validation, and clinical application
Authors: Zhang Ji , Wang Wenzheng , Du Jiaqi , Li Cai , Wang Suyun , Han Yikai , Wang Huafei , Zong Hong , Cheng Zhe , Tian Xin 
Published: August 2022

RationaleAnlotinib is a multi‐target tyrosine kinase inhibitor, approved in China for treating several cancer types. Dose individualization based on therapeutic drug monitoring (TDM) is a useful tool to reduce toxicity. However, it is not convenient for patients to go to hospital for routine TDM via venous blood sampling at a certain time.MethodsAn ultra‐performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) method was developed and validated for determination of anlotinib in human plasma and dried blood spot (DBS), characterized by simple sample preparation, high sensitivity, and short analysis time. The assay was validated in the concentration range of 0.2–200 ng/mL in plasma and 5–1000 ng/mL in DBS. This method was applied to monitor anlotinib exposure levels in patients with advanced biliary tract cancer (BTC) and non‐small cell lung cancer (NSCLC).ResultsThe trough plasma concentration (Ctrough) of anlotinib was highly variable among BTC patients with coefficients of variation (CV) of 47.5%. DBS and venous blood samples were also collected from NSCLC patients to determine whether DBS sampling is a viable alternative sampling approach. Pearson correlation coefficient (R) between DBS and plasma concentration was 0.985. Bland–Altman plot demonstrated that the difference between estimated and measured plasma concentration was −2.9%. And 87% of sample pairs had a maximal deviation of ±20%.ConclusionsAnlotinib exhibits a high inter‐individual variability in plasma exposure, and DBS sampling could be a promising tool for TDM of anlotinib.
A redesign methodology generating predefined‐time differentiators with bounded time‐varying gains
Authors: Aldana‐López Rodrigo , Seeber Richard , Gómez‐Gutiérrez David , Angulo Marco Tulio , Defoort Michael 
Published: August 2022

AbstractThere is an increasing interest in designing differentiators, which converge exactly before a prespecified time regardless of the initial conditions, that is, which are fixed‐time convergent with a predefined upper bound of their settling time (UBST), due to their ability to solve estimation and control problems with time constraints. However, for the class of signals with a known bound of their th time derivative, the existing design methodologies yield a very conservative UBST, or result in gains that tend to infinity at the convergence time. Here, we introduce a new methodology based on time‐varying gains (TVG) to design arbitrary‐order exact differentiators with a predefined UBST. This UBST is a priori set as one parameter of the algorithm. Our approach guarantees that the UBST can be set arbitrarily tight, and we also provide sufficient conditions to obtain exact convergence while maintaining bounded TVG. Additionally, we provide necessary and sufficient conditions such that our approach yields error dynamics with a uniformly Lyapunov stable equilibrium. Our results show how TVG offer a general and flexible methodology to design algorithms with a predefined UBST.
Evaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA
Authors: Barnhart Theodore B. , Farmer William H. , Hammond John C. , Sexstone Graham A. , Curran Janet H. , Koch Joshua C. , Driscoll Jessica M. 
Published: August 2022

AbstractBuilding continental‐scale hydrologic models in data‐sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow statistics (FDSS) in defining hydrologic regions across Alaska, USA; (2) evaluated if the hydrologic regions represented different hydrologic processes; and (3) tested the ability of random forest and direct assignment techniques, informed by statistically estimated FDSS (FDSSest) and basin characteristics (BCs), to correctly assign ungaged locations to hydrologic regions. Six hydrologic regions were identified across the domain using FDSS. Differences in mean flow, phase shift of the seasonal cycle, and skewness were the primary characteristics defining each region. Two regions represented arctic and continental climates, generally in the northern portion of the domain; four regions represented the southern, maritime portion of the domain. Random forest modeling with BCs (67% success rate) outperformed FDSSest (58% success rate) suggesting that no statistically estimated streamflow was needed to assign ungaged locations to a region. For regions with many sites, most region assignment techniques performed similarly. Random forest modeling performance declined when BCs and FDSSest were both used to predict region membership, suggesting FDSSest had little information in addition to BCs. This analysis demonstrated that FDSS‐based hydrologic regions discern process differences across a data‐sparse and hydrologically diverse landscape. Process importance rankings from random forest‐derived BCs provided model‐independent information for making modeling decisions.Key points
Fundamental daily streamflow statistics produce distinct hydrologic regions across Alaska, USA
Distinct hydrologic processes are recognizable in the identified hydrologic regions
Using basin characteristics, random forest modeling was best able to assign ungaged locations to hydrologic regions
Random forest‐derived predictor importance suggests that hydroclimatic factors and permafrost presence/absence drive hydrologic region assignment
Understanding the influence of check dam and season on habitat use to develop habitat suitability criteria for overwintering tadpoles of Nanorana spp.
Authors: Jithin Vijayan , Das Abhijit , Johnson Jeyaraj A. 
Published: August 2022

AbstractUnderstanding habitat availability and use patterns are essential in developing comprehensive conservation strategies for focal species. Studies on amphibian larval habitat use are limited, especially from modified habitats. We investigated the habitat availability and use patterns of overwintering tadpoles of the Nanorana frog in an anthropogenically modified stream in the western Himalaya. Habitat was assessed in terms of depth, velocity, substrate type, and instream cover. We quantified the microhabitat preference of the tadpoles to develop habitat suitability criteria (HSC) curves, the biological component of habitat simulation tools used in instream flow management. We analyzed the data covering winter and post‐winter seasons using cumulative link mixed models to understand the influence of check dams and seasons on the hydraulic properties of microhabitats used by the tadpoles. We confirm the influence of check dam and season on velocity and the influence of season on depth used by the tadpoles. Based on this, we generated HSCs for tadpoles occurring in natural and modified pools during both seasons. We recommend intermediate water depths (30–60 cm) during the low flow season to sustain the tadpole population in the study stream and other required habitat features. The study underlines the importance of spatial and temporal variation in the habitat suitability for Nanorana tadpoles. These HSCs can be used in hydrological models for estimating the minimum ecological flow for overwintering tadpoles in the study area. A large‐scale study based on the recommendations can lead to a better conservation plan in light of altered streamflow in the western Himalaya region.
Out‐of‐bag stability estimation for k‐means clustering
Authors: Liu Tianmou , Yu Han , Blair Rachael Hageman 
Published: August 2022

AbstractClustering data is a challenging problem in unsupervised learning where there is no gold standard. Results depend on several factors, such as the selection of a clustering method, measures of dissimilarity, parameters, and the determination of the number of reliable groupings. Stability has become a valuable surrogate to performance and robustness that can provide insight to an investigator on the quality of a clustering, and guidance on subsequent cluster prioritization. This work develops a framework for stability measurements that is based on resampling and OB estimation. Bootstrapping methods for cluster stability can be prone to overfitting in a setting that is analogous to poor delineation of test and training sets in supervised learning. Stability that relies on OB items from a resampling overcomes these issues and does not depend on a reference clustering for comparisons. Furthermore, OB stability can provide estimates at the level of the item, cluster, and as an overall summary, which has good interpretive value. This framework is extended to develop stability estimates for determining the number of clusters (model selection) through contrasts between stability estimates on clustered data, and stability estimates of clustered reference data with no signal. These contrasts form stability profiles that can be used to identify the largest differences in stability and do not require a direct threshold on stability values, which tend to be data specific. These approaches can be implemented using the R package bootcluster that is available on the Comprehensive R Archive Network.
Nanoscale Morphological Characterization of Coordinated Binder and Solid Electrolyte Interphase in Silicon‐Based Electrodes for Li‐Ion Batteries
Authors: Huet Lucas , Moreau Philippe , Dupré Nicolas , Devic Thomas , Roué Lionel , Lestriez Bernard 
Published: August 2022

AbstractThe physical crosslinking of polymeric binders through coordination chemistry significantly improves the electrochemical performance of silicon‐based negative electrodes. Scanning electron microscopy coupled with energy dispersive X‐ray spectroscopy is used to probe the nanoscale morphology of such electrodes. This technique reveals the homogeneous coordination of carboxylated binder with Zn cations and its layering on the silicon surface. The solid electrolyte interphase (SEI) formed after the first cycle is denser with Zn‐coordinated binder and preferentially observed on binder‐depleted zones. The superiority of coordinated binders can be attributed to their capacity to better stabilize the electrode and the SEI layer due to improved mechanical properties. This results in a lower SEI impedance, a higher first cycle coulombic efficiency, and a 40% improvement of capacity retention after 50 cycles for highly loaded electrodes of over 6 mAh cm–2.
Scheduling algorithms for truly heterogeneous hierarchical fog networks
Authors: Kaur Amanjot , Auluck Nitin 
Published: August 2022

AbstractFog computing has emerged as a viable framework for processing delay sensitive applications. Modern applications consist of latency‐sensitive and latency‐tolerant jobs, leading to fog architectures that are often multi‐tiered/hierarchical. FiFSA (hierarchical first fog scheduling algorithm) and EFSA (hierarchical elected fog scheduling algorithm) are capable of scheduling both online and batch jobs on hierarchical fog‐cloud architectures. We consider heterogeneity in computing capacity—both among fog devices in separate layers, and among fog devices in the same layers. In general, online jobs with modest cpu requirements are scheduled on lower tier fog devices, and batch jobs with significant cpu requirements are scheduled on higher tier‐fog nodes, or the cloud data center (cdc). FiFSA assigns jobs to the first fog device with sufficient spare capacity. EFSA employs a MinMin heuristic that assigns jobs to the fog device that results in minimum completion time, while considering fog load. The performance of the proposed algorithms has been evaluated on a real‐life workload trace, using both simulation scenarios and a prototype testbed. FiFSA and EFSA offer an improvement of 19% to 70% in completion times and an improvement of 42% to 72% in system cost over other comparable algorithms.
Qualitative prediction of Thymoquinone in the high‐performance liquid chromatography optimization method development using artificial intelligence models coupled with ensemble machine learning
Authors: Usman Abdullahi Garba , Işik Selin , Abba Sani Isah 
Published: August 2022

AbstractIn this study, three various artificial intelligence‐based models were employed including two non‐linear namely; Hammerstein–Wiener, the neuro‐fuzzy model, and a trivial linear multi‐linear regression analysis for the qualitative prediction of Thymoquinone in high‐performance liquid chromatography optimization method development. Various parameters which include mobile phase composition, flow rate, and concentration of the standard are used as the independent variables. Whereby, the Thymoquinone retention time is simulated to be the dependent variable. The predicted and experimental results were further estimated by using dual indices to assess the performances, which include the determination coefficient as the goodness of fit and mean squared error. The obtained results depicted the promising capacity of the non‐linear models; Hammerstein–Wiener and neuro‐fuzzy model over multi‐linear regression analysis. For the ensemble machine learning techniques, the results obtained from the non‐linear ensemble paradigm (neuro‐fuzzy ensemble) showed its ability in boosting the efficiency of the single model's performance up to 28%. The results illustrated the robustness and validity of the artificial intelligence‐based models and further confirmed the potential of ensemble techniques for the prediction of Thymoquinone.
Mechanical behavior of Glass fiber‐reinforced polymer‐timber‐steel tube‐concrete composite columns under axial compression
Authors: Zhang Fubin , Xie Shaofeng , Xiao Jianzhuang , Singh Amardeep , Xu Jing , Fang Hai 
Published: August 2022

AbstractThis paper proposes a novel glass fiber‐reinforced polymer (GFRP)‐timber‐steel tube‐concrete composite column (GTSC) that combines an outer steel tube with GFRP fabric reinforcement, an inner timber core, and concrete for the rest of the space. The mechanical behavior of eight specimens of novel composite columns was investigated considering diameters of timber cores, layer numbers, and angles of GFRP laminates. The results showed that as the size of the timber core increased from 0 to 50 mm, the ductility and the energy dissipation capacity of the composite column maximum increased by 61.5% and 63.4%, respectively. Conversely, the ultimate load carrying capacity and stiffness decreased. It was also found that the timber core weakened the strength of the confined concrete. However, timber core reduced the weight of columns, which slowed down the reduction of the ultimate load carrying capacity of per unit GTSCs, with the stiffness remains unchanged. GFRP laminates with an angle of 60° provide the best stiffness and ductility, and the layer numbers of GFRP has a positive effect on GTSC's mechanical performance. In addition, an analytical model was proposed based on the ultimate equilibrium method, which accounts for the ultimate bearing capacity of GTSC based on the influence of timber. Analyses revealed a good correlation between analytical and experimental results.
Liver dysfunction and energy storage mobilization in traíra, Hoplias malabaricus (Teleostei, Erythrinidae) induced by subchronic exposure to toxic cyanobacterial crude extract
Authors: Paulino Marcelo Gustavo , Rossi Priscila Adriana , Venturini Francine Perri , Tavares Driele , Sakuragui Marise Margareth , Moraes Gilberto , Terezan Ana Paula , Fernandes João Batista , Giani Alessandra , Fernandes Marisa Narciso 
Published: August 2022

AbstractMicrocystins (MC) are hepatotoxic for organisms. Liver MC accumulation and structural change are intensely studied, but the functional hepatic enzymes and energy metabolism have received little attention. This study investigated the liver and hepatocyte structures and the activity of key hepatic functional enzymes with emphasis on energetic metabolism changes after subchronic fish exposure to cyanobacterial crude extract (CE) containing MC. The Neotropical erythrinid fish, Hoplias malabaricus, were exposed intraperitoneally to CE containing 100 μg MC‐LR eq kg−1 for 30 days and, thereafter, the plasma, liver, and white muscle was sampled for analyses. Liver tissue lost cellular structure organization showing round hepatocytes, hyperemia, and biliary duct obstruction. At the ultrastructural level, the mitochondria and the endoplasmic reticulum exhibited disorganization. Direct and total bilirubin increased in plasma. In the liver, the activity of acid phosphatase (ACP) increased, and the aspartate aminotransferase (AST) decreased; AST increased in plasma. Alkaline phosphatase (ALP) and alanine aminotransferase (ALT) were unchanged in the liver, muscle, and plasma. Glycogen stores and the energetic metabolites as glucose, lactate, and pyruvate decrease in the liver; pyruvate decreased in plasma and lactate decreased in muscle. Ammonia levels increased and protein concentration decreased in plasma. CE alters liver morphology by causing hepatocyte intracellular disorder, obstructive cholestasis, and dysfunction in the activity of key liver enzymes. The increasing energy demand implies glucose mobilization and metabolic adjustments maintaining protein preservation and lipid recruitment to supply the needs for detoxification allowing fish survival.
Role of autophagy in lysophosphatidylcholine‐induced apoptosis in mouse Leydig cells
Authors: Zeng Lin , Ma Bingchun , Yang Si , Zhang Meijuan , Wang Jinglei , Liu Mengling , Chen Jiaxiang 
Published: August 2022

AbstractLysophosphatidylcholine (LPC), a major class of glycerophospholipids ubiquitously present in most tissues, plays a dominant role in many diseases, while it is still unknown about the potential mechanism of LPC affecting the testicular Leydig cells. In the present study, mouse TM3 Leydig cells in vitro were treated with LPC for 48 h. LPC was found to significantly induce apoptosis and oxidative stress of mouse TM3 Leydig cells; while inhibition of oxidative stress by N‐acetyl‐L‐cysteine, an inhibitor of oxidative stress, could rescue the induction of apoptosis, indicating that LPC induced apoptosis of mouse TM3 Leydig cells via oxidative stress. Interestingly, LPC was showed to inhibit autophagy; however, induction of autophagy by rapamycin significantly alleviated the induction of apoptosis by LPC. Taken together, oxidative stress was involved in LPC‐induced apoptosis of mouse TM3 Leydig cells, and autophagy might play a protective role in LPC‐induced apoptosis.
Equine placental extract supplement as a night barking remedy in dogs with cognitive dysfunction syndrome
Authors: Amano Tatsuya , Ikeda Takashi , Yamaguchi Makiko , Kakehi Nobuhisa , Hanada Keizo , Watanabe Tsuyuko , Tahara Kentarou , Hirano Eiichi 
Published: August 2022

AbstractWith the aging of pet dogs, there has been an increasing trend in senility‐related diseases; additionally, cognitive disorders accompanied by abnormal behaviours are a major burden for owners. Recently, there have been a series of consultations regarding the fact that night barking, which is an abnormal behaviour, remarkably interferes with the owner's sleep and adversely affects the owner's quality of life. However, there has been no effective solution to this problem. In this study, three aged pet dogs diagnosed with dementia were administered an equine placental extract (eqPE) as pet supplement, which has been shown in laboratory models to improve cognitive function. Consequently, night barking ceased 1 week after the administration of eqPE in case 2 and it was observed to decrease in the other two dogs. Furthermore, night barking disappeared 2 and 3 weeks after the administration of eqPE in cases 1 and 3, respectively. No recurrence or exacerbation of night barking was observed in the three cases treated with the eqPE, and no adverse events were observed. These results suggest that eqPE may be useful for improving night barking in pet dogs with dementia, and it is expected to be a new treatment method.
On Monotonicity Detection in Simplicial Branch and Bound over a Simplex
Authors: Casado L. G. , G.-Tóth B. , Hendrix E. M. T. , Messine F. 
Published: August 2022

Abstract
The concept of exploiting proven monotonicity for dimension reduction and elimination of partition sets is well known in the field of Interval Arithmetic Branch and Bound (B &B). Part of the concepts can be applied in simplicial B &B over a box. The focus of our research is here on minimizing a function over a lower simplicial dimension feasible set, like in blending and portfolio optimization problems. How can monotonicity be detected and be exploited in a B &B context? We found that feasible directions can be used to derive bounds on the directional derivative. Specifically, Linear Programming can be used to detect the sharpest bounds.
On the NLO QCD corrections to gluon-initiated ZH production
Authors: Degrassi Giuseppe , Gröber Ramona , Vitti Marco , Zhao Xiaoran 
Published: August 2022

Abstract
We compute the QCD corrections at next-to-leading order for the process gg → ZH, including both the virtual two-loop terms and real-emission contributions. The two-loop box diagrams in the virtual corrections are approximated analytically over the complete phase space, combining the results of an expansion in the limit of small transverse momentum and an expansion in the regime of high energy. We obtain both inclusive and differential results for the cross section. We find that the NLO QCD corrections are of the same size as the LO contribution up to ZH invariant masses close to 1 TeV, but they increase significantly when higher energies are considered, due to a class of real-emission diagrams in which the Z boson is radiated from an open quark line. Finally, we estimate the uncertainty due to the renormalization scheme used for the top-quark mass both on the total and differential cross section.