bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of Postoperative C-Reactive Protein with Use of Cetylpyridinium Chloride in Perioperative Oral Management: Sub-analysis of a Mouthwash Intervention Study
Authors: Kamijo Junpei , Otagiri Hiroki , Yanai Kota , Tobata Haruko , Sakai Hironori , Kurita Hiroshi 
Published: January 2024

Abstract

Purpose
Perioperative oral management (POM) reduces the risk of postoperative complications. We previously conducted a randomized controlled feasibility study using povidone iodine (PVP-I) or 0.05% cetylpyridinium chloride (CPC) in POM and found that perioperative self-care with CPC product may support antibiotic-induced changes in the oral flora. In this sub-analysis, we investigated how use of PVP-I or CPC products in the perioperative period affects postoperative changes in C-reactive protein (CRP).
Methods
Subjects who received PVP-I (n = 38) and CPC (n = 40) were divided based on a CRP threshold of 5 mg/dL. Tongue bacteria counts, operational taxonomic unit (OTU) counts, and Shannon Index immediately before surgery were compared in the high CRP (≥ 5 mg/dL) and low CRP (< 5 mg/dL) by Mann-Whitney U test. Dependent variables were selected from univariate results and stepwise multivariate logistic regression analysis was performed.
Results
There were significantly more patients with high CRP in the PVP-I group than in the CPC group. High CRP cases in the CPC group had significantly higher OTU counts and Shannon Index compared to low CRP cases in this group. Stepwise multivariate logistic regression analysis showed significant effects of the product (odds ratio 0.34) and Shannon Index (odds ratio 3.18).
Conclusion
Results of this study suggested that the use of CPC in POM was associated with lower CRP level. CRP is known to increase during postoperative period because of tissue inflammation. Shannon Index for tongue coating measured immediately before surgery is significantly lower in CPC group and may causes decreased CRP level.
Trial registration number
: UMIN000030919 (Date of registration: January 21, 2018)
A Privacy-Sharing Approach to IoT Based on Secure Multi-Party Computation
Authors: Ma Li , Zhang Bo , Li Yang , Fu YingXun , Ma DongChao 
Published: January 2024

Abstract

Edge computing nodes close to the perception layer of the IoT system have security risks such as privacy data leakage and unauthorized access. In response to such security risks, a privacy data sharing model for the Internet of Things based on secure multi-party computation is proposed. By running a reliable third-party alliance chain service on the edge computing node, the private data calculation relationship between the sensing layer devices is registered in the alliance chain chain code service, and a Bloom filter that records the trust status of the sensing layer device is constructed in the chain code.. A publicly verifiable private data sharing model that combines on-chain identity auditing and off-chain secure multi-party computation is constructed to achieve secure sharing of private data between sensing layer devices. Experiments show that the proposed method has more advantages in terms of task overhead and security.
Dual objective nonlinear PD sliding mode control based on an adaptive reference model for an active suspension system
Authors: Yuan Shipeng , Shao Sujuan , Nan Yang , Ma Chicheng , Wu Yuting , Sun Zhonghui , Liu Jiangduo 
Published: January 2024

Abstract

This article focuses on the study of nonlinear active suspension tracking control problems based on an adaptive reference model. To mitigate the drawback of compromised ride comfort caused by tracking errors while tracking the adaptive trajectory of body displacement, the paper explores a tracking controller with dual objectives. This includes a nonlinear PD controller for tracking the adaptive desired trajectory and a sliding mode controller concerning body velocity and acceleration. This approach ensures that the body displacement approximately tracks the desired trajectory while significantly improving ride comfort, additionally, this control method has the advantages of structural simplicity and insensitivity to tracking errors, implying that control parameters can be easily tuned, and control inputs can be effectively reduced. The stability of the controlled system is demonstrated through the Lyapunov stability theory, and a range for the body displacement tracking error is derived. Finally, the performance of the controller is tested on an experimental platform, with results indicating a substantial reduction of 69.22% and 54.66% in the RMS values of body acceleration under bump and random excitation, respectively.
Enhancement of nonlinear optic effect of the second harmonic generation in plasmonic waveguide using graphene and pyramid-shape gold nanoparticles
Authors: tootoonchi Atro , Karamdel Javad , Naderi Ebadollah , Olyaee Hassan Ghalami Bavil 
Published: January 2024

Abstract
This study introduces a novel approach to significantly enhance the Second Harmonic Generation (SHG) in plasmonic waveguides by integrating pyramid-shaped gold nanoparticles within a graphene matrix. Leveraging graphene's exceptional electrical, thermal, and optical properties, we optimize the nonlinear optical response, achieving unprecedented efficiency in SHG processes. Our investigation reveals that the geometric configuration, specifically the aspect ratio and spatial arrangement of gold nanoparticles, critically influences the magnitude of plasmonic light absorption and SHG enhancement. Furthermore, we explore the synergetic effect of incorporating a gold-silver nanoparticle alloy, demonstrating a substantial improvement in SHG performance over traditional gold nanoparticle setups. Through systematic tuning of nanoparticle characteristics and strategic material pairing, our work unveils a pathway to highly efficient, graphene-enhanced plasmonic devices for advanced optical applications, marking a significant stride in the field of nonlinear photonics.
Spatiotemporal Variability of Climatic Factors in Response to Vegetation Cover Change In Bangladesh
Authors: Rimi Reshma Afroz , Hossain S. M. Nawshad 
Published: January 2024

Abstract

Climate change and its impact on environment is become the hot topic in the world. Bangladesh is a highly populated developing and agro-based economic country. Impact of several climatic factors such as rainfall, air temperature, humidity on agriculture is immense. But changes found in the trend of these climatic factors in here. This research aimed to detect the trend of three climatic factors, rainfall, temperature, and humidity over last 42 years (1981–2022) and along this, to explore the relation between vegetation coverage and climatic factors. The entire analysis is conducted for Upazilla level in Bangladesh. Maan-Kendal Test and Sen slope estimation is followed to detect the trend of three climatic factors and multiple regression model, Geographically Weighted Regression (GWR) Model and Ordinary Least Square (OLS) Regression Model is applied to explore the relationship between vegetation coverage and climatic factors. Positive trend is found for rainfall (24–147 mm/year) and humidity (0.16% − 0.47%) but negative trend is detected for temperature (− 0.03 to 0.00 ℃) for some Upazilla in Bangladesh. By GWR model, ranges of very weak to weak influence of vegetation coverage on the climatic factors are found for most of the Upazilla in Bangladesh. From the results of OLS, very strong correlation is found between the change rate of vegetation coverage and climatic factors for most of the Upazilla in Bangladesh especially the Upazilla of Sylhet and Chittagong Division. As Upazilla Master Plan is initiated in Bangladesh for each Upazilla, the outcomes of this research will help the policy makers to take the suitable plan for environment as well as agricultural development for each Upazilla through which sustainable development can be ensured.
Clinical application of LC-MS/MS to detect fat-soluble vitamins in gastric cancer
Authors: Sun Li , Gao Qianqian , Shen Yan , Sun Wangwei , Yao Yongliang 
Published: January 2024

Abstract
Purpose
Gastric cancer is one of the most common malignant tumors, with the incidence and mortality ranking among the top four malignant tumors in the world. In recent years, more and more studies have reported that fat-soluble vitamins are involved in tumor metabolism. However, the sensitivity and specificity of conventional detection methods are low, while liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has the advantages of high sensitivity, high specificity, high stability and wide linear range, which makes up for the shortcomings of immunological methods. The purpose of this study was to accurately detect the content of fat-soluble vitamins in GC patients by LC-MS/MS, and to clarify the necessity of preoperative determination and regular postoperative monitoring.
Methods
Serum 25(OH)D3, 25(OH)D2, VA, VE and VK1 levels in gastric cancer patients and healthy volunteers were detected by LC-MS/MS.
Results
The results showed that the levels of serum 25(OH)D3, 25(OH)D2, VA and VK1 in gastric cancer patients were significantly lower than those in healthy volunteers, and there was no significant difference in VE content.
Conclusion
This study suggests that patients with gastric cancer should timely detect and supplement fat-soluble vitamins and LC-MS/MS will provide a more accurate detection protocol for the clinic.
Robust Transfer Learning for High-Dimensional Penalized Linear Regression with t-distributed Error
Authors: Pan Lulu , Yu Yongfu , Qin Guoyou 
Published: January 2024

Abstract
Background: This paper studies the robust transfer learning for high-dimensional penalized linear regression with t-distributed error (Trans-PtLR), using information from diverse available source datasets to improve the estimation and prediction of the target data, accounting for the problem that normal linear regression is sensitive to outliers or heavy-tailed errors.
Method: In transfer learning with known transferable sources, we propose the PtLR model with an unknown degrees-of-freedom of the t distribution to transfer information from heterogeneous sources to the target. Assuming the error term follows a t distribution, the computation of maximum likelihood estimation of model effects and degrees-of-freedom is achieved via a coordinated descent algorithm nested inside the expectation conditional maximization (ECM) algorithm. To avoid negative transfer, a data-driven transferable source detection algorithm is applied to exclude non-informative sources. The performance of the proposed Trans-PtLR is evaluated through extensive simulation studies and an application using Genotype-Tissue Expression (GTEx) data to predict gene expression levels.
Result: We compare the performance of Trans-PtLR and transfer learning for penalized normal linear model (Trans-PNLR) under different data patterns. Simulation results indicate that the Trans-PtLR substantially outperforms Trans-PNLR in estimation and variable selection accuracy when outliers and heavy-tail are present in the data. In application, Trans-PtLR can further reduce the average relative prediction error by 42.2%, outperforming Trans-PNLR with an average reduction of 23.7%.
Conclusion: The proposed transfer learning for penalized t-linear regression (Trans-PtLR) offers robustness and flexibility to accommodate complex data with outliers and heavytails.
Epidemiological Survey of Cardiometabolic Multimorbidity and Related Risk Factors in Chinese Population: A Cross-Sectional Study
Authors: Xu Siying , Wang Wenbin , Wang Jiabin , Cai Anping , Jiang Xiaofei , Feng Yingqing 
Published: January 2024

Abstract
Background
The widespread prevalence of Cardiometabolic Multimorbidity (CMM) presents significant challenges to global public health. While previous studies have primarily examined individual cardiometabolic diseases, there has been limited research on CMM. As such, we intend to assess the prevalence of CMM and identify predictive risk factors within the Chinese population which will hold considerable implications for the future management of CMM.
Methods
We employed data from The China Patient-Centered Evaluative Assessment of Cardiac Events Million Persons Project (China-PEACE MPP), enrolling a total of 102,358 participants aged 35–75 years. CMM was defined as the simultaneous presence of two or more of the following diseases: diabetes, hypertension, stroke, and coronary heart disease. Univariate and multivariate logistic regression analyses were performed on demographic variables and modifiable factors associated with CMM to identify its risk predictive factors.
Results
The participants, with an average age of 54.27 years, comprised 60.5% of women. The overall prevalence of CMM was 11.6%, with hypertension and diabetes coexisting as the most common comorbid combination at 8.5%. Multifactor logistic regression analysis revealed that increasing age (45–54 years (OR = 2.62, 95%CI: 2.39–2.88), 55–64 years (OR = 5.27, 95%CI: 4.83–5.78), and 65–75 years (OR = 8.36, 95%CI: 7.62–9.18) compared to 35–44 years), current alcohol consumption (OR = 1.23, 95%CI: 1.12–1.34), TG ≥ 2.3mmol/L (OR = 1.69, 95%CI: 1.61–1.78), recent use of lipid-lowering medications (OR = 3.47, 95%CI: 3.21–3.74), and recent use of antiplatelet aggregators (OR = 3.67, 95%CI: 3.33–4.04) were associated with an increased risk of CMM. Conversely, a reduced occurrence of CMM was associated with being female (OR = 0.74, 95%CI: 0.70–0.78), other marital statuses (OR = 0.91, 95%CI: 0.85–0.97), education level of high school or above (OR = 0.90, 95%CI: 0.85–0.94), annual household income not less than 50,000 yuan (OR = 0.93, 95% CI: 0.89–0.98, p = 0.004), and HDL-C ≥ 1.0mmol/L (OR = 0.84, 95%CI: 0.79–0.90).
Conclusions
In the general population of China, over one-tenth of individuals are affected by CMM, indicating a high current prevalence of the condition. This highlights the imperative for China to develop targeted intervention measures focusing on the risk factors of CMM to prevent its occurrence and progression, effectively manage the condition, and reduce associated adverse outcomes and healthcare resource consumption.
An exploration of future of bioplastics and their physical, chemical and biological characteristic through bibliometric Analysis
Authors: Pansuriya Dhrushi , Kaul D. S. , Kodgire Pravin , Nema Akanksha , Mistry Mitali 
Published: January 2024

Abstract
Recently, petroleum-based plastic has become an integral part of human lives; however, its imperishable nature makes it the leading pollutant in solid waste, creating serious environmental problems. Inadequate plastic waste management increases the toxicity of landfills and causes air and marine pollution. Several initiatives have been started to overcome these challenges. Its replacement with biodegradable plastic is one of the upcoming solutions. Thus, many researchers have developed biodegradable plastics from various biomaterials. Despite such potential, no study has reported the research trend for these materials in the literature. This study is carried out to shed light on the past, present, and future research trends in the bioplastic arena. Such a study is important for bioplastic-related research to be made available at a single source with in-depth analysis. A bibliometric analysis is a tool that is carried out for this purpose. Despite numerous research articles and review papers available in the same field, there are limited reported studies related to the bibliometric analysis of bioplastics. Hence, this study has focused on the bibliographic data of 3802 publications from January 1999 till 1st January 2021, extracted from the Web of Science core collection databases using various combinations of search strings. VOSviewer was used to analyze the bibliographic data. With the help of various analysis techniques available with VOSviewer, many types of analysis (e.g. predominantly used material, tested properties of bioplastic etc.) were carried out. Through thisreview, the development and geographical distribution of the research related to bioplasticshave been investigated.
VODcasts' effect on college-level EFL whole-language instruction: a year-long investigation
Authors: Mekheimer Mohamed 
Published: January 2024

Abstract

The study aimed to assess the impact of video-based training on students' linguistic development using VODcasts. It used an experimental approach with a pretest, posttest, and control group design. The experimental group received instruction through a remedial program incorporating authentic video material and dramatised literary works, while the control group received audio materials. The experimental group showed significant improvements in all language skills, while the control group did not. The results suggest that using real videos to teach language is a successful method, leading to proficient listening, reading comprehension, speaking, and writing skills in the experimental group.
Evaluation of dyslipidemia based on ATP ⅠⅠⅠ guideline in adults of southwest Iran: A population-based study
Authors: Cheraghian Bahman , Saki Nader , Sarvandian Sara , Hashemi Seyed Jalal , Hosseini Seyed Ahmad , Saki Sara , Rahimi Zahra 
Published: January 2024

Abstract
Background
Dyslipidemia is a main risk factor for cardiovascular disease. The prevalence of dyslipidemia was 22.6–81% across Africa, South East Asia, Europe, the Americas and Iran. We aimed to investigate the occurrence of dyslipidemia and its associated risk factors in the southwest region of Iran.
Methods
This population-based cross-sectional study was conducted on 9846 participants aged 35–70 years of the Hoveyzeh Cohort Study in southwest Iran during 2016–2018. Information on socioeconomic factors, demographic characteristics, comorbidities, laboratory tests, anthropometric measurements, and lifestyle was collected. The criteria for dyslipidemia were based on the ATP III classification for adults. The chi-square test was used for analysis. Also, multiple logistic regression was used to control the potential confounders.
Results
Among 9846 participants, the mean ± SD of age was 48.8 ± 9.2 years, and 59.1% of them were women. The overall prevalence of dyslipidemia was 43.5%, and abnormal HDL, LDL, TC, and TG were 17.9%, 21.8%, 36.2%, and 44%, respectively. The multiple logistic regression showed that male (OR=1.92, 95%CI: 1.74 − 2.14), obese participants (OR༝3.0, 95%CI: 2.02–4.45), low physical activity (OR༝0.80, 95%CI: 0.76–0.97), smokers (OR༝1.17, 95%CI: 1.05 − 1.31), rich people (OR༝1.19, 95%CI: 1.04–1.36), and diabetic patients (OR༝1.63, 95%CI: 1.47 − 1.80) had a higher odds of dyslipidemia (all P-values were < 0.05).
Conclusion
Our findings suggest that dyslipidemia is a complex condition that is influenced by various biological and lifestyle factors. Different prevention and treatment strategies may be needed for different population subgroups.
Systemic inflammatory response index as a predictor of stroke-associated pneumonia in patients with acute ischemic stroke treated by thrombectomy: A retrospective study
Authors: Zheng Feng , Huang Xinyue , Guo Xiumei , Gao Wen , Xiong Yu , Chen Chunhui , Zheng Hanlin , Pan Zhigang , Wang Lingxing , Zheng Shuni , Ke Chuhan , Xiao Yinfeng , Liu Qiaoling , Hu Weipeng 
Published: January 2024

Abstract

Background: The predictive value of systemic inflammatory response index (SIRI) for stroke-associated pneumonia (SAP) risk in patients with acute ischemic stroke (AIS) treated by thrombectomy remains unclear. This study aimed to investigate the predictive value of SIRI for SAP in patients with AIS treated by thrombectomy.
Methods: We included AIS patients treated by thrombectomy between August 2018 and August 2022 at our institute. We used multivariate logistic regression to construct the prediction model and performed a receiver operating characteristic curve analysis to evaluate the ability of SIRI to predict SAP and constructed a calibration curve to evaluate the prediction accuracy of the model. We evaluated the clinical application value of the nomogram using decision curve analysis.
Results: We included 84 eligible patients with AIS in the analysis, among which 56 (66.7%) had SAP. In the univariate analysis, there were significant differences in sex (p=0.035), National Institute of Health Stroke Scale score at admission ≥ 20 (p=0.019) and SIRI (p<0.001). The results of multivariable logistic analysis showed that the risk of SAP increased with the SIRI value (OR=1.171, 95% CI=1.034–1.325, p=0.013). Age (OR=4.130, 95% CI=1.224–13.934, p=0.022), and sex (OR=3.440, 95% CI=1.040–11.380, p=0.043) were also statistically significant. A nomogram with SIRI showed good prediction accuracy for SAP in AIS patients treated by thrombectomy (C-index value=0.798).
Conclusions: SIRI is an independent predictor for SAP in patients with AIS treated by thrombectomy. A high SIRI value may allow for the early identification of patients with AIS treated by thrombectomy at high risk for SAP.
Silvopastoral systems as a strategy to reduce GHG emissions and restore natural areas in livestock systems in the Amazonian foothills of Caquetá, Colombia
Authors: Hurtado Laura P. Serna , Reyes Ernesto , Bellagamba Alfredo , Rivera Julián E. , Villegas Gonzalo O. , Deblitz Claus , Chará Julián 
Published: January 2024

Abstract

Cattle ranching is an important socioeconomic activity for the department of Caquetá in the Colombian Amazon. However, this activity is linked to a large part of the deforestation in the region with the consequent loss of biodiversity and the generation of large quantities of greenhouse gases (GHG). The objective of this work was to estimate the effect of establishing a silvopastoral system (SPS) on productivity, GHG emissions and natural habitat conservation on a typical farm in the region with conventional pastures. The emissions of a conventional 80 hectares farm based on pastures such as Ischaemum indicum and Brachiaria/Uroochloa species with a forest remnant of 1 ha were compared with those of a farm in which the establishment of a SPS was modeled in 51% of the area and 15 ha were released for forest restoration. GHG emissions were estimated using IPCC Tier 2, considering changes in production and emissions due to the implementation of the SPS using production parameters and carbon sequestration coefficients generated in previous research in the area. It was found that the SPS increases the carrying capacity by 18.5% and beef and milk production by 28% in relation to the conventional system and reduces gross emissions by 4.9%. In addition, with the SPS, net emissions went from 40,148 tons of CO2 eq/year to a net capture of -302,188 tons of CO2 eq/year within the farm, thanks to the carbon capture capacity of the SPS and the restored area. It is concluded that the implementation of SPSs is a strategy that allows increasing production, restoring forest and wetland areas and generating carbon sinks in the productive activity.