bluuebunny/crossref_metadata_2025 huggingface dataset:
Material Circularity: A Novel Method for Biobased Carbon Quantification of Leather, Artificial Leather, and Trendy Alternatives
Authors: Carcione Federico , Defeo Gustavo Adrián , Galli Iacopo , Bartalini Saverio , Mazzotti Davide
Published: May 2023

In the past, climate change led the United Nations to define the Sustainable Development Goals Statement “blueprint to achieve a better and more sustainable future” and the European Commission to promote the “bioeconomy” concept and to launch the Green Deal Policy. Accordingly, the COP26 conference proposed a drastic reduction of fossil-based fuels and materials, in favor of biobased materials which should ensure intrinsic carbon neutrality. Contextually, many startups and established materials suppliers proposed new, trendy materials claiming sustainability advantages but, in many cases, without robust scientific backing. The need for transparency in terms of circularity led us to exploit a fast, reliable and easily deployable analytical method for assessing the biogenic carbon fraction in a variety of industrial materials. Our research team identified a radiocarbon analysis based on Saturated-absorption CAvity Ring-down (SCAR) spectroscopy as a quick and effective method for such a scope. Here we demonstrate its use for the determination of biogenic/fossil carbon proportions of polymeric and coated materials such as leather, coated textiles and trendy alternatives used in the fashion industry, with the scope of defining their intrinsic renewable content. The reliability of the SCAR method is validated through a comparison with the results obtained by the benchmark technique.
The Assessment of the Skin-Whitening and Anti-Wrinkling Effects of Anemarrhena asphodeloides Bunge Root Extracts and the Identification of Nyasol in a Developed Cream Product
Authors: Lee Myoung Hee , Jang Dong IL , Choi Jongkeun
Published: May 2023

Anemarrhena asphodeloides Bunge (A. asphodeloides Bunge) root extract contains nyasol as its main ingredient. Nyasol was extracted and prepared as a cosmetic raw material in 95% ethanol. To identify nyasol as a marker compound qualitative analysis was performed using ultra-performance liquid chromatographyi coupled with electrospray ionization–tandem mass spectrometry. Below a nyasol content of 12 μg/mL, the root extract exhibited negligible cytotoxicity. In this concentration range, melanin production in B16F10 mouse melanoma cells decreased as the concentration of nyasol increased, indicating a skin-whitening effect. In addition, an antiwrinkling effect was confirmed by evaluating the inhibition of MMP-1 protein expression in TNF-α-treated HaCaT cells by either A. asphodeloides Bunge root extract (>0.31 μg/mL) or nyasol (>0.25 μg/mL). High-performance liquid chromatography-coupled with a photodiode detector array was used to show that our extract contained 5.06 ± 0.01% nyasol. Furthermore, when this analysis method was applied for the quality control of a cream product containing 2 wt.% of A. asphodeloides Bunge root extract, the measured content of nyasol (0.1%) was over 90% of the nominal quantity. Therefore, the product was deemed to be within the required quality standards.
Fusion Extraction of Base Metals (Al, Cr, Fe, Ti and V) Using Ammonium Phosphate Salt as Flux
Authors: Chiweshe Trevor T. , Welman-Purchase Megan
Published: May 2023

The fusion method of using ammonium phosphate salt as flux was assessed for its ability to precipitate metaphosphate compounds containing trivalent ions M3+ = Al, Cr, Fe, Ti, and V as M(PO3)3 in inorganic salts and a certified reference material (CRM) mineral ore sample. Fusion analysis using mixtures of inorganic salts containing AlCl3, CrCl3, FeCl3, and VCl3 showed variable amounts of precipitates isolated as metaphosphate compounds in the order of iron (12%) < vanadium (13%) < chromium (30%) < (44%) aluminum. However, an analysis of the CRM (AMIS 0368) where magnetite (Fe3+/Fe2+) and ilmenite (Ti4+) are the dominant phases, showed that the obtained precipitates were in the order of chromium (less than 0.1%) < vanadium (1%) < aluminum (2%) < titanium (9%) < iron (68%). The metaphosphate compounds isolated via the use of this method were identified using XRD analysis. SEM–EDX analysis showed micro-crystalline particles from the inorganic salts that were irregular and clustered, contrary to the amorphous micro particles which were produced from the CRM. The degree of specificity improved considerably using CRM ore (AMIS 0368) with high iron content (~76%, Fe3+/Fe2+). This method was shown to be highly selective towards metals with a stable trivalent oxidation state. No other elements of a different oxidation state were precipitated.
Preparation of Cholesteric Polymer Networks with Narrow-Bandwidth Reflection and Memory Effect
Authors: Xing Zhe , Xue Lulu , Chen Yinjie , Zhang Wenguan , Zhou Zhong , Li Luhai , Cui Yuchen , Guo Yanan , Chang Yifan , Li Binbin
Published: May 2023

A polymer network with a memory effect based on a polymer-stabilized narrow-bandwidth cholesteric liquid crystal (CLC) was prepared using the washing-out/refill method. The effects of different polymerization conditions on the reflection properties of CLC films were investigated. Meanwhile, the selective reflection property and narrow-bandwidth reflection memory effect of the polymer network were proved, and the response mechanism was provided. Furthermore, different materials from liquid crystals, with an anisotropic refractive index, to toluene, with an isotropic refractive index, were refilled to polymer scaffolds with helical structures, which originated from the periodic arrangement of CLCs. It was confirmed that the reflection bandwidth of these films can be dramatically narrowed by the reduced birefringence (Δn) of the refilled materials. The narrowest bandwidth of 22.5 nm refilling toluene with an isotropic refractive index (Δn = 0) was obtained. These results may provide a novel idea for flexible reflective displays, color filters, printing, and colored cladding of a variety of objects.
Influence of Deposition Time on Structural, Morphological, and Optical Properties of CdS Thin Films Grown by Low-Cost Chemical Bath Deposition
Authors: El-Shaer Abdelhamid , Ezzat Sameh , Habib Mohamed A. , Alduaij Omar K. , Meaz Talaat M. , El-Attar Samy A.
Published: May 2023

CdS thin films were deposited on glass substrates employing low-cost and low-temperature chemical bath deposition (CBD). The effect of deposition time on the fabricated sample’s properties was investigated by XRD, SEM, EDX, Raman, UV-vis spectrophotometry, and PL spectroscopy. XRD results indicate the formation of cubic and hexagonal structures of CdS thin films. The calculated average crystal size ranged from 21–50 nm. SEM results indicate the formation of hierarchical nanoflakes where the nanoflakes are entangled with one another like plant roots. Raman study confirmed that the fabricated thin films have two distinct peaks that are centered at 298 cm−1 and 599 cm−1, which are characteristic vibration modes for CdS thin film. UV-vis absorption spectra indicate absorption band edges near 500 nm, which are related to the band gap values of CdS thin films. The estimated Eg of CdS thin films was reduced from 2.4 to 2.22 eV as the deposition time increased from 5 to 60 min. PL results show the main peak centered at 537 nm, its intensity decreasing as deposition time increases, indicating lower recombination of charge carriers. Our results reveal that CdS thin films are an excellent candidate for optoelectronic applications.
Plasma Cabozantinib Level Measurement in Patients with Renal Cell and Hepatocellular Carcinomas Using a Simple HPLC–UV Method Suitable for Clinical Application
Authors: Yasu Takeo , Gando Yoshito , Nishijima Ryosuke , Ikuta Risa , Suzuki Motofumi , Shirota Mikio
Published: May 2023

Cabozantinib, which is used to treat renal cell and hepatocellular carcinomas, is often associated with dose-dependent adverse events. Monitoring the levels of cabozantinib in the blood may maximize the therapeutic effect and prevent serious adverse events. In this study, we developed a high-performance liquid chromatography–ultraviolet (HPLC–UV) method of measuring plasma cabozantinib concentration. Human plasma samples (50 µL) were processed by simple deproteinization with acetonitrile, followed by chromatographic separation on a reversed-phase column with an isocratic mobile phase of 0.5% KH₂PO4 (pH 4.5) and acetonitrile (43:57, v/v) at a flow rate of 1.0 mL/min, with a 250 nm ultraviolet detector. The calibration curve was linear over the concentration range (0.05–5 µg/mL) with a coefficient of determination of 0.99999. The accuracy of the assay ranged from −4.35% to 0.98%, and recovery was >96.04%. The measurement time was 9 min. These findings confirm the effectiveness of this HPLC–UV method for cabozantinib quantification in human plasma, which is sufficiently simple for use for monitoring patients in clinical settings.
Automatic Analysis of MRI Images for Early Prediction of Alzheimer’s Disease Stages Based on Hybrid Features of CNN and Handcrafted Features
Authors: Khalid Ahmed , Senan Ebrahim Mohammed , Al-Wagih Khalil , Al-Azzam Mamoun Mohammad Ali , Alkhraisha Ziad Mohammad
Published: May 2023

Alzheimer’s disease (AD) is considered one of the challenges facing health care in the modern century; until now, there has been no effective treatment to cure it, but there are drugs to slow its progression. Therefore, early detection of Alzheimer’s is vital to take needful measures before it develops into brain damage which cannot be treated. Magnetic resonance imaging (MRI) techniques have contributed to the diagnosis and prediction of its progression. MRI images require highly experienced doctors and radiologists, and the analysis of MRI images takes time to analyze each slice. Thus, deep learning techniques play a vital role in analyzing a huge amount of MRI images with high accuracy to detect Alzheimer’s and predict its progression. Because of the similarities in the characteristics of the early stages of Alzheimer’s, this study aimed to extract the features in several methods and integrate the features extracted from more than one method into the same features matrix. This study contributed to the development of three methodologies, each with two systems, with all systems aimed at achieving satisfactory accuracy for the detection of AD and predicting the stages of its progression. The first methodology is by Feed Forward Neural Network (FFNN) with the features of GoogLeNet and DenseNet-121 models separately. The second methodology is by FFNN network with combined features between GoogLeNet and Dense-121 models before and after high-dimensionality reduction of features using the Principal Component Analysis (PCA) algorithm. The third methodology is by FFNN network with combined features between GoogLeNet and Dense-121 models separately and features extracted by Discrete Wavelet Transform (DWT), Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) methods called handcrafted features. All systems yielded super results in detecting AD and predicting the stages of its progression. With the combined features of the DenseNet-121 and handcrafted, the FFNN achieved an accuracy of 99.7%, sensitivity of 99.64%, AUC of 99.56%, precision of 99.63%, and a specificity of 99.67%.
Sexually Transmitted Diseases—An Update and Overview of Current Research
Authors: Wihlfahrt Kristina , Günther Veronika , Mendling Werner , Westermann Anna , Willer Damaris , Gitas Georgios , Ruchay Zino , Maass Nicolai , Allahqoli Leila , Alkatout Ibrahim
Published: May 2023

A rise in the rates of sexually transmitted diseases, both worldwide and in Germany, has been observed especially among persons between the ages of 15 and 24 years. Since many infections are devoid of symptoms or cause few symptoms, the diseases are detected late, may spread unchecked, and be transmitted unwittingly. In the event of persistent infection, the effects depend on the pathogen in question. Manifestations vary widely, ranging from pelvic inflammatory disease, most often caused by Chlamydia trachomatis (in Germany nearly 30% of PID) or Neisseria gonorrhoeae (in Germany <2% of PID), to the development of genital warts or cervical dysplasia in cases of infection with the HP virus. Causal treatment does exist in most cases and should always be administered to the sexual partner(s) as well. An infection during pregnancy calls for an individual treatment approach, depending on the pathogen and the week of pregnancy.
Clinical Validation of an Artificial Intelligence Model for Detecting Distal Radius, Ulnar Styloid, and Scaphoid Fractures on Conventional Wrist Radiographs
Authors: Lee Kyu-Chong , Choi In Cheul , Kang Chang Ho , Ahn Kyung-Sik , Yoon Heewon , Lee Jae-Joon , Kim Baek Hyun , Shim Euddeum
Published: May 2023

This study aimed to assess the feasibility and performance of an artificial intelligence (AI) model for detecting three common wrist fractures: distal radius, ulnar styloid process, and scaphoid. The AI model was trained with a dataset of 4432 images containing both fractured and non-fractured wrist images. In total, 593 subjects were included in the clinical test. Two human experts independently diagnosed and labeled the fracture sites using bounding boxes to build the ground truth. Two novice radiologists also performed the same task, both with and without model assistance. The sensitivity, specificity, accuracy, and area under the curve (AUC) were calculated for each wrist location. The AUC for detecting distal radius, ulnar styloid, and scaphoid fractures per wrist were 0.903 (95% C.I. 0.887–0.918), 0.925 (95% C.I. 0.911–0.939), and 0.808 (95% C.I. 0.748–0.967), respectively. When assisted by the AI model, the scaphoid fracture AUC of the two novice radiologists significantly increased from 0.75 (95% C.I. 0.66–0.83) to 0.85 (95% C.I. 0.77–0.93) and from 0.71 (95% C.I. 0.62–0.80) to 0.80 (95% C.I. 0.71–0.88), respectively. Overall, the developed AI model was found to be reliable for detecting wrist fractures, particularly for scaphoid fractures, which are commonly missed.
Papillomavirus Infection as Potential Cause of Miscarriage in the Early Gestational Age: A Prospective Study
Authors: Bruno Maria Teresa , Caruso Salvatore , Scalia Guido , Costanzo Maria , Di Pasqua Salvatore , Boemi Sara , Panella Marco Marzio , Palumbo Marco
Published: May 2023

The possible association between human papillomavirus (HPV) infection and negative pregnancy outcomes has been debated in the literature, with conflicting results from clinical trials. While some authors support a link between HPV and miscarriage, others argue that the mere detection of the virus does not necessarily indicate a causal relationship with negative pregnancy outcomes. In this study, we conducted a prospective, controlled investigation of the potential association between HPV infection and miscarriage. Our study included 59 women who had experienced a miscarriage and 57 women who had undergone voluntary termination of pregnancy (TOP) within the 12th week of gestation. We assessed HPV prevalence, maternal age, and HPV genotype in both groups and evaluated the relationship between these factors and pregnancy outcome. Unlike previous studies that only identified HPV in cases of abortion, we also correlated the positivity of chorionic villi with gestational age in both groups. We found a close correlation between positive chorionic villi and very early gestational age, with all 13 cases of virus-positive chorionic villi in the miscarriage group occurring in gestational periods of less than 8 + 5 weeks (<60 days) (RR = 28.6). Our analysis showed no correlation between HPV infection and maternal age or viral genotypes. The results suggest that the presence of HPV alone is not enough to cause spontaneous abortion, but a high viral load in early pregnancy may increase the risk of negative outcomes. These findings have important implications for the management of HPV infection during pregnancy and may provide a rationale for the use of HPV vaccines to reduce the incidence of spontaneous abortion and infertility due to preclinical spontaneous abortions.
Microembolizations in the Arterial Cerebral Circulation in Patients with Atrial Fibrillation Ablation Using the Cryoballoon Technique—Protocol and Methodology of a Prospective Observational Study
Authors: Erkapic Damir , Aleksic Marko , Roussopoulos Konstantinos , Weipert Kay Felix , Sözener Korkut , Kostev Karel , Allendörfer Jens , Rosenbauer Josef , Guenduez Dursun , Tanislav Christian
Published: May 2023

There is considerable uncertainty regarding the impact of microembolic signals (MESs) on neuropsychological abilities in patients receiving pulmonary vein isolation and beyond using the cryoballoon technique. We conducted the largest prospective observational study on this topic, providing insights into the gradual unmasking of procedure-related MESs and their impacts on neuropsychological outcomes. MESs were continuously detected periprocedurally using transcranial Doppler ultrasonography. Neuropsychological status was evaluated comprehensively using the CERAD Plus test battery, which consists of 11 neuropsychological subtests. Patients with atrial fibrillation were included in the study with an equal distribution (50:50) of paroxysmal or persistent presentations. Of 167 consecutive eligible patients, 100 were included within the study enrollment period from February 2021 to August 2022. The study, including the documentation of all follow-up visits, ended in November 2022. This paper focuses on describing the study protocol and methodology and presenting the baseline data.
Trends in the Use of Second-Generation Androgen Receptor Axis Inhibitors for Metastatic Hormone-Sensitive Prostate Cancer and Clinical Factors Predicting Biological Recurrence
Authors: Nakane Keita , Watanabe Hiromitsu , Naiki Taku , Takahara Kiyoshi , Yasui Takahiro , Miyake Hideaki , Shiroki Ryoichi , Koie Takuya
Published: May 2023

The advent of second-generation androgen receptor axis-targeted agents (ARATs) has revolutionized the treatment of metastatic hormone-sensitive prostate cancer (mHSPC). Biochemical recurrence-free survival (BRFS) was used to compare the efficacy of each ARAT. This multicenter retrospective study included 581 patients with newly diagnosed mHSPC who received first-line hormone therapy. The characteristics of patients treated with different ARATs were compared as well as changes in the usage of each drug over time. For BRFS, the apalutamide (Apa) and enzalutamide (Enza) groups, as well as the abiraterone acetate (Abi) and Apa/Enza groups, were compared. In addition, multivariate analysis was performed to determine predictive factors for biochemical recurrence (BCR). The use of second-generation ARATs tended to increase after May 2020. No significant difference in BRFS was found between patients receiving Apa and Enza (p = 0.490) and those receiving Abi or Apa/Enza (p = 0.906). Multivariate analysis revealed that the neutrophil-to-lymphocyte ratio (NLR) ≥ 2.76 and PSA ≥ 0.550 ng/mL were independent predictors of BCR. There were no significant differences in patient characteristics or BRFS in patients with mHSPC receiving different ARATs as first-line treatment. NLR and PSA may be prognostic factors following the first-line treatment of patients with mHSPC.
A Novel Deep Transfer Learning-Based Approach for Automated Pes Planus Diagnosis Using X-ray Image
Authors: Gül Yeliz , Yaman Süleyman , Avcı Derya , Çilengir Atilla Hikmet , Balaban Mehtap , Güler Hasan
Published: May 2023

Pes planus, colloquially known as flatfoot, is a deformity defined as the collapse, flattening or loss of the medial longitudinal arch of the foot. The first standard radiographic examination for diagnosing pes planus involves lateral and dorsoplantar weight-bearing radiographs. Recently, many artificial intelligence-based computer-aided diagnosis (CAD) systems and models have been developed for the detection of various diseases from radiological images. However, to the best of our knowledge, no model and system has been proposed in the literature for automated pes planus diagnosis using X-ray images. This study presents a novel deep learning-based model for automated pes planus diagnosis using X-ray images, a first in the literature. To perform this study, a new pes planus dataset consisting of weight-bearing X-ray images was collected and labeled by specialist radiologists. In the preprocessing stage, the number of X-ray images was augmented and then divided into 4 and 16 patches, respectively in a pyramidal fashion. Thus, a total of 21 images are obtained for each image, including 20 patches and one original image. These 21 images were then fed to the pre-trained MobileNetV2 and 21,000 features were extracted from the Logits layer. Among the extracted deep features, the most important 1312 features were selected using the proposed iterative ReliefF algorithm, and then classified with support vector machine (SVM). The proposed deep learning-based framework achieved 95.14% accuracy using 10-fold cross validation. The results demonstrate that our transfer learning-based model can be used as an auxiliary tool for diagnosing pes planus in clinical practice.
Identifying the Key Components in ResNet-50 for Diabetic Retinopathy Grading from Fundus Images: A Systematic Investigation
Authors: Huang Yijin , Lin Li , Cheng Pujin , Lyu Junyan , Tam Roger , Tang Xiaoying
Published: May 2023

Although deep learning-based diabetic retinopathy (DR) classification methods typically benefit from well-designed architectures of convolutional neural networks, the training setting also has a non-negligible impact on prediction performance. The training setting includes various interdependent components, such as an objective function, a data sampling strategy, and a data augmentation approach. To identify the key components in a standard deep learning framework (ResNet-50) for DR grading, we systematically analyze the impact of several major components. Extensive experiments are conducted on a publicly available dataset EyePACS. We demonstrate that (1) the DR grading framework is sensitive to input resolution, objective function, and composition of data augmentation; (2) using mean square error as the loss function can effectively improve the performance with respect to a task-specific evaluation metric, namely the quadratically weighted Kappa; (3) utilizing eye pairs boosts the performance of DR grading and; (4) using data resampling to address the problem of imbalanced data distribution in EyePACS hurts the performance. Based on these observations and an optimal combination of the investigated components, our framework, without any specialized network design, achieves a state-of-the-art result (0.8631 for Kappa) on the EyePACS test set (a total of 42,670 fundus images) with only image-level labels. We also examine the proposed training practices on other fundus datasets and other network architectures to evaluate their generalizability. Our codes and pre-trained model are available online.
Evaluating Pre-Analytical Variables for Saliva Cell-Free DNA Liquid Biopsy
Authors: Salfer Blake , Havo Daisy , Kuppinger Skyllar , Wong David , Li Feng , Zhang Liying
Published: May 2023

Liquid biopsy utilizing cell-free DNA (cfDNA) has become an emergent field of study for cancer screening and monitoring. While blood-based liquid biopsy has been investigated extensively, there are advantages to using other body fluids. Using saliva is noninvasive, repeatable, and it may be enriched with cfDNA from certain cancer types. However, the lack of standardization in the pre-analytical phase of saliva-based testing is a concern. In this study, we evaluated pre-analytical variables that impact cfDNA stability in saliva specimens. Using saliva from healthy individuals, we tested different collection devices and preservatives and their effects on saliva cfDNA recovery and stability. Novosanis’s UAS preservative helped stabilize cfDNA at room temperature for up to one week. Our study provides useful information for further improvements in saliva collection devices and preservatives.
Information-Geometric Approach for a One-Sided Truncated Exponential Family
Authors: Yoshioka Masaki , Tanaka Fuyuhiko
Published: May 2023

In information geometry, there has been extensive research on the deep connections between differential geometric structures, such as the Fisher metric and the α-connection, and the statistical theory for statistical models satisfying regularity conditions. However, the study of information geometry for non-regular statistical models is insufficient, and a one-sided truncated exponential family (oTEF) is one example of these models. In this paper, based on the asymptotic properties of maximum likelihood estimators, we provide a Riemannian metric for the oTEF. Furthermore, we demonstrate that the oTEF has an α = 1 parallel prior distribution and that the scalar curvature of a certain submodel, including the Pareto family, is a negative constant.
Flight Delay Regression Prediction Model Based on Att-Conv-LSTM
Authors: Qu Jingyi , Xiao Min , Yang Liu , Xie Wenkai
Published: May 2023

Accurate prediction results can provide an excellent reference value for the prevention of large-scale flight delays. Most of the currently available regression prediction algorithms use a single time series network to extract features, with less consideration of the spatial dimensional information contained in the data. Aiming at the above problem, a flight delay prediction method based on Att-Conv-LSTM is proposed. First, in order to fully extract both temporal and spatial information contained in the dataset, the long short-term memory network is used for getting time characteristics, and a convolutional neural network is adopted for obtaining spatial features. Then, the attention mechanism module is added to improve the iteration efficiency of the network. Experimental results show that the prediction error of the Conv-LSTM model is reduced by 11.41 percent compared with the single LSTM, and the prediction error of the Att-Conv-LSTM model is reduced by 10.83 percent compared with the Conv-LSTM. It is proven that considering spatio-temporal characteristics can obtain more accurate prediction results in the flight delay problem, and the attention mechanism module can also effectively improve the model performance.
Time-Varying Elasticity of Cyclically Adjusted Primary Balance and Effect of Fiscal Consolidation on Domestic Government Debt in South Africa
Authors: Buthelezi Eugene Msizi , Nyatanga Phocenah
Published: May 2023

This paper investigates the impact of the time-varying elasticity of the cyclically adjusted primary balance (CAPB) and fiscal consolidation on government debt. The time-varying parameter structural vector autoregression (TVP-VAR) model is used on a time series of data from 1979 to 2022. The contribution of this paper is on the understanding of the impact of fiscal consolidation on domestic government debt and the need to use time-varying elasticity when calculating the cyclical adjusted primary balance to provide a more accurate representation of discretionary actions taken by fiscal authorities. It is found that there is more variation in the CAPB with time-varying elasticity than with constant elasticity. Constant elasticity is not effective in capturing fiscal consolidation episodes, and time-varying elasticity is a better alternative. There is evidence that fiscal consolidation increases domestic government debt. The shocks of fiscal consolidation through government expenditure cuts reduce domestic government debt in the long run, while taxes increase domestic government debt. It is recommended that fiscal authorities use fiscal consolidation to reduce government expenditure that is related to inefficient expenditure. In the event of government expenditure, this expenditure needs to be in productive sectors of the economy that will bring about an increase in revenue rather than an increase in the tax rate. Given the result, a tax increase should be something that fiscal authorities are not using in the effort to stimulate economic growth or reduce domestic government debt.
Detection of Secondary Side Position for Segmented Dynamic Wireless Charging Systems Based on Primary Phase Angle Sensing
Authors: Xiong Wei , Liu Jiangtao , Chen Jing , Hu Dewang
Published: May 2023

In dynamic wireless charging systems, the detection of secondary side positions has been attracting much attention in academic research. Due to the strong electromagnetic interference and the presence of foreign objects in the charging area, the use of conventional detection methods such as wireless communication and infrared techniques may be problematic; therefore, as an alternative to solve the above problem, a new detection method based on phase angle sensing is proposed in this paper. Through phase analysis of the primary input impedance and by reference to the relationship between the input port phase angle and the secondary side position, the proposed method is able to sense the secondary side position in real time. In addition, an analysis of the sensitivity of the proposed method to parameter variations is also carried out. In order to verify the effectiveness of the proposed position detection method, a dynamic wireless charging system with four segments is built for experimental verification. The experimental results show that when the phase angle threshold is set at 300°, the secondary side position can be accurately identified, and the proposed method is quite robust within a parameter deviation of up to 4%.
A Compact 2.4 GHz L-Shaped Microstrip Patch Antenna for ISM-Band Internet of Things (IoT) Applications
Authors: Zambak Muhammad Fitra , Al-Bawri Samir Salem , Jusoh Muzammil , Rambe Ali Hanafiah , Vettikalladi Hamsakutty , Albishi Ali M. , Himdi Mohamed
Published: May 2023

Wireless communication technology integration is necessary for Internet of Things (IoT)-based applications to make their data easily accessible. This study proposes a new, portable L-shaped microstrip patch antenna with enhanced gain for IoT 2.4 GHz Industrial, Scientific, and Medical (ISM) applications. The overall dimensions of the antenna are 28 mm × 21 mm × 1.6 mm (0.22λo × 0.17λo × 0.013λo, with respect to the lowest frequency). The antenna design is simply comprised of an L-shape strip line, with a full ground applied in the back side and integrated with a tiny rectangular slot. According to investigations, the developed antenna is more efficient and has a greater gain than conventional antennas. The flexibility of the antenna’s matching impedance and performance are investigated through several parametric simulations. Results indicate that the gain and efficiency can be enhanced through modifying the rectangular back slot in conjunction with fine-tuning the front L-shaped patch. The finalized antenna operates at 2.4 GHz with a 98% radiation efficiency and peak gains of 2.09 dBi (measured) and 1.95 dBi (simulated). The performance of the simulation and measurement are found to be in good agreement. Based on the performance that was achieved, the developed L-shaped antenna can be used in a variety of 2.4 GHz ISM bands and IoT application environments, especially for indoor localization estimation scenarios, such as smart offices and houses, and fourth-generation (4G) wireless communications applications due to its small size and high fractional bandwidth.
Multiple Signal TDOA/FDOA Joint Estimation with Coherent Integration
Authors: Ouyang Xinxin , Yao Shanfeng , Wan Qun
Published: May 2023

Passive localization relies significantly on the estimation of the Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) to accurately determine the location of a target. The precision of TDOA and FDOA estimation is affected by signal parameters of time and frequency distribution. In case of multiple signals arising at different frequency bands and intercepted simultaneously by spatially separate sensors covering a wide frequency band, the traditional method is first to separate the signals from the mixed wideband signal through digital down conversion (DDC), which brings multiple narrowband signals, and then the estimation of TDOA and FDOA of each narrowband signal can be performed using cross ambiguity function (CAF). The paper introduces a novel approach for estimating TDOA and FDOA of multiple signals simultaneously, which employs a coherent integration method. First, the cross ambiguity function for each signal is realized with the narrowband signal as the same as the traditional method. Next, the phase relation of each CAF is analyzed, then the joint CAF can be obtained with phase compensation, from which multiple signal TDOA and FDOA estimations will be implemented simultaneously. Numerical simulations are performed to compare the two methods, and the results demonstrate the superiority of the proposed algorithm.
Potential of Pine Needle Biomass for Bioethanol Production
Authors: Wawro Aleksandra , Jakubowski Jakub , Gieparda Weronika , Pilarek Zenon , Łacka Agnieszka
Published: May 2023

Currently, fossil fuels are used to produce fuels and electricity, which are finite sources and have a negative impact on the natural environment. An excellent alternative to these fuels is biofuels, such as bioethanol from waste forest biomass. Pine needles are one of the most important available forest biomass materials with s significant impact on local understory vegetation. Forest waste biomass, which is a rich source of lignocellulose, can be used in various ways, such as for the eco-economical production of bioethanol. The aim of this study was to analyze the possibilities of bioethanol production from pine needle biomass obtained from forest land following different soil preparations and logging residue management. The pine needle dry matter yield, chemical components of pine needle biomass (cellulose, hemicellulose, lignin), and the amount of ethanol yield per hectare were evaluated. The highest average yield pine needle equal to 6.17 Mg∙ha−1 was observed. Bioethanol yield per hectare from this biomass was the highest for plowing with the LPZ-75 plow and was 1.08 m3∙ha−1. The discussed results were confirmed by detailed statistical analysis. To sum up, the researched pine needle biomass turned out to be an interesting raw material with the potential for bioethanol production.
State-of-the-Art Grid Stability Improvement Techniques for Electric Vehicle Fast-Charging Stations for Future Outlooks
Authors: Momoh Kabir , Zulkifli Shamsul Aizam , Korba Petr , Sevilla Felix Rafael Segundo , Afandi Arif Nur , Velazquez-Ibañez Alfredo
Published: May 2023

The growing trend for electric vehicles (EVs) and fast-charging stations (FCSs) will cause the overloading of grids due to the high current injection from FCSs’ converters. The insensitive nature of the state of charge (SOC) of EV batteries during FCS operation often results in grid instability problems, such as voltage and frequency deviation at the point of common coupling (PCC). Therefore, many researchers have focused on two-stage converter control (TSCC) and single-stage converter (SSC) control for FCS stability enhancement, and suggested that SSC architectures are superior in performance, unlike the TSCC methods. However, only a few research works have focused on SSC techniques, despite the techniques’ ability to provide inertia and damping support through the virtual synchronous machine (VSM) strategy due to power decoupling and dynamic response problems. TSCC methods deploy current or voltage control for controlling EVs’ SOC battery charging through proportional-integral (PI), proportional-resonant (PR), deadbeat or proportional-integral-derivative (PID) controllers, but these are relegated by high current harmonics, frequency fluctuation and switching losses due to transient switching. This paper reviewed the linkage between the latest research contributions, issues associated with TSCC and SSC techniques, and the performance evaluation of the techniques, and subsequently identified the research gaps and proposed SSC control with SOC consideration for further research studies.
Analysis and Design of a New High Voltage Gain Interleaved DC–DC Converter with Three-Winding Coupled Inductors for Renewable Energy Systems
Authors: Chen Shin-Ju , Yang Sung-Pei , Huang Chao-Ming , Huang Ping-Sheng
Published: May 2023

In this article, a new non-isolated interleaved DC–DC converter is proposed to provide a high voltage conversion ratio in renewable energy systems. The converter configuration is composed of a two-phase interleaved boost converter integrating a voltage-lift capacitor and three-winding coupled inductor-based voltage multiplier modules to achieve high step-up voltage conversion and reduce voltage stresses on the semiconductors (switches and diodes). The converter can achieve a high voltage conversion ratio when working at a proper duty ratio. The voltage stresses on the switches are significantly lower than the output voltage, which enables engineers to adopt low-voltage-rating MOSFETs with low on-state resistance. The switches can turn on under zero-current switching (ZCS) conditions because of the leakage inductor series reducing switching losses. Some diodes can naturally turn off under ZCS conditions to alleviate the reverse–recovery issue and to reduce reverse–recovery losses. The input current has small ripples due to the interleaved operation. The leakage inductor energy is recycled and voltage spikes on the switches are avoided. The proposed converter is suitable for applications in which high voltage gain, high efficiency and high power are required. The principle of operation, steady-state analysis and design considerations of the proposed converter are described in detail. In addition, a closed-loop controller is designed to reduce the effect of input voltage fluctuation and load change on the output voltage. Finally, a 1000 W laboratory prototype is built and tested. The theoretical analysis and the performance of the proposed converter were validated by the experimental results.
An MV-Connected Ultra-Fast Charging Station Based on MMC and Dual Active Bridge with Multiple dc Buses
Authors: Barresi Marzio , Ferri Edoardo , Piegari Luigi
Published: May 2023

The diffusion of electric vehicles will be strongly related to the capacity to charge them in short times. To do so, the necessity of widespread fast charging stations arises. However, their intermittent demand represents a challenging load for grid operators. In order to relieve their impact on the electrical grid operation, integrating storage systems in the charging stations represents a potential solution, although it complicates the overall system management. Moreover, standard converter architectures for the MV grid interface require the installation of bulky transformers and filters. In order to cope with the mentioned problems, this paper proposes an ultra-fast charging station topology based on a modular multilevel converter (MMC) structure and dual-active bridge (DAB) converters. Thanks to the multilevel converter properties, the proposed charging station can be directly interfaced with the MV grid without requiring transformers or filters. Additionally, exploiting the degree of freedom in the converter control system, such as circulating components, offers uneven power distribution among the converter submodules that can be managed. Along with the MMC control strategy, the article addresses a straightforward methodology to select the main parameters of the DAB converter as a function of the involved grid power and circulating power contributions, with the primary goal of obtaining a trade-off between internal balancing performances and a broad soft-switching region without incurring in converter oversizing. The effectiveness of the proposed charging station is finally discussed through numerical simulations, where its behavior during a power demand cycle is analyzed.
Combined Utilization of Cylinder and Different Shaped Alumina Nanoparticles in the Base Fluid for the Effective Cooling System Design of Lithium-Ion Battery Packs
Authors: Selimefendigil Fatih , Dilbaz Furkan , Öztop Hakan F.
Published: May 2023

It is important to consider the thermal management of lithium-ion batteries to overcome their limitations in usage and improve their performance and life cycles. In this study, a novel cooling system for the thermal management of lithium-ion battery packs is proposed by using an inner cylinder in the cooling channel and different-shaped nanoparticles in the base fluid, which is used as the cooling medium. The performance improvements in a 20 Ah capacity battery are compared by using a water–boehmite alumina (AlOOH) nanofluid, considering cylinder-, brick-, and blade-shaped nanoparticles up to a solid volume fraction of 2%. The numerical analysis is conducted using the finite element method, and Reynolds numbers between 100 and 600 are considered. When the efficacy of the coolants utilized is compared, it is apparent that as the Reynolds number increases, both cooling media decrease the highest temperature and homogenize the temperatures in the battery. The utilization of the cylinder in the mini-channel results in a 2 °C temperature drop at Re = 600 as compared to the flat channel. A boehmite alumina nanofluid with a 2% volume fraction reduces the maximum temperature by 5.1% at Re = 200. When the shape effect of the nanofluid is examined, it is noted that the cylinder-shaped particle improves the temperature by 4.93% as compared to blade-shaped nanoparticles and 7.32% as compared to brick-shaped nanoparticles. Thus, the combined utilization of a nanofluid containing cylindrical-shaped nanoparticles as the cooling medium and a cylinder in the mini-channel of a battery thermal management system provides an effective cooling system for the thermal management of the battery pack. The outcomes of this work are helpful for further system design and optimization studies related to battery thermal management.
Use of Kiwi Waste as Fuel in MFC and Its Potential for Use as Renewable Energy
Authors: Rojas-Flores Segundo , De La Cruz-Noriega Magaly , Cabanillas-Chirinos Luis , Benites Santiago M. , Nazario-Naveda Renny , Delfín-Narciso Daniel , Gallozzo-Cardemas Moisés , Díaz Felix , Murga-Torres Emzon , Rojas-Villacorta Walter
Published: May 2023

This research aimed to use kiwi waste as fuel to generate bioelectricity through microbial fuel cells. It was possible to generate an electrical current and voltage peaks of 3.807 ± 0.102 mA and 0.993 ± 0.061 V on day 11, showing an electrical conductivity of 189.82 ± 3.029 mS/cm and an optimum operating pH of 5.966 ± 0.121. The internal resistance of the cells was calculated using Ohm’s Law, resulting in a value of 14.957 ± 0.394 Ω, while the maximum power density was 212.68 ± 26.84 mW/m2 at a current density of 4.506 A/cm2. Through the analysis of the FTIR spectra carried out on the substrate, a decrease in the characteristic organic peaks was observed due to their decomposition during the electricity-generation process. In addition, it was possible to molecularly identify the bacteria Comamonas testosteroni, Sphingobacterium sp., and Stenotropho-monas maltophila adhered to the anodized biofilm. Finally, the capacity of this residue to generate bioelectricity was demonstrated by lighting an LED bulb with a voltage of 2.85 V.
Physicochemical Properties, Antioxidant Capacity, and Bioavailability of Laurus nobilis L. Leaf Polyphenolic Extracts Microencapsulated by Spray Drying
Authors: Dobroslavić Erika , Elez Garofulić Ivona , Zorić Zoran , Pedisić Sandra , Roje Marin , Dragović-Uzelac Verica
Published: May 2023

Laurel (Laurus nobilis L.) leaves are a rich source of polyphenols with the potential for use in functional foods, where the main obstacle is their low stability and bioavailability, which can be improved by spray drying (SD). This research examined the influence of SD parameters, including inlet temperature (120, 150, and 180 °C), carrier type (β-cyclodextrin (β-CD); β-CD + maltodextrin (MD) 50:50; β-CD + gum arabic (GA) 50:50), and sample:carrier ratio (1:1, 1:2 and 1:3) on the physicochemical properties, encapsulation efficiency, polyphenolic profile, antioxidant capacity and bioaccessibility of laurel leaf polyphenols. The highest encapsulation efficiency was achieved at a sample:carrier ratio 1:2 and the temperature of 180 °C by using either of the applied carriers. However, the application of β-CD + MD 50:50 ensured optimal solubility (55.10%), hygroscopicity (15.32%), and antioxidant capacity (ORAC 157.92 μmol Trolox equivalents per g of powder), while optimal moisture content (3.22%) was determined only by temperature, demanding conditions above 150 °C. A total of 29 polyphenols (dominantly flavonols) were identified in the obtained powders. SD encapsulation increased the bioaccessibility of laurel flavonols in comparison to the non-encapsulated extract by ~50% in the gastric and ~10% in the intestinal phase, especially for those powders produced with carrier mixtures.
Developing CuS for Predicting Aggressiveness and Prognosis in Lung Adenocarcinoma
Authors: Liu Honghao , Che Haijun , Zhang Mengyan , Lv Jinyue , Pu Chengjie , Wu Jiawei , Zhang Yan , Gu Yue
Published: May 2023

Cuproptosis is a newfound cell death form that depends on copper (Cu) ionophores to transport Cu into cancer cells. Studies on the relationship have covered most common cancer types and analyzed the links between cuproptosis-related genes (CRGs) and various aspects of tumor characteristics. In this study, we evaluated the role of cuproptosis in lung adenocarcinoma (LUAD) and constructed the cuproptosis-related score (CuS) to predict aggressiveness and prognosis in LUAD, so as to achieve precise treatment for patients. CuS had a better predictive performance than cuproptosis genes, possibly due to the synergy of SLC family genes, and patients with a high CuS had a poor prognosis. Functional enrichment analysis revealed the correlation between CuS and immune and mitochondrial pathways in multiple datasets. Furthermore, we predicted six potential drugs targeting high-CuS patients, including AZD3759, which is a targeted drug for LUAD. In conclusion, cuproptosis is involved in LUAD aggressiveness, and CuS can accurately predict the prognosis of patients. These findings provide a basis for precise treatment of patients with high CuS in LUAD.
A Constraint-Based Generalization Model Incorporating a Quality Control Mechanism
Authors: Blana Natalia , Kavadas Ioannis , Tsoulos Lysandros
Published: May 2023

Automation in map production has created the need for modeling the map composition process. Generalization is the most critical process in map composition, with considerable impact on the quality of features portrayed on the maps. Modeling of the generalization process has been an area of research for several years in the international cartographic community. Constraint-based generalization modeling prevailed, and it is evolving to an agent model or to other optimization models. The generalization model presented in this paper is based on constraint-based modeling. It introduces the standardization of the semantic and cartographic generalization process together with an evaluation mechanism for the assessment of the quality of the resulting cartographic data considering simultaneously the preservation of the shape of the portrayed linear and area features. For cartographers, quality management is a key factor in creating an evidence-based, reliable product. To achieve this objective, cartographers, drawing on international experience, should implement a quality policy and adopt a quality management system (QMS) as an integral part of the map production process, starting with the quality assessment of the input data and finishing with the evaluation of the final product.