cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28253912.v1
title: Visual Feedback System Supporting Robotic Manipulation of Hemp Plants

description: This paper presents an agricultural robotics system designed to automate the detection and manipulation of male hemp plants, addressing the challenge of manually removing these to enhance crop quality. The solution uses an industry-standard, inexpensive RGB-D camera as the input data source to derive control signals controlling the robotic arm and end effector. Input image data processing is performed by a dedicated neural network model trained using a dataset created specifically for the described task to achieve detection by stalk segmentation and postprocessing. The research involved assessing various neural network models, including UNet, DeepLabV3+, and YOLOv8 in various variants, for their capability to detect stalks accurately and swiftly. Fast operation is necessary for effective real-time feedback in robotic grasping tasks. Among tested architectures, the integration of UNet with ResNet50 was found to provide a good trade-off between detection precision and operational speed on edge AI devices. The resulting solution offers good accuracy and significantly outperforms existing methods in terms of processing speed, promising substantial improvements in agricultural robotics by enabling on-line adaptive grasping using low-cost components. The applications can be extended beyond hemp tending to include various other crops, eliminating tedious manual labor.
DOI: 10.6084/m9.figshare.29979376
title: Characterization of Cellulosic Fibers from the Inflorescences of <i>Echinops sphaerocephalus</i>: An Unexplored Source of Eco-Friendly Sustainable Fibers

description: This study identifies <i>Echinops sphaerocephalus</i> inflorescences as a novel, sustainable fiber source that avoids deforestation. Comprehensive characterization of their chemical, physical, thermal, and morphological properties reveals their potential for diverse applications. Chemical analysis shows that the fibers contain 39.5% cellulose, 36.5% hemicellulose, and 2.9% lignin, corroborated by FTIR spectroscopy. X-ray diffraction indicates a crystallite size of 2.25 nm and a crystallinity index of 47.5 ± 3.2%. Thermogravimetric analysis confirms the thermal stability up to 280°C. Morphological analysis by SEM reveals a hollow, microtubular structure with interconnected features and longitudinal microchannels, while AFM shows groove depths averaging 1.19 ± 0.49 μm. These structural traits contribute to a low density 0.51 ± 0.04 g/mL, tensile strength 34 ± 9 MPa, and thermal conductivity 0.049 ± 0.001 W/mK. A novel tea bag method, addressing a gap in assessing lightweight, hairy fibers, measured water absorption at 250 ± 33%. The combination of low density, high thermal stability, low thermal conductivity, and high water absorption positions these fibers as promising reinforcements for polymer composites, especially in biodegradable and lightweight applications. These findings highlight the untapped potential of this natural fiber for sustainable engineering and industrial uses. Such renewable fibers meet global demands for sustainable materials amid increasing environmental challenges.
DOI: 10.6084/m9.figshare.29979376.v1
title: Characterization of Cellulosic Fibers from the Inflorescences of <i>Echinops sphaerocephalus</i>: An Unexplored Source of Eco-Friendly Sustainable Fibers

description: This study identifies <i>Echinops sphaerocephalus</i> inflorescences as a novel, sustainable fiber source that avoids deforestation. Comprehensive characterization of their chemical, physical, thermal, and morphological properties reveals their potential for diverse applications. Chemical analysis shows that the fibers contain 39.5% cellulose, 36.5% hemicellulose, and 2.9% lignin, corroborated by FTIR spectroscopy. X-ray diffraction indicates a crystallite size of 2.25 nm and a crystallinity index of 47.5 ± 3.2%. Thermogravimetric analysis confirms the thermal stability up to 280°C. Morphological analysis by SEM reveals a hollow, microtubular structure with interconnected features and longitudinal microchannels, while AFM shows groove depths averaging 1.19 ± 0.49 μm. These structural traits contribute to a low density 0.51 ± 0.04 g/mL, tensile strength 34 ± 9 MPa, and thermal conductivity 0.049 ± 0.001 W/mK. A novel tea bag method, addressing a gap in assessing lightweight, hairy fibers, measured water absorption at 250 ± 33%. The combination of low density, high thermal stability, low thermal conductivity, and high water absorption positions these fibers as promising reinforcements for polymer composites, especially in biodegradable and lightweight applications. These findings highlight the untapped potential of this natural fiber for sustainable engineering and industrial uses. Such renewable fibers meet global demands for sustainable materials amid increasing environmental challenges.
DOI: 10.6084/m9.figshare.28309822
title: Low-Cost Microcontroller-Enabled Embedded System for Assessing Jute Retting Water Quality Parameter

description: Quality of jute fiber depends to a very great extent on the quality of water used for retting. Efficient assessment of water quality is crucial to enable decision-makers to interpret this information and execute necessary management practices. Hence, the present study introduced a microcontroller-based embedded system to measure temperature, pH, turbidity, and TDS of retting water. The developed system mainly encompasses temperature sensor, pH sensor, turbidity sensor, TDS sensor, Arduino ATmega 2560 microcontroller, MicroSD card module, and LCD. Field validation established a non-significant difference between actual and measured values of temperature (<i>F</i><sub><i>42,1</i></sub><i> = 1.052, p = .480</i>), pH (<i>F</i><sub><i>42,1</i></sub><i> = 1.116, p = .297</i>), Turbidity (<i>F</i><sub><i>42,1</i></sub><i> = 0.084, p = .774</i>), and TDS (<i>F</i><sub><i>42,1</i></sub><i> = 0.116, p = .992</i>) at 95% level of significance. Developed embedded system was also provided with two LEDs, i.e. green for “In progress” and red for “completed”, and a buzzer to alert a person about the status of the retting of jute plants. Developed embedded system is easy-to-build, easy-to-use, and cost effective (US $147.3) for determination of water quality parameter as well as end-point of retting which may be helpful for research and academic purpose. This development may also render an avenue for controlled retting of jute which may help farmers to produce high-quality fibers.
DOI: 10.6084/m9.figshare.28309822.v1
title: Low-Cost Microcontroller-Enabled Embedded System for Assessing Jute Retting Water Quality Parameter

description: Quality of jute fiber depends to a very great extent on the quality of water used for retting. Efficient assessment of water quality is crucial to enable decision-makers to interpret this information and execute necessary management practices. Hence, the present study introduced a microcontroller-based embedded system to measure temperature, pH, turbidity, and TDS of retting water. The developed system mainly encompasses temperature sensor, pH sensor, turbidity sensor, TDS sensor, Arduino ATmega 2560 microcontroller, MicroSD card module, and LCD. Field validation established a non-significant difference between actual and measured values of temperature (<i>F</i><sub><i>42,1</i></sub><i> = 1.052, p = .480</i>), pH (<i>F</i><sub><i>42,1</i></sub><i> = 1.116, p = .297</i>), Turbidity (<i>F</i><sub><i>42,1</i></sub><i> = 0.084, p = .774</i>), and TDS (<i>F</i><sub><i>42,1</i></sub><i> = 0.116, p = .992</i>) at 95% level of significance. Developed embedded system was also provided with two LEDs, i.e. green for “In progress” and red for “completed”, and a buzzer to alert a person about the status of the retting of jute plants. Developed embedded system is easy-to-build, easy-to-use, and cost effective (US $147.3) for determination of water quality parameter as well as end-point of retting which may be helpful for research and academic purpose. This development may also render an avenue for controlled retting of jute which may help farmers to produce high-quality fibers.
DOI: 10.6084/m9.figshare.28113539
title: Development of Antibacterial and Halochromic Textiles by Modification of Emodin from Japanese Knotweed

description: Emodin is a natural product with a wide range of biological activities, including antibacterial and antiviral activity against the human coronavirus NL63. Our aim was to develop antimicrobial textiles using the natural dye emodin and its derivatives and to investigate how chemical modification of emodin affects the binding properties to textiles and the antibacterial properties of the dyed textiles. Emodin was first modified by introducing different functional groups (NO<sub>2</sub>, SO<sub>3</sub>H, Br, and Cl) into the aromatic ring to obtain products with different colors. Products were used to dye various types of textiles without additional mordants. Wool and polyamide exhibited intense dye uptake, whereas cotton and polyester showed weaker affinity to emodin derivatives. The colors of dyed wool and polyamide varied, including light pink, red, violet, and almost black tones. The degree of washing fastness, pH sensitivity, and antibacterial activity of treated fabrics were also evaluated. The dyed textiles showed significant antibacterial activity against Gram-positive <i>Staphylococcus aureus</i>. Emodin is also present in Japanese knotweed, which is one of the most invasive alien plant species in the world and poses a major ecological and environmental problem in Europe. Therefore, this source may present environmentally friendly and sustainable source of natural dyeing agent.
DOI: 10.6084/m9.figshare.28113539.v1
title: Development of Antibacterial and Halochromic Textiles by Modification of Emodin from Japanese Knotweed

description: Emodin is a natural product with a wide range of biological activities, including antibacterial and antiviral activity against the human coronavirus NL63. Our aim was to develop antimicrobial textiles using the natural dye emodin and its derivatives and to investigate how chemical modification of emodin affects the binding properties to textiles and the antibacterial properties of the dyed textiles. Emodin was first modified by introducing different functional groups (NO<sub>2</sub>, SO<sub>3</sub>H, Br, and Cl) into the aromatic ring to obtain products with different colors. Products were used to dye various types of textiles without additional mordants. Wool and polyamide exhibited intense dye uptake, whereas cotton and polyester showed weaker affinity to emodin derivatives. The colors of dyed wool and polyamide varied, including light pink, red, violet, and almost black tones. The degree of washing fastness, pH sensitivity, and antibacterial activity of treated fabrics were also evaluated. The dyed textiles showed significant antibacterial activity against Gram-positive <i>Staphylococcus aureus</i>. Emodin is also present in Japanese knotweed, which is one of the most invasive alien plant species in the world and poses a major ecological and environmental problem in Europe. Therefore, this source may present environmentally friendly and sustainable source of natural dyeing agent.
DOI: 10.6084/m9.figshare.29605358
title: Stiffness and Strength-Related Sustainability Assessment of Natural Fibers for Injection Molded Composites

description: The growing demand for sustainable materials has led to an increased interest in bio-based composites reinforced with natural fibers such as flax, hemp, kenaf, and sisal. This study presents a comparative sustainability assessment of these fibers, highlighting significant differences based on processing methods and fiber characteristics. Life cycle assessment (LCA) results show that flax tow, a by-product of textile flax production, has the lowest environmental impact under economic allocation. In contrast, the impact of sisal fiber varies greatly depending on the processing method: wet separation in Tanzania significantly increases water consumption and methane emissions, while dry extraction methods in Brazil reduce these impacts. An integrated tool has been developed to incorporate material performance metrics into sustainability assessments to improve sustainable material selection, addressing the “LCA paradox.” This property-specific assessment framework enables multidisciplinary collaboration and supports the development of environmentally optimized natural fiber composites for injection molding and other applications.
DOI: 10.6084/m9.figshare.29605358.v1
title: Stiffness and Strength-Related Sustainability Assessment of Natural Fibers for Injection Molded Composites

description: The growing demand for sustainable materials has led to an increased interest in bio-based composites reinforced with natural fibers such as flax, hemp, kenaf, and sisal. This study presents a comparative sustainability assessment of these fibers, highlighting significant differences based on processing methods and fiber characteristics. Life cycle assessment (LCA) results show that flax tow, a by-product of textile flax production, has the lowest environmental impact under economic allocation. In contrast, the impact of sisal fiber varies greatly depending on the processing method: wet separation in Tanzania significantly increases water consumption and methane emissions, while dry extraction methods in Brazil reduce these impacts. An integrated tool has been developed to incorporate material performance metrics into sustainability assessments to improve sustainable material selection, addressing the “LCA paradox.” This property-specific assessment framework enables multidisciplinary collaboration and supports the development of environmentally optimized natural fiber composites for injection molding and other applications.
DOI: 10.6084/m9.figshare.30022436
title: Accelerated Aging of Natural Fiber Composites (NFCs), Their Fabrication Methods, Industrial Applications, Challenges, and Future Directions: An Overview

description: The long-term durability of natural fiber composites (NFCs) remains a critical challenge, particularly in structural applications exposed to outdoor environments. Due to their chemical composition and hydrophilic nature, natural fibers are highly susceptible to moisture, heat, and ultraviolet (UV) rays. These environmental factors accelerate degradation, compromising the structural integrity of NFCs over time. Hence, ensuring their durability is essential for their use in high-performance industrial applications. Despite these challenges, NFCs have attracted growing interest in recent decades as potential alternatives to conventional composites or construction materials. This interest is driven by several technical advantages such as natural fibers are lightweight, widely available, environmental-friendly, and offer specific mechanical properties comparable to those of synthetic fibers (glass fibers). Common plant-based natural fibers used in composites include flax, hemp, jute, kenaf, sisal, abaca, ramie, coir, PALF (pineapple leaf fiber), bamboo, date palm, oil palm, etc. This review paper provides a brief overview of NFCs and their fabrication methods. It then explores the effect of accelerated aging on their mechanical performance under hygrothermal and weathering conditions. Additionally, the paper highlights various industrial applications of NFCs across multiple sectors, identifies key challenges, and offers suggestions and future directions for the development and industrial adoption of NFCs.
DOI: 10.6084/m9.figshare.30022436.v1
title: Accelerated Aging of Natural Fiber Composites (NFCs), Their Fabrication Methods, Industrial Applications, Challenges, and Future Directions: An Overview

description: The long-term durability of natural fiber composites (NFCs) remains a critical challenge, particularly in structural applications exposed to outdoor environments. Due to their chemical composition and hydrophilic nature, natural fibers are highly susceptible to moisture, heat, and ultraviolet (UV) rays. These environmental factors accelerate degradation, compromising the structural integrity of NFCs over time. Hence, ensuring their durability is essential for their use in high-performance industrial applications. Despite these challenges, NFCs have attracted growing interest in recent decades as potential alternatives to conventional composites or construction materials. This interest is driven by several technical advantages such as natural fibers are lightweight, widely available, environmental-friendly, and offer specific mechanical properties comparable to those of synthetic fibers (glass fibers). Common plant-based natural fibers used in composites include flax, hemp, jute, kenaf, sisal, abaca, ramie, coir, PALF (pineapple leaf fiber), bamboo, date palm, oil palm, etc. This review paper provides a brief overview of NFCs and their fabrication methods. It then explores the effect of accelerated aging on their mechanical performance under hygrothermal and weathering conditions. Additionally, the paper highlights various industrial applications of NFCs across multiple sectors, identifies key challenges, and offers suggestions and future directions for the development and industrial adoption of NFCs.
DOI: 10.6084/m9.figshare.28638634
title: Extraction, Chemical Functionalization, and Application of <i>Stipa obtusa</i> Cellulose Microfibers for Lead Ion Adsorption

description: Environmental contamination by heavy metals, such as lead (Pb<sup>2+</sup>), presents significant risks to ecosystems and public health, necessitating the development of innovative and sustainable remediation methods. This study introduces a novel adsorbent derived from microcellulose (MC) extracted from <i>Stipa obtusa</i>, a grass species native to the Andean regions of Peru, Ecuador, and Bolivia, for the removal of lead ions from aqueous solutions. MC fibers were isolated through thermochemical processing, followed by chemical functionalization with sodium chlorite (NaClO₂). The resulting functionalized microfibers (FMC) were characterized using elemental analysis, Fourier-transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller surface area analysis (BET), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). Batch adsorption experiments identified optimal conditions: an adsorbent dosage of 0.4 mg/L, pH 5, and a contact time of 60 min, achieving a maximum adsorption capacity of 34 mg/g. Kinetic studies indicated the adsorption process followed a pseudo-second-order model, while the adsorption isotherm data best fitted the Freundlich model, indicating a heterogeneous adsorption process. These results demonstrate the potential of FMC as an efficient and environmentally friendly adsorbent for heavy metal ion removal in water treatment.
DOI: 10.6084/m9.figshare.28638634.v1
title: Extraction, Chemical Functionalization, and Application of <i>Stipa obtusa</i> Cellulose Microfibers for Lead Ion Adsorption

description: Environmental contamination by heavy metals, such as lead (Pb<sup>2+</sup>), presents significant risks to ecosystems and public health, necessitating the development of innovative and sustainable remediation methods. This study introduces a novel adsorbent derived from microcellulose (MC) extracted from <i>Stipa obtusa</i>, a grass species native to the Andean regions of Peru, Ecuador, and Bolivia, for the removal of lead ions from aqueous solutions. MC fibers were isolated through thermochemical processing, followed by chemical functionalization with sodium chlorite (NaClO₂). The resulting functionalized microfibers (FMC) were characterized using elemental analysis, Fourier-transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller surface area analysis (BET), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). Batch adsorption experiments identified optimal conditions: an adsorbent dosage of 0.4 mg/L, pH 5, and a contact time of 60 min, achieving a maximum adsorption capacity of 34 mg/g. Kinetic studies indicated the adsorption process followed a pseudo-second-order model, while the adsorption isotherm data best fitted the Freundlich model, indicating a heterogeneous adsorption process. These results demonstrate the potential of FMC as an efficient and environmentally friendly adsorbent for heavy metal ion removal in water treatment.
DOI: 10.6084/m9.figshare.30237112
title: Cutting-Edge Hybrid Machine Learning Models for Forecasting the Acid Resistance of Cementitious Composites Incorporating Eggshell and Glass Powders

description: This research introduced advanced hybrid machine learning (ML) techniques to create an efficient model for estimating the compressive strength after acid attack (CSAA). The models were developed based on mixtures containing eggshell powder (ESP) and glass powder (GP). Support vector regression (SVR) was integrated with sophisticated metaheuristic optimization techniques, namely the particle swarm optimization (PSO), firefly algorithm (FFA), and gray wolf optimization (GWO), to develop advanced forecasting models for the CSAA of cementitious composites. Additionally, conventional ML models, including random forest (RF) and decision tree (DT), were utilized for comparison. All three hybrid models demonstrated strong predictive capabilities, with SVR-PSO proving to be the most reliable method, attaining the maximum coefficient of determination (R<sup>2</sup>) score of 0.984, surpassing SVR-GWO (0.981) and SVR-FFA (0.980). In contrast, the RF model recorded an R<sup>2</sup> value of 0.974, while the DT model revealed a significantly reduced R<sup>2</sup> of 0.649. The partial dependence analyses and SHapley Additive exPlanations and partial dependence plots analyses highlighted the substantial impact of various parameters, revealing that compressive strength (CS) was the most influential factor, followed by GP and ESP. CS and GP had positive effects, while ESP negatively impacted CSAA. A user-friendly interface was developed to efficiently predict CSAA. Development of hybrid ML models for predicting CSAA in cementitious composites with ESP and GP.SVR-PSO achieved the highest accuracy (R2 = 0.984), outperforming SVR-GWO (R2 = 0.981) and SVR-FFA (R2 = 0.980).SHAP and partial dependence plots identified CS as the most influential factor, with GP having a positive and ESP a negative effect on CSAA.A user-friendly GUI was developed for rapid prediction. Development of hybrid ML models for predicting CSAA in cementitious composites with ESP and GP. SVR-PSO achieved the highest accuracy (R2 = 0.984), outperforming SVR-GWO (R2 = 0.981) and SVR-FFA (R2 = 0.980). SHAP and partial dependence plots identified CS as the most influential factor, with GP having a positive and ESP a negative effect on CSAA. A user-friendly GUI was developed for rapid prediction.