bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergetic Effect of Carbon Dot at Cellulose Nanofiber for Sustainable Metal-free Photocatalyst
Authors: Ahn Jungbin , Kim Hyungsup , pak Sewon 
Published: July 2021

Abstract
Metal-free photocatalyst was synthesized by attaching carbon dot (CD) to cellulose nanofiber (CNF) via simple in-situ synthesis. The graphitic core and functional groups of CD on CNF was controlled along the precursor concentration, while the fibrous structure of CNF was intact. The optical property of the samples was profoundly analyzed focusing on the electron recombination pathway. It reveals that the excited electrons in the CD transferred to the CNF and delayed the radiative recombination. The electron-hole pairs were efficiently separated in the composite where abundant amide group and sulfide bonding existed. The CD on the CNF surface improved the morphological stability of CNF under UV irradiation as well. As a result, the composite showed superior photocatalytic performance to degrade 98% of MB molecules within 25 min. The aerogel synthesized from CDCNF had good re-usability without sacrificing its photocatalytic effect. The synthesized CDCNF composite showed superior possibility for applying cellulose nanofiber to sustainable metal-free photocatalyst.
A Rare Case of Bilateral Primary B-Cell Non Hodgkin Lymphoma of Breast
Authors: Raval Maharshi Romelbhai , Patel Yash , Shah Suchi D. , Patel Kishan Gautam , Sharma Kamal 
Published: July 2021

Abstract
Primary B-Cell Non Hodgkin Lymphoma of Breast is a rare presentation of breast malignancy and it is necessary to differentiate it from secondary breast lymphoma as prognosis and treatment varies based on the diagnosis. We present a case of 47-year-old female with bilateral PBNHL of Breast which is rare due to younger age of presentation than earlier reported cases of this malignancy, lump with “peau de orange” appearance seen in both the breasts which is usually seen with high grade lymphoma and complete recovery of the patient while bilateral PBL outlines poor prognosis. Mammosonography findings included dilated ducts with hypoechoiec areas. MRI showed altered signal intensity. Findings of the imaging studies are non-specific and vary widely from case to case which is why biopsy which is gold standard was done to confirm the diagnosis.
Renal Replacement Therapy and Concurrent Fluconazole Therapy Increase Linezolid-Related Thrombocytopenia Among Adult Patients
Authors: Hsu Yueh-Chun , Chen Szu-Ying , Hung Yung-Jun , Huang Yu-Wei 
Published: July 2021

Abstract
Linezolid has been reported to be associated with thrombocytopenia. However, limited information is available on susceptibility to thrombocytopenia after linezolid usage. We aimed to investigate the risk factors for linezolid-associated thrombocytopenia (LAT). We conducted a retrospective cohort study of patients aged ≥ 18 years who received linezolid for ≥ 5 d during hospitalization in 2019. Information was extracted from electronic medical records. Thrombocytopenia was defined as a platelet count of < 100×109/L or a reduction from baseline ≥ 25%. Binary logistic regression and survival analyses were used to evaluate the risk factors for LAT. A total of 98 patients were enrolled. Thrombocytopenia occurred in 53.1% patients, with a median of 9 d after initiation of linezolid. There was no significant difference in the mortality or proportion of platelet transfusions between patients with and without thrombocytopenia. A higher risk of LAT was found in patients who received renal replacement therapy (RRT) (OR 4.8 [1.4–16.4]), concurrent fluconazole (OR 3.5 [1.2–9.8]), or a longer duration of linezolid treatment (OR 1.1 [1.0-1.1]). Patients who received RRT (8 vs. 15 d) or concurrent fluconazole (11 vs. 15 d) had a shorter median time to develop thrombocytopenia. Those who simultaneously received RRT and fluconazole had the shortest median of time (6.5 d) and the highest risk of developing thrombocytopenia (87.5%).
The Association of Pulmonary Function, Physical Activity, Cardiorespiratory Fitness, Borg Dyspnea Scales and Health Related Quality of Life in Patients With Resected Lung Cancer
Authors: Li Xinping , Chen Yi , Liu Shuangchun , Zhang Mingsheng 
Published: July 2021

Abstract
Purpose

This novel study aims to explore the relationship between pulmonary function, physical activity, cardiorespiratory fitness (CRF), dyspnea, and the health-related quality of life (HRQoL) of patients with resected lung cancer.
Methods

A cross-sectional study design with 38 lung cancer survivors after surgery for one month was conducted. We assessed CRF by measuring maximal oxygen consumption (VO2max) and anaerobic threshold (VT). Forced vital capacity (FVC) was measured using a spirometer. Physical activity, dyspnea, and HRQoL were investigated by 6-minute walking distance (6MWD), Borg dyspnea scales, and the SF-36 Health Survey (SF-36), respectively. Data analyses were conducted using SmartPLS to examine path analyses between the measures.
Results

There was a significant relationship between CRF and HRQoL in this cohort of cancer survivors. FVC (f2 = 0.265) and 6MWD (f2 = 0.389) have a medium to large effect size on the perceived CRF while CRF (f2 = 0.467) was found to have large effect sizes on perceived QoL. More importantly, our results showed that CRF positively and significantly mediated the paths between FVC, 6MWD, and HRQoL [β = 0.22 (0.457*0.474),P < 0.01; β = 0.28 (0.525*0.540), P < 0.01; respectively].
Conclusions

Pulmonary function, physical activity, and dyspnea had an indirect effect on the quality of life in patients with resected lung cancer. Furthermore, CRF mediates pulmonary function and physical activity to produce an impact on their quality of life.
Utilization of Localized Surface Plasmon Resonance of Silver Nanoparticles for the Spectrofluorimetric Estimation of Oxymetazoline in Dosage Forms: Application to Aqueous Humor
Authors: Elhaleem Shymaa M. Abd , Elsebaei Fawzi , Shalan Shereen , Belal Fathalla 
Published: July 2021

Abstract
A simple, novel, cost-effective and highly sensitive spectrofluorimetric method was developed for estimation of the nasal decongestant oxymetazoline (OMZ) whether per se or in its pharmaceutical preparations using colloidal silver nanoparticles (AgNPs). The method is based on the high catalytic potential activity of AgNPs on the fluorescence intensity of OMZ leading to 12-fold increase in its fluorescene intensity. The response was linear over the range of 20.0 to 700.0 ng/mL with lower detection limit of 5.0 ng/mL and limit of quantification of 14.0 ng/mL. The proposed method was applied to the assay of commercial nasal drops, nasal spray and aqueous humor. Interference likely to be encountered from co-administered drugs was studied. The developed method was optimized and validated as per International Council of Harmonization (ICH). An explanation for the drug-AgNPs interaction was proposed.
Enhanced Ultraviolet-Visible Photocatalysis of RGO/Equaixial Geometry TiO2 Composites on Degradation of Organic Dyes in Water
Authors: Hasan Jaafar , Wang Jing , Wang Zhentao , Idrees Muhammad , Batool Saima , Zhang Caiwei , Qin Chuanguang 
Published: July 2021

Abstract
The reduced graphene oxide dopped equaixial geometry TiO2 (rGO/egTiO2) composite as photocatalyst was synthesized hydrothermally with various mass ratios of tetrabutyl titanate. The photocatalyst is considered to be rGO/equaixial geometry TiO2 in terms of modifying the combined reduced graphene Oxide and TiO2. The rGO plays a vital role in rGO/egTiO2 composite as photocatalysts were analyzed in methylene blue (MB) and rhodamine B (RhB) photocatalytic degradation under UV and simulated solar light irradiation. This synthesized catalyst was characterized by various analytical techniques such as XPS, XRD, SEM, BET and TEM. The rGO/egTiO2 composite exhibits enhanced photo-catalytic performance with degradation rate of 97.5 and 97% on RhB and MB for 60 min under UV radiation respectively, while the degradation rate of 94 and 92 % was observed on the same dyes for 6 h under the simulated sunlight radiation. The enhanced photocatalytic performance of the rGO/egTiO2 composite under ultraviolet irradiation source was owing to a high separation efficiency of the photo-induced electron-hole pairs, while the photocatalytic performance under simulated sunlight radiation was due to the photosensitive and charge separator behavior of rGO. This offers us an excellent potential of significant photo catalytic activity for the removal of organic contaminants from wastewater.
Multi-Mode Circular Dichroism in N-Fold Rotational Symmetric Metamaterials
Authors: Li Shihao , Chen Kejian , Xu Yeli , Chen Yan 
Published: July 2021

Abstract
In this article, the effects of the rotation angle between upper and lower n-fold rotational symmetric nano-structures are studied. Various modes of circular dichroism (single wavelength band, dual-wavelength bands, and more than two wavelength bands) in the wavelength band from 3.3 to 5 µm are realized. Absorption up to 0.994 and absorptive circular dichroism up to 0.867 are observed. Meanwhile, sensitivity of circular dichroism to the rotation angle and reconfigure strategy for opposite responses has been discussed. Based on Born-Kuhn model, physical mechanism of mode’s switching is explained with charge distributions. The multi-mode chiroptical responses in mid-infrared band and the variety of design strategies have potential applications in the field of thermal remote sensing detection and tunable multi-band chiral devices.
Precipitation Variability and its Teleconnection with the Global SST and ENSO Indices in the Food Insecure Rural Areas of Tigray
Authors: Gebre Tewelde , Abreha Zenebe , Zenebe Amanuel , Zewold Woldegebrial 
Published: July 2021

Abstract
The impact of precipitation variability on food production is very significant. For food insecure rural areas, understanding the nature of precipitation variability and its teleconnection has paramount importance in guiding regional and local level decisions. In this study, we analyzed the monthly, seasonal and annual precipitation variability and the strength of its teleconnection with the global sea-surface temperature (SST) and El Niño Southern Oscillation (ENSO) indices in the food insecure rural areas of Tigray region, Ethiopia. The precipitation, SST, and ENSO indices data for the study were used from 1979 to 2019. A Summary of descriptive statistics and Mann Kendall test methods were applied to detect existence of trends; and Sen’s Slope and coefficient of variation are used to analyze the magnitude of the trend, and degree of variation in the trend of precipitation. Further, Pearson’s correlation is used to determine the effect of ENSO, and SST variations on the precipitation using the Canonical Correlation Analysis (CCA). The results revealed that the precipitation over the study areas is characterized by a distinctive bi-modal pattern with limited rains in March – May preceding the main rainy season June – September. The limited amount of precipitation, exacerbated by higher degree of variability, makes the food production in the study areas more uncertain. Besides, there was a very significant decline in the trend of March – May average precipitation and a significant decline in the trend of the annual average precipitation of Hintalo area. The SSTs of the central and eastern equatorial Pacific Ocean, and northeast and northwest equatorial Atlantic Ocean was strongly correlated with April’s average precipitation of the study areas. Further, the SST of south, west and southwest of equatorial Indian Ocean, and west equatorial Pacific Ocean were associated with July – September average precipitation with greater variation in strength among of the study areas. Moreover, July’s average precipitation of all the study areas, April’s average precipitation of Atsbi and Eirop, and May’s precipitation of Hintalo are found significantly associated with the ENSO indices of JFM, FMA, MJJ and MAM. Therefore, the task of achieving food security in the study areas should incorporate the design of informed food production strategies that can adapt the limited and variable precipitation based on these SST and ENSO indices.
Integration of Imaging Genomics Data for the Study of Alzheimer's Disease Using Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization
Authors: Wei Kai , Kong Wei , Wang Shuaiqun 
Published: July 2021

Abstract
Image genetics reveal the connection between microscopic genetics and macroscopic imaging and then detect diseases’ biomarkers. In this research, we make full use of the prior knowledge that has significant reference value for exploring the correlation of brain and genetics to explore more biologically substantial biomarkers. In this paper, we propose Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization (JCB-SNMF). The algorithm simultaneously projects structural Magnetic Resonance Imaging (sMRI), Single Nucleotide Polymorphism sites (SNPs), and gene expression data onto a common feature space, where heterogeneous variables with large coefficients in the same projection direction form a common module. In addition, the connectivity information of each region of the brain and genetic data are added as prior knowledge to identify regions of interest (ROI), SNP, and gene-related risks related to Alzheimer's disease (AD) patients. GraphNet regularization increases the anti-noise performance of the algorithm and the biological interpretability of the results. The simulation results show that compared with other NMF-based algorithms (JNMF, JSNMNMF), JCB-SNMF has better anti-noise performance and can identify and predict biomarkers closely related to AD from significant modules. By constructing a protein-protein interaction network (PPI), we identified SF3B1, RPS20, and RBM14 as potential biomarkers of AD. We also find some significant SNP-ROI and Gene-ROI pairs. Among them, two SNPs of rs4472239 and rs11918049 and three genes of KLHL8, ZC3H11A, and OSGEPL1 may have effects on the gray matter volume of multiple brain regions. This model provides a new way to further integrate multimodal impact genetic data to identify complex disease association patterns.
Study on the Impact of Comprehensive Urbanization on Urban Civil Building CO2 Emissions in China
Authors: Guo Rong , Li Nan , Mu Hailin , Zhang Ming , Yang Xiyue , Han Yixuan , Yao Rongkang , Shao Zhihao 
Published: July 2021

Abstract
With the rapid development of China, urbanization has become an important research topic of China's CO2 emissions. To fill the gap in considering the spatial correlation of the comprehensive urbanization that includes multi-dimensional factors on CO2 emissions from the operation phase of urban civil buildings (ubec). This study constructs a comprehensive evaluation indicator of urbanization from four aspects including population, economy, society and land urbanization by using the entropy method. The spatial spillover effect of ubec and the impact of comprehensive urbanization on ubec are also studied by using the spatial panel model in this paper. This study finds out that ubec has obvious spatial spillover effects. During the early years of the study period, the eastern coastal areas had greater carbon emissions, while in recent years they have gradually transitioned to the northwestern regions. Comprehensive urbanization has a significant promotion effect on it. And foreign direct investment and per capita energy consumption also have positive impact on ubec. This study provides a reference for measuring the effects of urbanization on sector-specific CO2 emissions and maybe useful for energy efficiency and emission abatement efforts in China.
Physicochemical Habitat Traits Preferred by Small Indigenous Fish (Chanda Nama ) in Indian River Discerning through Machine Learning
Authors: Raman Rohan Kumar , Das Archan Kanti , Manna Ranjan Kumar , Sahu Sanjeev Kumar , Das Basanta Kumar 
Published: July 2021

Abstract
Physicochemical traits of river influence the habitat of fish species in aquatic ecosystems. Fish showed a complex relationship with aquatic factors in river. Machine learning (ML) modeling is a useful tool to established relationship between complex systems. This study identified the preferred habitat indicators of Chanda nama (a small indigenous fish), in the Krishna River, of peninsular India, using machine learning modeling. Data were observed on Chanda nama fish distribution (presence/absence) and associated ten physical and chemical parameters of water at 22 sampling sites on the river during year 2001-02. Machine learning models such as random forest (RF), artificial neural network (ANN), support vector machine (SVM), k-nearest neighbors (KNN) used for the classification of Chanda nama distribution in the river. The ML model efficiency was evaluated using classification accuracy (CCI), Cohen’s kappa coefficient (k), sensitivity, specificity and receiver-operating-characteristics (ROC). Results showed that random forest is the best model with 82% accuracy, CCI (0.82), k (0.55), sensitivity (0.57), specificity (0.76) and ROC (0.72) for Chanda nama distribution (presence/absence) in the Krishna River. Random Forest model identified three preferred physicochemical habitat traits like altitude, temperature and depth for Chanda nama distribution in the Krishna River, India. This study will be helpful for researcher and policy maker to understand the important habitat physicochemical traits for sustainable management of small indigenous fish (Chanda nama ) in the river system.
Low density Lipoprotein Cholesterol and all-Cause Mortality rate Findings from a Study on Japanese Community-Dwelling Persons
Authors: Kawamoto Ryuichi , Kikuchi Asuka , Akase Taichi , Ninomiya Daisuke , Kumagi Teru 
Published: July 2021

Abstract
Background: Low-density lipoprotein cholesterol (LDL-C) independently impacts aging-related health outcomes and plays a critical role in cardiovascular diseases (CVDs). However, there are limited predictive data on all-cause mortality, especially for the Japanese community population. In this study, it was examined whether LDL-C is related to survival prognosis based on 7 or 10 years of follow-up.Methods: Participants included 1,610 men (63 ± 14 years old) and 2,074 women (65 ± 12 years old) who participated in the Nomura cohort study conducted in 2002 (first cohort) and 2014 (second cohort) and who continued throughout the follow-up periods (follow-up rates: 94.8% and 98.0%). Adjusted relative risk estimates were obtained for all-cause mortality using a basic resident register. The data were analyzed by a Cox regression with age as the time variable and risk factors including gender; age; body mass index (BMI); presence of diabetes; lipid levels; renal function; serum uric acid levels; blood pressure; and history of smoking, drinking, and CVD.Results: Of the 3,684 participants, 326 (8.8%) were confirmed to be deceased. Of these, 180 were men (11.2% of all men) and 146 were women (7.0% of all women). The univariate Cox regression analysis revealed that the hazard ratios (HRs) for all-cause mortality significantly increased with a decrease in LDL-C level (P < 0.001). The multivariate Cox regression analysis with adjustment variables showed that LDL-C grouping (HR: 0.71; 95% confidence interval [CI]: 0.62–0.82), gender (HR: 0.69, 95% CI: 0.51–0.93), age (HR: 1.09; 95% CI: 1.08–1.11), BMI (HR: 0.68; 95% CI: 0.54–0.86), history of CVD (HR: 1.38; 95% CI: 1.03–1.82), and presence of diabetes (HR: 1.65; 95% CI: 1.23–2.22) were significantly associated with all-cause mortality. Compared with individuals with LDL-C levels of 144 mg/dL or higher, the multivariate-adjusted HRs (95% CI) for all-cause mortality were 2.68 (1.67–4.28) for those with LDL-C levels under 70 mg/dL and 1.74 (1.17–2.59) for those with LDL-C levels between 70 and 92 mg/dL. Conclusions: There is an inverse relationship between the risk of all-cause mortality and LDL-C level, and this association is statistically significant.
Impact of Comorbidities On Physical Function And Survival of Middle-Aged As Compared To Older, Individuals With Cancer.
Authors: Koczwara Bogda , Deckx Laura , Ullah Shahid , Akker Marjan Van den 
Published: July 2021

Abstract
Purpose: To investigate if comorbidity predicts mortality and functional impairment in middle-aged individuals with cancer (50-64 years) as compared to older individuals.Methods: A prospective cohort study. Outcomes were mortality and functional impairment at 5 years follow-up. Comorbidity was assessed using adjusted Charlson comorbidity index and polypharmacy (≥5 drugs) as surrogate for comorbidity. Multivariate Cox-proportional hazards and binary logit models were used to assess the risk of 5-year mortality and functional impairment respectively.Results: We included 477 middle-aged (50-64 years) and 563 older (65+ years) individuals with cancer. The prevalence of comorbidity (at least one disease in addition to cancer) was 29% for middle-aged and 45% for older individuals, with polypharmacy observed in 15% and 31% respectively. Presence of ≥3 comorbidities nearly tripled the mortality risk in middle-aged individuals (HR 2.97, 95% CI: 1.43-6.16). In older individuals the HR was 1.7 (95% CI 1.1-2.8). Polypharmacy also significantly increased the risk for mortality in middle-aged (HR 2.35, 95% CI 1.32- 4.16) but not in older individuals (HR 1.2, 95% CI 0.9-1.8). Polypharmacy quadrupled the risk for functional impairment in middle-aged (OR 4.0, 95% CI 1.59-10.06) and older individuals (OR 4.4, 95% CI 1.6-11.7). Conclusion: Comorbidity and polypharmacy are associated with inferior outcomes in younger and older cancer individuals with the strength of association in younger individuals exceeding that of older individuals. Assessment and management of comorbidity should be a priority for cancer care across all age groups.
Households’ Climate Change Adaptation Strategies for Agriculture on the Eastern Tibetan Plateau
Authors: He Xinjun , Yan Jianzhong , Huang Anyi , Zhou Hong , Wu Ya , Yang Liang Emlyn , Paudel Basanta 
Published: July 2021

Abstract
How agriculture can better adapt to climate change has been a key topic of interest for scholars. This study provides insights from the eastern agricultural region of the Tibetan Plateau (TP). The Yellow River-Huangshui River valley (YHV) is an important food-producing region on the TP. The agricultural production of small households has been affected by significant climate change and by a series of interventions on the part of the local government. Five main adaptation strategies adopted by households include crop rotation (86.71%), increasing agricultural inputs (74.21%), changing the sowing time of crops (61.51%), expanding cropland area (32.94%) and raising more livestock (16.27%) to adapt to the effects of climate change. Regression analysis revealed that households’ perceptions of climate change and five types of livelihood capital are important factors influencing their adoption of various livelihood strategies. In addition, the adaptation strategies used by households in the YHV are incremental adjustments to their existing production, while transformative adaptation strategies (e.g., irrigation facilities, improved crop varieties, agricultural insurance), which are larger in scale and could fundamentally reduce households’ vulnerability to climate change have been planned by the government. Due to the presence of government interventions, households in the YHV area are more proactive in adapting to climate change. Finally, the results of this paper are conducive to guiding the local government to enhance its intervention role to promote households’ climate change adaptation behavior.