bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of Cellulose–Poly(Acrylic Acid) Using Sugarcane Bagasse Extracted Cellulose Fibres for the Removal of Heavy Metal Ions
Authors: Li Fuchao , Xie Zhemin , Wen Jianfeng , Tang Tao , Jiang Li , Hu Guanghui , Li Ming
Published: May 2023

In this study, sugarcane bagasse (SCB) was treated with sodium hydroxide and bleached to separate the non-cellulose components to obtain cellulose (CE) fibres. Cross-linked cellulose–poly(sodium acrylic acid) hydrogel (CE–PAANa) was successfully synthesised via simple free-radical graft-polymerisation to remove heavy metal ions. The structure and morphology of the hydrogel display an open interconnected porous structure on the surface of the hydrogel. Various factors influencing batch adsorption capacity, including pH, contact time, and solution concentration, were investigated. The results showed that the adsorption kinetics were in good agreement with the pseudo-second-order kinetic model and that the adsorption isotherms followed the Langmuir model. The maximum adsorption capacities calculated by the Langmuir model are 106.3, 333.3, and 163.9 mg/g for Cu(II), Pb(II), and Cd(II), respectively. Furthermore, X-ray photoelectron spectroscopy (XPS) and energy-dispersive X-ray spectrometry (EDS) results demonstrated that cationic exchange and electrostatic interaction were the main heavy metal ions adsorption mechanisms. These results demonstrate that CE–PAANa graft copolymer sorbents from cellulose-rich SCB can potentially be used for the removal of heavy metal ions.
Advances in Immunotherapy and Innovative Therapeutic Approaches for Cancer Treatment: Editorial to the Special Issue “State-of-the-Art Molecular Oncology in Italy”
Authors: Laudisi Federica , Stolfi Carmine
Published: May 2023

Cancer remains one of the most common causes of death worldwide, mainly due to late diagnosis and the lack of efficient therapeutic options for patients with advanced diseases [...]
Siphophage 0105phi7-2 of Bacillus thuringiensis: Novel Propagation, DNA, and Genome-Implied Assembly
Authors: Roberts Samantha M. , Aldis Miranda , Wright Elena T. , Gonzales Cara B. , Lai Zhao , Weintraub Susan T. , Hardies Stephen C. , Serwer Philip
Published: May 2023

Diversity of phage propagation, physical properties, and assembly promotes the use of phages in ecological studies and biomedicine. However, observed phage diversity is incomplete. Bacillus thuringiensis siphophage, 0105phi-7-2, first described here, significantly expands known phage diversity, as seen via in-plaque propagation, electron microscopy, whole genome sequencing/annotation, protein mass spectrometry, and native gel electrophoresis (AGE). Average plaque diameter vs. plaque-supporting agarose gel concentration plots reveal unusually steep conversion to large plaques as agarose concentration decreases below 0.2%. These large plaques sometimes have small satellites and are made larger by orthovanadate, an ATPase inhibitor. Phage head–host-cell binding is observed by electron microscopy. We hypothesize that this binding causes plaque size-increase via biofilm evolved, ATP stimulated ride-hitching on motile host cells by temporarily inactive phages. Phage 0105phi7-2 does not propagate in liquid culture. Genomic sequencing/annotation reveals history as temperate phage and distant similarity, in a virion-assembly gene cluster, to prototypical siphophage SPP1 of Bacillus subtilis. Phage 0105phi7-2 is distinct in (1) absence of head-assembly scaffolding via either separate protein or classically sized, head protein-embedded peptide, (2) producing partially condensed, head-expelled DNA, and (3) having a surface relatively poor in AGE-detected net negative charges, which is possibly correlated with observed low murine blood persistence.
Extent of N-Terminus Folding of Semenogelin 1 Cleavage Product Determines Tendency to Amyloid Formation
Authors: Osetrina Daria A. , Kusova Aleksandra M. , Bikmullin Aydar G. , Klochkova Evelina A. , Yulmetov Aydar R. , Semenova Evgenia A. , Mukhametzyanov Timur A. , Usachev Konstantin S. , Klochkov Vladimir V. , Blokhin Dmitriy S.
Published: May 2023

It is known that four peptide fragments of predominant protein in human semen Semenogelin 1 (SEM1) (SEM1(86–107), SEM1(68–107), SEM1(49–107) and SEM1(45–107)) are involved in fertilization and amyloid formation processes. In this work, the structure and dynamic behavior of SEM1(45–107) and SEM1(49–107) peptides and their N-domains were described. According to ThT fluorescence spectroscopy data, it was shown that the amyloid formation of SEM1(45–107) starts immediately after purification, which is not observed for SEM1(49–107). Seeing that the peptide amino acid sequence of SEM1(45–107) differs from SEM1(49–107) only by the presence of four additional amino acid residues in the N domain, these domains of both peptides were obtained via solid-phase synthesis and the difference in their dynamics and structure was investigated. SEM1(45–67) and SEM1(49–67) showed no principal difference in dynamic behavior in water solution. Furthermore, we obtained mostly disordered structures of SEM1(45–67) and SEM1(49–67). However, SEM1(45–67) contains a helix (E58-K60) and helix-like (S49-Q51) fragments. These helical fragments may rearrange into β-strands during amyloid formation process. Thus, the difference in full-length peptides’ (SEM1(45–107) and SEM1(49–107)) amyloid-forming behavior may be explained by the presence of a structured helix at the SEM1(45–107) N-terminus, which contributes to an increased rate of amyloid formation.
Spatial Gene Expression Analysis Reveals Characteristic Gene Expression Patterns of De Novo Neuroendocrine Prostate Cancer Coexisting with Androgen Receptor Pathway Prostate Cancer
Authors: Watanabe Ryuta , Miura Noriyoshi , Kurata Mie , Kitazawa Riko , Kikugawa Tadahiko , Saika Takashi
Published: May 2023

Neuroendocrine prostate carcinoma (NEPC) accounts for less than 1% of prostate neoplasms and has extremely poorer prognosis than the typical androgen receptor pathway-positive adenocarcinoma of the prostate (ARPC). However, very few cases in which de novo NEPC and APRC are diagnosed simultaneously in the same tissue have been reported. We report herein a 78-year-old man of de novo metastatic NEPC coexisting with ARPC treated at Ehime University Hospital. Visium CytAssist Spatial Gene Expression analysis (10× genetics) was performed using formalin-fixed, paraffin-embedded (FFPE) samples. The neuroendocrine signatures were upregulated in NEPC sites, and androgen receptor signatures were upregulated in ARPC sites. TP53, RB1, or PTEN and upregulation of the homologous recombination repair genes at NEPC sites were not downregulated. Urothelial carcinoma markers were not elevated. Meanwhile, Rbfox3 and SFRTM2 levels were downregulated while the levels of the fibrosis markers HGF, HMOX1, ELN, and GREM1 were upregulated in the tumor microenvironment of NEPC. In conclusion, the findings of spatial gene expression analysis in a patient with coexisting ARPC and de novo NEPC are reported. The accumulation of cases and basic data will help with the development of novel treatments for NEPC and improve the prognosis of patients with castration-resistant prostate cancer.
Impact of Chronic Oral Administration of Gold Nanoparticles on Cognitive Abilities of Mice
Authors: Ivlieva Alexandra L. , Petritskaya Elena N. , Rogatkin Dmitriy A. , Zinicovscaia Inga , Yushin Nikita , Grozdov Dmitrii
Published: May 2023

The influence of gold nanoparticles after their prolonged oral administration to mice (during pregnancy and lactation) on spatial memory and anxiety levels in offspring was investigated. Offspring were tested in the Morris water maze and in the elevated Plus-maze. The average specific mass content of gold which crossed the blood–brain barrier was measured using neutron activation analysis and constituted 3.8 ng/g for females and 1.1 ng/g for offspring. Experimental offspring showed no differences in spatial orientation and memory compared to the control, while their anxiety levels increased. Gold nanoparticles influenced the emotional state of mice exposed to nanoparticles during prenatal and early postnatal development, but not their cognitive abilities.
SIRT2 Deficiency Aggravates Diet-Induced Nonalcoholic Fatty Liver Disease through Modulating Gut Microbiota and Metabolites
Authors: Li Xingyu , Du Yimeng , Xue Chunyuan , Kang Xiaofeng , Sun Chao , Peng Huanyan , Fang Liaoxin , Han Yuchen , Xu Xiaojie , Zhao Caiyan
Published: May 2023

Non-alcoholic fatty liver disease (NAFLD), characterized by excessive lipid accumulation in hepatocytes, is an increasing global healthcare burden. Sirtuin 2 (SIRT2) functions as a preventive molecule for NAFLD with incompletely clarified regulatory mechanisms. Metabolic changes and gut microbiota imbalance are critical to the pathogenesis of NAFLD. However, their association with SIRT2 in NAFLD progression is still unknown. Here, we report that SIRT2 knockout (KO) mice are susceptible to HFCS (high-fat/high-cholesterol/high-sucrose)-induced obesity and hepatic steatosis accompanied with an aggravated metabolic profile, which indicates SIRT2 deficiency promotes NAFLD-NASH (nonalcoholic steatohepatitis) progression. Under palmitic acid (PA), cholesterol (CHO), and high glucose (Glu) conditions, SIRT2 deficiency promotes lipid deposition and inflammation in cultured cells. Mechanically, SIRT2 deficiency induces serum metabolites alteration including upregulation of L-proline and downregulation of phosphatidylcholines (PC), lysophosphatidylcholine (LPC), and epinephrine. Furthermore, SIRT2 deficiency promotes gut microbiota dysbiosis. The microbiota composition clustered distinctly in SIRT2 KO mice with decreased Bacteroides and Eubacterium, and increased Acetatifactor. In clinical patients, SIRT2 is downregulated in the NALFD patients compared with healthy controls, and is associated with exacerbated progression of normal liver status to NAFLD to NASH in clinical patients. In conclusion, SIRT2 deficiency accelerates HFCS-induced NAFLD-NASH progression by inducing alteration of gut microbiota and changes of metabolites.
Recent Progress of Cement-Based Materials Modified by Graphene and Its Derivatives
Authors: Li Houxuan , Zhao Ge , Zhang Hong
Published: May 2023

Graphene, with its excellent properties and unique structure, has been extensively studied in the context of modifiable cement-based materials. However, a systematic summary of the status of numerous experimental results and applications is lacking. Therefore, this paper reviews the graphene materials that improve the properties of cement-based materials, including workability, mechanical properties, and durability. The influence of graphene material properties, mass ratio, and curing time on the mechanical properties and durability of concrete is discussed. Furthermore, graphene’s applications in improving interfacial adhesion, enhancing electrical and thermal conductivity of concrete, absorbing heavy metal ions, and collecting building energy are introduced. Finally, the existing issues in current study are analyzed, and the future development trends are foreseen.
Electric and Magnetic Properties of the Multiferroic Composites Made Based on Pb(Fe1/2Nb1/2)1−xMnxO3 and the Nickel-Zinc Ferrite
Authors: Bochenek Dariusz , Chrobak Artur , Ziółkowski Grzegorz
Published: May 2023

This work presents the electrophysical properties of the multiferroic ceramic composites obtained as a result of combining both magnetic and ferroelectric material. The ferroelectric components of the composite are materials with the following chemical formulas: PbFe0.5Nb0.5O3 (PFN), Pb(Fe0.495Nb0.495Mn0.01)O3 (PFNM1), and Pb(Fe0.49Nb0.49Mn0.02)O3 (PFNM2), while the magnetic component of the composite is the nickel-zinc ferrite (Ni0.64Zn0.36Fe2O4 marked as F). The crystal structure, microstructure, DC electric conductivity, and ferroelectric, dielectric, magnetic, and piezoelectric properties of the multiferroic composites are performed. The conducted tests confirm that the composite samples have good dielectric and magnetic properties at room temperature. Multiferroic ceramic composites have a two-phase crystal structure (ferroelectric from a tetragonal system and magnetic from a spinel structure) without a foreign phase. Composites with an admixture of manganese have a better set of functional parameters. The manganese admixture increases the microstructure’s homogeneity, improves the magnetic properties, and reduces the electrical conductivity of composite samples. On the other hand, in the case of electric permittivity, a decrease in the maximum values of εm is observed with an increase in the amount of manganese in the ferroelectric component of composite compositions. However, the dielectric dispersion at high temperatures (associated with high conductivity) disappears.
A Bimetallic Organic Framework with Mn in MIL-101(Cr) for Lithium–Sulfur Batteries
Authors: Chen Shuo , Zhang Zhengfu , Wang Jinsong , Dong Peng
Published: May 2023

Lithium–sulfur batteries (LSBs) show excellent performance in terms of specific capacity and energy density. However, the cyclic stability of LSBs is compromised due to the “shuttle effect”, which hinders the practical applications of LSBs. Herein, a metal–organic framework (MOF) based on Cr ions as the main body composition, commonly known as MIL-101(Cr), was utilized to minimize the shuttle effect and improve the cyclic performance of LSBs. To obtain MOFs with a certain adsorption capacity for lithium polysulfide and a certain catalytic capacity, we propose an effective strategy of incorporating sulfur-loving metal ions (Mn) into the skeleton to enhance the reaction kinetics at the electrode. Based on the oxidation doping method, Mn2+ was uniformly dispersed in MIL-101(Cr) to produce bimetallic Cr2O3/MnOx as a novel sulfur-carrying cathode material. Then, a sulfur injection process was carried out by melt diffusion to obtain the sulfur-containing Cr2O3/MnOx-S electrode. Moreover, an LSB assembled with Cr2O3/MnOx-S showed improved first-cycle discharge (1285 mAh·g−1 at 0.1 C) and cyclic performance (721 mAh·g−1 at 0.1 C after 100 cycles), and the overall performance was much better than that of monometallic MIL-101(Cr) as a sulfur carrier. These results revealed that the physical immobilization method of MIL-101(Cr) positively affected the adsorption of polysulfides, while the bimetallic composite Cr2O3/MnOx formed by the doping of sulfur-loving Mn2+ into the porous MOF produced a good catalytic effect during LSB charging. This research provides a novel approach for preparing efficient sulfur-containing materials for LSBs.
A Modified Constitutive Model and Microstructure Characterization for 2195 Al-Li Alloy Hot Extrusion
Authors: Li Hui , Wang Jian , Huang Yuanchun , Fu Rong
Published: May 2023

The quality of extruded profiles depends largely on accurate constitutive models and thermal processing maps. In this study, a modified Arrhenius constitutive model for homogenized 2195 Al-Li alloy with multi-parameter co-compensation was developed and further enhanced the prediction accuracy of flow stresses. Through the processing map and microstructure characterization, the 2195 Al-Li alloy could be deformed optimally at the temperature range of 710~783 K and strain rate of 0.001~0.12 s−1, preventing the occurrence of local plastic flow and abnormal growth of recrystallized grains. The accuracy of the constitutive model was verified through numerical simulation of 2195 Al-Li alloy extruded profiles with large shaped cross-sections. Dynamic recrystallization occurred at different regions during the practical extrusion process, resulting in slight variations in the microstructure. The differences in microstructure were due to the varying degrees of temperature and stress experienced by the material in different regions.
Photoprotective and Anti-Aging Properties of the Apical Frond Extracts from the Mediterranean Seaweed Ericaria amentacea
Authors: Mirata Serena , Asnaghi Valentina , Chiantore Mariachiara , Salis Annalisa , Benvenuti Mirko , Damonte Gianluca , Scarfì Sonia
Published: May 2023

There is a growing interest in using brown algal extracts thanks to the bioactive substances they produce for adaptation to the marine benthic environment. We evaluated the anti-aging and photoprotective properties of two types of extracts (50%-ethanol and DMSO) obtained from different portions, i.e., apices and thalli, of the brown seaweed, Ericaria amentacea. The apices of this alga, which grow and develop reproductive structures during summer when solar radiation is at its peak, were postulated to be rich in antioxidant compounds. We determined the chemical composition and pharmacological effects of their extracts and compared them to the thallus-derived extracts. All the extracts contained polyphenols, flavonoids and antioxidants and showed significant biological activities. The hydroalcoholic apices extracts demonstrated the highest pharmacological potential, likely due to the higher content of meroditerpene molecular species. They blocked toxicity in UV-exposed HaCaT keratinocytes and L929 fibroblasts and abated the oxidative stress and the production of pro-inflammatory cytokines, typically released after sunburns. Furthermore, the extracts showed anti-tyrosinase and anti-hydrolytic skin enzyme activity, counteracting the collagenase and hyaluronidase degrading activities and possibly slowing down the formation of uneven pigmentation and wrinkles in aging skin. In conclusion, the E. amentacea apices derivatives constitute ideal components for counteracting sunburn symptoms and for cosmetic anti-aging lotions.
Integration of Water Quantity/Quality Needs with Socio-Economical Issues: A Focus on Monitoring and Modelling
Authors: Copetti Diego
Published: May 2023

Freshwater is essential for a multitude of different uses, including drinking supply, irrigation, and energy production [...]
Deep Q-Learning-Based Buffer-Aided Relay Selection for Reliable and Secure Communications in Two-Hop Wireless Relay Networks
Authors: Zhang Cheng , Liao Xuening , Wu Zhenqiang , Qiu Guoyong , Chen Zitong , Yu Zhiliang
Published: May 2023

This paper investigates the problem of buffer-aided relay selection to achieve reliable and secure communications in a two-hop amplify-and-forward (AF) network with an eavesdropper. Due to the fading of wireless signals and the broadcast nature of wireless channels, transmitted signals over the network may be undecodable at the receiver end or have been eavesdropped by eavesdroppers. Most available buffer-aided relay selection schemes consider either reliability or security issues in wireless communications; rarely is work conducted on both reliability and security issues. This paper proposes a buffer-aided relay selection scheme based on deep Q-learning (DQL) that considers both reliability and security. By conducting Monte Carlo simulations, we then verify the reliability and security performances of the proposed scheme in terms of the connection outage probability (COP) and secrecy outage probability (SOP), respectively. The simulation results show that two-hop wireless relay network can achieve reliable and secure communications by using our proposed scheme. We also performed comparison experiments between our proposed scheme and two benchmark schemes. The comparison results indicate that our proposed scheme outperforms the max-ratio scheme in terms of the SOP.
IoT System for Real-Time Posture Asymmetry Detection
Authors: La Mura Monica , De Gregorio Marco , Lamberti Patrizia , Tucci Vincenzo
Published: May 2023

The rise of the Internet of Things (IoT) has enabled the development of measurement systems dedicated to preventing health issues and monitoring conditions in smart homes and workplaces. IoT systems can support monitoring people doing computer-based work and avoid the insurgence of common musculoskeletal disorders related to the persistence of incorrect sitting postures during work hours. This work proposes a low-cost IoT measurement system for monitoring the sitting posture symmetry and generating a visual alert to warn the worker when an asymmetric position is detected. The system employs four force sensing resistors (FSR) embedded in a cushion and a microcontroller-based read-out circuit for monitoring the pressure exerted on the chair seat. Java-based software performs the real-time monitoring of the sensors’ measurements and implements an uncertainty-driven asymmetry detection algorithm. The shifts from a symmetric to an asymmetric posture and vice versa generate and close a pop-up warning message, respectively. In this way, the user is promptly notified when an asymmetric posture is detected and invited to adjust the sitting position. Every position shift is recorded in a web database for further analysis of the sitting behavior.
Deep Learning Techniques for Vehicle Detection and Classification from Images/Videos: A Survey
Authors: Berwo Michael Abebe , Khan Asad , Fang Yong , Fahim Hamza , Javaid Shumaila , Mahmood Jabar , Abideen Zain Ul , M.S. Syam
Published: May 2023

Detecting and classifying vehicles as objects from images and videos is challenging in appearance-based representation, yet plays a significant role in the substantial real-time applications of Intelligent Transportation Systems (ITSs). The rapid development of Deep Learning (DL) has resulted in the computer-vision community demanding efficient, robust, and outstanding services to be built in various fields. This paper covers a wide range of vehicle detection and classification approaches and the application of these in estimating traffic density, real-time targets, toll management and other areas using DL architectures. Moreover, the paper also presents a detailed analysis of DL techniques, benchmark datasets, and preliminaries. A survey of some vital detection and classification applications, namely, vehicle detection and classification and performance, is conducted, with a detailed investigation of the challenges faced. The paper also addresses the promising technological advancements of the last few years.
A High-Precision Real-Time Pose Measurement Method for the Primary Lens of Large Aperture Space Telescope Based on Laser Ranging
Authors: Shi Heng , Du Junfeng , Wang Lihua , Bian Jiang , Gao Guohan , Liu Dun , Fan Bin , Yang Hu
Published: May 2023

The aperture of space telescopes increases with their required resolution, and the transmission optical systems with long focal length and diffractive primary lens are becoming increasingly popular. In space, the changes in the pose of the primary lens relative to the rear lens group have a significant impact on the imaging performance of the telescope system. The measurement of the pose of the primary lens in real-time and with high-precision is one of the important techniques for a space telescope. In this paper, a high-precision real-time pose measurement method for the primary lens of a space telescope in orbit based on laser ranging is proposed, and a verification system is established. The pose change of the telescope’s primary lens can be easily calculated through six high-precision laser distance changes. The measurement system can be installed freely, which solves the problems of complex system structure and low measurement accuracy in traditional pose measurement techniques. Analysis and experiments show that this method can accurately obtain the pose of the primary lens in real-time. The rotation error of the measurement system is 2 × 10−5 degrees (0.072 arcsecs), and the translation error is 0.2 μm. This study will provide a scientific basis for high-quality imaging of a space telescope.
X-band MMICs for a Low-Cost Radar Transmit/Receive Module in 250 nm GaN HEMT Technology
Authors: Lee Hyeonseok , Park Hyeong-Geun , Le Van-Du , Nguyen Van-Phu , Song Jeong-Moon , Lee Bok-Hyung , Park Jung-Dong
Published: May 2023

This paper describes Monolithic Microwave Integrated Circuits (MMICs) for an X-band radar transceiver front-end implemented in 0.25 μm GaN High Electron Mobility Transistor (HEMT) technology. Two versions of single pole double throw (SPDT) T/R switches are introduced to realize a fully GaN-based transmit/receive module (TRM), each of which achieves an insertion loss of 1.21 dB and 0.66 dB at 9 GHz, IP1dB higher than 46.3 dBm and 44.7 dBm, respectively. Therefore, it can substitute a lossy circulator and limiter used for a conventional GaAs receiver. A driving amplifier (DA), a high-power amplifier (HPA), and a robust low-noise amplifier (LNA) are also designed and verified for a low-cost X-band transmit-receive module (TRM). For the transmitting path, the implemented DA achieves a saturated output power (Psat) of 38.0 dBm and output 1-dB compression (OP1dB) of 25.84 dBm. The HPA reaches a Psat of 43.0 dBm and power-added efficiency (PAE) of 35.6%. For the receiving path, the fabricated LNA measures a small-signal gain of 34.9 dB and a noise figure of 2.56 dB, and it can endure higher than 38 dBm input power in the measurement. The presented GaN MMICs can be useful in implementing a cost-effective TRM for Active Electronically Scanned Array (AESA) radar systems at X-band.
An Energy-Efficient Sensing Matrix for Wireless Multimedia Sensor Networks
Authors: Skosana Vusi , Abu-Mahfouz Adnan
Published: May 2023

A measurement matrix is essential to compressed sensing frameworks. The measurement matrix can establish the fidelity of a compressed signal, reduce the sampling rate demand, and enhance the stability and performance of the recovery algorithm. Choosing a suitable measurement matrix for Wireless Multimedia Sensor Networks (WMSNs) is demanding because there is a sensitive weighing of energy efficiency against image quality that must be performed. Many measurement matrices have been proposed to deliver low computational complexity or high image quality, but only some have achieved both, and even fewer have been proven beyond doubt. A Deterministic Partial Canonical Identity (DPCI) matrix is proposed that has the lowest sensing complexity of the leading energy-efficient sensing matrices while offering better image quality than the Gaussian measurement matrix. The simplest sensing matrix is the basis of the proposed matrix, where random numbers were replaced with a chaotic sequence, and the random permutation was replaced with random sample positions. The novel construction significantly reduces the computational complexity as well time complexity of the sensing matrix. The DPCI has lower recovery accuracy than other deterministic measurement matrices such as the Binary Permuted Block Diagonal (BPBD) and Deterministic Binary Block Diagonal (DBBD) but offers a lower construction cost than the BPBD and lower sensing cost than the DBBD. This matrix offers the best balance between energy efficiency and image quality for energy-sensitive applications.
Explainability-Informed Feature Selection and Performance Prediction for Nonintrusive Load Monitoring
Authors: Mollel Rachel Stephen , Stankovic Lina , Stankovic Vladimir
Published: May 2023

With the massive, worldwide, smart metering roll-out, both energy suppliers and users are starting to tap into the potential of higher resolution energy readings for accurate billing, improved demand response, improved tariffs better tuned to users and the grid, and empowering end-users to know how much their individual appliances contribute to their electricity bills via nonintrusive load monitoring (NILM). A number of NILM approaches, based on machine learning (ML), have been proposed over the years, focusing on improving the NILM model performance. However, the trustworthiness of the NILM model itself has hardly been addressed. It is important to explain the underlying model and its reasoning to understand why the model underperforms in order to satisfy user curiosity and to enable model improvement. This can be done by leveraging naturally interpretable or explainable models as well as explainability tools. This paper adopts a naturally interpretable decision tree (DT)-based approach for a NILM multiclass classifier. Furthermore, this paper leverages explainability tools to determine local and global feature importance, and design a methodology that informs feature selection for each appliance class, which can determine how well a trained model will predict an appliance on any unseen test data, minimising testing time on target datasets. We explain how one or more appliances can negatively impact classification of other appliances and predict appliance and model performance of the REFIT-data trained models on unseen data of the same house and on unseen houses on the UK-DALE dataset. Experimental results confirm that models trained with the explainability-informed local feature importance can improve toaster classification performance from 65% to 80%. Additionally, instead of one five-classifier approach incorporating all five appliances, a three-classifier approach comprising a kettle, microwave, and dishwasher and a two-classifier comprising a toaster and washing machine improves classification performance for the dishwasher from 72% to 94% and the washing machine from 56% to 80%.
Secure and Reliable Big-Data-Based Decision Making Using Quantum Approach in IIoT Systems
Authors: EL Azzaoui Abir , Salim Mikail Mohammed , Park Jong Hyuk
Published: May 2023

Nowadays, the industrial Internet of things (IIoT) and smart factories are relying on intelligence and big data analytics for large-scale decision making. Yet, this method is facing critical challenges regarding computation and data processing due to the complexity and heterogeneous nature of big data. Smart factory systems rely primarily on the analysis results to optimize production, predict future market directions, prevent and manage risks, and so on. However, deploying the existing classical solutions such as machine learning, cloud, and AI is not effective anymore. Smart factory systems and industries need novel solutions to sustain their development. On the other hand, with the fast development of quantum information systems (QISs), multiple sectors are studying the opportunities and challenges of implementing quantum-based solutions for a more efficient and exponentially faster processing time. To this end, in this paper, we discuss the implementation of quantum solutions for reliable and sustainable IIoT-based smart factory development. We depict various applications where quantum algorithms could improve the scalability and productivity of IIoT systems. Moreover, we design a universal system model where smart factories would not need to acquire quantum computers to run quantum algorithms based on their needs; instead, they can use quantum cloud servers and quantum terminals implemented at the edge layer to help them run the desired quantum algorithms without the need of an expert. To prove the feasibility of our model, we implement two real-world case studies and evaluate their performance. The analysis shows the benefits of quantum solutions in different sectors of smart factories.
Automatic Identification of Ultrasound Images of the Tibial Nerve in Different Ankle Positions Using Deep Learning
Authors: Kawanishi Kengo , Kakimoto Akihiro , Anegawa Keisuke , Tsutsumi Masahiro , Yamaguchi Isao , Kudo Shintarou
Published: May 2023

Peripheral nerve tension is known to be related to the pathophysiology of neuropathy; however, assessing this tension is difficult in a clinical setting. In this study, we aimed to develop a deep learning algorithm for the automatic assessment of tibial nerve tension using B-mode ultrasound imaging. To develop the algorithm, we used 204 ultrasound images of the tibial nerve in three positions: the maximum dorsiflexion position and −10° and −20° plantar flexion from maximum dorsiflexion. The images were taken of 68 healthy volunteers who did not have any abnormalities in the lower limbs at the time of testing. The tibial nerve was manually segmented in all images, and 163 cases were automatically extracted as the training dataset using U-Net. Additionally, convolutional neural network (CNN)-based classification was performed to determine each ankle position. The automatic classification was validated using five-fold cross-validation from the testing data composed of 41 data points. The highest mean accuracy (0.92) was achieved using manual segmentation. The mean accuracy of the full auto-classification of the tibial nerve at each ankle position was more than 0.77 using five-fold cross-validation. Thus, the tension of the tibial nerve can be accurately assessed with different dorsiflexion angles using an ultrasound imaging analysis with U-Net and a CNN.
The Practice of Detecting Potential Cosmic Rays Using CMOS Cameras: Hardware and Algorithms
Authors: Hachaj Tomasz , Piekarczyk Marcin
Published: May 2023

In this paper, we discuss a practice of potential cosmic ray detection using off-the-shelves CMOS cameras. We discuss and presents the limitations of up-to-date hardware and software approaches to this task. We also present a hardware solution that we made for long-term testing of algorithms for potential cosmic ray detection. We have also proposed, implemented and tested a novel algorithm that enables real-time processing of image frames acquired by CMOS cameras in order to detect tracks of potential particles. We have compared our results with already published results and obtained acceptable results overcoming some limitation of already existing algorithms. Both source codes and data are available to download.
A Wearable Multi-Modal Digital Upper Limb Assessment System for Automatic Musculoskeletal Risk Evaluation
Authors: Tahir Abdullah , Bai Shaoping , Shen Ming
Published: May 2023

Continuous ergonomic risk assessment of the human body is critical to avoid various musculoskeletal disorders (MSDs) for people involved in physical jobs. This paper presents a digital upper limb assessment (DULA) system that automatically performs rapid upper limb assessment (RULA) in real-time for the timely intervention and prevention of MSDs. While existing approaches require human resources for computing the RULA score, which is highly subjective and untimely, the proposed DULA achieves automatic and objective assessment of musculoskeletal risks using a wireless sensor band embedded with multi-modal sensors. The system continuously tracks and records upper limb movements and muscle activation levels and automatically generates musculoskeletal risk levels. Moreover, it stores the data in a cloud database for in-depth analysis by a healthcare expert. Limb movements and muscle fatigue levels can also be visually seen using any tablet/computer in real-time. In the paper, algorithms of robust limb motion detection are developed, and an explanation of the system is provided along with the presentation of preliminary results, which validate the effectiveness of the new technology.
Generating Defective Epoxy Drop Images for Die Attachment in Integrated Circuit Manufacturing via Enhanced Loss Function CycleGAN
Authors: Alam Lamia , Kehtarnavaz Nasser
Published: May 2023

In integrated circuit manufacturing, defects in epoxy drops for die attachments are required to be identified during production. Modern identification techniques based on vision-based deep neural networks require the availability of a very large number of defect and non-defect epoxy drop images. In practice, however, very few defective epoxy drop images are available. This paper presents a generative adversarial network solution to generate synthesized defective epoxy drop images as a data augmentation approach so that vision-based deep neural networks can be trained or tested using such images. More specifically, the so-called CycleGAN variation of the generative adversarial network is used by enhancing its cycle consistency loss function with two other loss functions consisting of learned perceptual image patch similarity (LPIPS) and a structural similarity index metric (SSIM). The results obtained indicate that when using the enhanced loss function, the quality of synthesized defective epoxy drop images are improved by 59%, 12%, and 131% for the metrics of the peak signal-to-noise ratio (PSNR), universal image quality index (UQI), and visual information fidelity (VIF), respectively, compared to the CycleGAN standard loss function. A typical image classifier is used to show the improvement in the identification outcome when using the synthesized images generated by the developed data augmentation approach.
Electrocortical Dynamics of Usual Walking and the Planning to Step over Obstacles in Parkinson’s Disease
Authors: Vitório Rodrigo , Lirani-Silva Ellen , Orcioli-Silva Diego , Beretta Victor Spiandor , Oliveira Anderson Souza , Gobbi Lilian Teresa Bucken
Published: May 2023

The neural correlates of locomotion impairments observed in people with Parkinson’s disease (PD) are not fully understood. We investigated whether people with PD present distinct brain electrocortical activity during usual walking and the approach phase of obstacle avoidance when compared to healthy individuals. Fifteen people with PD and fourteen older adults walked overground in two conditions: usual walking and obstacle crossing. Scalp electroencephalography (EEG) was recorded using a mobile 64-channel EEG system. Independent components were clustered using a k-means clustering algorithm. Outcome measures included absolute power in several frequency bands and alpha/beta ratio. During the usual walk, people with PD presented a greater alpha/beta ratio in the left sensorimotor cortex than healthy individuals. While approaching obstacles, both groups reduced alpha and beta power in the premotor and right sensorimotor cortices (balance demand) and increased gamma power in the primary visual cortex (visual demand). Only people with PD reduced alpha power and alpha/beta ratio in the left sensorimotor cortex when approaching obstacles. These findings suggest that PD affects the cortical control of usual walking, leading to a greater proportion of low-frequency (alpha) neuronal firing in the sensorimotor cortex. Moreover, the planning for obstacle avoidance changes the electrocortical dynamics associated with increased balance and visual demands. People with PD rely on increased sensorimotor integration to modulate locomotion.
A Return to the Sextant—Maritime Navigation Using Celestial Bodies and the Horizon
Authors: Critchley-Marrows Joshua J. R. , Mortari Daniele
Published: May 2023

Satellite navigation over recent decades has become the default and, in some cases, sole source of positioning for maritime vessels. The classic sextant has been all but forgotten by a significant number of ship navigators. However, recent risks to RF-derived positioning by jamming and spoofing have resurfaced the need to train sailors again in the art. Innovations in space optical navigation have long been perfecting the art of using celestial bodies and horizons to determine a space vessel’s attitude and position. This paper explores their application to the much older ship navigation problem. Models are introduced that utilize the stars and horizon to derive latitude and longitude. When assuming good star visibility conditions on the ocean, the accuracy delivered is at the 100 m level. This can meet requirements for ship navigation in coastal and oceanic voyages.
Assessment of a UWB Real Time Location System for Dairy Cows’ Monitoring
Authors: D’Urso Provvidenza Rita , Arcidiacono Claudia , Pastell Matti , Cascone Giovanni
Published: May 2023

In the field of precision livestock farming, many systems have been developed to identify the position of each cow of the herd individually in a specific environment. Challenges still exist in assessing the adequacy of the available systems to monitor individual animals in specific environments, and in the design of new systems. The main purpose of this research was to evaluate the performance of the SEWIO ultrawide-band (UWB) real time location system for the identification and localisation of cows during their activity in the barn through preliminary analyses in laboratory conditions. The objectives included the quantification of the errors performed by the system in laboratory conditions, and the assessment of the suitability of the system for real time monitoring of cows in dairy barns. The position of static and dynamic points was monitored in different experimental set-ups in the laboratory by the use of six anchors. Then, the errors related to a specific movement of the points were computed and statistical analyses were carried out. In detail, the one-way analysis of variance (ANOVA) was applied in order to assess the equality of the errors for each group of points in relation to their positions or typology, i.e., static or dynamic. In the post-hoc analysis, the errors were separated by Tukey’s honestly significant difference at p > 0.05. The results of the research quantify the errors related to a specific movement (i.e., static and dynamic points) and the position of the points (i.e., central area, perimeter of the investigated area). Based on the results, specific information is provided for the installation of the SEWIO in dairy barns as well as the monitoring of the animal behaviour in the resting area and the feeding area of the breeding environment. The SEWIO system could be a valuable support for farmers in herd management and for researchers in the analysis of animal behavioural activities.
Literary and journalistic activities of the Kharkiv educational center at the beginning of the 19th century in the research of Ivan Yerofeiv
Authors:   Mariupol State University, Melnychuk Iryna
Published: May 2023

The article analyzes the literary and critical works of Ivan Yerofeiv, dedicated to the activities of Vasyl Maslovich, a Kharkiv writer, journalist, founder of the Kharkiv Demokrit journal. The manuscripts studied by Erofeiv contain valuable information that determines the role and place of V. Maslovych in the process of the formation of the Kharkiv educational center, Ukrainian literature and journalism. The researcher's attention is focused on the nature of the journal's publications, the subject matter and nature of the artistic and journalistic works published in "Kharkiv Demokrit". I. Erofeiv singled out two currents in young Slobojan journalism which are scientific and ethnographic and satirical. Maslovich's journal also belonged to the latter. However, not only parodic and satirical works were published in Kharkiv Demokrit. The employees of the journal were mostly people with writing skills, whom Maslovich managed to drag to him from "Ukrainian Herald" and "Ukrainian Journal". Therefore, "Demokrit" was not so much a journal as a book for reading, created by a group of young writers from Slobojan. Among them are Y.M. Nakhimov and G.F. Kvitka who entered the history of Ukrainian literature. Therefore, when evaluating the publication, according to Yerofeiv, one should look for the "imprint" of contemporary Ukrainian literature in general in his work. Literary and philanthropic centers were located in landowners' estates, such as V. Tarnavskyi's Kachanivka, D. Troshchynskyi's Kibintsi, and O. Palitsyn's Popivka. Popular in these circles was the romanticization of Ukraine's past and light, shallow pictures from its present. It was this style that the first Slobozhan journalist had to focus on. I. Erofeiv's investigations about V. Maslovych are valuable primarily because the scientist drew attention to a far from "textbook" figure whose contribution to the development of Ukrainian culture deserves high appreciation. It is characteristic that in the studies about V. Maslovych I. Yerofeiv often emphasizes the true Ukrainian patriotism of the writer and journalist who stood in defence of the rights of the most disadvantaged strata of the Ukrainian population.
THE IMAGE OF A WOMAN IN MODERN UKRAINIAN POETRY (COLLECTION OF MARIA MASH «TODAY DEFINITELY NOT»)
Authors:   Institute of Literature of the National Academy of Sciences of Ukraine, Havryliuk Nadiia
Published: May 2023

The article examines the features of the image of a woman in the debut collection of Maria Mash from Lviv, «Today Definitely Not». It was found that this image does not fit into the thematic scheme: a lonely woman / a woman in love / a beloved woman. Because loneliness for the lyrical heroine is not the absence of a loved one, but the lack of understanding with him. Hence the need to find the exact word to describe feelings in order to form a common language of love. The image of a woman in M. Mash's collection is, at first glance, quite traditional (family welfare is in her hands, she rejoices in her husband's success and feels created for his happiness, and in her husband she sees her protection and partner for the «dance of life»). At the same time, this female image is individualized in the expression of emotions (for example, there are at least 14 types of love). Despite the fact that the woman in M. Mash's poetry is deeply feminine (she aspires to romance, has a chivalrous attitude towards herself, beauty and an ideal), she can only be called a romantic woman. Harmony in relationships is very important for the lyrical heroine, but no less weighty – the harmony of daily existence (so «today» is a whole life), a sense of inner balance and creative realization. Although the lyrical heroine of Maria Mash's debut collection invites her husband to dance, she does not allow him to control her thoughts and emotions. The woman from Maria Mash's poetry reveals herself to be self-sufficient, single-handedly changing the world for the better. The analysis of the image of a woman in the collection «Today Definitely Not» by Maria Mash proved the fundamental falsity of the binary opposition: «traditional/self-sufficient woman», which is common in feminist and gender studies.