bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Diminished Ovarian Reserve on Early Embryo Morphokinetics during In Vitro Fertilization: A Time-Lapse Study
Authors: Boucret Lisa , Tramon Léa , Riou Jérémie , Ferré-L’Hôtellier Véronique , Bouet Pierre-Emmanuel , May-Panloup Pascale
Published: December 2022

There is great controversy as to whether women with Diminished Ovarian Reserve (DOR) exhibit only a quantitative decrease in ovarian reserve or also impaired oocyte and embryo quality. In this retrospective study, we aimed to evaluate the impact of DOR on embryo morphokinetic parameters with a time-lapse system. 1314 embryos were obtained from 256 couples undergoing IVF or ICSI cycles, with 242 embryos in the DOR group as classified by the Bologna and POSEIDON criteria and 1072 embryos derived from the Normal Ovarian Reserve (NOR) group. For each morphokinetic parameter (t2, t3, t4, t5, t8, tB, ECC2, cc2a, ECC3, s2, s3), a generalized linear mixed model was created to control for female age, BMI, smoking status, method of insemination and correlation between oocytes from a same cohort. No significant association was found between DOR and any of the morphokinetic parameters studied. In a secondary analysis, we evaluated the influence of maternal aging, comparing morphokinetic characteristics between two age groups (<37 and ≥37 years). In the univariate analysis, we found that embryos from older women displayed a slower embryo development (in particular for t3, t4, t5, tB, and ECC2), although without statistical significance in the multivariate analysis. In conclusion, our study did not reveal any substantial impact of ovarian aging on early morphokinetic parameters and suggested potential biases that may be a source of controversy in the literature.
Multidimensional Scaling of Cognitive Ability and Academic Achievement Scores
Authors: Meyer Em M. , Reynolds Matthew R.
Published: December 2022

Multidimensional scaling (MDS) was used as an alternate multivariate procedure for investigating intelligence and academic achievement test score correlations. Correlation coefficients among Wechsler Intelligence Scale for Children, Fifth Edition (WISC-5) and Wechsler Individual Achievement Test, Third Edition (WIAT-III) validity sample scores and among Kaufman Assessment Battery for Children, Second Edition (KABC-II) and Kaufman Test of Educational Achievement, Second Edition (KTEA-2) co-norming sample scores were analyzed using multidimensional scaling (MDS). Three-dimensional MDS configurations were the best fit for interpretation in both datasets. Subtests were more clearly organized by CHC ability and academic domain instead of complexity. Auditory-linguistic, figural-visual, reading-writing, and quantitative-numeric regions were visible in all models. Results were mostly similar across different grade levels. Additional analysis with WISC-V and WIAT-III tests showed that content (verbal, numeric, figural) and response process facets (verbal, manual, paper-pencil) were also useful in explaining test locations. Two implications from this study are that caution may be needed when interpreting fluency scores across academic areas, and MDS provides more empirically based validity evidence regarding content and response mode processes.
Regional Differences and Dynamic Changes in Sea Use Efficiency in China
Authors: Zhang Qian , Yu Xuan
Published: December 2022

This study aims to identify the overall level of China’s sea use efficiency (SUE) from 2006 to 2018 as well as regional differences and dynamic changes The super-efficiency weighted slacks-based measure (Super-WSBM) model and the global Malmquist–Luenberger (GML) index are employed. Results indicate that the SUE is at a medium-efficiency level. The inspection period revealed a decline period (2006–2008), a steady increase period (2008–2013), and a rapid increase period (2013–2018), exhibiting a “checkmark” type of growth. SUE has significant regional differences, and the degree of polarization has increased. Shanghai, Guangdong, and Shandong are high-efficiency regions, but unlike Shandong, which has experienced a rapid growth, the SUE of Shanghai and Guangdong has declined to varying degree, in Shanghai being particularly significant; Jiangsu and Tianjin are medium-efficiency regions, and SUE has experienced a rapid growth; Fujian, Hebei, and Zhejiang are inferior-efficiency regions, and SUE has slightly increased; Liaoning, Hainan, and Guangxi are low-efficiency regions. Except for a slight decline in Hainan, Liaoning and Guangxi experienced small increases. Thus, a sea use policy must be formulated on the basis of local conditions to promote the coordinated development of the marine economy. Moreover, the negative external impact of sea use on the marine environment must be observed, and marine resources within the range of the sea must be utilized.
Fast High-Precision Bisection Feedback Search Algorithm and Its Application in Flattening the NURBS Curve
Authors: Zhu Kaige , Shi Guoyou , Liu Jiao , Shi Jiahui
Published: December 2022

It is important to accurately calculate flattening points when reconstructing ship hull models, which require fast and high-precision computation. However, some search algorithms, such as the bisection method, iterate near the optimal value too many times before converging in high-precision computation. The paper proposes a fast high-precision bisection feedback search (FHP-BFS) algorithm to solve the problem. In the FHP-BFS algorithm, the Newton–Raphson (NR) method is adopted to accelerate the convergence speed by considering the iteration characteristics of subintervals. Furthermore, a new feedback mechanism is proposed to control the feedback directions. In addition, an acceleration algorithm, called the interval reformation method, is used to guide the FHP-BFS algorithm for fast convergence. Finally, the flattening algorithm is improved by the FHP-BFS algorithm. In the comparative experiments, the practical efficacy of the FHP-BFS algorithm is first demonstrated, and then the optimal range of the threshold precision is determined. Next the FHP-BFS algorithm is compared to the best existing algorithms. Finally, the performance of the improved flattening algorithm is verified. The experiments demonstrate that the FHP-BFS algorithm has optimal performance among the compared algorithms, and it has an improved computation efficiency while maintaining robustness. The improved flattening algorithm reduces the computation time, ensures smoothness and meets practical engineering requirements.
Growth and Physiological Responses of Chrysotila roscoffensis (Coccolithales) to Different Phosphorus Resources
Authors: Zhou Li , Xiao Peng , Liu Baoning , Han Jichang , Li Yahe , Zhou Chengxu
Published: December 2022

The growth and physiological process of microalgae interact with environmental nutrients. In the present study, we compared the growth and physiological characteristics of coccolithophore Chrysotila roscoffensis under the effects of phosphate at high and low concentrations, and of organic phosphorus of adenosine triphosphate (ATP) and Na2-glycerophosphate (SG). The growth, photosynthesis, calcification, alkaline phosphatase activity, and inorganic nutrient absorption rate were comparatively studied. The results showed that the culture with a low concentration of initial phosphate (6 μM) had a lower growth rate than that with a high concentration (45 μM). However, a relatively similar maximum cell density could be achieved. Equimolar inorganic phosphorus supported a higher initial growth rate than organic phosphorus. ATP was better than SG at supporting higher growth rates, higher photosynthetic activity, and higher cell density. Cellular alkaline phosphatase (AP) responded rapidly to nutrient variations with sharp changes of activities, independent of the initial P resources. Cellular calcification was at a higher level in groups with lower growth rates. Phosphate in low concentration in the medium was not absorbed during the early growth period while that in high concentration was rapidly absorbed. Instead, phosphate in low concentration was rapidly absorbed in the late stationary phase. The absorption of nitrate was affected by the initial P resources as well. The DIN/DIP ratio in the water varied significantly during the growth periods. The results indicated that C. roscoffensis had flexible physiological strategies in utilizing varied phosphorus resources, and high cell density maintenance of C. roscoffensis may play roles in nutrient conditions in the water. This study may help to extend the understanding of nutrient utilization strategy in microalgae and to apply reference in the application of Chrysotila species in the removal of nutrient pollution.
CFD Analysis and Optimization of the DEMO WCLL Central Outboard Segment Bottom-Cap Elementary Cell
Authors: Melchiorri Lorenzo , Arena Pietro , Giannetti Fabio , Siriano Simone , Tassone Alessandro
Published: December 2022

In the design of magnetic confinement nuclear fusion power plants, the breeding blanket (BB) plays a crucial role since it must fulfil key functions such as tritium breeding, radiation-shielding, and removal of the heat power generated by the plasma. The latter task is achieved by the first wall (FW) and breeding zone (BZ) cooling systems, which in the water-cooled lithium–lead (WCLL) BB employ pressurized water. Different arrangements of BZ coolant conduits have been investigated in the recent past to identify an efficient layout, which could meet the structural materials’ operational temperature constraint and which could provide the optimal coolant outlet temperature. However, most of the computational fluid dynamic (CFD) analyses that have been carried out until now have been focused on the equatorial WCLL elementary cell of the central outboard segment (COB). The aim of this work is to broaden the analysis to other relevant locations in the blanket. An assessment of the design of the cooling system of the COB bottom-cap elementary BZ cell has been identified as a top design priority due to its different geometry and thermal loads. The cooling efficiency of the BZ and FW systems is investigated to assess if the coolant-appropriate design conditions are matched and the temperature distribution in the cell is analyzed to identify the onset of hot spots. Different layouts of the FW systems are proposed and compared in terms of thermal–hydraulic reliability.
Reflectance Confocal Microscopy in the Diagnosis of Onychomycosis: A Systematic Review
Authors: Lim Sophie Soyeon , Kim Bo Ri , Mun Je-Ho
Published: December 2022

Accurately diagnosing onychomycosis is vital, as therapy is time-consuming and accompanied by multiple adverse effects. Reflectance confocal microscopy (RCM), in contrast to traditional mycological testing, is a noninvasive, point-of-care tool that can rapidly identify fungal lesions. This systematic review aims to understand the utility of RCM in evaluating onychomycosis and follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic search of four databases was conducted. A total of five articles—three prospective cohort studies and two case reports—which reported RCM findings in nails clinically suspicious for onychomycosis were analyzed. Fungal hyphae or spores were visualized on RCM in 67 (81.7%) of the 82 mycologically confirmed cases of onychomycosis. Terms used to describe hyphae included bright, linear, lengthy, thready-like, branching and filamentous. Spores were described as bright, roundish structures with high reflection. The three cohort studies demonstrated RCM had a sensitivity of 52.9–91.7, a specificity of 57.58–90.2%, a positive predictive value of 61.1–88.6% and a negative predictive value of 68.0–90.5%. In conclusion, existing studies demonstrate how RCM can assist the diagnosis of onychomycosis at the bedside. Larger studies incorporating multiple testing modalities to confirm the diagnosis of onychomycosis are warranted to further explore the diagnostic utility of RCM.
The Effect of Human Growth Hormone on Endometrial Growth in Controlled Ovarian Hyperstimulation Cycles
Authors: Bavan Brindha , Gardner Rebecca M. , Zhang Wendy Y. , Aghajanova Lusine
Published: December 2022

This study aims to compare endometrial growth before and after the addition of human growth hormone (hGH) in controlled ovarian hyperstimulation (COH) cycles. A 5-year retrospective cohort study of patients treated with hGH to improve oocyte development during COH cycles was conducted. Each patient’s cycle without hGH immediately preceding cycle(s) with hGH was used for patients to serve as their own controls. Primary outcome was absolute growth in endometrial thickness from pre-stimulation start to day of hCG trigger. Mixed-model regression analysis controlled for patient correlation over repeat cycles and potential confounders. 80 patients were included. Mean age was 39.7 years; mean BMI was 23.8 kg/m2. Majority of patients were nulliparous, non-smoking, and White or Asian. Most common diagnosis was diminished ovarian reserve. Endometrial growth was compared between 159 COH cycles with hGH and 80 COH control cycles; mean increase was 4.5 mm and 3.9 mm, respectively-an unadjusted difference of 0.6 mm (95% CI: 0.2–1.1, p = 0.01). After adjusting for demographic/clinical factors, hGH was associated with 0.9 mm greater endometrial growth (0.4–1.4, p < 0.01). Absolute increase in endometrial thickness was higher in COH cycles that included hGH. Further prospective studies in embryo transfer cycles are needed.
Characteristics of Kidney Recipients of High Kidney Donor Profile Index Kidneys as Identified by Machine Learning Consensus Clustering
Authors: Thongprayoon Charat , Radhakrishnan Yeshwanter , Jadlowiec Caroline C. , Mao Shennen A. , Mao Michael A. , Vaitla Pradeep , Acharya Prakrati C. , Leeaphorn Napat , Kaewput Wisit , Pattharanitima Pattharawin , Tangpanithandee Supawit , Krisanapan Pajaree , Nissaisorakarn Pitchaphon , Cooper Matthew , Cheungpasitporn Wisit
Published: December 2022

Background: Our study aimed to characterize kidney transplant recipients who received high kidney donor profile index (KDPI) kidneys using unsupervised machine learning approach. Methods: We used the OPTN/UNOS database from 2010 to 2019 to perform consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 8935 kidney transplant recipients from deceased donors with KDPI ≥ 85%. We identified each cluster’s key characteristics using the standardized mean difference of >0.3. We compared the posttransplant outcomes among the assigned clusters. Results: Consensus cluster analysis identified 6 clinically distinct clusters of kidney transplant recipients from donors with high KDPI. Cluster 1 was characterized by young, black, hypertensive, non-diabetic patients who were on dialysis for more than 3 years before receiving kidney transplant from black donors; cluster 2 by elderly, white, non-diabetic patients who had preemptive kidney transplant or were on dialysis less than 3 years before receiving kidney transplant from older white donors; cluster 3 by young, non-diabetic, retransplant patients; cluster 4 by young, non-obese, non-diabetic patients who received dual kidney transplant from pediatric, black, non-hypertensive non-ECD deceased donors; cluster 5 by low number of HLA mismatch; cluster 6 by diabetes mellitus. Cluster 4 had the best patient survival, whereas cluster 3 had the worst patient survival. Cluster 2 had the best death-censored graft survival, whereas cluster 4 and cluster 3 had the worst death-censored graft survival at 1 and 5 years, respectively. Cluster 2 and cluster 4 had the best overall graft survival at 1 and 5 years, respectively, whereas cluster 3 had the worst overall graft survival. Conclusions: Unsupervised machine learning approach kidney transplant recipients from donors with high KDPI based on their pattern of clinical characteristics into 6 clinically distinct clusters.
The Dashboard Vitals of Parkinson’s: Not to Be Missed Yet an Unmet Need
Authors: Chaudhuri Kallol Ray , Titova Nataliya , Qamar Mubasher A. , Murășan Iulia , Falup-Pecurariu Cristian
Published: December 2022

The vitals of Parkinson’s disease (PD) address the often-ignored symptoms, which are considered either peripheral to the central core of motor symptoms of PD or secondary symptoms, which, nevertheless, have a key role in the quality of life (QoL) and wellness of people with Parkinson’s (PwP) [...]
Greek Guidelines for the Management of COPD, a Proposal of a Holistic Approach Based on the needs of the Greek Community
Authors: Tzanakis Nikolaos , Kosmas Epameinontas , Papaioannou Andriana I. , Hillas Georgios , Zervas Eleftherios , Loukides Stelios , Bakakos Petros , Katsaounou Paraskevi , Boutou Afroditi , Perlikos Photis , Rovina Nikolleta , Dimakou Katerina , Steiropoulos Paschalis , Stratakos Grigorios , Emmanouil Philipos , Tryfon Stavros , Koulouris Nikolaos
Published: December 2022

Despite that COPD remains one of the most common respiratory diseases worldwide, it can be managed effectively with certain treatments and, more importantly, be prevented by the early implementation of various measures. The pathology and pathophysiology of this disease continue to be studied, with new pharmacological and invasive therapies emerging. In this consensus paper, the Working Group of the Hellenic Thoracic Society aimed to consolidate the up-to-date information and new advances in the treatment of COPD. Local and international data on its prevalence are presented, with revised strategies on the diagnostic approach and the evaluation of risk assessment and disease severity classification. Emphasis is placed on the management and therapy of patients with COPD, covering both common principles, specialized modalities, and algorithms to distinguish between home care and the need for hospitalization. Although pharmacological treatment is commonly recognized in COPD, an integrative approach of pulmonary rehabilitation, physical activity, patient education, and self-assessment should be encountered for a comprehensive treatment, prevention of exacerbations, and increased quality of life in patients.
Time Value of Money Application for the Asymmetric Distribution of Payments and Facts of Economic Life
Authors: Slobodnyak Ilya , Sidorov Anatoly
Published: December 2022

This article is devoted to the applied aspects of using the concept of the time value of money for the purpose of determining the present value of cash flows in conditions of asymmetric distribution of payments and facts of economic life over time. Currently, such situation is standard when doing business and should be thoroughly studied. The purpose of the study is to prove that the method of distribution of payments affects the result of discounting, and that this information is essential when making management decisions and should be disclosed to the user of the information. Based on the basic provisions of the theory of the time value of money and analyzing the specifics of the asymmetric distribution of the described events, the authors come to the conclusion that it is necessary to supplement the cost discounting methodology by including in it a description of the basic approaches to distribution. As such approaches, the use of distribution methods that were called First Payment First Sale (FPFS), First Payment Last Sale (FPLS), and Current Payment Current Sale (CPCS) are proposed. Use of these methods in certain calculations is the main novelty of this article. The difference that arises as a result of the use of different approaches to assessment in the conditions of asymmetric distribution is illustrated with the simulated data. Taking into account a specific approach to the distribution of cash flows leads to a better understanding of the basis for discounting indicators, improves the quality of information and the validity of management decisions based on it, and reduces the risks of choosing the wrong financing strategy.
Big-Data-Based Text Mining and Social Network Analysis of Landscape Response to Future Environmental Change
Authors: Choi Chulmin , Lee Jooho , Machado Jessica , Kim Gunwoo
Published: December 2022

Climate change impacts the urban environment and landscape changes worldwide. To understand how South Korean citizens perceive these changes and what they expect for the future landscape, this study analyzed urban residents’ perceptions through text mining. Data related to the keywords “future landscape”, “future environment”, “well-being”, and “climate change” were collected from July 2020 to July 2021 from the Korean search engines Naver, Daum, and Google using the tool TEXTOM. Keywords, importance, and related words were derived through word frequency, TF-IDF, and N-gram analysis. CONCOR analysis was used to derive the meaning and relevance of the words. In “future landscape”, results showed a high frequency of the words “complex”, “apartment”, “future value”, and “sale”, and the connection strength was higher between “complex”, “landscape”, and “future value”. In “future environment”, “eco-friendly” showed the highest word frequency, and the words “New Deal”, “hydrogen” and “mobility” showed a high frequency and correlation. For “well-being”, “Green Cross” (a well-being-related company) showed the highest frequency, and the connection strength between satisfaction indexes was high. For “climate change”, “response” showed the highest frequency, and the connection strength between “carbon-neutral”, “UN-convention”, and “plan-establishment” was high. These results showed that South Koreans associate landscaping with the value of apartment complexes, that they expect solutions to mitigate climate change impacts with green and eco-friendly strategies, and lastly that well-being-related companies are receiving a great deal of public attention. Thus, it is expected that the results will help plan effective landscaping approaches to respond to environmental changes.
Land Evaluation for Acacia (Acacia mangium × Acacia auriculiformis) Plantations in the Mountainous Regions of Central Vietnam
Authors: Pham Tung Gia , Tran Chau Thi Minh , Nguyen Hai Thi , Trinh Ha Ngan , Nguyen Ngoc Bich , Nguyen Ha Khoa Ngoc , Tran Tan Trong , Le Huy Dinh , Le Quy Ngoc Phuong
Published: December 2022

In recent years, both scientists and local governments have been giving serious attention to land evaluation, especially in regard to the use of agricultural land. This is with the intention of increasing the sustainability of agricultural production. In Vietnam, acacia plantations play an important role in the livelihoods of farmers in mountainous regions. Therefore, identifying suitable areas for acacia plantations is an important consideration within mountainous areas. This research was conducted in Nam Dong district, Central Vietnam, using six physical soil criteria for land evaluation by the Analytic Hierarchy Process (AHP) and also the Fuzzy Analytic Hierarchy Process (FAHP). The results have shown that the ranking of selected criteria in both methods was the same, but the weighting of each criterion was different. Among the six physical soil criteria, soil depth has the highest priority, followed by slope, soil organic carbon content, soil texture, soil pH, and soil type. The suitability maps for acacia plantations within the area studied have shown that 9344 ha were not suitable, and 99 ha had low suitability for acacia plantation by both methods. For the AHP approach, 928 hectares were in the range of moderate suitability, and 3080 hectares were in the high suitability class. In contrast, the FAHP method determined 905 hectares to be of the moderate suitability class and 3102 hectares to be of the high suitability class. Based on the observed acacia’s productivity and the scores of the two methods, it shows that the FAHP has a stronger correlation than the of AHP. Within the six selected criteria, the FAHP method can increase the accuracy of land evaluation results by 4.62% in comparison to the original AHP method. Therefore, the FAHP is the most suitable method for land evaluation, especially for agricultural land planning. Further studies should be integrated into more social and economic criteria for comprehensive land evaluation scenarios.
Self-Induced Myofascial Release in Patients with Hemophilic Ankle Arthropathy: A Pilot Observational Study
Authors: Donoso-Úbeda Elena , Pérez-Llanes Raúl , Meroño-Gallut Javier , Ucero-Lozano Roberto , Cuesta-Barriuso Rubén
Published: December 2022

Background: Hemophilic ankle arthropathy is manifested by degenerative functional alterations (reduced muscle strength, mobility, and proprioception) and chronic pain. Myofascial release techniques are used to treat soft tissue adhesions, relieve pain, and reduce tissue sensitivity. The aim was to evaluate the safety of self-induced myofascial release in patients with hemophilic ankle arthropathy and to assess possible changes in musculoskeletal variables. Methods: We recruited 20 patients with ankle hemophilic arthropathy. Patients carried out a daily self-induced myofascial release exercise program using a foam roller over a period of 8 weeks. The primary variable was the frequency of hemarthrosis (regular telephone follow-up). Secondary variables were pain intensity (visual analog scale), range of motion (goniometry), and functional capacity of the lower limbs (six-minute walk test). Three evaluations were performed: pre-treatment (T0), post-treatment (T1), and at 8 weeks follow-up (T2). Results: There was a lower, non-significant, association in the frequency of hemarthrosis between the experimental and follow-up periods, compared to the pre-study period (SE = 0.50; 95%CI: −1.67; 0.28). There were significant within-subject changes in intensity of pain (T0: 4.91; T1: 2.79; T2: 2.46; p < 0.001), plantar flexion (T0: 125.55; T1: 131.5; T2: 130.30; p = 0.01), and functionality of the lower limbs (T0: 173.06; T1: 184.85; T2: 178.39; p = 0.009). Conclusions: Self-induced myofascial release is safe in patients with hemophilic ankle arthropathy. A protocol based on self-induced myofascial release can lead to changes in pain intensity, range of ankle motion in plantar flexion, and functionality in hemophilic patients.
Synthesis and Electrochemical Performance of V6O13 Nanosheets Film Cathodes for LIBs
Authors: Li Fei , Xu Haiyan , Liu Fanglin , Li Dongcai , Wang Aiguo , Sun Daosheng
Published: December 2022

V6O13 thin films were deposited on indium-doped tin oxide (ITO) conductive glass by a concise low-temperature liquid-phase deposition method and through heat treatment. The obtained films were directly used as electrodes without adding any other media. The results indicate that the film annealed at 400 °C exhibited an excellent cycling performance, which remained at 82.7% of capacity after 100 cycles. The film annealed at 400 °C with diffusion coefficients of 6.08 × 10−12 cm2·s−1 (Li+ insertion) and 5.46 × 10−12 cm2·s−1 (Li+ extraction) in the V6O13 film electrode. The high diffusion coefficients could be ascribed to the porous morphology composed of ultrathin nanosheets. Moreover, the film endured phase transitions during electrochemical cycling, the V6O13 partially transformed to Li0.6V1.67O3.67, Li3VO4, and VO2 with the insertion of Li+ into the lattice, and Li0.6V1.67O3.67, Li3VO4, and VO2 partially reversibly transformed backwards to V6O13 with the extraction of Li+ from the lattice. The phase transition can be attributed to the unique structure and morphology with enough active sites and ions diffusion channels during cycles. Such findings reveal a bright idea to prepare high-performance cathode materials for LIBs.
Nanomaterials as a Sustainable Choice for Treating Wastewater: A Review
Authors: Mbarek Wael Ben , Escoda Lluisa , Saurina Joan , Pineda Eloi , Alminderej Fahad M. , Khitouni Mohamed , Suñol Joan-Josep
Published: December 2022

The removal of dyes from textile effluents utilizing advanced wastewater treatment methods with high efficiency and low cost has received substantial attention due to the rise in pollutants in water. The purpose of this work is to give a comprehensive analysis of the different treatments for removing chemical dyes from textile effluents. The capability and potential of conventional treatments for the degradation of dyeing compounds in aqueous media, as well as the influence of multiple parameters, such as the pH solution, initial dye concentration, and adsorbent dose, are presented in this study. This study is an overview of the scientific research literature on this topic, including nanoreductive and nanophotocatalyst processes, as well as nanoadsorbents and nanomembranes. For the purpose of treating sewage, the special properties of nanoparticles are currently being carefully researched. The ability of nanomaterials to remove organic matter, fungus, and viruses from wastewater is another benefit. Nanomaterials are employed in advanced oxidation techniques to clean wastewater. Additionally, because of their small dimensions, nanoparticles have a wide effective area of contact. Due to this, nanoparticles’ adsorption and reactivity are powerful. The improvement of nanomaterial technology will be beneficial for the treatment of wastewater. This report also offers a thorough review of the distinctive properties of nanomaterials used in wastewater treatment, as well as their appropriate application and future possibilities. Since only a few types of nanomaterials have been produced, it is also important to focus on their technological feasibility in addition to their economic feasibility. According to this study, nanoparticles (NPs) have a significant adsorption area, efficient chemical reactions, and electrical conductivity that help treat wastewater effectively.
Micromechanics Modeling of Transverse Tensile Strength for Unidirectional CFRP Composite
Authors: Liu Liangbao , Zhang Xiaohui , Wang Zibiao , Wang Yana , Guo Jiangzhen
Published: December 2022

Transverse tensile strength of unidirectional (UD) composites plays a key role in overall failure of fiber-reinforced composites. To predict this strength by micromechanics, calculation of actual stress in constituent matrix is essentially required. However, traditional micromechanics models can only give the volume-averaged homogenized stress rather than an actual one for a matrix, which in practice will cause large errors. In this paper, considering the effect of stress concentration on a matrix, a novel micromechanics method was proposed to give an accurate calculation of the actual stress in the matrix for UD composite under transverse tension. A stress concentration factor for a matrix in transverse tensile direction is defined, using line-averaged pointwise stress (obtained from concentric cylinder assemblage model) divided by the homogenized quantity (obtained from a bridging model). The actual stress in matrix is then determined using applied external stress multiplied by the factor. Experimental validation on six UD carbon fiber-reinforced polymer (CFRP) specimens indicates that the predicted transverse tensile strength by the proposed method presents a minor deviation with an averaged relative error of 5.45% and thus is reasonable, contrary to the traditional method with an averaged relative error of 207.27%. Furthermore, the morphology of fracture section of the specimens was studied by scanning electron microscopy (SEM). It was observed that different scaled cracks appeared within the matrix, indicating that failure of a UD composite under transverse tension is mainly governed by matrix failure. Based on the proposed approach, the transverse tensile strength of a UD composite can be accurately predicted.
Numerical Simulations Based on a Meshfree Method for Nickel-Steel Welded Joint Manufactured by Micro-Jet Cooling
Authors: Uściłowska Anita , Szczucka-Lasota Bożena , Węgrzyn Tomasz , Szymczak Tadeusz , Łazarz Bogusław , Kamińska Joanna
Published: December 2022

The article presents a numerical–experimental approach to the weldability and mechanical resistance of the joint of Alloy 59 (2.4605, nickel-chromium-molybdenum) and S355J2W (1.8965) structural steel manufactured by the MIG process with the use of micro-jet cooling. This research was considered because the standard MIG process does not guarantee the procurement of a mixed hard-rusting structural steel superalloy weld of a repeatable and acceptable quality. Welds made through the classic MIG process express cracks that result from their unfavorable metallographic microstructure, while the joint supported by micro-jet cooling does not reflect any cracks and has a high strength with good flexibility. This was achieved by the application of helium for cooling. The joining technology was also considered in the numerical stage, represented by calculations in situ. For this purpose, the fundamental solution method (FSM) for the simulation of heat transfer during the process of welding with micro-jet cooling was implemented according to the initial boundary value problem (IBVP). The problem was solved employing the method of combining the finite difference method, Picard iterations, approximation by the radial basis function, and the fundamental solution method so as to solve the IVBP. The proposed method was validated by the data and results obtained during in situ experiments. The numerical approach enabled us to obtain variations in the temperature distribution values in HAZ with its different dimensional variants, ranging between 600 °C and 1400 °C.
Improvement of Mixed-Mode I/II Fracture Toughness Modeling Prediction Performance by Using a Multi-Fidelity Surrogate Model Based on Fracture Criteria
Authors: Wiangkham Attasit , Aengchuan Prasert , Kasemsri Rattanaporn , Pichitkul Auraluck , Tantrairatn Suradet , Ariyarit Atthaphon
Published: December 2022

Today, artificial intelligence plays a huge role in the mechanical engineering field for solving many complex problems and the problem with fracture mechanics is one of them. In fracture mechanics, artificial intelligence is used to predict crack behavior under various conditions such as mixed-mode loading. Many parameters are used for explaining the crack behavior under various conditions, but those parameters are obtained from destructive testing, in which usually, only one data point is obtained from each test. An artificial problem method requires a large amount of data to train the model to be able to learn crack behavior, which is a disadvantage of applying this method to fracture mechanics. To eliminate the disadvantage of the large amount of experiment data required for modeling, in this study, the small data obtained from the experiment along with data obtained from fracture criteria that were used for elementary prediction of mixed mode fracture toughness were used to create an artificial intelligence model. Data from the experiment was combined with fracture criteria data using the multi-fidelity surrogate model that is described in this study. The mixed mode I/II fracture toughness of the PMMA material was tested in order to primarily propose the data combination technique. After the modeling process, the prediction results indicated that the performance of a model in which the actual test data was combined with the data from the fracture criteria (multi-fidelity surrogate model) was more predictively effective compared to only actual data-based modeling.
The Construction of a Footbridge Prototype with Biological Self-Healing Concrete: A Field Study in a Humid Continental Climate Region
Authors: Jakubovskis Ronaldas , Boris Renata
Published: December 2022

Biological self-healing concrete (BSHC) offers a sustainable and economical way of increasing the lifespan of structures vulnerable to cracking. In recent decades, an enormous research effort has been dedicated to developing and optimizing the bacterial healing process. Nevertheless, most studies have been carried out under laboratory conditions. To verify the effectiveness and longevity of the embedded healing systems under normal service conditions, field studies on BSHC structures must be performed. In the present study, BSHC beams were designed as a structural part of a prototype footbridge. To select the optimal BSHC mix composition, a series of laboratory tests were also carried out. Laboratory tests have shown that the healing ratio in BSHC elements under rain-simulating healing conditions was several times higher in comparison to control specimens. Based on the laboratory results, the BSHC mix composition was selected and applied for structural bridge beams. To the best of the authors’ knowledge, the present study reports the first application of BSHC in a prototype footbridge. The long-term data gathered on the healing process in a humid continental climate zone will allow the benefits of biological self-healing to be quantitatively evaluated and will pave the way for the further optimization of this material.
A Review of the Influence of Copper Slag on the Properties of Cement-Based Materials
Authors: Jin Qiliang , Chen Lihua
Published: December 2022

Global copper slag (CS) emissions reached 57.2 million tons in 2021. Despite the increasing reuse of CS, the treatment of CS is still dominated by landfill so far, which not only occupies land resources but also causes damage to the environment. The application of CS to cement-based materials (CBMs) is one of the main approaches to its comprehensive utilization and has important economic and social implications. This article reviews the physicochemical properties, activity excitation, and heavy metal leaching properties of CS and summarizes the effect of CS on the working properties, mechanical properties, and durability of CBMs. At the end of the article, the existing problems in the research are analyzed, and the development trend is proposed, which provides technical guidance and reference for further research and application of CS in CBMs in the future.
Optimization of Cab Vibration Comfort for Construction Machinery Based on Multi-Target Regression Forests
Authors: Zhuang Chao , Wen Hansheng , Ni Xiangyu , Zhang Da , Bao Yangyang , Huang Haibo
Published: December 2022

With the increasing awareness of the importance of environmental protection and the fierce competition in the construction machinery market, improving the vibration comfort of a whole construction machine has become a new focus of competition; therefore, optimizing the performance of cab mounts has become an urgent problem to be solved. At present, the problems of low modeling efficiency, serious technical difficulties, and long development cycles exist in the design and optimization of cab mounts. In this paper, a multi-target regression forests method is introduced into the design and optimization of the construction machinery installation system, which circumvents the traditional complex modeling process and establishes a mapping relationship between cab assembly parameters and the mounts’ stiffness, as well as introduces the system decoupling rate and vibration isolation rate as the boundary conditions. Furthermore, the MRFs method is compared and evaluated with MLRP and Multi-SVR prediction results. Finally, a complete, accurate, and efficient design method for the cab mount system optimization is developed, improving the decoupling rate and vibration isolation rate of the cab system. This design method can predict the stiffness of the mounts in multiple directions.
Design and Manufacture of Similar Model of Folding Wings and Study on Dynamic Characteristics
Authors: Lu Xinqiang , Yang Rui , Qian Wei , Sun Shiyong
Published: December 2022

The research on full-size folding wings is limited by many factors, and the similar model has an irreplaceable role in its development and manufacturing process. In this study, a folding wing with core board and dimensional structure is designed and manufactured based on the principle of functional similarity and structural similarity, and the similar model can accomplish continuous folding from 0° to 90°. Based on the designed model, the finite element model simulation calculation and ground knocking modal test are completed, and the correction of the finite element model (FEM) is completed by comparing the test and simulation data. Finally, the full-component finite element model with small vibration frequency error and high matching of vibration MAC value is obtained and compared with the manufactured model. Since the gradient analysis of the full-component finite element model is extremely inefficient, a fast method of building the finite element model is proposed based on the simplified finite element model as a case study, which not only improves the efficiency of the FEM modeling and simulation analysis without changing the model structure and function, but also provides a good agreement of the vibration mode compared with the test data. In addition, the influence of the geometric parameters of the spring plate on the vibration mode of the finite element model is explored based on the simplified model to meet the demand for modal control of the similar model.
Dynamic Modeling and Vibration Characteristics Analysis of a Large-Scale Photoelectric Theodolite Tracking Frame
Authors: Liu Ruiqi , Zhang Han , Wang Xiaoming , Gao Qingjia , Liu Zhenyu , Yu Yi , Wang Qianglong
Published: December 2022

In this paper, the experimental modes of a large-scale photoelectric theodolite tracking frame are presented. On the basis of the experimental data and the gradient-less optimization approach, the modeling strategy and the parameterized equivalent dynamic finite element model are presented. Shafting, three-point leveling units, and other components are reasonably simplified during the modeling process. Influence factors such as contact stiffness are introduced as dynamic parameters in the model. The optimized parametric model obtained demonstrates that the linearization modeling strategy represents the dynamic response characteristics of this type of structure accurately. The maximum relative error of the first four-order natural frequencies between numerical simulation and experimental data is 4.45% when the consistency of mode shapes is taken into account. The research results in this paper can provide engineering guidance for the dynamic stiffness optimization design of the large-scale photoelectric theodolite tracking frame.
Prediction of the Roughness Reduction in Centrifugal Disc Finishing of Additive Manufactured Parts Based on Discrete Element Method
Authors: Kopp Marco , Uhlmann Eckart
Published: December 2022

One major drawback of additive manufacturing is the poor surface quality of parts, which negatively affects mechanical and tribological properties. Therefore, a surface finishing is necessary in most cases. Due to a high material removal rate, centrifugal disc finishing is a promising mass finishing operation for an effective surface finishing of additive manufactured parts. However, due to machining the workpieces in a freely movable manner, the process is hardly controllable, and the process design is often based on time-consuming and cost-intensive trial-and-error approaches. Especially when it comes to the machining of complex-shaped workpieces, finishing results are barely predictable. Therefore, the aim of this study is to set up a numerical simulation of the centrifugal disc finishing based on the Discrete Element Method (DEM) to predict finishing results. A procedure to determine the required DEM input parameters is presented and the simulation was validated using a freely movable force sensor. The results of the finishing experiments with additive manufactured workpieces made of Ti-6Al-4V were correlated with the simulated results. The derived correlation was used to predict local differences in the roughness reduction, which occurred when finishing workpieces with a limited accessibility to the surface. As a result, it is concluded that the complex relationship between the type of media, the accessibility to the surface, and the achievable finishing results can be modeled using the DEM.
Unilateral Laplace Transforms on Time Scales
Authors: Şan Müfit , Ortigueira Manuel D.
Published: December 2022

We review the direct and inverse Laplace transforms on non-uniform time scales. We introduce full backward-compatible unilateral Laplace transforms and studied their properties. We also present the corresponding inverse integrals and some examples.
An Algebraic Model for Quantum Unstable States
Authors: Fortin Sebastian , Gadella Manuel , Holik Federico , Jorge Juan Pablo , Losada Marcelo
Published: December 2022

In this review, we present a rigorous construction of an algebraic method for quantum unstable states, also called Gamow states. A traditional picture associates these states to vectors states called Gamow vectors. However, this has some difficulties. In particular, there is no consistent definition of mean values of observables on Gamow vectors. In this work, we present Gamow states as functionals on algebras in a consistent way. We show that Gamow states are not pure states, in spite of their representation as Gamow vectors. We propose a possible way out to the construction of averages of observables on Gamow states. The formalism is intended to be presented with sufficient mathematical rigor.
Feature Selection for High Dimensional Datasets Based on Quantum-Based Dwarf Mongoose Optimization
Authors: Elaziz Mohamed , Ewees Ahmed , Al-qaness Mohammed , Alshathri Samah , Ibrahim Rehab
Published: December 2022

Feature selection (FS) methods play essential roles in different machine learning applications. Several FS methods have been developed; however, those FS methods that depend on metaheuristic (MH) algorithms showed impressive performance in various domains. Thus, in this paper, based on the recent advances in MH algorithms, we introduce a new FS technique to modify the performance of the Dwarf Mongoose Optimization (DMO) Algorithm using quantum-based optimization (QBO). The main idea is to utilize QBO as a local search of the traditional DMO to avoid its search limitations. So, the developed method, named DMOAQ, benefits from the advantages of the DMO and QBO. It is tested with well-known benchmark and high-dimensional datasets, with comprehensive comparisons to several optimization methods, including the original DMO. The evaluation outcomes verify that the DMOAQ has significantly enhanced the search capability of the traditional DMO and outperformed other compared methods in the evaluation experiments.
An Ensemble Classification Method for Brain Tumor Images Using Small Training Data
Authors: Nguyen Dat Tien , Nam Se Hyun , Batchuluun Ganbayar , Owais Muhammad , Park Kang Ryoung
Published: December 2022

Computer-aided diagnosis (CAD) systems have been used to assist doctors (radiologists) in diagnosing many types of diseases, such as thyroid, brain, breast, and lung cancers. Previous studies have successfully built CAD systems using large, annotated datasets to train their models. The use of a large volume of training data helps these CAD systems to collect rich information for application in the diagnosis process. However, a large amount of training data is sometimes unavailable for training the models, such as for a new or less common disease and diseases that require expensive image acquisition devices. In such cases, conventional CAD systems are unable to learn their models efficiently. As a result, diagnostic performance is reduced. In this study, we focus on dealing with this problem; thus, our classification method can enhance the performance of conventional CAD systems based on the ensemble model of a support vector machine (SVM), multilayer perceptron (MLP), and few-shot (FS) learning network when working with small training datasets of brain tumor images. Through experiments, we confirmed that our proposed method outperforms conventional deep learning-based CAD systems when working with a small training dataset. In detail, we verified that the lack of training data led to the reduction of classification performance. In addition, we enhanced the classification accuracy from 3% to 10% compared to previous studies that used the SVM-based classification method or fine-tuning of a convolutional neural network (CNN) using two public datasets.