bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gas consumption analysis of Ethereum blockchain transactions
Authors: Khan Muhammad Milhan Afzal , Sarwar Hafiz Muhammad Azeem , Awais Muhammad 
Published: November 2021

AbstractIn Ethereum blockchain, whenever a transaction of smart contract is executed, transaction fee is charged in terms of Ethers. To calculate the transaction fee, a computational unit, gas is introduced in smart contracts. Gas consumption is calculated against the smart contract source code execution. The transaction initiator sets the gas price against per unit of gas and the total gas limit. If the gas limit is sufficient, the transaction will be mined otherwise it will be reverted. Smart contracts of Ethereum can be written in any high‐level language such as Solidity, Vyper, Python, Java and so forth, but Solidity is massively used for smart contracts creation. In this article, we have examined the 5000 transactions of Solidity based smart contracts from Etherscan and performed statistical analysis on opcodes and source code parameters used in these transactions to identify gas costly patterns. Our statistical results (correlation and regression) analyze the relationship of Solidity parameters and opcodes with the gas consumption. Factors causing an increase or decrease in the gas consumption of smart contracts are highlighted in this article. The regression analysis showed that 87.8% of the variability in the response variable (gas consumption) is due to the parameters used in this analysis. Our results will help the smart contract developers to write the gas optimized smart contracts. The results can be beneficial for end users as they will have to pay gas price for less number of gas units.
An accurate foreground moving object detection based on segmentation techniques and optimal classifier
Authors: Nagaraju Melam , Babu B. Sobhan , Sai Somayajulu Meduri V. N. S. S. R. K. , Sarma K. Subrahmanya Kousik , Vetagiri Advaitha 
Published: November 2021

AbstractIn video surveillance schemes, the motion object detection plays a significant role. To subtract the object background, a segmentation technique based on feature extraction is utilized in which the change in the training rate makes an alteration in the background. Thereafter, the extracted features are trained by using the self‐organizing map (SOM) network in which the weight parameters in the network is optimized with the help of artificial bee colony (ABC) optimization algorithm, so, the proposed methodology is named as HSOM‐ABC technique. This methodology is carried out to perform the classification process in this research. Initially, the whole dataset is preprocessed with the help of grayscale conversion method which converts the original image into grayscale color. After this, fuzzy c‐means clustering is applied to perform the segmentation process and this method divides the foreground and background parts efficiently. Then, feature extraction is done with the help of local binary pattern method which extract the relevant features from the segmented image. Finally, HSOM‐ABC method is proposed to accurate classification process. Hence, the moving objects are identified by categorizing the background and foreground images. MatLab platform is chosen for the proposed work simulation and the performance is evaluated by means of different parameters and it is compared with new existing approaches. Experimental outcomes show that the proposed strategy achieves higher precision value than any other existing methods.
Diet composition of the African manatee: Spatial and temporal variation within the Sanaga River Watershed, Cameroon
Authors: Takoukam Kamla Aristide , Gomes Dylan G. E. , Beck Cathy A. , Keith‐Diagne Lucy W. , Hunter Margaret E. , Francis‐Floyd Ruth , Bonde Robert K. 
Published: November 2021

AbstractThe present study aimed to investigate the diet of African manatees in Cameroon to better inform conservation decisions within protected areas. A large knowledge gap on diet and seasonal changes in forage availability limits the ability to develop informed local management plans for the African manatee in much of its range. This research took place in the Sanaga River Watershed, which includes two protected areas in the Littoral Region of Cameroon: the Douala‐Edea National Park and the Lake Ossa Wildlife Reserve. We analyzed 113 manatee fecal samples and surveyed shoreline emergent and submerged vegetation within the Sanaga River Watershed. We used microhistological analyses to determine the relative contribution of each plant species to African manatee diets and compared across locations and across seasons (wet vs. dry season). We found that the shoreline vegetation is diverse with over 160 plant species, unevenly distributed across space and season, and dominated by emergent vegetation mostly represented by the antelope grass (Echinochloa pyramidalis). We recorded a total of 36 plant species from fecal samples with a spatial and temporal distribution mostly reflecting that of the corresponding shoreline vegetation. African manatees appear to be primarily opportunistically feeding on available vegetation across the seasons and habitat. This work documents the current, but changing, state of plant availability in the Sanaga River Watershed and reports the African manatee diet in Cameroon for the first time. This information can play a critical role in successfully managing the species and these protected areas. If we wish to protect the African manatee and the aquatic ecosystems within the Sanaga River Watershed, we must understand how forage availability changes over time, especially as its waters become nutrient enriched, eutrophic, and exposed to invasive species of plants in a changing world.
The thermoregulatory role of relative bill and leg surface areas in a Mediterranean population of Great tit (Parus major)
Authors: Playà‐Montmany Núria , González‐Medina Erick , Cabello‐Vergel Julián , Parejo Manuel , Abad‐Gómez José M. , Sánchez‐Guzmán Juan M. , Villegas Auxiliadora , Masero José A. 
Published: November 2021

AbstractThere is growing evidence on the role of legs and bill as ‘thermal windows’ in birds coping with heat stress. However, there is a lack of empirical work examining the relationship between the relative bill and/or leg surface areas and key thermoregulatory traits such as the limits of the thermoneutral zone (TNZ) or the cooling efficiency at high temperatures. Here, we explored this relationship in a Mediterranean population of Great tit (Parus major) facing increasing thermal stress in its environment. The lower and upper critical limits of the TNZ were found to be 17.7 ± 1.6ºC and 34.5 ± 0.7°C, respectively, and the basal metabolic rate was 0.96 ± 0.12 ml O2 min−1 on average. The evaporative water loss (EWL) inflection point was established at 31.85 ± 0.27°C and was not significantly different from the value of the upper critical limit. No significant relationship was observed between the relative bill or tarsi size and TNZ critical limits, breadth, mass‐independent VO2, or mass‐independent EWL at any environmental temperature (from 10 to 40°C). However, Great tit males (but not females) with larger tarsi areas (a proxy of leg surface area) showed higher cooling efficiencies at 40°C. We found no support for the hypothesis that the bill surface area plays a significant role as a thermal window in Great tits, but the leg surface areas may play a role in males’ physiological responses to high temperatures. On the one hand, we argue that the studied population occupies habitats with available microclimates and fresh water for drinking during summer, so active heat dissipation by EWL might be favored instead of dry heat loss through the bill surface. Conversely, male dominance behaviors could imply a greater dependence on cutaneous EWL through the upper leg surfaces as a consequence of higher exposure to harsh environmental conditions than faced by females.
Assessing the nutritional consequences of switching foraging behavior in wood bison
Authors: Hecker Lee J. , Edwards Mark A. , Nielsen Scott E. 
Published: November 2021

AbstractDiet is one of the most common traits used to organize species of animals into niches. For ruminant herbivores, the breadth and uniqueness of their dietary niche are placed on a spectrum from browsers that consume woody (i.e., browse) and herbaceous (i.e., forbs) plants, to grazers with graminoid‐rich diets. However, seasonal changes in plant availability and quality can lead to switching of their dietary niche, even within species. In this study, we examined whether a population of wood bison (Bison bison athabascae) in northeast Alberta, Canada, seasonally switched their foraging behavior, and if so, whether this was associated with changes in nutrient acquisition. We hypothesized that bison should switch foraging behaviors from grazing in the winter when standing, dead graminoids are the only foliar plants readily available to browsing during spring and summer as nutritious and digestible foliar parts of browse and forbs become available. If bison are switching foraging strategy to maximize protein consumption, then there should be a corresponding shift in the nutritional niche. Alternatively, if bison are eating different plants, but consuming similar amounts of nutrients, then bison are switching their dietary niche to maintain a particular nutrient composition. We found wood bison were grazers in the winter and spring, but switch to a browsing during summer. However, only winter nutrient consumption of consumed plants differed significantly among seasons. Between spring and summer, bison maintained a specific nutritional composition in their diet despite compositional differences in the consumed plants. Our evidence suggests that bison are selecting plants to maintain a target macronutrient composition. We posit that herbivore's can and will switch their dietary niche to maintain a target nutrient composition.
Comprehensive investigation of fever cases enrolled during 2019 dengue outbreaks from three hyperendemic regions of North 24 Parganas district of West Bengal, India
Authors: Datta Sourav , Ghosh Manab , Paul Moumita , Halder Prantiki , Mallik Sudeshna , Mukhopadhyay Sumi , Saha Bibhuti , Kundu Pratip Kumar 
Published: November 2021

AbstractFor the past several decades, dengue fever has been emerging in epidemic proportions in several regions of the world. During August–September 2019, an increasing number of fever cases were being reported from some areas of North 24 Parganas district of West Bengal, India. Accordingly, outbreak investigation of fever cases from these affected areas of Bongoan, Barasat, and Habra was carried out. To characterize clinical and biochemical features of fever cases as well as to investigate the utility of CRP as a Dengue severity marker in resource‐limited settings. We systematically enrolled 108 patients from the affected region of North 24 Parganas. Standard diagnostic assays along with routine serological and biochemical parameters were performed. Of the 108 patients, 77 (71%) were confirmed with Dengue infection followed by 22 (20%) DENV seronegative and 9 (8%) coinfected DENV cases. Among the 77 confirmed Dengue patients, 53 (69%) had primary infection while 24 (31%) had secondary infection. Among the DENV clinical symptoms, fever (r = 0.50; p = 0.004), headache (r = 0.40; p = 0.03) and abdominal pain (r = −0.40; p = 0.02) were found to bear significant correlation with DENV viral load. The predominant circulating serotype was found to be DENV2. CRP Dengue severity cut‐off level of 10.15 mg/L (AUC: 0.85; 86% sensitivity, 77% specificity) was obtained. CRP had correlation with viral load (r = 0.4, p = 0.05) within febrile phase of infection. The performance of biomarkers can be influenced by local epidemiology, geography, and several patient factors, therefore, CRP Dengue severity cut‐off value may be region‐specific. This study for the first time attempts to estimate CRP Dengue severity cut‐off value based on routine immunoturbidometric evaluation from Dengue Hyperendemic zones of North 24 Parganas, West Bengal, Eastern India.
Molecular epidemiological study of the G protein of human respiratory syncytial virus detected in patients with acute respiratory infections in Gyeonggi Province, South Korea
Authors: Lee Yea‐Eun , Choi Ok‐Kyung , Bang Seon‐Jae , Cho Han‐Gil , Lee Hyun‐Kyung , Han Baek‐Sang , Lee Sun‐Hwa , Cheng Jinhua , Cho Joo‐Hyung , Suh Joo‐Won 
Published: November 2021

AbstractTo investigate the molecular characteristics of human respiratory syncytial virus (HRSV) detected in Gyeonggi Province from 2015/16 to 2017/18, 2331 specimens from patients with sporadic acute respiratory illness and 85 specimens from four HRSV outbreaks in the postpartum care center were analyzed by real‐time reverse transcription PCR. HRSVs were detected in 97 of the 2416 (4.0%) specimens, and among the positive specimens, 38 (39.2%) were identified as HRSV‐A and 59 (60.8%) as HRSV‐B. During the study periods, HRSV‐B predominated in all seasons, except in 2016/17 during which HRSV‐A predominated. Depending on the age groups, HRSV prevalence was the highest in 0‐ to 2‐year‐old patients. Comparison of noninfected subjects with HRSV‐infected subjects revealed that HRSV infection more frequently resulted in fever, nasal obstruction, and wheezing, although the frequency of sore throat was low; however, comparison of the symptoms between HRSV‐A‐ and HRSV‐B‐infected patients revealed no significant differences in symptoms. Phylogenetic analysis showed that all HRSV‐A patients had an ON1 genotype, and all HRSV‐B patients had an BA9 genotype. These results provide a valuable reference regarding the circulating pattern and molecular characterization of HRSV. Continuous monitoring will be essential to detect newly emerging HRSV genotypes.
Experimental study and molecular simulation on aggregation behavior of surface‐active ionic liquids containing saturated nitrogen heterocycles in aqueous solution
Authors: Gao Mingwei , Guo Xu , Liu Peng , Zhao Mingwei , Yin Hui , Dai Caili 
Published: November 2021

AbstractThe aggregation behavior of N‐decyl‐N‐methylmorpholinium bromide (DMMB) in aqueous solutions was systematically investigated by experimental measurements and molecular simulation, including surface tension, electrical conductivity, fluorescence measurement, 1H NMR and dissipative particle dynamic (DPD) simulation. The critical micelle concentration (cmc) of DMMB which was obtained by different techniques showed a pretty good agreement. From the surface tension measurements, a series of surface adsorption properties such as surface tension at the cmc (γcmc), effectiveness of surface tension reduction (∏cmc), maximum surface excess concentration (Γmax), minimum surface area per molecule (Amin), were determined. The cmc values and a variety of thermodynamic parameters (, and ) of micellization in the temperature range of 25–45°C were obtained via electrical conductivity experiments. In the investigated temperature range, the thermodynamic parameters reveal that micelle formation is entropy‐driven. Furthermore, micelle aggregation number (Nagg) of DMMB was calculated through the fluorescence measurement. Analysis of the 1H NMR spectrum indicates the micelle formation mechanism. The DPD simulation reflects the process of micro‐phase separation. From the simulation results, at concentrations higher than cmc, spherical micelles can be formed. The investigation of DMMB micelles may help us gain a better understanding about surfactant micellization process and expand the range of potential application in materials science.
Surgical Site Infections in patients undergoing major oncological surgery during the COVID‐19 paNdemic (SCION): A propensity‐matched analysis
Authors: Pantvaidya Gouri , Joshi Shalaka , Nayak Prakash , Kannan Sadhana , DeSouza Ashwin , Poddar Pabashi , Prakash Gagan , Vijaykumaran Preeti , Nair Deepa , Vaish Richa , Patkar Shraddha , Niyogi Devayani , Joshi Poonam , Chaudhari Vikram , Singh Vikas , Mathews Saumya , Pramesh C. S. , Badwe Rajendra A. , Puri Ajay 
Published: November 2021

AbstractBackground and ObjectivesThere are reports of outcomes of elective major cancer surgery during the COVID‐19 pandemic. We evaluated if reinforcement of hand hygiene, universal masking, and distancing as a part of pandemic precautions led to a decrease in the incidence of surgical site infections (SSIs) in major oncologic resections.MethodsPropensity score matching using the nearest neighbor algorithm was performed on 3123 patients over seven covariates (age, comorbidities, surgery duration, prior treatment, disease stage, reconstruction, and surgical wound type) yielding 2614 matched (pre‐COVID 1612 and COVID 1002) patients. Conditional logistic regression was used to identify if SSI incidence was lower amongst patients operated during the pandemic.ResultsThere was a 4.2% (p = 0.006) decrease in SSI in patients operated during the pandemic. On multivariate regression, surgery during the COVID‐19 period (odds ratio [OR] = 0.77; 95% confidence interval [CI] = 0.61–0.98; p = 0.03), prior chemoradiation (OR = 2.46; CI = 1.45–4.17; p < 0.001), duration of surgery >4 h (OR = 2.17; 95%CI = 1.55–3.05; p < 0.001) and clean contaminated wounds (OR = 2.50; 95% CI = 1.09–2.18; p = 0.012) were significantly associated with SSI.ConclusionIncreased compliance with hand hygiene, near‐universal mask usage, and social distancing during the COVID‐19 pandemic possibly led to a 23% decreased odds of SSI in major oncologic resections. Extending these low‐cost interventions in the post‐pandemic era can decrease morbidity associated with SSI in cancer surgery.
Recent progress in the development of chiral stationary phases for high‐performance liquid chromatography
Authors: Zhang Jun‐Hui , Xie Sheng‐Ming , Yuan Li‐Ming 
Published: November 2021

AbstractSeparations and analyses of chiral compounds are important in many fields, including pharmaceutical production, preparation of chemical intermediates, and biochemistry. High‐performance liquid chromatography using a chiral stationary phase is regarded as one of the most valuable methods for enantiomeric separation and analysis because it is highly efficient, is broadly applicable, and has powerful separation capability. The focus for development of this method is the identification of novel chiral stationary phases with superior recognition performance and good stability. The present article reviews recent progress in the development of new chiral stationary phases for high‐performance liquid chromatography between January 2018 and June 2021. These newly reported chiral stationary phases are divided into three categories: small organic molecule‐based (cyclodextrin and its derivatives, macrocyclic antibiotics, cinchona alkaloids, and other low molecular weight chiral molecules), macromolecule‐based (cellulose and amylose derivatives, chitin and chitosan derivatives, and synthetic helical polymers) and chiral porous material‐based (chiral metal‐organic frameworks, chiral covalent organic frameworks, and chiral inorganic mesoporous silicas). Each type of chiral stationary phase is discussed in detail.
Deep learning‐based ultrasonic dynamic video detection and segmentation of thyroid gland and its surrounding cervical soft tissues
Authors: Luo Hongxia , Ma Laifa , Wu Xiangqiong , Tan Guanghua , Zhu Hui , Wu Senmin , Li Kenli , Yang Yan , Li Shengli 
Published: November 2021

AbstractBackgroundThe prevalence of thyroid diseases has been increasing year by year. In this study, we established and validated a deep learning method (Cascade region‐based convolutional neural network, R‐CNN) based on ultrasound videos for automatic detection and segmentation of the thyroid gland and its surrounding tissues in order to reduce the workload of radiologists and improve the detection and diagnosis rate of thyroid disease.MethodsSeventy‐one patients with normal thyroid ultrasound were included. The ultrasound videos of 59 patients were used as the training dataset, the data of 12 patients were used as the validation dataset, and in addition, the data of 9 patents were used as the testing dataset. Ultrasound videos of thyroid examination, including five standard sections (left and right lobe transverse scan, central isthmus transverse scan, left and right lobe longitudinal scan), were collected from all patients. The radiologists labeled the neck tissues, including anterior cervical muscle, cricoid cartilage, trachea, thyroid gland, endothyroid vessels, carotid artery, internal jugular vein, and esophagus. A large dataset was constructed to train and test the deep learning method. The performance was evaluated using the COCO metrics AP, AP50, and AP75. We compared the Cascade R‐CNN with a state‐of‐the‐art method CenterMask in the test dataset.ResultsWe annotated 166817, 34364, and 29227 regions in training, validation and testing samples. The model could achieve a good detection performance for the thyroid left lobe, right lobe, isthmus, muscles, trachea, carotid artery, and jugular vein; the AP50 of these tissues were 86.5%, 87.5%, 89.1%, 96.1%, 96.6%, 97.7%, and 91.8%, respectively. In addition, the model showed good segmentation performance for the muscles, trachea, and carotid artery; the AP50 of these tissues were 96%, 96.6%, and 97.8%, respectively. For the left lobe, right lobe, isthmus, esophagus, and jugular vein, AP50 was ≥86%. However, the segmentation results for the cricoid cartilage and endothyroid vessels were not high (AP50 of 53.9% and 48.5%, respectively). For fair comparison, the performance of Cascade R‐CNN is better than that of CenterMask for detection and segmentation tasks. The difference was statistically significant (p < 0.05).ConclusionsThe new method could successfully detect and segment the thyroid gland and its surrounding tissues.
Triterpenes and limonoids of Cedrela: Distribution, biosynthesis, and 1H and 13C NMR data
Authors: Vasquez‐Ruiz Vianey , Ramírez‐Cisneros M. Ángeles , Rios Maria Yolanda 
Published: November 2021

AbstractCedrela genus, a member of the Meliaceae family, presents both chemical characteristics associated with and those that distinguish it from the rest of its members. The presence of triterpenes and limonoids is the characteristic of the Meliaceae family, but the class and type of these chemical constituents are distinctive for each genus. Cedrela includes cycloartane, ursane, oleanane, tirucallane, butyrospermane, and apotirucallane triterpenes, and its limonoids belongs to six class and nine types, known as class Ia‐type havanensines, class Ib‐type delevoyin, class II‐type gedunin, class IIIb‐type andirobin, class IIIg‐type mexicanolide, class IVa‐type evoludone, class Va‐type obacunol, class V‐type limonin, and class VIII. Each of these structural arrangements includes specific traits, defined by their biosynthetic origin, which can be established by means of structural elucidation techniques, particularly 1H and 13C NMR, which assisted by 2D NMR techniques, allowing to deduce their structures unequivocally. The constant presence of these skeletal arrangements in Cedrela ensures that they are its chemophenetic markers and their recurrence is an important criterion for their identity. This review is a compilation of the occurrence of triterpenes and limonoids in Cedrela genus, detailing their biosynthetic association and collecting and organizing their NMR data, with the purpose of facilitating its location, analysis, and use in the phytochemical study of species from this genus.