bluuebunny/crossref_metadata_2025 huggingface dataset:
(-)-Fenchone Prevents Cysteamine-Induced Duodenal Ulcers and Accelerates Healing Promoting Re-Epithelialization of Gastric Ulcers in Rats via Antioxidant and Immunomodulatory Mechanisms
Authors: Araruna Maria Elaine Cristina , Júnior Edvaldo Balbino Alves , Serafim Catarina Alves de Lima , Pessoa Matheus Marley Bezerra , Pessôa Michelle Liz de Souza , Alves Vitória Pereira , Silva Marcelo Sobral da , Sobral Marianna Vieira , Alves Adriano Francisco , Nunes Mayara Karla dos Santos , Araújo Aurigena Antunes , Batista Leônia Maria
Published: May 2024

Background: (-)-Fenchone is a naturally occurring monoterpene found in the essential oils of Foeniculum vulgare Mill., Thuja occidentalis L., and Peumus boldus Molina. Pharmacological studies have reported its antinociceptive, antimicrobial, anti-inflammatory, antidiarrheal, and antioxidant activities. Methods: The preventive antiulcer effects of (-)-Fenchone were assessed through oral pretreatment in cysteamine-induced duodenal lesion models. Gastric healing, the underlying mechanisms, and toxicity after repeated doses were evaluated using the acetic acid-induced gastric ulcer rat model with oral treatment administered for 14 days. Results: In the cysteamine-induced duodenal ulcer model, fenchone (37.5–300 mg/kg) significantly decreased the ulcer area and prevented lesion formation. In the acetic acid-induced ulcer model, fenchone (150 mg/kg) reduced (p < 0.001) ulcerative injury. These effects were associated with increased levels of reduced glutathione (GSH), superoxide dismutase (SOD), interleukin (IL)-10, and transforming growth factor-beta (TGF-β). Furthermore, treatment with (-)-Fenchone (150 mg/kg) significantly reduced (p < 0.001) malondialdehyde (MDA), myeloperoxidase (MPO), interleukin-1 beta (IL-1β), tumor necrosis factor-alpha (TNF-α), and nuclear transcription factor kappa B (NF-κB). A 14-day oral toxicity investigation revealed no alterations in heart, liver, spleen, or kidney weight, nor in the biochemical and hematological parameters assessed. (-)-Fenchone protected animals from body weight loss while maintaining feed and water intake. Conclusion: (-)-Fenchone exhibits low toxicity, prevents duodenal ulcers, and enhances gastric healing activities. Antioxidant and immunomodulatory properties appear to be involved in its therapeutic effects.
Exploring the Mechanism of Fufang Danshen Tablet against Atherosclerosis by Network Pharmacology and Experimental Validation
Authors: Liu Yuling , Su Weiwei , Li Peibo , Zeng Xuan , Zheng Yuying , Wang Yonggang , Peng Wei , Wu Hao
Published: May 2024

Atherosclerosis is the main pathological basis of cardiovascular diseases (CVDs). Fufang Danshen Tablet (FDT) is a traditional Chinese medicine that has been clinically used to treat CVDs for more than 40 years. Nevertheless, owing to the complexity of the ingredients, the pharmacological mechanism of FDT in the treatment of CVDs has not been fully elucidated. In this study, an integrated strategy of UFLC-Q-TOF-MS/MS, network pharmacology, molecular biology, and transcriptomics was used to elucidate the mechanisms of action of FDT in the treatment of atherosclerosis. In total, 22 absorbed constituents were identified in rat serum after oral administration of FDT. In silico, network pharmacology studies have shown that FDT regulates four key biological functional modules for the treatment of atherosclerosis: oxidative stress, cell apoptosis, energy metabolism, and immune/inflammation. In animal experiments, FDT exerted protective effects against atherosclerosis by reducing the plaque area and lipid levels in ApoE−/− mice. Furthermore, we found that FDT inhibited inflammatory macrophage accumulation by regulating the expression of Selp and Ccl2, which are both involved in monocyte adhesion and migration. The inhibition of monocyte recruitment by FDT is a new perspective to elucidate the anti-atherosclerotic mechanism of FDT, which has not been adopted in previous studies on FDT. Our results may help to elucidate the therapeutic mechanism of FDT against CVDs and provide potential therapeutic targets.
Enzymatic Metabolic Switches of Astrocyte Response to Lipotoxicity as Potential Therapeutic Targets for Nervous System Diseases
Authors: Angarita-Rodríguez Andrea , Matiz-González J. Manuel , Pinzón Andrés , Aristizabal Andrés Felipe , Ramírez David , Barreto George E. , González Janneth
Published: May 2024

Astrocytes play a pivotal role in maintaining brain homeostasis. Recent research has highlighted the significance of palmitic acid (PA) in triggering pro-inflammatory pathways contributing to neurotoxicity. Furthermore, Genomic-scale metabolic models and control theory have revealed that metabolic switches (MSs) are metabolic pathway regulators by potentially exacerbating neurotoxicity, thereby offering promising therapeutic targets. Herein, we characterized these enzymatic MSs in silico as potential therapeutic targets, employing protein–protein and drug–protein interaction networks alongside structural characterization techniques. Our findings indicate that five MSs (P00558, P04406, Q08426, P09110, and O76062) were functionally linked to nervous system drug targets and may be indirectly regulated by specific neurological drugs, some of which exhibit polypharmacological potential (e.g., Trifluperidol, Trifluoperazine, Disulfiram, and Haloperidol). Furthermore, four MSs (P00558, P04406, Q08426, and P09110) feature ligand-binding or allosteric cavities with druggable potential. Our results advocate for a focused exploration of P00558 (phosphoglycerate kinase 1), P04406 (glyceraldehyde-3-phosphate dehydrogenase), Q08426 (peroxisomal bifunctional enzyme, enoyl-CoA hydratase, and 3-hydroxyacyl CoA dehydrogenase), P09110 (peroxisomal 3-ketoacyl-CoA thiolase), and O76062 (Delta(14)-sterol reductase) as promising targets for the development or repurposing of pharmacological compounds, which could have the potential to modulate lipotoxic-altered metabolic pathways, offering new avenues for the treatment of related human diseases such as neurological diseases.
An Investigation into the Effects of Processing Factors on the Properties and Scaling-Up Potential of Propranolol-Loaded Chitosan Nanogels
Authors: Ho Hei Ming Kenneth , Day Richard M. , Craig Duncan Q. M.
Published: May 2024

Chitosan-triphosphate (TPP) nanogels are widely studied drug delivery carrier systems, typically prepared via a simple mixing process. However, the effects of the processing factors on nanogel production have not been extensively explored, despite the importance of understanding and standardising such factors to allow upscaling and commercial usage. This study aims to systematically evaluate the effects of various fabrication and processing factors on the properties of nanogels using a Design of Experiment approach. Hydrodynamic size, polydispersity index (PDI), zeta potential, and encapsulation efficiency were determined as the dependent factors. The temperature, stirring rate, chitosan grade, crosslinker choice, and the interaction term between temperature and chitosan grade were found to have a significant effect on the particle size, whereas the effect of temperature and the addition rate of crosslinker on the PDI was also noteworthy. Moreover, the addition rate of the crosslinker and the volume of the reaction vessel were found to impact the encapsulation efficiency. The zeta potential of the nanogels was found to be governed by the chitosan grade. The optimal fabrication conditions for the development of medium molecular weight chitosan and TPP nanogels included the following: the addition rate for TPP solution was set at 2 mL/min, while the solution was then stirred at a temperature of 50 °C and a stirring speed of 600 rpm. The volume of the glass vial used was 28 mL, while the stirrer size was 20 mm. The second aim of the study was to evaluate the potential for scaling up the nanogels. Size and PDI were found to increase from 128 nm to 151 nm and from 0.232 to 0.267, respectively, when the volume of the reaction mixture was increased from 4 to 20 mL and other processing factors were kept unchanged. These results indicate that caution is required when scaling up as the nanogel properties may be significantly altered with an increasing production scale.
Synergistic Enhancement of Targeted Wound Healing by Near-Infrared Photodynamic Therapy and Silver Metal–Organic Frameworks Combined with S- or N-Doped Carbon Dots
Authors: Nešić Maja D. , Popović Iva A. , Žakula Jelena , Korićanac Lela , Filipović Tričković Jelena , Valenta Šobot Ana , Jiménez Maria Victoria , Algarra Manuel , Dučić Tanja , Stepić Milutin
Published: May 2024

The literature data emphasize that nanoparticles might improve the beneficial effects of near-infrared light (NIR) on wound healing. This study investigates the mechanisms of the synergistic wound healing potential of NIR light and silver metal–organic frameworks combined with nitrogen- and sulfur-doped carbon dots (AgMOFsN-CDs and AgMOFsS-CDs, respectively), which was conducted by testing the fibroblasts viability, scratch assays, biochemical analysis, and synchrotron-based Fourier transform infrared (SR-FTIR) cell spectroscopy and imaging. Our findings reveal that the combined treatment of AgMOFsN-CDs and NIR light significantly increases cell viability to nearly 150% and promotes cell proliferation, with reduced interleukin-1 levels, suggesting an anti-inflammatory response. SR-FTIR spectroscopy shows this combined treatment results in unique protein alterations, including increased α-helix structures and reduced cross-β. Additionally, protein synthesis was enhanced upon the combined treatment. The likely mechanism behind the observed changes is the charge-specific interaction of N-CDs from the AgMOFsN-CDs with proteins, enhanced by NIR light due to the nanocomposite’s optical characteristics. Remarkably, the complete wound closure in the in vitro scratch assay was achieved exclusively with the combined NIR and AgMOFsN-CDs treatment, demonstrating the promising application of combined AgMOFsN-CDs with NIR light photodynamic therapy in regenerative nanomedicine and tissue engineering.
Novel Drug Delivery Systems: An Important Direction for Drug Innovation Research and Development
Authors: Chen Qian , Yang Zhen , Liu Haoyu , Man Jingyuan , Oladejo Ayodele Olaolu , Ibrahim Sally , Wang Shengyi , Hao Baocheng
Published: May 2024

The escalating demand for enhanced therapeutic efficacy and reduced adverse effects in the pharmaceutical domain has catalyzed a new frontier of innovation and research in the field of pharmacy: novel drug delivery systems. These systems are designed to address the limitations of conventional drug administration, such as abbreviated half-life, inadequate targeting, low solubility, and bioavailability. As the disciplines of pharmacy, materials science, and biomedicine continue to advance and converge, the development of efficient and safe drug delivery systems, including biopharmaceutical formulations, has garnered significant attention both domestically and internationally. This article presents an overview of the latest advancements in drug delivery systems, categorized into four primary areas: carrier-based and coupling-based targeted drug delivery systems, intelligent drug delivery systems, and drug delivery devices, based on their main objectives and methodologies. Additionally, it critically analyzes the technological bottlenecks, current research challenges, and future trends in the application of novel drug delivery systems.
Intercultural and Deliberative Disaster Ethics in Volcanic Eruptions
Authors: Bueno Gómez Noelia , Beato Bergua Salvador
Published: May 2024

The objectives of this article are (i) to identify the most challenging ethical dilemmas and questions arising from the experiences of communities and professionals affected by or involved in volcanic eruptions, including risk management, the dissemination of information, and tourism; and (ii) to provide arguments for intercultural ethics to address these dilemmas. Intercultural ethics provide invaluable resources to disaster ethics across all three phases of the complete disaster management cycle. In this article, intercultural ethics is viewed as an ethics grounded in ongoing dialogue, facilitating the examination and establishment of norms and a critical reflection on values and their evolution. This approach recognizes power dynamics that may influence fair participation in dialogues and aims to address them, while also integrating elements of deliberative ethics to ensure that dialogues genuinely contribute to legitimizing decisions. Intercultural sensibility helps bridge the gap between experts and non-experts in both directions (a) by emphasizing the duty of transferring scientific knowledge (for experts) and the responsibility of acquiring scientific literacy (for citizens); and (b) by highlighting the importance of a ‘knowledge dialogue’ that acknowledges the non-scientific knowledge of citizens, rooted in their cultural background and experiences of dealing with past disasters, and shaping life in volcanic territories.
Modeling Nitrogen Fate and Water and Nitrogen Use Efficiencies under Different Greenhouse Vegetable Production Systems Using the WHCNS-Veg Model
Authors: Zhang Hongyuan , Batchelor William D. , Hu Kelin , Han Hui , Li Ji
Published: May 2024

Quantitative evaluation of the effects of diverse greenhouse vegetable production systems (GVPS) on vegetable yield, soil water consumption, and nitrogen (N) fates could provide a scientific basis for identifying optimum water and fertilizer management practices for GVPS. This research was conducted from 2013 to 2015 in a greenhouse vegetable field in Quzhou County, North China. Three production systems were designed: conventional (CON), integrated (INT), and organic (ORG) systems. The WHCNS-Veg model was employed for simulating vegetable growth, water dynamics, and fates of N, as well as water and N use efficiencies (WUE and NUE) for four continuous growing seasons. The simulation results revealed that nitrate leaching and gaseous N emissions constituted the predominant N loss within GVPS, which separately accounted for 11.5–59.4% and 6.0–21.1% of the N outputs. The order of vegetable yield, N uptake, WUE, and NUE under different production systems was ORG > INT > CON, while the order of nitrate leaching and gaseous N loss was CON > INT > ORG. Compared to CON, ORG exhibited a significant increase in yield, N uptake, WUE, and NUE by 24.6%, 24.2%, 26.1%, and 89.7%, respectively, alongside notable reductions in nitrate leaching and gaseous N loss by 67.7% and 63.2%, respectively. The ORG system should be recommended to local farmers.
Facile Fabrication of Highly Efficient Chitosan-Based Multifunctional Coating for Cotton Fabrics with Excellent Flame-Retardant and Antibacterial Properties
Authors: Huang Yuan-Yuan , Zhang Li-Ping , Cao Xing , Tian Xin-Yu , Ni Yan-Peng
Published: May 2024

Interest in the development of eco-friendly, sustainable, and convenient bio-based coatings to enhance flame retardancy and antibacterial properties in cotton fabrics is growing. In this work, chitosan was protonated at its amino groups using a method with a high atom economy using an equimolar amount of amino trimethylene phosphonic acid (ATMP), resulting in the fabrication of a single-component chitosan-based multifunctional coating (ATMP-CS), thereby avoiding any additional neutralization or purification steps. Cotton fabrics coated with various loads of ATMP-CS were prepared through a padding–drying–curing process. The morphology, thermal stability, mechanical properties, antibacterial properties, flame-retardant behavior, and flame-retardant mechanism of these fabrics were investigated. The coating exhibited excellent film-forming properties, and it imparted a uniform protective layer onto the surfaces of the cotton fabrics. When the load capacity reached 11.5%, the coated fabrics achieved a limiting oxygen index of 29.7% and successfully passed the VFT test. Moreover, the ATMP-CS coating demonstrated antibacterial rates against Escherichia coli and Staphylococcus aureus reaching 95.1% and 99.9%, respectively. This work presents a straightforward and gentle approach to fabricating colorless, environmentally friendly, and highly efficient fabric coatings that have potential applications in promoting the use of bio-based materials.
How the Digital Product Passport Can Lead the Plastics Industry towards a Circular Economy—A Case Study from Bottle Caps to Frisbees
Authors: Rumetshofer Thomas , Straka Klaus , Fischer Jörg
Published: May 2024

The Digital Product Passport (DPP) as a product-specific data set is a powerful tool that provides information on the origin or composition of products and increases transparency and traceability. This recycling case study accompanies the production of 2192 frisbees, which originated from collected beverage bottle caps. In total, 486.7 kg of feedstock was collected and transformed into 363.2 kg of final product with verified traceability through all process steps via a DPP, provided by the R-Cycle initiative and based on the GS1 standard. This demanded a generally agreed dataset, the availability of technical infrastructure, and additional effort in the processing steps to collect and process the data. R-Cycle offers a one-layer DPP where the data structure is lean and information is visible to everyone. This is beneficial to a variety of stakeholders in terms of transparency. However, it does not allow the sharing of sensitive information. On the one hand, the DPP has a high potential to be an enabler for customer engagement, origin verification, or as a starting point for more efficient and advanced recycling of plastics. On the other hand, the DPP involves a certain effort in data generation and handling, which must be justified by the benefits. For small, simple packaging items, the DPP may not be the perfect solution for all problems. However, with a broader societal mindset and legislative push, the DPP can become a widely used and trusted declaration tool. This can support the plastics industry in its journey towards a circular economy.
WDFA-YOLOX: A Wavelet-Driven and Feature-Enhanced Attention YOLOX Network for Ship Detection in SAR Images
Authors: Wu Falin , Hu Tianyang , Xia Yu , Ma Boyi , Sarwar Saddam , Zhang Chunxiao
Published: May 2024

Ships are important targets for modern naval warfare detection and reconnaissance. The accurate detection of ships contributes to the maintenance of maritime rights and interests and the realisation of naval strategy. Synthetic Aperture Radar (SAR) image detection tasks play a vital role in ship detection, which has consistently been a research hotspot in the field of SAR processing. Although significant progress has been achieved in SAR ship detection techniques using deep learning methods, some challenges still persist. Natural images and SAR images significantly diverge in imaging mechanisms and scattering characteristics. In complex background environments, ships exhibit multiscale variations and dense arrangements, and numerous small-sized ships may be present, culminating in false or missed detections. To address these issues, we propose a novel SAR ship detection network, namely, a Wavelet-Driven Feature-Enhanced Attention–You Only Look Once X (WDFA-YOLOX) network. Firstly, we propose a Wavelet Cascade Residual (WCR) module based on the traditional image processing technique wavelet transform, which is embedded within an improved Spatial Pyramid Pooling (SPP) module, culminating in the formation of the effective wavelet transform-based SPP module (WSPP). The WSPP compensates for the loss of fine-grained feature information during pooling, enhancing the capability of the network to detect ships amidst complex background interference. Secondly, a Global and Local Feature Attention Enhancement (GLFAE) module is proposed, leveraging a parallel structure that combines convolutional modules with transformer modules to reduce the effect of irrelevant information and effectively strengthens valid features associated with small-sized ships, resulting in a reduction in false negatives in small-sized ship detection. Finally, a novel loss function, the Chebyshev distance-generalised IoU loss function, is proposed to significantly enhance both the precision of the detection box and the network convergence speed. To support our approach, we performed thorough experiments on the SSDD and HRSID, achieving an average precision (AP) of 99.11% and 96.20%, respectively, in ship detection. The experimental results demonstrate that WDFA-YOLOX has significant advantages in terms of detection accuracy, generalisation capability, and detection speed and can effectively realise more accurate detection in SAR images, consistently exhibiting superior performance and application value in SAR ship detection.
Winter Durum Wheat Disease Severity Detection with Field Spectroscopy in Phenotyping Experiment at Leaf and Canopy Level
Authors: Ganeva Dessislava , Filchev Lachezar , Roumenina Eugenia , Dragov Rangel , Nedyalkova Spasimira , Bozhanova Violeta
Published: May 2024

Accurate disease severity assessment is critical for plant breeders, as it directly impacts crop yield. While hyperspectral remote sensing has shown promise for disease severity assessment in breeding experiments, most studies have focused on either leaf or canopy levels, neglecting the valuable insights gained from a combined approach. Moreover, many studies have centered on experiments involving a single disease and a few genotypes. However, this approach needs to accurately represent the challenges encountered in field conditions, where multiple diseases could occur simultaneously. To address these gaps, our current study analyses a combination of diseases, yellow rust, brown rust, and yellow leaf spots, collectively evaluated as the percentage of the diseased leaf area relative to the total leaf area (DA) at both leaf and canopy levels, using hyperspectral data from an ASD field spectrometer. We quantitatively estimate overall disease severity across fifty-two winter durum wheat genotypes categorized into early (medium milk) and late (late milk) groups based on the phenophase. Chlorophyll content (CC) within each group is studied concerning infection response, and a correlation analysis is conducted for each group with nine vegetation indices (VI) known for their sensitivity to rust and leaf spot infection in wheat. Subsequent parametric (linear and polynomial) and nonparametric (partial least squares and kernel ridge) regression analyses were performed using all available spectral bands. We found a significant reduction in Leaf CC (>30%) in the late group and Canopy CC (<10%) for both groups. YROI and LRDSI_1 are the VIs that exhibited notable and strong negative correlations with Leaf CC in the late group, with a Pearson coefficient of −0.73 and −0.72, respectively. Interestingly, spectral signatures between the early and late disease groups at both leaf and canopy levels exhibit opposite trends. The regression analysis showed we could retrieve leaf CC only for the late group, with R2 of 0.63 and 0.42 for the cross-validation and test datasets, respectively. Canopy CC retrieval required separate models for each group: the late group achieved R2 of 0.61 and 0.37 (cross-validation and test), while the early group achieved R2 of 0.48 and 0.50. Similar trends were observed for canopy DA, with separate models for early and late groups achieving comparable R2 values of 0.53 and 0.51 (cross-validation) and 0.35 and 0.36 (test), respectively. All of our models had medium accuracy and tended to overfit. In this study, we analyzed the spectral response mechanism associated with durum wheat diseases, offering a novel crop disease severity assessment approach. Additionally, our findings serve as a foundation for detecting resistant wheat varieties, which is the most economical and environmentally friendly management strategy for wheat leaf diseases on a large scale in the future.
InSAR-DEM Block Adjustment Model for Upcoming BIOMASS Mission: Considering Atmospheric Effects
Authors: Wu Kefu , Fu Haiqiang , Zhu Jianjun , Hu Huacan , Li Yi , Liu Zhiwei , Wan Afang , Wang Feng
Published: May 2024

The unique P-band synthetic aperture radar (SAR) instrument, BIOMASS, is scheduled for launch in 2024. This satellite will enhance the estimation of subcanopy topography, owing to its strong penetration and fully polarimetric observation capability. In order to conduct global-scale mapping of the subcanopy topography, it is crucial to calibrate systematic errors of different strips through interferometric SAR (InSAR) DEM (digital elevation model) block adjustment. Furthermore, the BIOMASS mission will operate in repeat-pass interferometric mode, facing the atmospheric delay errors introduced by changes in atmospheric conditions. However, the existing block adjustment methods aim to calibrate systematic errors in bistatic mode, which can avoid possible errors from atmospheric effects through interferometry. Therefore, there is still a lack of systematic error calibration methods under the interference of atmospheric effects. To address this issue, we propose a block adjustment model considering atmospheric effects. Our model begins by employing the sub-aperture decomposition technique to form forward-looking and backward-looking interferograms, then multi-resolution weighted correlation analysis based on sub-aperture interferograms (SA-MRWCA) is utilized to detect atmospheric delay errors. Subsequently, the block adjustment model considering atmospheric effects can be established based on the SA-MRWCA. Finally, we use robust Helmert variance component estimation (RHVCE) to build the posterior stochastic model to improve parameter estimation accuracy. Due to the lack of spaceborne P-band data, this paper utilized L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR data, which is also long-wavelength, to emulate systematic error calibration of the BIOMASS mission. We chose climatically diverse inland regions of Asia and the coastal regions of South America to assess the model’s effectiveness. The results show that the proposed block adjustment model considering atmospheric effects improved accuracy by 72.2% in the inland test site, with root mean square error (RMSE) decreasing from 10.85 m to 3.02 m. Moreover, the accuracy in the coastal test site improved by 80.2%, with RMSE decreasing from 16.19 m to 3.22 m.
UAV Complex-Scene Single-Target Tracking Based on Improved Re-Detection Staple Algorithm
Authors: Huang Yiqing , Huang He , Niu Mingbo , Miah Md Sipon , Wang Huifeng , Gao Tao
Published: May 2024

With the advancement of remote sensing technology, the demand for the accurate monitoring and tracking of various targets utilizing unmanned aerial vehicles (UAVs) is increasing. However, challenges such as object deformation, motion blur, and object occlusion during the tracking process could significantly affect tracking performance and ultimately lead to tracking drift. To address this issue, this paper introduces a high-precision target-tracking method with anomaly tracking status detection and recovery. An adaptive feature fusion strategy is proposed to improve the adaptability of the traditional sum of template and pixel-wise learners (Staple) algorithm to changes in target appearance and environmental conditions. Additionally, the Moth Flame Optimization (MFO) algorithm, known for its strong global search capability, is introduced as a re-detection algorithm in case of tracking failure. Furthermore, a trajectory-guided Gaussian initialization technique and an iteration speed update strategy are proposed based on sexual pheromone density to enhance the tracking performance of the introduced re-detection algorithm. Comparative experiments conducted on UAV123 and UAVDT datasets demonstrate the excellent stability and robustness of the proposed algorithm.
3D Point Cloud Shape Generation with Collaborative Learning of Generative Adversarial Network and Auto-Encoder
Authors: Yang Dong , Wang Jingyuan , Yang Xi
Published: May 2024

A point cloud is a simple and concise 3D representation, but point cloud generation is a long-term challenging task in 3D vision. However, most existing methods only focus on their effectiveness of generation and auto-encoding separately. Furthermore, both generative adversarial networks (GANs) and auto-encoders (AEs) are the most popular generative models. But there is a lack of related research that investigates the implicit connections between them in the field of point cloud generation. Thus, we propose a new bidirectional network (BI-Net) trained with collaborative learning, introducing more priors through the alternate parameter optimizations of a GAN and AE combination, which is different from the way of combining them at the network structure and loss function level. Specifically, BI-Net acts as a GAN and AE in different data processing directions, where their network structures can be reused. If optimizing only the GAN without the AE, there is no direct constraint of ground truth on the generator’s parameter optimization. This unique approach enables better network optimization and leads to superior generation results. Moreover, we propose a nearest neighbor mutual exclusion (NNME) loss to further homogenize the spatial distribution of generated points during the reverse direction. Extensive experiments were conducted, and the results show that the BI-Net produces competitive and high-quality results on reasonable structure and uniform distributions compared to existing state-of-the-art methods. We believe that our network structure (BI-Net) with collaborative learning could provide a new promising method for future point cloud generation tasks.
A Tension Sensor Array for Cable-Driven Surgical Robots
Authors: Zhou Zhangxi , Yang Jianlin , Runciman Mark , Avery James , Sun Zhijun , Mylonas George
Published: May 2024

Tendon–sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device.
Hammerstein–Wiener Motion Artifact Correction for Functional Near-Infrared Spectroscopy: A Novel Inertial Measurement Unit-Based Technique
Authors: Al-Omairi Hayder R. , AL-Zubaidi Arkan , Fudickar Sebastian , Hein Andreas , Rieger Jochem W.
Published: May 2024

Participant movement is a major source of artifacts in functional near-infrared spectroscopy (fNIRS) experiments. Mitigating the impact of motion artifacts (MAs) is crucial to estimate brain activity robustly. Here, we suggest and evaluate a novel application of the nonlinear Hammerstein–Wiener model to estimate and mitigate MAs in fNIRS signals from direct-movement recordings through IMU sensors mounted on the participant’s head (head-IMU) and the fNIRS probe (probe-IMU). To this end, we analyzed the hemodynamic responses of single-channel oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) signals from 17 participants who performed a hand tapping task with different levels of concurrent head movement. Additionally, the tapping task was performed without head movements to estimate the ground-truth brain activation. We compared the performance of our novel approach with the probe-IMU and head-IMU to eight established methods (PCA, tPCA, spline, spline Savitzky–Golay, wavelet, CBSI, RLOESS, and WCBSI) on four quality metrics: SNR, △AUC, RMSE, and R. Our proposed nonlinear Hammerstein–Wiener method achieved the best SNR increase (p < 0.001) among all methods. Visual inspection revealed that our approach mitigated MA contaminations that other techniques could not remove effectively. MA correction quality was comparable with head- and probe-IMUs.
Advancements in Fatigue Detection: Integrating fNIRS and Non-Voluntary Attention Brain Function Experiments
Authors: Li Ting , Liu Peishuai , Gao Yuan , Ji Xiang , Lin Yu
Published: May 2024

Background: Driving fatigue is a significant concern in contemporary society, contributing to a considerable number of traffic accidents annually. This study explores novel methods for fatigue detection, aiming to enhance driving safety. Methods: This study utilizes electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to monitor driver fatigue during simulated driving experiments lasting up to 7 h. Results: Analysis reveals a significant correlation between behavioral data and hemodynamic changes in the prefrontal lobe, particularly around the 4 h mark, indicating a critical period for driver performance decline. Despite a small participant cohort, the study’s outcomes align closely with established fatigue standards for drivers. Conclusions: By integrating fNIRS into non-voluntary attention brain function experiments, this research demonstrates promising efficacy in accurately detecting driving fatigue. These findings offer insights into fatigue dynamics and have implications for shaping effective safety measures and policies in various industrial settings.
ZPD Retrieval Performances of the First Operational Ship-Based Network of GNSS Receivers over the North-West Mediterranean Sea
Authors: Antonini Andrea , Fibbi Luca , Viti Massimo , Sonnini Aldo , Montagnani Simone , Ortolani Alberto
Published: May 2024

This work presents the design and implementation of an operational infrastructure for the monitoring of atmospheric parameters at sea through GNSS meteorology sensors installed on liners operating in the north-west Mediterranean Sea. A measurement system, capable of operationally and continuously providing the values of surface parameters, is implemented together with software procedures based on a float-PPP approach for estimating zenith path delay (ZPD) values. The values continuously registered over a three year period (2020–2022) from this infrastructure are compared with the data from a numerical meteorological reanalysis model (MERRA-2). The results clearly prove the ability of the system to estimate the ZPD from ship-based GNSS-meteo equipment, with the accuracy evaluated in terms of correlation and root mean square error reaching values between 0.94 and 0.65 and between 18.4 and 42.9 mm, these extreme values being from the best and worst performing installations, respectively. This offers a new perspective on the operational exploitation of GNSS signals over sea areas in climate and operational meteorological applications.
Packed-Nanofiber Solid-Phase Extraction Coupled with High-Performance Liquid Chromatography Fluorescence for Determining Gut Microbiota–Host Cometabolites and Indoleamines in Human Urine
Authors: Wei Lanlan , Kang Xuejun
Published: May 2024

Exercise reduces the risk of inflammatory diseases by modulating different tissue and cell types, including those within the gastrointestinal tract. Obtaining a more comprehensive understanding of pathophysiology requires monitoring of dynamic changes in cometabolites. This study aimed to develop a method for determining gut microbiota–host cometabolites and indoleamines in human urine. Four key gut microbiota–host cometabolites were chromatographically separated by isocratic elution, with a running time of 10 min. The linearity of this method was confirmed over different concentration ranges: 1.0–400 ng/mL for melatonin (MEL), indole-3-propionic acid (3-IPA), indole (IND), and skatole (SKT). This method was extremely sensitive and stable and hence could be successfully applied to characterize the changes in gut microbiota–host cometabolites in human before- and after-running urine. The concentrations of MEL, 3-IPA, IND, and SKT in after-running urine were 84.0 ± 9.69, 25.9 ± 3.39, 343.7 ± 36.8, and 14.6 ± 1.36 ng/mL, respectively. Moreover, the concentrations in before-running urine were 54.2 ± 5.10, 14.4 ± 1.30, 250.8 ± 14.1, and 9.43 ± 1.07 ng/mL, respectively, which showed significantly less difference in concentrations (p < 0.05) in before- than after-running urine. Overall, the established method could simultaneously monitor gut microbiota–host cometabolites and hence can be further applied to clinical and comprehensive pathophysiological studies.
Mediatised Participation: Citizen Journalism and the Decline in User-Generated Content in Online News Media
Authors: Peña-Fernández Simón , Larrondo-Ureta Ainara , Agirreazkuenaga Irati
Published: May 2024

The second generation of web tools shook the journalist profession approximately two decades ago with the proactive incorporation of audiences into the media. Citizen journalism and user-generated content arose as an object of interest due to the democratising value of participation attributed to them, with empowered citizens who could emulate the professional and institutional practises of journalists. However, difficulties soon came to the surface, and audience participation in news media began to be limited. Within this context, this article conducts a critical review of studies on audience participation in news media based on a systematic literature review. The results indicate that, in general, audiences showed low interest in the creation of informative content and that their participation has grown increasingly problematic. In addition, journalists are reticent as they defend their professional role above all else, while company strategies have prioritised making participation profitable. For this reason, the idea of citizen journalism that offers user-created content through the media appears to be a thing of the past, with many characteristics that could define it as a failed innovation. Therefore, the text concludes that audience participation in the media could be defined as mediatised participation.
COVID-19: Uses and Perceptions of Music during Lockdown from a Gender Perspective
Authors: Arriaga-Sanz Cristina , Cabedo-Mas Alberto , Ripollés-Mansilla Antoni , Moliner-Miravet Lidón
Published: May 2024

Starting in the middle of March 2020, various lockdown measures and degrees of confinement were put in place in most European countries as a result of the COVID-19 pandemic. Although this situation meant that more people were likely to experience poorer mental health, largely due to the imposition of social distancing measures, many individuals incorporated music into their coping routines to help improve their psychological well-being. Using a gender perspective, this study analyzes how individuals used music during lockdown and explores the differences between men’s and women’s views on the impact that listening to and making music has on their perceived level of well-being. A questionnaire, MUSIVID19, was administered to a sample of 1868 participants from all the autonomous regions in Spain. The results reveal that in the uses and perceptions of music, the stereotypes underlying the patriarchal system were also reproduced during confinement.
Arts and Humanities Education: A Systematic Review of Emerging Technologies and Their Contribution to Social Well-Being
Authors: Usca Nancy , Samaniego Mariela , Yerbabuena Carlos , Pérez Isaac
Published: May 2024

The purpose of this study is to identify the most applied emerging technologies in the field of arts and humanities, exploring their advantages and potential obstacles. The research results aim to contribute to social and cultural well-being by enhancing the understanding and application of these technologies in cultural, linguistic, and artistic domains. Through a systematic literature review based on the PRISMA protocol, using search strings in two scientific databases, 158 studies were obtained that helped address the research questions posed. The findings indicate that, in arts and humanities, emerging technologies such as virtual reality, the Internet of Things, and mobile learning are transforming creativity, teaching, and management. Identified benefits include interactive, collaborative, and innovative learning, as well as increased accessibility to education. However, challenges such as a lack of digital skills among educators, deficiencies in infrastructure, and resistance to change highlight the need for training programs and overcoming obstacles for effective implementation of these technologies in arts and humanities education. It is concluded that the integration of emerging technologies in the fields of arts and humanities presents an opportunity to promote digital intervention in social well-being, as well as to stimulate creativity and cultural exploration. These initiatives facilitate the dissemination and appreciation of cultural heritage, while also promoting community participation and strengthening an ever-evolving cultural identity.
Precision Regulation and Forecasting of Greenhouse Tomato Growth Conditions Using an Improved GA-BP Model
Authors: Zhang Wei , Zhong Wenyu , Liu Zhidong , Du Baoxia , Li Mingliang , Huang Meng , Yu Helong , Chen Bowei , Tang You
Published: May 2024

Tomatoes are annual herbaceous plants of the family Solanaceae. They have very stringent requirements for their growing environment and climate conditions. To precisely control the greenhouse environment for tomato growth, this project designed and implemented a monitoring system utilizing programmable logic controllers and a data acquisition system for monitoring. Sensors are installed at key locations in the greenhouse, such as near the ground, in the plant canopy, and under the roof, to monitor environmental parameters such as temperature, humidity, light intensity, and carbon dioxide concentration in real time. A three-layer feedforward GA-BP neural network model was established using soil temperature, soil humidity, air humidity, and illumination as predictive parameters. This technology predicts optimal environmental parameters and performs real-time monitoring and intelligent control, overcoming the traditional BP neural network’s drawbacks of slow convergence, susceptibility to disturbance, and poor generalization ability, with the current model’s average prediction error being less than 5%. It provides a theoretical basis and decision support for precision control and related environmental forecasting in agricultural projects. Based on the growth characteristics, physiological and morphological features of tomatoes, and the comprehensive impact of planting conditions, the technology enhances tomato yield and quality while reducing production costs and labor inputs. It mainly includes the establishment of tomato growth models, measurement and control of environmental parameters, and the design and optimization of intelligent decision control systems. Research outcomes in this field are significant for improving agricultural production efficiency, ensuring food security, and promoting sustainable agricultural development.
Effects of Different Film Types on Cotton Growth and Yield under Drip Irrigation
Authors: Ma Zhanli , Liu Jian , Wen Yue , Li Wenhao , Zhu Yan , Song Libing , Li Yunguang , Liang Yonghui , Wang Zhenhua
Published: May 2024

To address residual plastic film in fields in which mulched drip irrigation technology is applied, a sprayable degradable film (consisting of 1–5% clay, 5–20% humic acid, 0.5–5% crosslinker, and 0.5–5% auxiliary and water) can be used as a superior alternative to the plastic film applied in drip-irrigated fields. A field experiment was conducted in Xinjiang, Northwest China, to test the impacts of five different mulching treatments (SF1, sprayable degradable film applied at 1900 kg ha−1; SF2, sprayable degradable film applied at 1900 kg ha−1; SF3, sprayable degradable film applied at 2500 kg ha−1; PF, plastic film; and NF, no film mulching) on cotton growth and development, yield, and water use efficiency. The results showed that, compared to the NF treatment, sprayable degradable film mulching (SF1, SF2, and SF3) positively impacted the soil hydrothermal environment, promoted root growth, significantly increased plant height and leaf area, and enhanced physiological characteristics, which, in turn, increased yield and water use efficiency by 11.79–15.00% and 21.88–30.21%, respectively. The maximum yield and water use efficiency were observed in the PF treatment, amounting to 5345 kg ha−1 and 1.28 kg m−3, respectively, and they had no significant differences from those in the SF3 treatment. In general, applying moderate amounts of sprayable degradable film at a rate of 2500 kg ha−1 represents an effective agronomic strategy for managing residual film contamination while maintaining stable cotton yields.
Enhancing Sewage Sludge Treatment with Hydrothermal Processing: A Case Study of Adana City
Authors: Un Cagri
Published: May 2024

As a byproduct of municipal wastewater treatment systems, sewage sludge has traditionally been treated in low-value applications such as landfilling, posing significant environmental risks due to its pollutant content. However, there is a growing interest in utilizing the energy potential of sewage sludge through thermochemical conversion methods. Among these methods, hydrothermal liquefaction (HTL) has come to the fore as a promising green approach, offering an environmentally friendly means of extracting bio-oils and biochemicals from sewage sludge. In this study, the HTL method, regarded as an innovative approach among sewage sludge treatment methods apart from incineration, pyrolysis, and landfilling, is comparatively investigated in terms of greenhouse gas (GHG) emissions alongside other methods. In particular, this study analyzes the projected amount and various characteristics of sewage sludge that could potentially be generated by 2030 for the city of Adana, which currently produces approximately 185 tons of sewage sludge per day. The findings indicate that without intervention, sludge production is projected to reach 68,897 tons per year by 2030. Moreover, this research demonstrates that the utilization of HTL for sludge treatment results in a reduction of emissions by approximately 7-fold compared with incineration of sewage sludge.