bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Role of Green Technology Innovation on the Development of Sustainable Tourism: Does Renewable Energy Use Help Mitigate Environmental Pollution? A Panel Data Analysis
Authors: Banga Cathrine , Deka Abraham , Kilic Hasan , Ozturen Ali , Ozdeser Huseyin 
Published: December 2021

Abstract
The tourism industry has been long blamed as the major driver to global warming due to it being the largest industry that uses more energy, most of which comes from sources that emits carbon-dioxide. However, despite all the blames on tourism for its negative effects on the environment, less work has been done to ascertain its impact on the environment. Unlike past studies that that alludes that tourism development exacerbates the emission of carbon-dioxide hence global warming, the current research shows that in the OECD countries, tourism does not have any significant link with greenhouse gasses emissions. This is so because OECD nations have long started to shift from fossil fuel use, as sources of energy, to renewable energy use which doesn’t exacerbates greenhouse gasses emissions. However, the current research concurs with the findings of past studies that renewable energy consumption significantly decreases greenhouse gases emissions. Using renewable energy sources of energy instead of fossil fuels should continue to be encouraged in all nations for the purpose of achieving low carbon in the future. The current study uses dynamic GMM model for 38 OECD countries from 2008 to 2019. Dynamic GMM model remains one of the best models since it corrects endogeneity problem in a model. GMM model overcomes autocorrelation, heteroskedasticity and normality problems, hence the robustness and reliability of results obtained. Gross Domestic Product and population size negatively affect greenhouse gasses emissions while inflation rate is observed to have a significant strong positive link with greenhouse gasses emissions.
Pilot-Scale Microsand-Ballasted Flocculation of Wastewater: Turbidity Removal, Parameters Optimization, and Mechanism Analysis
Authors: Sang Yimin , Lu Taotao , Lu Xianchun , Wang Shuguang , Shao Xueting , Han Yanhe , Li Lili 
Published: December 2021

Abstract
The flocs formed during microsand-ballasted flocculation (MBF) have attracted much attention. However, few studies have reported on comprehensive process parameters of MBF and its mechanism is still not well understood. Jar test and pilot-scale continuous experiments were here conducted on two kinds of simulated wastewater, labeled S1 (21.6-25.9 NTU) and S2 (96-105 NTU). Results revealed the hydraulic retention time ratio in the coagulation cell, injection & maturation cell, lamella settler of pilot-scale MBF equipment was 1: 3: 7.3. The optimum poly aluminum chloride doses for Samples S1 and S2 were 0.875 g/L and 1.0 g/L. Besides, the optimum size of microsand was 49-106 µm and the optimum dose was 1.0 g/L. Under aforementioned conditions, the effluent turbidity of S1 was below 0.47 NTU, lower than the Chinese drinking water standard; that of S2 was below 1.7 NTU, meeting the Chinese recycled water standard. Turbidity removal ranged from 98.0% to 98.8% for S1 and 98.5% to 99.5% for S2 when microsand was added. Therefore, microsand addition enhances MBF performance, where microsand serves as an initial core particle. Some microsand core particles bond together to form a dense core structure of micro-flocs by the adsorption bridging of inorganic polymeric flocculant. Moreover, the size of the largest micro-flocs may be controllable as long as the effective energy dissipation ɛ0 is adjusted appropriately through specific stirring speeds. This work provides comprehensive pilot-scale process parameters for using MBF to effectively treat wastewater and offers a clearer explanation of the formation mechanism of microsand-ballasted flocs.
Probing the Antioxidant Activity of Functional Proteins and Bioactive Peptides in Hermetia Illucens Larvae Fed with Food Wastes
Authors: Lu Jiaxin , Guo Yuwen , Muhmood Atif , Zeng Bei , Qiu Yizhan , Wang Pan , Ren Lianhai 
Published: December 2021

Abstract
Food waste is becoming more prevalent, and managing it is one of the most important issues in terms of food safety. In this study, functional proteins and bioactive peptides produced from the enzymatic digestion of Black soldier fly (Hermetia illucens L., BSF) fed with food wastes were characterized and quantified using proteomics-based analysis.The results revealed approximately 78 peptides and 57 proteins, including 40S ribosomal protein S4, 60S ribosomal protein L8, ATP synthase subunit alpha, ribosomal protein S3, Histone H2A, NADP- glutamate dehydrogenase, Fumarate hydratase, RNA helicase, Chitin binding Peritrophin-A, Lectin C-type protein, etc. were found in BSF. Furthermore, functional analysis of the proteins revealed that the 60S ribosomal protein L5 (RpL5) in BSF interacted with a variety of ribosomal proteins and played a key role in the glycolytic process (AT14039p). Higher antioxidant activity was found in peptide sequences such as GYGFGGGAGCLSMDTGAHLNR, VVPSANRAMVGIVAGGGRIDKPILK, AGLQFPVGR, GFKDQIQDVFK, and GFKDQIQDVFK. It was concluded that the bioconversion of food wastes by Hermetia illucens broght about the generation of variety of functional proteins and bioactive peptides with strong antioxidant activity. However, more studies are required for exploiting potential of Hermetia illucens in value addition of food wastes.
Chiral Fluorescence Recognition by Anthracene Fluorescent Dyes ⊂ Water-Soluble Pillar[5]arene Containing Phosphonic Acid Group (PWP[5])
Authors: Chen Yuliang , Lai Kaijie , Cai Jinmi , Li Yicheng , Wang Haibo 
Published: December 2021

Abstract
Chirality plays a pivotal role in drugs, agrochmeicals and food additives et al. The enantiomers of a chiral molecule often show huge difference in bioactivity, metabolism, and toxicity et al. thereby, the recognition of chiral molecules shows an increasingly important priority, and has become an important focus and frontier in medicine, biochemistry and other fields. In this paper, a novel method for chiral fluorescence recognition based on anthracene fluorescent dyes(AD) ⊂ water-soluble pillar[5] arene containing phosphonic acid group(PWP[5]) is developed. The AD as guest molecule can complex with PWP[5] to form 1:1 AD ⊂ PWP[5] assembly, and this assembly can be further used as a fluorescent probe to identify D/L-phenylalanine and D/L-phenylalaninol by fluorescent titration. The fluorescence intensity of the assembly was significantly reduced for D-phenylalanine and D-phenylalaninol, while L-phenylalanine or L-phenylalaninol was added to AD ⊂ PWP[5] assembly, the fluorescence intensity of the assembly almost unchanged. Hence, the chiral recognition based on assembly between the achiral fused ring fluorescent dye and achiral PWP[5] was developed.
The Safflower bHLH Transcription Factor CtbHLH41 Negatively Regulates SA-induced Leaf Senescence Through Interaction with CtCP1
Authors: Hong Yingqi , Zhang Jianyi , Lv Yanxi , Yao Na , Liu Xiuming 
Published: December 2021

Abstract
BackgroundSalicylic acid (SA) plays an important role in regulating leaf senescence. However, the molecular mechanism of leaf senescence of safflower (Carthamus tinctorius) is still elusive. In this study we found that the bHLH transcription factor (TF) CtbHLH41 in Carthamus tinctorius significantly delayed leaf senescence and inhibited the expression of senescence-related genes.ResultsIn order to explore how CtbHLH41 promotes leaf senescence, we carried out yeast two-hybrid screening. In this study, by exploring the mechanism of CtbHLH41 regulating CtCP1, it was found that CtCP1 promoted the hydrolysis of CtbHLH41 protein, accelerated the transcriptional activities of salicylic acid-mediated senescence-related genes CtSAG12 and CtSAG29, chlorophyll degradation genes CtNYC1 and CtNYE1, and accelerated leaf senescence. We found a negative SA regulator CtANS1, which interacts with CtbHLH41 and regulates its stability, thereby inhibiting CtCP1-mediated leaf senescence.ConclusionsIn short, our results provide a new insight into the mechanism of CtbHLH41 actively regulating the senescence of safflower leaves induced by SA.
Development of Dissolved Oxygen Forecast Model Using Hybrid Machine Learning Algorithm with Hydro-Meteorological Variables
Authors: Ahmed Abul Abrar Masrur , Chowdhury M A I , Ahmed Oli , Sutradhar Ambica 
Published: December 2021

Abstract
The ability to predict dissolved oxygen, which is a critical water quality (WQ) parameter, is critical for aquatic managers responsible for maintaining ecosystem health and the management of reservoirs affected by WQ. This paper reports forecasting dissolved oxygen (DO) concentration using multivariate adaptive regression splines (MARS) of running river water using a set of water quality and hydro-meteorological variables. This study’s key objectives were to assess input selection methods and five multi-resolution analyses as a data extraction approach. Moreover, the hybrid model is prepared by maximum overlap discrete wavelet transformation (MODWT) with the MARS model (i.e., MODWT-MARS). The proposed model is further compared with numerous machine learning methods. The result shows that the hybrid algorithms (i.e., MODWT-MARS) outperformed the other models (r = 0.981, WI = 0.990, RMAE = 2.47% and MAE = 0.089). This hybrid method may serve as the foundation for forecasting water quality variables with fewer predictor variables.
Durable T cell responses contrast with faster antibody waning in BNT162b2-vaccinated elderly at 6 month
Authors: Renia Laurent , Goh Yun Shan , Rouers Angeline , Bert Nina Le , Chia Wan Ni , Chavatte Jean Marc , Fong Siew-Wai , Chang Zi Wei , Zhuo Ziyi , Tay Matthew , Chan Yi Hao , Tan Chee Wha , Yeo Nicholas , Amrun Siti Naqiah , Huang Yuling , Hor Pei Xiang , Loh Chiew Yeee , Carissimo Guillaume , Dowla Samanzer , Lim Alicia , Zhang Jinyan , Ding Ying , Pada Surinder , Sun Louisa , Somani Jyoti , Lee Eng Sing , Lin Raymond , Ong Desmond , Leo Yee-Sin , Wang Lin-Fa , Lye David , Bertoletti Antonio , Ren Ee Chee , Young Barnaby , Ng Lisa Fong Poh 
Published: December 2021

Abstract
Efficient COVID-19 vaccines have been developed in record time. Here, we present findings from a comprehensive and integrated analysis of multiple compartments of the memory immune response in 312 individuals vaccinated with the BNT162b2 mRNA vaccine. Two vaccine doses induced high antibody and T cell responses in most individuals. However, antibody recognition of the Spike protein of delta variant was less efficient than that of the Wuhan strain. Age stratified analyses identified a group of low antibody responders where individuals ≥ 60 years were overrepresented. Waning of the antibody and cellular responses was observed in 30% of the vaccinees after six months. However, age did not influence the waning of these responses. Taken together, while individuals ≥ 60 years old took longer to acquire vaccine-induced immunity, they develop more sustained acquired immunity at six months post-vaccination. However, the higher proportion of older individuals in the group of antibody low responders and the lower antibody reactivity the Delta variant call for a booster immunization to increase immune responses and protection.
Controlled Oxygenation of Multiple Contiguous C–H Bonds via Electrophotocatalysis
Authors: Lambert Tristan , Shen Tao , Li Yi-Lun , Lai Liang-Chuan , Ye Ke-Yin 
Published: December 2021

Abstract
Chemical reactions that directly convert carbon-hydrogen (C–H) bonds to carbon-oxygen (C–O) bonds provide a powerful means to rapidly synthesize valuable organic compounds. However, achieving multiple C–H bond oxygenation reactions at the same time is challenging, particularly because of the risk of overoxidation. Here, we report the selective oxygenation of two or three contiguous C–H bonds, enabling the conversion of simple alkylarenes to diols, triols, or their corresponding acetates. The reactions are achieved using electrophotocatalysis—a process that utilizes both light and electricity to activate a single catalyst—to promote the oxidation reactions. The rapid increase in molecular complexity achieved by these multiple oxygenations enables the synthesis of some compounds of pharmaceutical interest by dramatically shorter sequences than previously achieved.
Living on the Edge and Beyond of Anoxia: Evolutionary Ecological Insights From Inside Crayfish Burrows
Authors: Pârvulescu Lucian , NECULAE Adrian , BARNETT Zanethia C. , DALOSTO Marcelo M. , KUKLINA Iryna , KAWAI Tadashi , MIOK Kristian , SANTOS Sandro , FURSE James M. , SÎRBU Ovidiu I. , STOECKEL James A. 
Published: December 2021

Abstract
Burrowing is a common trait among crayfish thought to help species deal with adverse environmental challenges. Here we used in-vivo experimental data and in-silico modelling of oxygen saturation in a virtual burrow inhabited by crayfish. Except for the entrance 200 mm region, the burrow microenvironment becomes anoxic, on average, within 8 hours, and 12-hour day-night multiple cycles were not sufficient for refreshing the burrow microenvironment even with temporary lack of crayfish. We asked whether the ecological category of crayfish burrowing activity is reflected in the physiological ability to cope with hypoxia and anoxia. As dissolved oxygen declined, respiration patterns of primary burrowers differed from those of secondary and tertiary burrowers, showing also the highest variability in anoxia tolerance. Secondary burrowers showed consistent tolerance with all species exhibiting a mean survival of > 3h anoxic conditions. Tertiary burrowers were variable, exhibiting moderate to zero tolerance of anoxia. The adaptive mechanisms to cope with hypoxia might be a basal legacy from the crayfish monophyletic ancestors – lobsters, traveller crustaceans often reaching deep depths in the ocean. These results challenge the current understanding of crayfish ecology, opening an evolutionary ecological perspective which might be relevant for the next generation of phylogenetical approaches.
Development and validation of polygenic risk scores for prediction of breast cancer and breast cancer subtypes in Chinese women
Authors: Hou Can , Yang Daowen , Hao Yu , Xu Bin , Song Huan , Li Jiayuan 
Published: December 2021

Abstract
Background
Studies investigating breast cancer polygenic risk score (PRS) in Chinese women are scarce. The objectives of this study were to develop and validate PRSs that could be used to stratify risk for overall and subtype-specific breast cancer in Chinese women, and to evaluate the performance of a newly proposed Artificial Neural Network (ANN) based approach for PRS construction.
Methods
The PRSs were constructed using the a GWAS dataset and validated in an independent case-control study. Three approaches, including repeated logistic regression (RLR), logistic ridge regression (LRR) and ANN based approach, were used to build the PRSs for overall and subtype-specific breast cancer based on 24 selected single nucleotide polymorphisms (SNPs). Predictive performance and calibration of the PRSs were evaluated unadjusted and adjusted for Gail-2 model 5-year risk or classical breast cancer risk factors.
Results
The primary PRSANN and PRSLRR both showed good predictive ability for overall breast cancer (IQ-OR 1.76 vs 1.58; AUC 0.601 vs 0.598) and remained to be predictive after adjustment. Although estrogen receptor negative (ER-) breast cancer was poorly predicted by the primary PRSs, the ER- PRSs trained solely on ER- breast cancer cases saw a substantial improvement in predictions of ER- breast cancer.
Conclusions
The SNP-24 based PRSs can provide additional risk information to help breast cancer risk stratification in the general population of China. The newly proposed ANN approach for PRS construction has potential to replace the traditional approaches, but more studies are needed to validate and investigate its performance.
Overall and Sex-Specific Risk Factors for Subjective Cognitive Decline: Findings From the 2015–2018 Behavioral Risk Factor Surveillance System Survey
Authors: Schliep Karen , Gu Lily , Lynch Kristine , Sorweid Michelle , Varner Michael , Foster Norman , Qeadan Fares 
Published: December 2021

Abstract
Background
Prior research indicates that at least 35% of Alzheimer’s disease and related dementia risk may be amenable to prevention. Subjective cognitive decline is often the first indication of preclinical dementia, with the risk of subsequent Alzheimer’s disease in such individuals being greater in women than men. We wished to understand how modifiable factors are associated with subjective cognitive decline, and whether differences exist by sex.
Methods
Data were collected from men and women (45 years and older) who completed the U.S. Behavioral Risk Factor Surveillance System Cognitive Decline Module (2015–2018), n=216,838. We calculated population attributable fractions for subjective cognitive decline, stratified by sex, of the following factors: limited education, deafness, social isolation, depression, smoking, physical inactivity, obesity, hypertension, and diabetes. Our models were adjusted for age, race, income, employment, marital and Veteran status, and accounted for communality among risk factors.
Results
The final study sample included more women (53.7%) than men, but both had a similar prevalence of subjective cognitive decline (10.6% of women versus 11.2% of men). Women and men had nearly equivalent overall population attributable fractions to explain subjective cognitive decline (39.7% for women versus 41.3% for men). The top three contributing risk factors were social isolation, depression, and hypertension, which explained three-quarters of the overall population attributable fraction.
Conclusions
While we did not identify any differences in modifiable factors between men and women contributing to subjective cognitive decline, other factors including reproductive or endocrinological health history or biological factors that interact with sex to modify risk warrant further research.
Probing the Effect of Selection Bias on Generalization: A Thought Experiment
Authors: Tsotsos John , Luo Jun 
Published: December 2021

Abstract
Learned systems in the domain of visual recognition and cognition impress in part because even though they are trained with datasets many orders of magnitude smaller than the full population of possible images, they exhibit sufficient generalization to be applicable to new and previously unseen data. Since training data sets typically represent such a small sampling of any domain, the possibility of bias in their composition is very real. But what are the limits of generalization given such bias, and up to what point might it be sufficient for a real problem task? Although many have examined issues regarding generalization from several perspectives, this question may require examining the data itself. Here, we focus on the characteristics of the training data that may play a role. Other disciplines have grappled with these problems also, most interestingly epidemiology, where experimental bias is a critical concern. The range and nature of data biases seen clinically are really quite relatable to learned vision systems. One obvious way to deal with bias is to ensure a large enough training set, but this might be infeasible for many domains. Another approach might be to perform a statistical analysis of the actual training set, to determine if all aspects of the domain are fairly captured. This too is difficult, in part because the full set of important variables might not be known, or perhaps not even knowable. Here, we try a different, simpler, approach in the tradition of the Thought Experiment, whose most famous instance is perhaps Schrödinger's Cat, to address part of these problems. There are many types of bias as will be seen, but we focus only on one, selection bias. The point of the thought experiment is not to demonstrate problems with all learned systems. Rather, this might be a simple theoretical tool to probe into bias during data collection to highlight deficiencies that might then deserve extra attention either in data collection or system development.
Investigation on Damping Characteristics of Hydrostatic Bearing Film by Using Scale Method
Authors: Hu Sheng-Yen , Chen Wen-Chou , Wang Chien-Hsun , Fu Hsin-Ming , Kang Yuan 
Published: December 2021

Abstract
The resonant peaks can be suppressed by damping, those effects is dependent on damping ratio of system. In this paper, we propose a scaling method to evaluate the damping ratio of hydrostatic bearings for the data from model test. This method fits specifically for the overdamping of all hydrostatic bearing. This is direct and the easiest method to obtain the damping characteristics of oil film for the lowest band before the first resonant peak. The frequency responses of acceleration per force for a single-degree-of-freedom mass-spring-damper model is used to generate the evaluation scales for the damping ratios of the modal test results of worktable mounting on hydrostatic bearing. The case study for experimental results of the impact response are evaluated for damping ratio of the hydrostatic film by these method. Furthermore, using this scaling method, the influences of three types of compensations on the damping ratio of a hydrostatic bearing are compared. The results reveal that the constant flow has the largest damping ratio, and the capillary restrictor has the smallest one.
Nanoscale-specific bioassimilation of sulfur: Time and coating specific modulation of transcriptomic and metabolomic pathways in diseased tomato
Authors: Wang Yi , Deng Chaoyi , Sharma Sudhir , Navarro Gilberto , LaReau Jacquelyn , Wang Zhengyang , Dimkpa Christian , Steven Blaire , Wang Zhenyu , Zhao Lijuan , Li Chunqiang , Dhankher Om , Xing Baoshan , Gardea-Torresdey Jorge , Elmer Wade , White Jason 
Published: December 2021

Abstract
Nanoscale sulfur was investigated as a multi-functional agricultural amendment to simultaneously enhance crop nutrition and suppress disease damage. Pristine (nS) and stearic acid coated (cS) sulfur nanoparticles were added to soil (0, 100, or 200 mg/L) that was planted with tomato (Solanum lycopersicum) and infested with the Fusarium wilt pathogen. Bulk sulfur (bS), ionic sulfate (iS), and healthy controls were included. In two greenhouse experiments, measured endpoints included time-dependent agronomic and photosynthetic parameters, disease severity/suppression, and a range of mechanistic biochemical and molecular endpoints, including the expression of 13 genes related to two S bioassimilation pathways and pathogenesis-response, and tissue-specific metabolomic profiles. The impact of treatment on the rhizosphere bacterial microbiome was also evaluated. Disease reduced tomato biomass by up to 87%, but amendment with nS and cS significantly reduced disease progress by 54 and 56%, respectively, compared to the infested controls. Increased S accumulation was evident in plant roots and leaves, independent of S type. Molecular analysis revealed particle size and coating-specific impacts on the plants. For nS and cS, two-photon microscopy and time-dependent gene expression data revealed a nanoscale specific elemental S bioassimilation pathway within the plant tissues. These findings correlated well with detailed metabolomic profiling of plant tissues at 4, 8, and 16 d, which exhibited increased disease resistance and plant immunity related metabolites with nanoscale treatment. The data also demonstrate a time-sensitive physiological window whereby nanoscale stimulation of plant immunity will be effective. An analysis of the rhizosphere soil bacterial community revealed minimal impacts from S soil treatments. These findings provide significant mechanistic insight into non-metal nanomaterial-based suppression of plant disease, and significantly advance efforts to develop sustainable nano-enabled agricultural strategies to increase food production.