bluuebunny/crossref_metadata_2025 huggingface dataset:
Total Antioxidant Capacity in Obese and Non-Obese Subjects and Its Association with Anthropo-Metabolic Markers: Systematic Review and Meta-Analysis
Authors: Anaya-Morua Wendoline , Villafan-Bernal José Rafael , Ramírez-Moreno Esther , García-Ortiz Humberto , Martínez-Portilla Raigam Jafet , Contreras-Cubas Cecilia , Martínez-Hernández Angélica , Centeno-Cruz Federico , Pedroza-Montoya Florencia Estefana , Orozco Lorena , Barajas-Olmos Francisco
Published: July 2023

The total antioxidant capacity (TAC) has been related to the development of and complications associated with chronic diseases, but its importance during obesity is not entirely clear. We conducted a systematic review and meta-analysis to clarify whether there are differences or similarities in the TAC between subjects with obesity (SO) and subjects with normal weight (NW). Following the recommendations of PRISMA and Cochrane, we performed a systematic search in the PubMed, Scopus, Web of Science, Cochrane, and PROSPERO databases, identifying 1607 studies. Among these, 22 studies were included in the final analysis, comprising 3937 subjects (1665 SO and 2272 NW) in whom serum TAC was measured, and from these 19,201 subjects, the correlation of serum TAC with anthropo-metabolic parameters was also estimated. The Newcastle–Ottawa method was used for the evaluation of the risk of bias. Using a random-effect model (REM), TAC was reduced in SO independently of age (SMD, −0.86; 95% CI −1.38 to −0.34; p = 0.0012), whereas malondialdehyde (SMD, 1.50; 95% CI 0.60 to 2.41), oxidative stress index (SMD, 1.0; 95% CI 0.16 to 1.84), and total oxidant status (SMD, 0.80; 0.22 to 1.37) were increased. There were seven significant pooled correlations of TAC with anthropometric and metabolic parameters: weight (r = −0.17), hip circumference (r= −0.11), visceral adipose index (r = 0.29), triglycerides (r = 0.25), aspartate aminotransferase (r = 0.41), alanine aminotransferase (r = 0.38), and uric acid (r = 0.53). Our results confirm a decrease in TAC and an increase in markers of oxidative stress in SO and underpin the importance of these serum biomarkers in obesity.
Korean Red Ginseng Attenuates Particulate Matter-Induced Senescence of Skin Keratinocytes
Authors: Kang Kyoung Ah , Piao Mei Jing , Fernando Pincha Devage Sameera Madushan , Herath Herath Mudiyanselage Udari Lakmini , Yi Joo Mi , Hyun Jin Won
Published: July 2023

Skin is a direct target of fine particulate matter (PM2.5), as it is constantly exposed. Herein, we investigate whether Korean red ginseng (KRG) can inhibit PM2.5-induced senescence in skin keratinocytes. PM2.5-treated human keratinocyte cell lines and normal human epidermal keratinocytes showed characteristics of cellular senescence, including flat and enlarged forms; however, KRG suppressed them in both cell types. Moreover, while cells exposed to PM2.5 showed a higher level of p16INK4A expression (a senescence inducer), KRG inhibited its expression. Epigenetically, KRG decreased the expression of the ten-eleven translocation (TET) enzyme, a DNA demethylase induced by PM2.5, and increased the expression of DNA methyltransferases suppressed by PM2.5, resulting in the decreased methylation of the p16INK4A promoter region. Additionally, KRG decreased the expression of mixed-lineage leukemia 1 (MLL1), a histone methyltransferase, and histone acetyltransferase 1 (HAT1) induced by PM2.5. Contrastingly, KRG increased the expression of the enhancer of zeste homolog 2, a histone methyltransferase, and histone deacetyltransferase 1 reduced by PM2.5. Furthermore, KRG decreased TET1, MLL1, and HAT1 binding to the p16INK4A promoter, corresponding with the decreased mRNA expression of p16INK4A. These results suggest that KRG exerts protection against the PM2.5-induced senescence of skin keratinocytes via the epigenetic regulation of p16INK4A.
Honokiol-Rich Magnolia officinalis Bark Extract Attenuates Trauma-Induced Neuropathic Pain
Authors: Borgonetti Vittoria , Galeotti Nicoletta
Published: July 2023

Neuropathic pain (NP) affects about 8% of the general population. Current analgesic therapies have limited efficacy, making NP one of the most difficult to treat pain conditions. Evidence indicates that excessive oxidative stress can contribute to the onset of chronic NP and several natural antioxidant compounds have shown promising efficacy in NP models. Thus, this study aimed to investigate the pain-relieving activity of honokiol (HNK)-rich standardized extract of Magnolia officinalis Rehder & E. Wilson bark (MOE), well known for its antioxidant and anti-inflammatory properties, in the spared nerve injury (SNI) model. The molecular mechanisms and efficacy toward neuroinflammation were investigated in spinal cord samples from SNI mice and LPS-stimulated BV2 microglia cells. MOE and HNK showed antioxidant activity. MOE (30 mg/kg p.o.) produced an antiallodynic effect in SNI mice in the absence of locomotor impairment, reduced spinal p-p38, p-JNK1, iNOS, p-p65, IL-1ß, and Nrf2 overexpression, increased IL-10 and MBP levels and attenuated the Notch signaling pathway by reducing Jagged1 and NEXT. These effects were prevented by the CB1 antagonist AM251. HNK reduced the proinflammatory response of LPS-stimulated BV2 and reduced Jagged1 overexpression. MOE and HNK, by modulating oxidative and proinflammatory responses, might represent interesting candidates for NP management.
Functional and Structural Insights into the Human PPARα/δ/γ Targeting Preferences of Anti-NASH Investigational Drugs, Lanifibranor, Seladelpar, and Elafibranor
Authors: Kamata Shotaro , Honda Akihiro , Ishikawa Ryo , Akahane Makoto , Fujita Ayane , Kaneko Chihiro , Miyawaki Saeka , Habu Yuki , Shiiyama Yui , Uchii Kie , Machida Yui , Oyama Takuji , Ishii Isao
Published: July 2023

No therapeutic drugs are currently available for nonalcoholic steatohepatitis (NASH) that progresses from nonalcoholic fatty liver via oxidative stress-involved pathways. Three cognate peroxisome proliferator-activated receptor (PPAR) subtypes (PPARα/δ/γ) are considered as attractive targets. Although lanifibranor (PPARα/δ/γ pan agonist) and saroglitazar (PPARα/γ dual agonist) are currently under investigation in clinical trials for NASH, the development of seladelpar (PPARδ-selective agonist), elafibranor (PPARα/δ dual agonist), and many other dual/pan agonists has been discontinued due to serious side effects or little/no efficacies. This study aimed to obtain functional and structural insights into the potency, efficacy, and selectivity against PPARα/δ/γ of three current and past anti-NASH investigational drugs: lanifibranor, seladelpar, and elafibranor. Ligand activities were evaluated by three assays to detect different facets of the PPAR activation: transactivation assay, coactivator recruitment assay, and thermal stability assay. Seven high-resolution cocrystal structures (namely, those of the PPARα/δ/γ-ligand-binding domain (LBD)–lanifibranor, PPARα/δ/γ-LBD–seladelpar, and PPARα-LBD–elafibranor) were obtained through X-ray diffraction analyses, six of which represent the first deposit in the Protein Data Bank. Lanifibranor and seladelpar were found to bind to different regions of the PPARα/δ/γ-ligand-binding pockets and activated all PPAR subtypes with different potencies and efficacies in the three assays. In contrast, elafibranor induced transactivation and coactivator recruitment (not thermal stability) of all PPAR subtypes, but the PPARδ/γ-LBD–elafibranor cocrystals were not obtained. These results illustrate the highly variable PPARα/δ/γ activation profiles and binding modes of these PPAR ligands that define their pharmacological actions.
Bradykinin B1 Receptor Affects Tumor-Associated Macrophage Activity and Glioblastoma Progression
Authors: Shen Ching-Kai , Huang Bor-Ren , Charoensaensuk Vichuda , Yang Liang-Yo , Tsai Cheng-Fang , Liu Yu-Shu , Lu Dah-Yuu , Yeh Wei-Lan , Lin Chingju
Published: July 2023

Bradykinin is a small active peptide and is considered an inflammatory mediator in several pathological conditions. Bradykinin exerts its effects by coupling to its receptors, including bradykinin B1 (B1R) and bradykinin B2. B1R has been implicated in the development of various cancers. Our previous study reported that B1R promoted glioblastoma (GBM) development by supporting the migration and invasion of GBM cells. However, the mechanisms underlying the effects of B1R on tumor-associated macrophages (TAMs) and GBM progression remain unknown. Accordingly, to explore the regulatory effects of B1R overexpression (OE) in GBM on tumor-associated immune cells and tumor progression, we constructed a B1R wild-type plasmid and developed a B1R OE model. The results reveal that B1R OE in GBM promoted the expression of ICAM-1 and VCAM-1—cell adhesion molecules—in GBM. Moreover, B1R OE enhanced GBM cell migration ability and monocyte attachment. B1R also regulated the production of the protumorigenic cytokines and chemokines IL-6, IL-8, CXCL11, and CCL5 in GBM, which contributed to tumor progression. We additionally noted that B1R OE in GBM increased the expression of CD68 in TAMs. Furthermore, B1R OE reduced the level of reactive oxygen species in GBM cells by upregulating heme oxygenase-1, an endogenous antioxidant protein, thereby protecting GBM cells from oxidative stress. Notably, B1R OE upregulated the expression of programmed death-ligand 1 in both GBM cells and macrophages, thus providing resistance against T-cell response. B1R OE in GBM also promoted tumor growth and reduced survival rates in an intracranial xenograft mouse model. These results indicate that B1R expression in GBM promotes TAM activity and modulates GBM progression. Therefore, B1R could be an effective target for therapeutic methods in GBM.
Parafoveal and Perifoveal Accommodation Response to Defocus Changes Induced by a Tunable Lens
Authors: Sharmin Najnin , Papadogiannis Petros , Romashchenko Dmitry , Lundström Linda , Vohnsen Brian
Published: July 2023

The accommodative response of the human eye is predominantly driven by foveal vision, but reacts also to off-foveal stimuli. Here, we report on monocular accommodation measurements using parafoveal and perifoveal annular stimuli centered around the fovea and extending up to 8° radial eccentricity for young emmetropic and myopic subjects. The stimuli were presented through a sequence of random defocus step changes induced by a pupil-conjugated tunable lens. A Hartmann–Shack wavefront sensor with an infrared beacon was used to measure real-time changes in ocular aberrations up to and including the fourth radial order across a 3 mm pupil at 20 Hz. Our findings show a significant reduction in accommodative response with increased radial eccentricity.
Study on the Internal Mechanics and Energy Characteristics of Soil under Different Failure Modes
Authors: Tang Lian-Sheng , Wang Yu-Xi
Published: July 2023

Under uniaxial compression, the soil mass may be subjected to transverse tensile splitting or swelling failure. This failure is caused by the tensile stress in the soil; that is, part of the vertical stress is converted into lateral stress. In order to investigate the factors that influence the stress transfer phenomenon, the failure mode of the soil mass can be predicted more accurately, and the internal force of the soil mass can be analyzed. This paper begins with the definition of the stress conversion coefficient and measures it by combining macroscopic mechanical properties with microscopic structure analyses. By carrying out a uniaxial compression test on a large soil sample, an equivalent tensile test was carried out according to the equivalent transverse displacement measured using the S-type tension sensor in order to explore the change law of the stress conversion coefficient. The arrangement and distribution of pores and particles at different positions in the samples before and after compression were further observed and analyzed using the SEM test to explore the formation mechanism of the stress transition phenomenon, and the following research results were obtained: (1) The stress conversion coefficient of the soil under compression is not invariable. An increase in the loading rate and a decrease in water content cause brittleness, and the stress conversion coefficient of the soil decreases. (2) Shear failure is more likely to occur in large samples of brittle soils under uniaxial compression. (3) The tensile stress in the compressed soil is caused by the invasion and extrusion of soil particles.
Quadratic Curve Fitting-Based Image Edge Line Segment Detection: A Novel Methodology
Authors: Qiao Rui , Xu Guili , Wang Ping , Cheng Yuehua , Dong Wende
Published: July 2023

In the field of computer vision, edge line segment detection in images is widely used in tasks such as 3D reconstruction and simultaneous localization and mapping. Currently, there are many algorithms that primarily focus on detecting straight line segments in undistorted images, but they do not perform well in detecting edge line segments in distorted images. To address this quandary, the present study introduces a novel method of line segment identification founded on the principles of quadratic fitting. The method proposed utilizes the inherent property of a linear projection in a three-dimensional space, whereby it appears as a quadratic curve in a distorted two-dimensional image. This approach applies an iterative estimation process to ascertain the optimal parameters of the quadratic form that aligns with the edge contour. This process is facilitated by implementing an assumption and validation mechanism. Upon deriving the optimal model, it is then employed to identify the line segments that are encompassed within the edge contour. The experimental assessment of this novel method incorporates its application to both distorted and distortion-free image datasets. The method eliminates the necessity for preliminary processing to discarding distortions, thereby making it universally applicable to both distorted and non-distorted images. In addition to this, the experimental results based on the dataset indicate that the proposed algorithm in this paper achieves an average computational efficiency that is 27 times faster than traditional ones. Thus, this research will contribute to line segment detection in computer vision.
Hyaluronic Acid as a Mechanism to Mitigate the Effects of Face Lower Third Aging in Dentistry: A Review
Authors: Martins Helena , Carpinteiro Inês , Mascarenhas Paulo , Goes Margarida , Oliveira Henrique
Published: July 2023

Aging can have a negative impact on the perioral region, affecting both appearance and self-esteem. Dentists offer various treatment options to address these changes, using surgical and non-surgical techniques. One such technique is facial filling with hyaluronic acid, a minimally invasive approach to improve the perioral region’s function and aesthetics and counteract aging effects. A literature review was conducted to collect scientific evidence on the subject, utilizing the mnemonic PI(C)O to refine the research question. The search for articles was accomplished on the EBSCOhost platform, specifically targeting those published between January 2009 and April 2023 in MEDLINE Complete, CINAHL Complete, and MedicLatina databases. Sixteen articles were carefully chosen, and the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method were followed throughout the process. The major findings reported in the selected articles suggest that using hyaluronic acid as a mechanism to mitigate the effects of face lower third aging following orofacial harmonization procedures in dentistry offers significant benefits to patients, improving the aesthetic appearance of the face, increasing patients’ self-esteem and satisfaction, and providing a better quality of life. Nevertheless, a weak evidence level was found in the selected articles due to methodological issues, highlighting the need to increase the methodological quality of future studies.
Enhanced Distributed Non-Linear Voltage Regulation and Power Apportion Technique for an Islanded DC Microgrid
Authors: Lasabi Olanrewaju , Swanson Andrew , Jarvis Leigh , Aluko Anuoluwapo , Brown Matthew
Published: July 2023

There is a growing focus on exploring direct current (DC) microgrids in traditional power grids. A key challenge in operating these microgrids is ensuring proper current distribution among converters. While conventional droop control has been used to address this issue, it requires compensating for voltage deviations in the DC bus. This paper introduces an innovative distributed secondary control approach that effectively addresses both voltage restoration and current sharing challenges within a standalone DC microgrid. The distributed secondary control proposed in this study is integrated into the microgrid’s cyber layer, enabling information sharing between controllers. This distributed approach ensures reliability, even in the event of partial communication connection failures. The controller employs a fuzzy logic control approach to dynamically determine the parameters of the secondary control, resulting in an enhanced control response. Additionally, the proposed approach can handle constant power and resistive loads without specific requirements. Employing the Lyapunov method, we have derived adequate stability conditions for the proposed controller. The performance of the controller has been assessed using MATLAB/Simulink® models and validated with real-time experimental testing performed with a SpeedgoatTM real-time machine, considering five different test cases. The results indicated that the proposed control system is robust in achieving its control objectives within a DC microgrid, exhibiting fast response and minimal oscillations.
Three-Dimensional Motion Compensation Method Based on Sparse Array Designed for Time-Division Multiplexing Multiple-Input-Multiple-Output Through-Wall Radar
Authors: Pan Jun , Liang Xiao , Wu Shiyou , Zhao Di , Yan Kun , Nie Jinliang , Hu Jianmin , Zhou Bin , Fang Guangyou
Published: July 2023

A large-aperture radar composed of a multiple-input-multiple-output (MIMO) planar array can complete 3D through-wall imaging (TWI), but the simultaneous work of the multiple transceiver channels leads to difficulties in designing the hardware. In engineering, multiple transceiver channels are usually realized by time-division multiplexing (TDM) in MIMO radar, which is called TDM MIMO radar. A time delay will be introduced when the channels are switched, which will cause high sidelobes and position deviation in the 3D imaging of moving targets, also known as range migration. This paper proposes a motion compensation algorithm based on sparse array, designed to eliminate range migration in moving targets in 3D TWI scenes. In the proposed algorithm, the coincident array elements of the equivalent array are used as the compensation channels to calculate the position difference of the target, which can correct the remaining MIMO channels. The proposed algorithm is compared with no compensation, and the reference-channel-based motion compensation algorithm (RCMCA). According to the simulation and experimental results, the proposed motion compensation algorithm can effectively eliminate sidelobes, and keep the position deviation within 0.30 m in the 3D TWI of moving targets under the TDM MIMO radar, without increasing the system complexity.
Sourdough Wheat Bread Enriched with Grass Pea and Lupine Seed Flour: Physicochemical and Sensory Properties
Authors: Cacak-Pietrzak Grażyna , Sujka Katarzyna , Księżak Jerzy , Bojarszczuk Jolanta , Dziki Dariusz
Published: July 2023

Legume seeds, such as grass pea, yellow lupine, and narrow-leaf lupine, are highly nutritious and offer a wide range of health benefits. The objective of this research was to explore the possibility of partially replacing wheat flour (at levels of 10, 15, 20, and 25%) with flour derived from these legume seeds in sourdough wheat bread and examine its impact on the physicochemical and sensory properties of the bread. The physical properties of the dough were also assessed. The substitution of wheat flour with ground legume seeds resulted in increased water absorption (from 54.1 to 63.5%) and prolonged dough development time (from 2.0 to 13.5 min). Ground lupine seeds reduced the volume of the bread and increased its crumb density, consequently making the bread harder. The most significant increase in hardness was observed when narrow-leaf lupine flour was added to the wheat flour (from 8.4 to 22.5 N). Narrow-leaf lupine had the greatest impact on enhancing the protein content in the enriched bread (from 11.5 to 20%), while yellow lupine caused the highest increase in fiber content (from 1.9 to 6.9%). The proposed additives slightly but significantly (p < 0.05) increased the antioxidant activity and phenolic content in the bread samples. Importantly, for all legume seeds, replacing up to 15% of the wheat flour allowed the production of bread with high consumer acceptability.
Multilabel Genre Prediction Using Deep-Learning Frameworks
Authors: Unal Fatima Zehra , Guzel Mehmet Serdar , Bostanci Erkan , Acici Koray , Asuroglu Tunc
Published: July 2023

In this study, transfer learning has been used to overcome multilabel classification tasks. As a case study, movie genre classification by using posters has been chosen. Six state-of-the-art pretrained models, VGG16, ResNet, DenseNet, Inception, MobileNet, and ConvNeXt, have been employed for this experiment. The movie posters have been obtained from Internet Movie Database (IMDB). The dataset has been divided using an iterative stratification technique. A sequence of dense layers has been added on top of each model and these models have been trained and fine-tuned. All the results of the models compared considered accuracy, loss, Hamming loss, F1-score, precision, and AUC metrics. When the metrics used were evaluated, the most successful result regarding accuracy has been obtained from the modified DenseNet architecture at 90%. Also, the ConvNeXt, which is the newest model among all, performed quite satisfactorily, reaching over 90% accuracy. This study uses an iterative stratification method to split an unbalanced dataset which provides more reliable results than the classical splitting method which is the common method in the literature. Also, the feature extraction capabilities of the six pretrained models have been compared. The outcome of this study shows promising results regarding multilabel classification. As for future work, it is planned to enhance this study by using natural language processing and ensemble methods.
Neural Network-Based Bilingual Lexicon Induction for Indonesian Ethnic Languages
Authors: Resiandi Kartika , Murakami Yohei , Nasution Arbi Haza
Published: July 2023

Indonesia has a variety of ethnic languages, most of which belong to the same language family: the Austronesian languages. Due to the shared language family, words in Indonesian ethnic languages are very similar. However, previous research suggests that these Indonesian ethnic languages are endangered. Thus, to prevent that, we propose the creation of a bilingual dictionary between ethnic languages, using a neural network approach to extract transformation rules, employing character-level embedding and the Bi-LSTM method in a sequence-to-sequence model. The model has an encoder and decoder. The encoder reads the input sequence character by character, generates context, and then extracts a summary of the input. The decoder produces an output sequence wherein each character at each timestep, as well as the subsequent character output, are influenced by the previous character. The first experiment focuses on Indonesian and Minangkabau languages with 10,277 word pairs. To evaluate the model’s performance, five-fold cross-validation was used. The character-level seq2seq method (Bi-LSTM as an encoder and LSTM as a decoder) with an average precision of 83.92% outperformed the SentencePiece byte pair encoding (vocab size of 33) with an average precision of 79.56%. Furthermore, to evaluate the performance of the neural network model in finding the pattern, a rule-based approach was conducted as the baseline. The neural network approach obtained 542 more correct translations compared to the baseline. We implemented the best setting (character-level embedding with Bi-LSTM as the encoder and LSTM as the decoder) for four other Indonesian ethnic languages: Malay, Palembang, Javanese, and Sundanese. These have half the size of input dictionaries. The average precision scores for these languages are 65.08%, 62.52%, 59.69%, and 58.46%, respectively. This shows that the neural network approach can identify transformation patterns of the Indonesian language to closely related languages (such as Malay and Palembang) better than distantly related languages (such as Javanese and Sundanese).
Experimental Study on the Properties of Simulation Materials for an Aquifuge for a Fluid–Solid Coupling Physical Similarity Model Test
Authors: Shen Xiong , Li Jizu , Feng Guorui , Zhao Dekang , Liu Qin
Published: July 2023

In order to meet the special requirements of physical and mechanical strength and high water resistance of similar material in aquifuge (aquitard) strata for the testing of the fluid–solid coupling physical similarity model for a mine water inrush. Based on the similarity theory of solid–fluid coupling in equivalent homogeneous continuous media, a new type of aquifuge simulation material was developed, which used river sand as the skeleton of the material, gypsum and calcium carbonate powder as the auxiliary cementing agent, and paraffin wax and petroleum jelly as the waterproof cementing agent. Similar materials of aquifuge (aquitard) strata are created according to a specific proportion of the components and an established technological process. Through orthogonal tests and systematic analysis, the influence mechanism of the different proportions of the raw materials on the variation of the physical–mechanical strength and hydraulic parameters is studied in this paper. The experimental results demonstrate when the mass ratio of solid material to liquid material is 8:1 and 9:1, the mass ratios of river sand, calcium carbonate, and gypsum is 30:3:7, 30:3:7, and 50:3:7, and the mass ratios of paraffin wax to petroleum jelly are 1:2, 1:1, and 2:1, respectively. The controlled ranges of uniaxial compressive strength, softening coefficient, and permeability coefficient of the similar materials are 16.99–426.47 kPa, 0.660–0.805, and 1.01 × 10−7–8.34 × 10−7 cm/s, respectively. The above data show that the materials have the characteristics of low strength, controllable water absorption, and low permeability.
Hybrid Graph Models for Traffic Prediction
Authors: Chen Renyi , Yao Huaxiong
Published: July 2023

Obtaining accurate road conditions is crucial for traffic management, dynamic route planning, and intelligent guidance services. The complex spatial correlation and nonlinear temporal dependence pose great challenges to obtaining accurate road conditions. Existing graph-based methods use a static adjacency matrix or a dynamic adjacency matrix to aggregate spatial information between nodes, which cannot fully represent the topological information. In this paper, we propose a Hybrid Graph Model (HGM) for accurate traffic prediction. The HGM constructs a static graph and a dynamic graph to represent the topological information of the traffic network, which is beneficial for mining potential and obvious spatial correlations. The proposed method combines a graph neural network, convolutional neural network, and attention mechanism to jointly extract complex spatial–temporal features. The HGM consists of two different sub-modules, called spatial–temporal attention module and dynamic graph convolutional network, to fuse complex spatial–temporal information. Furthermore, the proposed method designs a novel gated function to adaptively fuse the results from spatial–temporal attention and dynamic graph convolutional network to improve prediction performance. Extensive experiments on two real datasets show that the HGM outperforms comparable state-of-the-art methods.
Porous Carbon Materials Based on Blue Shark Waste for Application in High-Performance Energy Storage Devices
Authors: Brandão Ana T. S. C. , State Sabrina , Costa Renata , Enache Laura-Bianca , Potorac Pavel , Vázquez José A. , Valcarcel Jesus , Silva A. Fernando , Enachescu Marius , Pereira Carlos M.
Published: July 2023

The scientific community’s interest in developing sustainable carbon materials from biomass waste is increasing steadily, responding to the need to reduce dependence on fossil fuels. Every day, different biomass sources are suggested for obtaining porous carbon materials with characteristics for application in different areas. Porous carbon materials with a high specific surface area are a subject of interest for application in energy storage devices. This work reports the use of blue shark chondroitin sulfate and gelatine as precursors for developing porous carbon materials for energy storage devices. Commercial chondroitin sulfate was used for comparison. The porous carbons obtained in this study underwent various characterization techniques to assess their properties. A BET surface area analyzer measured the specific surface area and pore size. Additionally, scanning electron microscopy (SEM) coupled with energy dispersive X-ray analysis (EDX), a high resolution-scanning transmission electron microscope (HR-STEM), Raman spectroscopy, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) were employed to examine the morphology, composition, and structure of the carbons. A modified glassy carbon (GC) electrode was used as the working electrode for the electrochemical characterization. Cyclic voltammetry and galvanostatic charge/discharge techniques were employed with ethaline, an environmentally friendly and sustainable electrolyte based on choline chloride, to assess the electrochemical performance. Furthermore, the most promising samples were subjected to ball-milling to investigate the impact of this process on surface area and capacitance. Blue shark chondroitin sulfate-based carbon presented a specific surface area of 135.2 m2 g−1, compared to 76.11 m2 g−1 of commercial chondroitin sulfate, both carbonized for 1 h at 1000 °C. Blue shark gelatine presented a specific surface area of 30.32 m2 g−1. The associated specific capacitance of these three samples is 40 F g−1, 25 F g−1, and 7 F g−1. Ball-milling on these samples increased the specific surface area and capacitance of the three studied samples with different optimal milling times. This study presents the novel utilization of carbon materials derived from blue shark (with and without ball-milling) through a one-step carbonization process. These carbon materials were combined with an environmentally friendly DES electrolyte. The aim was to explore their potential application in energy storage devices, representing the first instance of employing blue shark-based carbon materials in this manner.
EEM Fluorescence Spectroscopy Coupled with HPLC-DAD Analysis for the Characterization of Bud Derivative Dietary Supplements: A Preliminary Introduction to GEMMAPP, the Free Data-Repository from the FINNOVER Project
Authors: Turrini Federica , Donno Dario , Grasso Federica , Mustorgi Eleonora , Beccaro Gabriele Loris , Guido Maddalena , Fior Teresa , Grilli Massimo , Pittaluga Anna , Boggia Raffaella
Published: July 2023

Bud derivatives (BDs) represent a category of botanicals obtained by macerating the meristematic tissues (buds or young sprouts) of plants; widely used since ancient times in complementary medicine, they remain poorly investigated to date. In this study, a contribution is made toward the identification of the correct “a posteriori” attribution of the botanical species in commercial BDs, which is very important for ensuring the quality and safety of these natural products. Excitation–emission matrix (EEM) fluorescence spectroscopy proved to be a rapid, non-destructive and low-cost analytical instrument for providing a preliminary qualitative characterization of the BDs, allowing for the identification of specific spectral regions related to flavonol compounds and cinnamic and benzoic acids, in agreement with the targeted chromatographic analysis (HPLC-DAD), which completely defined a phytochemical profile for each BD considered. This information will be implemented in the first web application for the recognition of vegetable buds, named GEMMAPP, which was designed by the Authors and is proposed as a tool and future scientific data repository for providing information about the main, typical BDs of the France–Italy Alcotra territory.
Trust Model of Privacy-Concerned, Emotionally Aware Agents in a Cooperative Logistics Problem
Authors: Carbo Javier , Molina Jose Manuel
Published: July 2023

In this paper, we propose a trust model to be used in a hypothetical mixed environment where humans and unmanned vehicles cooperate. We address the inclusion of emotions inside a trust model in a coherent way to investigate the practical approaches to current psychological theories. The most innovative contribution of this work is the elucidation of how privacy issues play a role in the cooperation decisions of the emotional trust model. Both emotions and trust were cognitively modeled and managed with the beliefs, desires and intentions (BDI) paradigm in autonomous agents implemented in GAML (the programming language of the GAMA agent platform), that communicate using the IEEE FIPA standard. The trusting behavior of these emotional agents was tested in a cooperative logistics problem wherein agents have to move objects to destinations and some of the objects and places are associated with privacy issues. Simulations of the logistic problem show how emotions and trust contribute to improving the performance of agents in terms of both time savings and privacy protection.
Review and Analysis of Existing Approaches to Investigate Property Degradation of Phase Change Materials and Development of a New Systematic Approach
Authors: Mehling Harald
Published: July 2023

With increasing commercial success of PCM, the long-term development of properties becomes more important. It has been investigated already for decades in a variety of ways and a wide range of testing conditions. Previous reviews concluded that further work toward standardization of testing is needed. In a desktop study, the current approach to testing was analyzed. It is shown that standardization should not mean to always test with the same methods using the same conditions, e.g., as different applications impose different conditions. Instead, testing should be tailored to the individual case. For this, a new, systematic approach was developed. It identifies first the basic functions and related properties that might be subject to testing, e.g., with a specific application in mind, and then gives an approach to find the degradation effects and underlying mechanisms to allow tailoring and optimizing test procedures. As an example, the approach is applied to the function of heat storage. Here, a new degradation effect was identified, and for degradation by phase separation, it is shown by an example that it could even be reversed at suitable conditions. Therefore, tailoring testing conditions to the individual case is needed. Deeper knowledge of degradation mechanisms is required, so further R&D is suggested.
A Novel Deep Dense Block-Based Model for Detecting Alzheimer’s Disease
Authors: Çelebi Selahattin Barış , Emiroğlu Bülent Gürsel
Published: July 2023

Alzheimer’s disease (AD), the most common form of dementia and neurological disorder, affects a significant number of elderly people worldwide. The main objective of this study was to develop an effective method for quickly diagnosing healthy individuals (CN) before they progress to mild cognitive impairment (MCI). Moreover, this study presents a unique approach to decomposing AD into stages using machine-learning architectures with the help of tensor-based morphometric image analysis. The proposed model, which uses a neural network built on the Xception architecture, was thoroughly assessed by comparing it with the most recent convolutional neural network (CNN) models described in the literature. The proposed method outperformed the other models in terms of performance, achieving an impressive average classification accuracy of 95.81% using the dataset. It also had very high sensitivity, specificity, accuracy, and F1 scores, with average scores of 95.41%, 97.92%, 95.01%, and 95.21%, respectively. In addition, it showed a superior classification ability compared to alternative methods, especially for MCI estimation, as evidenced by a mean area under the ROC curve (AUC) of 0.97. Our study demonstrated the effectiveness of deep-learning-based morphometric analysis using brain images for early AD diagnosis.
Combined Effects of Different LED Light Recipes and Slow-Release Fertilizers on Baby Leaf Lettuce Growth for Vertical Farming: Modeling through DoE
Authors: Barbieri Francesco , Barbi Silvia , Bertacchini Alessandro , Montorsi Monia
Published: July 2023

The modern agriculture system based on open-field crops requires a lot of energy and resources in terms of soil, water, and chemicals. Vertical farming (VF) systems could be a viable alternative for some types of cultivation that are receiving interest thanks to their high modularity, optimized water and nutrients use, and LEDs employment as an energy-efficient light source. However, VF design and installation are expensive and require well-tailored optimization depending on the specific crop to increase its competitiveness. This work analyzed the effects of different combinations of NPK (nitrogen-phosphorus-potassium) slow-release fertilizers and LED-based light recipes on the growth of baby leaf lettuce (Lactuca sativa L.), taking advantage of the Design of Experiments (DoE) methodology. The type of slow-release fertilizer, its quantity measured as the number of aggregates from 0 to 6, and the type of light recipe were considered as input factors, and their possible influence on the growth of lettuce (in terms of morphological parameters) in a controlled indoor farming system was measured. Results suggest that using higher fertilizer inputs equal to six aggregates leads to an increase of average leaf area equal to 46% (from 13.00 cm2 to 19.00 cm2), while the fresh weight of lettuce increases by 65% (from 1.79 g to 2.96 g). However, the height of plants also depends on the combination of the light recipes. In particular, the separate coupling of higher inputs of two fertilizers and light recipes leads to an increase in the height of lettuce equal to 33% (from 6.00 cm to 8.00 cm).
Study on the Creep of Damage-Containing Anthracite: Theory and Experiment
Authors: Li Gang , Yan Guochao , Kong Shaoqi , Bai Xuyang , Du Chaofei , Li Jiajun , Zhang Jiawei
Published: July 2023

Fractal derivatives characterize the accelerated creep phase of the creep process. In this study, based on the fractal order theory, the integer-order derivatives are defined from the spatio-temporal self-similarity phenomenon of the dynamic process using the scale change method, and the viscoplastic model is improved to establish a new creep instantonal model with damage to describe the complete creep phase of anthracite. The effects of damage variables on initial and accelerated creep were investigated by performing graded-loading creep tests. Based on the experimental data, inversions of the model-related parameters were performed, and parameter sensitivities were analyzed. The results show that the proposed model can better characterize the complete creep process of anthracite coal, which verifies the correctness and rationality of the model. The damage content affects the initial and accelerated creep strain under different loading levels, and a specific functional relationship exists between them. The study’s findings can provide some reference material for the stability control of anthracite affected by disturbing stresses.
Monitoring Ground Displacement in Mining Areas with Time-Series Interferometric Synthetic Aperture Radar by Integrating Persistent Scatterer/Slowly Decoherent Filtering Phase/Distributed Scatterer Approaches Based on Signal-to-Noise Ratio
Authors: Wang Zhiwei , Li Wenhui , Zhao Yue , Jiang Aihui , Zhao Tonglong , Guo Qiuying , Li Wanqiu , Chen Yang , Ren Xiaofang
Published: July 2023

During the interferometric synthetic aperture radar (InSAR)-based ground displacement monitoring in mining areas, the overlying land is mainly covered by low vegetation and arable land, which makes interferograms acquired by InSAR techniques easily susceptible to decorrelation, resulting in the quantity and density of highly coherent points (CPs) are not enough to reflect the spatial location and spatio-temporal evolution process of ground displacement, which is hardly meeting requirements of high-precision ground displacement monitoring. In this study, we developed an approach for monitoring ground displacement in mining areas by integrating Persistent Scatterer (PS), Slowly Decoherent Filtering Phase (SDF), and Distributed Scatterer (DS) based on signal-to-noise ratio (SNR) to increase the spatial density of CPs. A case study based on a mining area in Heze was carried out to verify the reliability and feasibility of the proposed method in practical applications. Results showed that there were four significant displacement areas in the study area and the quantity of CPs acquired by the proposed method was maximum 6.7 times that of conventional PS-InSAR technique and maximum 2.3 times that of SBAS-InSAR technique. The density of CPs acquired by the proposed method increased significantly. The acquired ground displacement information of the study area was presented in more detail. Moreover, the monitoring results were highly consistent with ground displacement results extracted by PS-InSAR and SBAS-InSAR methods in terms of displacement trends and magnitudes.
Obtaining, Characterization and Applications of Advanced Materials
Authors: Sandu Ion
Published: July 2023

This special issue focused on scientific works in the field of obtaining, characterization and recent applications of advanced materials, protective films, nanomaterials with multiple uses, including medical, heritage artefact conservation science and civil and industrial engineering [...]
An Improved AoT-DCGAN and T-CNN Hybrid Deep Learning Model for Intelligent Diagnosis of PTCs Quality under Small Sample Space
Authors: Ma Zihan , Chen Yuxiang , Fan Yu , He Xiaohai , Luo Wei , Shu Jun
Published: July 2023

The intelligent diagnosis of premium threaded connections (PTCs) is vital for ensuring the robust and leak-proof performance of tubing under high-temperature, high-pressure, acidic gas conditions. However, achieving accurate diagnostic results necessitates a substantial number of PTCs curves under diverse make-up conditions, presenting considerable challenges in practical industrial detection. In this study, we introduce an end-to-end classification model, which combines an asynchronously optimized two-dimensional deep convolutional generative adversarial network (AoT-DCGAN) and a two-dimensional convolutional neural network (T-CNN), designed to enhance the classification performance under small sample size. Our proposed method first leverages AoT-DCGAN to identify the distribution patterns of the original samples and generate synthetic counterparts. Concurrently, we implement a novel weight optimization strategy, termed asynchronous optimization (AO), to alleviate the issue of gradient vanishing during the generator’s optimization phase. Following this, a novel T-CNN model is devised and trained on the enlarged dataset to automate the classification of PTCs curves. The performance evaluation of our method, based on recall, specificity, F1-score, precision values, and confusion matrices at varying data augmentation ratios, demonstrates that the model’s classification capabilities are enhanced as the dataset size escalates, peaking at a dataset size of 1200. Moreover, given the same training set, the T-CNN model outperforms traditional machine learning and deep learning models, achieving classification accuracies of up to 95.9%, 95.5%, and 96.7% for the AC, ATI, and NDT curves, respectively. Lastly, it was confirmed that applying asynchronous optimization in the DCGAN training process results in a more consistent decline in the loss function.
A Method Based on an Autoencoder for Anomaly Detection in DC Motor Body Temperature
Authors: Demircioğlu Emine Hümeyra , Yılmaz Ersen
Published: July 2023

Anomaly detection has an important role in industrial systems. Abnormal situations occurring in a system cause anomalies, and the anomalies reduce system performance over time, and may also make the system malfunction. Therefore, the correct and timely detection of anomalies is of critical importance for predictive maintenance. In this study, an autoencoder-based method is proposed for anomaly detection in DC motor body temperature. The performance of the method was examined on a dataset that was created specifically for this study. In the experiments, the three-sigma outlier method was also applied on the same dataset for the same purpose and its performance results are used for comparison. The performance results of both methods are represented in terms of three measures, namely, accuracy, recall, and precision. The experimental study showed that the proposed method achieved over 96% ratios for all three measures, and it can be successfully used for anomaly detection in DC motor body temperature. Additionally, it can be concluded that the proposed system can be preferred for anomaly detection in time series data collected from different types of sensors when the performance results are taken into consideration.
Hydro–Mechanical Behaviour of a Rainfall-Induced Landslide by Instrumental Monitoring: Landslide–Rainfall Threshold of the Western Black Sea Bartin Region of Türkiye
Authors: Taskiran Taha , Alli Serdar , Yilmaz Yuksel
Published: July 2023

Bartin City is located in the Western Black Sea Region of Türkiye, where rainfall-induced landslides are more frequently observed. Although it is known that many landslides are induced by rainfall, there is limited knowledge regarding how rainfall triggers these landslides in the city. To clarify the triggering mechanisms of rainfall-induced landslides, a detailed field monitoring program was performed on a chosen area to represent landslides in Bartin. The instrumentation included the measurements of site suction, volumetric water content, groundwater level, and rainfall amount over a period of two years. Various stability analyses were performed regarding pore pressures after both transient flow infiltration analysis and site-measured suction values. The rainfall intensity–duration thresholds were obtained for both dry and wet periods as a result of the numerical analyses performed by means of parameters obtained from field monitoring. The results show that the wet period conditions create more critical conditions before failure compared to the dry period conditions, so landslides occur more easily in wet periods. According to the landslide–rainfall threshold relations, landslide-risk limits are reached if the rainfall intensity is over 10 mm/h for the dry periods and lasts between 0.85 h and 17 h depending on the saturated hydraulic conductivity of the soil. When the rainfall intensities are less than 10 mm/h, longer rainfall durations are needed for a landslide to occur. For the wet periods, landslide-risk situations are encountered if the rainfall intensity over 1 mm/h continues for 0.36 h–3.67 h, depending on the saturated hydraulic conductivities.
Luminescent Materials: Synthesis, Characterization and Applications
Authors: Rodrigues Joana
Published: July 2023

Luminescent materials are capable of transforming certain types of energy into electromagnetic radiation, which means that in response to a specific stimulus, these materials emit light typically within the ultraviolet (UV) to the infrared (IR) spectral region [...]