bluuebunny/crossref_metadata_2025 huggingface dataset:
Calibrating Glucose Sensors at the Edge: A Stress Generation Model for Tiny ML Drift Compensation
Authors: Sabatini Anna , Cenerini Costanza , Vollero Luca , Pau Danilo
Published: June 2024

Background: Continuous glucose monitoring (CGM) systems offer the advantage of noninvasive monitoring and continuous data on glucose fluctuations. This study introduces a new model that enables the generation of synthetic but realistic databases that integrate physiological variables and sensor attributes into a dataset generation model and this, in turn, enables the design of improved CGM systems. Methods: The presented approach uses a combination of physiological data and sensor characteristics to construct a model that considers the impact of these variables on the accuracy of CGM measures. A dataset of 500 sensor responses over a 15-day period is generated and analyzed using machine learning algorithms (random forest regressor and support vector regressor). Results: The random forest and support vector regression models achieved Mean Absolute Errors (MAEs) of 16.13 mg/dL and 16.22 mg/dL, respectively. In contrast, models trained solely on single sensor outputs recorded an average MAE of 11.01±5.12 mg/dL. These findings demonstrate the variable impact of integrating multiple data sources on the predictive accuracy of CGM systems, as well as the complexity of the dataset. Conclusions: This approach provides a foundation for developing more precise algorithms and introduces its initial application of Tiny Machine Control Units (MCUs). More research is recommended to refine these models and validate their effectiveness in clinical settings.
Enhancing Icephobic Coatings: Exploring the Potential of Dopamine-Modified Epoxy Resin Inspired by Mussel Catechol Groups
Authors: Koochaki Mohammad , Momen Gelareh , Lavoie Serge , Jafari Reza
Published: June 2024

A nature-inspired approach was employed through the development of dopamine-modified epoxy coating for anti-icing applications. The strong affinity of dopamine’s catechol groups for hydrogen bonding with water molecules at the ice/coating interface was utilized to induce an aqueous quasi-liquid layer (QLL) on the surface of the icephobic coatings, thereby reducing their ice adhesion strength. Epoxy resin modification was studied by attenuated total reflectance infrared spectroscopy (ATR-FTIR) and nuclear magnetic resonance spectroscopy (NMR). The surface and mechanical properties of the prepared coatings were studied by different characterization techniques. Low-temperature ATR-FTIR was employed to study the presence of QLL on the coating’s surface. Moreover, the freezing delay time and temperature of water droplets on the coatings were evaluated along with push-off and centrifuge ice adhesion strength to evaluate their icephobic properties. The surface of dopamine-modified epoxy coating presented enhanced hydrophilicity and QLL formation, addressed as the main reason for its remarkable icephobicity. The results demonstrated the potential of dopamine-modified epoxy resin as an effective binder for icephobic coatings, offering notable ice nucleation delay time (1316 s) and temperature (−19.7 °C), reduced ice adhesion strength (less than 40 kPa), and an ice adhesion reduction factor of 7.2 compared to the unmodified coating.
Advancing Tissue Culture with Light-Driven 3D-Printed Microfluidic Devices
Authors: Li Xiangke , Wang Meng , Davis Thomas P. , Zhang Liwen , Qiao Ruirui
Published: June 2024

Three-dimensional (3D) printing presents a compelling alternative for fabricating microfluidic devices, circumventing certain limitations associated with traditional soft lithography methods. Microfluidics play a crucial role in the biomedical sciences, particularly in the creation of tissue spheroids and pharmaceutical research. Among the various 3D printing techniques, light-driven methods such as stereolithography (SLA), digital light processing (DLP), and photopolymer inkjet printing have gained prominence in microfluidics due to their rapid prototyping capabilities, high-resolution printing, and low processing temperatures. This review offers a comprehensive overview of light-driven 3D printing techniques used in the fabrication of advanced microfluidic devices. It explores biomedical applications for 3D-printed microfluidics and provides insights into their potential impact and functionality within the biomedical field. We further summarize three light-driven 3D printing strategies for producing biomedical microfluidic systems: direct construction of microfluidic devices for cell culture, PDMS-based microfluidic devices for tissue engineering, and a modular SLA-printed microfluidic chip to co-culture and monitor cells.
Advances in Neuropsychology: Top Papers Published in Brain Sciences in 2022–2023
Authors: Zoccolotti Pierluigi
Published: June 2024

The spectrum of typical neuropsychology topics has gradually broadened in recent years thanks to advances in neuroimaging and electrophysiological techniques [...]
A Narrative Review of the Dorsal Root Ganglia and Spinal Cord Mechanisms of Action of Neuromodulation Therapies in Neuropathic Pain
Authors: da Silva Matheus Deroco Veloso , Martelossi-Cebinelli Geovana , Yaekashi Kelly Megumi , Carvalho Thacyana T. , Borghi Sergio M. , Casagrande Rubia , Verri Waldiceu A.
Published: June 2024

Neuropathic pain arises from injuries to the nervous system in diseases such as diabetes, infections, toxicity, and traumas. The underlying mechanism of neuropathic pain involves peripheral and central pathological modifications. Peripheral mechanisms entail nerve damage, leading to neuronal hypersensitivity and ectopic action potentials. Central sensitization involves a neuropathological process with increased responsiveness of the nociceptive neurons in the central nervous system (CNS) to their normal or subthreshold input due to persistent stimuli, leading to sustained electrical discharge, synaptic plasticity, and aberrant processing in the CNS. Current treatments, both pharmacological and non-pharmacological, aim to alleviate symptoms but often face challenges due to the complexity of neuropathic pain. Neuromodulation is emerging as an important therapeutic approach for the treatment of neuropathic pain in patients unresponsive to common therapies, by promoting the normalization of neuronal and/or glial activity and by targeting cerebral cortical regions, spinal cord, dorsal root ganglia, and nerve endings. Having a better understanding of the efficacy, adverse events and applicability of neuromodulation through pre-clinical studies is of great importance. Unveiling the mechanisms and characteristics of neuromodulation to manage neuropathic pain is essential to understand how to use it. In the present article, we review the current understanding supporting dorsal root ganglia and spinal cord neuromodulation as a therapeutic approach for neuropathic pain.
DfMA Integrated Assessment Model for Selecting Optimal Design Alternatives in OSC Projects
Authors: Jung Seoyoung , Lee Seulki , Yu Jungho
Published: June 2024

To select the optimal design alternative in off-site construction (OSC) projects, the building industry has turned to design for manufacturing and assembly (DfMA). However, most DfMA developments in the OSC field until now have been on improving the production process in OSC projects and guideline strategies on how to apply them. The application of DfMA guidelines only provides background knowledge to designers on how to design. However, it cannot inspect whether the DfMA concept is fully reflected in a design draft to examine the suitability to the OSC production environment, and it cannot determine the optimal alternative from among multiple design alternatives. Thus, this study developed an integrated assessment model of OSC-DfMA consisting of the OSC-DfMA production suitability assessment model and the OSC-DfMA production efficiency assessment model to support decision-making for selecting the optimal design alternative of an OSC project. In this study, the scope of the main research was limited to precast concrete (PC)-based OSC projects. Firstly, we developed an OSC-DfMA production suitability assessment model to review whether design drafts are suitable in the OSC production environment by applying checklist and matrix techniques. Secondly, we developed an OSC-DfMA production efficiency assessment model to select an optimal alternative in terms of production efficiency among multiple design drafts. Thirdly, we conducted a case study to validate the usefulness of the OSC-DfMA assessment model developed in this study. Finally, we discuss the possibility of using AI technology to consider the facility capacity and resource constraints during the production of OSC building components. The study results are of practical value in providing the basis for expanding the applicability of DfMA by proposing a DfMA assessment model suitable for OSC contexts.
A Low-Carbon Composite Cementitious Material Manufactured by a Combined Process of Red Mud
Authors: Zhao Zhenhua , Wu Fufei , Dong Shuangkuai , Zhang Qiuyue , Huang Chuanteng , Chen Liangliang
Published: June 2024

In present study, the effects of varying dosages of combined red mud on the microstructure and hydration process of low-carbon composite cementitious material. The findings indicated a gradual decrease in the reactivity of RM, following a linear trend. The non-evaporable water content of the composite binder exhibited an initial increase followed by a subsequent decrease, with the optimal content identified at 10%, for RM content ranging from 10% to 90%, non-evaporable water decreases linearly. Optimal bending strength and compressive strength were achieved in the mortar when incorporating 10% of RM, reaching 8.56 MPa and 51.2 MPa at 28 days, respectively. The porosity was at its lowest when the RM content was added at 10%, but further increasing RM dosage was reversed. The pore size distribution aligned with the experimental findings on porosity. X-ray diffraction (XRD) analysis revealed the involvement of RM in the secondary hydration reaction, thereby enhancing the mechanical properties of low-carbon composite cementitious material. The optimal content of RM is suggested to be 10%, with a maximum recommended limit of 30%. The analysis has shown that red mud particles serve a dual purpose in low-carbon composite cementitious material. They enhance compactness by acting as fillers and promote cement hydration through surface activity, thereby enhancing mechanical properties, durability, and pore size distribution.
Assessing the Impact of Street Visual Environment on the Emotional Well-Being of Young Adults through Physiological Feedback and Deep Learning Technologies
Authors: Zhao Wei , Tan Liang , Niu Shaofei , Qing Linbo
Published: June 2024

Investigating the impact of street visual environments on young adults’ emotions is crucial for the promotion of walkable and healthy streets. However, the applicability and accuracy of existing studies are limited by a lack of large-scale sample validation. Moreover, many studies have determined emotions through subjective evaluation methods or relied solely on a single physiological indicator to assess levels of emotional arousal, neglecting the significance of emotional valence. In response, this study aims to enhance our understanding of the emotional impact of street visual environments by employing a method that integrates physiological feedback technology and deep learning. We collected videos of 100 streets from five districts in Chengdu to serve as experimental stimuli, and utilizing physiological feedback technology, we gathered data on electrocardiograms (ECG), electrodermal activity (EDA), and respiratory responses (RESP) from 50 participants as they observed these street environments. Subsequently, we applied deep learning techniques to process the video and physiological data, ultimately obtaining 500 data entries on street visual environment elements and 25,000 data entries on emotional arousal and valence. Additionally, we established multiple linear regression and multinomial logistic regression models to explore the relationship between visual street environments and emotions. The results reveal that elements such as green view factor (GVF), sky view factor (Sky VF), and sidewalk view factor (SVF) not only reduce emotional arousal levels but also facilitate the shift from negative to positive emotions, positively affecting emotional regulation. In contrast, visual enclosure (VE), vehicle view factor (VVF), and person view factor (PVF) are associated with negative emotional arousal, adversely affecting emotional valence. Moreover, the impact of specific visual environmental elements on different emotional states may vary. This study introduces a novel, multidisciplinary approach to accurately quantify the relationship between the environment and emotions, providing significant theoretical and practical insights for the development of healthier cities.
Study on the Effect of Cracking Parameters on the Migration Characteristics of Chloride Ions in Cracked Concrete
Authors: Huang Tao , Feng Shuang , Wang Mengge , Peng Zhongqi
Published: June 2024

In engineering, concrete often develops cracks due to various reasons, which accelerate the erosion rate of chloride ions in concrete and consequently expedite the degradation of the mechanical properties of concrete structures. This study simplifies the four-phase model into a two-phase model using homogenization methods. Based on this, numerical simulations are employed to investigate the influences of dimensionless structural parameters and material parameters of cracks on the equivalent diffusion coefficient of cracked concrete, and a theoretical model for the equivalent diffusion coefficient of cracked concrete is established according to Fick’s diffusion law. The research findings indicate that when cracks are positioned in the middle of the boundary through which chloride ions enter and exit the concrete, and the direction of the cracks is parallel to the diffusion direction of chloride ions; this scenario is the most detrimental to the durability of concrete. For n cracks (n ≥ 2), when they are parallel to the x-axis and symmetrical about the x-axis, and the spacing between cracks equals 1/n times the width of the concrete, this scenario is the most detrimental to the durability of concrete containing multiple cracks. Whether for a single crack or multiple cracks, when they are in the most unfavorable condition, the “parallel-then-series” theoretical model can accurately predict the equivalent diffusion coefficient of cracked concrete.
Seismic Performance of Wall-Type Concrete-Filled Steel Tubular Column to H-Beam Connections with Internal Diaphragms
Authors: Liu Hanchao , Lei Honggang , Huang Yuqi , Chen Yongchang , Xu Feng
Published: June 2024

This study introduces a new internal diaphragm joint to connect steel beams with wall-type concrete-filled steel tubular (WCFST) columns. This study combines experimental research with numerical simulations for analysis. Firstly, one full-scale test specimen was designed and subjected to cyclic loading. The obtained failure mode and hysteresis curves illustrate that the joint specimens exhibit ample energy dissipation capacities. Subsequently, a reliable FE model was obtained based on experimental verification, and parametric analysis was conducted. The findings indicate that axial compression ratios critically affect the load-carrying capacity and displacement at failure, with a 2% reduction in capacity for each 0.1 increment in the ratio. The thicknesses of the column web and flange in the joint area are recommended to be 0.85 to 1.2 times and 1 to 1.2 times the beam flange thickness, respectively. The length of the internal diaphragm is advised to be between 0.2 and 0.3 times the width of the cross-section. Overall, these results significantly enrich our understanding of WCFST systems and will inform future design and construction best practices.
Implementing All-Weather Photocatalysis of Exhaust Fumes Based on the g-C3N4/TiO2/SrAl2O4: Eu2+, Dy3+ Ternary Composite Coating
Authors: Zhou Bochao , Li Hailong , Cui Ao , Wang Di , Guo Fucheng , Wang Chao
Published: June 2024

This study examines the use of SrAl2O4: Eu2+, Dy3+ long-afterglow materials doped into g-C3N4/TiO2 coatings for photodegradation. The prepared sample was tested for the purification of automotive exhaust fumes, with the optimal mass ratio of g-C3N4/TiO2 and SrAl2O4: Eu2+, Dy3+ determined to be 1:1. Characterization tests, including XRD, FT-IR, XPS, and TG-DSC, were conducted to evaluate the microstructure and properties of the samples. Under poor lighting conditions, g-C3N4/TiO2 reduced CH and NOx by 59 ppm and 13 ppm within 4 h, respectively, while g-C3N4/TiO2/SrAl2O4: Eu2+, Dy3+ decreased CH and NOx by 98ppm and 34ppm, respectively, resulting in a significant improvement in degradation efficiency. The addition of long-afterglow materials significantly improves the efficiency of photocatalysts in purifying exhaust fumes in low-light environments, providing potential value for all-weather exhaust treatment in the future.
Mullite 3D Printed Humidity Sensors
Authors: Milovanov Yurii , Bertero Arianna , Coppola Bartolomeo , Palmero Paola , Tulliani Jean-Marc
Published: June 2024

Mullite substrates with two different porosities were 3D printed, and tested as humidity sensors. To evaluate the effects of porosity on humidity sensitivity, the samples were sintered at 1400 °C (Sensor 1) and 1450 °C (Sensor 2). The sensors were tested in a range from 0% to 85% relative humidity (RH) at room temperature. When exposed to water vapor at room temperature, the impedance value dropped down from 155 MΩ under dry air to 480 kΩ under 85 RH% for Sensor 1 and from 115 MΩ under dry air to 410 kΩ for Sensor 2. In addition, response time and recovery time were below 2 min, whatever the firing temperature, when RH changed from 0% to 74%. Finally, tests carried out involving ammonia, methane, carbon dioxide and nitrogenous oxide, as well as ethanol and acetone, showed no interference.
Upcycled Graphene Oxide Nanosheets for Reversible Room Temperature NO2 Gas Sensor
Authors: Trinh Vien , Xu Kai , Yu Hao , Ha Nam , Hu Yihong , Khan Muhammad Waqas , Ou Rui , Luan Yange , Zhang Jiaru , Ma Qijie , Ren Guanghui , Ou Jian Zhen
Published: June 2024

Graphene oxide (GO) nanosheets, as one of the most studied graphene derivatives, have demonstrated an intrinsically strong physisorption-based gas–matter behavior, owing to its enhanced volume–surface ratio and abundant surface functional groups. The exploration of efficient and cost-effective synthesis methods for GO is an ongoing task. In this work, we explored a novel approach to upcycle inexpensive polyethylene terephthalate (PET) plastic waste into high-quality GO using a combination of chemical and thermal treatments based on a montmorillonite template. The obtained material had a nanosheet morphology with a lateral dimension of around ~2 µm and a thickness of ~3 nm. In addition, the GO nanosheets were found to be a p-type semiconductor with a bandgap of 2.41 eV and was subsequently realized as a gas sensor. As a result, the GO sensor exhibited a fully reversible sensing response towards ultra-low-concentration NO2 gas with a limit of detection of ~1.43 ppb, without the implementation of an external excitation stimulus including elevating the operating temperature or bias voltages. When given a thorough test, the sensor maintained an impressive long-term stability and repeatability with little performance degradation after 5 days of experiments. The response factor was estimated to be ~11% when exposed to 1026 ppb NO2, which is at least one order of magnitude higher than that of other commonly seen gas species including CH4, H2, and CO2.
Extending the Shelf-Life of Nectarines through Fish Gelatin/Cellulose Nanocrystals/Cinnamon Essential Oil-Based Edible Coatings
Authors: Akbari Reza , Tarighi Javad , Razavi Mahsa Sadat , Tahmasebi Mohammad , Carullo Daniele , Farris Stefano
Published: June 2024

The effect of bacterial cellulose nanocrystal–fish gelatin/cinnamon essential oil (BCNCs–FGelA/CEO) nanocoatings containing different concentrations of essential oil (1.2, 1.8, and 2.4 mL/L) on reducing the ripening and aging processes of ‘Red Gold’ nectarine fruit during cold storage (60 days, 4 °C) was studied. As a general trend, the application of the coating delayed the ripening process, and increasing the concentration of essential oil was effective in improving the coating efficacy. After 60 days, the lowest values of weight loss (6.93%), peroxidase and polyphenol oxidase activity (11.49 and 0.48 abs min−1 g−1, respectively), soluble solid content (14.56%), and pH (4.17) were detected for samples covered with the BCNCs–FGelA coatings containing the highest tested CEO concentration, whereas the maximum values of the same parameters (20.68%, 18.74 and 0.76 abs min−1 g−1, 17.93%, and 4.39, respectively) were found in the uncoated samples. In addition, increasing the concentration of the essential oil resulted in a better preservation of the firmness, ascorbic acid, and total acidity of the samples. Finally, the respiration rate and ethylene production of coated samples were lower than those detected in uncoated samples, though some differences arose depending on the amount of CEO loaded in the coatings. This study showed the capability of BCNCs–FGelA/CEO coatings to increase the cold storage period and preserve the quality of ‘Red Gold’ nectarine fruit, thereby reducing losses and increasing economic efficiency in the fruit industry.
Revealing the Microstructure Evolution and Mechanical Properties of Al2O3-Reinforced FCC-CoCrFeMnNi Matrix Composites Fabricated via Gas Atomization and Spark Plasma Sintering
Authors: Dai Pan , Chen Runjie , Luo Xian , Yang Lin , Wen Lei , Tu Tao , Wang Chen , Zhao Wenwen , Lv Xianghong
Published: June 2024

In the present work, novel Al2O3 particles were used to reinforce heterogeneous CoCrFeMnNi high-entropy alloy (HEA) matrix composites with nano- (5.0 wt.%) and nano- + micro- (5.0 wt.% + 10.0 wt.%) specimens. Al2O3 particles were fabricated via gas atomization and spark plasma sintering. The microstructure evolution and properties, i.e., density, hardness, and room temperature compression, were systematically investigated. The results indicate that the concentration of the Cr element in the pure CoCrFeMnNi HEA and the HEA matrix composite can be effectively reduced by using a gas-atomized HEA powder as the matrix. The formation of an impurity phase can also be inhibited, while the distribution uniformity of matrix elements can be improved. The composites prepared via gas-atomized powders formed a network microstructure composed of continuous Al2O3-rich regions and isolated Al2O3-poor regions, exhibiting good plasticity and improved density. The relative densities of the pure HEA, nano- (5.0 wt.%), and nano- + micro- (5.0 wt.% + 10.0 wt.%) composites were 98.9%, 97%, and 94.1%, respectively. The results demonstrate a significant improvement in the relative densities compared to the values (97.2%, 95.7%, and 93.8%) of the composites prepared via mechanical alloying. In addition, compared to the compressive fracture strains of nano- (5.0 wt.%) and nano- + micro- (5.0 wt.% + 10.0 wt.%) composites based on the mechanically alloyed HEA powder, the values of the nano- (5.0 wt.%) and nano- + micro- (5.0 wt.% + 10.0 wt.%) specimens prepared via gas atomization and spark plasma sintering increased by 80% and 67%, respectively.
A Clustering and PL/SQL-Based Method for Assessing MLP-Kmeans Modeling
Authors: Silva-Blancas Victor Hugo , Jiménez-Hernández Hugo , Herrera-Navarro Ana Marcela , Álvarez-Alvarado José M. , Córdova-Esparza Diana Margarita , Rodríguez-Reséndiz Juvenal
Published: June 2024

With new high-performance server technology in data centers and bunkers, optimizing search engines to process time and resource consumption efficiently is necessary. The database query system, upheld by the standard SQL language, has maintained the same functional design since the advent of PL/SQL. This situation is caused by recent research focused on computer resource management, encryption, and security rather than improving data mining based on AI tools, machine learning (ML), and artificial neural networks (ANNs). This work presents a projected methodology integrating a multilayer perceptron (MLP) with Kmeans. This methodology is compared with traditional PL/SQL tools and aims to improve the database response time while outlining future advantages for ML and Kmeans in data processing. We propose a new corollary: hk→H=SSE(C),wherek>0and∃X, executed on application software querying data collections with more than 306 thousand records. This study produced a comparative table between PL/SQL and MLP-Kmeans based on three hypotheses: line query, group query, and total query. The results show that line query increased to 9 ms, group query increased from 88 to 2460 ms, and total query from 13 to 279 ms. Testing one methodology against the other not only shows the incremental fatigue and time consumption that training brings to database query but also that the complexity of the use of a neural network is capable of producing more precision results than the simple use of PL/SQL instructions, and this will be more important in the future for domain-specific problems.
On Predicting Exam Performance Using Version Control Systems’ Features
Authors: Canale Lorenzo , Cagliero Luca , Farinetti Laura , Torchiano Marco
Published: June 2024

The advent of Version Control Systems (VCS) in computer science education has significantly improved the learning experience. The Learning Analytics community has started to analyze the interactions between students and VCSs to evaluate the behavioral and cognitive aspects of the learning process. Within the aforesaid scope, a promising research direction is the use of Artificial Intelligence (AI) to predict students’ exam outcomes early based on VCS usage data. Previous AI-based solutions have two main drawbacks: (i) They rely on static models, which disregard temporal changes in the student–VCS interactions. (ii) AI reasoning is not transparent to end-users. This paper proposes a time-dependent approach to early predict student performance from VCS data. It applies and compares different classification models trained at various course stages. To gain insights into exam performance predictions it combines classification with explainable AI techniques. It visualizes the explanations of the time-varying performance predictors. The results of a real case study show that the effect of VCS-based features on the exam success rate is relevant much earlier than the end of the course, whereas the timely submission of the first lab assignment is a reliable predictor of the exam grade.
Deepening Divides or Inciting Change? Ongoing Impacts of COVID-19 on Teaching and Teacher Education in the United States
Authors: Borrero Noah
Published: June 2024

Through the lenses of teaching and teacher education, this article explores the evolving impacts of the COVID-19 pandemic on education. Challenges associated with COVID-19 in schooling, learning, teaching, and teacher education are highlighted to showcase ongoing systemic inadequacies and emerging opportunities for change. Cultural assets are presented as a theoretical framework for bridging gaps between individualistic and collective approaches to learning. Specific classroom projects that foster cultural assets are connected with a larger educational movement for Ethnic Studies in public education in the United States to provide examples of ways that education can evolve in more equitable ways into the future.
Segmentation and Multi-Timepoint Tracking of 3D Cancer Organoids from Optical Coherence Tomography Images Using Deep Neural Networks
Authors: Branciforti Francesco , Salvi Massimo , D’Agostino Filippo , Marzola Francesco , Cornacchia Sara , De Titta Maria Olimpia , Mastronuzzi Girolamo , Meloni Isotta , Moschetta Miriam , Porciani Niccolò , Sciscenti Fabrizio , Spertini Alessandro , Spilla Andrea , Zagaria Ilenia , Deloria Abigail J. , Deng Shiyu , Haindl Richard , Szakacs Gergely , Csiszar Agnes , Liu Mengyang , Drexler Wolfgang , Molinari Filippo , Meiburger Kristen M.
Published: June 2024

Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively monitor organoid growth. Optical coherence tomography (OCT) is a promising imaging modality for organoid analysis due to its high-resolution, label-free, non-destructive, and real-time 3D imaging capabilities, but accurately identifying and quantifying organoids in OCT images remain challenging due to various factors. Here, we propose an automatic deep learning-based pipeline with convolutional neural networks that synergistically includes optimized preprocessing steps, the implementation of a state-of-the-art deep learning model, and ad-hoc postprocessing methods, showcasing good generalizability and tracking capabilities over an extended period of 13 days. The proposed tracking algorithm thoroughly documents organoid evolution, utilizing reference volumes, a dual branch analysis, key attribute evaluation, and probability scoring for match identification. The proposed comprehensive approach enables the accurate tracking of organoid growth and morphological changes over time, advancing organoid analysis and serving as a solid foundation for future studies for drug screening and tumor drug sensitivity detection based on organoids.
Elastography of the Male Pelvic Region—Perspectives on Malignant Lesions
Authors: Santos Rute , Loft Martina Kastrup , Pedersen Malene Roland Vils
Published: June 2024

Ultrasound elastography is widely used to assess tissue stiffness for lesion characterization, including differentiation between benign and malignant lesions. This study focuses on the use of elastography in the male pelvis, including the prostate, testicles, and rectum, by comparing elastography types (shear wave and strain). This article provides a summary of the existing literature on the use of elastography in the male pelvic region and outlines the clinical perspective. Ultrasound elastography is a good technique for evaluating and monitoring lesions in the male pelvic region.
Macular OCT’s Proficiency in Identifying Retrochiasmal Visual Pathway Lesions in Multiple Sclerosis—A Pilot Study
Authors: Cujbă Larisa , Banc Ana , Stan Cristina , Drugan Tudor , Nicula Cristina
Published: June 2024

Optical coherence tomography (OCT) is a non-invasive imaging technique based on the principle of low-coherence interferometry that captures detailed images of ocular structures. Multiple sclerosis (MS) is a neurodegenerative disease that can lead to damage of the optic nerve and retina, which can be depicted by OCT. The purpose of this pilot study is to determine whether macular OCT can be used as a biomarker in the detection of retrochiasmal lesions of the visual pathway in MS patients. We conducted a prospective study in which we included 52 MS patients and 27 healthy controls. All participants underwent brain MRI, visual field testing, and OCT evaluation of the thicknesses of the peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell layer (GCL), and macular inner plexiform layer (IPL). OCT measurements were adjusted for optic neuritis (ON). VF demonstrated poor capability to depict a retrochiasmal lesion identified by brain MRI (PPV 0.50). In conclusion, the OCT analysis of the macula appears to excel in identifying retrochiasmal MS lesions compared to VF changes. The alterations in the GCL and IPL demonstrate the most accurate detection of retrochiasmal visual pathway changes in MS patients.
Simultaneous Optimization and Integration of Multiple Process Heat Cascade and Site Utility Selection for the Design of a New Generation of Sugarcane Biorefinery
Authors: Garcia Victor Fernandes , Ensinas Adriano Viana
Published: June 2024

Biorefinery plays a crucial role in the decarbonization of the current economic model, but its high investments and costs make its products less competitive. Identifying the best technological route to maximize operational synergies is crucial for its viability. This study presents a new superstructure model based on mixed integer linear programming to identify an ideal biorefinery configuration. The proposed formulation considers the selection and process scale adjustment, utility selection, and heat integration by heat cascade integration from different processes. The formulation is tested by a study where the impact of new technologies on energy efficiency and the total annualized cost of a sugarcane biorefinery is evaluated. As a result, the energy efficiency of biorefinery increased from 50.25% to 74.5% with methanol production through bagasse gasification, mainly due to its high heat availability that can be transferred to the distillery, which made it possible to shift the bagasse flow from the cogeneration to gasification process. Additionally, the production of DME yields outcomes comparable to methanol production. However, CO2 hydrogenation negatively impacts profitability and energy efficiency due to the significant consumption and electricity cost. Nonetheless, it is advantageous for surface power density as it increases biofuel production without expanding the biomass area.
Guided Drawing with Preschool Dual Language Learners in Head Start: Building Science Vocabulary and Content Knowledge
Authors: Cassano Christina M. , Paciga Kathleen A.
Published: June 2024

Drawing offers a way for young children to demonstrate what they understand about the world. This study reports on the findings from an eight-week intervention program called guided drawing designed to build vocabulary and content knowledge for dual language learners in Head Start settings. Four researcher-designed assessment measures were used to assess thirteen preschoolers’ vocabulary and concept knowledge at the receptive, expressive, and definitional levels in a pre/post-intervention design. Analysis of researcher-designed measures reveals positive changes in all vocabulary and concept knowledge areas targeted by the intervention. Thematic analysis of researcher–child interactions and drawing products indicates the guided drawing intervention provided opportunities and context for every participating child to explore new content and concepts related to science learning; reveal what they know; grow knowledge and vocabulary; reveal misunderstandings; and overhear and adopt new language.
Textile Antenna with Dual Bands and SAR Measurements for Wearable Communication
Authors: Abdelghany Mahmoud A. , Ahmed Mohamed I. , Ibrahim Ahmed A. , Desai Arpan , Ahmed Mai. F.
Published: June 2024

A novel dual-wideband textile antenna designed for wearable applications is introduced in this study. Embedding antennas into wearable devices requires a detailed analysis of the specific absorption rate (SAR) to ensure safety. To achieve this, SAR values were meticulously simulated and evaluated within a human voxel model, considering various body regions such as the left/right head and the abdominal region. The proposed antenna is a monopole design utilizing denim textile as the substrate material. The characterization of the denim textile substrate is carried out using two different methods. The first analysis included a DAC (Dielectric Assessment Kit), while a ring resonator technique was employed for the second examination. Operating within the frequency bands of (58.06%) 2.2–4 GHz and (61.43) 5.3–10 GHz, the antenna demonstrated flexibility in its dual-wideband capabilities. Extensive simulations and tests were conducted to assess the performance of the antenna in both flat and bent configurations. The SAR results obtained from these tests indicate that the antenna complies with safety standard limits when integrated with the human voxel model. This validation underscores the potential of the proposed antenna for seamless integration into wearable applications, offering a promising solution for future developments in this domain.
Digital Twins in Industry 4.0
Authors: Park Sangchan , Maliphol Sira , Woo Jiyoung , Fan Liu
Published: June 2024

Since Grieves [...]
Exploring Android Obfuscators and Deobfuscators: An Empirical Investigation
Authors: Ebad Shouki A. , Darem Abdulbasit A.
Published: June 2024

Researchers have proposed different obfuscation transformations supported by numerous smartphone protection tools (obfuscators and deobfuscators). However, there is a need for a comprehensive study to empirically characterize these tools that belong to different categories of transformations. We propose a property-based framework to systematically classify twenty cutting-edge tools according to their features, analysis type, programming language support, licensing, applied obfuscation transformations, and general technical drawbacks. Our analysis predominantly reveals that very few tools work at the dynamic level, and most tools (which are static-based) work for Java or Java-based ecosystems (e.g., Android). The findings also show that the widespread adoption of renaming transformations is followed by formatting and code injection. In addition, this paper pinpoints the technical shortcomings of each tool; some of these drawbacks are common in static-based analyzers (e.g., resource consumption), and other drawbacks have negative effects on the experiment conducted by students (e.g., a third-party library involved). According to these critical limitations, we provide some timely recommendations for further research. This study can assist not only Android developers and researchers to improve the overall health of their apps but also the managers of computer science and cybersecurity academic programs to embed suitable obfuscation tools in their curricula.
Integration of Renewable Energy Technologies for Sustainable Development in South Africa: A Focus on Grid-Connected PV Systems
Authors: Kumba Hagreaves , Olanrewaju Oludolapo A. , Pasipamire Ratidzo
Published: June 2024

Energy is essential for crucial development in Africa. The current electricity shortages and load shedding in South Africa show that the country faces significant challenges in reaching positive economic growth. For industries to operate sustainably, an innovative mechanism must be tailored to solve the negative impacts of industrial energy use, particularly climate change. This study aims to show how renewable energy technologies can provide new economic opportunities, contribute to higher standards of living, and reduce the impacts of society on ecosystems, among other things. This paper presents a feasibility analysis and optimization of new energy technologies by designing and simulating a grid-connected PV system for sustainable development. PV Syst software (PV Syst 6.8.8) was used to simulate and optimize the PV system. The software was employed to design and model the PV systems, calculating energy production, economic performance, and environmental impact. Using simulation data, the researchers compared PV system performance across three scenarios and identified the optimal system. Scenario A was chosen as the best system, with an energy production of 1720 MWh/year. Overall, the findings of this study suggest that grid-connected PV systems are a feasible and sustainable option for meeting South Africa’s energy needs. By implementing the results and recommendations, the government, investors, and community can work together to develop and deploy a successful PV system that will benefit all.
Evaluation of Different Methodologies for Wave Energy Conversion Systems Integration into the Power Grid Using Power Hardware-in-Loop Emulation
Authors: Vujkov Barbara , Dragić Mile , Žnidarec Matej , Popadić Bane , Šljivac Damir , Dumnić Boris
Published: June 2024

The ocean energy resources hold the promise of a sustainable solution within global efforts to diversify energy sources and mitigate climate change. Wave energy conversion (WEC) systems, as emerging technologies, offer adaptability and the potential to harness predictable wave energy. However, integration of WEC systems into a power grid brings challenges for system operators due to their nature of operation. Addressing these demands is a multilayered process that involves highly efficient power electronic devices, control systems, and efficient energy storage solutions. This paper specifically focuses on the methodologies of the grid integration of a specific wave energy conversion system—a point absorber developed by the company Sigma Energy. Proposed methodologies are experimentally tested using power hardware-in-loop (PHIL) emulation of a fully monitored and controlled small-scale microgrid equipped with a battery energy storage system (BESS), different emulators of loads, and distributed generators (DG).
A Modified Variable Power Angle Control for Unified Power Quality Conditioner in a Distorted Utility Source
Authors: Chaiyaphun Krittapas , Santiprapan Phonsit , Areerak Kongpol
Published: June 2024

The distorted supply voltage degrades the control performance of a unified power quality conditioner (UPQC). This problem causes incorrect calculations in the harmonic identification and reference signal generation processes. This paper proposes a modified harmonic identification of the UPQC. The reference compensating current calculation for the shunt active power filter (shunt APF) is developed using the sliding window with the Fourier analysis (SWFA) method. In addition, the variable power angle control (PAC) is applied to operate the reference signal generation of the series APF and the shunt APF of the UPQC. Under the distorted voltage and nonlinear load conditions, the proposed approach can provide accurate reference compensating signals and successfully share the load reactive power compensation between the shunt APF and the series APF. In this work, a three-phase, three-wire power system with linear and nonlinear loads was implemented. The proposed method was validated using the processor-in-the-loop technique on an eZdsp™ F28335 board and the MATLAB/Simulink program. The testing results indicated that SWFA has excellent filtering performance and enhances harmonic identification compared to the operation without any filter or with low pass filters (LPF). With the proposed approach, the percentage of total harmonic distortion of voltage and current could be maintained within the IEEE519-2022 standard, and the magnitude of the RMS voltage across the load was in the recommended range specified by ANSI C84.1-2016.
A Two-Stage Twisted Blade μ-Vertical Axis Wind Turbine: An Enhanced Savonius Rotor Design
Authors: Pérez-Terrazo Andrés , Moreno Martin , Trejo-Zúñiga Iván , López José Alberto
Published: June 2024

Wind turbines are a solution for sustainable energy, significantly reducing carbon emissions and fostering a circular economy for more cost-effective and cleaner power generation, in line with worldwide environmental aspirations. In this context, this research aims to explore a novel two-stage, twisted-blade micro-Vertical-Axis Wind Turbine (μ-VAWT)alternative inspired by the Savonius Rotor (SR). This investigation utilizes the κ−ω SST turbulence model to explore the power coefficient (CP) and torque coefficient (CT), finding CP values ranging from 0.02 to 0.08 across the turbine by altering the free stream velocity (V). CT analysis further delves into four specific sections, highlighting areas of particular interest. These results are validated by examining velocity contours, pressure contours, and streamlines in four horizontal sections, demonstrating that the proposed turbine model exhibits minimal torque fluctuation. Moreover, the analysis of vertical wind streamlines illustrates very low interference with various wind turbine proposals, underscoring the turbine’s efficiency and potential for integration into diverse wind energy projects.
Advancing Industrial Process Electrification and Heat Pump Integration with New Exergy Pinch Analysis Targeting Techniques
Authors: Walmsley Timothy Gordon , Lincoln Benjamin James , Padullés Roger , Cleland Donald John
Published: June 2024

The process integration and electrification concept has significant potential to support the industrial transition to low- and net-zero-carbon process heating. This increasingly essential concept requires an expanded set of process analysis tools to fully comprehend the interplay of heat recovery and process electrification (e.g., heat pumping). In this paper, new Exergy Pinch Analysis tools and methods are proposed that can set lower bound work targets by acutely balancing process heat recovery and heat pumping. As part of the analysis, net energy and exergy load curves enable visualization of energy and exergy surpluses and deficits. As extensions to the grand composite curve in conventional Pinch Analysis, these curves enable examination of different pocket-cutting strategies, revealing their distinct impacts on heat, exergy, and work targets. Demonstrated via case studies on a spray dryer and an evaporator, the exergy analysis targets net shaft-work correctly. In the evaporator case study, the analysis points to the heat recovery pockets playing an essential role in reducing the work target by 25.7%. The findings offer substantial potential for improved industrial energy management, providing a robust framework for engineers to enhance industrial process and energy sustainability.
Trace Elements in Maize Biomass Used to Phyto-Stabilise Iron-Contaminated Soils for Energy Production
Authors: Wyszkowski Mirosław , Kordala Natalia
Published: June 2024

The aim of the study was to determine the feasibility of using maize biomass for the phyto-stabilisation of iron-contaminated soils under conditions involving the application of humic acids (HAs). The biomass yield content of maize trace elements was analysed. In the absence of HAs, the first dose of Fe-stimulated plant biomass growth was compared to the absence of Fe contamination. The highest soil Fe contamination resulted in a very large reduction in maize biomass yield, with a maximum of 93%. The addition of HAs had a positive effect on plant biomass, with a maximum of 53%, and reduced the negative effect of Fe. There was an almost linear increase in maize biomass yield with increasing doses of HAs. Analogous changes were observed in dry matter content in maize. Soil treatment with Fe caused a significant increase in its content in maize biomass, with a maximum increase of three times in the series without HAs. There was also a decrease in Co, Cr and Cd content (by 17%, 21% and 44%, respectively) and an increase in Cu, Ni, Pb, Zn and Mn accumulation (by 32%, 63%, 75%, 97% and 203%, respectively). The application of HAs to the soil reduced the content of this trace element and its growth in the biomass of this plant under the influence of Fe contamination. They had a similar effect on other trace elements contained in the maize biomass. HAs contributed to a decrease in the level of most of the tested trace elements (except Ni and Pb) in the maize biomass. The reduction ranged from 11% (Cr and Mn) to 72% (Cd). The accumulation of Ni and Pb in the maize biomass was higher in the objects with HAs application than in the series without their addition. Humic acid application is a promising method for the reduction of the effects of soil Fe contamination on plants.
A Dynamic Tanks-in-Series Model for a High-Temperature PEM Fuel Cell
Authors: Danilov Valery A. , Kolb Gunther , Cremers Carsten
Published: June 2024

A dynamic tanks-in-series model has been developed for the coupled heat, mass, and charge transfer processes in a high-temperature proton exchange membrane fuel cell. The semi-empirical model includes the heat and mass balance equations in the gas channels and the membrane electrode assembly together with the charge balance at the electrode/membrane interfaces. The outputs of the tanks-in-series model are the concentration, the temperature, and the current density with a step change from tank to tank. The dynamic non-isothermal model is capable of predicting both the transient and steady-state behavior of the fuel cell and reproducing impedance data under harmonic perturbations of the cell potential together with a comprehensive interpretation of experimental data.