bluuebunny/crossref_metadata_2025_split huggingface dataset:
To Analyse the Mechanical Performance of Concrete by Partially Substituting Plastic in Coarse Aggregate
Authors: Reddy B. Dileep Kumar , Anitha B. , Mohith P. , Madhavi K. , Naik D. Anil Kumar , Rahul E. , Eswar P. 
Published: April 2023

Abstract
A coin has two faces, and while concrete is without doubt the most beneficial material in the building business, it also has drawbacks. Concrete production uses raw ingredients that have detrimental environmental effects in one way or another. For example, the production of aggregates release dust into the environment, whereas the creation of cement produces carbon dioxide. The geology of the region where coarse aggregates are produced is also affected. A step in this direction is the use of waste materials in addition to or instead of cement. Many of these items, like rice husk and silica fume, are already in use. Plastic coarse aggregates are used in this study in place of natural coarse aggregates. Plastic garbage was only little processed to create plastic aggregates. The biggest environmental issue now is plastic, which is having an immediate. Due to certain of its characteristics, such as inert behaviour and resistance to deterioration, it can be employed in the construction business, according to some recent studies. Using left over plastic can also aid in the reduction of waste plastic. Several experiments were carried out to investigate the mechanical attributes of concrete using plastic coarse particles. Plastic coarse aggregates of varied plastic composition were used to produce concrete. Concrete was made using plastic coarse aggregates in various amounts of 0%, 2.5%, 5.0%, 7.5%, 10.0%, and 12.5%.
Retrospective Study of the Efficacy of Docetaxel/Carboplatin Combination Therapy as Postoperative Adjuvant Chemotherapy for Nonsquamous Cell Carcinoma of the Cervix
Authors: Koike Ryo , Yunokawa Mayu , Omatsu Kohei , Kurihara Nozomi , Nomura Hidetaka , Sekizawa Akihiko , Kanao Hiroyuki 
Published: April 2023

Abstract
Objective Optimal adjuvant chemotherapy for nonsquamous cervical carcinoma has not yet been established. This study investigated the efficacy and safety of docetaxel/carboplatin (DC) for early stage nonsquamous cell cervical carcinoma after radical hysterectomy (RH).Methods We evaluated 157 patients with stage IB-IIB nonsquamous cervical carcinoma with intermediate risk and high risk treated at our institution with DC after type II or III RH from 2007 to 2021. Patients received docetaxel (60–70 mg/m2) and carboplatin (area under the curve 5–6) every 3 weeks for six cycles. The primary endpoint was 2-year recurrence-free survival (RFS) and the secondary endpoint was adverse events (AEs).Results There were 106 intermediate-risk and 51 high-risk patients. The high-risk patients included 11 with positive parametrial involvement, 20 with pelvic lymph node metastases, and 20 with both parametrial involvement and pelvic lymph node metastases. The 2-year RFS rates for intermediate- risk, high-risk, and positive pelvic lymph nodes were 94.8% (95% confidence interval [CI], 87.9–97.8), 80.1% (95% CI, 64.1–89.5), and 74.5% (95% CI, 55.4–86.4), respectively. Sixteen patients had recurrence, including local recurrence (n = 6), distant metastasis (n = 9), and local and distant metastasis (n = 1). Hematologic toxicity was the most frequent AE, especially leukopenia and neutropenia. Nausea and constipation were the most frequent nonhematologic toxicities.Conclusion DC therapy at our institution showed good 2-year RFS, and postoperative adjuvant therapy with DC therapy is suggested as a useful strategy for patients with nonsquamous cervical carcinoma.
Effect of different structure of Cu/Mn catalysts on ozone decomposition ability
Authors: Li Hao , Li Yunhe , Liu Mengyu , Wang Penghui , Zhao Baogang , Sun Tianjun 
Published: April 2023

Abstract
A simple co-precipitation method was utilized to synthesize Cu/Mn catalysts with different physiochemical properties for high humidity ozone decomposition. The catalysts were then tested for their activity and stability in decomposing ozone, and their physical and chemical properties were analyzed through various characterization techniques. Furthermore, the characterization after stability testing provided insights into the internal mechanism of the ozone reaction process. The Cu/Mn-NN catalyst demonstrated excellent ozone decomposition activity in the temperature of 25–100°C, maintaining the conversion above 91% for continuous ozone decomposition for 12 hours at room temperature, the relative humidity (RH) of 85%, and the weight space velocity of 300 L·g− 1·h− 1. Characterization revealed that the Cu/Mn-NN catalyst, exhibited the larger specific surface area, better reducibility and oxygen storage capacity, richer surface functional groups and oxygen vacancies. Additionally, characterization after the stability test confirmed the accumulation of oxygen intermediate species on the catalyst surface. The findings also suggested that the catalytic environment created by nitrate precursors played a vital role in preventing catalyst particle aggregation, facilitating electron transfer within the catalyst, ensuring uninterrupted migration of lattice oxygen, and timely regeneration of oxygen vacancies.
Human Risk Exposure Assessment Of Endocrine-Disrupting Heavy Metals Found In Microplastics and Microrubbers: Case Study-Ahvaz Metropolitan, Iran
Authors: Soltani ZHaleh Mahdavi , Cheraghi Mahboobeh , Jaafarzadeh Neematollah , Tavakkoli Haman 
Published: April 2023

Abstract
This study's objective is to investigate the type, concentration, and spectrometry analysis of six endocrine-disrupting heavy metals (based on World Health Organization/International Program on Chemical Safety (WHO/IPCS) proposal and list from 2002) detected on the surface of microplastics and microrubbers in the soils of municipal solid waste landfills in the Ahvaz metropolitan area. This study also seeks to evaluate the Human health risk posed by such pollutants. Ten sampling stations and two control stations were chosen using the systematic grid sampling method in both locations. Microplastics and microrubbers particles were recovered from samples utilizing density difference and flotation procedures Next, the samples were analyzed with a stereomicroscope, polarized light microscopy, and Scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDS). Metals were also analyzed using various coupled plasma mass spectrometry (ICP-MS). The existence of endocrine-disrupting heavy metals on the particles' surface was confirmed. According to the results of the noncarcinogenic risk assessment (HQ) of several exposure pathways to particles and pollutant compounds carrying them, the ingestion pathway posed a greater risk of exposure to children than other pathways. In addition, the noncarcinogenic risks of the majority of compounds examined do not exceed the permissible limit (HI ≤ 1), and there is no noncarcinogenic risk associated with the cumulative effects of these elements on humans.
Thyroid disease diagnosis based on feature interpolation and dynamic weighting ensemble model
Authors: Xie Yufei , Yu Weiwei , Song Shasha , Wang Wenlin , Gao Wenke , Jia Ying , Wen Shaotai , Wang Chongyang , Wang Sen 
Published: April 2023

Abstract
Medical diagnosis is the basis for modern medical treatment planning, rapid and accurate testing is responsible for patients’ lives and health. Thanks to increasingly sophisticated large-scale data collection techniques, the advantages of big data and artificial intelligence technologies for data analysis are gradually coming to the fore. However, medical data mostly have missing items and non-human biases, and common algorithms often show instability in learning data distribution patterns. In this paper, a feature interpolation algorithm based on feature importance is proposed for thyroid disease classification dataset, and a dynamic assignment integration model is designed to further optimize the weight assignment of the integration model in terms of distance and accuracy, which improves the accuracy and smoothness of the model. The classification accuracy reaches 94.75%, which is 2.45% higher than the original model, and the index AUC is almost the same as the original model. The generalization learning performance is poor because the deep learning algorithm lacks the support of a priori knowledge in learning data features. In this paper, the convolutional model is introduced to the sequence data prediction and propose a feature-enhanced small network EdcNet, and combine it with the feature interpolation algorithm to explore the role and effect of lightweight convolution in sequence analysis, and the final classification accuracy and AUC reach 95.6% and 99.1%, respectively.
Determination of the initial abstraction ratio and curve number of the upper catchment area of the Sawaga river watershed, Bukidnon
Authors: Perodes Jemima , Fornis Ricardo 
Published: April 2023

Abstract
The Curve Number (CN) method has been widely used for estimating runoff from rainfall. However, some uncertainties in the method have been recognized by various researchers all over the world. One of which is the NRCS-assumed initial abstraction ratio (Ia/S) of 0.20. In this study, the Ia/S and the CN for the upper catchment area of the local watershed of the Sawaga river in Bukidnon were determined using rainfall-runoff event analysis of rainfall events with a total precipitation depth ranging from 21.50 mm to 57.90 mm. The event Ia/S values ranged from 0.0019 to 0.4603. The representative values of Ia/S and CN are 0.03 and 62.3, respectively. Evaluating the performance of both the original NRCS and the locally derived values through their direct runoff prediction, the standard error, coefficient of determination, and Nash-Sutcliffe efficiency indicated that both are good and have predicted the direct runoff satisfactorily. However, these indicators showed that the locally derived values gained higher accuracy in general. The percentage of mean bias displayed the most significant difference between the two, classifying the original NRCS-CN values as unsatisfactory while the locally adapted values as very good. These findings suggest that the CN method with certain adjustments on Ia/S and CN values is appropriate for the direct runoff estimation in the upper catchment area of the Sawaga river, Bukidnon.
Optimal bounds for complete elliptic integral of the second kind from means
Authors: Shi Yong-Guo , Li Na 
Published: April 2023

Abstract
We give the new double inequalities for the quasi-arithmetic mean and Seiffert-like mean. As applications, two new optimal bounds are presented for the complete elliptic integral of the second kind. And numerical comparisons illustrate that some bounds of our results are better than before.
AMS(2020) subject Classification: 26E60, 33C75, 26D20.
On-line Evolutionary Identification Technology for Milling Chatter of Thin Walled Parts Based on the Incremental-Sparse K-Means and the Online Sequential Extreme Learning Machine
Authors: Wang Zhixue , Yue Caixu , Liu Xianli , Li Maoyue , Meng Boyang , Yong Liying 
Published: April 2023

Abstract
In the milling process of thin-walled parts, chatter is very easy to occur, which has a very adverse impact on the surface quality and machining efficiency of the workpiece. In order to solve the problem of low accuracy of milling state identification caused by few initial samples and dynamic changes in the milling process, a hybrid online evolutionary chatter identification model combining unsupervised learning and supervised learning is proposed. First of all, aiming at the problem that traditional K-Means algorithm is difficult to adapt to online dynamic clustering of milling chatter, an online Incremental-Sparse K-Means algorithm (ISK-Means) was proposed, and the dynamic incremental-sparse strategy of K-Means was designed. Secondly, aiming at the problem that the Online Sequential Extreme Learning Machine (OS-ELM) algorithm directly adds its predicted samples to the training sample set during the incremental learning process, and the pseudo-samples in the training sample set would lead to the degradation of the OS-ELM model, a hybrid online evolutionary chatter identification model combining the ISK-Means and the OS-ELM was proposed, and the online identification and evolution strategy was designed.Finally, the experimental results show that the ISK-Means algorithm can greatly improve the clustering efficiency and is suitable for milling chatter online dynamic clustering. Meanwhile, compared with the existing model, the recognition accuracy of the hybrid online evolutionary chatter recognition model combined with ISK-Means algorithm and OS-ELM algorithm is improved by 1.31%. This is of great significance for the online control of subsequent chatter.
SARS-CoV-2 NSP12 utilizes various host splicing factors for replication and splicing regulation
Authors: Yang Li , Zeng Xiao-Tao , Ren Si-Xue , Liang Lin-Lin , Huang Qiu-Xia , Fan Hong , Ren Hai-Yan , Cheng Wei 
Published: April 2023

Abstract
Background
The RNA-dependent RNA polymerase (RdRp) is a crucial element in the replication and transcription of RNA viruses. Although the RdRps of lethal human coronaviruses SARS-CoV-2, SARS-CoV, and MARS-CoV have been extensively studied, the molecular mechanism of the catalytic subunit NSP12, which is involved in pathogenesis, remains unclear.
Results
In this study, the biochemical and cell biological results demonstrate the interactions between SARS-CoV-2 NSP12 and seven host proteins, including three splicing factors (SLU7, PPIL3, and AKAP8), suggesting that the polymerase activity and stability of SARS-CoV-2 RdRp were affected by them to varying degrees. Furthermore, the entry efficacy of SARS-CoV-2 pseudovirus considerably decreased when SLU7 or PPIL3 was knocked out, indicating that abnormal splicing of the host genome was responsible for this occurrence. In addition, NSP12 and its homologues from SARS-CoV and MARS-CoV suppressed thealternative splicing (AS) of cellular genes, which were influenced by the three splicing factors.
Conclusions
Overall, our research illustrates that SARS-CoV-2 NSP12 can engage with various splicing factors, thereby impacting virus entry, replication, and gene splicing. This not only improves our understanding of how viruses cause diseases but also lays the foundation for the development of antiviral therapies.
A New 2D Chaotic System and Application in Hash Function by Cipher Block Chaining
Authors: Behroo Y. , Giglou H. Babaei , Parvaz R. 
Published: April 2023

Abstract
In the proposed method, one-way hash function construction based on chaotic map with changeable parameters and cellular automata is introduced. The main structure of the proposed algorithm based on a new 2D chaotic system, cipher block chaining(CBC) and using of the cellular automata. In the first step, the input original messages are expressed as a matrix form which, the elements of this matrix have structure as $8$ bits sized. The chaotic system and cellular automata have been used in the encryption section of the algorithm. Also, in the proposed steps, the cipher block chaining(CBC) has been introduced and used to obtain the final hash values. In the simulation section by using some statistical tests, the advantages of the proposed algorithm are studied.
Social cognition, socioeconomic status and subjective well-being of Chinese migrant workers
Authors: Huang Weichao , Su Shipeng , Sun Xiaoyu , Zhang Yashan 
Published: April 2023

Abstract
In the framework of the new economic norm, industrial restructuring and social development have made it more difficult for migrant workers to experience subjective well-being. The subjective well-being of migrant workers is based on the unity of internal and external needs, material and immaterial needs. Thus, based on data from the 2017 China General Social Survey (CGSS), this paper applies ordered logit models and OLS models to investigate the impact of social cognition and socioeconomic status on the subjective well-being of migrant workers and their intergenerational differences. The results indicate that: (1) Social cognition has a significant impact, and the impact of fairness perception is more pronounced than depression perception and class change perception; (2) among socioeconomic status, personal income did not have a significant effect as education level, car ownership and house property ownership; (3) there are intergenerational differences. The emotional state of the older generation is the most critical factor influencing their subjective well-being. In contrast, the new generation is more concerned with their feelings about future expectations. The older generation is more concerned with their house property ownership, while the increase in income, education and car ownership can significantly increase the subjective well-being of the new generation. For this reason, we believe that the Chinese government should gradually change the existing urban and rural management system to create a fair and just social environment; make migrant workers receive the same protection as urban residents and improve the income distribution mechanism; pay attention to the social security of the older generation of migrant workers and the development opportunities of the new generation of migrant workers and their ability to integrate into the city to improve their subjective well-being.
AI Modeling for High-Fidelity Heat Transfer and Thermal Distortion Forecast in Metal Additive Manufacturing
Authors: Ball Amit Kumar , Basak Amrita 
Published: April 2023

Abstract
In this study, a novel AI-based modeling approach is introduced to estimate high-fidelity heat transfer calculations and predict thermal distortion in metal additive manufacturing, specifically for the multi laser powder bed fusion (ML-PBF) process. The effects of start position and printing orientation on deformation and stress distribution in parts produced using ML-PBF additive manufacturing process were investigated. A total of 512 simulations were executed, and the maximum and minimum deformation values were recorded and compared. A significant improvement e.g., 53% in deformation was observed between the best and worst printing cases. A low-fidelity modeling framework, based on a feedforward neural network was developed for the rapid prediction of thermal displacement with high accuracy. The model with unknown test cases demonstrated a strong positive correlation (R = 0.88) between high-fidelity and network-predicted low-fidelity outputs. The simplicity, computational efficiency, and ease of use of the developed model make it a valuable tool for preliminary evaluation and optimization in the early stages of the design process. By adjusting controlling factors and identifying trends in thermal history, the model can be scaled to a high-fidelity model for increased accuracy, significantly reducing development time and cost. The findings of this study provide valuable insights for designers and engineers working in the field of additive manufacturing, offering a better understanding of deformation/thermal displacement control and optimization in the PBF process using multiple lasers.
Study on mechanical, thermal and morphology behavior of sisal / Bentonite nanoclay reinforced cardanol biopolymer composites
Authors: Paul N. E. Edwin 
Published: April 2023

AbstractCardanol and its derivatives are presently thought to be particularly appealing intermediates for generating novel materials from renewable bio-sources for utilize in environmentally pleasant procedures. In order to create novel polymer composites, this study details the synthesis and characterisation of a bio resin named cardanol that is produced from cashew nut shell liquid (CSNL). Locally harvested sisal fibers were dried out in an oven to reduce humidity. These fibers were then cut into 15 mm lengths and chemically treated sisal fibers using an alkaline process. Compression moulding was used to make polymer composites of cardanol reinforced with 15% wt% 15 mm sisal fiber (SF) and bentonite nanoclay (with nanoclay% levels of 0%, 1%, 3%, 5%, and 7%). FT-IR spectroscopies were used to characterise the bio resin cardanol. Mechanical behaviour for cardanol nano composites was assessed using tensile, flexural, and impact tests and water absorption test. Furthermore, the thermal and morphology behaviour of cardanol nanoclay composites is examined. The results confirmed that increasing the range of nanoclay by up to 5% enhanced mechanical characteristics.
WITHDRAWN: Vancomycin-cement reactions cause Red Man Syndrome and other life-threatening hypersensitivity reactions; the challenge of managing periprosthetic joint infection
Authors: Msh  , MM  , HR  
Published: April 2023

Abstract
Periprosthetic joint infections (PJI) are commonly treated with antibiotic-impregnated bone cement (AIBC). We described a 62-year-old female, who showed After 18 hours of surgery, symptoms of Red Man Syndrome (RMS) and other hypersensitivities were caused by a spacer containing vancomycin. Vancomycin can cause a variety of hypersensitivity reactions, including RMS and anaphylaxis. It can be challenging for physicians to manage emergency RMS features and life-threatening reactions such as anaphylaxis shock after using vancomycin-loaded bone cement following PJI. The patient received immediate emergency healthcare, intravenous fluid therapy, epinephrine, corticosteroids, and antihistamines in response to serious side effects, including flushing, erythema, agitation, urticaria, tachycardia, pruritus on the trunk and buttocks, severe itching, hypovolemia, macular rashes, and exfoliative dermatitis. Delayed surgery to remove antibiotic-loaded bone cement has been suggested as a successful treatment for periprosthetic joint infections (PJI).
Most Accurate Multiclass Linear Classifiers Producing Disconnected Decision Regions
Authors: Chaiyakan Songkomkrit , Vichitthamaros Preecha 
Published: April 2023

Abstract
The work concerns linear multiclass classification where training data can be arbitrary in shape and a decision region is allowed to be disconnected. The main objective is to achieve highest training accuracy, resulting in originally proposed and alternative polygonal classifiers through the detection of an individual misclassified instance and the investigation of majority voting in a decision region respectively. When separating hyperplanes are restricted to cut only one axis, two similar versions of box classifiers which give rectangular decision regions are proposed. Algorithms for finding minimal hyperplanes and cuts while maintaining the same training accuracy are also provided. All four classifiers are developed through 0-1 mixed integer linear programming (MILP). Alternative versions are recommended when training data is very large in number.