bluuebunny/crossref_metadata_2025_split huggingface dataset:
A multigroup marine predator algorithm and its application for the power system economic load dispatch
Authors: Pan Jeng‐Shyang , Shan Jie , Chu Shu‐Chuan , Jiang Shi‐Jie , Zheng Shi‐Guang , Liao Lyuchao 
Published: September 2021

AbstractMarine Predator Algorithm (MPA) is an optimization algorithm inspired by the behavior of predator and prey to catch their own food. MPA is simple and easy to implement. To further improve the performance of MPA, this paper proposes a Multigroup Marine Predator Algorithm (MGMPA). The multigroup mechanism is to divide the initial population into several independent groups. These groups generate the top predator and the Elite matrix based on different strategies and share information after a fixed iteration. Above strategies include the maximum of the same group, the average of the same group, the maximum of different groups and the average of different groups. To verify its performance, the paper compares MGMPA with some classic algorithms such as Particle Swarm Optimization (PSO), Parallel Particle Swarm Optimization (PPSO), Slap Swarm Algorithm (SSA), and Marine Predator Algorithm (MPA). In addition, the proposed MGMPA is also applied to solve Economic Load Dispatch problem (ELD). The experimental results show that the proposed MGMPA has significant advantages under the CEC2013 suite and obtains the minimum cost of power system operation and the maximum economic benefits in the application.
Utilization of human to nanogrid to support the energy storage system
Authors: Shariff Samir M. , Alam Mohammad S. , Rafat Yasser , Ahmad Furkan , Khan Mohammad I. 
Published: September 2021

AbstractThe serious growing concern of climate change has pushed the adoption of the sustainable energy systems such as wind energy, solar energy, etc. Likewise the renewable energy, energy harvesting from human motion may be utilized in various purposes. Based on the distributed power generation technology, the present study proposes a model of Human to Nanogrid that harnesses and stores the human energy used during a workout into banks of supercapacitors. There are specific machines at the fitness center that were chosen based on the maximum load they can lift and the exercises they can perform on specific muscle groups. This study examines the mechanical energy that different users generate from a machine over time, and compares the power output of the humans and the consumption of energy in a gymnasium. To calculate the payback period, break‐even analysis is conducted based on the collected data and the energy savings, emission reduction, and impact reduction analyses are conducted.
Machine learning for cooperative spectrum sensing and sharing: A survey
Authors: Janu Dimpal , Singh Kuldeep , Kumar Sandeep 
Published: September 2021

AbstractWith the rapid development of next‐generation wireless communication technologies and the increasing demand of spectrum resources, it becomes necessary to introduce learning and reasoning capabilities in cognitive radio networks (CRN). In particular, our focus is on two fundamental applications in CRNs, namely spectrum sensing (SS) and spectrum sharing. The application of machine learning (ML) techniques has added new aspects to SS and spectrum sharing. This paper offers a survey on various ML‐based algorithms in the cooperative spectrum sensing (CSS) and dynamic spectrum sharing (DSS) domain, with its emphasis on types of features extracted from primary user signal, types of ML algorithm, and performance metrics utilized for evaluation of ML algorithms. Starting with the basic principles and challenges of SS, this paper also justifies the applicability of supervised, unsupervised, and reinforcement ML algorithms in the CSS domain. The application of ML algorithms, to solve the DSS problem has also been reviewed. Finally, the survey paper is concluded with some suggested open research challenges and future directions for ML application in next‐generation communication technologies.
Bricolage: A pluralistic approach to evaluating human ecosystem initiatives
Authors: Hargreaves Margaret 
Published: September 2021

AbstractThis article presents a reflection on the use of bricolage in two case illustrations. An eclectic approach, bricolage can be used as a transdisciplinary, mixed paradigm approach for reconciling the different ontological (“real world”) and epistemological (“theory of knowledge”) perspectives that complexity science and systems thinking bring to evaluation. Bricolage can be used in all four elements of evaluation design: (1) theoretical frameworks, (2) inquiry frameworks, (3) methods and metrics, and (4) values and valuing in evaluation. Bricolage can be applied to the choice of conceptual frameworks that define an evaluand; the selection of research questions or lines of inquiry that focus a study; the choice of data collection and analytic methods; and the implementation of strategies for incorporating and assessing value in evaluation.
Introducing systems‐ and complexity‐informed evaluation
Authors: Gates Emily F. , Walton Mat , Vidueira Pablo , McNall Miles 
Published: September 2021

AbstractFor the last several decades and recently amidst the COVID‐19 pandemic, many in the global evaluation communities call for shifts from linear, reductionist ways of thinking and working to approaches that embrace systems and complexity. In this introductory chapter, we orient readers to key systems and complexity traditions and terms and how these have been put to use in the evaluation field. Doing so provides a foundation from which to engage with the subsequent chapters. We close this chapter with highlights from the case examples featured in this issue.
Mitochondria‐specific nanocatalysts for chemotherapy‐augmented sequential chemoreactive tumor therapy
Authors: Huang Hui , Dong Caihong , Chang Meiqi , Ding Li , Chen Liang , Feng Wei , Chen Yu 
Published: September 2021

AbstractEndogenic tumor chemodynamic therapy (CDT) is emerging as a tumor‐therapeutic strategy featuring in situ treatments with high efficiency and specificity based on the Fenton reaction principle. Considering the limitation of monotherapy and relatively insufficient intracellular level of endogenous hydrogen peroxide (H2O2) in tumor tissues, a mitochondria‐specific nanocatalyst composed of cisplatin prodrug and gallic acid‐ferrous (GA‐Fe(II)) nanocomposites is successfully fabricated to fulfill chemotherapy‐augmented sequential chemoreactive tumor therapy. The bioactive cisplatin elevates the level of endogenous H2O2 through the activation of nicotinamide adenine dinucleotide phosphate oxidase (NOX)‐related cascaded reactions, and the GA‐Fe(II) nanocomposites possessing sustainable Fenton catalytic activity subsequently catalyzes H2O2 into highly reactive and toxic hydroxyl radicals to substantially inhibit tumor progression. Especially, this mitochondria‐specific nanocatalyst amplifies oxidative stress, stimulates mitochondrial dysfunction, downregulates AKT/mTOR signaling and finally induces cell autophagic death. Both in vitro and in vivo measurements verify that the chemotherapy‐augmented sequential chemoreactive nanotherapy based on the mitochondria‐specific nanocatalyst implements excellent anticancer efficiency and avoids undesired side effects. This work reveals the enormous potential of chemotherapy‐augmented CDT for combating tumors.
Inverse Association of Telomere Length With Liver Disease and Mortality in the US Population
Authors: Rattan Puru , Penrice Daniel D. , Ahn Joseph C. , Ferrer Alejandro , Patnaik Mrinal , Shah Vijay H. , Kamath Patrick S. , Mangaonkar Abhishek A. , Simonetto Douglas A. 
Published: August 2021

Physiologic aging leads to attrition of telomeres and replicative senescence. An acceleration of this process has been hypothesized in the progression of chronic liver disease. We sought to examine the association of telomere length (TL) with liver disease and its impact on mortality risk. A cohort of 7,072 adults with leukocyte TL measurements from the National Health and Nutrition Examination Survey 1999‐2002 with mortality follow‐up through 2015 was analyzed. Liver disease was defined by aminotransferase levels and classified into etiology‐based and advanced fibrosis categories. Multivariable‐adjusted linear regression models estimated effect sizes, with 95% confidence intervals (CIs), of the presence of liver disease on TL. Cox regression models evaluated associations between TL and all‐cause mortality risk using adjusted hazard ratios (HRs). The cohort was representative of the US population with mean age 46.1 years and mean TL 5.79 kilobase pairs. No overall association between TL and liver disease was found; however, there was a significant negative association of TL and advanced liver fibrosis in individuals aged 65 and above. The liver disease cohort (HR 1.22, 95% CI 0.99‐1.51) and those with metabolic syndrome (HR 1.26, 95% CI 0.96‐1.67) had increased mortality risk with shorter TL. The relationship between TL and all‐cause mortality was stronger in women (HR 1.51, 95% CI 1.02‐2.23) and in non‐Hispanic Whites (HR 1.37, 95% CI 1.02‐1.84). Conclusion: Shortened leukocyte TL is independently associated with advanced liver disease at older ages, and with a higher risk of all‐cause mortality in those with liver disease. These associations reaffirm the need to better understand the role of telomeres in the progression of liver disease.
Effects of flooding duration on the occurrence of three hardwood floodplain forest species inside and outside a dike relocation area at the Elbe River
Authors: Schindler Melanie , Donath Tobias W. , Terwei André , Ludewig Kristin 
Published: August 2021

AbstractFloodplain forests have become rare in Europe due to anthropogenic changes. A critical aspect of their restoration is reintroducing flooding via dike relocation, as implemented at the Elbe River near Lenzen/Germany. How forest development is influenced by dike relocation is still unclear and difficult to predict. Inside the dike relocation area at the Elbe River, most trees were planted. Due to high tree mortality, we asked if the relative elevation of the planted trees and thus the number of flooding days inside the relocation area was comparable to the prevailing flooding regime in the surrounding active floodplain. Therefore, the positions of Ulmus laevis, Quercus robur, and Crataegus monogyna individuals were recorded using a DGPS and merged with a digital terrain model. Subsequently, relative elevations and numbers of flooding days per year and growing season (averages for 2011–2017) were calculated. The most flooding tolerant species, U. laevis, occurred at the lowest sites and tolerated the highest number of flooding days, followed by Q. robur, and finally by the least flooding tolerant species C. monogyna. All three species occurred at lower sites inside the dike relocation area and were exposed to longer flooding durations compared to sites outside the area. This was due to the complex morphology of this area and its special flooding and flow dynamics, which differed from the conditions in the surrounding active floodplain. Although the mean flooding duration was within the growth range of hardwood floodplain forests (Ficario‐Ulmetum), most individuals may not have established at the planted sites under natural conditions. Therefore, we recommend not relying only on plantings but also allowing natural succession. Then, species that can cope with the hydrological site characteristics may also establish in the long term.
Gingivitis resolution followed by optical coherence tomography and fluorescence imaging: A case study
Authors: Le Nhan , Cheng Harrison , Subhash Hrebesh , Kilpatrick‐Liverman LaTonya , Wang Ruikang K. 
Published: August 2021

AbstractGingivitis is highly prevalent in adults, and if left untreated, can progress to periodontitis. In this article, we present an interesting case study where the resolution of gingivitis was followed over a period of 10 days using optical coherence tomography (OCT) and light‐induced autofluorescence (LIAF). We demonstrate that OCT and its functional angiography can distinctively capture the changes during the resolution of gingivitis; while LIAF can detect red‐fluorescent signals associated with mature plaque present at the inflamed site. The acute inflammatory region showed evidence of angiogenesis based on the quantification of vessel density and number; while no angiogenesis was detected within the less inflamed region. Gingival thickness showed a reduction of 140 ± 26 μm on average, measured between the peak gingivitis event and the period wherein the inflammation was resolved. Vessels in the angiogenesis site was found to reduce exponentially. The mildly inflamed site showed a decreasing trend in the vessel size, which however was within the error of the measurement.
Research progress on the formation mechanism of azeotrope and its separation process in microwave field
Authors: Qi Junjie , Zeng Fanlai , Jia Hanbing , Fang Jing , Li Hao , Wen Xiufang , Fang Zhiqiang 
Published: August 2021

AbstractIn the process of petrochemical, coal chemical, and pharmaceutical industries, a large amount of azeotrope is usually produced. The traditional method of separating azeotrope consumes a lot of energy. Therefore, it is of great significance to develop a low energy consumption and high efficiency method of separating azeotrope to achieve economic benefits and reduce energy consumption. The use of microwave fields for enhanced distillation processes to separate azeotrope is currently of great interest. In this paper, the mechanism of azeotropic formation is reviewed from three aspects: experimental studies, quantum chemical calculations and molecular simulations, and the influence of cluster structure on azeotropic formation is analyzed. Then the paper discusses the experimental study of microwave‐enhanced distillation process to separate azeotrope and the molecular simulation process, and the mechanism of microwave‐assisted azeotropic separation and the feasibility of industrialization are analyzed. © 2021 Society of Chemical Industry (SCI).
Anaerobic co‐digestion of food waste and microalgae in an integrated treatment plant
Authors: Ferreira Luísa Ornelas , Astals Sergi , Passos Fabiana 
Published: August 2021

AbstractBACKGROUNDAnaerobic co‐digestion has been considered for improving anaerobic digesters’ stability and methane production, particularly for residues with low biodegradability or lack of alkalinity. Food waste was identified as a biomass with macro and micronutrients unbalance and low alkalinity content, both of which hamper its anaerobic digestion. The present study focused on evaluating the anaerobic co‐digestion of food waste and microalgal biomass harvested from an open pond treating food waste digestate.RESULTSAccording to BMP tests results, mono‐digestion of food waste showed low methane yield (~35–68 mL CH4·g VS−1), most likely due to acid accumulation, as was observed by the low pH and low methane content in biogas. Process stabilisation was further attested through anaerobic co‐digestion with microalgae at different proportions in terms of volatile solids (VS). The highest methane yield was obtained at 75:25 of food waste and microalgae (514 mL CH4·g VS−1), with the highest synergy between substrates (28% higher compared to theoretical value). Moreover, estimates for real scenarios of co‐digestion in an integrated treatment system composed of an anaerobic reactor and microalgae‐based ponds revealed that, due to low microalgae production, proportions of 99:1 would be more realistic.CONCLUSIONResearch showed how a higher proportion of food waste was preferable, although a minimum amount of microalgae seemed important for maintaining process stability and increasing methane production. In the demonstration‐scale plant, co‐digestion and co‐disposal was estimated to be more sustainable when carried out in solid‐state or with recirculation of treated effluent. © 2021 Society of Chemical Industry (SCI).
Patient experiences at dental school clinics: A comparative analysis of online reviews
Authors: Gupta Rahul , Alraqiq Hosam M. 
Published: September 2021

AbstractPurpose/objectivesOnline review sites have become popular platforms for health care consumers to rate their experiences. An analysis of online reviews can help dental school clinics learn from patient feedback that is not accessible through formal patient surveys. This study's objectives were to characterize patient‐generated reviews posted on the Yelp and Google review sites and assess any associations between dental schools’ ratings and their respective characteristics.MethodsThis cross‐sectional study analyzed patient‐generated Yelp and Google reviews regarding their experiences at 65 dental school clinics between June and August 2019. Quantitative analysis of selected dental school characteristics and patient ratings was performed using analysis of variance, with effect size measured by the omega‐squared (ω2) statistic. Statistical significance was set at p = 0.05. Qualitative analysis of review content was conducted using NVivo software.ResultsAmong 65 dental schools in the Unite States, 63 schools (96.9%) had reviews available on Google, and 55 schools (84.6%) had reviews available on Yelp. A total of 4702 patient reviews were included in the analysis (2516 [53.5%] from Google [mean rating = 3.6 ± 0.6 stars] and 2186 [46.5%] from Yelp [mean rating = 3.1 ± 0.9 stars). A school location in the South/Midwest was significantly associated with a higher Yelp rating compared with a school location in the Northeast/West (ω2 = 0.140, 95% confidence interval = 0.002–0.310, p = 0.003). Qualitative analysis found that review content was predominantly negative; while subthemes in care delivery generated positive responses to care quality, those regarding the pre‐care and post‐care categories garnered negative responses. This finding was particularly true for comments addressing staff helpfulness, billing and payment, and clinic functioning.ConclusionsThis study's findings indicated that dental programs’ online reviews were predominantly negative and covered categories that were not addressed in existing satisfaction surveys.
Implication of light and scanning electron microscopy for pollen morphology of selected taxa of family Asteraceae and Brassicaceae
Authors: Umber Faria , Zafar Muhammad , Ullah Riaz , Bari Ahmed , Khan Muhammad Yahya , Ahmad Mushtaq , Sultana Shazia 
Published: September 2021

AbstractThe present study was intended to assess pollen morphological attributes of selected Asteraceous and Brassicaceous species from tehsil Esa Khel (Mianwali), Punjab using scanning electron microscopy (SEM) and light microscopy (LM) techniques for its systematic and taxonomic significance for correct identification. Pollen from 12 different species belongs to two plant families from various distributional localities were collected, acetolyzed and measured. Different palynomorphological features were investigated using LM and SEM techniques. In Asteraceous species, three types of pollen (tricolporate, trizonocolporate, and tetracolporate) were observed. Pollen shape was observed prolate‐spheroidal in three species while oblate and oblate‐spheroidal were detected inParthenium hysterophorusandErigeron bonariensis. While sculpturing pattern of exine were echinate, echinate fenestrate, echinate perforate and scabrate echinate. Mesocolpium measurement was calculated maximum forSonchus oleraceous(16.6 μm). Brassicaceae pollen were circular, lobate, tricolpate and exine show reticulate peculiarities. Whereas dominant shape was oblate‐spheroidal followed by prolate‐spheroidal and sub‐prolate inLepidium didymumandSisymbrium irio, respectively. Mesocolpium distance was noted highest inRaphanus raphanistrum(14.4 μm). Exine thickness was noted maximum inErigeron bonariensis(2.9 μm) in Asteraceous species and in Brassicaceae;Lepedium didymumexine measurement was 2.7 μm. The study showed that pollen micromorphology has important role to accurately identify and classify diverse plants genera belong to different families. Based on these taxonomic palynomorph features, the accurate identification of species from flora of tehsil Esa Khel, Mianwali were elaborated.
Phylogenetic comparative morphological analysis of fern spores in subfamily Pteridoideae (Pteridaceae, Pteridophyta)
Authors: Vaganov Alexey V. 
Published: September 2021

AbstractScanning electron microscopy (SEM) was used to characterize spore morphology of 24 taxa of the subfamily Pteridoideae C. Chr. ex Crabbe, Jermy & Mickel of the family Pteridaceae E.D.M. Kirchn. The family is considered to be one of the most taxonomically confusing families due to its high level of polymorphism. The standardized data on spore morphology of the subfamily Pteridoideae were projected onto the final phylogenetic tree in the Mesquite program. This approach made it possible to carry out a comprehensive interdisciplinary analysis of the evolution of spore morphology characters of the subfamily Pteridoideae, as well as to assess the relationships in the family Pteridaceae. The equatorial ridge (cingulum, “flange”) has been proven as one of the key spore morphology features, which confirms the close relationship of “Onychium clade” with Pteris. The species‐specific characters of the subfamily are fold and tubercle along laesura, equatorial ridge on proximal and distal side, tubercle, and folds on proximal and distal side. The knowledge will help to solve the problems of taxonomy in the family Preridaceae and to supplement the information on the natural classification of the subfamily Pteridoideae.
COVID‐19 disease in hospitalized young adults in India and China: Evaluation of risk factors predicting progression across two major ethnic groups
Authors: Panda Smriti , Roy Sankanika , Garg Rohit K. , Hui Gan , Gorard Jack , Bhutada Mayank , Sun Yuanli , Bhatnagar Sushma , Mohan Anant , Dar Lalit , Liu Mao 
Published: September 2021

AbstractData pertaining to risk factor analysis in coronavirus disease 2019 (COVID‐19) is confounded by the lack of data from an ethnically diverse population. In addition, there is a lack of data for young adults. This study was conducted to assess risk factors predicting COVID‐19 severity and mortality in hospitalized young adults. A retrospective observational study was conducted at two centers from China and India on COVID‐19 patients aged 20–50 years. Regression analysis to predict adverse outcomes was performed using parameters including age, sex, country of origin, hospitalization duration, comorbidities, lymphocyte count, and National Early Warning Score 2 (NEWS2) score at admission. A total of 420 patients (172 East Asians and 248 South Asians) were included. The predictive model for intensive care unit (ICU) admission with variables NEWS2 Category II and higher, diabetes mellitus, liver dysfunction, and low lymphocyte counts had an area under the curve (AUC) value of 0.930 with a sensitivity of 0.931 and a specificity of 0.784. The predictive model for mortality with NEWS2 Category III, cancer, and decreasing lymphocyte count had an AUC value of 0.883 with a sensitivity of 0.903 and a specificity of 0.701. A combined predictive model with bronchial asthma and low lymphocyte count, in contrast, had an AUC value of 0.768 with a sensitivity of 0.828 and a specificity of 0.719 for NEWS2 score (5 or above) at presentation. NEWS2 supplemented with comorbidity profile and lymphocyte count could help identify hospitalized young adults at risk of adverse COVID‐19 outcomes.