bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancing Methodologies for Investigating PM2.5 Removal Using Green Wall System
Authors: Falzone Claudia , Jupsin Hugues , El Jarroudi Moussa , Romain Anne-Claude
Published: June 2024

Combustion processes are the primary source of fine particulate matter in indoor air. Since the 1970s, plants have been extensively studied for their potential to reduce indoor air pollution. Leaves can retain particles on their surfaces, influenced by factors such as wax content and the presence of hairs. This study introduces an innovative experimental approach using metal oxide particles in an office-like environment to evaluate the depolluting effect of plant walls. Two plant walls were installed in a controlled room, housing three plant species: Aglaonema commutatum ‘Silver Bay’, Dracaena fragrans, and Epipremnum aureum. Metal oxide particles were introduced via a compressed air blower positioned between the two walls. The concentration of these particles was monitored using PM2.5 sensors, and the deposition of iron (Fe) on the leaves was quantified through Inductively Coupled Plasma Mass Spectrometry (ICP-MS). This novel methodology effectively demonstrated the utility of both real-time sensors and ICP-MS in quantifying airborne particle concentrations and leaf deposition, respectively. The results revealed that Dracaena fragrans had a 44% higher Fe particle retention rate compared to the control (wallpaper). However, further validation through methodological replication is necessary to confirm the reproducibility of these findings.
New Generation of Osteoinductive and Antimicrobial Polycaprolactone-Based Scaffolds in Bone Tissue Engineering: A Review
Authors: Coppola Bartolomeo , Menotti Francesca , Longo Fabio , Banche Giuliana , Mandras Narcisa , Palmero Paola , Allizond Valeria
Published: June 2024

With respect to other fields, bone tissue engineering has significantly expanded in recent years, leading not only to relevant advances in biomedical applications but also to innovative perspectives. Polycaprolactone (PCL), produced in the beginning of the 1930s, is a biocompatible and biodegradable polymer. Due to its mechanical and physicochemical features, as well as being easily shapeable, PCL-based constructs can be produced with different shapes and degradation kinetics. Moreover, due to various development processes, PCL can be made as 3D scaffolds or fibres for bone tissue regeneration applications. This outstanding biopolymer is versatile because it can be modified by adding agents with antimicrobial properties, not only antibiotics/antifungals, but also metal ions or natural compounds. In addition, to ameliorate its osteoproliferative features, it can be blended with calcium phosphates. This review is an overview of the current state of our recent investigation into PCL modifications designed to impair microbial adhesive capability and, in parallel, to allow eukaryotic cell viability and integration, in comparison with previous reviews and excellent research papers. Our recent results demonstrated that the developed 3D constructs had a high interconnected porosity, and the addition of biphasic calcium phosphate improved human cell attachment and proliferation. The incorporation of alternative antimicrobials—for instance, silver and essential oils—at tuneable concentrations counteracted microbial growth and biofilm formation, without affecting eukaryotic cells’ viability. Notably, this challenging research area needs the multidisciplinary work of material scientists, biologists, and orthopaedic surgeons to determine the most suitable modifications on biomaterials to design favourable 3D scaffolds based on PCL for the targeted healing of damaged bone tissue.
Nature’s Plastic Predators: A Comprehensive and Bibliometric Review of Plastivore Insects
Authors: Boctor Joseph , Pandey Gunjan , Xu Wei , Murphy Daniel V. , Hoyle Frances C.
Published: June 2024

Unprecedented plastic production has resulted in over six billion tons of harmful waste. Certain insect taxa emerge as potential agents of plastic biodegradation. Through a comprehensive manual and bibliometric literature analysis, this review analyses and consolidates the growing literature related to insect-mediated plastic breakdown. Over 23 insect species, representing Coleoptera, Lepidoptera, and 4 other orders, have been identified for their capacity to consume plastic polymers. Natural and synthetic polymers exhibit high-level similarities in molecular structure and properties. Thus, in conjunction with comparative genomics studies, we link plastic-degrading enzymatic capabilities observed in certain insects to the exaptation of endogenous enzymes originally evolved for digesting lignin, cellulose, beeswax, keratin and chitin from their native dietary substrates. Further clarification is necessary to distinguish mineralisation from physicochemical fragmentation and to differentiate microbiome-mediated degradation from direct enzymatic reactions by insects. A bibliometric analysis of the exponentially growing body of literature showed that leading research is emerging from China and the USA. Analogies between natural and synthetic polymer’s degradation pathways will inform engineering robust enzymes for practical plastic bioremediation applications. By aggregating, analysing, and interpreting published insights, this review consolidates our mechanistic understanding of insects as a potential natural solution to the escalating plastic waste crisis.
Poly-l-Lactic Acid Scaffolds Additivated with Rosmarinic Acid: A Multi-Analytical Approach to Assess The Morphology, Thermal Behavior, and Hydrophilicity
Authors: Schiera Veronica , Carfì Pavia Francesco , La Carrubba Vincenzo , Brucato Valerio , Dintcheva Nadka Tz.
Published: June 2024

This study aims to demonstrate the possibility of incorporating a natural antioxidant biomolecule into polymeric porous scaffolds. To this end, Poly-l-Lactic Acid (PLLA) scaffolds were produced using the Thermally Induced Phase Separation (TIPS) technique and additivated with different amounts of rosmarinic acid (RA). The scaffolds, with a diameter of 4 mm and a thickness of 2 mm, were characterized with a multi-analytical approach. Specifically, Scanning Electron Microscopy analyses demonstrated the presence of an interconnected porous network, characterized by a layer of RA at the level of the pore’s surfaces. Moreover, the presence of RA biomolecules increased the hydrophilic nature of the sample, as evidenced by the decrease in the contact angle with water from 128° to 76°. The structure of PLLA and PLLA containing RA molecules has been investigated through DSC and XRD analyses, and the obtained results suggest that the crystallinity decreases when increasing the RA content. This approach is cost-effective, and it can be customized with different biomolecules, offering the possibility of producing porous polymeric structures containing antioxidant molecules. These scaffolds meet the requirements of tissue engineering and could offer a potential solution to reduce inflammation associated with scaffold implantation, thus improving tissue regeneration.
Rice Bran Valorization through the Fabrication of Nanofibrous Membranes by Electrospinning
Authors: Alonso-González María , Felix Manuel , Romero Alberto
Published: June 2024

The high production rate of fossil-based plastics, coupled with their accumulation and low degradability, is causing severe environmental problems. As a result, there is a growing interest in the use of renewable and natural sources in the polymer industry. Specifically, rice bran is a highly abundant by-product of the agro-food industry, with variable amounts of protein and starch within its composition, which are usually employed for bioplastic development. This study aims to valorize rice bran through the production of nanofiber membranes processed via electrospinning. Due to its low solubility, the co-electrospinning processing of rice bran with potato starch, known for its ability to form nanofibers through this technique, was chosen. Several fiber membranes were fabricated with modifications in solution conditions and electrospinning parameters to analyze their effects on the synthesized fiber morphology. This analysis involved obtaining micrographs of the fibers through scanning electron microscopy (SEM) and fiber diameter analysis. Potato starch membranes were initially investigated, and once optimal electrospinning conditions were identified, the co-electrospinning of rice bran and potato starch was conducted. Attempts were made to correlate the physical properties of the solutions, such as conductivity and density, with the characteristics of the resulting electrospun fibers. The results presented in this study demonstrate the potential valorization of a rice by-product for the development of bio-based nanofibrous membranes. This not only offers a solution to combat current plastic waste accumulation but also opens up a wide range of applications from filtration to biomedical devices (i.e., in tissue engineering).
Controlling the Friction Coefficient and Adhesive Properties of a Contact by Varying the Indenter Geometry
Authors: Lyashenko Iakov A. , Pham Thao H. , Popov Valentin L.
Published: June 2024

In the present paper, we describe a series of laboratory experiments on the friction between rigid indenters with different geometrical forms and an elastic sheet of elastomer as a function of the normal load. We show that the law of friction can be controlled by the shape of the surface profile. Since the formulation of the adhesive theory of friction by Bowden and Tabor, it is widely accepted and confirmed by experimental evidence that the friction force is roughly proportional to the real contact area. This means that producing surfaces with a desired dependence of the real contact area on the normal force will allow to “design the law of friction”. However, the real contact area in question is that during sliding and differs from that at the pure normal contact. Our experimental studies show that for indenters having a power law profile f(r) = cnrn with an index n < 1, the system exhibits a constant friction coefficient, which, however, is different for different values of n. This opens possibilities for creating surfaces with a predefined coefficient of friction.
An Experimental Analysis of Taguchi-Based Gray Relational Analysis, Weighted Gray Relational Analysis, and Data Envelopment Analysis Ranking Method Multi-Criteria Decision-Making Approaches to Multiple-Quality Characteristic Optimization in the CNC Drilling Process
Authors: Abdullahu Fitore , Zhujani Fatlume , Todorov Georgi , Kamberov Konstantin
Published: June 2024

The goal of this research is to optimize the input parameters utilized in dry CNC drilling of forging steel to attain sustainable machining. Particular emphasis will be placed on achieving high productivity while minimizing the impact on surface quality. To achieve the aforementioned goal, three Taguchi-based multi-criteria decision-making (MCDM) approaches, such as traditional gray relational analysis (GRA), weighted gray relational analysis (WGRA), and data envelopment analysis ranking (DEAR), were used for simultaneous optimization of the MRR and Ra. In Taguchi’s L12 (24) orthogonal array design, the cutting mode parameters—such as cutting speed, depth of cut, feed rate, and point angle—have been chosen as the input parameters for the modeling and analysis of the drilling process characteristics. The process of determining the effect of the input parameters on the output parameters was carried out with the use of analysis of variance (ANOVA). The best results from the studies were Ra = 2.19 and MRR = 375 mm3/s, which corresponded to Taguchi’s single optimization levels, S2F1D1A2 and S2F2D2A1, respectively. In the next step, the performance values obtained for each MCDM technique were reoptimized using the Taguchi method, and the optimal levels were obtained: for traditional GRA, the level S2F1D2A1 (Ra = 2.52 µm, MRR = 125 mm3/s); for WGRA, the level S2F1D1A1 (Ra = 2.31 µm, MRR = 83 mm3/s); and for DEAR, the level S2F2D2A1 (Ra = 4.42 µm, MRR = 375 mm3/s), respectively. Lastly, in order to compare the experiments’ performance, validation tests were carried out. The results of the experiments using multi-objective optimization show that traditional GRA improved the overall quality response characteristics by 29.86% compared to the initial setup parameters, while weighted GRA improved them by 34.48%, with the DEAR method providing an improvement of 96%. Based on the findings of this investigation, the DEAR optimization method outperforms the GRA method. As a result, the proposed methods are useful tools for multi-objective optimization of cutting parameters.
Retaining Resveratrol Content in Berries and Berry Products with Agricultural and Processing Techniques: Review
Authors: Ispiryan Audrone , Kraujutiene Ingrida , Viskelis Jonas
Published: June 2024

Resveratrol is a natural compound that can be found in red wine, grapes, and berries. It has attracted attention due to its potential health benefits. The aim of this review was to align ways of retaining resveratrol contents in berries and products made of berries, and to show which agricultural and processing techniques can maximize the content in the berries and their products and how this can be achieved. The scientific literature has revealed that resveratrol concentration in berries and berry-derived products varies significantly depending on the source and the processing techniques applied. Resveratrol content can range from 0.03–0.06 mg/kg in blueberries to 5–10 mg/kg in grape skins. Agricultural techniques such as controlled water stress (e.g., increasing resveratrol in grapes to 8.3–11.5 mg/kg), optimal sun exposure (e.g., enhancing blueberries to 1.5–2.1 mg/kg), balanced nutrient management, and selecting high-resveratrol cultivars (e.g., up to 15 mg/kg in certain grapes) can substantially increase resveratrol content. Processing methods like cold pressing, centrifugation, ultrafiltration, and freeze-drying are effective in preserving resveratrol levels, while traditional pasteurization tends to reduce its concentration. For instance, high-temperature short-time pasteurization can reduce resveratrol in juice from 1.5 mg/kg to 0.8 mg/kg, whereas cold pressing retains more resveratrol (1.5 mg/kg to 1.4 mg/kg). By optimizing these agricultural and processing techniques, manufacturers can enhance the resveratrol content in berry-derived products, meeting the growing consumer demand for health-enhancing natural products and supporting a healthier society. This approach aligns with the commitment to overcoming the technical challenges associated with resveratrol use, ensuring its potential is fully realized in both health-related and non-health-related applications.
Effects of Climatic Disturbance on the Trade-Off between the Vegetation Pattern and Water Balance Based on a Novel Model and Accurately Remotely Sensed Data in a Semiarid Basin
Authors: Fang Qingqing , Yue Ziqi , Zhang Shanghong , Wang Guoqiang , Xue Baolin , Guo Zixiang
Published: June 2024

Vegetation is a natural link between the atmosphere, soil, and water, and it significantly influences hydrological processes in the context of climate change. Under global warming, vegetation greening significantly aggravates the water conflicts between vegetation water use and water resources in water bodies in arid and semiarid regions. This study established an improved eco-hydrological coupled model with related accurately remotely sensed hydrological data (precipitation and soil moisture levels taken every 3 j with multiply verification) on a large spatio-temporal scale to determine the optimal vegetation coverage (M*), which explored the trade-off relationship between the water supply, based on hydrological balance processes, and the water demand, based on vegetation transpiration under the impact of climate change, in a semiarid basin. Results showed that the average annual actual vegetation coverage (M) in the Hailar River Basin from 1982 to 2012 was 0.62, and that the average optimal vegetation coverage (M*) was 0.56. In 67.23% of the region, M* was lower than M, which aggravated the water stress problem in the Hailar River Basin. By identifying the sensitivity of M* to vegetation characteristics and meteorological parameters, relevant suggestions for vegetation-type planting were proposed. Additionally, we also analyzed the dynamic threshold of vegetation under different climatic conditions, and we found that M was lower than M* under only four of the twenty-eight climatic conditions considered (rainfall increase by 10%, 20%, and 30% with no change in temperature, and rainfall increase by 20% with a temperature increase of 1 °C), thereby meeting the system equilibrium state under the condition of sustainable development. This study revealed the dynamic relationship between vegetation and hydrological processes under the effects of climate change and provided reliable recommendations to support vegetation management and ecological restoration in river basins. The remote sensing data help us to extend the model in a semiarid basin due to its accuracy.
Forest 3D Radar Reflectivity Reconstruction at X-Band Using a Lidar Derived Polarimetric Coherence Tomography Basis
Authors: Guliaev Roman , Pardini Matteo , Papathanassiou Konstantinos P.
Published: June 2024

Tomographic Synthetic Aperture Radar (SAR) allows the reconstruction of the 3D radar reflectivity of forests from a large(r) number of multi-angular acquisitions. However, in most practical implementations it suffers from limited vertical resolution and/or reconstruction artefacts as the result of non-ideal acquisition setups. Polarisation Coherence Tomography (PCT) offers an alternative to traditional tomographic techniques that allow the reconstruction of the low-frequency 3D radar reflectivity components from a small(er) number of multi-angular SAR acquisitions. PCT formulates the tomographic reconstruction problem as a series expansion on a given function basis. The expansion coefficients are estimated from interferometric coherence measurements between acquisitions. In its original form, PCT uses the Legendre polynomial basis for the reconstruction of the 3D radar reflectivity. This paper investigates the use of new basis functions for the reconstruction of X-band 3D radar reflectivity of forests derived from available lidar waveforms. This approach enables an improved 3D radar reflectivity reconstruction with enhanced vertical resolution, tailored to individual forest conditions. It also allows the translation from sparse lidar waveform vertical reflectivity information into continuous vertical reflectivity estimates when combined with interferometric SAR measurements. This is especially relevant for exploring the synergy of actual missions such as GEDI and TanDEM-X. The quality of the reconstructed 3D radar reflectivity is assessed by comparing simulated InSAR coherences derived from the reconstructed 3D radar reflectivity against measured coherences at different spatial baselines. The assessment is performed and discussed for interferometric TanDEM-X acquisitions performed over two tropical Gabonese rainforest sites: Mondah and Lopé. The results demonstrate that the lidar-derived basis provides more physically realistic vertical reflectivity profiles, which also produce a smaller bias in the simulated coherence validation, compared to the conventional Legendre polynomial basis.
Development of a Smartwatch with Gas and Environmental Sensors for Air Quality Monitoring
Authors: González Víctor , Godoy Javier , Arroyo Patricia , Meléndez Félix , Díaz Fernando , López Ángel , Suárez José Ignacio , Lozano Jesús
Published: June 2024

In recent years, there has been a growing interest in developing portable and personal devices for measuring air quality and surrounding pollutants, partly due to the need for ventilation in the aftermath of COVID-19 situation. Moreover, the monitoring of hazardous chemical agents is a focus for ensuring compliance with safety standards and is an indispensable component in safeguarding human welfare. Air quality measurement is conducted by public institutions with high precision but costly equipment, which requires constant calibration and maintenance by highly qualified personnel for its proper operation. Such devices, used as reference stations, have a low spatial resolution since, due to their high cost, they are usually located in a few fixed places in the city or region to be studied. However, they also have a low temporal resolution, providing few samples per hour. To overcome these drawbacks and to provide people with personalized and up-to-date air quality information, a personal device (smartwatch) based on MEMS gas sensors has been developed. The methodology followed to validate the performance of the prototype was as follows: firstly, the detection capability was tested by measuring carbon dioxide and methane at different concentrations, resulting in low detection limits; secondly, several experiments were performed to test the discrimination capability against gases such as toluene, xylene, and ethylbenzene. principal component analysis of the data showed good separation and discrimination between the gases measured.
Surface Plasmon Resonance-Enhanced CdS/FTO Heterojunction for Cu2+ Detection
Authors: Chen Feng , Zhao Mingfu , Zhang Bin , Zhao Minggang , Ma Ye
Published: June 2024

Copper ion (Cu2+) pollution poses a serious threat to marine ecology and fisheries. However, the complexity of seawater and its interference factors make the online detection of Cu2+ quite challenging. To address this issue, we introduce the concept of the photo-assisted adjustment barrier effect into electrochemical detection, using it as a driving force to generate electrochemical responses. The Schottky barrier demonstrates a remarkable regulatory influence on the electrochemical response under photoexcitation, facilitating the response through Cu2+ adsorption. We developed a 4-MBA-AuNPs/CdS/FTO composite that serves as a sensitive platform for Cu2+ detection, achieving a detection limit of 70 nM. Notably, the photo-assisted adjustment of the barrier effect effectively counters the interference posed by ions in seawater, ensuring accurate detection. Furthermore, the sensor exhibits a promising recovery rate (99.62–104.9%) in real seawater samples, highlighting its practical applications. This innovative approach utilizing the photo-assisted adjustment barrier effect offers a promising path for developing electrochemical sensors that can withstand interference.
A Low-Frequency Vibration Sensor Based on Ball Triboelectric Nanogenerator for Marine Pipeline Condition Monitoring
Authors: Huang Xili , Wei Bin , Ling Ziyun , Yang Fang , Pang Hongchen
Published: June 2024

Marine pipeline vibration condition monitoring is a critical and challenging issue, on account of the complex marine environment, while powering the required monitoring sensors remains problematic. This study introduces a vibration sensor based on a ball triboelectric nanogenerator (B-TENG) for marine pipelines condition monitoring. The B-TENG consists of an acrylic cube, polyester rope, aluminum electrodes, and PTFE ball, which converts vibration signals into electrical signals without the need for an external energy supply. The experimental results show that B-TENG can accurately monitor the frequency, amplitude, and direction of vibration in the range of 1–5 Hz with a small error of 0.67%, 4.4%, and 5%, and an accuracy of 0.1 Hz, 0.97 V/mm, and 1.5°, respectively. The hermetically sealed B-TENG can monitor vibration in underwater environments. Therefore, the B-TENG can be used as a cost-effective, self-powered, highly accurate vibration sensor for marine pipeline monitoring.
Comparison Analysis of Roundness Measurement of Small Cylindrical Workpieces with Different Styluses
Authors: Wu Borong , Zeng Chuang , Li Qiaolin
Published: June 2024

To investigate the high-accuracy roundness metrology of a needle roller 1.5 mm in diameter and 5.8 mm in length using the stitching linear scan method, a ruby ball stylus with a tip radius of 150 μm and a diamond stylus with a tip radius of 2 μm were employed to perform experiments under the same conditions. The precision coordinate data, derived from the needle roller’s cross-sectional circumference, were segmented into uniform eighths, each scanned with the stylus of a roughness measuring machine. The roundness profile of the needle roller was obtained by stitching the arc profiles, which were characterized according to the precision coordinate data of the arcs. The cross-correlation function, Euclidean distance, residual sum of squares, position error, and curvature of the measured arcs were used to evaluate the results, which can reflect the performance of the stylus. A comparison of the results obtained using the ruby ball stylus versus the diamond stylus demonstrates the ruby ball stylus’ greater suitability for use in the roundness metrology of the needle roller bearing examined in this paper.
Explicit Image Caption Reasoning: Generating Accurate and Informative Captions for Complex Scenes with LMM
Authors: Cui Mingzhang , Li Caihong , Yang Yi
Published: June 2024

The rapid advancement of sensor technologies and deep learning has significantly advanced the field of image captioning, especially for complex scenes. Traditional image captioning methods are often unable to handle the intricacies and detailed relationships within complex scenes. To overcome these limitations, this paper introduces Explicit Image Caption Reasoning (ECR), a novel approach that generates accurate and informative captions for complex scenes captured by advanced sensors. ECR employs an enhanced inference chain to analyze sensor-derived images, examining object relationships and interactions to achieve deeper semantic understanding. We implement ECR using the optimized ICICD dataset, a subset of the sensor-oriented Flickr30K-EE dataset containing comprehensive inference chain information. This dataset enhances training efficiency and caption quality by leveraging rich sensor data. We create the Explicit Image Caption Reasoning Multimodal Model (ECRMM) by fine-tuning TinyLLaVA with the ICICD dataset. Experiments demonstrate ECR’s effectiveness and robustness in processing sensor data, outperforming traditional methods.
Real-Time Tracking Data and Machine Learning Approaches for Mapping Pedestrian Walking Behavior: A Case Study at the University of Moratuwa
Authors: Sawandi Harini , Jayasinghe Amila , Retscher Guenther
Published: June 2024

The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such pedestrian-friendly walking environments. Identifying locations and routes with high pedestrian concentration is critical for improving pedestrian-friendly walking environments. This paper presents a quantitative method to map pedestrian walking behavior by utilizing real-time data from mobile phone sensors, focusing on the University of Moratuwa, Sri Lanka, as a case study. This holistic method integrates new urban data, such as location-based service (LBS) positioning data, and data clustering with unsupervised machine learning techniques. This study focused on the following three criteria for quantifying walking behavior: walking speed, walking time, and walking direction inside the experimental research context. A novel signal processing method has been used to evaluate speed signals, resulting in the identification of 622 speed clusters using K-means clustering techniques during specific morning and evening hours. This project uses mobile GPS signals and machine learning algorithms to track and classify pedestrian walking activity in crucial sites and routes, potentially improving urban walking through mapping.
Human Joint Angle Estimation Using Deep Learning-Based Three-Dimensional Human Pose Estimation for Application in a Real Environment
Authors: Choi Jin-Young , Ha Eunju , Son Minji , Jeon Jean-Hong , Kim Jong-Wook
Published: June 2024

Human pose estimation (HPE) is a technique used in computer vision and artificial intelligence to detect and track human body parts and poses using images or videos. Widely used in augmented reality, animation, fitness applications, and surveillance, HPE methods that employ monocular cameras are highly versatile and applicable to standard videos and CCTV footage. These methods have evolved from two-dimensional (2D) to three-dimensional (3D) pose estimation. However, in real-world environments, current 3D HPE methods trained on laboratory-based motion capture data encounter challenges, such as limited training data, depth ambiguity, left/right switching, and issues with occlusions. In this study, four 3D HPE methods were compared based on their strengths and weaknesses using real-world videos. Joint position correction techniques were proposed to eliminate and correct anomalies such as left/right inversion and false detections of joint positions in daily life motions. Joint angle trajectories were obtained for intuitive and informative human activity recognition using an optimization method based on a 3D humanoid simulator, with the joint position corrected by the proposed technique as the input. The efficacy of the proposed method was verified by applying it to three types of freehand gymnastic exercises and comparing the joint angle trajectories during motion.
Quadruped Robot Control: An Approach Using Body Planar Motion Control, Legs Impedance Control and Bézier Curves
Authors: Pedro Gabriel Duarte Gonçalves , Bermudez Gabriel , Medeiros Vivian Suzano , Cruz Neto Hélio Jacinto da , Barros Luiz Guilherme Dias de , Pessin Gustavo , Becker Marcelo , Freitas Gustavo Medeiros , Boaventura Thiago
Published: June 2024

In robotics, the ability of quadruped robots to perform tasks in industrial, mining, and disaster environments has already been demonstrated. To ensure the safe execution of tasks by the robot, meticulous planning of its foot placements and precise leg control are crucial. Traditional motion planning and control methods for quadruped robots often rely on complex models of both the robot itself and its surrounding environment. Establishing these models can be challenging due to their nonlinear nature, often entailing significant computational resources. However, a more simplified approach exists that focuses on the kinematic model of the robot’s floating base for motion planning. This streamlined method is easier to implement but also adaptable to simpler hardware configurations. Moreover, integrating impedance control into the leg movements proves advantageous, particularly when traversing uneven terrain. This article presents a novel approach in which a quadruped robot employs impedance control for each leg. It utilizes sixth-degree Bézier curves to generate reference trajectories derived from leg velocities within a planar kinematic model for body control. This scheme effectively guides the robot along predefined paths. The proposed control strategy is implemented using the Robot Operating System (ROS) and is validated through simulations and physical experiments on the Go1 robot. The results of these tests demonstrate the effectiveness of the control strategy, enabling the robot to track reference trajectories while showing stable walking and trotting gaits.
Analysis of Varroa Mite Colony Infestation Level Using New Open Software Based on Deep Learning Techniques
Authors: Divasón Jose , Romero Ana , Martinez-de-Pison Francisco Javier , Casalongue Matías , Silvestre Miguel A. , Santolaria Pilar , Yániz Jesús L.
Published: June 2024

Varroa mites, scientifically identified as Varroa destructor, pose a significant threat to beekeeping and cause one of the most destructive diseases affecting honey bee populations. These parasites attach to bees, feeding on their fat tissue, weakening their immune systems, reducing their lifespans, and even causing colony collapse. They also feed during the pre-imaginal stages of the honey bee in brood cells. Given the critical role of honey bees in pollination and the global food supply, controlling Varroa mites is imperative. One of the most common methods used to evaluate the level of Varroa mite infestation in a bee colony is to count all the mites that fall onto sticky boards placed at the bottom of a colony. However, this is usually a manual process that takes a considerable amount of time. This work proposes a deep learning approach for locating and counting Varroa mites using images of the sticky boards taken by smartphone cameras. To this end, a new realistic dataset has been built: it includes images containing numerous artifacts and blurred parts, which makes the task challenging. After testing various architectures (mainly based on two-stage detectors with feature pyramid networks), combination of hyperparameters and some image enhancement techniques, we have obtained a system that achieves a mean average precision (mAP) metric of 0.9073 on the validation set.
Contrast Enhancement Method Using Region-Based Dynamic Clipping Technique for LWIR-Based Thermal Camera of Night Vision Systems
Authors: Choi Cheol-Ho , Han Joonhwan , Cha Jeongwoo , Choi Hyunmin , Shin Jungho , Kim Taehyun , Oh Hyun Woo
Published: June 2024

In the autonomous driving industry, there is a growing trend to employ long-wave infrared (LWIR)-based uncooled thermal-imaging cameras, capable of robustly collecting data even in extreme environments. Consequently, both industry and academia are actively researching contrast-enhancement techniques to improve the quality of LWIR-based thermal-imaging cameras. However, most research results only showcase experimental outcomes using mass-produced products that already incorporate contrast-enhancement techniques. Put differently, there is a lack of experimental data on contrast enhancement post-non-uniformity (NUC) and temperature compensation (TC) processes, which generate the images seen in the final products. To bridge this gap, we propose a histogram equalization (HE)-based contrast enhancement method that incorporates a region-based clipping technique. Furthermore, we present experimental results on the images obtained after applying NUC and TC processes. We simultaneously conducted visual and qualitative performance evaluations on images acquired after NUC and TC processes. In the visual evaluation, it was confirmed that the proposed method improves image clarity and contrast ratio compared to conventional HE-based methods, even in challenging driving scenarios such as tunnels. In the qualitative evaluation, the proposed method demonstrated upper-middle-class rankings in both image quality and processing speed metrics. Therefore, our proposed method proves to be effective for the essential contrast enhancement process in LWIR-based uncooled thermal-imaging cameras intended for autonomous driving platforms.
Coloniality and Refugee Education in the United States
Authors: Koyama Jill , Turan Adnan
Published: June 2024

In this paper, we demonstrate the ways in which the schooling of refugee youth in the United States reflects ongoing coloniality in education. Drawing on data collected in a case study, conducted between 2013 and 2016, as part of a larger ongoing ethnography of a Southwest United States District school’s response to refugee students, we show how the enactment of policies, pedagogies, and practices within schools reinforce the government’s control over refugee students and their families. In schools, the students are kept out of certain school spaces, marginalized in remedial courses, and denied academic opportunities and integrated support services. Using empirical data, we demonstrate how the restriction of the students’ movement in and around schools is embedded within the larger limitations embedded in coloniality and assimilation. We situate our analysis within the tensions and interactions between coloniality, assimilation, and neoliberalism as articulated in studies within anthropology and sociology, migration studies, critical refugee studies, and cultural studies. We conclude with a call for the decolonization of education and offer a practical starting point in refugee education.
Organizational Citizenship Behaviors in the Portuguese Hospitality Industry: A Study on Sociodemographic and Professional Variables
Authors: Cordeiro João Pedro , Pitacho Liliana , Lima Daniela
Published: June 2024

The aim of this research is to reflexively analyze and discuss organizational citizenship behaviors. By conducting an empirical test based on the assertions within the fields of the positive organizational behavior and the social identity theory, the specific objective is to analyze the relationship between organizational citizenship and sociodemographic and professional variables. A study was carried out by surveying employees of Portuguese hotel units. The sample consisted of 798 employees, mostly males, between 30 and 34 years old, with secondary school education, serving as operatives or undifferentiated employees, and having middle levels of seniority in the organization. The main results show that hotel employees develop organizational citizenship behaviors, albeit of different types and levels, which are supported by some sociodemographic and professional variables. The findings show that age and seniority are the most important and strongest variables significantly related to organizational citizenship behaviors. This study has several implications, highlighting the role and support that managers and decision-makers must have in reinforcing positive voluntary personal and social behaviors among hotel employees. This research aims to contribute to the formulation and implementation of management strategies anchored in organizational citizenship behaviors, supporting the formulation of management systems centered on behavioral attitudes at work in the context of the hotel sector.
From Individual Motivation to Geospatial Epidemiology: A Novel Approach Using Fuzzy Cognitive Maps and Agent-Based Modeling for Large-Scale Disease Spread
Authors: Song Zhenlei , Zhang Zhe , Lyu Fangzheng , Bishop Michael , Liu Jikun , Chi Zhaohui
Published: June 2024

In the past few years, there have been many studies addressing the simulation of COVID-19’s spatial transmission model of infectious disease in time. However, very few studies have focused on the effect of the epidemic environment variables in which an individual lives on the individual’s behavioral logic leading to changes in the overall epidemic transmission trend at larger scales. In this study, we applied Fuzzy Cognitive Maps (FCMs) to modeling individual behavioral logistics, combined with Agent-Based Modeling (ABM) to perform “Susceptible—Exposed—Infectious—Removed” (SEIR) simulation of the independent individual behavior affecting the overall trend change. Our objective was to simulate the spatiotemporal spread of diseases using the Bengaluru Urban District, India as a case study. The results show that the simulation results are highly consistent with the observed reality, in terms of trends, with a Root Mean Square Error (RMSE) value of 0.39. Notably, our approach reveals a subtle link between individual motivation and infection-recovery dynamics, highlighting how individual behavior can significantly impact broader patterns of transmission. These insights have potential implications for epidemiologic strategies and public health interventions, providing data-driven insights into behavioral impacts on epidemic spread. By integrating behavioral modeling with epidemic simulation, our study underscores the importance of considering individual and collective behavior in designing sustainable public health policies and interventions.
Comparative Analysis of Riverine Plastic Pollution Combining Citizen Science, Remote Sensing and Water Quality Monitoring Techniques
Authors: Molnár Attila Dávid , Málnás Kristóf , Bőhm Sára , Gyalai-Korpos Miklós , Cserép Máté , Kiss Tímea
Published: June 2024

The Tisza River is the longest tributary of the Danube, draining the eastern part of the Carpathian Basin (Central Europe). Five countries share its catchment with different waste production and management practices. Large amounts of waste, including macroplastics (MaPs), are washed into the river. Some of the litter is trapped by the riparian vegetation forming litter accumulations. The study aimed to map the amount of litter by a citizen science program and remote sensing data and to compare the MaP data to the amount of microplastic fragments in sediments. Volunteers reported 3216 riverine litter accumulations from five countries along the entire length of the Tisza (2016–2022). The results suggest that low flow conditions (e.g., impoundment by dams) support litter and MaP trapping. The volume of large accumulations registered by the citizens showed a good correlation with the area of drifting litter revealed on Sentinel-2 images (2016–2022) using machine learning algorithms. Though the MaPs probably fragmentate during their fluvial transport, no clear connection was found between the volume of litter accumulations and the mean microplastic fragment content of sediments (2019–2022). The “Clean Tisza Map“ reveals the high degree of stranded pollutants along rivers and supports public cleanup activities.
The Symmetric Effect of Financial Development, Human Capital and Urbanization on Ecological Footprint: Insights from BRICST Economies
Authors: Majeed Abdul , Wang Juan , Zhou Yewang , Muniba
Published: June 2024

Environmental degradation is a serious concern and its prevention strategies have become a central topic worldwide. It is widely accepted that improving environmental quality is essential for advancing sustainable development and societal well-being. From this perspective, the present research employed panel data from 1990 to 2022 from BRICST economies to assess the effects of financial development, human capital, urban population, energy consumption, and economic growth on environmental quality regarding ecological footprint. This study employs second-generation empirical techniques such as CIPS and CADF unit root tests, Westerlund bootstrap cointegration, and DFE/MG/PMG-ARDL models to examine the connections among the studied variables. The empirical findings of this study uncover that in the BRICST countries, environmental quality is exacerbated by human capital, urban population, energy consumption, and economic growth. On the other hand, financial development and GDP2 help improve environmental quality. Additionally, the interaction of the term financial development results with the terms human capital and urban population has a negative effect and reduces ecological footprint by improving environmental quality. From the policy perspective, the selected countries must implement policies that promote equitable financial resources, plan sustainable urbanization to promote compact cities and green infrastructure, and invest in green energy to address the adverse environmental consequences in BRICST economies.
Direct Illuminance-Contribution-Based Lighting Control for IoT-Based Lighting Systems in Smart Buildings
Authors: Kim Dae Ho , Jeon Seung Hyun , Sung Jung-Sik
Published: June 2024

With the advent of low-voltage light-emitting diodes (LEDs) and advances in Internet of Things (IoT) technologies, smart buildings have recently become more energy efficient. Nevertheless, the lighting-control system is one of the major sources of electrical energy consumption in commercial buildings. This study proposes a direct illuminance-contribution-based lighting-control framework to reduce the energy of LED luminaires and ensure illuminance for user requirements in smart buildings. Specifically, we designed a direct illuminance-contribution-based lighting-control algorithm (DIC-LCA) using luminaires that are ideally axisymmetric with all light emitted below the horizontal plane and developed a WiFi lighting controller for the IoT-based lighting-control systems in smart buildings. The DIC-LCA can adjust the dimming level by calculating the illuminance based on the line of sight (LOS) distance for energy saving and user satisfaction. After simulation analysis, we prove that energy savings can be achieved by controlling the dimming levels of LED luminaires with high light contribution.
Esketamine Exposure Impairs Cardiac Development and Function in Zebrafish Larvae
Authors: Huang Shuo , Wang Jingyi , Lin Tingting , He Chengyong , Chen Zhiyuan
Published: June 2024

Esketamine is a widely used intravenous general anesthetic. However, its safety, particularly its effects on the heart, is not fully understood. In this study, we investigated the effects of esketamine exposure on zebrafish embryonic heart development. Zebrafish embryos were exposed to esketamine at concentrations of 1, 10, and 100 mg/L from 48 h post-fertilization (hpf) to 72 hpf. We found that after exposure, zebrafish embryos had an increased hatching rate, decreased heart rate, stroke volume, and cardiac output. When we exposed transgenic zebrafish of the Tg(cmlc2:EGFP) strain to esketamine, we observed ventricular dilation and thickening of atrial walls in developing embryos. Additionally, we further discovered the abnormal expression of genes associated with cardiac development, including nkx2.5, gata4, tbx5, and myh6, calcium signaling pathways, namely ryr2a, ryr2b, atp2a2a, atp2a2b, slc8a3, slc8a4a, and cacna1aa, as well as an increase in acetylcholine concentration. In conclusion, our findings suggest that esketamine may impair zebrafish larvae’s cardiac development and function by affecting acetylcholine concentration, resulting in weakened cardiac neural regulation and subsequent effects on cardiac function. The insights garnered from this research advocate for a comprehensive safety assessment of esketamine in clinical applications.
Efficient and Rapid Combined Electrocoagulation–Filtration of Arsenic in Drinking Water
Authors: Channa Najeebullah , Gadhi Tanveer A. , Mahar Rasool Bux , Ali Imran , Sajjad Sana , Freyria Francesca S. , Bonelli Barbara , Widderich Sonke , Frechen Franz-Bernd
Published: June 2024

Arsenic (As) contamination is a severe problem in drinking-water sources. This study designed and investigated a novel combined electrocoagulation–filtration (ECF) system to investigate As treatment and filtration in drinking water in collaboration with HANDS-Pakistan and Medico International, Germany. Two separate pilot-scale ECF systems were designed and developed with an electrocoagulation (EC) unit and a commercially available PAUL® filter configured with vertical flat-sheet ultra-low-pressure membranes of 0.04 µm pore size for the combined treatment and filtration of different As concentrations. Real drinking water at different As concentrations, i.e., 100, 200, and 300 μg/L were tested on one ECF system with EC electrodes of iron (Fe) and another system with aluminum (Al), at different treatment times (0, 5, 10, 20, 45, 60, 120, 180 min), at a fixed current density (12 mA/cm2) and water flow rate of 1 L/min. The initial results showed 99% As removal within 5 min with the combined ECF treatment for both electrodes of Fe and Al. In addition, the effect of ECF on different water-quality parameters and the ionic interference on ECF performance and As filtration were analyzed. The results showed the promising potential of combined ECF treatment and filtration for treating and purifying As.