bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving Accuracy of Face Recognition in the Era of Mask-Wearing: An Evaluation of a Pareto-Optimized FaceNet Model with Data Preprocessing Techniques
Authors: Akingbesote Damilola , Zhan Ying , Maskeliūnas Rytis , Damaševičius Robertas
Published: June 2023

The paper presents an evaluation of a Pareto-optimized FaceNet model with data preprocessing techniques to improve the accuracy of face recognition in the era of mask-wearing. The COVID-19 pandemic has led to an increase in mask-wearing, which poses a challenge for face recognition systems. The proposed model uses Pareto optimization to balance accuracy and computation time, and data preprocessing techniques to address the issue of masked faces. The evaluation results demonstrate that the model achieves high accuracy on both masked and unmasked faces, outperforming existing models in the literature. The findings of this study have implications for improving the performance of face recognition systems in real-world scenarios where mask-wearing is prevalent. The results of this study show that the Pareto optimization allowed improving the overall accuracy over the 94% achieved by the original FaceNet variant, which also performed similarly to the ArcFace model during testing. Furthermore, a Pareto-optimized model no longer has a limitation of the model size and is much smaller and more efficient version than the original FaceNet and derivatives, helping to reduce its inference time and making it more practical for use in real-life applications.
Design of a Small-Scale Hydroponic System for Indoor Farming of Leafy Vegetables
Authors: Nikolov Neiko V. , Atanasov Atanas Z. , Evstatiev Boris I. , Vladut Valentin N. , Biris Sorin-Stefan
Published: June 2023

The reduction of the population and labour force in rural areas, adverse climate changes, soil pollution and degradation, and reduced soil fertility necessitate new and intensive approaches to and methods of vegetable production. In this study, a new high-tech, small-scale hydroponic system based on the Internet of Things (IoT) for growing leafy vegetables was designed. For the assembly of the high-tech small-scale hydroponic system, low-cost materials and sensors are used, allowing remote monitoring and process automation during the cultivation of leafy vegetables and seedlings. Experimental investigations of the installation were conducted, with lettuce as the grown crop. The environmental and technological parameters of the system were monitored and analysed in order to assess the suitability of the system. The obtained results confirm that the small-scale hydroponic system maintained the set parameters of air temperature, air humidity and pH of the nutrient solution within the optimal limits for growing lettuce. Other parameters, such as temperature and electrical conductivity of the nutrient solution, had small deviations from the required optimal limits. In the initially set experiment, 75% germination of the lettuce seeds was achieved. The main advantages of the proposed hydroponic system are the simplicity of its management and easy installation. Furthermore, it offers the possibility for remote monitoring and control without any high requirements towards the experience of the user with such facilities. The designed and implemented small hydroponic system can help small and medium-sized vegetable growers achieve indoor sustainable farming of leafy vegetables year-round.
Design and Test of an Arc-Shaped Tooth Press Device for Combined Soil Preparation Equipment for Growing Potatoes
Authors: Zhao Zhiming , Zhu Xiaoxin , Li Jicheng , Lyu Jinqing , Qi Yu , Liu Jinni
Published: June 2023

In response to the low soil breakage rate and poor flatness of current combined soil preparation equipment for growing potatoes under the clay loam conditions of Northeast China, this paper presents the design of an arc-shaped tooth press device for such equipment, describing its overall structure and working principle. By conducting force analysis on the press roller and shear stress analysis with MATLAB, we obtained the structural parameters and the corresponding value ranges impacting the operational effectiveness of the press device. A three-factor, five-level quadratic regression orthogonal rotational combination test was carried out using EDEM discrete element simulation software, taking the soil breakage rate and flatness as the test indicators. The forward speed, roller tooth arc length, and angle between the roller tooth and the vertical direction (ABRTVD) were the test factors. Design-Expert 8.0.6 software was used for data processing and analysis, and the results showed that the optimal parameter combination consisted of a forward speed of 0.72~1.15 m·s−1, a roller tooth arc length of 58.7 mm, and an ABRTVD of 37.74°, at which point the soil breakage rate was 93.58% and the flatness value was 21.36 mm. The optimal combination of parameters was selected for the field test, resulting in a soil breakage rate of 95.6% and a flatness value of 20.6 mm. The results of the simulation test were found to be consistent with the field test results, thus validating the efficacy of the device design. The findings of this study can provide a reference for enhancing the operational performance of combined soil preparation equipment for growing potatoes under clay loam conditions.
Impact of Salinity, Elevated Temperature, and Their Interaction with the Photosynthetic Efficiency of Halophyte Crop Chenopodium quinoa Willd
Authors: Shuyskaya Elena , Rakhmankulova Zulfira , Prokofieva Maria , Kazantseva Varvara , Lunkova Nina
Published: June 2023

Chenopodium quinoa is a genetically diverse crop that can adapt to a wide range of environments, including temperatures and salinities. However, only a few studies have assessed the combined effects of two or more environmental factors on C. quinoa. Here, we investigated the effects of salinity (300 mM NaCl), elevated temperature (35 °C), and their interaction with growth, water–salt balance, the efficiency of photosystem II (PSII), the activity of cyclic electron transport (CET) around photosystem I (PSI), Rubisco and PEPC enzyme content, and the expression of photosynthetic genes. We found that elevated temperature did not decrease the biomass but caused a significant increase in the water and potassium content of C. quinoa leaves. The decrease in PSII efficiency under elevated temperature was accompanied by an increase in the expression of genes encoding the components of PSII (psbA) and linear electron transport (FDI), as well as the main photosynthetic protein Rubisco (rbcL). Moreover, the strongest effect was induced by the combined effect of elevated temperature and salinity, which induced high oxidative stress (a threefold increase in MDA), a threefold decrease in the biomass, a twofold decrease in PSII efficiency, and a two- to eightfold decrease in the expression of the photosynthetic genes psbA, FDI, and rbcL. PSI was more tolerant to all forms of stress; however, the combined effect of elevated temperature and salinity downregulated the expression of PGR5 and FNR1, which may diminish the role of PGR5/PGRL1-dependent CET in favor of the NDH-dependent CET of PSI. The obtained data on the functioning of photosystems and the expression of photosynthetic genes under combined stress (elevated temperature and salinity) can make a significant contribution to understanding the mechanisms of tolerance of C. quinoa to multiple stresses under climate change conditions.
Plasma Treated Cattle Slurry Moderately Increases Cereal Yields
Authors: Cottis Thomas , Mousavi Hesam , Solberg Svein Øivind
Published: June 2023

Plasma treatment offers an approach to enhance the nitrogen (N) content of livestock slurry and biogas digestate, thereby increasing the efficacy of organic fertilizers. This innovative method is used to produce nitrogen-enriched organic fertilizer (NEO) containing a double concentration of plant-available N. Over three years, we conducted a comprehensive study in 14 spring wheat and barley field trials in Norway. The primary objective was to assess and compare the cereal grain yield achieved by applying NEO to other conventional fertilizers. The NEO utilized in our research was derived from the unit developed by the Norwegian company N2 Applied. The results indicated that 120 kg N ha−1 in NEO yielded in the same range of cereal grains as 95 kg N ha−1 in mineral fertilizer. Moreover, the combination of untreated slurry and 55 kg N ha−1 in mineral fertilizer Opti-NS yielded the same as 120 kg N ha−1 in NEO. Surprisingly a combination of 12 kg N ha−1 in mineral fertilizer at sowing day and 108 kg N ha−1 in NEO at the three-leaf stage led to a higher yield in spring wheat than 120 kg N ha−1 NEO spread at sowing day in two out of three experimental years. Moreover, applying NEO directly to plants has shown no visible signs of harm. Lastly, filtering the slurry resulted in higher cereal grain yields than the untreated slurry. In conclusion, despite possessing the same N content, utilizing NEO yielded a 15–20% lower cereal grain yield than mineral fertilizer. Nonetheless, 20–30% more yield than the native amount of cattle slurry it derived. However, we have observed an unexplained loss of approximately 17% of the nitrogen in NEO, which does not translate into increased grain yield or nitrogen productivity.
Inhibition of Listeria monocytogenes Cocktail Culture Biofilms on Crab and Shrimp Coupons and the Expression of Biofilm-Related Genes
Authors: Roy Pantu Kumar , Kim So Hee , Jeon Eun Bi , Park Eun Hee , Park Shin Young
Published: June 2023

Listeria monocytogenes, a bacterium that is transmitted by tainted food, causes the infection listeriosis. In this study, quercetin was tested for its antibacterial properties and effectiveness as a food additive in preventing the growth of L. monocytogenes cocktail (ATCC19117, ATCC19113, and ATCC15313) biofilms on crabs and shrimps. Quercetin showed the least bactericidal activity and no discernible microbial growth at a minimum inhibitory concentration (MIC) of 250 µg/mL. The biofilm inhibition was performed at sub-MICs (1/2, 1/4, and 1/8 MIC). There was no quercetin added to the control group. Additionally, the present work examines the expression of various genes related to biofilm formation and quorum sensing (flaA, fbp, agrA, hlyA, and prfA). The levels of target genes were all significantly down-regulated. Quercetin (0–125 µg/mL) on the surfaces of the crab and shrimp was studied; its inhibitory effects were measured as log reductions at 0.39–2.31 log CFU/cm2 and 0.42–2.36 log CFU/cm2, respectively (p < 0.05). Quercetin reduced the formation of biofilms by disrupting cell-to-cell connections and causing cell lysis, which led to the deformation of the cells, evidenced by FE-SEM (field-emission scanning electron microscopy). These findings emphasize the significance of using natural food agents to target bacteria throughout the entire food production process.
Ceratonia siliqua L. Pod Extract: From Phytochemical Characterization to Liposomal Formulation and Evaluation of Behaviour in Cells
Authors: De Luca Maria , Tuberoso Carlo Ignazio Giovanni , Pons Ramon , García María Teresa , Morán María del Carmen , Martelli Giuseppe , Vassallo Antonio , Caddeo Carla
Published: June 2023

The formulation of plant extracts in phospholipid vesicles is a promising strategy to exploit their biological properties while solving problems related to poor solubility in water, high instability, and low skin permeation and retention time. In this study, Ceratonia siliqua ripe pods were used for the preparation of a hydro-ethanolic extract, which showed antioxidant properties owing to the presence of biologically active compounds identified by liquid chromatography–mass spectrometry (e.g., hydroxybenzoic acid and flavonoid derivatives). To improve the applicability of the extract in therapy, a topical formulation based on liposomes was explored. The vesicles were characterized by small size (around 100 nm), negative charge (−13 mV), and high entrapment efficiency (>90%). Furthermore, they displayed both spherical and elongated shapes, with oligolamellar structure. Their biocompatibility was demonstrated in cells, including erythrocytes and representative skin cell lines. The antioxidant activity of the extract was proved by the scavenging of free radicals, the reduction of ferric ions, and the protection of skin cells from oxidative damage.
Cigarette Smoke-Induced Respiratory Response: Insights into Cellular Processes and Biomarkers
Authors: Cha Sang-Ryul , Jang Jimin , Park Sung-Min , Ryu Se Min , Cho Seong-Joon , Yang Se-Ran
Published: June 2023

Cigarette smoke (CS) poses a significant risk factor for respiratory, vascular, and organ diseases owing to its high content of harmful chemicals and reactive oxygen species (ROS). These substances are known to induce oxidative stress, inflammation, apoptosis, and senescence due to their exposure to environmental pollutants and the presence of oxidative enzymes. The lung is particularly susceptible to oxidative stress. Persistent oxidative stress caused by chronic exposure to CS can lead to respiratory diseases such as chronic obstructive pulmonary disease (COPD), pulmonary fibrosis (PF), and lung cancer. Avoiding exposure to environmental pollutants, like cigarette smoke and air pollution, can help mitigate oxidative stress. A comprehensive understanding of oxidative stress and its impact on the lungs requires future research. This includes identifying strategies for preventing and treating lung diseases as well as investigating the underlying mechanisms behind oxidative stress. Thus, this review aims to investigate the cellular processes induced by CS, specifically inflammation, apoptosis, senescence, and their associated biomarkers. Furthermore, this review will delve into the alveolar response provoked by CS, emphasizing the roles of potential therapeutic target markers and strategies in inflammation and oxidative stress.
Mammalian Animal and Human Retinal Organ Culture as Pre-Clinical Model to Evaluate Oxidative Stress and Antioxidant Intraocular Therapeutics
Authors: Kropp Martina , Mohit Mohit , Leroy-Ciocanea Cristina Ioana , Schwerm Laura , Harmening Nina , Bascuas Thais , De Clerck Eline , Kreis Andreas J. , Pajic Bojan , Johnen Sandra , Thumann Gabriele
Published: June 2023

Oxidative stress (OS) is involved in the pathogenesis of retinal neurodegenerative diseases such as age-related macular degeneration (AMD) and diabetic retinopathy (DR) and an important target of therapeutic treatments. New therapeutics are tested in vivo despite limits in terms of transferability and ethical concerns. Retina cultures using human tissue can deliver critical information and significantly reduce the number of animal experiments along with increased transferability. We cultured up to 32 retina samples derived from one eye, analyzed the model’s quality, induced OS, and tested the efficiency of antioxidative therapeutics. Bovine, porcine, rat, and human retinae were cultured in different experimental settings for 3–14 d. OS was induced by a high amount of glucose or hydrogen peroxide (H2O2) and treated with scutellarin, pigment epithelium-derived factor (PEDF), and/or granulocyte macrophage colony-stimulating factor (GM-CSF). The tissue morphology, cell viability, inflammation, and glutathione level were determined. The retina samples showed only moderate necrosis (23.83 ± 5.05 increased to 27.00 ± 1.66 AU PI-staining over 14 d) after 14 days in culture. OS was successfully induced (reduced ATP content of 288.3 ± 59.9 vs. 435.7 ± 166.8 nM ATP in the controls) and the antioxidants reduced OS-induced apoptosis (from 124.20 ± 51.09 to 60.80 ± 319.66 cells/image after the scutellarin treatment). Enhanced mammalian animal and human retina cultures enable reliable, highly transferable research on OS-triggered age-related diseases and pre-clinical testing during drug development.
The Influence of Melatonin Treatment in the Vinification of Feteasca Neagra and Cabernet Sauvignon Wines on the Profile of Polyphenolic Compounds and Antioxidant Activity
Authors: Eremia Sandra A. V. , Albu Camelia , Radu Gabriel-Lucian , Alecu Andreia , Brinduse Elena
Published: June 2023

Until recently, the main antioxidant role among wine constituents was attributed to polyphenolic compounds, but once the presence of melatonin in wines was confirmed, an interesting new field of research opened up due to its possible synergistic effects with other antioxidants in the winemaking process, which may lead to a change in the profile of polyphenolic compounds and antioxidant activity. In order to investigate the evolution of active principles from the phenylpropanoid metabolism associated with the synergistic effects of melatonin, for the first time, a melatonin treatment was performed in the pre-stage of the different winemaking processes of Feteasca Neagra and Cabernet Sauvignon wines with different melatonin concentrations. After comparing the acquired results for the evolution of the polyphenolic compound profile and antioxidant activity of treated wines, we ascertained an increase in the antioxidant compound concentrations, especially in resveratrol, quercetin, and cyanidin-3-glucoside, directly proportional to the used melatonin concentration; an intensification in activity of PAL and C4H enzymes; and the modification in the expression of specific anthocyanin biosynthesis genes, especially UDP-D-glucose-flavonoid-3-O-glycosyltransferase. It was also shown that the application of melatonin in the pre-stage of the winemaking process can be successfully used to obtain red wines with increased antioxidant activity (almost 14%).
Unleashing Ferroptosis in Human Cancers: Targeting Ferroptosis Suppressor Protein 1 for Overcoming Therapy Resistance
Authors: Lee Jaewang , Roh Jong-Lyel
Published: June 2023

Ferroptosis, a recently identified form of regulated cell death characterized by the iron-dependent accumulation of lethal lipid peroxidation, has gained increasing attention in cancer therapy. Ferroptosis suppressor protein 1 (FSP1), an NAD(P)H-ubiquinone oxidoreductase that reduces ubiquinone to ubiquinol, has emerged as a critical player in the regulation of ferroptosis. FSP1 operates independently of the canonical system xc–/glutathione peroxidase 4 pathway, making it a promising target for inducing ferroptosis in cancer cells and overcoming ferroptosis resistance. This review provides a comprehensive overview of FSP1 and ferroptosis, emphasizing the importance of FSP1 modulation and its potential as a therapeutic target in cancer treatment. We also discuss recent progress in developing FSP1 inhibitors and their implications for cancer therapy. Despite the challenges associated with targeting FSP1, advances in this field may provide a strong foundation for developing innovative and effective treatments for cancer and other diseases.
A Study of Collaborative Trajectory Planning Method Based on Starling Swarm Bionic Algorithm for Multi-Unmanned Aerial Vehicle
Authors: Chen Fayin , Tang Yong , Li Nannan , Wang Tao , Hu Yiwen
Published: June 2023

This academic paper addresses the challenges associated with trajectory planning for affordable and light-weight Unmanned Aerial Vehicle (UAV) swarms, despite limited computing resources and extensive cooperation requirements. Specifically, an imitation-based starling cluster cooperative trajectory planning technique is proposed for a fixed-wing model of a six-degree-of-freedom UAV cluster. To achieve this, dynamic trajectory prediction of the rapid random search tree is utilized to generate a track solution adapted to the terrain environment. Additionally, the Dubins aircraft path solution is applied as it is suitable for executing input track commands by the UAV model. Computational simulations on different cluster sizes show the approach can maintain the cluster state while navigating diverse terrains, with the track solution complying with the UAV’s physical model properties.
Switching Control of Closed-Loop Supply Chain Systems with Markov Jump Parameters
Authors: Wu Huiming , Guo Sicong
Published: June 2023

The switching system model of a closed-loop supply chain with Markov jump parameters is established. The system is modeled as a switching system with Markov jump parameters, taking into account the uncertainties of the process and the inventory decay factors. The Markov switching idea is applied to the controller design and performance analysis of the system to effectively suppress the bullwhip effect while ensuring the stability of the closed-loop supply chain system. Simulation examples are presented to illustrate the validity of the results obtained.
A Multi-Input Fusion Model for Privacy and Semantic Preservation in Facial Image Datasets
Authors: Yang Yuanzhe , Niu Zhiyi , Qiu Yuying , Song Biao , Zhang Xinchang , Tian Yuan
Published: June 2023

The widespread application of multimedia technologies such as video surveillance, online meetings, and drones facilitates the acquisition of a large amount of data that may contain facial features, posing significant concerns with regard to privacy. Protecting privacy while preserving the semantic contents of facial images is a challenging but crucial problem. Contemporary techniques for protecting the privacy of images lack the incorporation of the semantic attributes of faces and disregard the protection of dataset privacy. In this paper, we propose the Facial Privacy and Semantic Preservation (FPSP) model that utilizes similar facial feature replacement to achieve identity concealment, while adding semantic evaluation to the loss function to preserve semantic features. The proposed model is versatile and efficient in different task scenarios, preserving image utility while concealing privacy. Our experiments on the CelebA dataset demonstrate that the model achieves a semantic preservation rate of 77% while concealing the identities in facial images in the dataset.
Research on a Rolling Bearing Fault Diagnosis Method Based on Multi-Source Deep Sub-Domain Adaptation
Authors: Xie Fengyun , Wang Linglan , Zhu Haiyan , Xie Sanmao
Published: June 2023

Rolling bearings are the core component of rotating machinery. In order to solve the problem that the distribution of collected rolling bearing data is inconsistent during the operation of bearings under complex working conditions, which results in poor fault identification effects, a fault diagnosis method based on multi-source deep sub-domain adaptation (MSDSA) is proposed in this paper. The proposed method uses CMOR wavelet transform to transform the collected vibration signal into time–frequency maps and construct multiple sets of source–target domain data pairs, and a rolling bearing fault diagnosis network based on a multi-source deep sub-domain adaptive network is established. The network uses shared and domain-specific feature extraction networks to extract data features together. At the same time, the local maximum mean discrepancy (LMMD) was introduced to effectively capture the fine-grained information of the category. Each set of data was used to train the corresponding classifier. Finally, multiple sets of classifiers were combined to reduce the classification loss of the target domain samples at the classification boundary to achieve fault identification. In order to make the training process more stable, the network used the Ranger optimizer for parameter tuning. This paper verifies the effectiveness of the proposed method through two sets of comparative experiments. The proposed method achieves 97.78%, 99.65%, and 99.34% in three migration tasks. The experimental results show that the proposed method has a high recognition rate and generalization performance.
Applying Statistical Models to Optimize the Weld Bead Geometry in the Vertical Oscillation Arc Narrow Gap All-Position GMAW
Authors: Liu Hongsheng , Xue Ruilei , Zhou Jianping , Bao Yang , Xu Yan
Published: June 2023

Vertical oscillation arc welding for narrow gap gas metal arc welding (NG-GMAW) has a relatively simple structure, and it is widely used in all-position pipeline field welding. However, it has some shortcomings, such as incomplete fusion defects on the sidewall and interlayer. Aiming at resolving these shortcomings, a mathematical model is proposed to obtain appropriate welding parameters in different positions. In this model, the response surface methodology (RSM) based on the central composite design (CCD) was developed to study the interactions between welding parameters and the weld bead geometry. Then the analysis of variance (ANOVA) was used to evaluate the accuracy and significance of the proposed model. Finally, experiments were carried out in flat, vertical, and overhead positions to obtain the optimal parameters. The macroscopic metallography of the transversal section of the weld bead under the optimizing welding parameters showed that the weld beads were free of defects in the sidewall and interlayers.
Single vs. Multi-Label: The Issues, Challenges and Insights of Contemporary Classification Schemes
Authors: Sajid Naseer Ahmed , Rahman Atta , Ahmad Munir , Musleh Dhiaa , Basheer Ahmed Mohammed Imran , Alassaf Reem , Chabani Sghaier , Ahmed Mohammed Salih , Salam Asiya Abdus , AlKhulaifi Dania
Published: June 2023

Over the decades, a tremendous increase has been witnessed in the production of documents available in digital form. The increased production of documents has gained so much momentum that their rate of production jumps two-fold every five years. These articles are searched over the internet via search engines, digital libraries, and citation indexes. However, the retrieval of relevant research papers for user queries is still a pipedream. This is because scientific documents are not indexed based on some subject classification hierarchies. Hence, the classification of these documents becomes a challenging task for the researchers. Classification of the documents can be two-fold: one way is to assign a single label to each document and the other is to assign multi-labels to each document based on its belonging domains. Classification of the documents can be performed by using either the available metadata or the whole content of the documents. While performing classification, there are many challenges which may belong to the dataset, feature selection technique, preprocessing methodology, and which classification model is suitable for the classification of the documents. This paper highlights the issues for single-label and multi-label classification by using either metadata or content of the documents and why metadata-based approaches are better than content-based approaches in terms of feasibility.
Detection of Adversarial Attacks against the Hybrid Convolutional Long Short-Term Memory Deep Learning Technique for Healthcare Monitoring Applications
Authors: Albattah Albatul , Rassam Murad A.
Published: June 2023

Deep learning (DL) models are frequently employed to extract valuable features from heterogeneous and high-dimensional healthcare data, which are used to keep track of patient well-being via healthcare monitoring systems. Essentially, the training and testing data for such models are collected by huge IoT devices that may contain noise (e.g., incorrect labels, abnormal data, and incomplete information) and may be subject to various types of adversarial attacks. Therefore, to ensure the reliability of the various Internet of Healthcare Things (IoHT) applications, the training and testing data that are required for such DL techniques should be guaranteed to be clean. This paper proposes a hybrid convolutional long short-term memory (ConvLSTM) technique to assure the reliability of IoHT monitoring applications by detecting anomalies and adversarial content in the training data used for developing DL models. Furthermore, countermeasure techniques are suggested to protect the DL models against such adversarial attacks during the training phase. An experimental evaluation using the public PhysioNet dataset demonstrates the ability of the proposed model to detect anomalous readings in the presence of adversarial attacks that were introduced in the training and testing stages. The evaluation results revealed that the model achieved an average F1 score of 97% and an accuracy of 98%, despite the introduction of adversarial attacks.
Fingerprint Based Codebook for RIS Passive Beamforming Training
Authors: Nor Ahmed M. , Fratu Octavian , Halunga Simona
Published: June 2023

In this article, we propose a new RIS passive beamforming scheme in two main stages. First, a fingerprint-based codebook (FP-CB) design phase occurs, where the area of interest is divided into a number of points and the optimal reflection patterns (RPs) corresponding to these points are determined and stored alongside the coordinates of these points in the codebook database (DB). Second, there is the searching and learning online stage, in which, based on the receiver (RX) and FP points’ locations, the system determines a group of candidate RPs. Then, it just searches through them instead of examining the entire CB RPs to select the best RP that can be used for configuring RIS during the data transmission period. The proposed mechanism proves that designing a positioning information-based CB can highly reduce the system overhead computational complexity and enhance performance comparable to the conventional CB-based scheme and the full channel estimation (CE)-based scheme. For example, selecting only 10 candidate RPs from the FP-CB can obtain a better effective achievable rate than a CE-based scheme in a rapidly changing channel.
Optimization of a Multi-Type PMSM Based on Pyramid Neural Network
Authors: Liu Xiaoyu , Peng Wenqian , Xie Liuyin , Zhang Xiang
Published: June 2023

In this paper, a novel bat algorithm based on the quantum computing concept and pyramid neural network (PNN) is presented and applied to the electromagnetic motor optimization problem. Due to the problems of high loss, high temperature rise and threatening motor safety, it is necessary to optimize the design of high-speed permanent magnet synchronous motor (HPMSM) structure. In order to use less training data and avoid the problem of large computational costs due to repeated finite element simulation in the electromagnetic structure design, this paper adopted a performance-driven method to establish the PMSM model. This model could effectively reduce the dimensions of the parameter space and establish an effective high-quality model within a wide range of parameters. For the purpose of obtaining a reliable proxy model with less training data, this paper adopted a pyramid-shaped neural network, which could reduce the risk of overtraining and improve the utilization of specific problem knowledge embedded in the training data set. The quantum bat algorithm (QBA) was used to optimize the structure of the PMSM. Compared with the classical GA and PSO algorithms, the QBA has the characteristics of a rapid convergence speed, simple structure, strong searching ability and stronger local jumping mechanism. The correctness and effectiveness of the proposed PNN-based QBA method were verified using simulation analysis and a prototype test.
Entity Relationship Extraction Based on a Multi-Neural Network Cooperation Model
Authors: Liu Yibo , Zuo Qingyun , Wang Xu , Zong Teng
Published: June 2023

Entity relation extraction mainly extracts relations from text, which is one of the important tasks of natural language processing. At present, some special fields have insufficient data; for example, agriculture, the metallurgical industry, etc. There is a lack of an effective model for entity relationship recognition under the condition of insufficient data. Inspired by this, we constructed a suitable small balanced data set and proposed a multi-neural network collaborative model (RBF, Roberta–Bidirectional Gated Recurrent Unit–Fully Connected). In addition, we also optimized the proposed model. This model uses the Roberta model as the coding layer, which is used to extract the word-level features of the text. This model uses BiGRU (Bidirectional Gated Recurrent Unit)–FC (Fully Connected) as the decoding layer, which is used to obtain the optimal relationship of the text. To further improve the effect, the input layer is optimized by feature fusion, and the learning rate is optimized by the cosine annealing algorithm. The experimental results show that, using the small balanced data set, the F1 value of the RBF model proposed in the paper is 25.9% higher than the traditional Word2vec–BiGRU–FC model. It is 18.6% higher than the recent Bert–BiLSTM (Bidirectional Long Short Term Memory)–FC model. The experimental results show that our model is effective.
Effect of the Gap between Cemented Posts and Remaining Gutta-Percha on the Clinical Outcome of Endodontically Treated Teeth Managed by Undergraduate Dental Students: A Prospective Study with 4 Years of Follow-Up
Authors: Sayed Mohammed E. , Ahmad Manawar , Naim Hina , Jokhadar Hossam F. , AlResayes Saad Saleh , Alqahtani Nasser M. , Alqahtani Saeed M. , Hothan Halah Mohammed , Faqihi Jibreel A. , Othman Maha Abdu , Alaqi Halah A. , Daak Huda Ali , Hakami Nardeen , Masmali Amal M. , Hakami Malak Ibrahim
Published: June 2023

It is common to detect a gap between the apical portion of the post and the most coronal part of gutta-percha in a root canal during post and core treatment in endodontically treated teeth. It may compromise the seal that gutta-percha material provides in the root canal filling, leading to apical leakage, which is often thought to be one of the most common causes for failure of endodontic treatment. The prevention of apical leakage to achieve a complete apical seal and its effect on periapical health of endodontically treated teeth of post and core in long term clinical research remains unanswered. Post and core treatment were provided to 100 patients by undergraduate students in the year 2016–2017. A total of 70 patients in all were called back to the Prosthodontic Clinic for follow-up care after 4 years to assess the clinical result in terms of the gap between the post-operative and residual gutta-percha. The cemented posts were divided into three groups depending on the space between the cemented post end and the remaining gutta-percha: group I revealed no gaps, group II revealed gaps between >0.1 and 1 mm, and group III revealed gaps more than 1 mm. The periapical index (PAI) was used to determine the apical condition of each tooth. Chi-square test was used for evaluating the data, and a p-value of 0.05 was considered statistically significant. A total of 28.6% post and core treated teeth were found diseased while 71.4% teeth were found normal. In group I, 90% of the teeth and in group II, 66.7% of teeth were evaluated as normal; however, in group III, 41.2% teeth were found diseased. In endodontically treated teeth restored with a post and core, a gap between the apical end of the post and the coronal section of the residual gutta-percha was associated with a greater prevalence of disease. The post and core treatment by undergraduate students achieved a clinically acceptable outcome in terms of the gap between the post end and the remaining gutta-percha.
Insights into the Antimicrobial Potential of Acorn Extracts (Quercus ilex and Quercus suber)
Authors: Silva Sara , Machado Manuela , Coelho Marta , Costa Eduardo M. , Pintado Manuela
Published: June 2023

Acorns, frequently left uncollected in the fields, have been a part of the traditional medicine of different cultures. Among the different properties associated with them, their antimicrobial potential is of particular importance. However, this characterization has long been superficial and has not ventured into other topics such as biofilm inhibition. Thus, the current work aimed to characterize the antimicrobial and antibiofilm potential of an array of phenolic rich extracts attained from acorns, two different acorn varieties Q. ilex and Q. suber, considering the fruit and shell separately, fresh and after heat-treating the acorns to aid in the shelling process. To accomplish this, the extracts’ capacity to inhibit an array of different microorganisms was evaluated, the minimum bactericidal concentration (MBC) was determined, time-death curves were drawn whenever an MBC was found and the antibiofilm potential of the most effective extracts was drawn. The overall results showed that Gram-positive microorganisms were the most susceptible out of all the microorganisms tested, with the shell extracts being the most effective overall, exhibiting bactericidal effect against S. aureus, B. cereus and L. monocytogenes as well as being capable of inhibiting biofilm formation via the two S. aureus strains. The attained results demonstrated that acorn extracts, particularly shell extracts, pose an interesting antimicrobial activity which could be exploited in an array of food, cosmetic and pharmaceutical applications.
Atlantic Masters: Three Early Modern Afro-Brazilian Artists
Authors: Valerio Miguel A.
Published: June 2023

Brazil received the largest number of Africans enslaved into the Americas: nearly five million by some estimates. Thus, Brazil became the world’s largest slavocracy. But slavery was not the only experience available to Africans and Brazilians of African descent in slavery-era Brazil. Numerically, Afro-Brazilians dominated the arts in colonial Brazil. However, very few of those artists and artisans, many of whom were enslaved, are known by name today. Free Afro-Brazilian artists, such as Aleijadinho, Mestre Valentim, and Teófilo de Jesus, on the other hand, fared far better. In this article, I turn to these three mixed-race artists’ works and what little is known of their lives, not only as exemplary Afro-Brazilian artists but also as some of the most important artists of Brazil’s late colonial period, where they had the greatest impact on the artistic developments in their home regions. These artists’ careers thus illustrate how artists of African descent contributed to and defined urban and sacred spaces in the early modern Atlantic. This is therefore an invitation to look at Afrodescendants’ role in early modern art beyond the anonymity of slavery and static representation.
High-Order Above-Threshold Ionization Using a Bi-Elliptic Orthogonal Two-Color Laser Field with Optimal Field Parameters
Authors: Jašarević Abdulah S. , Hasović Elvedin , Milošević Dejan B.
Published: June 2023

In the present paper, we study the high-order above-threshold ionization of noble-gas atoms using a bi-elliptic orthogonal two-color (BEOTC) field. We give an overview of the SFA theory and calculate the differential ionization rate for various values of the laser field parameters. We show that the ionization rate strongly depends on the ellipticity and the relative phase between two field components. Using numerical optimization, we find the values of ellipticity and relative phase that maximize the ionization rate at energies close to the cutoff energy. To explain the obtained results, we present, to the best of our knowledge, for the first time the quantum-orbit analysis in the BEOTC field. We find and classify the saddle-point (SP) solutions and study their contributions to the total ionization rate. We analyze quantum orbits and corresponding velocities to explain the contribution of relevant SP solutions.
Quantum Control of a Nonlinear Time-Dependent Interaction of a Damped Three-Level Atom
Authors: Korashy Sameh , Abdel-Aty Mahmoud
Published: June 2023

We investigate some new aspects of the nonlinear interaction between a three-level Ξ-type atom and bimodal field. The photon-assisted atomic phase damping, detuning parameter, Kerr nonlinearity and the time-dependent coupling have been considered. The general solution has been obtained by using the Schrődinger equation when the atom and the field are initially prepared in the excited state and coherent state, respectively. The atomic population inversion and concurrence are discussed. It is shown that the time-dependent coupling parameter and the detuning parameter can be considered as quantum controller parameters of the atomic population inversion and quantum entanglement in the considered model.
Polysaccharides and Structural Proteins as Components in Three-Dimensional Scaffolds for Breast Cancer Tissue Models: A Review
Authors: Pasquier Eva , Rosendahl Jennifer , Solberg Amalie , Ståhlberg Anders , Håkansson Joakim , Chinga-Carrasco Gary
Published: June 2023

Breast cancer is the most common cancer among women, and even though treatments are available, efficiency varies with the patients. In vitro 2D models are commonly used to develop new treatments. However, 2D models overestimate drug efficiency, which increases the failure rate in later phase III clinical trials. New model systems that allow extensive and efficient drug screening are thus required. Three-dimensional printed hydrogels containing active components for cancer cell growth are interesting candidates for the preparation of next generation cancer cell models. Macromolecules, obtained from marine- and land-based resources, can form biopolymers (polysaccharides such as alginate, chitosan, hyaluronic acid, and cellulose) and bioactive components (structural proteins such as collagen, gelatin, and silk fibroin) in hydrogels with adequate physical properties in terms of porosity, rheology, and mechanical strength. Hence, in this study attention is given to biofabrication methods and to the modification with biological macromolecules to become bioactive and, thus, optimize 3D printed structures that better mimic the cancer cell microenvironment. Ink formulations combining polysaccharides for tuning the mechanical properties and bioactive polymers for controlling cell adhesion is key to optimizing the growth of the cancer cells.
Objective Evaluation of Active Interactions between the Operator and Display Screen Equipment Using an Innovative Acquisition System
Authors: De Palma Giuseppe , Sala Emma , Rubino Sofia , Dalola Simone , Ferrari Marco , Marioli Daniele , Apostoli Pietro , Tomasi Cesare , Righetti Francesca , Mattioli Flavia , Ferrari Vittorio
Published: June 2023

The occupational risk of operators using display screen equipment (DSE) is usually evaluated according to the extent of time spent in active operator–DSE interactions. Risk assessment is based on activity data collected through questionnaires. We evaluated an original and innovative system that can objectively assess active operator–DSE interactions by collecting electrical impulses generated by the activation of mouse, keyboard and a camera that collects attentive eye-screen fixation. The main aim of this study was to evaluate the system’s performance on an employee sample involved in the task of active reading and copying at a DSE workstation connected to the system. In the context of mandatory health surveillance at work, we enrolled 38 DSE operators with normal neuropsychological and eye assessments who were required to complete two predefined reading and writing tasks. The obtained results show that the system is able to collect activity data derived from operator–DSE interactions through screen fixation, keyboard tapping and mouse handling. In the copying task, the session duration as recorded by the system was highly related to the screen fixation time. In the copying task, mouse and keyboard activities were more strongly related to session duration than screen fixation. For the copying task, it was also possible to obtain individual profiles of operator–DSE interactions while performing the same standardized tasks. Collected data can allow an objective evaluation of active time spent by DSE operators at their workstations, thus allowing a more accurate occupational health risk assessment and management. Prospective analysis of individual operator–DSE interaction profiles can favor the setup of targeted preventive and organizational interventions from an of even wider worker wellbeing perspective.
Regulation of EMT Markers, Extracellular Matrix, and Associated Signalling Pathways by Long Non-Coding RNAs in Glioblastoma Mesenchymal Transition: A Scoping Review
Authors: Leung Dexter Hoi Long , Phon Brandon Wee Siang , Sivalingam Mageswary , Radhakrishnan Ammu Kutty , Kamarudin Muhamad Noor Alfarizal
Published: June 2023

Glioblastoma (GBM) mesenchymal (MES) transition can be regulated by long non-coding RNAs (lncRNAs) via modulation of various factors (Epithelial-to-Mesenchymal (EMT) markers, biological signalling, and the extracellular matrix (ECM)). However, understanding of these mechanisms in terms of lncRNAs is largely sparse. This review systematically analysed the mechanisms by which lncRNAs influence MES transition in GBM from a systematic search of the literature (using PRISMA) performed in five databases (PubMed, MEDLINE, EMBASE, Scopus, and Web of Science). We identified a total of 62 lncRNAs affiliated with GBM MES transition, of which 52 were upregulated and 10 were downregulated in GBM cells, where 55 lncRNAs were identified to regulate classical EMT markers in GBM (E-cadherin, N-cadherin, and vimentin) and 25 lncRNAs were reported to regulate EMT transcription factors (ZEB1, Snai1, Slug, Twist, and Notch); a total of 16 lncRNAs were found to regulate the associated signalling pathways (Wnt/β-catenin, PI3k/Akt/mTOR, TGFβ, and NF-κB) and 14 lncRNAs were reported to regulate ECM components (MMP2/9, fibronectin, CD44, and integrin-β1). A total of 25 lncRNAs were found dysregulated in clinical samples (TCGA vs. GTEx), of which 17 were upregulated and 8 were downregulated. Gene set enrichment analysis predicted the functions of HOXAS3, H19, HOTTIP, MEG3, DGCR5, and XIST at the transcriptional and translational levels based on their interacting target proteins. Our analysis observed that the MES transition is regulated by complex interplays between the signalling pathways and EMT factors. Nevertheless, further empirical studies are required to elucidate the complexity in this process between these EMT factors and the signalling involved in the GBM MES transition.
Quantifying Yeast Microtubules and Spindles Using the Toolkit for Automated Microtubule Tracking (TAMiT)
Authors: Ansari Saad , Gergely Zachary R. , Flynn Patrick , Li Gabriella , Moore Jeffrey K. , Betterton Meredith D.
Published: June 2023

Fluorescently labeled proteins absorb and emit light, appearing as Gaussian spots in fluorescence imaging. When fluorescent tags are added to cytoskeletal polymers such as microtubules, a line of fluorescence and even non-linear structures results. While much progress has been made in techniques for imaging and microscopy, image analysis is less well-developed. Current analysis of fluorescent microtubules uses either manual tools, such as kymographs, or automated software. As a result, our ability to quantify microtubule dynamics and organization from light microscopy remains limited. Despite the development of automated microtubule analysis tools for in vitro studies, analysis of images from cells often depends heavily on manual analysis. One of the main reasons for this disparity is the low signal-to-noise ratio in cells, where background fluorescence is typically higher than in reconstituted systems. Here, we present the Toolkit for Automated Microtubule Tracking (TAMiT), which automatically detects, optimizes, and tracks fluorescent microtubules in living yeast cells with sub-pixel accuracy. Using basic information about microtubule organization, TAMiT detects linear and curved polymers using a geometrical scanning technique. Images are fit via an optimization problem for the microtubule image parameters that are solved using non-linear least squares in Matlab. We benchmark our software using simulated images and show that it reliably detects microtubules, even at low signal-to-noise ratios. Then, we use TAMiT to measure monopolar spindle microtubule bundle number, length, and lifetime in a large dataset that includes several S. pombe mutants that affect microtubule dynamics and bundling. The results from the automated analysis are consistent with previous work and suggest a direct role for CLASP/Cls1 in bundling spindle microtubules. We also illustrate automated tracking of single curved astral microtubules in S. cerevisiae, with measurement of dynamic instability parameters. The results obtained with our fully-automated software are similar to results using hand-tracked measurements. Therefore, TAMiT can facilitate automated analysis of spindle and microtubule dynamics in yeast cells.