bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving the Traits of Perilla frutescens (L.) Britt Using Gene Editing Technology
Authors: Karthik Sivabalan , Chae Jia , Han Seong , Kim Jee , Kim Hye , Chung Young-Soo , Kim Hyun , Heo Jae
Published: May 2024

Plant breeding has evolved significantly over time with the development of transformation and genome editing techniques. These new strategies help to improve desirable traits in plants. Perilla is a native oil crop grown in Korea. The leaves contain many secondary metabolites related to whitening, aging, antioxidants, and immunity, including rosmarinic acid, vitamin E, luteolin, anthocyanins, and beta-carotene. They are used as healthy and functional food ingredients. It is an industrially valuable cosmetics crop. In addition, perilla seeds are rich in polyunsaturated fatty acids, such as α-linolenic acid and linoleic acid. They are known to be effective in improving neutral lipids in the blood, improving blood circulation, and preventing dementia and cardiovascular diseases, making them excellent crops whose value can be increased through improved traits. This research will also benefit perilla seeds, which can increase their stock through various methods, such as the increased production of functional substances and improved productivity. Recently, significant attention has been paid to trait improvement research involving gene-editing technology. Among these strategies, CRISPR/Cas9 is highly adaptable, enabling accurate and efficient genome editing, targeted mutagenesis, gene knockouts, and the regulation of gene transcription. CRISPR/Cas9-based genome editing has enormous potential for improving perilla; however, the regulation of genome editing is still at an early stage. Therefore, this review summarizes the enhancement of perilla traits using genome editing technology and outlines future directions.
Antimicrobial Solid Starch–Iodine Complex via Reactive Extrusion and Its Application in PLA-PBAT Blown Films
Authors: Kulkarni Apoorva , Sharma Dimple , Ermlich Alexander , Manjure Shilpa , Narayan Ramani , Bergholz Teresa M.
Published: May 2024

In this study, a solid masterbatch of starch–iodine complex with 6.7 wt.% iodine was prepared in pellet form using a ZSK-30 twin-screw extruder. Thermogravimetric (TGA) and isothermal TGA analysis of the pellets revealed that there was no significant loss of iodine due to sublimation during reactive extrusion. These solid pellets demonstrated antifungal properties when applied to strawberries via dip coating in an aqueous solution, extending their shelf life from two days to eight days, thereby reducing fungal growth and visual decay. Furthermore, the solid pellets displayed antibacterial activity against E. coli, as evidenced by the clear zone of inhibition observed in the Kirby–Bauer test. To enhance practical application, these pellets were further blended with PLA-PBAT film formulations at 10 and 18% by wt. to make blown films with effective iodine loadings of 0.7 and 1.3% by wt. These films showed superior antibacterial activity against E. coli compared with PLA control films and the commercial silver antimicrobial-containing films during direct inoculation tests as per ISO 22196. Tensile strength and elongation at break in machine direction (MD) for the starch–iodine-containing blown films were comparable to the control films in MD, but tensile strength was reduced to 37–40% in the transverse direction (TD). This was due to a non-uniform dispersion of the starch–iodine complex in the films, as confirmed by the visual and SEM analyses. Thus, this study illustrates the practical utility of the solid starch–iodine complex as a safe and efficient means of introducing iodine into an environment, mitigating the typical hazards associated with handling solid iodine.
Laboratory and Numerical Investigation of Pre-Tensioned Reinforced Concrete Railway Sleepers Combined with Plastic Fiber Reinforcement
Authors: Németh Attila , Ibrahim Sarah Khaleel , Movahedi Rad Majid , Szalai Szabolcs , Major Zoltán , Kocsis Szürke Szabolcs , Jóvér Vivien , Sysyn Mykola , Kurhan Dmytro , Harrach Dániel , Baranyai Gusztáv , Fekete Imre , Nagy Richárd , Csótár Hanna , Madarász Klaudia , Pollák András , Molnár Bálint , Hermán Bence , Kuczmann Miklós , Gáspár László , Fischer Szabolcs
Published: May 2024

This research investigates the application of plastic fiber reinforcement in pre-tensioned reinforced concrete railway sleepers, conducting an in-depth examination in both experimental and computational aspects. Utilizing 3-point bending tests and the GOM ARAMIS system for Digital Image Correlation, this study meticulously evaluates the structural responses and crack development in conventional and plastic fiber-reinforced sleepers under varying bending moments. Complementing these tests, the investigation employs ABAQUS’ advanced finite element modeling to enhance the analysis, ensuring precise calibration and validation of the numerical models. This dual approach comprehensively explains the mechanical behavior differences and stresses within the examined structures. The incorporation of plastic fibers not only demonstrates a significant improvement in mechanical strength and crack resistance but paves the way for advancements in railway sleeper technology. By shedding light on the enhanced durability and performance of reinforced concrete structures, this study makes a significant contribution to civil engineering materials science, highlighting the potential for innovative material applications in the construction industry.
Experimental Study on Rats with Critical-Size Bone Defects Comparing Effects of Autologous Bone Graft, Equine Bone Substitute Bio-Gen® Alone or in Association with Platelet-Rich Fibrin (PRF)
Authors: Ciobanu Petru , Danciu Mihai , Pascu Andrei , Gardikiotis Ioannis , Forna Norin , Sirbu Mihnea Theodor , Calistru Anca-Elena , Puha Bogdan , Veliceasa Bogdan , Sirbu Paul-Dan
Published: May 2024

Background: A critical-sized bone defect (CsBD) is considered one that will not heal spontaneously and requires reconstruction. This study aims to compare the results of using different bone reconstructive techniques and to study the potential of platelet-rich fibrin (PRF) to enhance the healing properties of a bone substitute (BS). Methods: In this experimental study on rats, the treatment of critical-sized bone defects was carried out by analysing four groups: a control group in which the bone defect was left empty; a group treated with Bio-Gen®; another group in which the defect was treated with PRF in combination with Bio-Gen®; and the last that was treated with autologous bone graft (ABG). The defects were evaluated by microcomputed tomography (µCT) and then histomorphometrically. Results: From both the histological and imagistic point of view, the best results were registered in the ABG group, followed by the group treated with Bio-Gen® with PRF, Bio-Gen® group, and control group, with statistically significant differences. Conclusions: A 5 mm defect in the rat radius can be considered critical. ABG showed the best results in treating the bone defect. PRF significantly enhanced the efficacy of Bio-Gen®.
Mechanical, Fire, and Electrical Insulation Properties of Polyurethane Fly Ash Composites
Authors: Shivakumar Kunigal N. , Kenchappa Bharath , Imran Kazi A.
Published: May 2024

This paper demonstrates that ash composites, comprising fly ash and polyurethane, can be used to develop value-added products that exhibit an effective decrease in the leaching of coal ash inorganics to less than one-third of the Environmental Protection Agency (EPA)’s maximum contaminant level (MCL) when soaked in a water circulation system for 14 months. Furthermore, the composite blocks remain safe even with ruptured surfaces. The concept of encapsulating fly ash within ash composites by using a polar polymer to bind the fine inorganic particles, mimicking how nature does it in the original unburned coal, ensures the safety of the composite. The ash composites can be formulated to have designed mechanical, fire, and electrical properties by controlling the formulation and the density. The properties of typical density composites were produced, measured, and compared with commercial materials. This paper also demonstrates that ash composite technology can be extended to coal ash stored in ponds. Finally, a typical electric utility box cover was designed, fabricated, and test validated. The box cover has less than one-half the weight of the original box cover for the same design limits. Finally, the benefits of this ash-composite technology for product manufacturers, society, and ash producers are summarized.
A Hierarchical Axiomatic Evaluation of Additive Manufacturing Equipment and the 3D Printing Process Based on Sustainability and Human Factors
Authors: Mendoza-Muñoz Ismael , Montoya-Reyes Mildrend Ivett , Maldonado-Macías Aidé Aracely , Jacobo-Galicia Gabriela , Vargas-Bernal Olivia Yessenia
Published: May 2024

As interest in additive manufacturing (AM) continues to increase, it has become more important to have a robust method to help potential users select the AM process that best suits their technological needs while providing the greatest potential benefits in terms of sustainability and its effect on people. This paper presents the development of a framework for selecting the best AM process for a given application by considering both sustainability and human factors through the combination of axiomatic design and the analytic hierarchy process. Thirty-one participants with varying levels of expertise (novice and advanced users) were involved in the study, considering the frequency of 3D printer usage (novice users: never, rarely; expert users: sometimes, almost always, always) for prototyping parts. They employed fused deposition modeling (FDM) and stereolithography (SLA) (both 3D desktop printers) and collected data on five evaluation criteria. The participation of experts helped establish a novel methodology, with material cost deemed most important (49.8%), followed by cycle time (28%), energy consumption (11.7%), error rate (6.6%), and equipment noise (3.9%). The results showed that FDM was the optimal equipment option for advanced users. By examining the information content of the other options, it was found that FDM demanded less information than SLA, regardless of the user’s level of expertise. The proposed method is appropriate to assess the sustainability aspect of FDM and SLA; however, it can be further improved by adding indicators such as environmental impact, recyclability, and ergonomic and occupational health factors.
Effect of Cross-Well Natural Fractures and Fracture Network on Production History Match and Well Location Optimization in an Ultra-Deep Gas Reservoir
Authors: Chen Dong , Jiao Yuwei , Yang Fenglai , Liu Chuxi , Yang Min , Leines Artieda Joseph , Yu Wei
Published: May 2024

Understanding subsurface natural fracture systems is crucial to characterize well production dynamics and long-term productivity potential. In addition, the placement of future wells can benefit from in-depth fracture network connectivity investigations, vastly improving new wells’ profitability and life cycles if they are placed in dense, well-connected natural fracture zones. In this study, a novel natural fracture calibration workflow is proposed. This workflow starts with the extraction of sector geology and a natural fracture model from the pre-built full-field model. Then, a cross wellbore discrete fracture network (CW-DFN) is created using a novel CW-DFN generation tool, based on image log data. An innovative fracture network identification tool is developed to detect the interconnected regional fracture network (IcFN) with CW-DFN. The non-intrusive embedded discrete fracture model (EDFM) is utilized to numerically incorporate the complex IcFN and CW-DFN in a reservoir simulation, and it is history-matched by tuning their conductivities. This workflow is applied to a single vertical well within a natural fracture carbonate reservoir in Northwest China. The study results show that the number of CW-DFNs is 11, and the number of IcFNs is 72. The non-intersected natural fractures only account for 5.5% of the production, and thus can be removed to improve simulation efficiency. The history-matching absolute average relative deviation (AARD) is 15.16%. The calibrated effective fracture permeability is 280 millidarcy, with an aperture of 0.001 m, equating to a conductivity of 0.28 millidarcy-meter. The 30-year gas production forecast is estimated to be 1.66 billion cubic meters based on a history-matched model. Finally, if the well is drilled to the east of the sector, 30-year production declines to 1.33 billion cubic meters (a reduction of 20%). However, if the well is drilled to the west of the sector, 30-year production increases to 2 billion cubic meters (an improvement of 20.5%).
Analysis of Rock Mass Energy Characteristics and Induced Disasters Considering the Blasting Superposition Effect
Authors: Chen Lu , Yang Xiaocong , Guo Lijie , Yu Shibo
Published: May 2024

Upon reaching deeper levels of extraction, dynamic hazards such as rockburst become more pronounced, with the high energy storage characteristics of rock masses in high-stress environments being the fundamental factor behind rockburst disasters. Additionally, deep-seated mineral extraction commonly involves drilling and blasting methods, where the vibrational energy generated by mining explosions combines with the elastic energy of rock masses, leading to a sudden growth in the risk and intensity of rockburst disasters. This paper, with deep mining at Sanshandao Gold Mine as the focal point, systematically investigates the impact of blasting vibrations on rockburst disasters in deep mines. Initially, based on extensive data on measured geostress considering the tri-arch cross-section form of deep tunnels, the elastic energy storage of the surrounding rocks in deep tunnels was calculated. The results indicate that the maximum energy storage of the surrounding rocks occurs at the bottom of the tunnel, with the peak accumulation position located at a distance of five times the tunnel radius. On this basis, the Map3D numerical simulation analysis was adopted to systematically capture the accumulation behavior and distribution characteristics of disturbance energy. Subsequently, by conducting the dynamic impact experiments with an improved Split Hopkinson pressure bar (SHPB) and monitoring vibration signals at various locations, the paper provides insights into the propagation patterns of impact energy in a long sample (400 mm in length and 50 mm in diameter). Analysis of the scattering behavior of vibrational energy reveals that the combined portion of blasting vibration energy constitutes 60% of the total vibrational energy. Finally, a rockburst disaster evaluation model based on energy accumulations was proposed to analyze the rockburst tendencies around deep tunnels. The results indicated that the disaster-driven energy increased by 19.9% and 12.2% at different places on the roadway. Also, the probability and intensity of a rockburst would be raised.
Opening Polish Schools to Ukrainian Refugee Children and Providing Them with Spiritual Support: Survey Results
Authors: Nazaruk Stanisława , Budnyk Olena , Ruszkowska Marzena , Dąbrowska Izabela , Sokołowska Barbara , Tkachuk Tamara
Published: May 2024

Following the Russian Federation’s attack on Ukraine, many women and children were forced to flee their homeland out of fear for lives. Poland, as a country bordering Ukraine, has accepted the most refugees, compared to other EU states. Soon after, Ukrainian school-age children began their education in Polish schools, but the process of their enrolment and adaptation to a new environment, as well as the provision of psychological assistance, became a significant challenge. The aim of the study was to inquire about the actions taken by principals of primary schools in Poland in connection with accepting refugee students from Ukraine to their institutions, as well as determining the possibilities of providing these students with spiritual support. The following survey research conducted in the four voivodeships that accepted the largest number of refugees, in urban and rural environments, allowed the identification of the practical solutions used by school principals in organising the assistance provided to refugee students from Ukraine in learning and integration with peers. As the research has indicated, the most important challenges in working with Ukrainian children affected by war are psycho-emotional experiences, depression and adaptation problems. Therefore, the priority in working with them was to use the strategy of spiritual support and solidarity, focusing on the prioritised human values—humanism, tolerance, faith, love, empathy, kindness, and mutual help. The conclusions drawn from the experience gained by Polish schools, in particular, in terms of the spiritual support for children of war, can be used by educational systems in other countries.
Shamanistic Rituals to Âşıks Performances: Symbolism of Summoning Spirits
Authors: Yeşildal Ünsal Yılmaz , Güzelderen Banu , Düzgün Fatih
Published: May 2024

Âşıks, renowned for their adeptness at improvisational poetry, are viewed as the inheritors of certain shamanic functions within historical contexts. Originally, shamans assumed diverse roles encompassing poetry, medicine, and priesthood before social and religious transformations prompted a gradual shift of the poetic responsibilities, first to individuals termed ozan (bards) and later to âşık, beginning from the 15th to 16th centuries. Âşıks share parallels with shamans in their upbringing, developmental stages toward âşıklık (bardhood), and esteemed societal positions. Their reverence for deceased masters becomes evident in their artistic presentations, wherein they express homage to the memories, and consequently the spirits, of their masters by reciting the works of esteemed âşık masters, notably Köroğlu, during their performances. This practice, referred to as “usta malı söylemek” (the performance of the masters’ poems and folk songs) within the Turkish âşık tradition, represents an endeavor to establish a connection with the spirits of ancestors. The resemblance between the tradition of âşıks evolving within the master–apprentice dynamic and shamans invoking the spirits of departed ancestors, embarking on celestial and subterranean journeys empowered by them, and the âşıks’ homage to their masters’ spirits through recitations of their works, thereby sensing their masters’ influence by engaging with them, is striking. This study explores the extent to which contemporary âşıks consciously embrace this resemblance. To this end, a sample group of 34 âşıks residing in diverse regions of Türkiye was interviewed, and the acquired data were analyzed using the document analysis method. Accordingly, all the âşıks who participated in the study were nurtured within the tradition of the master–apprentice relationship akin to shamans. They diligently sought to evoke the spirits of their masters during their performances by reciting masters’ poems and songs, reminiscent of shamans invoking the spirits of deceased shaman ancestors through prayers resembling divine verses. Furthermore, while variations specific to different regions and age groups existed among these âşıks, it was observed that consciously reciting the poems of their masters elevated the masters’ spirits. Simultaneously, they harbored concerns about the potential harm that neglecting this practice might inflict upon the tradition, themselves, and their surroundings.
Trans-Belief: Developing Artificial Intelligence NLP Model Capable of Religious-Belief-like Cognitive Processes for Expected Enhanced Cognitive Ability
Authors: Dagan Ido
Published: May 2024

This paper investigates the possibility of developing artificial intelligence (AI) systems capable of exhibiting limited cognitive processes analogous to aspects of human religious belief. The literature review pertains to the most essential cognitive mechanisms of belief and the most relevant models for AI with belief. Accordingly, and as a result of the theoretical review, drawing inspiration from belief cognition to endow AI with enhanced cognitive capacities, the core objective is to try to build a theoretical model that simulates cognitive processes of belief, equipping AI agents with abilities to recognize subtle divine synchronistic patterns and form provisional convictions computationally modeled on belief cognitive mechanisms. The hypothesis is that this could hopefully unlock a higher level of cognitive function and could enhance capacities for nuanced, context-sensitive reasoning and prediction for these AI models. The method is a novel “Trans-Belief” theoretical model that will be considered, integrating fuzzy and doxastic logic models to trace synchronistic divine patterns, in the results section. Finally, in the discussion, additional moral aspects and the nature of the data set of the model will be examined, and directions for future research will be proposed. While not implying AI can or should fully replicate complex human spirituality, tentative artificial belief could impart beneficial qualities like contextual awareness. However, developing belief-inspired algorithms requires grappling with profound philosophical questions regarding singularity and implementing strong ethical safeguards on any AI-granted agency over human affairs. This represents an early exploration of belief’s implications for machine learning, necessitating future research and discussion.
Characterization and Validation of ECOSTRESS Sea Surface Temperature Measurements at 70 m Spatial Scale
Authors: Wethey David S. , Weidberg Nicolas , Woodin Sarah A. , Vazquez-Cuervo Jorge
Published: May 2024

The ECOSTRESS push-whisk thermal radiometer on the International Space Station provides the highest spatial resolution temperature retrievals over the ocean that are currently available. It is a precursor to the future TRISHNA (CNES/ISRO), SBG (NASA), and LSTM (ESA) 50 to 70 m scale missions. Radiance transfer simulations and triple collocations with in situ ocean observations and NOAA L2P geostationary satellite ocean temperature retrievals were used to characterize brightness temperature biases and their sources in ECOSTRESS Collection 1 (software Build 6) data for the period 12 January 2019 to 31 October 2022. Radiometric noise, non-uniformities in the focal plane array, and black body temperature dynamics were characterized in ocean scenes using L1A raw instrument data, L1B calibrated radiances, and L2 skin temperatures. The mean brightness temperature biases were −1.74, −1.45, and −1.77 K relative to radiance transfer simulations in the 8.78, 10.49, and 12.09 µm wavelength bands, respectively, and skin temperatures had a −1.07 K bias relative to in situ observations. Cross-track noise levels range from 60 to 600 mK and vary systematically along the focal plane array and as a function of wavelength band and scene temperature. Overall, radiometric uncertainty is most strongly influenced by cross-track noise levels and focal plane non-uniformity. Production of an ECOSTRESS sea surface temperature product that meets the requirements of the SST community will require calibration methods that reduce the biases, noise levels, and focal plane non-uniformities.
Error Analysis and Correction of FENGYUN-4A GIIRS Temperature Profile Products in Summer over the Qinghai–Tibet Plateau
Authors: Jiang Xiaofei , Wang Qiguang , Niu Ning
Published: May 2024

To understand the applicability of the temperature profile product of the FENGYUN-4A (FY-4A) geostationary interferometric infrared detector (GIIRS) in summer over the Qinghai–Tibet Plateau and to improve product quality, the error of GIIRS temperature products was analyzed based on radiosonde data. A long short-term memory network model (LSTM) was used to correct the GIIRS temperature profile product in summer over the plateau at a high altitude (above 500 hPa), and further evaluation of the corrected product was conducted. The results show that summertime GIIRS temperature retrievals over the Qinghai–Tibet Plateau had a positive bias above 150 hPa and a negative bias below 150 hPa, resulting in an overall negative bias. The root mean square error was between 2 and 2.9 K, and the root mean square error was relatively large at 100 hPa and above. The LSTM established in this study could effectively correct the GIIRS temperature over the plateau. The correlation and root mean square error of the corrected GIIRS temperature and the radiosonde observation temperature were significantly improved. Using a trained LSTM correction model to correct the hourly GIIRS temperature can improve the accuracy and usability of the product. After correction, the average bias of the GIIRS temperature compared to the ERA5 temperature product was reduced from −0.26 K to 0.06 K, and the root mean square error was reduced from 2.25 K to 1.25 K. The correction model can be applied to different seasons, and it can also correct the GIIRS temperature in larger areas based on other high-precision and high-resolution data, achieving good results, thus indicating that the correction model has universal applicability.
Hyperspectral Image Classification Based on Two-Branch Multiscale Spatial Spectral Feature Fusion with Self-Attention Mechanisms
Authors: Ma Boran , Wang Liguo , Wang Heng
Published: May 2024

In recent years, the use of deep neural network in effective network feature extraction and the design of efficient and high-precision hyperspectral image classification algorithms has gradually become a research hotspot for scholars. However, due to the difficulty of obtaining hyperspectral images and the high cost of annotation, the training samples are very limited. In order to cope with the small sample problem, researchers often deepen the network model and use the attention mechanism to extract features; however, as the network model continues to deepen, the gradient disappears, the feature extraction ability is insufficient, and the computational cost is high. Therefore, how to make full use of the spectral and spatial information in limited samples has gradually become a difficult problem. In order to cope with such problems, this paper proposes two-branch multiscale spatial–spectral feature aggregation with a self-attention mechanism for a hyperspectral image classification model (FHDANet); the model constructs a dense two-branch pyramid structure, which can achieve the high efficiency extraction of joint spatial–spectral feature information and spectral feature information, reduce feature loss to a large extent, and strengthen the model’s ability to extract contextual information. A channel–space attention module, ECBAM, is proposed, which greatly improves the extraction ability of the model for salient features, and a spatial information extraction module based on the deep feature fusion strategy HLDFF is proposed, which fully strengthens feature reusability and mitigates the feature loss problem brought about by the deepening of the model. Compared with five hyperspectral image classification algorithms, SVM, SSRN, A2S2K-ResNet, HyBridSN, SSDGL, RSSGL and LANet, this method significantly improves the classification performance on four representative datasets. Experiments have demonstrated that FHDANet can better extract and utilise the spatial and spectral information in hyperspectral images with excellent classification performance under small sample conditions.
Development of a Low-Cost Markerless Optical Motion Capture System for Gait Analysis and Anthropometric Parameter Quantification
Authors: Espitia-Mora Laura Alejandra , Vélez-Guerrero Manuel Andrés , Callejas-Cuervo Mauro
Published: May 2024

Technological advancements have expanded the range of methods for capturing human body motion, including solutions involving inertial sensors (IMUs) and optical alternatives. However, the rising complexity and costs associated with commercial solutions have prompted the exploration of more cost-effective alternatives. This paper presents a markerless optical motion capture system using a RealSense depth camera and intelligent computer vision algorithms. It facilitates precise posture assessment, the real-time calculation of joint angles, and acquisition of subject-specific anthropometric data for gait analysis. The proposed system stands out for its simplicity and affordability in comparison to complex commercial solutions. The gathered data are stored in comma-separated value (CSV) files, simplifying subsequent analysis and data mining. Preliminary tests, conducted in controlled laboratory environments and employing a commercial MEMS-IMU system as a reference, revealed a maximum relative error of 7.6% in anthropometric measurements, with a maximum absolute error of 4.67 cm at average height. Stride length measurements showed a maximum relative error of 11.2%. Static joint angle tests had a maximum average error of 10.2%, while dynamic joint angle tests showed a maximum average error of 9.06%. The proposed optical system offers sufficient accuracy for potential application in areas such as rehabilitation, sports analysis, and entertainment.
Development of a Method for Soil Tilth Quality Evaluation from Crumbling Roller Baskets Using Deep Machine Learning Models
Authors: Tekeste Mehari Z. , Guo Junxian , Habtezgi Desale , He Jia-Hao , Waz Marcin
Published: May 2024

A combination tillage with disks, rippers, and roller baskets allows the loosening of compacted soils and the crumbling of soil clods. Statistical methods for evaluating the soil tilth quality of combination tillage are limited. Light Detection and Ranging (LiDAR) data and machine learning models (Random Forest (RF), Support Vector Machine (SVM), and Neural Network (NN)) are proposed to investigate roller basket pressure settings on soil tilth quality. Soil profiles were measured using LiDAR (stop and go and on-the-go) and RGB visual images from a Completely Randomized Design (CRD) tillage experiment on clay loam soil with treatments of roller basket down, roller basket up, and no-till in three replicates. Utilizing RF, SVM, and NN methods on the LiDAR data set identified median, mean, maximum, and standard deviation as the top features of importance variables that were statistically affected by the roller settings. Applying multivariate discriminatory analysis on the four statistical measures, three soil tilth classes were predicted with mean prediction rates of 77% (Roller-basket down), 64% (Roller-basket up), and 90% (No till). The LiDAR data analytics-inspired soil tilth classes correlated well with the RGB image discriminatory analysis. Soil tilth machine learning models were shown to be successful in classifying soil tilth with regard to onboard operator pressure control settings on the roller basket of the combination tillage implement.
Development of an Optical System for Strain Drop Measurement of Osteosarcoma Cells on Substrates with Different Stiffness
Authors: Apa Ludovica , Martire Maria Vittoria , Carraro Serena , Cosentino Marianna , Del Prete Zaccaria , Peruzzi Barbara , Rizzuto Emanuele
Published: May 2024

Adherent cells perceive mechanical feedback from the underlying matrix and convert it into biochemical signals through a process known as mechanotransduction. The response to changes in the microenvironment relies on the cell’s mechanical properties, including elasticity, which was recently identified as a biomarker for various diseases. Here, we propose the design, development, and characterization of a new system for the measurement of adherent cells’ strain drop, a parameter correlated with cells’ elasticity. To consider the interplay between adherent cells and the host extracellular matrix, cell stretching was combined with adhesion on substrates with different stiffnesses. The technique is based on the linear stretching of silicone chambers, high-speed image acquisition, and feedback for image centering. The system was characterized in terms of the strain homogeneity, impact of collagen coating, centering capability, and sensitivity. Subsequently, it was employed to measure the strain drop of two osteosarcoma cell lines, low-aggressive osteoblast-like SaOS-2 and high-aggressive 143B, cultured on two different substrates to recall the stiffness of the bone and lung extracellular matrices. Results demonstrated good substrate homogeneity, a negligible effect of the collagen coating, and an accurate image centering. Finally, the experimental results showed an average strain drop that was lower in the 143B cells in comparison with the SaOS-2 cells in all the tested conditions.
A Programmable Ambient Light Sensor with Dark Current Compensation and Wide Dynamic Range
Authors: Shi Nianbo , Yang Jian , Cao Zhixiang , Jin Xiangliang
Published: May 2024

Ambient light sensors are becoming increasingly popular due to their effectiveness in extending the battery life of portable electronic devices. However, conventional ambient light sensors are large in area and small in dynamic range, and they do not take into account the effects caused due to a dark current. To address the above problems, a programmable ambient light sensor with dark current compensation and a wide dynamic range is proposed in this paper. The proposed ambient light sensor exhibits a low current power consumption of only 7.7 µA in dark environments, and it operates across a wide voltage range (2–5 V) and temperature range (−40–80 °C). It senses ambient light and provides an output current proportional to the ambient light intensity, with built-in dark current compensation to effectively suppress the effects of a dark current. It provides a wide dynamic range over the entire operating temperature range with three selectable output-current gain modes. The proposed ambient light sensor was designed and fabricated using a 0.18 µm standard CMOS process, and the effective area of the chip is 663 µm × 652 µm. The effectiveness of the circuit was verified through testing, making it highly suitable for portable electronic products and fluorescent fiber-optic temperature sensors.
A Novel Method of UAV-Assisted Trajectory Localization for Forestry Environments
Authors: Huang Jian , Guo Xiansheng
Published: May 2024

Global positioning systems often fall short in dense forest environments, leading to increasing demand for innovative localization methods. Notably, existing methods suffer from the following limitations: (1) traditional localization frameworks necessitate several fixed anchors to estimate the locations of targets, which is difficult to satisfy in complex and uncertain forestry environments; (2) the uncertain environment severely decreases the quality of signal measurements and thus the localization accuracy. To cope with these limitations, this paper proposes a new method of trajectory localization for forestry environments with the assistance of UAVs. Based on the multi-agent DRL technique, the topology of UAVs is optimized in real-time to cater for high-accuracy target localization. Then, with the aid of RSS measurements from UAVs to the target, the least squares algorithm is used to estimate the location, which is more flexible and reliable than existing localization systems. Furthermore, a shared replay memory is incorporated into the proposed multi-agent DRL system, which can effectively enhance learning performance and efficiency. Simulation results show that the proposed method can obtain a flexible and high-accuracy localization system with the aid of UAVs, which exhibits better robustness against high-dimensional heterogeneous data and is suitable for forestry environments.
Cam-Unet: Print-Cam Image Correction for Zero-Bit Fourier Image Watermarking
Authors: Boujerfaoui Said , Douzi Hassan , Harba Rachid , Ros Frédéric
Published: May 2024

Image watermarking often involves the use of handheld devices under non-structured conditions for authentication purposes, particularly in the print-cam process where smartphone cameras are used to capture watermarked printed images. However, these images frequently suffer from perspective distortions, making them unsuitable for automated information detection. To address this issue, Cam-Unet, an end-to-end neural network architecture, is presented to predict the mapping from distorted images to rectified ones, specifically tailored for print-cam challenges applied to ID images. Given the limited availability of large-scale real datasets containing ground truth distortions, we created an extensive synthetic dataset by subjecting undistorted images to print-cam attacks. The proposed network is trained on this dataset, using various data augmentation techniques to improve its generalization capabilities. Accordingly, this paper presents an image watermarking system for the print-cam process. The approach combines Fourier transform-based watermarking with Cam-Unet as perspective distortion correction. Results show that the proposed method outperforms existing watermarking approaches typically employed to counter print-cam attacks and achieves an optimal balance between efficiency and cost-effectiveness.
Characterization of Gas–Liquid Two-Phase Slug Flow Using Distributed Acoustic Sensing in Horizontal Pipes
Authors: Ali Sharifah , Jin Ge , Fan Yilin
Published: May 2024

This article discusses the use of distributed acoustic sensing (DAS) for monitoring gas–liquid two-phase slug flow in horizontal pipes, using standard telecommunication fiber optics connected to a DAS integrator for data acquisition. The experiments were performed in a 14 m long, 5 cm diameter transparent PVC pipe with a fiber cable helically wrapped around the pipe. Using mineral oil and compressed air, the system captured various flow rates and gas–oil ratios. New algorithms were developed to characterize slug flow using DAS data, including slug frequency, translational velocity, and the lengths of slug body, slug unit, and the liquid film region that had never been discussed previously. This study employed a high-speed camera next to the fiber cable sensing section for validation purposes and achieved a good correlation among the measurements under all conditions tested. Compared to traditional multiphase flow sensors, this technology is non-intrusive and offers continuous, real-time measurement across long distances and in harsh environments, such as subsurface or downhole conditions. It is cost-effective, particularly where multiple measurement points are required. Characterizing slug flow in real time is crucial to many industries that suffer slug-flow-related issues. This research demonstrated the DAS’s potential to characterize slug flow quantitively. It will offer the industry a more optimal solution for facility design and operation and ensure safer operational practices.
Device-Free Wireless Sensing for Gesture Recognition Based on Complementary CSI Amplitude and Phase
Authors: Cai Zhijia , Li Zehao , Chen Zikai , Zhuo Hongyang , Zheng Lei , Wu Xianda , Liu Yong
Published: May 2024

By integrating sensing capability into wireless communication, wireless sensing technology has become a promising contactless and non-line-of-sight sensing paradigm to explore the dynamic characteristics of channel state information (CSI) for recognizing human behaviors. In this paper, we develop an effective device-free human gesture recognition (HGR) system based on WiFi wireless sensing technology in which the complementary CSI amplitude and phase of communication link are jointly exploited. To improve the quality of collected CSI, a linear transform-based data processing method is first used to eliminate the phase offset and noise and to reduce the impact of multi-path effects. Then, six different time and frequency domain features are chosen for both amplitude and phase, including the mean, variance, root mean square, interquartile range, energy entropy and power spectral entropy, and a feature selection algorithm to remove irrelevant and redundant features is proposed based on filtering and principal component analysis methods, resulting in the construction of a feature subspace to distinguish different gestures. On this basis, a support vector machine-based stacking algorithm is proposed for gesture classification based on the selected and complementary amplitude and phase features. Lastly, we conduct experiments under a practical scenario with one transmitter and receiver. The results demonstrate that the average accuracy of the proposed HGR system is 98.3% and that the F1-score is over 97%.
Coverage Planning for UVC Irradiation: Robot Surface Disinfection Based on Swarm Intelligence Algorithm
Authors: Guo Peiyao , Luo Dekun , Wu Yizhen , He Sheng , Deng Jianyu , Yao Huilu , Sun Wenhong , Zhang Jicai
Published: May 2024

Ultraviolet (UV) radiation has been widely utilized as a disinfection strategy to effectively eliminate various pathogens. The disinfection task achieves complete coverage of object surfaces by planning the motion trajectory of autonomous mobile robots and the UVC irradiation strategy. This introduces an additional layer of complexity to path planning, as every point on the surface of the object must receive a certain dose of irradiation. Nevertheless, the considerable dosage required for virus inactivation often leads to substantial energy consumption and dose redundancy in disinfection tasks, presenting challenges for the implementation of robots in large-scale environments. Optimizing energy consumption of light sources has become a primary concern in disinfection planning, particularly in large-scale settings. Addressing the inefficiencies associated with dosage redundancy, this study proposes a dose coverage planning framework, utilizing MOPSO to solve the multi-objective optimization model for planning UVC dose coverage. Diverging from conventional path planning methodologies, our approach prioritizes the intrinsic characteristics of dose accumulation, integrating a UVC light efficiency factor to mitigate dose redundancy with the aim of reducing energy expenditure and enhancing the efficiency of robotic disinfection. Empirical trials conducted with autonomous disinfecting robots in real-world settings have corroborated the efficacy of this model in deactivating viruses.
Compact Ultra-Wideband Wilkinson Power Divider in Parallel Stripline with Modified Isolation Branches
Authors: Go Dong-Jae , Min Byung-Cheol , Kim Mun-Ju , Choi Hyun-Chul , Kim Kang-Wook
Published: May 2024

An efficient design method for a compact and ultra-wideband multi-stage Wilkinson power divider in a parallel stripline (PSL) is proposed. To enhance the frequency bandwidth of the proposed power divider while reducing its size, the isolation branch is modified; that is, two capacitors are connected to both sides of a resistor at each isolation branch. For an efficient design process, the PSL power divider is equivalently represented by two microstrip power dividers, and the design equations are derived. Based on the design equations, an in-house algorithm is utilized to optimally determine the design parameters, including the line impedance, resistance, and capacitance of each stage. For example, a three-stage PSL power divider is designed with three λ/4 transmission lines at a base frequency of 5 GHz. To verify the accuracy of the design procedure, 3D EM simulations and measurements are performed, and the results show good agreement. Compared with the conventional three-stage Wilkinson power divider, the proposed PSL power divider achieves a wider frequency bandwidth of 1.16 to 6.51 GHz (139.5%) and a 23% shorter transmission line length of 207°, while exhibiting an insertion loss of 0.7 to 1.4 dB.
Reliability of Ultrasound Measurements of the Median Nerve in Asymptomatic Subjects Using a Handheld Device
Authors: Alfuraih Abdulrahman M. , Aldahlawi Rana Hussain , Habib Yomna S. , Alhowimel Ahmed S. , Bedewi Mohamed Abdelmohsen
Published: May 2024

This study investigated the reliability of measuring the median nerve cross-sectional area (CSA) at the carpal tunnel inlet using a handheld ultrasound device (HUD) compared to a standard ultrasound system, focusing on intra- and inter-operator reproducibility among novice and expert operators. Employing a prospective cross-sectional design, 37 asymptomatic adults were assessed using both devices, with measurements taken by an expert with over five years of experience and a novice with less than six months. The CSA was determined using manual tracing and ellipse methods, with reproducibility evaluated through intraclass correlation coefficients (ICCs) and agreement assessed via Bland–Altman plots. Results showed a high degree of agreement between the devices, with excellent intra-operator reproducibility (ICC > 0.80) for the expert, and moderate reproducibility for the novice (ICCs ranging from 0.539 to 0.841). Inter-operator reliability was generally moderate, indicating acceptable consistency across different experience levels. The study concludes that HUDs are comparable to standard ultrasound systems for assessing median nerve CSA in asymptomatic subjects, with both devices providing reliable measurements. This supports the use of HUDs in diverse clinical environments, particularly where access to traditional ultrasound is limited. Further research with a larger sample and symptomatic patients is recommended to validate these findings.
The Fluorescent Detection of Glucose and Lactic Acid Based on Fluorescent Iron Nanoclusters
Authors: Ge Jing , Mao Wenlu , Wang Xinyi , Zhang Muqi , Liu Siyu
Published: May 2024

In this paper, a novel fluorescent detection method for glucose and lactic acid was developed based on fluorescent iron nanoclusters (Fe NCs). The Fe NCs prepared using hemin as the main raw material exhibited excellent water solubility, bright red fluorescence, and super sensitive response to hydrogen peroxide (H2O2). This paper demonstrates that Fe NCs exhibit excellent peroxide-like activity, catalyzing H2O2 to produce hydroxyl radicals (•OH) that can quench the red fluorescence of Fe NCs. In this paper, a new type of glucose sensor was established by combining Fe NCs with glucose oxidase (GluOx). With the increase in glucose content, the fluorescence of Fe NCs decreases correspondingly, and the glucose content can be detected in the scope of 0–200 μmol·L−1 (μM). Similarly, the lactic acid sensor can also be established by combining Fe NCs with lactate oxidase (LacOx). With the increase in lactic acid concentration, the fluorescence of Fe NCs decreases correspondingly, and the lactic acid content can be detected in the range of 0–100 μM. Furthermore, Fe NCs were used in the preparation of gel test strip, which can be used to detect H2O2, glucose and lactic acid successfully by the changes of fluorescent intensity.
On-Machine LTS Integration for Layer-Wise Surface Quality Characterization in MEX/P
Authors: Fernández Alejandro , Zapico Pablo , Blanco David , Peña Fernando , Beltrán Natalia , Mateos Sabino
Published: May 2024

Material Extrusion (MEX) currently stands as the most widespread Additive Manufacturing (AM) process, but part quality deficiencies remain a barrier to its generalized industrial adoption. Quality control in MEX is a complex task as extrusion performance impacts the consistency of mechanical properties and the surface finish, dimensional accuracy, and geometric precision of manufactured parts. Recognizing the need for early-stage process monitoring, this study explores the potential of integrating Laser Triangulation Sensors (LTS) into MEX/P manufacturing equipment for layer-wise 3D inspections. Using a double-bridge architecture, an LTS-based sub-micrometric inspection system operates independently from the manufacturing process, enabling comprehensive digitization and autonomous reconstruction of the target layer’s topography. Surface texture is then computed using standardized indicators and a new approach that provides insight into layer quality uniformity. A case study evaluating two alternative extruder head designs demonstrates the efficacy of this integrated approach for layer quality characterization. Implementing a generalized layer-wise procedure based on this integration can significantly mitigate quality issues in MEX manufacturing and optimize process parameter configurations for enhanced performance.