bluuebunny/crossref_metadata_2025 huggingface dataset:
Sensor-Based Fertigation Management Enhances Resource Utilization and Crop Performance in Soilless Strawberry Cultivation
Authors: Bonelli Lucia , Montesano Francesco Fabiano , D’Imperio Massimiliano , Gonnella Maria , Boari Angela , Leoni Beniamino , Serio Francesco
Published: February 2024

The use of wireless sensors for real-time sensing of substrate water status and electrical conductivity could be an effective tool for precision irrigation management in soilless cultivation. In this research, the effects of timer-based (TB) compared to smart sensor-based irrigation (SB) were investigated. The highest consumption of fertilizers and water were recorded in TB, with nutrient solution and total applied water savings of 38% and 26%, respectively, in SB. The highest yield was obtained in SB treatment, with a total and marketable yield decrease of 7% in TB, with no differences in terms of the total soluble solids content, dry matter, firmness, juice pH and titratable acidity of the strawberry fruits. The higher yield, combined with water and nutrient saving in SB, allowed water use efficiency (fresh weight of marketable fruits per liter of total water applied) to be increased by 46% and nutrient productivity (fresh weight of marketable product per gram of nutrient supplied via nutrient solution) by 74%. The study confirms that sensor-based, compared to empiric fertigation management, ameliorates the sustainability of open, free-drain, soilless cultivation of strawberry, leading to better resource use without compromising crop performance and fruit quality.
Endometrial Microbiome and Its Correlation to Female Infertility: A Systematic Review and Meta-Analysis
Authors: Foteinidou Panagiota , Exindari Maria , Chatzidimitriou Dimitrios , Gioula Georgia
Published: February 2024

The endometrial cavity was considered sterile until the second half of the 20th century. Through modern technological advances and the sequencing of the bacterial 16S rRNA gene, it was proven that the area possesses its own unique microbiome, which can be categorised into two types, Lactobacillus-dominant (LD, with a Lactobacillus spp. abundance percentage greater than 90%) and non-Lactobacillus-dominant (non-LD, with a Lactobacillus spp. abundance percentage smaller than 90%), with other species like Bifidobacterium, Gardnerella, Prevotella, and Streptococcus also being prominent. The aim of this study was to investigate the possible correlation of the endometrial microbiome to female infertility, through the identification and appraisal of studies published in the databases PubMed, Web of Science, and Scopus. Moreover, 12 studies met the research criteria, including the analysis of endometrial fluid or tissue samples from infertile women through PCR, culturomics-based, or NGS methods. According to most of these studies, a eubiotic LD-type microbiome seems to be best for maximising endometrial receptivity and pregnancy chances, whereas a dysbiotic non-LD-type microbiome, with increased α-diversity and a higher number of pathogens, has a harmful effect. There were few studies that presented contradictory results without, however, a satisfactory explanation. Thus, more time and a greater number of studies are required to clarify contradictions and achieve more certain results.
The Effects of Occupation, Education and Dwelling Place on Attitudes towards Animal Welfare in China
Authors: Carnovale Francesca , Xiao Jin , Shi Binlin , Arney David R. , Phillips Clive J. C.
Published: February 2024

Attitudes to animal welfare are not understood well in China, the country with the highest output of farm animals in the world. We surveyed attitudes of the public around China using a team of researchers to conduct individual interviews, with 1301 respondents in total. Contrary to results obtained in several other countries, high school leavers were more concerned about animal welfare than those who had obtained a university degree. We speculate that this may reflect the labour market currently existing in China, with limited opportunities for graduates. Scientists were less supportive, and artists more supportive, of good animal welfare. Urban dwellers were more concerned about animal welfare than rural residents, with village residents in the middle, which confirmed our theory that such a difference prevails in developing countries, where a large proportion of the rural population are involved in agriculture. It is concluded that education level, occupation and living place all have pronounced influences on attitudes to animal welfare in China, some of which follow international trends.
Improving the Efficiency of CRISPR Ribonucleoprotein-Mediated Precise Gene Editing by Small Molecules in Porcine Fibroblasts
Authors: Zhao Yunjing , Li Xinyu , Liu Chang , Jiang Chaoqian , Guo Xiaochen , Xu Qianqian , Yin Zhi , Liu Zhonghua , Mu Yanshuang
Published: February 2024

The aim of this study was to verify whether small molecules can improve the efficiency of precision gene editing using clustered regularly interspaced short palindromic repeats (CRISPR) ribonucleoprotein (RNP) in porcine cells. CRISPR associated 9 (Cas9) protein, small guide RNA (sgRNA), phosphorothioate-modified single-stranded oligonucleotides (ssODN), and different small molecules were used to generate precise nucleotide substitutions at the insulin (INS) gene by homology-directed repair (HDR) in porcine fetal fibroblasts (PFFs). These components were introduced into PFFs via electroporation, followed by polymerase chain reaction (PCR) for the target site. All samples were sequenced and analyzed, and the efficiencies of different small molecules at the target site were compared. The results showed that the optimal concentrations of the small molecules, including L-189, NU7441, SCR7, L755507, RS-1, and Brefeldin A, for in vitro-cultured PFFs’ viability were determined. Compared with the control group, the single small molecules including L-189, NU7441, SCR7, L755507, RS-1, and Brefeldin A increased the efficiency of HDR-mediated precise gene editing from 1.71-fold to 2.28-fold, respectively. There are no benefits in using the combination of two small molecules, since none of the combinations improved the precise gene editing efficiency compared to single small molecules. In conclusion, these results suggested that a single small molecule can increase the efficiency of CRISPR RNP-mediated precise gene editing in porcine cells.
Variants in CLCN1 and PDE4C Associated with Muscle Hypertrophy, Dysphagia, and Gait Abnormalities in Young French Bulldogs
Authors: Shelton G. Diane , Mickelson James R. , Friedenberg Steven G. , Cullen Jonah N. , Graham Karina , Carpentier Missy C. , Guo Ling T. , Minor Katie M.
Published: February 2024

(1) Background: Muscle hypertrophy, swallowing disorders, and gait abnormalities are clinical signs common to many muscle diseases, including muscular dystrophies, non-dystrophic myotonias, genetic myopathies associated with deficiency of myostatin, and acquired inflammatory myopathies. Here, we investigated underlying causes of this triad of clinical signs in four young French bulldogs via muscle histopathology coupled with whole genome and Sanger sequencing. (2) Methods: Dogs were evaluated by veterinary clinical internists and neurologists, and biopsies were obtained for histopathological diagnosis. DNA was submitted for whole genome sequencing, followed by bioinformatics evaluation and confirmation of variants via Sanger sequencing in two cases. (3) Results: Two novel variants were identified. The first, found in two related French bulldogs, was a homozygous variant in the chloride channel gene CLCN1 known to cause non-dystrophic congenital myotonia, and the second, found in an unrelated French bulldog, was a heterozygous variant in the cAMP phosphodiesterase gene PDE4C, which is the major phosphodiesterase expressed in skeletal muscle and may play a role in decreasing muscle atrophy. An underlying molecular basis in one other case has not yet been identified. (4) Conclusions: Here, we identified two novel variants, one in the CLCN1 and one in the PDE4C gene, associated with clinical signs of muscle hypertrophy, dysphagia, and gait abnormalities, and we suggested other bases of these phenotypes in French bulldogs that are yet to be discovered. Identification of genes and deleterious variants associated with these clinical signs may assist breeders in improving the overall health of this very popular breed and may lead to the identification of new therapies to reverse muscle atrophy in people and animals with neuromuscular diseases.
Coming Home, Staying Home: Adopters’ Stories about Transitioning Their New Dog into Their Home and Family
Authors: Thumpkin Eileen , Pachana Nancy , Paterson Mandy
Published: February 2024

Published research estimates shelter dogs’ post-adoption returns at 7–20%, with a significant percentage of these occurring in the first month post-adoption. To better understand factors that contribute to the success or failure of long-term rehoming outcomes, this study sought to understand post-adoption challenges up to four years post-adoption, targeting dogs identified as more likely to be returned. Thirty-one adopters participated in semi-interviews. Thematic analysis of their responses yielded three themes: (1) The adoption process takes time and requires patience; (2) Building trust and learning limits are essential to lasting adoptive relationships; and (3) Human–dog relationships are idiosyncratic because they involve unique individuals. These results have potential application in programs designed to guide adopters and dogs through a successful adoption process. Access to real-life adoption stories, such as those uncovered in this study, might help new adopters develop reasonable expectations and learn from others’ experiences as they work to develop lasting relationships with their dogs.
Spatiotemporal Niche Separation among Passeriformes in the Halla Mountain Wetland of Jeju, Republic of Korea: Insights from Camera Trap Data
Authors: Jeong Young-Hun , Choi Sung-Hwan , Banjade Maniram , Jin Seon-Deok , Park Seon-Mi , Kunwar Binod , Oh Hong-Shik
Published: February 2024

This study analyzed 5322 camera trap photographs from Halla Mountain Wetland, documenting 1427 independent bird sightings of 26 families and 49 species of Passeriformes. Key observations include morning activities in Cyanoptila cyanomelana and Horornis canturians and afternoon activity in Muscicapa dauurica and Phoenicurus auroreus. Wetlands were significantly preferred (P_i = 0.398) despite their smaller area, contrasting with underutilized grasslands (P_i = 0.181). Seasonal activity variations were notable, with overlap coefficients ranging from 0.08 to 0.81 across species, indicating diverse strategies in resource utilization and thermoregulation. Population density was found to be a critical factor in habitat usage, with high-density species showing more consistent activity patterns. The study’s results demonstrate the ecological adaptability of Passeriformes in the Halla Mountain Wetland while highlighting the limitations of camera trapping methods. These limitations include their fixed field of view and intermittent recording capability, which may not fully capture the spectrum of complex avian behaviors. This research underlines the need for future studies integrating various methodologies, such as direct observation and acoustic monitoring, to gain a more comprehensive understanding of avian ecology.
Effect of Myrtus communis L. Plant Extract as a Milk Supplement on the Performance, Selected Blood Parameters and Immune Response of Holstein Calves
Authors: Uyarlar Cangir , Rahman Abdur , Ozcinar Umit , Cetingul İbrahim Sadi , Gultepe Eyup Eren , Bayram Ismail
Published: February 2024

This research aimed to understand the effects of adding myrtle plant extract obtained from its leaves (MPEL) and roots (MPER) to the milk fed to suckling female Holstein calves, focusing on performance, reproduction, selected blood parameters and immune response. The 50 Holstein female calves, one week of age, were divided into five groups: one group received no plant extract (Control), while the others were supplemented with myrtle plant extracts at doses of 25 mL/day leaf extract (MPEL-25), 25 mL/day root extract (MPER-25), 50 mL/day leaf extract (MPEL-50) and 50 mL/day root extract (MPER-50) for each calf in each treatment group. The extracts were given along with the milk to the experimental groups for 60 days, and for an additional 12 days post-weaning. The results reveal that the feed consumption and live weights increased significantly. Significantly higher leukocyte counts were observed in the 50 mL/head × day myrtle groups, and a higher IgG concentration was also noted in the MPER-50 group compared to the other groups. The serum non-esterified fatty acid (NEFA) concentration significantly decreased in the MPEL-50 and MPER-50 groups, whereas the betahyrdoxy butyric acid (BHBA) concentration increased and the serum glucose concentration significantly decreased with myrtle supplementation. In conclusion, it was determined that the performance, immune system and negative energy balance compensation of female Holstein calves were positively affected by administering extracts obtained from the leaves and roots of the Myrtus communis L. plant at dose levels of 25 and 50 mL/head × day for 72 days, without causing any side effects.
Updating the Status quo on the Eco-Friendly Approach for Antioxidants Recovered from Plant Matrices Using Cloud Point Extraction
Authors: Travičić Vanja , Cvanić Teodora , Šovljanski Olja , Erceg Tamara , Perović Milica , Stupar Alena , Ćetković Gordana
Published: February 2024

The concepts of “green chemistry” are gaining importance in the agri-food sector due to the need to minimize pollution from toxic chemicals, improve the safety and sustainability of industrial processes, and provide “clean-labeled products” required by consumers. The application of the cloud point extraction (CPE) is considered a promising alternative to conventional organic solvents. In the CPE, the separation of compounds from the bulk solution occurs by adding a surfactant (either non-ionic or ionic). When the solution is heated to or above a critical temperature, referred to as the cloud point, two phases are formed—micellar and aqueous. Recently, the horizons of the traditional CPE have been increasingly expanding by improved procedures and integration with other techniques, such as the microwave- and ultrasonic-assisted extraction. This article provides an updated overview of the theory and research articles on the CPE from 2018 to 2023 and critically discusses the issues relevant to the potential applicability of the CPE as a promising and green technique for antioxidants recovered from plant materials. Finally, some future perspectives and research needs for improved CPE are presented.
Bus Rescheduling for Long-Term Benefits: An Integrated Model Focusing on Service Capability and Regularity
Authors: Deng Sen , He Zhaocheng , Zhong Jiaming , Xie Jiemin
Published: February 2024

Unplanned disruptions, such as vehicle breakdowns, in a public transportation system can lead to severe delays and even service interruptions, preventing the successful implementation of subsequent plans and the overall stability of transit services. A common solution to address such issues is implementing a bus bridging service using an experience-based response strategy, involving the deployment of spare buses to continue affected services. However, with this approach, it becomes impractical and challenging to generate a feasible and rational rescheduling scheme for the remaining transit services when spare buses are insufficient or widespread disruptions occur. In response to this challenge, we propose an innovative model that integrates service capability and regularity, aiming to minimize rescheduling costs through timetable adjustments and scheduling reassignments. We apply dynamic programming to comprehensively consider the hysteresis effects of disruptions and achieve a long-term optimal rescheduling scheme. To efficiently solve the proposed model, the large neighborhood search algorithm is improved by incorporating operational rules. Finally, several experiments are conducted under an actual transit operation scenario in Shenzhen. The results demonstrate that our method significantly reduces trip cancellations and, simultaneously, diminishes the increase in the departure interval resulting from the adjusted schedule by 23.27%.
Utilizing Differences in Mercury Injection Capillary Pressure and Nuclear Magnetic Resonance Pore Size Distributions for Enhanced Rock Quality Evaluation: A Winland-Style Approach with Physical Meaning
Authors: Gu Zheng , Wang Shuoshi , Guo Ping , Zhao Wenhua
Published: February 2024

Pore structure is a fundamental parameter in determining the hydrocarbon storage capacity and flow characteristics of a reservoir. Mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) are two commonly utilized techniques for characterizing rock pore structures. However, current studies indicate that disparities in testing methodologies due to distinct physical characteristics lead to a partial misalignment in pore size distributions. We conducted MICP (dynamic) and NMR (static) experiments on eight tight sandstone and eight shale samples and proposed a method to utilize information from the differences in MICP and NMR pore size distributions, aiming to enhance the accuracy of rock quality analysis. We observed that in rock cores where large pores are interconnected with smaller pore throats, MICP tends to overestimate the proportion of these smaller pores and underestimate the larger ones. Furthermore, we integrated information from both dynamic and static experimental processes based on physical significance and found that the fitting accuracy of the newly proposed method is superior to the Winland r35 equation. Compared to the Winland r35 equation, our new method significantly improves fitting accuracy, increasing the R-squared value from 0.46 to 0.93 in sandstones and from 0.80 to 0.87 in shales. This represents a potential high-precision, comprehensive tool for rock quality analysis, offering a new perspective for an in-depth understanding of rock properties.
Hybrid Precoding Design for Wireless Fading Channels
Authors: Seo Bangwon
Published: February 2024

Precoding techniques are widely used to eliminate interference between multiple user signals in a wireless fading channel environment. The linear MMSE precoding technique, one of the most widely used techniques so far, has low computational complexity but has the disadvantage of relatively poor symbol error rate (SER) performance. The symbol-level precoding (SLP) technique, on which much research has been conducted recently, has excellent SER performance but has the disadvantage of being too computationally complex. In this paper, we propose a hybrid precoding technique that simultaneously applies SLP and MMSE precoding to appropriately adjust SER performance and computational complexity performance. If two different types of precoding techniques are applied simultaneously, interference may occur between signals to which different types of precoding are applied, which can significantly deteriorate SER performance. Therefore, in this paper, precoding is designed to prevent interference between the two signals using the null space of the channel matrices. Through computer simulation, the proposed scheme showed that its SER performance was superior to that of the linear MMSE scheme, and the computational complexity was much lower than that of the SLP scheme.
High-Quality Cutting of Soda–Lime Glass with Bessel Beam Picosecond Laser: Optimization of Processing Point Spacing, Incident Power, and Burst Mode
Authors: Liu Jiaxuan , Yang Jianjun , Chen Hui , Li Jinxuan , Zhang Decheng , Zhong Jian , Pan Xinjian
Published: February 2024

Soda–lime glass has a wide range of applications in the fields of smart electronics, optical components, and precision originals. In order to investigate the effect of processing parameters on picosecond Bessel laser cutting of soda–lime glass and to achieve high-quality soda–lime glass cutting, a series of cutting experiments were conducted in this study. In this study, it was found that the machining point spacing, the incident laser energy, and the number of burst modes had a significant effect on the machining of the samples. The atomic force microscope (AFM) showed a better quality of roughness of the machined cross-section when the spacing of the machining points was 1 μm, a locally optimal solution was obtained when the number of burst modes was 2, and a locally optimal solution was also obtained when the incident laser power was 11.5 W. In this study, better machining quality was achieved for soda–lime glass of 1 mm thickness, with an average roughness of 158 nm and a local optimum of 141 nm.
A Novel Hybrid Approach for Concrete Crack Segmentation Based on Deformable Oriented-YOLOv4 and Image Processing Techniques
Authors: He Zengsheng , Su Cheng , Deng Yichuan
Published: February 2024

Regular crack inspection plays a significant role in the maintenance of concrete structures. However, most deep-learning-based methods suffer from the heavy workload of pixel-level labeling and the poor performance of crack segmentation with the presence of background interferences. To address these problems, the Deformable Oriented YOLOv4 (DO-YOLOv4) is first developed for crack detection based on the traditional YOLOv4, in which crack features can be effectively extracted by deformable convolutional layers, and the crack regions can be tightly enclosed by a series of oriented bounding boxes. Then, the proposed DO-YOLOv4 is further utilized in combination with the image processing techniques (IPTs), leading to a novel hybrid approach, termed DO-YOLOv4-IPTs, for crack segmentation. The experimental results show that, owing to the high precision of DO-YOLOv4 for crack detection under background noise, the present hybrid approach DO-YOLOv4-IPTs outperforms the widely used Convolutional Neural Network (CNN)-based crack segmentation methods with less labeling work and superior segmentation accuracy.
Electromagnetic–Thermal Characteristics Analysis of a Tubular Permanent Magnet Linear Generator for Free-Piston Engines
Authors: Liu Wenzhen , Feng Huihua , Li Jian , Jia Boru
Published: February 2024

Temperature rise of the tubular permanent magnet linear generator (TPMLG) might lead to insulation failure and demagnetization of permanent magnets, affecting the safe and stable operation of other equipment and the entire system. Herein, a bidirectional electromagnetic–thermal coupling method for analyzing the electromagnetic loss and thermal characteristics of a TPMLG considering the effect of increased temperature on the permanent magnet was proposed. To study the electromagnetic–thermal characteristics of the TPMLG under stable power generation, a two-dimensional electromagnetic field model and a three-dimensional temperature field model were established and coupled. The temperature field of the TPMLG was numerically calculated using computational fluid dynamics over finite volume method under natural air cooling and forced air cooling conditions. Effects of loss and air flow velocity on the steady temperature field were investigated. Results indicated that copper loss increased by 24.5% considering the influence of temperature rise. The windings’ top central position in the TPMLG was the spot with the highest temperature of 127.8 °C and there was a potential demagnetization risk for the permanent magnets. Some reference for future research of clarifying thermal characteristics and cooling design was provided.
Lightweight Non-Destructive Detection of Diseased Apples Based on Structural Re-Parameterization Technique
Authors: Han Bo , Lu Ziao , Dong Luan , Zhang Jingjing
Published: February 2024

This study addresses the challenges in the non-destructive detection of diseased apples, specifically the high complexity and poor real-time performance of the classification model for detecting diseased fruits in apple grading. Research is conducted on a lightweight model for apple defect recognition, and an improved VEW-YOLOv8n method is proposed. The backbone network incorporates a lightweight, re-parameterization VanillaC2f module, reducing both complexity and the number of parameters, and it employs an extended activation function to enhance the model’s nonlinear expression capability. In the neck network, an Efficient-Neck lightweight structure, developed using the lightweight modules and augmented with a channel shuffling strategy, decreases the computational load while ensuring comprehensive feature information fusion. The model’s robustness and generalization ability are further enhanced by employing the WIoU bounding box loss function, evaluating the quality of anchor frames using outlier metrics, and incorporating a dynamically updated gradient gain assignment strategy. Experimental results indicate that the improved model surpasses the YOLOv8n model, achieving a 2.7% increase in average accuracy, a 24.3% reduction in parameters, a 28.0% decrease in computational volume, and an 8.5% improvement in inference speed. This technology offers a novel, effective method for the non-destructive detection of diseased fruits in apple grading working procedures.
Performance Evaluation of L1-Norm-Based Blind Deconvolution after Noise Reduction with Non-Subsampled Contourlet Transform in Light Microscopy Images
Authors: Kim Kyuseok , Kim Ji-Youn
Published: February 2024

Noise and blurring in light microscope images are representative factors that affect accurate identification of cellular and subcellular structures in biological research. In this study, a method for l1-norm-based blind deconvolution after noise reduction with non-subsampled contourlet transform (NSCT) was designed and applied to a light microscope image to analyze its feasibility. The designed NSCT-based algorithm first separated the low- and high-frequency components. Then, the restored microscope image and the deblurred and denoised images were compared and evaluated. In both the simulations and experiments, the average coefficient of variation (COV) value in the image using the proposed NSCT-based algorithm showed similar values compared to the denoised image; moreover, it significantly improved the results compared with that of the degraded image. In particular, we confirmed that the restored image in the experiment improved the COV by approximately 2.52 times compared with the deblurred image, and the NSCT-based proposed algorithm showed the best performance in both the peak signal-to-noise ratio and edge preservation index in the simulation. In conclusion, the proposed algorithm was successfully modeled, and the applicability of the proposed method in light microscope images was proved based on various quantitative evaluation indices.
Renewable Energy Systems 2023
Authors: Cimmino Luca , Vicidomini Maria
Published: February 2024

In the last few years, the adoption of renewable technologies and energy efficiency strategies has become increasingly pivotal for reaching the ambitious target of an 80–95% reduction in greenhouse gas emissions by 2050 [...]
Modelling and Measuring Trust in Human–Robot Collaboration
Authors: Loizaga Erlantz , Bastida Leire , Sillaurren Sara , Moya Ana , Toledo Nerea
Published: February 2024

Recognizing trust as a pivotal element for success within Human–Robot Collaboration (HRC) environments, this article examines its nature, exploring the different dimensions of trust, analysing the factors affecting each of them, and proposing alternatives for trust measurement. To do so, we designed an experimental procedure involving 50 participants interacting with a modified ‘Inspector game’ while we monitored their brain, electrodermal, respiratory, and ocular activities. This procedure allowed us to map dispositional (static individual baseline) and learned (dynamic, based on prior interactions) dimensions of trust, considering both demographic and psychophysiological aspects. Our findings challenge traditional assumptions regarding the dispositional dimension of trust and establish clear evidence that the first interactions are critical for the trust-building process and the temporal evolution of trust. By identifying more significant psychophysiological features for trust detection and underscoring the importance of individualized trust assessment, this research contributes to understanding the nature of trust in HRC. Such insights are crucial for enabling more seamless human–robot interaction in collaborative environments.
Automated Scoring of Translations with BERT Models: Chinese and English Language Case Study
Authors: Cui Yizhuo , Liang Maocheng
Published: February 2024

With the wide application of artificial intelligence represented by deep learning in natural language-processing tasks, the automated scoring of translations has also advanced and improved. This study aims to determine if the BERT-assist system can reliably assess translation quality and identify high-quality translations for potential recognition. It takes the Han Suyin International Translation Contest as a case study, which is a large-scale and influential translation contest in China, with a history of over 30 years. The experimental results show that the BERT-assist system is a reliable second rater for massive translations in terms of translation quality, as it can effectively sift out high-quality translations with a reliability of r = 0.9 or higher. Thus, the automated translation scoring system based on BERT can satisfactorily predict the ranking of translations according to translation quality and sift out high-quality translations potentially shortlisted for prizes.
Hydroxyalkyl Amination of Agarose Gels Improves Adsorption of Bisphenol A and Diclofenac from Water: Conceivable Prospects
Authors: Ljunggren Lennart , Ivanova Svetlana , Ivanov Alexander E.
Published: February 2024

The hydroxyalkyl amination of agarose gels was studied as an approach to improve adsorption of polyphenols and pharmaceuticals from water. Three commercially available agarose gels, Zetarose FlashFlow4, ZetaCell-CL6B and Sepharose 4B were chemically modified using tris-(hydroxymethyl)aminomethane, TRIS, and ethanolamine, EA. The adsorbed amounts of bisphenol A and diclofenac were significantly higher on TRIS- and EA-derivatives compared with the parent gels. Regarding bisphenol A adsorption on TRIS-ZetaCell-CL6B, a maximal adsorption capacity, Q max of 16 μmol/mL gel and an equilibrium dissociation constant KL of 2.7 × 10−4 mol/L were observed. Filtration of diclofenac-contaminated water through TRIS-Zetarose FlashFlow 4 resulted in a 10-fold reduction of the pollutant concentration within 64 column volumes of the effluent. The moderate binding affinity of polyphenols to TRIS- and EA-adsorbents facilitates efficient polyphenol desorption and column regeneration. The effects of TRIS- and EA-substituents in agarose gels, can be harnessed for the development of environmental adsorbents, as well as for the preparative separation of polyphenols and pharmaceuticals. We consider the physical shapes and textures of the prospective adsorbents with a particular focus on spongy macroporous cryogels. These innovative materials hold promise for future applications in liquid and air filtration.
Finite Element Modeling and Experimental Validation of AA 5052-H34 Machining: A Comprehensive Study on Chip Morphology and Temperature Analysis
Authors: Al-Khafaji Abbas Farhan Jawad , Davoodi Behnam , Niknam Seyed Ali
Published: February 2024

An understanding of the dynamic behavior of materials plays a crucial role in machining improvement. According to the literature on this issue, one of the alloys whose dynamic behavior has been investigated less is AA 5052-H34, despite its numerous industrial applications. Using finite element (FE) modeling greatly reduces machining research costs. This research delved into the dynamic behavior modeling of AA 5052-H34 during dry-turning FE simulation. The dynamic behavior of AA 5052-H34 was achieved using the Johnson–Cook (J-C) constitutive equation, which was calculated using the uniaxial tensile and Split-Hopkinson pressure bar (SHPB) tests. To confirm the accuracy of the material model, these SHPB tests were then simulated in Abaqus. The J-C constitutive equation, paired with a J-C damage criterion, was employed in a chip formation and cutting temperature simulation. It was found that the feed rate significantly influences the dynamic behavior of AA 5052-H34. The thickness and morphology of the chip were investigated. The experimental and numerical chip thicknesses showed a direct relationship with the feed rate. The simulation temperature was also analyzed, and, as expected, it showed an upward trend with increasing cutting speed and feed rate. Then, the accuracy of the proposed FE simulation was confirmed by the agreement of the experimental and simulation results.
Evaluating the Effectiveness of Best Management Practices in Adapting the Impacts of Climate Change-Induced Urban Flooding
Authors: Bhusal Amrit , Thakur Balbhadra , Kalra Ajay , Benjankar Rohan , Shrestha Aruna
Published: February 2024

Floods are amongst the most destructive and costly natural disasters impacting communities around the globe. The severity and reoccurrence of flooding events have been more common in recent years as a result of the changing climate and urbanization. Best Management Practices (BMPs) are commonly used flood management techniques that aim to alleviate flooding and its impacts by capturing surface runoff and promoting infiltration. Recent studies have examined the effectiveness of BMPs in countering the effects of flooding; however, the performance of such strategies still needs to be analyzed for possible future climate change. In this context, this research employs climate model-driven datasets from the North American Regional Climate Change Assessment Program to evaluate the effects of climate change on urban hydrology within a study region by calculating historical and projected 6 h 100-year storm depths. Finally, the climate-induced design storms are simulated in the PCSWMM model, and the three BMP options (i.e., porous pavement, infiltration trench, and green roof) are evaluated to alleviate the impact of flooding events. This study quantifies the impact of changing climate on flood severity based on future climate models. The results indicate that peak discharge and peak volume are projected to increase by a range of 5% to 43% and 8% to 94%, respectively. In addition, the results demonstrated that green roofs, Permeable Pavement, and infiltration trenches help to reduce peak discharge by up to 7%, 14%, and 15% and reduce flood volume by up to 19%, 24%, and 29%, respectively, thereby presenting a promising solution to address the challenges posed by climate change-induced flooding events.
The Lower Atmospheric Characteristics of Dust Storms Using Ground-Based Sensor Data: A Comparative Analysis of Two Cases in Jinan, China
Authors: Li Tian , Tan Chenghao , Zhao Zilong , Yao Wenjiao
Published: February 2024

Two severe dust storm (DS) events (15–17 March and 28–29 March) hit northern China in 2021 consecutively. The lower atmospheric vertical dynamic and thermal structures during the two cases were compared using the ground-based sensor data from the microwave radiometer and radar wind profiler, combined with the environmental and meteorological observations data in Jinan, China. It was found that both cases occurred under the background of cold vortexes over northeastern China. The dust was transported through the cold air on the northwest route. During the dust period, 2–3 km was the west or northwest airflow, and below 2 km was the northeast wind. The variation in the dynamic structure determined the duration of the DS. During the DS maintenance phase, the vertical wind shear (VWS) below 3 km measured approximately 10 m∙(s∙km)−1. The increased VWS during the dust intrusion period facilitated the transportation of dust. In contrast, the more significant VWS was not conducive to the maintenance of DS, and the shift to south wind control in the upper middle layer indicated the weakening of DS. In both cases, we observed a cliff-like decrease in relative humidity as a prominent indicator of dust outbreaks, occurring approximately 2–5 h beforehand. The diurnal difference between the vertical temperature and relative humidity during the dust maintenance period was found to be insignificant.
A Novel Domination in Vague Influence Graphs with an Application
Authors: Shi Xiaolong , Cai Ruiqi , Talebi Ali Asghar , Mojahedfar Masomeh , Liu Chanjuan
Published: February 2024

Vague influence graphs (VIGs) are well articulated, useful and practical tools for managing the uncertainty preoccupied in all real-life difficulties where ambiguous facts, figures and explorations are explained. A VIG gives the information about the effect of a vertex on the edge. In this paper, we present the domination concept for VIG. Some issues and results of the domination in vague graphs (VGs) are also developed in VIGs. We defined some basic notions in the VIGs such as the walk, path, strength of In-pair , strong In-pair, In-cut vertex, In-cut pair (CP), complete VIG and strong pair domination number in VIG. Finally, an application of domination in illegal drug trade was introduced.
Harnessing the Power of Zinc-Solubilizing Bacteria: A Catalyst for a Sustainable Agrosystem
Authors: Singh Swapnil , Chhabra Rohit , Sharma Ashish , Bisht Aditi
Published: February 2024

A variety of agrochemicals, especially fertilizers, are applied indiscriminately by farmers across trapezoidal landscapes to increase productivity and satisfy the rising food demand. Around one-third of the populace in developing nations is susceptible to zinc (Zn) deficiency as a result of their direct reliance on cereals as a source of calories. Zinc, an essential micronutrient for plants, performs several critical functions throughout the life cycle of a plant. Zinc is frequently disregarded, due to its indirect contribution to the enhancement of yield. Soil Zn deficiency is one of the most prevalent micronutrient deficiencies that reduces crop yield. A deficiency of Zn in both plants and soils results from the presence of Zn in fixed forms that are inaccessible to plants, which characterizes the majority of agricultural soils. As a result, alternative and environmentally sustainable methods are required to satisfy the demand for food. It appears that the application of zinc-solubilizing bacteria (ZSB) for sustainable agriculture is feasible. Inoculating plants with ZSB is likely a more efficacious strategy for augmenting Zn translocation in diverse edible plant components. ZSB possessing plant growth-promoting characteristics can serve as bio-elicitors to promote sustainable plant growth, through various methods that are vital to the health and productivity of plants. This review provides an analysis of the efficacy of ZSB, the functional characteristics of ZSB-mediated Zn localization, the mechanism underlying Zn solubilization, and the implementation of ZSB to increase crop yield.
Solar and Wind Data Recognition: Fourier Regression for Robust Recovery
Authors: Al-Aboosi Abdullah F. , Muñoz Vazquez Aldo Jonathan , Al-Aboosi Fadhil Y. , El-Halwagi Mahmoud , Zhan Wei
Published: February 2024

Accurate prediction of renewable energy output is essential for integrating sustainable energy sources into the grid, facilitating a transition towards a more resilient energy infrastructure. Novel applications of machine learning and artificial intelligence are being leveraged to enhance forecasting methodologies, enabling more accurate predictions and optimized decision-making capabilities. Integrating these novel paradigms improves forecasting accuracy, fostering a more efficient and reliable energy grid. These advancements allow better demand management, optimize resource allocation, and improve robustness to potential disruptions. The data collected from solar intensity and wind speed is often recorded through sensor-equipped instruments, which may encounter intermittent or permanent faults. Hence, this paper proposes a novel Fourier network regression model to process solar irradiance and wind speed data. The proposed approach enables accurate prediction of the underlying smooth components, facilitating effective reconstruction of missing data and enhancing the overall forecasting performance. The present study focuses on Midland, Texas, as a case study to assess direct normal irradiance (DNI), diffuse horizontal irradiance (DHI), and wind speed. Remarkably, the model exhibits a correlation of 1 with a minimal RMSE (root mean square error) of 0.0007555. This study leverages Fourier analysis for renewable energy applications, with the aim of establishing a methodology that can be applied to a novel geographic context.
Sign-to-Text Translation from Panamanian Sign Language to Spanish in Continuous Capture Mode with Deep Neural Networks
Authors: Teran-Quezada Alvaro A. , Lopez-Cabrera Victor , Rangel Jose Carlos , Sanchez-Galan Javier E.
Published: February 2024

Convolutional neural networks (CNN) have provided great advances for the task of sign language recognition (SLR). However, recurrent neural networks (RNN) in the form of long–short-term memory (LSTM) have become a means for providing solutions to problems involving sequential data. This research proposes the development of a sign language translation system that converts Panamanian Sign Language (PSL) signs into text in Spanish using an LSTM model that, among many things, makes it possible to work with non-static signs (as sequential data). The deep learning model presented focuses on action detection, in this case, the execution of the signs. This involves processing in a precise manner the frames in which a sign language gesture is made. The proposal is a holistic solution that considers, in addition to the seeking of the hands of the speaker, the face and pose determinants. These were added due to the fact that when communicating through sign languages, other visual characteristics matter beyond hand gestures. For the training of this system, a data set of 330 videos (of 30 frames each) for five possible classes (different signs considered) was created. The model was tested having an accuracy of 98.8%, making this a valuable base system for effective communication between PSL users and Spanish speakers. In conclusion, this work provides an improvement of the state of the art for PSL–Spanish translation by using the possibilities of translatable signs via deep learning.
Comparative Analysis of Bone Regeneration According to Particle Type and Barrier Membrane for Octacalcium Phosphate Grafted into Rabbit Calvarial Defects
Authors: Pyo Se-Wook , Paik Jeong-Won , Lee Da-Na , Seo Young-Wook , Park Jin-Young , Kim Sunjai , Choi Seong-Ho
Published: February 2024

This animal study was aimed to evaluate the efficacy of new bone formation and volume maintenance according to the particle type and the collagen membrane function for grafted octacalcium phosphate (OCP) in rabbit calvarial defects. The synthetic bone substitutes were prepared in powder form with 90% OCP and granular form with 76% OCP, respectively. The calvarial defects were divided into four groups according to the particle type and the membrane application. All specimens were acquired 2 weeks (n = 5) and 8 weeks (n = 5) after surgery. According to the micro-CT results, the new bone volume increased at 2 weeks in the 76% OCP groups compared to the 90% OCP groups, and the bone volume ratio was significantly lower in the 90% OCP group after 2 weeks. The histomorphometric analysis results indicated that the new bone area and its ratio in all experimental groups were increased at 8 weeks except for the group with 90% OCP without a membrane. Furthermore, the residual bone graft area and its ratio in the 90% OCP groups were decreased at 8 weeks. In conclusion, all types of OCP could be applied as biocompatible bone graft materials regardless of its density and membrane application. Neither the OCP concentration nor the membrane application had a significant effect on new bone formation in the defect area, but the higher the OCP concentration, the less graft volume maintenance was needed.
Deep Learning for Generalized EEG Seizure Detection after Hypoxia–Ischemia—Preclinical Validation
Authors: Abbasi Hamid , Davidson Joanne O. , Dhillon Simerdeep K. , Zhou Kelly Q. , Wassink Guido , Gunn Alistair J. , Bennet Laura
Published: February 2024

Brain maturity and many clinical treatments such as therapeutic hypothermia (TH) can significantly influence the morphology of neonatal EEG seizures after hypoxia–ischemia (HI), and so there is a need for generalized automatic seizure identification. This study validates efficacy of advanced deep-learning pattern classifiers based on a convolutional neural network (CNN) for seizure detection after HI in fetal sheep and determines the effects of maturation and brain cooling on their accuracy. The cohorts included HI–normothermia term (n = 7), HI–hypothermia term (n = 14), sham–normothermia term (n = 5), and HI–normothermia preterm (n = 14) groups, with a total of >17,300 h of recordings. Algorithms were trained and tested using leave-one-out cross-validation and k-fold cross-validation approaches. The accuracy of the term-trained seizure detectors was consistently excellent for HI–normothermia preterm data (accuracy = 99.5%, area under curve (AUC) = 99.2%). Conversely, when the HI–normothermia preterm data were used in training, the performance on HI–normothermia term and HI–hypothermia term data fell (accuracy = 98.6%, AUC = 96.5% and accuracy = 96.9%, AUC = 89.6%, respectively). Findings suggest that HI–normothermia preterm seizures do not contain all the spectral features seen at term. Nevertheless, an average 5-fold cross-validated accuracy of 99.7% (AUC = 99.4%) was achieved from all seizure detectors. This significant advancement highlights the reliability of the proposed deep-learning algorithms in identifying clinically translatable post-HI stereotypic seizures in 256Hz recordings, regardless of maturity and with minimal impact from hypothermia.
Mendelian Randomisation Analysis of Causal Association between Lifestyle, Health Factors, and Keratoconus
Authors: Cheng Jiaxuan , Yang Lanting , Ye Yishan , He Lvfu , Chen Shihao , Wang Junjie
Published: February 2024

Keratoconus (KC), a leading cause of vision impairment, has an unclear aetiology. This study used Mendelian randomization (MR) to explore the causal links between various factors (smoking, asthma, Down syndrome, inflammatory bowel disease, atopic dermatitis, and serum 25-hydroxyvitamin D levels) and KC. A two-sample MR design, grounded in genome-wide association study (GWAS) summary statistics, was adopted using data from FinnGen, UK Biobank, and other GWAS-related articles. The inverse-variance weighted (IVW) method was employed, complemented by the Wald ratio method for factors with only one single-nucleotide polymorphism (SNP). Sensitivity and stability were assessed through Cochrane’s Q test, the MR-Egger intercept test, MR-PRESSO outlier test, and the leave-one-out analysis. The IVW results for the ORA (Ocular Response Analyzer) biomechanical parameters indicated significant associations between tobacco smoking (CH: p < 0.001; CRF: p = 0.009) and inflammatory bowel disease (CH: p = 0.032; CRF: p = 0.001) and corneal biomechanics. The Wald ratio method showed tobacco smoking was associated with a lower risk of KC (p = 0.024). Conversely, asthma (p = 0.009), atopic dermatitis (p = 0.012), inflammatory bowel disease (p = 0.017), and serum 25-hydroxyvitamin D levels (p = 0.039) were associated with a higher risk of KC by IVW, and the same applied to Down syndrome (p = 0.004) using the Wald ratio. These results underscore the role of corneal biomechanics as potential mediators in KC risk, warranting further investigation using Corvis ST and Brillouin microscopy. The findings emphasise the importance of timely screening for specific populations in KC prevention and management.