bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Improvement of Dye-Sensitized Solar Cells with Pressed TiO2 Nanoparticles Layer
Authors: Wu Tian-Chiuan , Huang Wei-Ming , Meen Teen-Hang , Tsai Jenn-Kai
Published: May 2023

A simple and low-cost fabrication method of dye-sensitized solar cells (DSSCs) was developed to improve the structure and performance of the photoanode with the pressed layer and compact TiO2 thin film using spin coating, screen printing, and mechanical compression. In this study, four different TiO2 layers were adopted to fabricate photoanodes: a mesoporous TiO2 nanoparticles (NPs) layer, a pressed TiO2 NPs layer, a mesoporous TiO2 NPs layer on the TiO2 compact thin film, and a pressed TiO2 NPs layer on the TiO2 compact thin film. The compact thin film was deposited on the fluorine-doped tin oxide (FTO) glass via spin coating, while the mesoporous TiO2 NPs layer was deposited via the screen-printing method. The pressed TiO2 NPs layer was produced by compressing the mesoporous TiO2 NPs layer with a hydraulic press machine. When using the pressed TiO2 NPs layer for the photoanode of DSSC, the power conversion efficiency of DSSC was enhanced the most. The electron lifetime for DSSC with photoanodes based on the pressed TiO2 NPs and mesoporous TiO2 NPs layers were 8.217 and 6.287 ms, respectively. The power conversion efficiency of DSSC with photoanodes based on the pressed TiO2 NPs layer was 5.4%, while that based on the mesoporous TiO2 NPs layer was 4.08%. DSSC with photoanodes based on the pressed TiO2 NPs layer showed a significant increase in the power conversion efficiency by 36.16% compared to that based on the mesoporous TiO2 NPs layer.
Application of Plant Waxes in Edible Coatings
Authors: Pashova Sabka
Published: May 2023

The aim of the paper is to present edible coatings based on lipids and their application in the food industry. Therefore, this paper discusses the following: different types of plant waxes; the need for plant waxes; the advantages and disadvantages of edible coatings based on plant waxes; edible coatings based on lipids applied in the food industry; application of the most popular Carnauba wax; Candelilla Wax in the composition of edible coatings. Plant waxes are presented with their specific characteristics. Moreover, the cuticle waxes obtained from waste peels of fresh fruits and vegetables are presented; their properties and application in the composition of edible coatings are based on plant waxes. In this regard, an effective and applicable method for the industrial extraction/separation of plant wax from the cuticle and waste peels of fresh fruits and vegetables before their processing (production of wine, high-alcohol beverages, fruit-sugar preserves, vegetable preserves, juices, etc.) is proposed. Properties and possible applications of the isolated cuticle plant waxes are presented.
EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications
Authors: Duy Tan Nguyen , Nguyen Duy-Ngoc , Hoang Hong-Nhat , Le Thi-Thu-Huong
Published: May 2023

The Internet of Things (IoT) integrates different advanced technologies in which a wireless sensor network (WSN) with many smart micro-sensor nodes is an important portion of building various IoT applications such as smart agriculture systems, smart healthcare systems, smart home or monitoring environments, etc. However, the limited energy resources of sensors and the harsh properties of the WSN deployment environment make routing a challenging task. To defeat this routing quandary, an energy-efficient routing protocol based on grid cells (EEGT) is proposed in this study to improve the lifespan of WSN-based IoT applications. In EEGT, the whole network region is separated into virtual grid cells (clusters) at which the number of sensor nodes is balanced among cells. Then, a cluster head node (CHN) is chosen according to the residual energy and the distance between the sink and nodes in each cell. Moreover, to determine the paths for data delivery inside the cell with small energy utilization, the Kruskal algorithm is applied to connect nodes in each cell and their CHN into a minimum spanning tree (MST). Further, the ant colony algorithm is also used to find the paths of transmitting data packets from CHNs to the sink (outside cell) to reduce energy utilization. The simulation results show that the performance of EEGT is better than the three existing protocols, which are LEACH-C (low energy adaptive clustering hierarchy), PEGASIS (power-efficient gathering in sensor information systems), and PEGCP (maximizing WSN life using power-efficient grid-chain routing protocol) in terms of improved energy efficiency and extended the lifespan of the network.
Schiff-Based Modified Bentonite Clay Composites for Wastewater Treatment: Experimental and DFT-Based Analysis
Authors: Mutahir Sadaf , Yaqoob Fakhira , Khan Muhammad Asim , Alsuhaibani Amnah Mohammed , Abouzied Amr S. , Refat Moamen S. , Huwaimel Bader
Published: May 2023

A new bentonite clay composite was synthesized by modifying bentonite clay and Schiff base (SB). The purpose of the composite was to eliminate methylene blue (MB) from wastewater. To characterize its efficacy, several spectroscopic techniques (UV-Visible spectroscopy, FTIR, SEM, and XRD) were used. The interactions between the adsorbent dose, pH, initial dye concentration, and contact duration were also tested to evaluate the adsorption capacity of the adsorbent. The results demonstrated that changes in the modification led to a considerable increase in adsorption capacity, with a maximum monolayer adsorption capacity of 258 mg/g being achieved at pH 11. Based on the batch experiments, molecular dynamics simulations, and DFT studies, the pseudo-second-order model described the sorption of MB on the bentonite clay composite the best. It was found that the adsorption of MB on the bentonite clay composite primarily followed a monolayer adsorption mechanism. Using the Langmuir isotherm model, the experimental results were consistent, indicating the monolayer adsorption mechanism. Finally, this study demonstrated that the bentonite-SB adsorbent had enormous promise for the elimination of methylene blue (MB) from wastewaters, as evidenced by the electron density mapping within the molecular electrostatic potential plot and the electrostatic potential graphing within the iso-surface plot.
Feeding Behaviour of the Mite Blattisocius mali on Eggs of the Fruit Flies Drosophila melanogaster and D. hydei
Authors: Michalska Katarzyna , Mrowińska Agnieszka , Studnicki Marcin , Jena Manoj Kumar
Published: May 2023

Many predatory mites use insects for dispersal; however, their possible negative effects on insect hosts during transportation and on insect offspring while preying in the hosts’ habitats are still poorly understood. A recent study has revealed that the predatory mite Blattisocius mali can not only spread by means of drosophilid fruit flies but also feed on their bodies during dispersal. The aim of this study was to examine the capability of B. mali to prey upon the eggs of their fruit fly hosts and determine the effect of the egg’s age on the voracity of this predator. Drosophila melanogaster oviposited on agar media for 1 h and D. hydei for 8 or 16 h. During 10-h experiments with fifteen fly eggs per cage, a single female predator totally consumed on average 3.62 ± 0.673 “1-h” D. melanogaster eggs and 3.00 ± 0.612 “8-h” eggs of D. hydei, while it partially consumed 2.75 ± 0.586 and 3.00 ± 0.612 eggs of each fly species. In the experiments involving D. hydei, the predator totally destroyed a similar number of “8-h” and “16-h” eggs, but it partially consumed significantly more younger eggs than older eggs. Ethological observations showed that mites returned to some partially fed eggs, usually from the side where the first puncture was made, and only then did they consume them whole.
Cross-Landscape Approaches to Human Wildlife Conflicts—Naïve or Necessary?
Authors: Göttert Thomas
Published: May 2023

When I was approached to edit a Special Issue (SI) on “Human wildlife conflicts across landscapes”, I was particularly interested in the unprejudiced, not to say near-naïve approach to the subject [...]
Effects of Biotic and Abiotic Factors on the Spatiotemporal Distribution of Round Scad (Decapterus maruadsi) in the Hainan Island Offshore Area
Authors: Wang Liangming , Yang Changping , Liu Yan , Shan Binbin , Ma Shengwei , Sun Dianrong
Published: May 2023

Fishery resource and environmental data from four surveys conducted in the Hainan Island offshore area from March 2021 to June 2022 were used to investigate the spatiotemporal distribution of round scad (Decapterus maruadsi). A generalized additive model was applied to explore the relationships among abundance and distribution, also biotic and abiotic factors (i.e., temperature, salinity, chlorophyll-a concentration, water depth, phytoplankton abundance, zooplankton abundance, and jack mackerel (Trachurus japonicas) abundance). Round scad abundance (average 67.17 kg/km2) showed distinct spatial and seasonal differences around Hainan Island, with highest abundance in summer (171.72 kg/km2) and lowest abundance in spring (3.06 kg/km2). The optimal model revealed that jack mackerel abundance, sea bottom temperature, sea surface temperature, and latitude very significantly (p < 0.01) affected round scad distribution. Jack mackerel abundance (mainly in the range 0–50 kg/km2) was positively correlated with round scad distribution. The distribution showed a dome-shaped relationship with bottom water temperature in the range 18–30 °C, with maximum abundance at 24 °C. The distribution was negatively correlated with surface water temperature in the range 22–30 °C. Sea surface chlorophyll-a concentration and longitude were significantly correlated (p < 0.05) with round scad distribution. The results provide theoretical support to further investigate the formation mechanism of round scad fishing grounds and to enrich knowledge of pelagic fish abundance in the continental-shelf waters of the northern South China Sea.
Automatic Classification of Colour Fundus Images for Prediction Eye Disease Types Based on Hybrid Features
Authors: Shamsan Ahlam , Senan Ebrahim Mohammed , Shatnawi Hamzeh Salameh Ahmad
Published: May 2023

Early detection of eye diseases is the only solution to receive timely treatment and prevent blindness. Colour fundus photography (CFP) is an effective fundus examination technique. Because of the similarity in the symptoms of eye diseases in the early stages and the difficulty in distinguishing between the type of disease, there is a need for computer-assisted automated diagnostic techniques. This study focuses on classifying an eye disease dataset using hybrid techniques based on feature extraction with fusion methods. Three strategies were designed to classify CFP images for the diagnosis of eye disease. The first method is to classify an eye disease dataset using an Artificial Neural Network (ANN) with features from the MobileNet and DenseNet121 models separately after reducing the high dimensionality and repetitive features using Principal Component Analysis (PCA). The second method is to classify the eye disease dataset using an ANN on the basis of fused features from the MobileNet and DenseNet121 models before and after reducing features. The third method is to classify the eye disease dataset using ANN based on the fused features from the MobileNet and DenseNet121 models separately with handcrafted features. Based on the fused MobileNet and handcrafted features, the ANN attained an AUC of 99.23%, an accuracy of 98.5%, a precision of 98.45%, a specificity of 99.4%, and a sensitivity of 98.75%.
Correction: Kim et al. Assessment of Enhancement Kinetics Improves the Specificity of Abbreviated Breast MRI: Performance in an Enriched Cohort. Diagnostics 2023, 13, 136
Authors: Kim Haejung , Ko Eun Young , Kim Ka Eun , Kim Myoung Kyoung , Choi Ji Soo , Ko Eun Sook , Han Boo-Kyung
Published: May 2023

There were errors in the original publication [...]
PTC-MAS: A Deep Learning-Based Preoperative Automatic Assessment of Lymph Node Metastasis in Primary Thyroid Cancer
Authors: Fu Ruqian , Yang Hao , Zeng Dezhi , Yang Shuhan , Luo Peng , Yang Zhijie , Teng Hua , Ren Jianli
Published: May 2023

Background: Identifying cervical lymph node metastasis (LNM) in primary thyroid cancer preoperatively using ultrasound is challenging. Therefore, a non-invasive method is needed to assess LNM accurately. Purpose: To address this need, we developed the Primary Thyroid Cancer Lymph Node Metastasis Assessment System (PTC-MAS), a transfer learning-based and B-mode ultrasound images-based automatic assessment system for assessing LNM in primary thyroid cancer. Methods: The system has two parts: YOLO Thyroid Nodule Recognition System (YOLOS) for obtaining regions of interest (ROIs) of nodules, and LMM assessment system for building the LNM assessment system using transfer learning and majority voting with extracted ROIs as input. We retained the relative size features of nodules to improve the system’s performance. Results: We evaluated three transfer learning-based neural networks (DenseNet, ResNet, and GoogLeNet) and majority voting, which had the area under the curves (AUCs) of 0.802, 0.837, 0.823, and 0.858, respectively. Method III preserved relative size features and achieved higher AUCs than Method II, which fixed nodule size. YOLOS achieved high precision and sensitivity on a test set, indicating its potential for ROIs extraction. Conclusions: Our proposed PTC-MAS system effectively assesses primary thyroid cancer LNM based on preserving nodule relative size features. It has potential for guiding treatment modalities and avoiding inaccurate ultrasound results due to tracheal interference.
Oral Manifestations in Monkeypox: A Scoping Review on Implications for Oral Health
Authors: Issa Asmaa Wajeeh , Alkhofash Nada Fayyad , Gopinath Divya , Varma Sudhir Rama
Published: May 2023

Background: The monkeypox outbreak in 2022 caused concern in the public. Infected patients usually present prodromal symptoms, such as lesions on their skin and mucous membranes, including the oral cavity. The current study aims to review the most common oral/perioral manifestations reported to date. Methods: A literature search was conducted in the PubMed, Research Gate, and Wiley Online Library databases, as well as in the Google search engine, using keywords related to the condition. Of the 56 publications identified, 30 were selected, including 27 case reports, two case series types, and one cross-sectional study published from 2003 to 2023 in endemic and non-endemic countries. Of the 54 patients in these studies, data on the oral symptoms and sites of monkeypox were interpreted from 47 patients. Results: Oral/perioral signs as one of the initial manifestations were reported in 23 out of 47 patients (48.93%). Out of the 47 patients with oral/perioral involvement, the most common signs/symptoms were sore throat, followed by ulcers, vesicles, dysphagia and odynophagia, and erythema. Conclusion: The most common oral symptom of monkeypox is sore throat, followed by ulcers. The symptoms usually occur in the pharynx/oropharynx, followed by the tonsils and tongue. Adequate knowledge about the characteristics of this virus and their association with the oral cavity is necessary, and could help oral health professionals to distinguish between different infections.
STEM Education in Early Years: Challenges and Opportunities in Changing Teachers’ Pedagogical Strategies
Authors: Leung Wai Man Vivienne
Published: May 2023

In recent years, there have been growing calls to include STEM education in early childhood (EC). This has created new challenges for EC teachers as they try to find ways to integrate STEM content and pedagogical strategies into school-based curricula. This study interviewed 24 EC teachers to understand their roles in implementing STEM education in preschool classrooms. The qualitative interviews explored changes in teachers’ roles and challenges before and after integrating STEM-related activities. The study revealed that the STEM education process is a dynamic one, and that the role of EC teachers is changing from one delivering teacher-centered knowledge to one fostering STEM-related learning in children. The research findings indicate that EC teachers face various challenges when implementing STEM education. The transformation of the teacher’s role during STEM classroom practices when encountering a range of challenges is discussed.
Characteristics of Offset Corbino Thin Film Transistor: A Physical Model
Authors: Kong Jiaquan , Liu Chuan , Li Xiaojie , Ou Hai , She Juncong , Deng Shaozhi , Chen Jun
Published: May 2023

Offset Corbino thin film transistor is a good candidate for high voltage thin film transistor (HVTFT) due to the uniform drain electric field distribution benefiting from the circular structure. The physical model of offset Corbino thin film transistor characteristics has yet to be clarified. In this study, Equations are derived to describe the current–voltage relations of Corbino TFT with offset at the drain or source sides. The influence of offset position and parameters on the saturation voltage and the saturation current was described quantitatively. Three-dimensional Computer-Aided Design simulation and experiment results verify the theoretical physical model. Our physical model provides design rules for high voltage offset Corbino TFT when considering the voltage tolerance and saturation current balance.
Quantifying the Simulation–Reality Gap for Deep Learning-Based Drone Detection
Authors: Dieter Tamara Regina , Weinmann Andreas , Jäger Stefan , Brucherseifer Eva
Published: May 2023

The detection of drones or unmanned aerial vehicles is a crucial component in protecting safety-critical infrastructures and maintaining privacy for individuals and organizations. The widespread use of optical sensors for perimeter surveillance has made optical sensors a popular choice for data collection in the context of drone detection. However, efficiently processing the obtained sensor data poses a significant challenge. Even though deep learning-based object detection models have shown promising results, their effectiveness depends on large amounts of annotated training data, which is time consuming and resource intensive to acquire. Therefore, this work investigates the applicability of synthetically generated data obtained through physically realistic simulations based on three-dimensional environments for deep learning-based drone detection. Specifically, we introduce a novel three-dimensional simulation approach built on Unreal Engine and Microsoft AirSim for generating synthetic drone data. Furthermore, we quantify the respective simulation–reality gap and evaluate established techniques for mitigating this gap by systematically exploring different compositions of real and synthetic data. Additionally, we analyze the adaptation of the simulation setup as part of a feedback loop-based training strategy and highlight the benefits of a simulation-based training setup for image-based drone detection, compared to a training strategy relying exclusively on real-world data.
The Online Frequency Security Assessment of a Power System Considering the Time-Varying Characteristics of Renewable Energy Inertia
Authors: Peng Zefeng , Lu Yulin , Zhang Yingmin , Deng Wenjun , Zeng Qi
Published: May 2023

The continuous increase in the penetration rate of renewable energy has led to a decrease in the system’s frequency response capability, which presents great challenges to the safety and stability of the power system. In order to ensure the safe operation of the power system, online frequency safety assessment has become necessary. However, the time-varying characteristics of the virtual inertia HNE of renewable energy stations make it more difficult to accurately predict the lowest point of the system frequency after a disturbance. Based on the general average system frequency (G-ASF) model, this paper proposes a G-ASF-H model that considers the time-varying characteristics of the virtual inertia of renewable energy stations, accurately predicts the lowest frequency point after a system disturbance, and realizes the online frequency safety assessment of the system. Firstly, a unified virtual synchronous generator model is established to identify the virtual inertia time constant of the renewable energy station in real time; then, under the pre-defined frequency safety verification event, the maximum deviation of the system frequency is periodically calculated and judged based on the G model to realize the online frequency safety assessment. The example analysis on the IEEE 10-machine 39-node system shows that the model has a high calculation speed and accuracy under different disturbances or daily load level scenarios and can be used for the online security assessment of new power systems with time-varying virtual inertia characteristics.
Implementation of a Fusion Classification Model for Efficient Pen-Holding Posture Detection
Authors: Wu Xiaoping , Liu Yupeng , Zhang Chu , Qi Hengnian , Jacques Sébastien
Published: May 2023

Pen-holding postures (PHPs) can significantly affect the speed and quality of writing, and incorrect postures can lead to health problems. This paper presents and experimentally implements a methodology for quickly recognizing and correcting poor writing postures using a digital dot matrix pen. The method first extracts basic handwriting information, including page number, handwriting coordinates, movement trajectory, pen tip pressure, stroke sequence, and pen handling time. This information is then used to generate writing features that are fed into our proposed fusion classification model, which combines a simple parameter-free attention module for convolutional neural networks (CNNs) called NetworkSimAM, CNNs, and an extension of the well-known long short-term memory (LTSM) called Mogrifier LSTM or MLSTM. Finally, the method ends with a classification step (Softmax) to recognize the type of PHP. The implemented method achieves significant results through receiver operating characteristic (ROC) curves and loss functions, including a recognition accuracy of 72%, which is, for example, higher than that of the single-stroke model (i.e., TabNet incorporating SimAM). The obtained results show that a promising solution is provided for accurate and efficient PHP recognition and has the potential to improve writing speed and quality while reducing health problems induced by incorrect postures.
Aspects of Dynamics in Dialogue Collaboration
Authors: Vogel Carl , Koutsombogera Maria , Reverdy Justine
Published: May 2023

Collaborative dialogue is an important category of human interaction and is widely studied in the literature, especially in fields that attempt to develop new technologies that enable wider varieties of collaborative dialogues. The ingredients of collaboration in dialogue are less thoroughly addressed. We describe the theoretical framework within which we are working and our approach to the construction of a theory of what may make dialogue collaborative. We study a multimodal dialogue corpus (MULTISIMO) testing for positive and negative correlations between dialogue content features and interaction features that one might reasonably imagine are related to assessments of degrees of collaboration. The duration before the second speaker’s first turn and degree of imbalance in the number of words produced by speakers negatively correlate with collaboration assessments (that is, imbalances of content and a delay in the first speaker yielding the floor lead to diminished perceptions of collaboration), while a monotonically increasing duration of focus in successive dialogue sections (rather than overall dialogue duration) correlates positively (that is, when participants are deemed to be extending the duration of the task rather than increasing speed with experience, this is perceived as collaborative).
Method for Digital Cancellation of System Interference in a Full-Duplex Power Line Communication System
Authors: Mukhamadiev Semen , Rogozhnikov Eugeniy , Dmitriyev Edgar , Pokamestov Dmitriy , Kryukov Yakov , Novichkov Serafim , Lakontsev Dmitry
Published: May 2023

Every year the number of IoT devices is growing, which gives a boost to development of such technology as Power Line Communication (PLC). The term PLC refers to the use of a power supply circuit to transmit data. Full-duplex technology can be applied to increase the data transfer rate in a PLC. The difficulty in using a full duplex is the need to suppress the transmitter’s own signal (interference signal). Analog cancellation and digital cancellation are used for this purpose. Common algorithms for digital cancellation are adaptive algorithms. In this paper adaptive algorithms such as Particle Swarm Optimization (PSO) and Recursive Least Squares (RLS) are considered and a modification of the classical RLS is proposed. The proposed algorithm uses precalculated weight coefficients together with periodic reinitialization of the filter. This avoids the influence of significant changes in the input signal on the further process of filter adaptation and provides the highest level of echo suppression. The proposed algorithm provides an improvement of parameters such as Error Vector Magnitude (EVM) and Signal-to-Interference Ratio (SIR) in comparison with classical RLS and PSO, according to the results of the study.
Optimization of a Single-Switch Wireless Power Transfer Circuit Based on a Multi-Coil Array
Authors: Yang Yi , Zhang Xin , Guo Ke , Zhang Wenxin , Xie Shiyun
Published: May 2023

In response to the issue of large input current ripple and noise, which can cause current shocks and compromise the overall stability in single-tube wireless power transmission systems, a P# type LCC-S compensation network and a multi-coil phase-shifting control method have been proposed to suppress input current ripple, improve input current waveform, reduce input current total harmonic distortion (THD), and ultimately enhance system efficiency and stability. Firstly, the working mode and waveform of the P# type LCC-S compensation network are analyzed, and the calculation method for its parameters is provided. Secondly, the analytical relationship between input current, input voltage, coil mutual inductance, and load impedance of the multi-coil array is derived. Additionally, Fourier transform is used to analyze the input current composition, and the phase shift suppression method is employed to reduce the input current ripple. Finally, a test platform is constructed to verify the relevant experiments. The experimental results demonstrate that the input current ripple is significantly suppressed at the rated transmission power, and the system efficiency is improved to 88.2%, which validates the effectiveness of the proposed method.
Automatic Emotion Recognition from EEG Signals Using a Combination of Type-2 Fuzzy and Deep Convolutional Networks
Authors: Baradaran Farzad , Farzan Ali , Danishvar Sebelan , Sheykhivand Sobhan
Published: May 2023

Emotions are an inextricably linked component of human life. Automatic emotion recognition can be widely used in brain–computer interfaces. This study presents a new model for automatic emotion recognition from electroencephalography signals based on a combination of deep learning and fuzzy networks, which can recognize two different emotions: positive, and negative. To accomplish this, a standard database based on musical stimulation using EEG signals was compiled. Then, to deal with the phenomenon of overfitting, generative adversarial networks were used to augment the data. The generative adversarial network output is fed into the proposed model, which is based on improved deep convolutional networks with type-2 fuzzy activation functions. Finally, in two separate class, two positive and two negative emotions were classified. In the classification of the two classes, the proposed model achieved an accuracy of more than 98%. In addition, when compared to previous studies, the proposed model performed well and can be used in future brain–computer interface applications.
Magnetic Localization of Wireless Ingestible Capsules Using a Belt-Shaped Array Transmitter
Authors: Castro Ivan , de Wit Jan Willem , van Vooren Jasper , Van Quaethem Tom , Huang Weixi , Torfs Tom
Published: May 2023

In the last 20 years, research into and clinical use of wireless ingestible capsules (WIC) has increased, with capsule endoscopy being the most common application in clinical practice. Additionally, there has been an increased research interest in sensing capsules. To maximize the usefulness of the information provided by these devices, it is crucial to know their location within the gastrointestinal tract. The main WIC localization methods in research include radio frequency approaches, video-based methods, and magnetic-based methods. Of these methods, the magnetic-based methods show the most potential in terms of localization accuracy. However, the need for an external transmitting (or sensing) array poses an important limitation, as evidenced by most of the reported methods involving a rigid structure. This poses a challenge to its wearability and performance in daily life environments. This paper provides an overview of the state of the art on magnetic-based localization for WIC, followed by a proof of concept of a system that aims to solve the wearability challenges. Comparative performance simulations of different transmitter arrays are presented. The effect of including one or two receiver coils in the WIC is also evaluated in the simulation. Experimental localization results for a planar transmitter array and for a more wearable belt-shaped transmitter are presented and compared. A localization mean absolute error (MAE) as low as 6.5 mm was achieved for the planar array in a volume of 15 cm × 15 cm × 15 cm, starting at a 5 cm distance from the transmitter. Evaluating the belt array in a similar volume of interest (15 cm × 15 cm × 15 cm starting at 7.5 cm distance from the transmitter) resulted in an MAE of 13.1 mm across the volume and a plane-specific MAE as low as 9.5 mm when evaluated at a 12.5 cm distance. These initial results demonstrate comparable performances between these two transmitters, while the belt array has the potential to enable measurements in daily-life environments. Despite these promising results, it was identified that an improvement in the model for the magnetic field when using transmitter coils with ferrite cores is necessary and is likely to result in better localization accuracy. This belt-array approach, together with compensation techniques for body motion, as recently reported for rigid arrays, has the potential to enable WIC localization in uncontrolled environments with minimal impact on the user’s daily life.
Enhancing Hydrogen Production from Biogas through Catalyst Rearrangements
Authors: Pajak Marcin , Brus Grzegorz , Kimijima Shinji , Szmyd Janusz S.
Published: May 2023

Recent trends in hydrogen production include using renewable energy sources, e.g., biogas as feedstocks for steam reforming. Crucial to the field is minimizing existing reforming reactors for their applications to fuel cell systems. Here, we present a novel design of a steam reforming reactor for an efficient biogas conversion to hydrogen. The design includes a radial division of the catalytic insert into individual segments and substituting parts of the catalytic material with metallic foam. The segment configuration is optimized using a genetic algorithm to maximize the efficiency of the reactor. Changes in the catalytic insert design influence the thermal conditions inside the reactor, leading to moderation of the reaction rate. This article presents a promising approach to producing hydrogen from renewable sources via steam reforming. A significant enhancement in the reforming process effectiveness is achieved with a notable decrease in the amount of the catalyst used. The final results demonstrate the capability for acquiring a similar level of biogas conversion with a 41% reduction of the catalytic material applied.
Chemical Release Accident Caused by the Abnormal Reaction of Potassium Permanganate Mixtures during Optical Film Manufacturing: A Brief Case Review
Authors: Park Jihoon , Kim Byung-Hoon , Hwang Seung-Ryul , Park Choonhwa
Published: May 2023

Small- and large-scale accidents often occur in workplaces handling hazardous chemical substances. These accidents are usually caused by leaks, explosions, fires and complex chemicals; a large proportion of these chemical accidents are caused by leaks. A chemical release accident that injured four people occurred during an optical film-manufacturing process. This report analyzes the causes of this accident and provides effective measures for accident prevention. This accident was caused by an abnormal reaction during the input of raw materials prior to their heating. Tertiary butyl alcohol (t-BuOH), distilled water (DW), and potassium permanganate (KMnO4) were mainly used in this process. We found that this mixture reacted with unknown impurities. After KMnO4 was added to the mixture of t-BuOH and DW, a large amount of heat was suddenly released from the reactor for one minute. In particular, a small amount of methanol (4%), which could have entered the mixture during the cleaning process, and seal oil containing glycerin (13%) were suspected to be the key materials influencing the rapid reaction. Given the significant findings about this accident, the precautionary technical/administrative measures we provide herein may help prevent such accidents in future.
A Hybrid Text Generation-Based Query Expansion Method for Open-Domain Question Answering
Authors: Zhu Wenhao , Zhang Xiaoyu , Zhai Qiuhong , Liu Chenyun
Published: May 2023

In the two-stage open-domain question answering (OpenQA) systems, the retriever identifies a subset of relevant passages, which the reader then uses to extract or generate answers. However, the performance of OpenQA systems is often hindered by issues such as short and semantically ambiguous queries, making it challenging for the retriever to find relevant passages quickly. This paper introduces Hybrid Text Generation-Based Query Expansion (HTGQE), an effective method to improve retrieval efficiency. HTGQE combines large language models with Pseudo-Relevance Feedback techniques to enhance the input for generative models, improving text generation speed and quality. Building on this foundation, HTGQE employs multiple query expansion generators, each trained to provide query expansion contexts from distinct perspectives. This enables the retriever to explore relevant passages from various angles for complementary retrieval results. As a result, under an extractive and generative QA setup, HTGQE achieves promising results on both Natural Questions (NQ) and TriviaQA (Trivia) datasets for passage retrieval and reading tasks.
Optimizing the Quality of Service of Mobile Broadband Networks for a Dense Urban Environment
Authors: Imoize Agbotiname Lucky , Udeji Friday , Isabona Joseph , Lee Cheng-Chi
Published: May 2023

Mobile broadband (MBB) services in Lagos, Nigeria are marred with poor signal quality and inconsistent user experience, which can result in frustrated end-users and lost revenue for service providers. With the introduction of 5G, it is becoming more necessary for 4G LTE users to find ways of maximizing the technology while they await the installation and implementation of the new 5G networks. A comprehensive analysis of the quality of 4G LTE MBB services in three different locations in Lagos is performed. Minimal optimization techniques using particle swarm optimization (PSO) are used to propose solutions to the identified problems. A methodology that involves data collection, statistical analysis, and optimization techniques is adopted to measure key performance indicators (KPIs) for MBB services in the three locations: UNILAG, Ikorodu, and Oniru VI. The measured KPIs include reference signal received power (RSRP), reference signal received quality (RSRQ), received signal strength indicator (RSSI), and signal-to-noise ratio (SINR). Specific statistical analysis was performed, and the mean, standard deviation, skewness, and kurtosis were calculated for the measured KPIs. Additionally, the probability distribution functions for each KPI were plotted to infer the quality of MBB services in each location. Subsequently, the PSO algorithm was used to optimize the KPIs in each location, and the results were compared with the measured data to evaluate the effectiveness of the optimization. Generally, the optimization process results in an improvement in the quality of service (QoS) in the investigated environments. Findings also indicated that a single KPI, such as RSRP, is insufficient for assessing the quality of MBB services as perceived by end-users. Therefore, multiple KPIs should be considered instead, including RSRQ and RSSI. In order to improve MBB performance in Lagos, recommendations require mapping and replanning of network routes and hardware design. Additionally, it is clear that there is a significant difference in user experience between locations with good and poor reception and that consistency in signal values does not necessarily indicate a good user experience. Therefore, this study provides valuable insights and solutions for improving the quality of MBB services in Lagos and can help service providers better understand the needs and expectations of their end users.
Towards a Better Understanding of Texturization during High-Moisture Extrusion (HME)—Part I: Modeling the Texturability of Plant-Based Proteins
Authors: Högg Elisabeth , Rauh Cornelia
Published: May 2023

This study focused on predicting high-moisture texturization of plant-based proteins (soy protein concentrate (SPC), soy protein isolate (SPI), pea protein isolate (PPI)) at different water contents (57.5%, 60%, 65%, 70%, and 72.5% (w/w db)) to optimize and guarantee the production of high-moisture meat analogs (HMMA). Therefore, high-moisture extrusion (HME) experiments were performed, and the texture of the obtained high-moisture extruded samples (HMES) was sensory evaluated and categorized into poorly-textured, textured, or well-textured. In parallel, data on heat capacity (cp) and phase transition behavior of the plant-based proteins were determined using differential scanning calorimetry (DSC). Based on the DSC data, a model for predicting cp of hydrated, but not extruded, plant-based proteins was developed. Furthermore, based on the aforementioned model for predicting cp and DSC data on phase transition behavior of the plant-based proteins in combination with conducted HME trials and the mentioned model for predicting cp, a texturization indicator was developed, which could be used to calculate the minimum threshold temperature required to texturize plant-based proteins during HME. The outcome of this study could help to minimize the resources of expensive extrusion trials in the industry to produce HMMA with defined textures.
Contents and Correlations of Nε-(carboxymethyl)lysine, Nε-(carboxyethyl)lysine, Acrylamide and Nutrients in Plant-Based Meat Analogs
Authors: Fu Shuang , Ma Yurong , Wang Yinan , Sun Chongzhen , Chen Feng , Cheng Ka-Wing , Liu Bin
Published: May 2023

High temperatures applied in the production of plant-based meat analogs (PBMA) lead to the occurrence of Maillard reactions, in which harmful compounds Nε-(carboxymethyl)lysine (CML), Nε-(carboxyethyl)lysine (CEL) and acrylamide are formed. However, little research has focused on these compounds in PBMA. In this study, the contents of CML, CEL and acrylamide in 15 commercial-sold PBMA were determined by an ultra-high performance liquid chromatograph coupled with a triple quadrupole tandem mass spectrometer (UHPLC-QqQ-MS/MS). Nutrients (protein, amino acids, fatty acids and sugars) which are related to the formation of these compounds were also studied. The results showed that CML, CEL and acrylamide contents were in the range of 16.46–47.61 mg/kg, 25.21–86.23 mg/kg and 31.81–186.70 μg/kg, respectively. Proteins account for 24.03–53.18% of PBMA. Except for Met + Cys, which is the limiting amino acid of most PBMA, all other indispensable amino acids met the requirements for adults. Besides, PBMA had more n-6 fatty acids than n-3 fatty acids. A correlation analysis showed that proteins and the profiles of amino acid and fatty acid had little influence on CML but significant influence on CEL and acrylamide. The results of the present study can be used as a reference to produce PBMA with higher amounts of nutrients and lower amounts of CML, CEL and acrylamide.
Depth Image Enhancement Algorithm Based on Fractional Differentiation
Authors: Huang Tingsheng , Wang Xinjian , Xie Da , Wang Chunyang , Liu Xuelian
Published: May 2023

Depth image enhancement techniques can help to improve image quality and facilitate computer vision tasks. Traditional image-enhancement methods, which are typically based on integer-order calculus, cannot exploit the textural information of an image, and their enhancement effect is limited. To solve this problem, fractional differentiation has been introduced as an innovative image-processing tool. It enables the flexible use of local and non-local information by taking into account the continuous changes between orders, thereby improving the enhancement effect. In this study, a fractional differential is applied in depth image enhancement and used to establish a novel algorithm, named the fractional differential-inverse-distance-weighted depth image enhancement method. Experiments are performed to verify the effectiveness and universality of the algorithm, revealing that it can effectively solve edge and hole interference and significantly enhance textural details. The effects of the order of fractional differentiation and number of iterations on the enhancement performance are examined, and the optimal parameters are obtained. The process data of depth image enhancement associated with the optimal number of iterations and fractional order are expected to facilitate depth image enhancement in actual scenarios.
Probing the Effect of Young’s Modulus on the Reservoir Regulation Abilities of Dispersed Particle Gels
Authors: Wang Zizhao , Zhu Zhixuan , Jiang Tianyu , Liu Jinming , Dong Yunbo , Wu Yining , Zhao Mingwei , Dai Caili , Li Lin
Published: May 2023

The mechanical strength of dispersed particle gels (DPGs), which can be directly characterized by Young’s modulus, is an important parameter affecting reservoir regulation performance. However, the effect of reservoir conditions on the mechanical strength of DPGs, as well as the desired range of mechanical strength for optimum reservoir regulation performance, have not been systematically studied. In this paper, DPG particles with different Young’s moduli were prepared and their corresponding migration performances, profile control capacities and enhanced oil recovery abilities were studied by simulated core experiments. The results showed that with increase in Young’s modulus, the DPG particles exhibited improved performance in profile control as well as enhanced oil recovery. However, only the DPG particles with a modulus range of 0.19–0.762 kPa could achieve both adequate blockage in large pore throats and migration to deep reservoirs through deformation. Considering the material costs, applying DPG particles with moduli within the range of 0.19–0.297 kPa (polymer concentration: 0.25–0.4%; cross-linker concentration: 0.7–0.9%) would ensure optimum reservoir control performance. Direct evidence for the temperature and salt resistance of DPG particles was also obtained. When aged in reservoir conditions below 100 °C and at a salinity of 10 × 104 mg·L−1, the Young’s modulus values of the DPG particle systems increased moderately with temperature or salinity, indicating a favorable impact of reservoir conditions on the reservoir regulation abilities of DPG particles. The studies in this paper indicated that the practical reservoir regulation performances of DPGs can be improved by adjusting the mechanical strength, providing basic theoretical guidance for the application of DPGs in efficient oilfield development.
Superhydrophobic/Superoleophilic PDMS/SiO2 Aerogel Fabric Gathering Device for Self-Driven Collection of Floating Viscous Oil
Authors: Liu Feng , Di Xin , Sun Xiaohan , Wang Xin , Yang Tinghan , Wang Meng , Li Jian , Wang Chengyu , Li Yudong
Published: May 2023

The persistent challenge of removing viscous oil on water surfaces continues to pose a major concern and requires immediate attention. Here, a novel solution has been introduced in the form of a superhydrophobic/superoleophilic PDMS/SiO2 aerogel fabric gathering device (SFGD). The SFGD is based on the adhesive and kinematic viscosity properties of oil, enabling self-driven collection of floating oil on the water surface. The SFGD is able to spontaneously capture the floating oil, selectively filter it, and sustainably collect it into its porous fabric interior through the synergistic effects of surface tension, gravity, and liquid pressure. This eliminates the need for auxiliary operations such as pumping, pouring, or squeezing. The SFGD demonstrates exceptional average recovery efficiencies of 94% for oils with viscosities ranging from 10 to 1000 mPa·s at room temperature, including dimethylsilicone oil, soybean oil, and machine oil. With its facile design, ease of fabrication, high recovery efficiency, excellent reclaiming capabilities, and scalability for multiple oil mixtures, the SFGD represents a significant advancement in the separation of immiscible oil/water mixtures of various viscosities and brings the separation process one step closer to practical application.
Comparison of Different Aerogel Granules for Use as Aggregate in Concrete
Authors: Welsch Torsten , Vievers Yannick , Schnellenbach-Held Martina , Bialuschewski Danny , Milow Barbara
Published: May 2023

In previous work of this group, a structural lightweight concrete was developed by embedding silica aerogel granules in a high-strength cement matrix. This concrete, called high-performance aerogel concrete (HPAC), is a lightweight building material characterized by its simultaneous high compressive strength and very low thermal conductivity. Besides these features, high sound absorption, diffusion permeability, water repellence and fire resistance qualify HPAC as an interesting material for the construction of single-leaf exterior walls without any further insulation. During the development of HPAC, the type of silica aerogel was found to majorly influence both fresh and hardened concrete properties. To clarify these effects, a systematic comparison of SiO2 aerogel granules with different levels of hydrophobicity as well as different synthesis methods was conducted in the present study. The granules were analyzed for their chemical and physical properties as well as their compatibility in HPAC mixtures. These experiments included determinations of pore size distribution, thermal stability, porosity, specific surface and hydrophobicity, as well as fresh/hardened concrete experiments such as measurements of compressive strength, flexural bending strength, thermal conductivity and shrinking behavior. It was found that the type of aerogel has a major influence on the fresh and hardened concrete properties of HPAC, particularly compressive strength and shrinkage behavior, whereas the effect on thermal conductivity is not very pronounced.