bluuebunny/crossref_metadata_2025 huggingface dataset:
Mineralogy and K–Ar geochronology of clay alteration associated with uranium mineralization in the Patterson Lake Corridor, Saskatchewan
Authors: Powell Jeremy W. , Percival Jeanne B. , Potter Eric G. , van der Lelij Roelant , Xie Ruikai
Published: June 2022

The Patterson Lake Corridor (PLC) along the southwestern margin of the Athabasca Basin contains high-grade uranium deposits entirely within crystalline basement rocks. Visible–near infrared–shortwave infrared (VNIR–SWIR) spectroscopy measurements were collected on drill core samples from several locations in the PLC. The Triple R and Arrow deposits exhibit downhole spectral trends related to the crystallinity and thermal maturity of clays (illite and kaolinite) and mineralization. The K–Ar dates of silt-and-clay size fractions (10–6 

μ

m; 6–2 

μ

m; 2–0.6 

μ

m; 0.6–0.2 

μ

m; <0.2 

μ

m) from five clay-altered samples decrease with grain size, and span 1608 ± 17 Ma to 1060 ± 14 Ma for the Spitfire discovery (
n
 = 14) and 1342 ± 17 Ma to 289 ± 4.3 Ma for the Arrow deposit (
n
 = 4). Alteration assemblages are broadly similar to Athabasca Basin basement-hosted deposits, and K–Ar dates indicate that high-grade uranium mineralization in the PLC reflects remobilization and concentration of primary ores. Integration of geochronology, clay mineralogy and VNIR–SWIR spectral parameters identify fertile fluid conduits when expanded to property or corridor scales, and provide additional evidence that ore grades of the Athabasca Basin deposits reflect several stages of hydrothermal mineralization spanning
c.
1000 Ma.

Supplementary material:
Supporting information document and datasets are available at
https://doi.org/10.6084/m9.figshare.c.6033890

Thematic collection:
This article is part of the Uranium Fluid Pathways collection available at:
https://www.lyellcollection.org/cc/uranium-fluid-pathways
Dynamics of the cerebral autoregulatory response to paced hyperventilation assessed using subcomponent and time-varying analyses
Authors: Clough Rebecca H. , Minhas Jatinder S. , Haunton Victoria J. , Hanby Martha F. , Robinson Thompson G. , Panerai Ronney B.
Published: June 2022

The dynamic response of critical closing pressure (CrCP) and resistance-area product (RAP) of the cerebral circulation to a step change in mean arterial pressure can shed light on the nonstationary changes induced by paced hyperventilation and the effects of hypocapnia on the autoregulation of cerebral blood flow. Contrary to hypercapnia, where the response is dominated by CrCP, hypocapnia shows an initial depression of cerebral autoregulation, followed by improvements controlled by changes in RAP.
A Note on Quotient Reflective Subcategories of O-REL
Authors: Qasim Muhammad , Aslam Ch. Muhammad Afaq
Published: June 2022

In this paper, we examine the category of ordered-RELspaces. We show that it is a normalized and geometric topological category and give the characterization of local

T

¯

0

, local

T

0

′

, and local

T

1

ordered-RELspaces. Furthermore, we characterize explicitly several notions of

T

0

’s and

T

1

objects in O-REL and study their mutual relationship. Finally, it is shown that the category of

T

0

’s (resp.

T

1

) ordered-RELspaces are quotient reflective subcategories of O-REL.
A Comparative Analysis of Blockchain in Enhancing the Drug Traceability in Edible Foods Using Multiple Regression Analysis
Authors: Suresh Kumar K. , Nassa Vinay Kumar , Uike Dipesh , kalra Ashima , Sahu Ajay Kumar , Athavale Vijay Anant , Saravanan V.
Published: June 2022

The growing need for access to safer food items is increasing, and hence, there is a need for a better supply chain management system in the food industry is increasing. The increased complexity of the existing systems tends to introduce more issues to the stakeholders, and also, the cost of product traceability is quite high. Hence, the industry is looking for effective solutions in relation to drug traceability, and the application of Blockchain technology enables the stakeholders in the food and beverage (F&B) sector to track the movement of goods, supported in gathering the required details so that the contaminated products can be identified and recalled without much delay and lesser recall costs to protect the lives of the individuals. The tampered food items are increasing and are impacting the supply chain process, brand name of the companies, and claim assurance. They create an adverse impact on the health of the individuals and cause higher economic loss to the health-care industry. The existing studies tend to focus on laying emphasis of the need for an enhanced, effective, and end tracking systems in the industry. The emergence of Blockchain technology enables centralized tracking of information support in enhancing the data privacy and increasing transparency and support in eradicating the tampered food products in the supply chain system. These approaches leverage the usage of smart contracts and decentralize the storage of information in a secure manner for enhanced product traceability in the F&B industry. The implementation of smart contracts generates better data governance, which tends to meet the needs and requirements of the stakeholders, and applies effective measures of food traceability. The primary objective of the study is to perform an analysis of Blockchain in enhancing drug traceability in the food sector. The researcher uses quantitative analysis for the study as it helps in understanding the critical determinants influencing drug traceability in food effectively, the survey method is used to gather the information, and past reviews are also used to possess a better understanding of the subject area effectively.
A Variable Selection Method Based on Fast Nondominated Sorting Genetic Algorithm for Qualitative Discrimination of Near Infrared Spectroscopy
Authors: Liu Hubin , Liu Na , Yuan Yuhui , Zhang Cihai , Zhao Longlian , Li Junhui
Published: June 2022

A reliable and effective qualitative near-infrared (NIR) spectroscopy discrimination method is critical for excellent model building, yet the performance of models built by these methods is highly dependent on valid feature extraction. The goal of feature selection is to associate the selected variables with the property of interest, which many have done successfully. However, many of selection methods focus only on strong association with the analytes or properties of interest, neglecting correlations between variables. A variable selection method based on a fast nondominated-ranking genetic algorithm (NSGA-II) was proposed in this paper for qualitative discrimination of NIR spectra. The method had two objective functions: (1) maximizing the sum of ratios of interclass variance to intraclass variance, (2) minimizing the sum of correlation coefficients between the selected variables. FT-NIR spectra of a total of 124 tobacco samples from different origins and parts in Guizhou Province, China, were used as the experimental objects, and the part-grade discrimination models of tobacco leaves were established by combining this method with partial least squares-based discriminant analysis (PLS-DA), and compared with PLS-DA model based on the full spectrum. The results showed that the performance of PLS-DA model with the NSGA-II was improved, with a comparable or better correct discrimination rate and reasonable discrimination rate, and could discriminate different parts of the tobacco leaves well. It indicates that the NSGA-II can select a few and effective feature variables to build a high-performance qualitative discrimination model and is proved to be a promising algorithm. In addition, the method is not designed exclusively for spectral data. It is a general strategy that could be used for variable selection for other types of data.
Research on Discourse Reconstruction Effect of Animated Film Cross-Cultural Communication Based on Machine Learning
Authors: Dai Hongyang , Lee Jonghan
Published: June 2022

Animated films are an important carrier of cultural dissemination, a way of conveying national culture and displaying regional culture in film and television, and an important medium for constructing national image and cultural form in the process of cross-cultural dissemination. The special film language expression of emotion in animated films also highlights its unique charm, status, and cultural communication role in the field of communication and at the same time reflects the unique value of the flash point in the ever-changing modern society. This paper starts with the related concepts of machine learning models, analyzes machine learning characteristics and model quality factors, and builds a model evaluation index system based on this and then proposes machine learning model evaluation implementation and index data processing methods. In building the corresponding evaluation experiment, the training model and animation film sentiment classification analysis need big data animation film culture data; the existing open source experimental data is very small and not suitable for the experiment of this paper. The principle of support vector machine is mainly introduced. And an improved machine learning model for animated film cultural sentiment classification is built. Experiments show that the performance of each index of the improved machine learning model is better than that of the support vector machine classifier.
Optimization of Stir Casting Variables for Production of Multiwalled Carbon Nanotubes: AA7149 Composite
Authors: Refaai Mohamad Reda A. , Ravi Samraj , Prasath S. , Thirupathy Maridurai , Subbiah Ram , Diriba Abdi
Published: June 2022

Combining liquefied metals with multiwalled carbon nanotube‐aluminium alloy 7149 composites enables the creation of intricate designs and mass production was manufactured using mechanical stir casting, thixoforming, and T6 heat treatment. Taguchi with two factorial levels was chosen to investigate the optimum parameter and affect variables such as carbon nanotube concentration, magnesium wettability, and ring mechanical stir duration were used in addition to a robust design of experiments. The response variables were the S/N ratio, hardness, and ultimate tensile strength. The fourth DOE run resulted in an optimised nanocomposite with 107.8 HV hardness and 278.1 MPa tensile strength that contained 0.75 wt.% magnesium and 1% multiwalled carbon nanotube and stirred time of 10 minutes. The as‐forged AA7149 alloy had a lower hardness value (76.3%) but a higher ultimate tensile strength value (108.4%). It was demonstrated that combining thixoforming and heat treatment improves the mechanical properties of multiwalled carbon nanotube produced under mechanical stir casting conditions.
[Retracted] Clinical Value of Abdominal Ultrasonography in the Diagnosis of Acute Abdomen in Children
Authors: Xu Xinxin , Ye Jian
Published: June 2022

In order to study the practical application value of abdominal ultrasonography in the diagnosis and treatment of acute abdomen in children, this study uses the method of collecting clinical actual cases and scientific analysis to estimate the clinical diagnostic value of high‐frequency ultrasound and low‐frequency ultrasound. In order to further clarify its curative effect and treatment advantages, a retrospective analysis of medical records was conducted, and 95 children with acute abdominal pain and suspected appendicitis who were admitted to a hospital from September 2021 to November 2021 were reviewed. ATIL HD15000 color Doppler ultrasound was used for diagnosis. The results are as follows: the sensitivity, specificity, positive predictive value, and negative predictive value of low‐frequency probe in the diagnosis of intussusception in children were 83.61%, 73.33%, 92.73%, and 52.38%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value in the diagnosis of mesenteric lymphadenitis were 80.00%, 81.97%, 52.17%, and 94.34%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of high‐frequency probe in the diagnosis of intussusception in children were 93.44%, 80.00%, 95.00%, and 75.00%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value in the diagnosis of mesenteric lymphadenitis were 93.33%, 95.08%, 82.35%, and 98.31%, respectively. Among the children with appendicitis confirmed by operation and pathology, 69 cases were detected by high‐frequency ultrasound and 4 cases were missed (including 3 cases of acute simple appendicitis and 1 case of perforated appendicitis). The false negative was 4%, there was no false positive, and the sensitivity, specificity and accuracy were 95%, 100%, and 96%. In the same cases, 28 cases were detected by low‐frequency ultrasound, 45 cases were missed, the false negative was 61%, and there was no false positive. The sensitivity, specificity, and accuracy were 39%, 100%, and 53%. The sensitivity, accuracy, and false negative of high‐frequency ultrasound in the diagnosis of acute appendicitis were significantly higher than that of low‐frequency ultrasound. This study shows that ultrasound has high accuracy, sensitivity, and specificity in the diagnosis of acute appendicitis. Low‐frequency ultrasound can show the whole picture of the disease and the situation in the abdominal cavity, which can better guide the clinical treatment. Color Doppler hemodynamics is a useful supplement to two‐dimensional ultrasound, and ultrasound also plays a positive role in the differential diagnosis of acute appendicitis in children.
Learning Strategies for Reading and Writing the Quran: Improving Student Competence as Preservice Teachers at the Faculty of Tarbiyah and Teacher Training
Authors: Hakim Rosniati , Ritonga Mahyudin , Khodijah Khodijah , Zulmuqim Zulmuqim , Remiswal Remiswal , Jamalyar Ahmad Reshad
Published: June 2022

Students must realize competence according to the chosen majors and study programs. The Faculty of Tarbiyah and Teacher Training, one of the students’ choices for continuing education, also has a mission to become a faculty that fosters students to become prospective professional educators. The reality that occurs is inversely proportional to the mission, and there are still Islamic education students as Islamic education preservice teachers who cannot read the Qur’an properly, while the Qur’an is the primary source in teaching Islam to students if they will become teachers in the future. This study aimed to critically analyze the strategies and policies implemented in conducting Quranic reading and writing learning at the Faculty of Tarbiyah and Teacher Training, UIN Imam Bonjol Padang. This study used a qualitative approach, and data were collected using interviews, observations, and study documentation. Based on the results of the study, Quranic reading and writing skills learning starts from mapping the abilities of all students, but the follow-up of mapping is not realized in continuous learning. However, the intracurricular and extracurricular activities carried out can improve students’ Quranic reading and writing competencies.
Web-Based News Straining and Summarization Using Machine Learning Enabled Communication Techniques for Large-Scale 5G Networks
Authors: Arora Amita , Gupta Ashlesha , Siwach Manvi , Dadheech Pankaj , Kommuri Krishnaveni , Altuwairiqi Majid , Tiwari Basant
Published: June 2022

In recent times, text summarization has gained enormous attention from the research community. Among the many uses of natural language processing, text summarization has emerged as a critical component in information retrieval. In particular, within the past two decades, many attempts have been undertaken by researchers to provide robust, useful summaries of their findings. Text summarizing may be described as automatically constructing a summary version of a given document while keeping the most important information included within the content itself. This method also aids users in quickly grasping the fundamental notions of information sources. The current trend in text summarizing, on the other hand, is increasingly focused on the area of news summaries. The first work in summarizing was done using a single-document summary as a starting point. The summarizing of a single document generates a summary of a single paper. As research advanced, mainly due to the vast quantity of information available on the internet, the concept of multidocument summarization evolved. Multidocument summarization generates summaries from a large number of source papers that are all about the same subject or are about the same event. Because of the content duplication, the news summarization system, on the other hand, is unable to cope with multidocument news summarizations well. Using the Naive Bayes classifier for classification, news websites were distinguished from nonnews web pages by extracting content, structure, and URL characteristics. The classifier was then used to differentiate between the two groups. A comparison is also made between the Naive Bayes classifier and the SMO and J48 classifiers for the same dataset. The findings demonstrate that it performs much better than the other two. After those important contents have been extracted from the correctly classified newscast web pages. Then, extracted relevant content is used for the keyphrase extraction from the news articles. Keyphrases can be a single word or a combination of more than one word representing the news article’s significant concept. Our proposed approach of crucial phrase extraction is based on identifying candidate phrases from the news articles and choosing the highest weight candidate phrase using the weight formula. Weight formula includes features such as TFIDF, phrase position, and construction of lexical chain to represent the semantic relations between words using WordNet. The proposed approach shows promising results compared to the other existing techniques.
Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer
Authors: Al-Shamma’a Abdullrahman A. , Hussein Farh Hassan M. , Noman Abdullah M. , Al-Shaalan Abdullah M. , Alkuhayli Abdulaziz
Published: June 2022

Hybrid renewable energy microgrid has become an attractive solution to electrify urban areas. This research proposes a microgrid design problem including photovoltaic (PV) arrays, wind turbine, diesel, and batteries for which Harris hawk optimization (HHO), a metaheuristic technique, is applied. Based on a long-term techno-economic assessment, the HHO approach is used to determine the best hybrid microgrid size for a community in Saudi Arabia’s northern region. The efficacy of HHO is investigated, and its performance was compared with seven metaheuristic techniques, grasshopper optimization algorithm (GOA), cuckoo search optimizer (CSO), genetic algorithm (GA), Big Bang–Big Crunch (BBBC), coyote optimizer, crow search, and butterfly optimization algorithm (BOA), to attain the HRE microgrid optimal sizing based on annualized system cost (ASC) reduction. Some benchmarks (optimum and worst solutions, mean, median, standard deviation, and rate of convergence) are used to distinguish and analyze the performance of these eight metaheuristic-based approaches. The HHO surpassed the other seven metaheuristic techniques in achieving the best HRE microgrid solution with the lowest ASC (USD 149229.9) followed by GOA (USD 149380.5) and CSO (USD 149382.5). The findings revealed that the HHO, GOA, CSO, and coyote have acceptable performance in terms of capturing the global solution and the speed of convergence, with only minimal oscillations. The BBBC, crow search, GA, and BA, on the other hand, have unacceptably poor performance, trapping to the local solution, oscillations, and a long convergence time. In terms of optimal solution and convergence rate, the BBBC and GA both perform poorly when compared to the other metaheuristic techniques.
A New Methodology for Solving Piecewise Quadratic Fuzzy Cooperative Continuous Static Games
Authors: Xiao He , Zhang Xiaoju , Lin Dong , Abd El- Wahed Khalifa Hamiden , Edalatpanah S. A.
Published: June 2022

This paper deals with

n

-players fuzzy cooperative continuous static games (FCCSGs). The cost function coefficients are characterized by piecewise quadratic fuzzy numbers. One of the best approximate intervals, namely, the inexact interval of the piecewise quadratic fuzzy number is used. Furthermore, we proposed a new methodology based on the weighted Tchebycheff method to solve CCSG with

n

-players. The advantages of the approach are the ability to enable the decision-maker to have satisfactory solution and applied for different real-world problems with various types of fuzzy numbers. There is also a stability set of the first kind without differentiability for the optimal compromise solution that was found. In the future, the proposed methodology could be used in different types of real-world problems and multiple decision-makers. This proposed work can also be extended to hypersoft set, fuzzy hypersoft sets, intuitionistic hypersoft sets, bipolar hypersoft sets, and pythagorean hypersoft sets. At the end, a numerical example is given to demonstrate the computational efficiency of the proposed method.
An Efficient Rotation Forest-Based Ensemble Approach for Predicting Severity of Parkinson’s Disease
Authors: Sheikhi Saeid , Kheirabadi Mohammad Taghi
Published: June 2022

Parkinson’s disease (PD) is a neurodegenerative nervous system disorder that mainly affects body movement, and it is one of the most common diseases, particularly in elderly individuals. This paper proposes a new machine learning approach to predict Parkinson’s disease severity using UCI’s Parkinson’s telemonitoring voice dataset. The proposed method analyses the patient's voice data and classifies them into “severe” and “nonsevere” classes. At first, a subset of features was selected, then a novel approach with a combination of Rotation Forest and Random Forest was applied on selected features to determine each patient’s disease severity. Analysis of the experimental results shows that the proposed approach can detect the severity of PD patients in the early stages. Moreover, the proposed model is compared with several algorithms, and the results indicate that the model is highly successful in classifying records and outperformed the other methods concerning classification accuracy and F1-measure rate.
A Systematic Review and Meta‐analysis on the Occurrence of Biomarker Mutation in Colorectal Cancer among the Asian Population
Authors: Afolabi Hafeez , Md Salleh Salzihan , Zakaria Zaidi , Seng Ch’ng Ewe , Mohd Nafil Siti Norasikin Binti , Abdul Aziz Ahmad Aizat Bin , Wada Yusuf , Irekeola Ahmad
Published: June 2022

Globally, colorectal carcinoma (CRC) is the third most common cancer and the third major cause of cancer‐related death in both sexes. KRAS and BRAF mutations are almost mutually exclusively involved in the pathogenesis of CRC. Both are major culprits in treatment failure and poor prognosis for CRC. Method. A systematic review and meta‐analysis of various research was done following the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis (PRISMA) guidelines. This trial is registered with PROSPERO CRD42021256452. The initial search included 646 articles; after the removal of noneligible studies, a total of 88 studies was finally selected. Data analysis was carried out using OpenMeta Analyst and Comprehensive Meta‐Analysis 3.0 (CMA 3.0) software to investigate the prevalence of KRAS and BRAF mutations among patients with CRC in Asia. Results. The meta‐analysis comprises of 25,525 sample sizes from Asia with most being male 15,743/25525 (61.7%). Overall prevalence of KRAS mutations was (59/88) 36.3% (95% CI: 34.5‐38.2) with I2 = 85.54% (P value < 0.001). In 43/59 studies, frequency of KRAS mutations was majorly in codon 12 (76.6% (95% CI: 74.2–78.0)) and less in codon 13 (21.0% (95% CI: 19.1‐23.0)). Overall prevalence of BRAF mutations was 5.6% (95% CI: 3.9‐8.0) with I2 = 94.00% (P value < 0.001). When stratified according to location, a higher prevalence was observed in Indonesia (71.8%) while Pakistan has the lowest (13.5%). Conclusion. Total prevalence of KRAS and BRAF mutations in CRC was 36.6% and 5.6%, respectively, and the results conformed with several published studies on KRAS and BRAF mutations.
Potential of Waste to Energy Conversion in Egypt
Authors: Ezzat Salem Mohamed , Abd El-Halim Hamdy , Refky Amr , Nassar Ibrahim Ahmed
Published: June 2022

This paper proposes a study on the potential of waste-to-energy (WTE) possibility in the Arab Republic of Egypt. WTE is a viable option for municipal solid waste (MSW) management and a renewable energy source. The issue of waste spread is a chronic environmental challenge in the Arab Republic of Egypt. The MSW practices in Egypt are simply done by collecting the waste and dumping it in open landfill sites. This research aims to assess the potential contribution of the WTE facility to meet electricity demand in Cairo City, which is Egypt’s capital and the biggest city in population as a sample, and then apply the results to all of Egypt. The paper introduced a step-by-step calculation for the electrical power that can be generated from Cairo MSW. Four scenarios for WTE utilization were developed: Mass Burn without any waste processing, Mass Burn with 25% recycling, Mass Burn excluding 50% of organic material, and Mass Burn excluding 50% of organic material with 25% recycling. The Mass Burn scenario implies full MSW stream incineration; the Mass Burn with recycling scenario considers a partial separation of reusable materials and the waste leftover for incineration; the Mass Burn with excluding 50% of organic material scenario considers a partial separation of organic materials and the waste leftover for incineration; the Mass Burn with excluding 50% of organic material with 25% recycling scenario considers a partial separation of organic materials and partial separation of reusable materials and the waste leftover for incineration. The analyses were done for the period 2011–2031 for Cairo with a total population of about 10 million in Nov 2021. The results show the huge potential of WTE conversion as a source of renewable energy, which is a key factor in Egypt’s sustainable development strategy 2030. Available data have been theoretically processed to show the decision-makers in Egypt the amount of electrical power that can be generated by using the WTE options to manage the MSW in Egypt.
A Hybrid Deep Learning Model for Trash Classification Based on Deep Trasnsfer Learning
Authors: Yuan Zhen , Liu Jinfeng
Published: June 2022

Trash classification is an effective measure to protect the ecological environment and improve resource utilization. With the development of deep learning, it is possible to use the deep convolutional neural network for trash classification. In order to classify the trash of the TrashNet dataset, which consists of six classes of garbage images, this paper proposes a hybrid deep learning model based on deep transfer learning, which includes upper and lower streams. Firstly, the upper stream divides the input garbage image into category MPP (metal, paper, and plastic class) or category CGT (cardboard, glass, and trash class). Then, the lower stream predicts the exact class of trash according to the results of the upper stream. The proposed hybrid deep learning model achieves the best result with 98.5 % than that of the state-of-the-art approaches. Through the verification of CAM (class activation map), the proposed model can reasonably use the features of the image for classification, which explains the reason for the superior performance of this model.
Using the Intelligent System to Improve the Delivered Adequacy of Dialysis by Preventing Intradialytic Complications
Authors: Karimi Mohammad , Dideban Daryoosh , Heidari Hadi
Published: June 2022

Acute kidney failure patients while detoxificated by hemodialysis (HD) mostly or continuously faced regular problems such as low blood pressure (hypotension), muscle cramps, nausea, or vomiting. Higher intradialytic symptom leads to low-quality HD treatment. Although more known therapeutic interventions are used to relieve the HD side effects, this study was designed to investigate how intelligent systems can make highly beneficial alterations in dialysis facilities and equipment to ease intradialytic complications and help the staff deliver high-quality treatment. A search was performed among relevant research articles based on nonpharmacological intervention methods considered to prevent adverse effects of renal replacement therapy until 2020 in the PubMed databases using the terms “intradialytic complications,” “intradialytic complication interventions,” “nonpharmacological interventions,” “intradialytic exercises,” and “adequacy calculation methods.” Studies included the prevalence of intradialytic complications, different strategies with the aim of preventing complications, the outcome of intradialytic exercises on dialysis symptoms, and dialysis dose calculation methods. The results showed the incidence of hypotension varying between 5% and 30%, fatigue, muscular cramps, and vomiting as the most common complications during dialysis, which greatly affect the outcome of HD sessions. To prevent hypotension, ultrafiltration profiling, sodium modeling, low dialysate temperature, and changing the position to Trendelenburg are some strategies. Urea reduction ratio (URR), formal urea kinetic modeling (FUKM), formal single-pool urea kinetics, and online clearance monitoring (OCM) are methods for calculating the delivered dose of dialysis in which OCM is a low-cost and accessible way to monitor regularly the quality of dialysis delivered. Integration of the chair and HD machine which is in direct contact with the patient provides an intelligent system that improves the management of the dialysis session to enhance the quality of healthcare service.
Antioxidant and Anticarcinogenic Potentials of Propolis for Dimethylhydrazine‐Induced Colorectal Cancer in Wistar Rats
Authors: Salehi Alireza , Hosseini Seyed Mohammad , Kazemi Sohrab
Published: June 2022

Propolis is a natural compound with anticarcinogenic properties. The present study aimed to compare the inhibitory effect of ethanolic extract of propolis (EEP) and vitamin E on dimethylhydrazine‐induced colon lesions in rats. In this study, 60 rats were randomly categorized into six 10‐member groups. After 13 weeks, blood and colon tissue were sampled to examine some factors. The parameters included red (RBC) and white (WBC) blood cell profile, lactate dehydrogenase (LDH), C‐reactive protein (CRP), total protein (TP), creatine kinase (CPK), and albumin, as well as the extent of colon histological lesions, protein expression (adenomatous polyposis coli (APC), proliferating cell nuclear antigen (PCNA), carcinoembryonic antigen (CEA), and platelet‐derived growth factor (PDGF)), and oxidative stress markers (total antioxidant capacity (TAC), malondialdehyde (MDA), and superoxide dismutase (SOD)) in colon tissue. A significant decrease was observed in congestion, mitotic index, inflammation, and cell destruction in colon tissue in dimethylhydrazine group in comparison with the control group (P < 0.05). The EEP exposed rats exhibited a significant lower oxidative stress than the DMH group (P < 0.05). Furthermore, the extract significantly affected TAC level (P < 0.05). While the expression level of APC rose substantially in the EEP‐treated group compared to the DMH group, the level of PCNA, CEA, and PDGF proteins significantly reduced. It seems that the EEP can efficiently prevent DMH‐induced colonic lesions. Furthermore, its effectiveness is more than the vitamin E, which is a strong antioxidant.
A Multiobjective Hybrid Optimization Algorithm for Path Planning of Coal Mine Patrol Robot
Authors: Gao Yongxin , Dai Zhonglin , Yuan Jing
Published: June 2022

In the complex underground environment, the paths planned for coal mine patrol robot are often too long and unsmooth under the influence of low visibility and poor road conditions. To solve the problems, this paper improves the hybrid algorithm between the improved artificial fish swarm algorithm (AFSA) and the dynamic window algorithm (DWA) for global path planning of coal mine patrol robot and introduces the improved genetic algorithm (GA) to enhance the path planning accuracy. Based on the global optimal path, the improved DWA was adopted to design a new adaptive trajectory evaluation function, which improves the ability of the patrol robot to avoid local obstacles. The proposed optimization algorithm was proved feasible through simulations. In addition, a simulation platform for the control of coal mine patrol robot was established, using the software development platform for coal mine patrol robot and robot operating system (ROS). The simulation results show that the improvement shortened the path length by 0.12 m, reduced the time by 3.14 s, and removed many turning points and redundant points. Therefore, the proposed improved hybrid path planning algorithm is effective and superior.
[Retracted] Development Mode of Recreation Belt around the City: Ecological Authenticity or Fashion Creativity?
Authors: Zhao Liang , Shen Yuanyuan , Gu Nailin , Dai Jingyu
Published: June 2022

The recreational belt around the city has low population density, good ecological environment, and rich natural and cultural landscapes, which can meet the tourism needs of urban residents to get close to nature and experience culture. Particularly in today’s increasingly normal epidemic prevention and control, outing and microtourism have become the first choice of urban public tourism and an important part of rural tourism development. In the process of developing rural tourism, there are two distinct voices: one is to pay attention to the local complex and strive to let people “see mountains and water and remember nostalgia.” In the era of cultural tourism integration, we should promote rural tourism with culture, highlight rural culture with rural tourism, and give full play to the bridge between cultural tourism and rural cultural innovation. In view of this situation, this paper discusses the theme orientation of the advanced development of the recreational belt around the city through three studies. In Study 1, tourists’ perceptions of local complex and rural cultural creation were compared through field investigation. In Study 2, brand trust was used as a calibration variable to further test the robustness of the conclusion. Study 3 analyzed the “distortion” mechanism of rural cultural creation and tested the intermediary effect of psychological distance. At the same time, it discusses the evolution model of the recreational space system around the city. The development of recreation space shows that the recreation space around the city is the product of the agglomeration of population and economic activities, and its occurrence and development process is closely related to the expansion of urban space and the change of human living space. This paper analyzes the spatial process of the development of recreation around the city, focuses on the types of recreation space that continue to appear in the development and evolution of modern recreation space, and then tries to find the context of the gradual development and evolution of recreation around the city with the process of urbanization and excavate the organic connection between the recreational space and the city and its surrounding areas in the process of development and evolution. It is found that (1) tourists’ perception of local culture is further distorted, which leads to a further reduction in tourists’ perception of “local culture” and “recreation,” and (2) the increase in psychological distance is the key psychological mechanism for tourists to perceive “lost property.”
Health Care Quality in CKD Subjects: A Cross-Sectional In-Hospital Evaluation
Authors: Rzayeva L. , Matyukhin I. , Ritter O. , Patschan S. , Patschan D.
Published: June 2022

Background and Aim. Chronic kidney disease (CKD) is an emerging problem in both clinical and ambulatory medicine. Much effort in terms of managing CKD must be put into the control of so-called progression factors. In the current investigation, we evaluated the CKD-associated health care quality in all in-hospital subjects that were treated in a newly founded university hospital for a period of 1 year. Methods. The study was performed in a retrospective and observational manner. All adult (age 18 years or older) in-hospital subjects treated from January until December 2019 were included. CKD was diagnosed according to the KDIGO 2012 CKD Guideline. The following variables were assessed: CKD stage, quantification/analysis (yes/no) of blood pressure, proteinuria, serum phosphate, serum 25-OH-D3, ferritin and transferrin saturation, and blood gas analysis. In addition, recommendations of the following medicines were analyzed (given/not given): ACE inhibitor or sartan, phosphate binder, vitamin D3 (activated or native), iron, erythropoietin, and bicarbonate. It was also evaluated whether discharge letters contained CKD-related diagnoses or not. Results. In total, 581 individuals were included in the study. The majority of aspects related to the monitoring and therapeutic management of CKD were either considered in only a small proportion of affected individuals (e.g., quantification of PTH − 5.5%/25-OH-D3 − 6%/transferrin saturation − 13.6%) or avoided nearly at all (e.g., recommendation of erythropoietin—1%, documentation of CKD-MBD diagnosis—0.3%). A reasonable quality of care was identified concerning the blood pressure monitoring (performed in 100%) and blood gas analysis (55% of the patients received analysis). Serum phosphate was measured in 12.9%, particularly in subjects at higher CKD stages. Conclusions. The current investigation revealed poor quality of care in CKD patients treated at the Brandenburg University Hospital over the period of one year. Quality improvement must be achieved, most likely via a standardized educational program for physicians and a directer access to CKD management guidelines.
Design of Optimization Algorithm for Configuration of Amateur Sports Training Equipment in Smart City Community
Authors: Wan Yuehong , Tang Hong
Published: June 2022

Community amateur sports training equipment is necessary to ensure the development of national fitness activities. It is found that the design concept of community public sports space in China is not perfect, the structural layout is not reasonable, the stock space is not optimized, and the resource allocation is not balanced. In particular, there is a lack of indoor fitness facilities and sports venues in the community, and the people's “fitness where to go” is still a difficult problem. In the smart city construction, the resource integration and optimization of community amateur sports training facilities have also been further developed. Considering various influencing factors, this paper establishes a location model of community amateur sports training facilities with the least total cost and convenience. Aiming at the practical optimization problem with high complexity, an improved adaptive weight multiobjective particle swarm optimization (PSO) model is proposed. These parameters in the algorithm were adjusted dynamically, which balanced the overall search ability and partial improvement ability of the PSO algorithm and completed the optimal scheduling of community amateur sports training equipment configuration while ensuring the optimal global solution. Experimental results show that the algorithm’s efficiency and searching ability have been further promoted. It also has an excellent performance in solving the complex location problem of community amateur sports training facilities.
A Multiparameter Coupled Prediction Model for Annular Cuttings Bed Height in Horizontal Wells
Authors: Lu Zongyu , Wu Baocheng , Shi Jiangang , Xi Chuanming , Wei Kai
Published: June 2022

Cuttings accumulation in horizontal drilling is one of the main reasons for high drilling torque and drag and serious backing pressure and consequently influencing the rate of penetration (ROP), so inhibiting the generation of cuttings bed and keeping the hole clean is an important prerequisite to ensure the smooth and safe drilling of horizontal section. In order to master the formation mechanism of cuttings bed and reveal the influence law of influencing factors, based on the three-layer cuttings bed migration model and the two-phase solid-liquid flow theory, this paper establishes a numerical simulation method for cuttings migration characteristics in the annulus of horizontal wells, reveals the cuttings concentration distribution law and migration characteristics in the horizontal well section, and fits the engineering prediction model of cuttings bed height considering many factors such as geology, engineering, and fluid body according to the simulation results. The analysis of sensitive factors shows that the rate of penetrating, cuttings density, and drill pipe eccentricity is not conducive to borehole cleaning, and cuttings are easy to accumulate to form cuttings bed; increasing the drilling fluid density, displacement, and drill pipe speed is conducive to borehole cleaning and reducing the height of cuttings bed. The research shows that within the range of normal construction parameters, the error of the horizontal cuttings height prediction model is less than 10%, which can meet the needs of engineering analysis. The model provides convenience for engineering applications.
Reproducibility of the Blood and Urine Exposome: A Systematic Literature Review and Meta-Analysis
Authors: Goerdten Jantje , Yuan Li , Huybrechts Inge , Neveu Vanessa , Nöthlings Ute , Ahrens Wolfgang , Scalbert Augustin , Floegel Anna
Published: June 2022

Endogenous and exogenous metabolite concentrations may be susceptible to variation over time. This variability can lead to misclassification of exposure levels and in turn to biased results. To assess the reproducibility of metabolites, the intraclass correlation coefficient (ICC) is computed. A literature search in three databases from 2000 to May 2021 was conducted to identify studies reporting ICCs for blood and urine metabolites. This review includes 192 studies, of which 31 studies are included in the meta-analyses. The ICCs of 359 single metabolites are reported, and the ICCs of 10 metabolites were meta-analyzed. The reproducibility of the single metabolites ranges from poor to excellent and is highly compound-dependent. The reproducibility of bisphenol A (BPA), mono-ethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-2-ethylhexyl phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-benzyl phthalate (MBzP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), methylparaben, and propylparaben is poor to moderate (ICC median: 0.32; range: 0.15–0.49), and for 25-hydroxyvitamin D [25(OH)D], it is excellent (ICC: 0.95; 95% CI, 0.90–0.99). Pharmacokinetics, mainly the half-life of elimination and exposure patterns, can explain reproducibility. This review describes the reproducibility of the blood and urine exposome, provides a vast dataset of ICC estimates, and hence constitutes a valuable resource for future reproducibility and clinical epidemiologic studies.
Preclinical Efficacy of BCMA-Directed CAR T Cells Incorporating a Novel D Domain Antigen Recognition Domain
Authors: Buonato Janine M. , Edwards Justin P. , Zaritskaya Liubov , Witter Alexandra R. , Gupta Ankit , LaFleur David W. , Tice David A. , Richman Laura K. , Hilbert David M.
Published: June 2022

Chimeric antigen receptor (CAR) T-cell therapies directed against B-cell maturation antigen (BCMA) have shown compelling clinical activity and manageable safety in subjects with relapsed and refractory multiple myeloma (RRMM). Prior reported CAR T cells have mostly used antibody fragments such as humanized or murine single-chain variable fragments or camelid heavy-chain antibody fragments as the antigen recognition motif. Herein, we describe the generation and preclinical evaluation of ddBCMA CAR, which uses a novel BCMA binding domain discovered from our D domain phage display libraries and incorporates a 4-1BB costimulatory motif and CD3-zeta T-cell activation domain. Preclinical in vitro studies of ddBCMA CAR T cells cocultured with BCMA-positive cell lines showed highly potent, dose-dependent measures of cytotoxicity, cytokine production, T-cell degranulation, and T-cell proliferation. In each assay, ddBCMA CAR performed as well as the BCMA-directed scFv-based C11D5.3 CAR. Furthermore, ddBCMA CAR T cells demonstrated in vivo tumor suppression in three disseminated BCMA-expressing tumor models in NSG-immunocompromised mice. On the basis of these promising preclinical data, CART-ddBCMA is being studied in a first-in-human phase I clinical study to assess the safety, pharmacokinetics, immunogenicity, efficacy, and duration of effect for patients with RRMM (NCT04155749).
In VitroInsertional Mutagenesis Screen Identifies Novel Genes Driving Breast Cancer Metastasis
Authors: Miskey Csaba , Botezatu Lacramioara , Temiz Nuri A. , Gogol-Döring Andreas , Bartha Áron , Győrffy Balázs , Largaespada David A. , Ivics Zoltán , Sebe Attila
Published: June 2022

Metastasis, a complex, multistep process, is responsible for the overwhelming majority of cancer-related deaths. Despite its devastating consequences, it is not possible to effectively treat cancer that has spread to vital organs, the mechanisms leading to metastasis are still poorly understood, and the catalog of metastasis promoting genes is still incomprehensive. To identify new driver genes of metastasis development, we performed an in vitro Sleeping Beauty transposon-based forward genetic screen in nonmetastatic SKBR3 human breast cancer cells. Boyden chamber-based matrix invasion assays were used to harvest cells that acquired a de novo invasive phenotype. Using targeted RNA sequencing data from 18 pools of invasive cells, we carried out a gene-centric candidate gene prediction and identified established and novel metastasis driver genes. Analysis of these genes revealed their association with metastasis related processes and we further established their clinical relevance in metastatic breast cancer. Two novel candidate genes, G protein–coupled receptor kinase interacting ArfGAP 2 (GIT2) and muscle-associated receptor tyrosine kinase (MUSK), were functionally validated as metastasis driver genes in a series of in vitro and in vivo experimental metastasis models. We propose that our robust and scalable approach will be a useful addition to the toolkit of methodologic resources used to identify genes driving cancer metastasis.

Implications:

Novel metastasis drivers were identified in a human breast cancer cell line by performing an in vitro, Sleeping Beauty transposon-based forward genetic screen and an RNA fusion-based candidate gene prediction.