bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis and Characterization of Mono- and Biphasic Ca1−xMnxHPO4·nH2O Compounds
Authors: Alyami Mohammed , Alsunaidi Haya Ali , Al-Kafawein Juma'a , Alanazi Abdulaziz A. , Alotibi Satam , Abdulaziz Fahad , Mahmoud Nada T. , Alshaaer Mazen 
Published: August 2024

Calcium phosphates and manganese phosphates play a significant role in biomedical and engineering applications, and these compounds are both synergistic. These compounds could have great potential for use in different applications, particularly as precursors of biomaterials. Therefore, the aim of this study was to explore the effect of the gradual replacement of Ca2+ with Mn2+ on the phase composition and crystal structure of brushite (CaHPO4·2H2O), which could be useful for the production of Mono- and Biphasic Ca1−xMnxHPO4·nH2O Compounds. In order to prepare the starting solutions required for this study, Ca(NO3)2·4H2O, (NH4)2·HPO4, and Mn(NO3)2·4H2O were used at various molar concentrations. Afterwards, the Ca1−xMnxHPO4·nH2O compounds were prepared using dissolution and precipitation methods. These compounds were characterized using XRD, SEM, FT-IR, XPS, and TGA techniques. The findings revealed that Mn substituted Ca partially at low Mn/Ca molar ratios, 0.25, and Mn doping increased the unit cell of CaHPO4·2H2O. The produced biphasic compound was composed of monoclinic CaHPO4·2H2O and nanostructured orthorhombic MnHPO4·(H2O)3 after a continuous increase in the Mn/Ca molar ratio to 1.5. When the Ca/Mn molar ratio was above 1.5, a monophasic compound of the MnHPO4·(H2O)3 phase was formed. The MnHPO4·(H2O)3 compound was successfully prepared for the first time using this dissolution-precipitation method. It was also established that the Mn/Ca ratio of the starting solution can be modified to produce CaHPO4·2H2O and MnHPO4·(H2O)3 phases with specific weight percent compositions.
Preoperative Nutrition Impacts Retear Rate After Arthroscopic Rotator Cuff Repair
Authors: Shitara Hitoshi , Ichinose Tsuyoshi , Sasaki Tsuyoshi , Hamano Noritaka , Kamiyama Masataka , Miyamoto Ryosuke , Ino Fukuhisa , Nakase Kurumi , Honda Akira , Yamamoto Atsushi , Takagishi Kenji , Chikuda Hirotaka 
Published: August 2024

Background:
A rotator cuff retear following arthroscopic rotator cuff repair (ARCR) is a concern in older patients. However, only a few of its risk factors are amenable to preoperative intervention. We aimed to elucidate the relationship between preoperative nutritional status and rotator cuff retears after ARCR.

Methods:
This single-center retrospective study included patients aged ≥65 years with rotator cuff tears who underwent ARCR. The Geriatric Nutritional Risk Index (GNRI) was used to assess preoperative nutritional status. Data collection encompassed patient demographics, clinical assessments, and surgical specifics. Patients were divided into healed and retear groups based on 2-year post-ARCR magnetic resonance imaging results. Logistic regression analysis was conducted to adjust for confounding factors and detect independent risk factors for retears. The GNRI cutoff value for retear prediction was determined by a stratum-specific likelihood ratio; clinical outcomes were compared based on the cutoff values obtained.

Results:
Overall, 143 patients were included. The retear rate was 20.3%. The albumin level, GNRI, postoperative shoulder strength of abduction and external rotation, and postoperative Japanese Orthopaedic Association and Constant scores in the retear group were significantly lower than those in the healed group. The logistic regression analysis showed that low risk of morbidity and mortality (compared with no risk) based on the GNRI (odds ratio [OR], 3.39) and medial-lateral tear size per mm (OR = 1.10) were independent risk factors for a retear 2 years after ARCR. Stratum-specific likelihood ratio analysis identified data-driven strata as GNRI < 103, 103 ≤ GNRI < 109, and GNRI ≥ 109. Univariate analysis showed that patients with GNRI < 103 had a significantly higher retear risk than those with 103 ≤ GNRI < 109 and those with GNRI ≥ 109. Logistic regression analysis showed that GNRI < 103 compared with 103 ≤ GNRI < 109 (OR = 3.88) and GNRI < 103 compared with GNRI ≥ 109 (OR = 5.62), along with the medial-lateral tear size per mm (OR = 1.10), were independent risk factors for a retear at 2 years after ARCR.

Conclusions:
When assessing the risk of a retear after ARCR, GNRI ≥ 103 may indicate good preoperative nutritional status. However, more data are essential to ascertain the importance of this finding.

Level of Evidence:
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Understanding Strain Signals from Low-Frequency Distributed Acoustic Sensing In-Well Measurements: Experimental and Numerical Modeling
Authors: Bradley N. A. , Haavik K. E. , Landrø M. 
Published: August 2024

Summary
Over the past few decades, the potential of distributed measurements using in-well fiberoptic data has been demonstrated. In particular, low-frequency distributed acoustic sensing (LF-DAS) has experienced rapid growth toward monitoring wells for integrity and production purposes. Despite technological advancements, applications in this space have been hindered by a limited understanding of the data. The richness of detail in the data is a double-edged sword; while it provides substantial amounts of information to guide the operator, it simultaneously complicates the task of deciphering the underlying signals. To address this issue, it would be advantageous to devise a straightforward approach to understand the nature of common signals due to strain encountered during routine well operations.
We present an experimental method for interpreting tubing strain signals using a long spring that is fixed at both ends, mimicking the tubing in a well. Tracking the position of coils over time allows us to record the displacement when a force is applied to the spring. We show that the displacement observed from such an experiment is similar to what we observe in LF-DAS data from wells in operation. Typical signals, such as the pistoning effect on a valve or strain caused by fluid flow, are compared with experimental data. More complex phenomena, such as stick/slip friction and thermal expansion, are modeled using a mass-spring system and compared with wellbore examples. Developing a fundamental understanding of the signals will allow for real-time identification of events, facilitated by fiber-optic data, substantially enhancing operational outcomes by preempting integrity issues and promoting production optimization.
Stacking model based on six base classifiers to improve prediction of soil liquefaction: a multi-dataset study
Authors: Yao Xiaofei , Chen Yumin , Gao Hongmei , Sarajpoor Saeed , Li zhenxiong , Han Yi 
Published: August 2024

Abstract

Prediction of soil liquefaction during earthquake is a crucial task to mitigate or avoid damage caused by liquefaction. The existing machine learning methods have achieved satisfactory prediction accuracy on specific datasets, but they are unable to perform well on other datasets. To overcome the limitation, a novel prediction method based on stacking strategy are proposed to evaluate earthquake-induced liquefaction potential of soil, which is composed of six base classifiers and secondary classifier. The hyperparameters are tuned by grid search algorithm and the AUC value under ten folds cross validation are utilized as the basis for obtain the optimal hyperparameters. The applicability of stacking model was verified using three widely used datasets. Six performance metrics are utilized to analyze and compare the performance of base classifiers and stacking model. The result indicates proposed model outperforms base classifier in all three datasets in terms of the metrics mentioned above. Furthermore, the proposed method underwent a comparative evaluation against other existing machine learning techniques, revealing that the prediction accuracy achieved by the proposed model surpasses that of the existing methods. Also, this study investigated the importance of input parameters so as to interpret the complicated relationship between liquefaction potential and input parameters.
Analysis of CO2 Emissions by Selected Sri Lankan Apparel Industry Factories Across Economic Shifts (2019-2022)
Authors: Dissanayake Thilina , Lokupitiya Erandathie 
Published: August 2024

Abstract

The effects of economic growth on environmental well-being are frequently examined, but it is equally crucial to evaluate the impact of economic downturns. This study aims to address this gap by focusing on Sri Lanka’s export-based apparel manufacturing sector. Due to global concern on climate change and related impacts, there is an urgent need to reduce industry sector emissions of greenhouse gases, including CO2. The study investigates monthly CO2 emissions from 2019 to 2022, covering pre-COVID-19 (Jan 2019 - Jan 2020), COVID-19 (Feb 2020 - May 2021), and the economic crisis (Jun 2021 - Dec 2022) periods. Data from six major export-oriented apparel factories were analyzed for their CO2 emissions, using IPCC (2006) guidelines for national greenhouse gas inventories. The monthly CO2 emissions showed a significant disparity across the considered economic periods (χ² = 23.44, p<0.001). Notably, Scope 1 emissions, entailing onsite direct emissions from fuel combustion, witnessed a distinct mean increase of 126% during the economic crisis period (241.47 ± 62.25 t CO2) compared to the mean COVID-19 period (106.78 ± 40.61 t CO2, p<0.001) and a 78% rise compared to pre-COVID-19 levels (135.17 ± 30.64 t CO2, p<0.001). Multiple linear regression on monthly average exchange rates and monthly production revealed a significant impact on monthly emissions (Adj. R² = 0.761, p<0.001), with both factors showing positive influences. The current study highlights the importance of incorporating greener solutions in industries and countries facing similar economic challenges.
Simulation of nitrate nitrogen concentration and DOM characteristics in southwest karst wetlands using an improved GMS model
Authors: Gong Chunjin , Dai Junfeng , Wan Zupeng , Zhang Hongyan 
Published: August 2024

Abstract

This study aims to simulate and predict the nitrate nitrogen (NO3−-N) concentration in groundwater using a Gaussian function model combined with the Groundwater Modeling System (GMS) identification model. Additionally, the components of dissolved organic matter (DOM) in groundwater were measured using fluorescence spectroscopy to analyze their variation characteristics and effects on NO3−-N. The results demonstrated that the Gaussian curve fitting method accurately simulates NO3−-N concentration. For the southwest karst wetland, coupling the Gaussian function model with the GMS model effectively simulates and predicts changes in groundwater NO3−-N concentrations. The simulation indicates that NO3−-N concentrations are lower in the northern region and higher in the central area, with peak values at lower elevations reaching 20.732 mg/L. NO3−-N is primarily concentrated in the southwestern region of the study area and the upper part of Mudong Lake, showing a diffusion trend from west to east. Analysis of DOM characteristics reveals significant contributions from autochthonous sources, primarily endogenous metabolic products of microbial decomposition. The total fluorescence intensity and its components generally increase downstream, being lowest at the source and highest at river confluences. The humification index (HIX) indicates that groundwater with lower NO3−-N concentrations has lower HIX values, while higher NO3−-N concentrations correspond to higher HIX values. In summary, this study provides new insights into the simulation and prediction of NO3−-N in groundwater and the characteristics of DOM, serving as a reference for the protection of groundwater systems in the southwest karst basin.
Livestock Feeding Practices in South Kivu, Eastern Democratic Republic of Congo: Challenges and Opportunities
Authors: Azine Pascaline Ciza , Mugumaarhahama Yannick , Mutwedu Valence Bwana , Baenyi Simon Patrick , Kunde Emmanuel Amani , Mwanga Jean-Claude Ithe Mwanga , Bacigale Samy Bashizi , Karume Katcho , Ayagirwe Rodrigue Basengere-Balthazar 
Published: August 2024

Abstract

Livestock production in South Kivu is a major source of rural income. Increasing livestock productivity through improved livestock feeding is critical to alleviating poverty among smallholder farmers. The study aims to provide evidence-based recommendations for improving livestock productivity in South Kivu. It assesses the availability and use of feeds for livestock in Kabare, Uvira and Walungu. Current feeding practices are traditional, resulting in suboptimal animal nutrition. Livestock diets consist mainly of fodder and crop residues. Different botanical families provide essential fodder for livestock in the region. Disparities in forage availability affect animal nutrition and productivity, requiring targeted interventions. Additionally, a comprehensive SWOT and NOISE analysis were conducted to assess the current state and potential approaches for improving livestock feeding practices. Strengths include farmers' expertise and strategies to cope with forage scarcity, particularly in the dry season. Weaknesses include limited land tenure and limited adoption of intensive systems. Opportunities include diversification of food sources and farmer training. Challenges include climate variability and socioeconomic constraints. Proposed improvements focus on feed quality, nutritional supplements, and training. Strategic actions include policy advocacy and community involvement. Exceptions highlight the importance of tailoring practices to local contexts.
Investigation of the impact of diverse climate conditions on the cultivation suitability of Cinnamomum cassia using the MaxEnt model, HPLC and chemometric methods in China
Authors: Li Yanqun , Yang Yang , Gu Dingze , Cheng Yanrong , Lv Xuejuan , Huang Yan , Ye Peng , Liu Xiaomin , Tan Huiping , Liu Yujie , Guo Yongtong , Bai Mei , Huang Rongshao , Wu Hong 
Published: August 2024

Abstract

Cinnamomum cassia Presl. is a subtropical plant that is used for food and medicine. Climate change has changed the suitable habitats of medicinal plants, which might have repercussions for the efficacy of herbal remedies. In this study, the potential distribution in each period of Cinnamomum cassia was predicted and the quality in different suitable habitats was evaluated. According to the results, (1) precipitation, temperature, and soil are the primary environmental variables influencing C. cassia distribution. (2) The high-suitable habitats of current climate scenarios were predominantly located in the southern regions (Guangdong and Guangxi etc.) of China. Under future climate scenarios, suitable habitats will increasingly move northward, with a greater concentration south of the Yangtze River. (3) HPLC and FTIR, combined with chemometrics, can be effective methods for identifying different suitable habitats of C. cassia. The content of trans-cinnamaldehyde is significantly higher in the high suitability habitat compared to the medium-low suitability habitat. Our findings can offer valuable guidance for the identification of suitable C. cassia cultivation areas in China, as well as for the evaluation of C. cassia resource quality and the rational use of resources in different suitable habitats.
Model Research on the Impact of Tree Greening Layout with Wind-responsive Characteristics on the Wind Environment in Residential Areas
Authors: Zhai Yumei , Li Xin , Zhao Ye , Tian Qihui , Wang Ruoyu , Zhang Guoyi , Chen Zhonggou , Zhu Junhao , Ren Xinyi 
Published: August 2024

Abstract

With the concept of living environment put forward, creating a comfortable, healthy and energy-saving living environment has attracted more attention. The optimization of wind environment is of positive significance for urban ecological livability and alleviating urban heat island effect. Considering the wind-induced response of trees, this paper uses computer simulation technology to explore the distribution of flow field around greening in different building spaces and layout forms, and puts forward the optimization strategy of greening layout around buildings. The research shows that different building environments will also have a certain impact on the wind environment behind trees. Roof greening is more complicated than the wind field around buildings, and the wind-induced deformation of trees is obvious, and the wind reduction rate is higher. In addition, considering the influence of wind-induced response on trees, different planting spacing has different wind reduction efficiency. The proportion of ideal wind speed area in different horizontal layout forms of trees from large to small is row, enclosure and row.
A Year-Long Investigation of the PM2.5 Dynamics in Klang Valley-Malaysia Using Variance Decomposition and Impulse Response Function Analyses
Authors: MUSTAFA ZAINOL , BELAL AMINA AHMED , MAMI AHMED , LATIF MOHD TALIB , Rusli M.N. 
Published: August 2024

Abstract

The current well-being of the general population is significantly affected by air pollution. Notably, particulate matter measuring 2.5 µm or less in diameter (PM2.5) is a primary concern due to its ability to infiltrate the respiratory system thoroughly. Therefore, this study investigated the temporal correlations between the 2021 PM2.5 levels in Klang Valley, Malaysia, using a vector auto-regressive model (VAR). The methodology in this study also involved examining the dynamics of the daily average PM2.5 levels within the same year by utilizing two approaches: variance decomposition and impulse response function (IRF). Consequently, the primary factor responsible for the PM2.5 level variations was the self-contribution of PM2.5, accounting for approximately 80.94% of the total variations. Other contributions produced negligible effects on PM2.5 levels over long periods, including wind speed (WS, 3.55%), humidity (Hum., 3.23%), and carbon monoxide (CO, 1.47%). A rapid decrease in PM2.5 levels was observed based on one standard deviation (SD) shock in PM2.5. Meanwhile, lower PM2.5 levels were reported due to temperature (Temp.) with Hum. disturbances, whereas the constant CO disturbances appeared throughout the observed period. In contrast, higher PM2.5 levels were correlated with NO2 disturbances. This observation was attributed to ground level O3, WS, and wind direction (WD) fluctuations, occasionally generating temporary declines lasting up to five days. Overall, the PM2.5-based air pollution in Klang Valley could be addressed in this study by emphasizing the significance of implementing specific measures. The relevance of policies prioritizing local emission sources and promoting efficient pollution management techniques should be highlighted.
A Study on Analysis Based on Linear Polarization Resistance, Anodic Polarization and Electrochemical Impedance Spectroscopy in Geopolymer Concrete
Authors: N Karthiga @Shenbagam , V Kannan , P Raja Priya , I Jerin Leno 
Published: August 2024

Abstract

Effects on the induction of chloride in the reinforcements of geopolymer concrete are of greater importance in the current applications to study the prevention of corrosion in the field of marine engineering. Experiments on corrosion have been carried out in five different solutions with different concentrations and compositions from which the point of initial degradation of steel reinforcement was found out. Further on the density of corrosion that led to failure was analyzed in detail. From the tests carried out it was found that as the value of alkaline in the electrolyte increases the value of chloride threshold also increases. The effect of corrosion was found to decrease in geopolymer concrete when reinforcements have been immersed in calcium hydroxide as it improves the stability of the passive film created.
On high-dimensional Kuramoto model with symmetry-breaking terms
Authors: Liu Xinyun , Li Xueyan , Shi Yushi 
Published: August 2024

Abstract

M.A. Lohe first proposed the high-dimensional Kuramoto model with symmetry-breaking terms (Quantum synchronization over quantum networks, Journal of Physics A: Mathematical and Theoretical, 43:465301, 2010), which is the real form of a quantum network synchronization model. Forthe homogeneous case, by analyzing the limit set and the spectrum of the linearized model, thealmost global synchronization is derived from the topology of some kind of connecting graphs.
Optimizing focused very-high-energy electron beams for radiation therapy based on Monte Carlo simulation
Authors: An Chaofan , Zhang Wei , Dai Zeyi , Li Jia , Yang Xiong , Wang Jike , Nie Yuancun 
Published: August 2024

Abstract

A TOPAS-based optimization program has been developed to precisely concentrate the dose of focused very-high-energy electron (VHEE) beams on deep-seated targets. This is accomplished by optimizing the magnetic gradients, positions, and number of quadrupole magnets within TOPAS. Using only three quadrupole magnets, the program focuses 250 MeV VHEE beams to achieve a maximum dose position deeper than 17 cm, while maintaining entrance and exit doses within 25% and limiting the lateral dimensions to ≤ 1 cm at the maximum dose location. The linear relationship between the magnetic gradient of the last quadrupole magnet and the maximum dose position enables dose location adjustments through gradient variation. Multiple positions were validated in TOPAS with errors within 1%. The spread-out electron peak (SOEP) is achieved by combining two VHEE beams with different maximum dose positions using the differential evolution method, covering a target depth of 12–17 cm and attaining a dose flatness better than 99%. This pioneering program imposes constraints on entrance dose, exit dose, maximum dose position, and the lateral dimensions of dose deposition at the maximum dose position within phantom. This program may be a promising tool in the applications of focused VHEE in highly conformal treatment plans based on TOPAS.