bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding Challenges of Genetic Testing on Neuromuscular Disorders from the Parental Lens
Authors: Hakim Zada Farheen , Ahmad Azahari Ahmad , Wong Sau , Ali Adli , Ismail Noor
Published: November 2023

Neuromuscular disorders, characterized by progressive muscle degeneration and weakness, present substantial challenges to both affected individuals and their families. Genetic testing assumes a pivotal role in facilitating early diagnosis, intervention, treatment, and informed family planning for these conditions. The objective of this qualitative study is to delve into the knowledge, awareness, and perceptions surrounding genetic testing within the cohort of parents caring for individuals with neuromuscular disorders in Malaysia. A semi-structured interview approach was employed to elicit data from parents of individuals diagnosed with neuromuscular disorders, encompassing those with clinical diagnoses and those diagnosed through genetic testing. Examination of the interview responses yielded nine overarching themes, which furnish invaluable insights into the perspectives of Malaysian parents concerning genetic testing. The study discerned several challenges associated with genetic testing, notably encompassing the limited awareness among parents, the financial constraints associated with genetic testing, and the perceived significance of genetic testing in the context of neuromuscular disorders. The findings suggest that the level of knowledge and awareness pertaining to genetic testing for neuromuscular disorders among parents in Malaysia varies, with initial levels of awareness ranging from relatively low to reasonably sufficient prior to and following the birth of an affected child. However, the investigation revealed that parents tended to cultivate more favorable perceptions regarding genetic testing subsequent to their experience with genetic counseling. This underscores the potential for heightened awareness and comprehension as a consequence of the personal experience of parenting an affected child confirmed through genetic testing and genetic counseling, ultimately influencing parental awareness.
Electric Vehicles Energy Management for Vehicle-to-Grid 6G-Based Smart Grid Networks
Authors: Naja Rola , Soni Aakash , Carletti Circe
Published: November 2023

This research proposes a unique platform for energy management optimization in smart grids, based on 6G technologies. The proposed platform, applied on a virtual power plant, includes algorithms that take into account different profiles of loads and fairly schedules energy according to loads priorities and compensates for the intermittent nature of renewable energy sources. Moreover, we develop a bidirectional energy transition mechanism towards a fleet of intelligent vehicles by adopting vehicle-to-grid technology and peak clipping. Performance analysis shows that the proposed energy provides fairness to electrical vehicles, satisfies urgent loads, and optimizes smart grids energy.
The Iconic Philippine Coral Reef at Steinhart Aquarium: The Husbandry, Welfare, Behavior, and Veterinary Care Considerations of a Large Multi-Taxa Living Coral Reef System
Authors: Krol Lana , Melton Brenda , Delbeek J. Charles , Dunker Freeland H. , Shepherd Bart
Published: November 2023

In 2008, Steinhart Aquarium at the California Academy of Sciences in San Francisco, CA, USA, unveiled a brand new facility with the 212,000 gallon Philippine Coral Reef habitat as its iconic centerpiece. Designing and managing a system that consists of a living reef this large, with associated invertebrates and teleosts, has been a challenge for the aquarium’s husbandry and veterinary teams. Establishing appropriate lighting, water quality, and flow has required a scientific approach and resulting adjustments to the original habitat design. The medical management of reef species has required an in-habitat approach as well as trial-and-error therapeutics. Determining the criteria for assessing the welfare of corals and other tank inhabitants has been a shifting process that has heavily utilized photography-tracked changes and other quantitative parameters as baselines. This report details the successes and limitations of establishing the environmental and veterinary management of this mesocosm. The consideration of interplay between species is discussed, and recommendations for monitoring welfare both on an individual and tank level are made. Making adjustments for the benefit of the exhibit and its animals is key for the unique aquarium displays that comprise captive coral reef systems.
Changes and Transformations on the Coast Using the Example of Roses (Alt Empordà, Catalonia)
Authors: Bouzas Sabater Marc , Burch i Rius Josep , Julià Brugués Ramon , Palahí Grimal Lluís , Pons Mir Pere , Solà Subiranas Joan
Published: November 2023

This article aims to show the transformation of the coast in the extreme northeast of the Iberian Peninsula. It is focused on the Ciutadella de Roses. Data were integrated from the digital elevation model (LIDAR), a geomorphological analysis, and lithostratigraphic and chronological correlations based on eight geological boreholes and twelve radiocarbon datings, along with historical data and archaeological remains found in the surroundings of the Ciutadella. This enabled a hypothesis to be established on the palaeolandscape around the site. The evolution of the shoreline from Ancient Greek times to the modern period is detailed, and evidence of its form at different chronological moments is presented. To sum up, the article defines the evolution of the palaeolandscape in the territory and links it to the historical evolution of the site. In addition, the evolution of the relationship between river courses, the sea and the sea level is explained.
A Corpus Analysis of the Effects of Definiteness and Animacy on Word Order Variation
Authors: Asadpour Hiwa
Published: November 2023

This article deals with the analysis of word order variation regarding subjects, direct objects, and non-direct object phrases called the “Target” in the corpus of languages of northwestern Iran, viz., Armenian, Mukri Kurdish, and Northeastern Kurdish (Indo-European), Jewish Northeastern Neo-Aramaic (Semitic), and Azeri Turkic (Turkic). The objective is to examine the effects of formal and semantic (in)definiteness in combination with animacy on Target word order variation to find out which one can be a triggering factor.
Lubrication Performance of Misaligned Journal Bearings with Flexible Structure under Shock Load Conditions
Authors: Hong Sung-Ho , Jeon Woo-Ju
Published: November 2023

Bearings might be damaged due to shock loads caused by disturbances, in addition to static loads. In this study, a flexible structure was applied to enhance the lubrication characteristics of misaligned journal bearings subjected to impact loads. When an impact load is added to the bearing, a misaligned journal bearing has a high possibility of metal-to-metal contact. It might also lead to failure. Misalignment can occur at any time during bearing operation. A flexible structure is applied to the end of the bearing as a way to improve lubrication performance in a system where impact loads might be applied. The bearing’s lubrication performance was numerically assessed under unsteady-state conditions. An elastohydrodynamic lubrication analysis was conducted, taking into account elastic deformation. The lubrication characteristics of misaligned journal bearings were compared with the dimensionless minimum film thickness. The flexible structure and elastic modulus of the bearing were investigated so that it could support the load without contact according to the change in the maximum magnitude of the impact load. When subjected to oil film pressure, this flexible structure underwent elastic deformation, resulting in enlargement of the oil film. A misaligned journal bearing with a suitable flexible structure provided stable lubrication without metal-to-metal contact, even under shock load conditions. The flexible structure was incorporated into the high-load-bearing region of the journal bearing as a groove. Therefore, the application of a flexible structure in misaligned journal bearings can effectively enhance lubrication performance in misaligned conditions and under shock loads.
Mean-Value-at-Risk Portfolio Optimization Based on Risk Tolerance Preferences and Asymmetric Volatility
Authors: Hidayat Yuyun , Purwandari Titi , Sukono  , Prihanto Igif Gimin , Hidayana Rizki Apriva , Ibrahim Riza Andrian
Published: November 2023

Investors generally aim to obtain a high return from their stock portfolio. However, investors must realize that a high value-at-risk (VaR) is essential to calculate for this aim. One of the objects in the VaR calculation is the asymmetric return volatility of stocks, which causes an unbalanced decrease and increase in returns. Therefore, this study proposes a mean-value-at-risk (mean-VaR) stock portfolio optimization model based on stocks’ asymmetric return volatility and investors’ risk aversion preferences. The first stage is the determination of the mean of all stocks in the portfolio conducted using the autoregressive moving average Glosten–Jagannathan–Runkle generalized autoregressive conditional heteroscedasticity (ARMA-GJR-GARCH) models. Then, the second stage is weighting the capital of each stock based on the mean-VaR model with the investors’ risk aversion preferences. This is conducted using the Lagrange multiplier method. Then, the model is applied to stock data in Indonesia’s capital market. This application also analyzed the sensitivity between the mean, VaR, both ratios, and risk aversion. This research can be used for investors in the design and weighting of capital in a stock portfolio to ensure its asymmetrical effect is as small as possible.
An Exploration of Prediction Performance Based on Projection Pursuit Regression in Conjunction with Data Envelopment Analysis: A Comparison with Artificial Neural Networks and Support Vector Regression
Authors: Yu Xiaohong , Lou Wengao
Published: November 2023

Data envelopment analysis (DEA) is a leading approach in performance analysis and discovering newer benchmarks, and the traditional DEA models cannot forecast the future efficiency of decision-making units (DMUs). Machine learning, such as the artificial neural networks (ANNs), support vector machine/regression (SVM/SVR), projection pursuit regression (PPR), etc., have been viewed as beneficial for managers in predicting system behaviors. PPR is especially suitable for small and non-normal distribution samples, the usual cases in DEA analysis. This paper integrates DEA and PPR to cover the shortcomings we faced while using DEA and DEA-BPNN, DEA-SVR, etc. This study explores the advantages of combining these complementary methods into an integrated performance measurement and prediction model. Firstly, the DEA approach is used to evaluate and rank the efficiency of DMUs. Secondly, we establish two DEA-PPR combined models to describe the DEA efficiency scores (also called the production function) and the DEA-efficient frontier function. The first combined model’s input variables are input–output indicators in the DEA model, and the output variable is the DEA efficiency. In the second model, its input variables are input or output indicators in the DEA model, and the output variable is the optimal input indicator for input-oriented DEA or the output indicator for output-oriented DEA. We conducted positive research on two examples with actual data and virtual small, medium-sized, and large samples. Compared with the DEA-BPNN and DEA-SVR models, the results show that the DEA-PPR combined model has more vital global optimization ability, better convergence, higher accuracy, and a simple topology. The DEA-PPR model can obtain robust results for both small and large cases. The DEA-BPNN and DEA-SVR models cannot obtain robust results for small and medium-sized samples due to overfitting. For large samples, the DEA-PPR model outperforms DEA-BPNN, DEA-SVR, etc. The DEA-PPR combined model possesses better suitability, applicability, and reliability than the DEA-BPNN model, the DEA-SVR model, etc.
A Deep Learning Neural Network Method Using Linear Eigenvalue Statistics for Schizophrenic EEG Data Classification
Authors: Liu Haichun , Li Lanzhen , Ye Yumeng , Pan Changchun , Yang Genke , Chen Tao , Zhang Tianhong , Wang Jijun , Qiu Caiming (Robert)
Published: November 2023

Electroencephalography (EEG) signals can be used as a neuroimaging indicator to analyze brain-related diseases and mental states, such as schizophrenia, which is a common and serious mental disorder. However, the main limiting factor of using EEG data to support clinical schizophrenia diagnosis lies in the inadequacy of both objective characteristics and effective data analysis techniques. Random matrix theory (RMT) and its linear eigenvalue statistics (LES) can provide an effective mathematical modeling method for exploring the statistical properties of non-stationary nonlinear systems, such as EEG signals. To obtain an accurate classification and diagnosis of schizophrenia, this paper proposes a LES-based deep learning network scheme in which a series of random matrixes, consisting of EEG data sliding window sampling and their eigenvalues, are employed as features for deep learning. Due to the fact that the performance of the LES-based scheme is sensitive to the LES’s test function, the proposed LES-based deep learning network is embedded with two ways of combining LES’s test functions with learning techniques: the first is to have the LES’s test function assigned, while, using the second way, the optimal LES’s test function should be solved in a functional optimization problem. In this paper, various test functions and different optimal learning methods were coupled in experiments. Our results revealed a binary classification accuracy of nearly 90% in distinguishing between healthy controls (HC) and patients experiencing the first episode of schizophrenia (FES). Additionally, we achieved a ternary classification accuracy of approximately 70% by including clinical high risk for psychosis (CHR). The LES-embedded approach yielded notably higher classification accuracy compared to conventional machine learning methods and standard convolutional neural networks. As the performance of schizophrenia classification is strongly influenced by test functions, a functional optimization problem was proposed to identify an optimized test function, and an approximated parameter optimization problem was introduced to limit the search area of suitable basis functions. Furthermore, the parameterization test function optimization problem and the deep learning network were coupled to be synchronously optimized during the training process. The proposal approach achieved higher classification accuracy rates of 96.87% between HC and FES, with an additional 89.06% accuracy when CHR was included. The experimental studies demonstrated that the proposed LES-based method was significantly effective for schizophrenic EEG data classification.
Healthcare Cost Prediction Based on Hybrid Machine Learning Algorithms
Authors: Zou Shujie , Chu Chiawei , Shen Ning , Ren Jia
Published: November 2023

Healthcare cost is an issue of concern right now. While many complex machine learning algorithms have been proposed to analyze healthcare cost and address the shortcomings of linear regression and reliance on expert analyses, these algorithms do not take into account whether each characteristic variable contained in the healthcare data has a positive effect on predicting healthcare cost. This paper uses hybrid machine learning algorithms to predict healthcare cost. First, network structure learning algorithms (a score-based algorithm, constraint-based algorithm, and hybrid algorithm) for a Conditional Gaussian Bayesian Network (CGBN) are used to learn the isolated characteristic variables in healthcare data without changing the data properties (i.e., discrete or continuous). Then, the isolated characteristic variables are removed from the original data and the remaining data used to train regression algorithms. Two public healthcare datasets are used to test the performance of the proposed hybrid machine learning algorithm model. Experiments show that when compared to popular single machine learning algorithms (Long Short Term Memory, Random Forest, etc.) the proposed scheme can obtain similar or higher prediction accuracy with a reduced amount of data.
Robust Optimization for the Two-Dimensional Strip-Packing Problem with Variable-Sized Bins
Authors: Liu Kaiyuan , Zhang Hongyu , Wang Chong , Li Hui , Chen Yongquan , Chen Qiong
Published: November 2023

The two-dimensional strip-packing problem (2D-SPP) emerges as a notable variant of the cutting and packing (C&P) problem, aiming to optimize the arrangement of small rectangular items within unique strips with a fixed width and infinite height to minimize the usage of height. Despite extensive academic exploration, applying 2D-SPP solutions in industrial settings remains challenging. Two significant issues, often overlooked in academia yet frequently encountered in industrial contexts, are the uncertain demand for items, exacerbated by the bullwhip effect, and the need for diverse types of strips to cater to varying customer needs. Our paper addresses this academia–industry gap by proposing a robust optimization model for the uncertain 2D-SPP with variable-sized bins, aiming to manage the demand fluctuations within a box uncertainty set framework. Additionally, we employ the contiguous one-dimensional relaxation technique in conjunction with column generation to tighten the lower bound of the problem, thereby augmenting solution accuracy. Furthermore, we leverage the Karush–Kuhn–Tucker (KKT) condition to transform the model into a more tractable form, subsequently leading to an exact solution. Based on datasets from a real-life plastic-cutting company, comprehensive experiments validate the effectiveness and efficiency of our proposed relaxation method and algorithm, showcasing the potential for an improved industrial application of 2D-SPP solutions.
Unveiling Deep Learning Insights: A Specialized Analysis of Sucker Rod Pump Dynamographs, Emphasizing Visualizations and Human Insight
Authors: Martinović Bojan , Bijanić Milos , Danilović Dusan , Petrović Andrija , Delibasić Boris
Published: November 2023

This study delves into the heightened efficiency and accuracy of 11 deep learning models classifying 11 dynamograph classes in the oil production sector. Introducing a novel framework with the Grad–CAM method, we address the “black box” issue, providing transparency in the models’ decision-making processes. Our analysis includes a comparative study with human experts, revealing a comprehensive understanding of both machine and human interpretive strategies. Results highlight the notable speed and precision of machine learning models, marking a significant advancement in rapid, reliable dynamograph classification for oil production decision-making. Additionally, nuanced findings in the model’s diagnostic accuracy reveal limitations in situations featuring the simultaneous occurrence of multiple pump issues. This underscores the need for additional features and domain-specific logic to enhance discernment and diagnostic precision in complex scenarios. The exploration of qualitative aspects distinguishes interpretive approaches, highlighting strengths and limitations. Machines, driven by algorithmic patterns and data processing, excel in rapid identification, albeit with occasional misclassifications. In contrast, human experts leverage experience and domain-specific knowledge for nuanced interpretation, providing a comprehensive understanding of both quantitative metrics and qualitative nuances. In conclusion, this study not only demonstrates the accelerated and enhanced accuracy of dynamograph classification by machine learning models compared to junior and medior domain experts, but also provides valuable insights into specific features and patterns guiding the decision-making process. This understanding allows continuous refinement, combining machine speed with human understanding for improved results in oil production. The potential for further studies and improvements in this domain is substantial.
Three-Dimensional Imaging-Guided Lung Anatomic Segmentectomy: A Single-Center Preliminary Experiment
Authors: Cannone Giorgio , Verzeletti Vincenzo , Busetto Alberto , Lione Luigi , Bonis Alessandro , Nicotra Samuele , Rebusso Alessandro , Mammana Marco , Schiavon Marco , Dell’Amore Andrea , Rea Federico
Published: November 2023

Background and objectives: VATS segmentectomy has been proven to be effective in the treatment of stage I NSCLC, but its technical complexity remains one of the most challenging aspects for thoracic surgeons. Furthermore, 3D-CT reconstruction images can help in planning and performing surgical procedures. In this paper, we present our personal experience of 11 VATS anatomical resections performed after accurate pre-operative planning with 3D reconstructions. Materials and methods: A 3D virtual model of the lungs, airways, and vasculature was obtained, starting from a 1.25 mm 3-phase contrast CT scan, and the original images were used for the semi-automatic segmentation of the lung parenchyma, airways, and tumor. Results: Six males and five females were included in this study. The median diameter of the pulmonary lesion at the pre-operative chest CT scan was 20 mm. The surgical indication was confirmed in seven patients: in three cases, a lobectomy, instead of a segmentectomy, was needed due to intraoperative findings of nodal metastasis. Meanwhile, only in one case, we performed a lobectomy because of inadequate surgical resection margins. Skin-to-skin operative average time was 142 (IQR 1-3 105–182.5) min. The median post-operative stay was 6 (IQR 1-3 3.5–7) days. The mean value of the closest surgical margin was 13.7 mm. Conclusion: Image-guided reconstructions are a useful tool for surgeons to perform complex resections in order to spare healthy parenchyma and to ensure disease-free margins. Nevertheless, human skill and surgeon experience still remain fundamental for the final decisions regarding the proper resection to perform.
Cleaner Biofuel Production via Process Parametric Optimization of Nonedible Feedstock in a Membrane Reactor Using a Titania-Based Heterogeneous Nanocatalyst: An Aid to Sustainable Energy Development
Authors: Ameen Maria , Zafar Muhammad , Ahmad Mushtaq , Munir Mamoona , Abid Islem , Mustafa Abd El-Zaher M. A. , Athar Mohammad , Makhkamov Trobjon , Mamarakhimov Oybek , Yuldashev Akramjon , Khaydarov Khislat , Mammadova Afat O. , Botirova Laziza , Makkamov Zokirjon
Published: November 2023

Membrane technology has been embraced as a feasible and suitable substitute for conventional time- and energy-intensive biodiesel synthesis processes. It is ecofriendly, easier to run and regulate, and requires less energy than conventional approaches, with excellent stability. Therefore, the present study involved the synthesis and application of a highly reactive and recyclable Titania-based heterogeneous nanocatalyst (TiO2) for biodiesel production from nonedible Azadhiracta indica seed oil via a membrane reactor, since Azadhiracta indica is easily and widely accessible and has a rich oil content (39% w/w). The high free fatty acids content (6.52 mg/g KOH) of the nonedible oil was decreased to less than 1% via two-step esterification. Following the esterification, transesterification was performed using a heterogeneous TiO2 nanocatalyst under optimum conditions, such as a 9:1 methanol–oil molar ratio, 90 °C reaction temperature, 2 wt.% catalyst loading, and an agitation rate of 600 rpm, and the biodiesel yield was optimized through response surface methodology (RSM). Azadhiracta indica seed oil contains 68.98% unsaturated (61.01% oleic acid, 8.97% linoleic acid) and 31.02% saturated fatty acids (15.91% palmitic acid, 15.11% stearic acid). These fatty acids transformed into respective methyl esters, with a total yield up to 95% achieved. The biodiesel was analyzed via advanced characterization techniques like gas chromatography–mass spectrometry (GC-MS), Fourier transform infrared spectroscopy (FT-IR), and nuclear magnetic resonance (NMR), whereas the catalyst was characterized via X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), and Fourier transform infrared spectroscopy (FT-IR). Due to its physicochemical properties, Azadirachta indica seed oil is a highly recommended feedstock for biodiesel production. Moreover, it is concluded that the Titania-based heterogeneous nanocatalyst (TiO2) is effective for high-quality liquid fuel synthesis from nonedible Azadirachta indica seed oil in a membrane reactor, which could be an optional green route to cleaner production of bioenergy, eventually leading to sustenance, robustness, and resilience that will aid in developing a holistic framework for integrated waste management.
Influence of Specimen Diameter for Titanium Grade 1 on SHPB Tests and Its Verification Using FEM
Authors: Kim Yeon-Bok , Park ByeongJin , Kim Jeong
Published: November 2023

The split Hopkinson pressure bar (SHPB) is a machine used for obtaining dynamic material properties at high strain rates of 102–104 s−1. In the SHPB test, the material properties obtained vary depending on the shape of the specimen. In other words, it is important to understand the behavior of the specimen when selecting the specimen dimensions. However, specific standards, such as the size of specimens and bars for the SHPB, have not yet been established. This study investigates the effect of changing the specimen diameter on strain and stress results. Comparison and verification with experimental results were performed using the LS-DYNA program. Specimens are cylindrical titanium grade 1. The specifications of bars and length (L) of the specimens were not changed. The results revealed that the reflected ratio increased, and the transmitted ratio decreased as the area of the specimen decreased. The ratios of these strains are affected by impedance (Z=ρAC). The area reduction of specimens under the same conditions made it possible to obtain dynamic properties at a higher strain rate. It was shown that the impedance relationship and strain rate can be altered by varying the diameter of the specimen without changing the dimensions or material of the bar itself.
Lifestyle and Quality of Life of Women Diagnosed with Hypothyroidism in the Context of Non-Alcoholic Fatty Liver
Authors: Janota Barbara , Adamek Brygida , Szczepańska Elżbieta , Biernacki Krzysztof , Janczewska Ewa
Published: November 2023

Interconnections between hypothyroidism and metabolic disturbances manifesting in the liver and body composition have not yet been comprehensively analyzed in the context of lifestyle. This study aimed to assess the selected lifestyle factors and quality of life in the context of the development of NAFL (non-alcoholic fatty liver) in women diagnosed with hypothyroidism. This study included 134 women categorized into three groups: with hypothyroidism and NAFL, with only hypothyroidism, and with only NAFL. We compared the groups concerning the KomPAN and WHOQOL-BREF questionnaires, anthropometric measurements, body composition parameters, and the stage of liver steatosis. The individuals with NAFL most frequently consumed lard, fried dishes, processed meats, red meat, sweets, and sweetened beverages. The individuals with hypothyroidism without coexisting NAFL exhibited the highest satisfaction with health. The NAFL group had the highest average body fat percentage. Selected lifestyle aspects influenced the development of NAFL in women diagnosed with hypothyroidism. Women’s overall quality of life did not vary depending on the coexisting medical conditions. Preventive programs should promote the following: the regular consumption of meals, the appropriate energy supply, physical activity, mental health support, and striving for proper body composition parameters.
Study on the Influence of Coil Arrangement on the Output Characteristics of Electromagnetic Galloping Energy Harvester
Authors: Xiong Lei , Gao Shiqiao , Jin Lei , Sun Yaoqiang , Du Xueda , Liu Feng
Published: November 2023

The arrangement of the induction coil influences the electromagnetic damping force and output characteristics of electromagnetic energy harvesters. Based on the aforementioned information, this paper presents a proposal for a multiple off-center coil electromagnetic galloping energy harvester (MEGEH). This study establishes both a theoretical model and a physical model to research the influence of the position and quantity of the induction coils on the output characteristics of an energy harvester. Additionally, it conducts wind tunnel tests and analyzes the obtained results. With the increase in the number of induction coils, there is a significant improvement in the duty cycle and output power of the MEGEH, resulting in an amplified energy conversion efficiency. At a wind speed of 9 m/s, the duty ratios of a single set of coils (SC), two sets of coils (TC), and multiple sets of coils (MC) are 30%, 51%, and 100%, respectively. The total output powers are 0.4 mW, 0.62 mW, and 0.72 mW. However, the rate of output growth has decreased from 55% to 16%. The position of the coils affects the initial electromagnetic damping of the energy harvester. Changing the position can reduce the initial electromagnetic damping, thereby decreasing the critical wind speed. The critical wind speed of the MEGEH decreases as the induction coil is positioned further away from the vibration center. When the distance is sufficiently large, the electromagnetic damping force becomes negligible. When the induction coil is positioned centrally, the MEGEH demonstrates its maximum critical wind speed, which has been measured at 4.01 m/s. When the initial distance between the induction coil and the vibrating component is increased to 10 mm, the critical wind speed reaches its minimum value of 2.23 m/s. Therefore, it is necessary to optimize the arrangement of the coils. The coils of the MEGEH should be arranged with the MC and a 10 mm offset from the center.
Correlation of Transmission Properties with Glucose Concentration in a Graphene-Based Microwave Resonator
Authors: Yasir Muhammad , Peinetti Fabio , Savi Patrizia
Published: November 2023

Carbon-based materials, such as graphene, exhibit interesting physical properties and have been recently investigated in sensing applications. In this paper, a novel technique for glucose concentration correlation with the resonant frequency of a microwave resonator is performed. The resonator exploits the variation of the electrical properties of graphene at radio frequency (RF). The described approach is based on the variation in transmission coefficient resonating frequency of a microstrip ring resonator modified with a graphene film. The graphene film is doctor-bladed on the ring resonator and functionalised in order to detect glucose. When a drop with a given concentration is deposited on the graphene film, the resonance peak is shifted. The graphene film is modelled with a lumped element analysis. Several prototypes are realised on Rogers Kappa substrate and their transmission coefficient measured for different concentrations of glucose. Results show a good correlation between the frequency shift and the concentration applied on the film.
Application of Quantum Chemistry in the Study of Flotation Reagents
Authors: Tang Xiaoqin , Chen Jianhua , Chen Ye , Krivovichev Sergey V.
Published: November 2023

Flotation reagents are significant for modifying the interfacial characteristics of mineral grains to achieve the effective separation of minerals. Since the 1960s, when quantum chemistry was first introduced into the study of flotation reagents, many achievements have been made, although some controversial topics remain. The application of quantum chemistry in the research of flotation reagents for the separation of various minerals in the past decade is herein comprehensively and systematically reviewed. The main directions and gaps of current research are pointed out, the theoretical basis for the design and development of novel flotation reagents is summarized, and more importantly, the potential for the targeting design and development of efficient, selective, and environmentally friendly flotation reagent molecules by means of quantum chemistry is explored.
Insight into Crystalline Structure and Physicochemical Properties of Quartz-Carbon Ore
Authors: Liu Xi , Zhao Xiaoguang , Wang Xianguang , Tang Yili , Liao Juan , Wu Qianwen , Wang Jie , Zhang Jun , Yang Huaming
Published: November 2023

Composites made from carbon and nanominerals show great potential for thermal phase change materials, environmental water treatment, and biomass conversion. In 2019, a micro and nano-quartz-carbon ore was discovered in Feng-cheng City, Jiangxi Province. The study of the structural and physicochemical changes of quartz-carbon ore (QZC) during calcination is essential for the preparation of QZC-based composites and to broaden their application areas. Firstly, the SiO2 crystal structure evolution of QZC during calcination was investigated using in-situ X-ray diffraction (XRD), 29Si magic-angle sample spinning nuclear magnetic resonance (MAS NMR), and Fourier transform infrared FTIR spectroscopy. Then, the changes in carbon during calcination were investigated using Raman spectroscopy, 13C MAS NMR, and X-ray photoelectron spectroscopy (XPS). In addition, changes in the QZC morphology were observed using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) techniques. Finally, the evolution of the physicochemical properties of QZC during calcination was revealed using thermogravimetric (TG), Brunauer–Emmet–Teller (BET), resistivity, thermal conductivity, and zeta potential techniques.
Theoretical Study on Fluorinated Derivatives of Sulfolane, Cyclopentanone, and Gamma-Butyrolactone
Authors: Tshepelevitsh Sofja , Kütt Agnes , Leito Ivo
Published: November 2023

In this paper, fluorinated compounds based on sulfolane, cyclopentanone, and gamma-butyrolactone are studied computationally, focusing on their applicability in electrochemical devices and acid–base-related studies. Candidates for solvents with (1) high polarity, (2) good electrochemical stability, and (3) low basicity were searched for. Some of the compounds are studied here for the first time. Electrochemical stabilities, dielectric constants, boiling points, basicities, and lipophilicities were estimated using DFT and COSMO-RS methods with empirical corrections. The effect of fluorination on these properties as well as the bond parameters was studied. The possible synthesis routes of the proposed compounds are outlined. Some molecules display a combination of estimated properties favorable for a solvent, although none of the studied compounds are expected to surpass acetonitrile and propylene carbonate by the width of the electrochemical stability window.
Herb and Flowers of Achillea millefolium subsp. millefolium L.: Structure and Histochemistry of Secretory Tissues and Phytochemistry of Essential Oils
Authors: Konarska Agata , Weryszko-Chmielewska Elżbieta , Sulborska-Różycka Aneta , Kiełtyka-Dadasiewicz Anna , Dmitruk Marta , Gorzel Małgorzata
Published: November 2023

Achillea millefolium L. herb and flowers have high biological activity; hence, they are used in medicine and cosmetics. The aim of this study was to perform morpho-anatomical analyses of the raw material, including secretory tissues, histochemical assays of the location of lipophilic compounds, and quantitative and qualitative analysis of essential oil (EO). Light and scanning electron microscopy techniques were used to analyse plant structures. The qualitative analyses of EO were carried out using gas chromatography-mass spectrometry (GC/MS). The results of this study showed the presence of exogenous secretory structures in the raw material, i.e., conical cells (papillae) on the adaxial surface of petal teeth and biseriate glandular trichomes on the surface flowers, bracts, stems, and leaves. Canal-shaped endogenous secretory tissue was observed in the stems and leaves. The histochemical assays revealed the presence of total, acidic, and neutral lipids as well as EO in the glandular trichome cells. Additionally, papillae located at the petal teeth contained neutral lipids. Sesquiterpenes were detected in the glandular trichomes and petal epidermis cells. The secretory canals in the stems were found to contain total and neutral lipids. The phytochemical assays demonstrated that the A. millefolium subsp. millefolium flowers contained over 2.5-fold higher amounts of EO (6.1 mL/kg) than the herb (2.4 mL/kg). The EO extracted from the flowers and herb had a similar dominant compounds: β-pinene, bornyl acetate, (E)-nerolidol, 1,8-cineole, borneol, sabinene, camphor, and α-pinene. Both EO samples had greater amounts of monoterpenes than sesquiterpenes. Higher amounts of oxygenated monoterpenes and oxygenated sesquiterpenoids were detected in the EO from the herb than from the flowers.
Synthesis, Structure, and Characterizations of a Volatile/Soluble Heterometallic Hexanuclear Precursor [NaMn2(thd)4(OAc)]2
Authors: Zhang Yuxuan , Wei Zheng , Dikarev Evgeny V.
Published: November 2023

The paper describes a heterobimetallic mixed-ligand hexanuclear precursor [NaMn2(thd)4(OAc)]2 (1) (thd = 2,2,6,6-tetramethyl-3,5-heptadionate; OAc = acetate) that was designed based on its lithium homoleptic analogue, [LiMn2(thd)5], by replacing one of the thd ligands with an acetate group in order to accommodate 5-coordinated sodium instead of tetrahedral lithium ion. The complex, which is highly volatile and soluble in a variety of common solvents, has been synthesized by both the solid-state and solution methods. The unique “dimer-of-trimers” heterometallic structure consists of two trinuclear [NaMnII2(thd)4]+ units firmly bridged by two acetate ligands. X-ray diffraction techniques, DART mass spectrometry, ICP-OES analysis, and IR spectroscopy have been employed to confirm the structure and composition of the hexanuclear complex. Similar to the Li counterpart forming LiMn2O4 spinel material upon thermal decomposition, the title Na:Mn = 1:2 compound was utilized as the first single-source precursor for the low-temperature preparation of Na4Mn9O18 tunnel oxide. Importantly, four Mn sites in the hexanuclear molecule can be potentially partially substituted by other transition metals, leading to heterotri- and tetrametallic precursors for the advanced quaternary and quinary Na-ion oxide cathode materials.
Syntheses, Structures and Reactivity of Metal Complexes of Trindane, Trindene, Truxene, Decacyclene and Related Ring Systems: Manifestations of Three-Fold Symmetry
Authors: Lock Philippa E. , Reginato Nada , Bruno-Colmenárez Julia , McGlinchey Michael J.
Published: November 2023

The triple condensation of cyclopentanone or indanone to trindane (C15H18) or truxene (C27H18), respectively, provides convenient access to molecular skeletons on which major fragments of the prototypical fullerene C60 can be assembled. In particular, early approaches (both organic and organometallic) towards sumanene, as well as the final successful synthesis, are described. Organometallic derivatives of trindane have been prepared in which Cr(CO)3, Mo(CO)3, [Mn(CO)3]+ or [(C5H5)Fe(CO)2]+ are η6-bonded to the central arene ring. The debromination of hexabromotrindane yields trindene, which forms a tri-anion to which as many as three organometallic fragments, such as Mn(CO)3, W(CO)3Me, or Rh(CO)2, may be attached. Truxene forms complexes whereby three metal fragments can bind either to the peripheral arene rings, or to the five-membered rings, and these can be interconverted via η6 ↔ η5 haptotropic shifts. Truxene also forms a double-decker sandwich with Ag(I) bridges, and decacyclene, C36H18, forms triple-decker sandwiches bearing multiple cyclopentadienyl-nickel or -iron moieties. The organic chemistry of trindane has been investigated, especially with respect to its unexpectedly complex oxidation products, which were only identified unambiguously via X-ray crystallography. The three-fold symmetric trindane framework has also been used as a template upon which a potential artificial receptor has been constructed. Finally, the use of truxene and truxenone derivatives in a wide range of applications is highlighted.
Influence of Five Drying Methods on Active Compound Contents and Bioactivities of Fresh Flowers from Syringa pubescens Turcz
Authors: Xu Weidong , Zhang Jiameng , Wu Yanfang , Zhang Zichen , Wang Xinsheng , Ma Junying
Published: November 2023

The flower of Syringa pubescens Turcz. is used in Chinese folk medicine and also as a flower tea for healthcare. The effects of five drying methods on the active compound contents, the antioxidant abilities, anti-inflammatory properties and enzyme inhibitory activities were evaluated. The plant materials were treated using shade-drying, microwave-drying, sun-drying, infrared-drying and oven-drying. The seven active compounds were simultaneously determined using an HPLC method. Furthermore, the chemical profile was assessed using scanning electron microscopy, ultraviolet spectroscopy and infrared spectroscopy. The antioxidant capacities and protective effects on L02 cells induced with hydrogen peroxide were measured. The anti-inflammatory effects on lipopolysaccharide-induced RAW264.7 cells were investigated. The enzyme inhibitory activities were determined against α-amylase, α-glucosidase cholinesterases and tyrosinase. The results indicated that drying methods had significant influences on the active compound contents and biological properties. Compared with other samples, the OD samples possessed low IC50 values with 0.118 ± 0.004 mg/mL for DPPH radical, 1.538 ± 0.0972 for hydroxyl radical and 0.886 ± 0.199 mg/mL for superoxide radical, while the SHD samples had stronger reducing power compared with other samples. The SHD samples could be effective against H2O2-induced injury on L02 cells by the promoting of T-AOC, GSH-PX, SOD and CAT activities and the reducing of MDA content compared with other samples. Furthermore, SPF samples, especially the SHD sample, could evidently ameliorate inflammation through the inhibition of IL-6, IL-1β and TNF-α expression. All the studied SPF samples exhibited evidently inhibitory effects on the four enzymes. The IC50 values of inhibitory activity on α-glucosidase and α-amylase from SHD sample were 2.516 ± 0.024 and 0.734 ± 0.034 mg/mL, respectively. SD samples had potential inhibitory effects on cholinesterases and tyrosinase with IC50 values of 3.443 ± 0.060 and 1.732 ± 0.058 mg/mL. In consideration of active compound contents and biological activities, it was recommended that SHD and SD be applied for drying SPF at an industrial scale.
The Conformational Change of the L3 Loop Affects the Structural Changes in the Substrate Binding Pocket Entrance of β-Glucosidase
Authors: Nam Ki Hyun
Published: November 2023

β-glucosidase (Bgl) hydrolyzes cellobiose to glucose, thereby releasing non-reducing terminal glucosyl residues. Bgl is an essential enzyme belonging to the biomass-degrading enzyme family, which plays a vital role in enzymatic saccharification during biofuel production. The four loops above the Bgl substrate-binding pocket undergo a conformational change upon substrate recognition. However, the structural dynamism of this loop and how it is conserved among Bgl family members remain unknown. Herein, to better understand the four loops above the substrate-binding pocket of Bgl, four Bgl crystal structures in Thermoanaerobacterium saccharolyticum (TsaBgl) were determined at 1.5–2.1 Å. The L1, L2, and L4 loops of TsaBgl showed a rigid conformation stabilized by their neighboring residues via hydrogen bonds and hydrophobic interactions. The TsaBgl L3 loop showed relatively high flexibility and two different N-terminal region conformations. The conformational change in the TsaBgl L3 loop induced a change in charge and shaped at the substrate-binding pocket entrance. The amino acid sequences and structures of the TsaBgl L1–4 loops were compared with other 45 Bgl proteins, and a diversity of the L2 and L3 loops was observed. Differences in amino acids and lengths of Bgls L2–L3 loop induced differences in the conformation and structure of the Bgls substrate-binding pocket entrance. These findings expand our knowledge on the molecular function of the loops in the Bgl enzyme family.
Validity and Reliability of POM-Checker for Measuring Shoulder Range of Motion in Healthy Participants: A Pilot Single-Center Comparative Study
Authors: Chu Hongmin , Kim Weonjin , Joo Seongsu , Park Eunsik , Kim Yeong Won , Kim Cheol-Hyun , Lee Sangkwan
Published: November 2023

Background. The aim of this study was to compare shoulder movement measurements between a Kinect-based markerless ROM assessment device (POM-Checker) and a 3D motion capture analysis system (BTS SMART DX-400). Methods. This was a single-visit clinical trial designed to evaluate the validity and reliability of the POM-Checker. The primary outcome was to assess the equivalence between two measurement devices within the same set of participants, aiming to evaluate the validity of the POM-Checker compared to the gold standard device (3D Motion Analysis System). As this was a pilot study, six participants were included. Results. The intraclass correlation coefficient (ICC) and the corresponding 95% confidence intervals (CIs) were used to assess the reproducibility of the measurements. Among the 18 movements analyzed, 16 exhibited ICC values of >0.75, indicating excellent reproducibility. Conclusion. The results showed that the POM-checker is reliable and validated to measure the range of motion of the shoulder joint.
Unraveling Degradation Processes and Strategies for Enhancing Reliability in Organic Light-Emitting Diodes
Authors: Naqvi Syed , Baig Mirza , Farid Tanveer , Nazir Zahid , Mohsan Syed , Liu Zhe , Cai Wanqing , Chang Shuai
Published: November 2023

Organic light-emitting diodes (OLEDs) have emerged as a promising technology for various applications owing to their advantages, including low-cost fabrication, flexibility, and compatibility. However, a limited lifetime hinders the practical application of OLEDs in electronic devices. OLEDs are prone to degradation effects during operation, resulting in a decrease in device lifetime and performance. This review article aims to provide an exciting overview of OLED degradation effects, highlighting the various degradation mechanisms. Subsequently, an in-depth exploration of OLEDs degradation mechanisms and failure modes is presented. Internal and external processes of degradation, as well as the reactions and impacts of some compounds on OLED performance, are then elucidated. To overcome degradation challenges, the review emphasizes the importance of utilizing state-of-the-art analytical techniques and the role of these techniques in enhancing the performance and reliability of OLEDs. Furthermore, the review addresses the critical challenges of lifetime and device stability, which are crucial for the commercialization of OLEDs. This study also explores strategies to improve OLEDs’ lifetime and stability, such as using barrier layers and encapsulation techniques. Overall, this article aims to contribute to the advancement of OLED technology and its successful integration into diverse electronic applications.