bluuebunny/crossref_metadata_2025 huggingface dataset:
The Triterpenoids from Munronia pinnata and Their Anti-Proliferative Effects
Authors: Yang Xuerong , Liu Peiyuan , Wei Yulu , Song Jingru , Yan Xiaojie , Jiang Xiaohua , Li Jianxing , Li Xiangqin , Li Dianpeng , Lu Fenglai
Published: September 2023

Six new tirucallane-type triterpenoids, named munropenes A–F (1–6), were extracted from the whole plants of Munronia pinnata using a water extraction method. Their chemical structures were determined based on detailed spectroscopic data. The relative configurations of the acyclic structures at C-17 of munropenes A–F (1–6) were established using carbon–proton spin-coupling constants (2,3JC,H) and inter-proton spin-coupling constants (3JH,H). Furthermore, the absolute configurations of munropenes A–F (1–6) were determined through high-performance liquid chromatography (HPLC), single-crystal X-ray diffraction, and electronic circular dichroism (ECD) analyses. The antiproliferative effects of munropenes A–F were evaluated in five tumor cell lines: HCT116, A549, HepG2, MCF7, and MDAMB. Munropenes A, B, D, and F (1, 2, 4, and 6) inhibited proliferation in the HCT116 cell line with IC50 values of 40.90, 19.13, 17.66, and 32.62 µM, respectively.
The In Vitro Antimicrobial Susceptibility of Borrelia burgdorferi sensu lato: Shedding Light on the Known Unknowns
Authors: Hunfeld Klaus-Peter , Kraiczy Peter , Norris Douglas E. , Lohr Benedikt
Published: September 2023

Human Lyme borreliosis (LB) represents a multisystem disorder that can progress in stages. The causative agents are transmitted by hard ticks of the Ixodes ricinus complex that have been infected with the spirochete Borrelia burgdorferi sensu lato. Today, LB is considered the most important human tick-borne illness in the Northern Hemisphere. The causative agent was identified and successfully isolated in 1982 and, shortly thereafter, antibiotic treatment was found to be safe and efficacious. Since then, various in vitro studies have been conducted in order to improve our knowledge of the activity of antimicrobial agents against B. burgdorferi s. l. The full spectrum of in vitro antibiotic susceptibility has still not been defined for some of the more recently developed compounds. Moreover, our current understanding of the in vitro interactions between B. burgdorferi s. l. and antimicrobial agents, and their possible mechanisms of resistance remains very limited and is largely based on in vitro susceptibility experiments on only a few isolates of Borrelia. Even less is known about the possible mechanisms of the in vitro persistence of spirochetes exposed to antimicrobial agents in the presence of human and animal cell lines. Only a relatively small number of laboratory studies and cell culture experiments have been conducted. This review summarizes what is and what is not known about the in vitro susceptibility of B. burgdorferi s. l. It aims to shed light on the known unknowns that continue to fuel current debates on possible treatment resistance and mechanisms of persistence of Lyme disease spirochetes in the presence of antimicrobial agents.
The Paradox of Fictional Creatures
Authors: Rouillé Louis
Published: September 2023

Authors create fictional characters; that is a “creationist locution”. Artefactualism takes such statements very seriously and holds that fictional characters are abstract artefacts, i.e., entities that are both created and abstract. Anti-creationists, by contrast, deny that we need to postulate such doubtful entities to explain creationist locutions. In this paper, I present this debate in the form of a paradox, which organises the many existing theories of creationist locutions in a single logical space. This new way of framing the problem displays the crucial role of so-called “linking principles”. In general, it seems that fictionality entails nonexistence, while creation entails existence. This is why “fictional creatures” are puzzling. I further argue that to create means to invent and to realise, and finally, that fictional characters are invented but not created, contra artefactualism. I thus advocate for a new kind of anti-creationism about fictional characters.
From “Whither” to “Whence”: A Decolonial Reading of Malabou
Authors: Cicoria Rachel
Published: September 2023

A turn from the “whither” to the “whence” of anarchism is at stake in Catherine Malabou’s interpretation of Latin American decolonial theory. This is a turn from a materialist philosophy that seeks to open the space of anarchism within the modern state toward one that discerns anarchism as already operative in the modern state given the social implications of colonial legacies. In tracing this turn, I propose a development of Malabou’s work insofar as I put her in dialogue with María Lugones, who is much closer to Malabou than the more canonical decolonial figures she actively engages, especially in view of anarchism as a form of social–political plasticity. Understanding Lugones’ critique of earlier iterations of decolonial theory helps make explicit an immanent anarchic resistance to domination as an explosive inhabitation of everyday loci of tension.
Optimal Orientation Angle Configuration of Polarizers Exists in a 3 × 3 Mueller Matrix Polarimeter
Authors: Wei Hanyue , Zhou Yifu , Ren Liyong , Ma Feiya
Published: September 2023

A 3 × 3 Mueller matrix polarimeter, as one of the primary polarization measurement tools, has attracted intensive interest in various fields of polarization optics. In this paper, from a novel viewpoint with more mathematical analysis of the basic configuration and the working performance of a 3 × 3 Mueller matrix polarimeter, we systematically study the relationship between Mueller matrix measurement errors with the configuration and characteristics of polarizers in the polarimeter. We figure out that, mathematically, there is an optimal orientation angle configuration (0°, 60°, and 120°) of polarizers, which inherently ensures a minimal relative measurement error in general. Moreover, we interpret the internal source of such a robust error resistance under this optimized configuration mathematically for the first time. Simulation and practical experiments show the effectiveness of our mathematical analyses, and compared to the frequently used orientation angle configuration, the average relative error is reduced by up to 32% under such an optimized configuration.
Proline, Cysteine and Branched-Chain Amino Acids in Abiotic Stress Response of Land Plants and Microalgae
Authors: Ingrisano Rachele , Tosato Edoardo , Trost Paolo , Gurrieri Libero , Sparla Francesca
Published: September 2023

Proteinogenic amino acids are the building blocks of protein, and plants synthesize all of them. In addition to their importance in plant growth and development, growing evidence underlines the central role played by amino acids and their derivatives in regulating several pathways involved in biotic and abiotic stress responses. In the present review, we illustrate (i) the role of amino acids as an energy source capable of replacing sugars as electron donors to the mitochondrial electron transport chain and (ii) the role of amino acids as precursors of osmolytes as well as (iii) precursors of secondary metabolites. Among the amino acids involved in drought stress response, proline and cysteine play a special role. Besides the large proline accumulation occurring in response to drought stress, proline can export reducing equivalents to sink tissues and organs, and the production of H2S deriving from the metabolism of cysteine can mediate post-translational modifications that target protein cysteines themselves. Although our general understanding of microalgae stress physiology is still fragmentary, a general overview of how unicellular photosynthetic organisms deal with salt stress is also provided because of the growing interest in microalgae in applied sciences.
Gene Expression and Interaction Analysis of FsWRKY4 and FsMAPK3 in Forsythia suspensa
Authors: Tan Xinjie , Chen Jiaxi , Zhang Jiaqi , Guo Guangyang , Zhang Hongxiao , Zhao Xingli , Lv Shufang , Xu Huawei , Hou Dianyun
Published: September 2023

Forsythia suspensa is a deciduous shrub that belongs to the family Myrtaceae, and its dried fruits are used as medicine. F. suspensa contains several secondary metabolites, which exert pharmacological effects. One of the main active components is forsythin, which exhibits free radical scavenging, antioxidant, anti-inflammatory, and anti-cancer effects. Mitogen-activated protein kinase (MAPKs) can increase the activity of WRKY family transcription factors in a phosphorylated manner, thereby increasing the content of secondary metabolites. However, the mechanism of interaction between MAPKs and WRKYs in F. suspensa remains unclear. In this study, we cloned the genes of FsWRKY4 and FsMAPK3, and performed a bioinformatics analysis. The expression patterns of FsWRKY4 and FsMAPK3 were analyzed in the different developmental stages of leaf and fruit from F. suspensa using real-time fluorescence quantitative PCR (qRT-PCR). Subcellular localization analysis of FsWRKY4 and FsMAPK3 proteins was performed using a laser scanning confocal microscope. The existence of interactions between FsWRKY4 and FsMPAK3 in vitro was verified by yeast two-hybridization. Results showed that the cDNA of FsWRKY4 (GenBank number: OR566682) and FsMAPK3 (GenBank number: OR566683) were 1587 and 522 bp, respectively. The expression of FsWRKY4 was higher in the leaves than in fruits, and the expression of FsMAPK3 was higher in fruits but lower in leaves. The subcellular localization results indicated that FsWRKY4 was localized in the nucleus and FsMAPK3 in the cytoplasm and nucleus. The prey vector pGADT7-FsWRKY4 and bait vector pGBKT7-FsMAPK3 were constructed and co-transferred into Y2H Glod yeast receptor cells. The results indicated that FsWRKY4 and FsMAPK3 proteins interact with each other in vitro. The preliminary study may provide a basis for more precise elucidation of the synthesis of secondary metabolites in F. suspensa.
Antifungal Activity of Rue Essential Oil and Commercial Chitosan on Native Corn Foliar Diseases
Authors: Ceja-Torres Luis Fernando , López-Díaz Sigifredo , Silva-Ramos María Guadalupe , Silva-García José Teodoro , Medina-Medrano José Roberto , Gutiérrez-Hernández Germán Fernando
Published: September 2023

Native corn in Cherán, Michoacán, southwestern Mexico, represents a high-impact economic, social, and religious support, although its yield is low due to fungal diseases. Fungicides are mainly used for their control, but the fungi involved create resistance. The aims of this study are to determine the incidence of foliar diseases in the field, isolate the causal fungi, evaluate the in vitro effect of the essential oil of rue (Ruta graveolens) on them, and identify the secondary metabolites. The essential oil was obtained using the steam distillation technique on fresh plants. Also used was an industrial-grade chitosan, and the commercial fungicide benomyl was used as a positive control. Rue essential oil was characterized by mass spectrometry with ultra-high-performance liquid chromatography with electrospray ionization (UHPLC-ESI). The highest incidence of disease was obtained for leaf rust (35%), followed by gray leaf spot (GLS) (24%) and leaf blight (19%). Rue essential oil inhibited 100% of the mycelial growth of Coniothyrium phyllachorae and 96% of the mycelium of Exseroilum turcicum. The benomyl fungicide effectively inhibited C. phyllachorae (86 to 91%), but not E. turcicum, with the opposite effect when using chitosan by inhibiting 89 to 90% of the latter’s mycelial development. The majority compound of the essential oil of R. graveolens was 2-(3-phenylprop-2-enoyl)chromen-4-one; however, fatty acids were also detected: linoleic, palmitic, and retinoic acid.
The Evaluation of Cellulose Acetate Capsules Functionalized for the Removal of Cd(II)
Authors: Pérez-Silva Irma , Canales-Feliciano Gladis D. , Rodríguez José A. , Mendoza-Huizar Luis H. , Pérez-Estrada Salvador , Ibarra Israel S. , Páez-Hernández M. Elena
Published: September 2023

Cellulose acetate is derived from cellulose and has the characteristics of biodegradability and reusability. So, it has been used for the elimination of toxic compounds capable of producing different diseases, such as cadmium, that result from human and industrial activity. For this reason, capsules functionalized with Cyanex 923 were prepared and characterized by FTIR spectroscopy, Energy Dispersive X-ray Spectroscopy (EDX), and SEM. The functionalized capsules were used for removing and recovering Cd(II) by modifying variables such as HCl concentration in the extraction medium and carrier content in the capsules, among others. The extraction of cadmium from battery leachates and the three isotherm models, Langmuir, Freundlich, and Dubinin Radushkevich, were also tested to model the cadmium removal process. The results showed a favorable physical sorption with a good capacity for extraction and the possibility of reusing the capsules for up to seven cycles without a decrease in the percentage of cadmium recovery.
Virtual Design of 3D-Printed Bone Tissue Engineered Scaffold Shape Using Mechanobiological Modeling: Relationship of Scaffold Pore Architecture to Bone Tissue Formation
Authors: Alshammari Adel , Alabdah Fahad , Wang Weiguang , Cooper Glen
Published: September 2023

Large bone defects are clinically challenging, with up to 15% of these requiring surgical intervention due to non-union. Bone grafts (autographs or allografts) can be used but they have many limitations, meaning that polymer-based bone tissue engineered scaffolds (tissue engineering) are a more promising solution. Clinical translation of scaffolds is still limited but this could be improved by exploring the whole design space using virtual tools such as mechanobiological modeling. In tissue engineering, a significant research effort has been expended on materials and manufacturing but relatively little has been focused on shape. Most scaffolds use regular pore architecture throughout, leaving custom or irregular pore architecture designs unexplored. The aim of this paper is to introduce a virtual design environment for scaffold development and to illustrate its potential by exploring the relationship of pore architecture to bone tissue formation. A virtual design framework has been created utilizing a mechanical stress finite element (FE) model coupled with a cell behavior agent-based model to investigate the mechanobiological relationships of scaffold shape and bone tissue formation. A case study showed that modifying pore architecture from regular to irregular enabled between 17 and 33% more bone formation within the 4–16-week time periods analyzed. This work shows that shape, specifically pore architecture, is as important as other design parameters such as material and manufacturing for improving the function of bone tissue scaffold implants. It is recommended that future research be conducted to both optimize irregular pore architectures and to explore the potential extension of the concept of shape modification beyond mechanical stress to look at other factors present in the body.
Origin and Geological Significance of Residual Oil in High-Angle Joint Fissures: A Case Study of the Nadu Formation in Baise Basin, South China
Authors: Gao Ye , Liu Yan , Xu Yaohui , Liu Baolei , He Wenxiang , Duan Hongliang , Chen Wei , Cheng Wei , Tian Weichao , Fan Yunpeng
Published: September 2023

The Baise Basin is a Paleogene pull-apart basin with numerous strike-slip faults which are not favorable for hydrocarbon preservation. The Nadu Formation, research object of this paper, is generally rich in oil and contains a large number of high-angle joint fissures. Analyzing the origin of residual oil in high-angle joint fissures can reveal the hydrocarbon migration and accumulation characteristics of the pull-apart-type basins. Molecular geochemical composition characteristics of crude oil and oil source of the Nadu Formation were discussed based on the saturated hydrocarbon biomarker compound and stable carbon isotope distribution of n-alkanes. The studied samples were selected from four members (E2n1, E2n2, E2n3up, and E2n3low) of the Nadu Formation. The results suggested that the average oil content of E2n1 fissures is 0.32 mg/cm2, and the oil distribution is not uniform. The distribution of oil on the fissures of E2n2 and E2n3 is uniform and complete, and the oil content reaches 0.53 mg/cm2. The oil in the joint fissures of the Nadu Formation is heavy, as the light hydrocarbon is seriously lost during migration. Thus, the oil in the joint fissures is residue after crude oil loses light components during migration. By comparing the molecular biomarker characteristics and stable carbon isotopic compositions, crude oil of the Nadu Formation can be classified into three categories: E2n1, E2n2 + E2n3up, and E2n3low. The E2n1 oils have the lowest maturity and are sourced from the E2n1 source rocks. Moreover, the maturity of E2n2 and E2n3 samples are relatively high. Biomarker and carbon isotope characteristics of the E2n2 and E2n3up oils are similar, indicating that they are derived from the E2n2 + E2n3up source rocks. The E2n3low oils are the mixture of the crude oil generated from the E2n3up source rocks and the E2n3low source rocks. Results presented show that the residual oil of high-angle joint fissures in the Nadu Formation is contributed by adjacent source rocks. The crude oil discharged from the Nadu Formation can only migrate upward along high-angle joints in a short distance, and the migration distance is usually less than 5 m. In conclusion, although the Nadu Formation has developed a large number of high-angle joint fissures, crude oil in the Nadu Formation has not vertically migrated for long distance along the joint fissures. The well-preserved fractures as important shale oil storage spaces indicate that the Nadu Formation has good shale oil exploration potential. The results may provide insights into the origins of hydrocarbons in the Nadu Formation from the Baise Basin and enhanced knowledge for optimizing future exploration and production.
Lattice Shrinkage of 2D-COFs under Electron Beam Irradiation
Authors: Ren Shiwei , Sun Shina , Xu Mingkun , Li Song , Ding Yubing , Shao Mingchao
Published: September 2023

Over the past two decades, covalent organic frameworks (COFs) have become the most widely studied porous crystalline materials. Their specific physical and chemical properties are determined by the arrangement of atoms (crystal structure). Therefore, the determination of their structure is arguably the most important characterization step for COFs. Although single-crystal X-ray diffraction is the most widely used method for structure determination, confirmation of the structure of COFs is limited to lattice fringes in transmission electron microscopy (TEM) because of their small crystal size (nanocrystals) or poor crystal quality. At present, many two-dimensional COFs (2D-COFs) have clear powder X-ray diffraction (PXRD) patterns, but specific lattice fringes are not available for all 2D-COFs. This severely hinders the development of the COF field. Here, we discovered the lattice shrinkage behavior of COFs under electron beam irradiation by comparing the lattice fringes of 2D-COFs under different conditions. By comparing the lattice fringes of a 1,3,5-tris-(4-aminophenyl)triazine-1,3,5-tris-(4-formylphenyl)triazine covalent organic framework (TAPT-TFPT COF) at room temperature and under liquid nitrogen freezing conditions, we found that the lattice fringes are in good agreement with the PXRD and the theoretical values of the COF (2.213 nm) under freezing conditions. However, the lattice fringe spacing is only 1.656 nm at room temperature. The discovery not only provides new insights into the TEM characterization of COFs, but also further expands the range of crystalline COF materials.
An Exponentiality Test of Fit Based on a Tail Characterization against Heavy and Light-Tailed Alternatives
Authors: Karagrigoriou Alex , Mavrogiannis Ioannis , Papasotiriou Georgia , Vonta Ilia
Published: September 2023

Log-concavity and log-convexity play a key role in various scientific fields, especially in those where the distinction between exponential and non-exponential distributions is necessary for inferential purposes. In the present study, we introduce a testing procedure for the tail part of a distribution which can be used for the distinction between exponential and non-exponential distributions. The conspiracy and catastrophe principles are initially used to establish a characterization of (the tail part of) the exponential distribution, which is one of the main contributions of the present work, leading the way for the construction of the new test of fit. The proposed test and its implementation are thoroughly discussed, and an extended simulation study has been undertaken to clarify issues related to its implementation and explore the extent of its capabilities. A real data case is also investigated.
Context-Aware Robotic Assistive System: Robotic Pointing Gesture-Based Assistance for People with Disabilities in Sheltered Workshops
Authors: Drolshagen Sandra , Pfingsthorn Max , Hein Andreas
Published: September 2023

People with disabilities are severely underrepresented in the open labor market. Yet, pursuing a job has a positive impact in many aspects of life. This paper presents a possible approach to improve inclusion by including a robotic manipulator into context-aware Assistive Systems. This expands the assistance possibilities tremendously by adding gesture-based feedback and aid. The system presented is based on the intelligent control system of behavior trees, which—together with a depth camera, specifically designed policies, and a collaborative industrial robotic manipulator—can assist workers with disabilities in the workplace. A developed assistance node generates personalized action sequences. These include different robotic pointing gestures, from simple waving, to precisely indicating the target position of the workpiece during assembly tasks. This paper describes the design challenges and technical implementation of the first Context-Aware Robotic Assistive System. Moreover, an in-field user study in a Sheltered Workshop was performed to verify the concept and developed algorithms. In the assembly task under consideration, almost three times as many parts could be assembled with the developed system than with the baseline condition. In addition, the reactions and statements of the participants showed that the robot was considered and accepted as a tutor.
A Novel Generalization of Q-Rung Orthopair Fuzzy Aczel Alsina Aggregation Operators and Their Application in Wireless Sensor Networks
Authors: Ali Wajid , Shaheen Tanzeela , Haq Iftikhar Ul , Alballa Tmader , Alburaikan Alhanouf , El-Wahed Khalifa Hamiden Abd
Published: September 2023

Q-rung orthopair fuzzy sets have been proven to be highly effective at handling uncertain data and have gained importance in decision-making processes. Torra’s hesitant fuzzy model, on the other hand, offers a more generalized approach to fuzzy sets. Both of these frameworks have demonstrated their efficiency in decision algorithms, with numerous scholars contributing established theories to this research domain. In this paper, recognizing the significance of these frameworks, we amalgamated their principles to create a novel model known as Q-rung orthopair hesitant fuzzy sets. Additionally, we undertook an exploration of Aczel–Alsina aggregation operators within this innovative context. This exploration resulted in the development of a series of aggregation operators, including Q-rung orthopair hesitant fuzzy Aczel–Alsina weighted average, Q-rung orthopair hesitant fuzzy Aczel–Alsina ordered weighted average, and Q-rung orthopair hesitant fuzzy Aczel–Alsina hybrid weighted average operators. Our research also involved a detailed analysis of the effects of two crucial parameters: λ, associated with Aczel–Alsina aggregation operators, and N, related to Q-rung orthopair hesitant fuzzy sets. These parameter variations were shown to have a profound impact on the ranking of alternatives, as visually depicted in the paper. Furthermore, we delved into the realm of Wireless Sensor Networks (WSN), a prominent and emerging network technology. Our paper comprehensively explored how our proposed model could be applied in the context of WSNs, particularly in the context of selecting the optimal gateway node, which holds significant importance for companies operating in this domain. In conclusion, we wrapped up the paper with the authors’ suggestions and a comprehensive summary of our findings.
Cybersecurity in Internet of Medical Vehicles: State-of-the-Art Analysis, Research Challenges and Future Perspectives
Authors: Bhukya Chidambar , Thakur Prabhat , Mudhivarthi Bhavesh , Singh Ghanshyam
Published: September 2023

The “Internet-of-Medical-Vehicles (IOMV)” is one of the special applications of the Internet of Things resulting from combining connected healthcare and connected vehicles. As the IOMV communicates with a variety of networks along its travel path, it incurs various security risks due to sophisticated cyber-attacks. This can endanger the onboard patient’s life. So, it is critical to understand subjects related to “cybersecurity” in the IOMV to develop robust cybersecurity measures. In this paper, the goal is to evaluate recent trends and state-of-the-art publications, gaps, and future outlooks related to this research area. With this aim, a variety of publications between 2016 and 2023 from “Web-of-Science” and “Scopus” databases were analysed. Our analysis revealed that the IOMV is a niche and unexplored research area with few defined standards and frameworks, and there is a great need to implement robust cybersecurity measures. This paper will help researchers to gain a comprehensive idea of this niche research topic, as it presents an analysis of top journals and highly cited papers, their challenges and limitations, the system model and architecture of the IOMV, related applicable standards, potential cyber-attacks, factors causing cybersecurity risks, various artificial intelligence techniques for developing potential countermeasures, the assessment and parameterisation of cybersecurity risks, constraints and challenges, and future outlooks for implementing cybersecurity measures in the IOMV.
ECG-Free Heartbeat Detection in Seismocardiography and Gyrocardiography Signals Provides Acceptable Heart Rate Variability Indices in Healthy and Pathological Subjects
Authors: Parlato Salvatore , Centracchio Jessica , Esposito Daniele , Bifulco Paolo , Andreozzi Emilio
Published: September 2023

Cardio-mechanical monitoring techniques, such as Seismocardiography (SCG) and Gyrocardiography (GCG), have received an ever-growing interest in recent years as potential alternatives to Electrocardiography (ECG) for heart rate monitoring. Wearable SCG and GCG devices based on lightweight accelerometers and gyroscopes are particularly appealing for continuous, long-term monitoring of heart rate and its variability (HRV). Heartbeat detection in cardio-mechanical signals is usually performed with the support of a concurrent ECG lead, which, however, limits their applicability in standalone cardio-mechanical monitoring applications. The complex and variable morphology of SCG and GCG signals makes the ECG-free heartbeat detection task quite challenging; therefore, only a few methods have been proposed. Very recently, a template matching method based on normalized cross-correlation (NCC) has been demonstrated to provide very accurate detection of heartbeats and estimation of inter-beat intervals in SCG and GCG signals of pathological subjects. In this study, the accuracy of HRV indices obtained with this template matching method is evaluated by comparison with ECG. Tests were performed on two public datasets of SCG and GCG signals from healthy and pathological subjects. Linear regression, correlation, and Bland-Altman analyses were carried out to evaluate the agreement of 24 HRV indices obtained from SCG and GCG signals with those obtained from ECG signals, simultaneously acquired from the same subjects. The results of this study show that the NCC-based template matching method allowed estimating HRV indices from SCG and GCG signals of healthy subjects with acceptable accuracy. On healthy subjects, the relative errors on time-domain indices ranged from 0.25% to 15%, on frequency-domain indices ranged from 10% to 20%, and on non-linear indices were within 8%. The estimates obtained on signals from pathological subjects were affected by larger errors. Overall, GCG provided slightly better performances as compared to SCG, both on healthy and pathological subjects. These findings provide, for the first time, clear evidence that monitoring HRV via SCG and GCG sensors without concurrent ECG is feasible with the NCC-based template matching method for heartbeat detection.
ADFSNet: An Adaptive Domain Feature Separation Network for the Classification of Wheat Seed Using Hyperspectral Images
Authors: Zhao Xin , Liu Shuo , Que Haotian , Huang Min , Zhu Qibing
Published: September 2023

Wheat seed classification is a critical task for ensuring crop quality and yield. However, the characteristics of wheat seeds can vary due to variations in climate, soil, and other environmental factors across different years. Consequently, the present classification model is no longer adequate for accurately classifying novel samples. To tackle this issue, this paper proposes an adaptive domain feature separation (ADFS) network that utilizes hyperspectral imaging techniques for cross-year classification of wheat seed varieties. The primary objective is to improve the generalization ability of the model at a minimum cost. ADFS leverages deep learning techniques to acquire domain-irrelevant features from hyperspectral data, thus effectively addressing the issue of domain shifts across datasets. The feature spaces are divided into three parts using different modules. One shared module aligns feature distributions between the source and target datasets from different years, thereby enhancing the model’s generalization and robustness. Additionally, two private modules extract class-specific features and domain-specific features. The transfer mechanism does not learn domain-specific features to reduce negative transfer and improve classification accuracy. Extensive experiments conducted on a two-year dataset comprising four wheat seed varieties demonstrate the effectiveness of ADFS in wheat seed classification. Compared with three typical transfer learning networks, ADFS can achieve the best accuracy of wheat seed classification with small batch samples updated, thereby addressing new seasonal variability.
Incremental Learning for Online Data Using QR Factorization on Convolutional Neural Networks
Authors: Kim Jonghong , Lee WonHee , Baek Sungdae , Hong Jeong-Ho , Lee Minho
Published: September 2023

Catastrophic forgetting, which means a rapid forgetting of learned representations while learning new data/samples, is one of the main problems of deep neural networks. In this paper, we propose a novel incremental learning framework that can address the forgetting problem by learning new incoming data in an online manner. We develop a new incremental learning framework that can learn extra data or new classes with less catastrophic forgetting. We adopt the hippocampal memory process to the deep neural networks by defining the effective maximum of neural activation and its boundary to represent a feature distribution. In addition, we incorporate incremental QR factorization into the deep neural networks to learn new data with both existing labels and new labels with less forgetting. The QR factorization can provide the accurate subspace prior, and incremental QR factorization can reasonably express the collaboration between new data with both existing classes and new class with less forgetting. In our framework, a set of appropriate features (i.e., nodes) provides improved representation for each class. We apply our method to the convolutional neural network (CNN) for learning Cifar-100 and Cifar-10 datasets. The experimental results show that the proposed method efficiently alleviates the stability and plasticity dilemma in the deep neural networks by providing the performance stability of a trained network while effectively learning unseen data and additional new classes.
Identification of Soil Types and Salinity Using MODIS Terra Data and Machine Learning Techniques in Multiple Regions of Pakistan
Authors: Haq Yasin Ul , Shahbaz Muhammad , Asif Shahzad , Ouahada Khmaies , Hamam Habib
Published: September 2023

Soil, a significant natural resource, plays a crucial role in supporting various ecosystems and serves as the foundation of Pakistan’s economy due to its primary use in agriculture. Hence, timely monitoring of soil type and salinity is essential. However, traditional methods for identifying soil types and detecting salinity are time-consuming, requiring expert intervention and extensive laboratory experiments. The objective of this study is to propose a model that leverages MODIS Terra data to identify soil types and detect soil salinity. To achieve this, 195 soil samples were collected from Lahore, Kot Addu, and Kohat, dating from October 2022 to November 2022. Simultaneously, spectral data of the same regions were obtained to spatially map soil types and salinity of bare land. The spectral reflectance of band values, salinity indices, and vegetation indices were utilized to classify the soil types and predict soil salinity. To perform the classification and regression tasks, the study employed three popular techniques in the research community: Random Forest (RF), Ada Boost (AB), and Gradient Boosting (GB), along with Decision Tree (DT), K-Nearest Neighbor (KNN), and Extra Tree (ET). A 70–30 test train validation split was used for the implementation of these techniques. The efficacy of the multi-class classification models for soil types was evaluated using accuracy, precision, recall, and f1-score. On the other hand, the regression models’ performances were evaluated and compared using R-squared (R2), Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). The results demonstrated that Random Forest outperformed other methods for both predicting soil types (accuracy = 65.38, precision = 0.60, recall = 0.57, and f1-score = 0.57) and predicting salinity (R2 = 0.90, MAE = 0.56, MSE = 0.98, RMSE = 0.97). Finally, the study designed a web portal to enable real-time prediction of soil types and salinity using these models. This web portal can be utilized by farmers and decision-makers to make informed decisions regarding soil, crop cultivation, and agricultural planning.
A Deep Learning Approach for Precision Viticulture, Assessing Grape Maturity via YOLOv7
Authors: Badeka Eftichia , Karapatzak Eleftherios , Karampatea Aikaterini , Bouloumpasi Elisavet , Kalathas Ioannis , Lytridis Chris , Tziolas Emmanouil , Tsakalidou Viktoria Nikoleta , Kaburlasos Vassilis G.
Published: September 2023

In the viticulture sector, robots are being employed more frequently to increase productivity and accuracy in operations such as vineyard mapping, pruning, and harvesting, especially in locations where human labor is in short supply or expensive. This paper presents the development of an algorithm for grape maturity estimation in the framework of vineyard management. An object detection algorithm is proposed based on You Only Look Once (YOLO) v7 and its extensions in order to detect grape maturity in a white variety of grape (Assyrtiko grape variety). The proposed algorithm was trained using images received over a period of six weeks from grapevines in Drama, Greece. Tests on high-quality images have demonstrated that the detection of five grape maturity stages is possible. Furthermore, the proposed approach has been compared against alternative object detection algorithms. The results showed that YOLO v7 outperforms other architectures both in precision and accuracy. This work paves the way for the development of an autonomous robot for grapevine management.
Best Parameters of Heart Rate Variability for Assessing Autonomic Responses to Brief Rectal Distention in Patients with Irritable Bowel Syndrome
Authors: Ali M. Khawar , Gong Shiyuan , Nojkov Borko , Burnett Colin , Chen Jiande D. Z.
Published: September 2023

Heart rate variability (HRV) has been used to measure autonomic nervous system (ANS) activity noninvasively. The purpose of this study was to identify the most suitable HRV parameters for ANS activity in response to brief rectal distension (RD) in patients with Irritable Bowel Syndrome (IBS). IBS patients participated in a five-session study. During each visit, an ECG was recorded for 15 min for baseline values and during rectal distension. For rectal distension, a balloon was inflated in the rectum and the pressure was increased in steps of 5 mmHg for 30 s; each distension was followed by a 30 s rest period when the balloon was fully deflated (0 mmHg) until either the maximum tolerance of each patient was reached or up to 60 mmHg. The time-domain, frequency-domain and nonlinear HRV parameters were calculated to assess the ANS activity. The values of each HRV parameter were compared between baseline and RD for each of the five visits as well as for all five visits combined. The sensitivity and robustness/reproducibility of each HRV parameter were also assessed. The parameters included the Sympathetic Index (SI); Root Mean Square of Successive Differences (RMSSD); High-Frequency Power (HF); Low-Frequency Power (LF); Normalized HF Power (HFn); Normalized LF Power (LFn); LF/HF; Respiratory Sinus Arrhythmia (RSA); the Poincare Plot’s SD1, SD2 and their ratio; and the pNN50, SDSD, SDNN and SDNN Index. Data from 17 patients were analyzed and compared between baseline and FD and among five sessions. The SI was found to be the most sensitive and robust HRV parameter in detecting the ANS response to RD. Out of nine parasympathetic parameters, only the SDNN and SDNN Index were sensitive enough to detect the parasympathetic modulation to RD during the first visit. The frequency-domain parameters did not show any change in response to RD. It was also observed that the repetitive RD in IBS patients resulted in a decreased autonomic response due to habituation because the amount of change in the HRV parameters was the highest during the first visit but diminished during subsequent visits. In conclusion, the SI and SDNN/SDNN Index are most sensitive at assessing the autonomic response to rectal distention. The autonomic response to rectal distention diminishes in repetitive sessions, demonstrating the necessity of randomization for repetitive tests.
GPU Rasterization-Based 3D LiDAR Simulation for Deep Learning
Authors: Denis Leon , Royen Remco , Bolsée Quentin , Vercheval Nicolas , Pižurica Aleksandra , Munteanu Adrian
Published: September 2023

High-quality data are of utmost importance for any deep-learning application. However, acquiring such data and their annotation is challenging. This paper presents a GPU-accelerated simulator that enables the generation of high-quality, perfectly labelled data for any Time-of-Flight sensor, including LiDAR. Our approach optimally exploits the 3D graphics pipeline of the GPU, significantly decreasing data generation time while preserving compatibility with all real-time rendering engines. The presented algorithms are generic and allow users to perfectly mimic the unique sampling pattern of any such sensor. To validate our simulator, two neural networks are trained for denoising and semantic segmentation. To bridge the gap between reality and simulation, a novel loss function is introduced that requires only a small set of partially annotated real data. It enables the learning of classes for which no labels are provided in the real data, hence dramatically reducing annotation efforts. With this work, we hope to provide means for alleviating the data acquisition problem that is pertinent to deep-learning applications.
Tris-Copper Nanozyme as a Novel Laccase Mimic for the Detection and Degradation of Phenolic Compounds
Authors: Chai Tong-Qing , Wang Jia-Li , Chen Guo-Ying , Chen Ling-Xiao , Yang Feng-Qing
Published: September 2023

Phenolic compounds are one of the main organic pollutants in the environment that can seriously affect ecosystems, even at very low concentrations. Due to the resistance of phenolic compounds to microorganisms, conventional biological treatment methods face challenges in effectively addressing this pollution problem. In this study, a novel laccase mimic (Tris-Cu nanozyme) is prepared using a simple and rapid synthesis strategy based on the coordination of copper ions and amino groups in Tris(hydroxymethyl)aminomethane (Tris). It is found that the Tris-Cu nanozyme exhibits good catalytic activity against a variety of phenolic compounds, the Km, Vmax and Kcat are determined to be 0.18 mM, 15.62 μM·min−1 and 1.57 × 107 min−1 using 2,4-dichlorophenol (2,4-DP) as the substrate, respectively. Then, based on the laccase-like activity of the Tris-Cu nanozyme, a novel colorimetric method for 2,4-DP (the limit of detection (LOD) = 2.4 μM, S/N = 3) detection in the range of 10–400 μM was established, and its accuracy was verified by analyzing tap and lake water samples. In addition, the Tris-Cu nanozyme shows excellent removal abilities for six phenolic compounds in experiments. The removal percentages for 2,4-DP, 2-chlorophenol (2-CP), phenol, resorcinol, 2,6-dimethoxyphenol (2,6-DOP), and bisphenol A (BPA) are 100%, 100%, 100%, 100%, 87%, and 81% at 1 h, respectively. In the simulated effluent, the Tris-Cu nanozyme maintains its efficient catalytic activity towards 2,4-DP, with a degradation percentage of 76.36% at 7 min and a reaction rate constant (k0) of 0.2304 min−1. Therefore, this metal–organic complex shows promise for applications in the monitoring and degrading of environmental pollutants.
FILNet: Fast Image-Based Indoor Localization Using an Anchor Control Network
Authors: Liu Sikang , Huang Zhao , Li Jiafeng , Li Anna , Huang Xingru
Published: September 2023

This paper designs a fast image-based indoor localization method based on an anchor control network (FILNet) to improve localization accuracy and shorten the duration of feature matching. Particularly, two stages are developed for the proposed algorithm. The offline stage is to construct an anchor feature fingerprint database based on the concept of an anchor control network. This introduces detailed surveys to infer anchor features according to the information of control anchors using the visual–inertial odometry (VIO) based on Google ARcore. In addition, an affine invariance enhancement algorithm based on feature multi-angle screening and supplementation is developed to solve the image perspective transformation problem and complete the feature fingerprint database construction. In the online stage, a fast spatial indexing approach is adopted to improve the feature matching speed by searching for active anchors and matching only anchor features around the active anchors. Further, to improve the correct matching rate, a homography matrix filter model is used to verify the correctness of feature matching, and the correct matching points are selected. Extensive experiments in real-world scenarios are performed to evaluate the proposed FILNet. The experimental results show that in terms of affine invariance, compared with the initial local features, FILNet significantly improves the recall of feature matching from 26% to 57% when the angular deviation is less than 60 degrees. In the image feature matching stage, compared with the initial K-D tree algorithm, FILNet significantly improves the efficiency of feature matching, and the average time of the test image dataset is reduced from 30.3 ms to 12.7 ms. In terms of localization accuracy, compared with the benchmark method based on image localization, FILNet significantly improves the localization accuracy, and the percentage of images with a localization error of less than 0.1m increases from 31.61% to 55.89%.
A Markov Chain Model for Determining the Optimal Time to Move Pregnant Cows to Individual Calving Pens
Authors: Phyo Cho Nilar , Tin Pyke , Zin Thi Thi
Published: September 2023

The use of individual calving pens in modern farming is widely recognized as a good practice for promoting good animal welfare during parturition. However, determining the optimal time to move a pregnant cow to a calving pen can be a management challenge. Moving cows too early may result in prolonged occupancy of the pen, while moving them too late may increase the risk of calving complications and production-related diseases. In this paper, a simple random walk type Markov Chain Model to predict the optimal time for moving periparturient cows to individual calving pens was proposed. Behavior changes such as lying time, standing time, and rumination time were analyzed using a video monitoring system, and we formulated these changes as the states of a Markov Chain with an absorbing barrier. The model showed that the first time entering an absorbing state was the optimal time for a pregnant cow to be moved to a calving pen. The proposed method was validated through a series of experiments in a real-life dairy farm, showing promising results with high accuracy.
CoFe2O4/MoS2@Au: Multifunction Z-Scheme Heterojunction for SERS Monitoring and Photocatalytic Degradation of Fungicides
Authors: Dong Qirong , Wei Qingyi , Pu Hongbin
Published: September 2023

Efficient detection and degradation of fungicides are greatly concerned with aquatic food safety. Herein, a multifunction CoFe2O4/MoS2@Au (ACMS) composite was synthesized for crystal violet (CV) and malachite green (MG) photocatalytic degradation and SERS determination. As the construction of the Z-scheme heterostructure of ACMS, which enhanced the light absorption capability and the separation efficiency of photoexcited carrier significantly, ACMS possessed an excellent photocatalytic performance with a degradation rate of 94.76% for CV under simulated solar light irradiation. Furthermore, the multifunction ACMS exhibited superior SERS capability with a detection limit (LOD) of 4.309 × 10−2 μg L−1 for MG residues in water. And the ACMS substrates could be utilized to determine the MG residues in crucian carp extract, resulting in a recovery rate of 96.00~116.00%. In addition, such multifunction heterojunctions were performed for in situ monitoring of the photodegradation process. This research opened up a novel perspective on the applications of heterojunction-based multifunction materials for food safety control.