bluuebunny/crossref_metadata_2025 huggingface dataset:
West Nile Virus Infection in Occupational Settings—A Systematic Review
Authors: Odigie Amienwanlen E. , Stufano Angela , Schino Valentina , Zarea Aya Attia Koraney , Ndiana Linda A. , Mrenoshki Daniela , Ugochukwu Iniobong C. I. , Lovreglio Piero , Greco Grazia , Pratelli Annamaria , Camero Michele , Tempesta Maria
Published: February 2024

Background: West Nile virus (WNV) is an emerging mosquito-borne neurotropic virus, belonging to the Flaviviridae family and the Orthoflavivirus genus. The effective control of WNV requires a targeted preventive strategy that also needs the identification of the higher-risk populations. Hence, this study focused on a systematic literature review of WNV-acquired infection in work-related settings and the assessment of the exposure risks among different occupational categories. Methods: A comprehensive search was conducted to identify studies until September 2023 in multiple databases such as PubMed/MEDLINE, SCOPUS and Web of Science, according to the PRISMA 2020 statement. Risk of bias of collected papers was assessed by the ROB tool of the National Toxicology Program’s Office of Health Assessment and Translation handbook. Results: A total of 21 studies were included in the systematic review, out of which seventeen were observational studies and four were case reports. Workers identified as at higher risk for WNV infection were military workers, veterinarians, agricultural workers, farmers, and laboratory workers with contact with infected fluids or aerosols. Conclusions: The identification of higher-risk workers could facilitate active surveillance by occupational physicians, which could improve our understanding of the epidemiology of WNV and, in addition, could help tailor appropriate preventive recommendations, reducing the overall burden of disease in high-risk areas.
Michelia compressa-Derived Santamarine Inhibits Oral Cancer Cell Proliferation via Oxidative Stress-Mediated Apoptosis and DNA Damage
Authors: Lu Hsin-I , Chen Kuan-Liang , Yen Ching-Yu , Chen Chung-Yi , Chien Tsu-Ming , Shu Chih-Wen , Chen Yu-Hsuan , Jeng Jiiang-Huei , Chen Bing-Hung , Chang Hsueh-Wei
Published: February 2024

The anti-oral cancer effects of santamarine (SAMA), a Michelia compressa var. compressa-derived natural product, remain unclear. This study investigates the anticancer effects and acting mechanism of SAMA against oral cancer (OC-2 and HSC-3) in parallel with normal (Smulow–Glickman; S-G) cells. SAMA selectively inhibits oral cancer cell viability more than normal cells, reverted by the oxidative stress remover N-acetylcysteine (NAC). The evidence of oxidative stress generation, such as the induction of reactive oxygen species (ROS) and mitochondrial superoxide and the depletion of mitochondrial membrane potential and glutathione, further supports this ROS-dependent selective antiproliferation. SAMA arrests oral cancer cells at the G2/M phase. SAMA triggers apoptosis (annexin V) in oral cancer cells and activates caspases 3, 8, and 9. SAMA enhances two types of DNA damage in oral cancer cells, such as γH2AX and 8-hydroxy-2-deoxyguanosine. Moreover, all of these anticancer mechanisms of SAMA are more highly expressed in oral cancer cells than in normal cells in concentration and time course experiments. These above changes are attenuated by NAC, suggesting that SAMA exerts mechanisms of selective antiproliferation that depend on oxidative stress while maintaining minimal cytotoxicity to normal cells.
Review of Advances in Coating and Functionalization of Gold Nanoparticles: From Theory to Biomedical Application
Authors: Arcos Rosero Wilmmer Alexander , Bueno Barbezan Angelica , Daruich de Souza Carla , Chuery Martins Rostelato Maria Elisa
Published: February 2024

Nanoparticles, especially gold nanoparticles (Au NPs) have gained increasing interest in biomedical applications. Used for disease prevention, diagnosis and therapies, its significant advantages in therapeutic efficacy and safety have been the main target of interest. Its application in immune system prevention, stability in physiological environments and cell membranes, low toxicity and optimal bioperformances are critical to the success of engineered nanomaterials. Its unique optical properties are great attractors. Recently, several physical and chemical methods for coating these NPs have been widely used. Biomolecules such as DNA, RNA, peptides, antibodies, proteins, carbohydrates and biopolymers, among others, have been widely used in coatings of Au NPs for various biomedical applications, thus increasing their biocompatibility while maintaining their biological functions. This review mainly presents a general and representative view of the different types of coatings and Au NP functionalization using various biomolecules, strategies and functionalization mechanisms.
Effect of Molecules’ Physicochemical Properties on Whey Protein/Alginate Hydrogel Rheology, Microstructure and Release Profile
Authors: Delanne-Cuménal A. , Lainé E. , Hoffart V. , Verney V. , Garrait G. , Beyssac E.
Published: February 2024

The encapsulation of molecules with different physicochemical properties (theophylline, blue dextran, salicylic acid and insulin) in whey protein (WP) and alginate (ALG) microparticles (MP) for oral administration was studied. MP based on WP/ALG were prepared by a cold gelation technique and coated with WP solution after reticulation. Molecules influenced polymer solution viscosity and elasticity, resulting in differences regarding encapsulation efficiency (from 23 to 100%), MP structure and swelling (>10%) and in terms of pH tested. Molecule release was due to diffusion and/or erosion of MP and was very dependent on the substance encapsulated. All the loaded MP were successfully coated, but variation in coating thickness (from 68 to 146 µm) and function of the molecules encapsulated resulted in differences in molecule release (5 to 80% in 1 h). Gel rheology modification, due to interactions between WP, ALG, calcium and other substances, was responsible for the highlighted differences. Measuring rheologic parameters before extrusion and reticulation appeared to be one of the most important aspects to study in order to successfully develop a vector with optimal biopharmaceutical properties. Our vector seems to be more appropriate for anionic high-molecular-weight substances, leading to high viscosity and elasticity and to MP enabling gastroresistance and controlled release of molecules at intestinal pH.
Can 3D Printed Tablets Be Bioequivalent and How to Test It: A PBPK Model Based Virtual Bioequivalence Study for Ropinirole Modified Release Tablets
Authors: Shuklinova Olha , Wyszogrodzka-Gaweł Gabriela , Baran Ewelina , Lisowski Bartosz , Wiśniowska Barbara , Dorożyński Przemysław , Kulinowski Piotr , Polak Sebastian
Published: February 2024

As the field of personalized dosing develops, the pharmaceutical manufacturing industry needs to offer flexibility in terms of tailoring the drug release and strength to the individual patient’s needs. One of the promising tools which have such capacity is 3D printing technology. However, manufacturing small batches of drugs for each patient might lead to huge test burden, including the need to conduct bioequivalence trials of formulations to support the change of equipment or strength. In this paper we demonstrate how to use 3D printing in conjunction with virtual bioequivalence trials based on physiologically based pharmacokinetic (PBPK) modeling. For this purpose, we developed 3D printed ropinirole formulations and tested their bioequivalence with the reference product Polpix. The Simcyp simulator and previously developed ropinirole PBPK model were used for the clinical trial simulations. The Weibull-fitted dissolution profiles of test and reference formulations were used as inputs for the model. The virtual bioequivalence trials were run using parallel design. The study power of 80% was reached using 125 individuals. The study demonstrated how to use PBPK modeling in conjunction with 3D printing to test the virtual bioequivalence of newly developed formulations. This virtual experiment demonstrated the bioequivalence of one of the newly developed formulations with a reference product available on a market.
The Past, Present, Future: Pathophysiology, Diagnosis, and Treatment of Human Skin Diseases
Authors: Ebrahimnejad Niki , Jaafar Duaa , Goodarzi Heidi
Published: February 2024

When thinking of skin disease, cancer comes up almost immediately as an example. While the American Cancer Society lists 6 major cancer types, the National Institute of Arthritis and Musculoskeletal and Skin Diseases identifies 13 significant benign skin disorders, reflecting the diversity of skin conditions in dermatology. This topical review aims to provide an overview of the pathophysiology of these major skin cancers and disorders and to summarize conventional diagnostic methods and current treatment approaches.
Exploring Ocimum basilicum’s Secondary Metabolites: Inhibition and Molecular Docking against Rhynchophorus ferrugineus for Optimal Action
Authors: Darrag Hossam Moustafa , Ghazzawy Hesham S. , Nasser Alzain Mashail , Hakami Emadaldeen Hamad , Almuhanna Hani Taher , Alqahtani Nashi K.
Published: February 2024

The objective of our work is to create a practical procedure to produce in vitro cell suspensions of O. basilicum and to ascertain the factors that encourage enhanced secondary metabolite production. We investigated the impact of these metabolites on Rhynchophorus ferrugineus’s adult and larval target enzymes. The explants were cultivated on Murashige and Skoog (MS) media with 0.1 to 1 mg/L plant growth regulators (PGRs) to create calluses. 2,4-Dichlorophenoxyacetic acid (2,4-D), kinetin, 1-naphthylacetic acid (NAA), and indole-3-butryic acid (IBA) at 0.5, 0.5, 0.1, and 1 mg/L, respectively, with 3% sucrose led to the highest biomass accumulation. In cell suspensions, the total phenolic content (TPC) and total flavonoid content (TFC) were 39.68 and 5.49 mg/g DW, respectively, with abiotic Verticillium dahliae as an activator. Rosmarinic acid, ursolic acid, nepetoidin A and B, salvigenin, and quercetin-3-O-rutinoside as flavonoids and phenolics were analyzed using UPLC-I TQD MS, with the highest concentrations reached after 40 days. The extract demonstrates insecticidal activity against the fourth-instar larvae of R. ferrugineus, with adults at 1197 µg/mL and 12.5 µg/larvae as LC50 and LD50 values. The extract inhibited acetylcholine esterase (AChE), acid phosphatases (ACPs), alkaline phosphatases (ALPs), and gamma-aminobutyric acid-transaminase (GABA-T) in larval tissue in vitro, with IC50 values of 124.2, 149.3, 157.8, and 204.8 µg/mL, and in vivo, with IC50 values of 157.2, 179.4, 185.3, and 241.6 µg/mL, after 24 h. Pure compounds identified the activity of the extract, showing the inhibition of AChE, ACPs, ALPs, and GABA-T with IC50 values ˂ 200 µg/mL (in vitro). The ABMET examination revealed good oral permeability, and docking tests showed that the compounds bind AChE, ACPs, ALPs, and GABA-T. These findings show that a green bioprocessing method such as an O. basilicum cell suspension is a quick and straightforward technique for producing phenolic compounds, and it may be used to develop sustainable bio-insecticides and new green procedures.
Zinc Finger Protein8 (GhZFP8) Regulates the Initiation of Trichomes in Arabidopsis and the Development of Fiber in Cotton
Authors: Liu Yongchang , Ma Xiaomei , Li Ying , Yang Xiaoyu , Cheng Wenhan
Published: February 2024

Cotton is one of the most important natural fibers used in the textile industry worldwide. It is important to identify the key factors involved in cotton fiber development. In this study, zinc finger protein8 (GhZFP8) encoding a C2H2 transcription factor (TF) was cloned from cotton. qPCR showed that the transcripts of GhZFP8 in cotton were detected in the leaves and fibers at 3, 6, and 30 days post-anthesis (DPA), but not in the roots, stems, or flowers. The overexpression of GhZFP8 increased the trichome number on the siliques, leaves, and inflorescence, but inhibited the growth. The expression of trichome development and cell-elongation-related genes decreased obviously in GhZFP8 overexpressor Arabidopsis. Indole-3-acetic acid (IAA) and 1-Aminocyclopropanecarboxylic acid (ACC) contents were much higher in GhZFP8 overexpressors than that found in the wild type, but the gibberellin (GA) content was lower. The interference of GhZFP8 in cotton caused smaller bolls and shorter fibers than that of the control. The results of DNA affinity purification (DAP)-seq showed that GhZFP8 could bind to the promoter, exon, intron, and intergenic region of the target genes, which are involved in photosynthesis, signal transduction, synthesis of biomass, etc. Our findings implied that GhZFP8 processed multiple biological functions and regulated the development of cotton fiber.
Plant Reproductive Success Mediated by Nectar Offered to Pollinators and Defensive Ants in Terrestrial Bromeliaceae
Authors: Torres Carolina , Mazzei Mariana P. , Vesprini José L. , Galetto Leonardo
Published: February 2024

Most plants produce floral nectar to attract pollinators that impact pollination and seed production; some of them also secrete extrafloral nectar harvested by insects that may influence the plant reproductive success. The aim of this study was to analyze the effects of excluding pollinators and/or ants on the per-plant reproductive success in two species (Dyckia floribunda Griseb. and Dyckia longipetala Baker, Bromeliaceae) that produce floral and extrafloral nectar. The hypothesis states that both ecological processes (pollination and ant defense) involving nectar-mediated animal–plant interactions are beneficial for plant reproductive success. We expected the highest decrease in the plant fruit and seed sets when the pollinators and ants were excluded, and a moderate decrease when solely ants were excluded, compared to the control plants (those exposed to pollinators and ants). In addition, a lower natural reproductive success was also expected in the self-incompatible D. longipetala than in the self-compatible D. floribunda, as the former totally depends on animal pollination for seed production. D. floribunda and D. longipetala presented similar trends in the response variables, and the expected results for the experimental treatments were observed, with some variations between species and among populations. The ecological function of nectar is important because these two plant species depend on pollinators to produce seeds and on ants to defend flowers from the endophytic larvae of Lepidoptera. The study of multispecies interactions through mechanistic experiments could be necessary to clarify the specific effects of different animals on plant reproductive success.
Defining Populations and Predicting Future Suitable Niche Space in the Geographically Disjunct, Narrowly Endemic Leafy Prairie-Clover (Dalea foliosa; Fabaceae)
Authors: Morris Ashley B. , Visger Clayton J. , Fox Skyler J. , Scalf Cassandra , Fleming Sunny , Call Geoff
Published: February 2024

Conservation actions for rare species are often based on estimates of population size and number, which are challenging to capture in natural systems. Instead, many definitions of populations rely on arbitrarily defined distances between occurrences, which is not necessarily biologically meaningful despite having utility from a conservation management perspective. Here, we introduce a case study using the narrowly endemic and highly geographically disjunct leafy prairie-clover (Dalea foliosa), for which we use nuclear microsatellite loci to assess the current delimitations of populations and management units across its entire known range. We model future potential suitable niche space for the species to assess how currently defined populations could fare under predicted changes in climate over the next 50 years. Our results indicate that genetic variation within the species is extremely limited, particularly so in the distal portions of its range (Illinois and Alabama). Within the core of its range (Tennessee), genetic structure is not consistent with populations as currently defined. Our models indicate that predicted suitable niche space may only marginally overlap with the geology associated with this species (limestone glades and dolomite prairies) by 2070. Additional studies are needed to evaluate the extent to which populations are ecologically adapted to local environments and what role this could play in future translocation efforts.
Arthrocnemum Moq.: Unlocking Opportunities for Biosaline Agriculture and Improved Human Nutrition
Authors: Ramírez Esteban , Rodríguez Nuria , de la Fuente Vicenta
Published: February 2024

(1) Background: This study provides novel insights into the elemental content and biomineralization processes of two halophytic species of the genus Arthrocnemum Moq. (A. macrostachyum and A. meridionale). (2) Methods: Elemental content was analyzed using ICP-MS, while biominerals were detected through electron microscopy (SEM and TEM) and X-ray diffraction. (3) Results: The elemental content showed significant concentrations of macronutrients (sodium, potassium, magnesium, and calcium) and micronutrients, especially iron. Iron was consistently found as ferritin in A. macrostachyum chloroplasts. Notably, A. macrostachyum populations from the Center of the Iberian Peninsula exhibited exceptionally high magnesium content, with values that exceeded 40,000 mg/kg d.w. Succulent stems showed elemental content consistent with the minerals identified through X-ray diffraction analysis (halite, sylvite, natroxalate, and glushinskite). Seed analysis revealed elevated levels of macro- and micronutrients and the absence of heavy metals. Additionally, the presence of reduced sodium chloride crystals in the seed edges suggested a mechanism to mitigate potential sodium toxicity. (4) Conclusions: These findings highlight the potential of Arthrocnemum species as emerging edible halophytes with nutritional properties, particularly in Western European Mediterranean territories and North Africa. They offer promising prospects for biosaline agriculture and biotechnology applications.
Antioxidant and Antifungal Activities and Characterization of Phenolic Compounds Using High-Performance Liquid Chromatography and Mass Spectrometry (HPLC-MS) in Empetrum rubrum Vahl ex Willd.
Authors: Schneider Carlos , González-Reyes Makarena , Vergara Carola , Fuica-Carrasco Camila , Zapata Patricio
Published: February 2024

In searching for compounds with antioxidant and antifungal activity, our study focused on the subshrub species Empetrum rubrum Vahl ex Willd. (Ericaceae). We measured the antioxidant activity of its methanolic extract (MEE) obtained from the aerial parts (leaves and stems) and of its methanolic extract (MEF) obtained from the lyophilized fruits. The antioxidant activity of the MEE and MEF was evaluated in vitro via a 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical and 2,2′-Azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) cationic radical. The results were expressed in gallic acid and Trolox equivalents for the DPPH and ABTS assays, respectively. The antioxidant activities, for the DPPH and ABTS assays, were also evaluated by considering the IC50 values. Concerning the antioxidant activity, the total phenolic content (TPC) in the MEE and MEF was determined using the Folin–Ciocalteu method. Polyphenols contained in the leaves, stems, and fruits of E. rubrum were determined qualitatively by employing high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) analysis. The antifungal activity of the MEE obtained from the aerial parts of E. rubrum was tested against Rhizoctonia solani. The results of IC50 values measured by the DPPH and ABTS methods with MEE were 0.4145 ± 0.0068 mg mL−1 and 0.1088 ± 0.0023 mg mL−1, respectively, and the IC50 values for MEF were 6.4768 ± 0.0218 mg mL−1 and 0.7666 ± 0.0089 mg mL−1 measured by the DPPH and ABTS methods, respectively. The HPLC-MS analysis revealed the presence of anthocyanins, phenolic acids derivatives, and flavonols. In vitro, mycelial growth of this fungus was reduced from 90% to nearly 100% in the presence of MEE. The observed antifungal effect is related to the presence of the abovementioned phenols, detected in the MEE.
Rheological and Flexural Strength Characteristics of Cement Mixtures through the Synergistic Effects of Graphene Oxide and PVA Fibers
Authors: Cho Byoung Hooi , Choi Dong Wook , Park Mi Hwan
Published: February 2024

This study investigates the synergistic effects of incorporating graphene oxide (GO) and polyvinyl alcohol (PVA) fibers into cement paste mixtures, aiming to modify their rheological properties and flexural behaviors with resistance to crack formation. The relationship between static yield stress and critical shear strain was examined in ten cement paste mixtures with varying concentrations of 6 mm and 12 mm PVA fibers and 0.05% GO. Additionally, viscosity analyses were performed. For the specimens fabricated from these mixtures, flexural strength tests were conducted using the Digital Image Correlation (DIC) technique for precise strain analysis under load history. The results indicated a significant increase in static yield stress, viscosity, and critical shear strain due to the combined addition of GO and PVA fibers, more so than when added individually. Notably, in PVA fiber-reinforced cement mixtures, the integration of GO increased the crack initiation load by up to 23% and enhanced pre-crack strain by 30 to 50%, demonstrating a notable delay in crack initiation and a reduction in crack propagation. Microstructural analyses using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) revealed a concentrated presence of GO around and on the PVA fibers. This promotes increased C-S-H gel formation, resulting in a denser microstructure. Additionally, GO effectively interacts with PVA fibers, enhancing the adherence of hydration products at their interface.
Performance of Fabrics with 3D-Printed Photosensitive Acrylic Resin on the Surface
Authors: Becker Payton , Ciesielska-Wrόbel Izabela
Published: February 2024

Additive manufacturing (AM), also known as three-dimensional printing (3DP), has been widely applied to various fields and industries, including automotive, healthcare, and rapid prototyping. This study evaluates the effects of 3DP on textile properties. The usability of a textile and its durability are determined by its strength, washability, colorfastness to light, and abrasion resistance, among other traits, which may be impacted by the application of 3DP on the fabric’s surface. This study examines the application of photosensitive acrylic resin on two fabric substrates: 100% cotton and 100% polyester white woven fabrics made of yarns with staple fibers. A simple alphanumeric text was translated into braille and the braille dots were 3D printed onto both fabrics. The color of the printed photosensitive acrylic resin was black, and it was an equal mixture of VeroCyanV, VeroYellowV, and VeroMagentaV. The 3D-printed design was the same on both fabrics and was composed of braille dots with a domed top. Both of the 3DP fabrics passed the colorfastness to washing test with no transfer or color change, but 3D prints on both fabrics showed significant color change during the colorfastness to light test. The tensile strength tests indicated an overall reduction in strength and elongation when the fabrics had 3DP on their surface. An abrasion resistance test revealed that the resin had a stronger adhesion to the cotton than to the polyester, but both resins were removed from the fabric with the abrader. These findings suggest that while 3DP on textiles offers unique possibilities for customization and design, mechanical properties and color stability trade-offs need to be considered. Further evaluation of textiles and 3D prints of textiles and their performance in areas such as colorfastness and durability are warranted to harness the full potential of this technology in the fashion and textile industry.
Topographically and Chemically Enhanced Textile Polycaprolactone Scaffolds for Tendon and Ligament Tissue Engineering
Authors: Bauer Benedict , Emonts Caroline , Pitts Johannes , Buhl Eva Miriam , Eschweiler Jörg , Hänsch Robert , Betsch Marcel , Gries Thomas , Menzel Henning
Published: February 2024

The use of tissue engineering to address the shortcomings of current procedures for tendons and ligaments is promising, but it requires a suitable scaffold that meets various mechanical, degradation-related, scalability-related, and biological requirements. Macroporous textile scaffolds made from appropriate fiber material have the potential to fulfill the first three requirements. This study aimed to investigate the biocompatibility, sterilizability, and functionalizability of a multilayer braided scaffold. These macroporous scaffolds with dimensions similar to those of the human anterior cruciate ligament consist of fibers with appropriate tensile strength and degradation behavior melt-spun from Polycaprolactone (PCL). Two different cross-sectional geometries resulting in significantly different specific surface areas and morphologies were used at the fiber level, and a Chitosan-graft-PCL (CS-g-PCL) surface modification was applied to the melt-spun substrates for the first time. All scaffolds elicited a positive cell response, and the CS-g-PCL modification provided a platform for incorporating functionalization agents such as drug delivery systems for growth factors, which were successfully released in therapeutically effective quantities. The fiber geometry was found to be a variable that could be manipulated to control the amount released. Therefore, scaled, surface-modified textile scaffolds are a versatile technology that can successfully address the complex requirements of tissue engineering for ligaments and tendons, as well as other structures.
Filming Biblical Interpretations from the Ground: Anti-Empire Matthean Interpretations in Huwag Kang Papatay (2017) and the Philippine “Drug War”
Authors: Ibita Ma. Marilou S.
Published: February 2024

Ditsi Carolino’s “Huwag Kang Papatay” (Thou Shall Not Kill, 2017) is an unconventional Jesus film. As a documentary, it presents the problems and the responses by members of the Roman Catholic Church in Metro Manila to the so-called “War on Drugs” (commonly known as Tokhang) of the Duterte government that resulted in thousands of extrajudicial killing (EJK) victims. From a biblical lens, this paper analyzes examples of grassroots recontextualizing interpretations of select Matthean passages like (1) Mt 6:9−13, the Lord’s Prayer, in the context of praying for an extrajudicial killing victim; (2) Mt 2:1−18, a street theater adaptation showing the massacre of the innocents, representing the beginning of the EJKs; and (3) Mt 27:27−50, a street theater adaptation of Jesus’ passion recontextualized in the plight of the victimized drug personalities. These episodes are examined using insights from biblical narrative criticism, performance criticism, empire studies, ritual studies and a liberationist approaches. The paper concludes that biblical interpretations from the ground in this documentary film demonstrate Matthew’s anti-empire message by recontextualizing Jesus’s story in the context of extrajudicial killings to advocate for political dialogue and action-response against human rights violations and development issues caused by the EJKs.
What Affects Human Decision Making in Human–Robot Collaboration?: A Scoping Review
Authors: Liu Yuan , Caldwell Glenda , Rittenbruch Markus , Belek Fialho Teixeira Müge , Burden Alan , Guertler Matthias
Published: February 2024

The advent of Industry 4.0 has heralded advancements in Human–robot Collaboration (HRC), necessitating a deeper understanding of the factors influencing human decision making within this domain. This scoping review examines the breadth of research conducted on HRC, with a particular focus on identifying factors that affect human decision making during collaborative tasks and finding potential solutions to improve human decision making. We conducted a comprehensive search across databases including Scopus, IEEE Xplore and ACM Digital Library, employing a snowballing technique to ensure the inclusion of all pertinent studies, and adopting the PRISMA Extension for Scoping Reviews (PRISMA-ScR) for the reviewing process. Some of the important aspects were identified: (i) studies’ design and setting; (ii) types of human–robot interaction, types of cobots and types of tasks; (iii) factors related to human decision making; and (iv) types of user interfaces for human–robot interaction. Results indicate that cognitive workload and user interface are key in influencing decision making in HRC. Future research should consider social dynamics and psychological safety, use mixed methods for deeper insights and consider diverse cobots and tasks to expand decision-making studies. Emerging XR technologies offer the potential to enhance interaction and thus improve decision making, underscoring the need for intuitive communication and human-centred design.
Source Depth Discrimination Using Intensity Striations in the Frequency–Depth Plane in Shallow Water with a Thermocline
Authors: Li Xiaobin , Sun Chao
Published: February 2024

A source depth discrimination method based on intensity striations in the frequency–depth plane with a vertical linear array in a shallow water environment is proposed and studied theoretically and experimentally. To quantify the orientation of the interference patterns, a generalized waveguide variant (GWV) η is introduced. Due to the different dominance of the mode groups, the GWV distribution in the surface source is sharply peaked, indicating the presence of striations in the interferogram and the slope associated with the source–array range, while the distribution of the submerged source is more diffuse, and its interferogram is chaotic. The existence or lack of a distinct peak is used to separate the surface and submerged source classes. The method does not demand prior knowledge of the sound speed profile or the relative movement between the source and the array. In addition, it is the presence of the striations, not the value of η, that is exploited to separate the surface and submerged source classes, which means the source–array range can be unknown. The proposed method is validated using experimental data on the towing ship in SWellEx–96 and numerical modeling. The method’s performance under noise situations and for different source–array ranges is also investigated.
Radar High-Resolution Range Profile Rejection Based on Deep Multi-Modal Support Vector Data Description
Authors: Dong Yue , Wang Penghui , Fang Ming , Guo Yifan , Cao Lili , Yan Junkun , Liu Hongwei
Published: February 2024

Radar Automatic Target Recognition (RATR) based on high-resolution range profile (HRRP) has received intensive attention in recent years. In practice, RATR usually needs not only to recognize in-library samples but also to reject out-of-library samples. However, most rejection methods lack a specific and accurate description of the underlying distribution of HRRP, which limits the effectiveness of the rejection task. Therefore, this paper proposes a novel rejection method for HRRP, named Deep Multi-modal Support Vector Data Description (DMMSVDD). On the one hand, it forms a more compact rejection boundary with the Gaussian mixture model in consideration of the high-dimensional and multi-modal structure of HRRP. On the other hand, it captures the global temporal information and channel-dependent information with a dual attention module to gain more discriminative structured features, which are optimized jointly with the rejection boundary. In addition, a semi-supervised extension is proposed to refine the boundary with available out-of-library samples. Experimental results based on measured data show that the proposed methods demonstrate significant improvement in the HRRP rejection performance.
Underwater Acoustic Nonlinear Blind Ship Noise Separation Using Recurrent Attention Neural Networks
Authors: Song Ruiping , Feng Xiao , Wang Junfeng , Sun Haixin , Zhou Mingzhang , Esmaiel Hamada
Published: February 2024

Ship-radiated noise is the main basis for ship detection in underwater acoustic environments. Due to the increasing human activity in the ocean, the captured ship noise is usually mixed with or covered by other signals or noise. On the other hand, due to the softening effect of bubbles in the water generated by ships, ship noise undergoes non-negligible nonlinear distortion. To mitigate the nonlinear distortion and separate the target ship noise, blind source separation (BSS) becomes a promising solution. However, underwater acoustic nonlinear models are seldom used in research for nonlinear BSS. This paper is based on the hypothesis that the recovery and separation accuracy can be improved by considering this nonlinear effect in the underwater environment. The purpose of this research is to explore and discover a method with the above advantages. In this paper, a model is used in underwater BSS to describe the nonlinear impact of the softening effect of bubbles on ship noise. To separate the target ship-radiated noise from the nonlinear mixtures, an end-to-end network combining an attention mechanism and bidirectional long short-term memory (Bi-LSTM) recurrent neural network is proposed. Ship noise from the database ShipsEar and line spectrum signals are used in the simulation. The simulation results show that, compared with several recent neural networks used for linear and nonlinear BSS, the proposed scheme has an advantage in terms of the mean square error, correlation coefficient and signal-to-distortion ratio.
Provisioning of Fog Computing over Named-Data Networking in Dynamic Wireless Mesh Systems
Authors: Glazkov Roman , Moltchanov Dmitri , Srikanteswara Srikathyayani , Samuylov Andrey , Arrobo Gabriel , Zhang Yi , Feng Hao , Himayat Nageen , Spoczynski Marcin , Koucheryavy Yevgeni
Published: February 2024

Fog computing is today considered a promising candidate to improve the user experience in dynamic on-demand computing services. However, its ubiquitous application would require support for this service in wireless multi-hop mesh systems, where the use of conventional IP-based solutions is challenging. As a complementary solution, in this paper, we consider a Named-Data Networking (NDN) approach to enable fog computing services in autonomous dynamic mesh formations. In particular, we jointly implement two critical mechanisms required to extend the NDN-based fog computing architecture to wireless mesh systems. These are (i) dynamic face management systems and (ii) a learning-based route discovery strategy. The former makes it possible to solve NDN issues related to an inability to operate over a broadcast medium. Also, it improves the data-link layer reliability by enabling unicast communications between mesh nodes. The learning-based forwarding strategy, on the other hand, efficiently reduces the amount of overhead needed to find routes in the dynamically changing mesh networks. Our numerical results show that, for static wireless meshes, our proposal makes it possible to fully benefit from the computing resources sporadically available up to several hops away from the consumer. Additionally, we investigate the impacts of various traffic types and NDN caching capabilities, revealing that the latter result in much better system performance while the popularity of the compute service contributes to additional performance gains.
Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches
Authors: Ramli Albara Ah , Liu Xin , Berndt Kelly , Goude Erica , Hou Jiahui , Kaethler Lynea B. , Liu Rex , Lopez Amanda , Nicorici Alina , Owens Corey , Rodriguez David , Wang Jane , Zhang Huanle , Aranki Daniel , McDonald Craig M. , Henricson Erik K.
Published: February 2024

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3 to 16 years of age underwent eight walking/running activities, including five 25 m walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-min walk test (6MWT), a 100 m fast walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens.
Ventricular Arrhythmias in Left Ventricular Assist Device Patients—Current Diagnostic and Therapeutic Considerations
Authors: Załucka Laura , Świerżyńska Ewa , Orczykowski Michał , Dutkowski Krzysztof , Szymański Jarosław , Kuriata Jarosław , Dąbrowski Rafał , Kołsut Piotr , Szumowski Łukasz , Sterliński Maciej
Published: February 2024

Left ventricular assist devices (LVAD) are used in the treatment of advanced left ventricular heart failure. LVAD can serve as a bridge to orthotopic heart transplantation or as a destination therapy in cases where orthotopic heart transplantation is contraindicated. Ventricular arrhythmias are frequently observed in patients with LVAD. This problem is further compounded as a result of diagnostic difficulties arising from presently available electrocardiographic methods. Due to artifacts from LVAD-generated electromagnetic fields, it can be challenging to assess the origin of arrhythmias in standard ECG tracings. In this article, we will review and discuss common mechanisms, diagnostics methods, and therapeutic strategies for ventricular arrhythmia treatment, as well as numerous problems we face in LVAD implant patients.
Active Compensation Technology for the Target Measurement Error of Two-Axis Electro-Optical Measurement Equipment
Authors: Lan Lintao , Hua Fangwu , Fang Fang , Jiang Wei
Published: February 2024

For two-axis electro-optical measurement equipment, there are many error sources in parts manufacturing, assembly, sensors, calibration, and so on, which cause some random errors in the final measurement results of the target. In order to eliminate the random measurement error as much as possible and improve the measurement accuracy, an active compensation technique for target measurement error is proposed in this paper. Firstly, the error formation mechanism and error transfer model establishment of the two-axis electro-optical measurement equipment were studied, and based on that, three error compensation and correction methods were proposed: the least square (LS)-based error compensation method, adaptive Kalman filter(AKF)-based error correction method, and radial basis function neural network (RBFNN)-based error compensation method. According to the theoretical analysis and numerical simulation comparison, the proposed RBFNN-based error compensation method was identified as the optimal error compensation method, which can approximate the random error space surface more precisely, so that a more accurate error compensation value can be obtained, and in order to improve the measurement accuracy with higher precision. Finally, the experimental results proved that the proposed active compensation technology was valid in engineering applicability and could efficiently enhance the measurement accuracy of the two-axis electro-optical measurement equipment.
Analysis of Wi-SUN FAN Network Formation Time
Authors: Quispe Ananias Ambrosio , Riella Rodrigo Jardim , Iantorno Luciana Michelotto , Mariani Leonardo Santanna , Fernandez Evelio M. Garcia
Published: February 2024

The Wi-SUN FAN (Wireless Smart Ubiquitous Network Field Area Network) standard is attracting great interest in various applications such as smart meters, smart cities and Internet of Things (IoT) devices due to the attractive features that the standard offers, such as multihop and mesh topologies, a relatively high data rate, frequency hopping, and interoperability between manufacturers. However, the process of connecting nodes in Wi-SUN FAN networks, which includes discovering, joining, and forming the network, has been shown to be slow, especially in multihop environments, which has motivated research and experimentation to analyze this process. In the existing literature, to measure network formation time, some authors have performed experiments with up to 100 devices, which is a costly and time-consuming methodology. Others have used simulation tools that are difficult to replicate, because little information is available about the methodology used or because they are proprietary. Despite these efforts, there is still a lack of information to adequately assess the formation time of Wi-SUN FAN networks, since the experimental tests reported in the literature are expensive and time-consuming. Therefore, alternatives such as computer simulation have been explored to speed up performance analysis in different scenarios. With this perspective, this paper is focused on the implementation of the Wi-SUN FAN network formation process using the Contiki-NG open source operating system and the Cooja simultor, where a functionality was added that makes it possible to efficiently analyze the network performance, thereby facilitating the implementation of new techniques to reduce network training time. The simulation tool was integrated into Contiki-NG and has been used to estimate the network formation times in various indoor environments. The correspondence between the experimental and numerical results obtained shows that our proposal is efficient to study the formation process of this type of networks.
NeoSLAM: Long-Term SLAM Using Computational Models of the Brain
Authors: Pizzino Carlos Alexandre Pontes , Costa Ramon Romankevicius , Mitchell Daniel , Vargas Patrícia Amâncio
Published: February 2024

Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics, enabling autonomous robots to navigate and create maps of unknown environments. Nevertheless, the SLAM methods that use cameras face problems in maintaining accurate localization over extended periods across various challenging conditions and scenarios. Following advances in neuroscience, we propose NeoSLAM, a novel long-term visual SLAM, which uses computational models of the brain to deal with this problem. Inspired by the human neocortex, NeoSLAM is based on a hierarchical temporal memory model that has the potential to identify temporal sequences of spatial patterns using sparse distributed representations. Being known to have a high representational capacity and high tolerance to noise, sparse distributed representations have several properties, enabling the development of a novel neuroscience-based loop-closure detector that allows for real-time performance, especially in resource-constrained robotic systems. The proposed method has been thoroughly evaluated in terms of environmental complexity by using a wheeled robot deployed in the field and demonstrated that the accuracy of loop-closure detection was improved compared with the traditional RatSLAM system.
Filling the Gaps: Using Synthetic Low-Altitude Aerial Images to Increase Operational Design Domain Coverage
Authors: Rüter Joachim , Maienschein Theresa , Schirmer Sebastian , Schopferer Simon , Torens Christoph
Published: February 2024

A key necessity for the safe and autonomous flight of Unmanned Aircraft Systems (UAS) is their reliable perception of the environment, for example, to assess the safety of a landing site. For visual perception, Machine Learning (ML) provides state-of-the-art results in terms of performance, but the path to aviation certification has yet to be determined as current regulation and standard documents are not applicable to ML-based components due to their data-defined properties. However, the European Union Aviation Safety Agency (EASA) published the first usable guidance documents that take ML-specific challenges, such as data management and learning assurance, into account. In this paper, an important concept in this context is addressed, namely the Operational Design Domain (ODD) that defines the limitations under which a given ML-based system is designed to operate and function correctly. We investigated whether synthetic data can be used to complement a real-world training dataset which does not cover the whole ODD of an ML-based system component for visual object detection. The use-case in focus is the detection of humans on the ground to assess the safety of landing sites. Synthetic data are generated using the methods proposed in the EASA documents, namely augmentations, stitching and simulation environments. These data are used to augment a real-world dataset to increase ODD coverage during the training of Faster R-CNN object detection models. Our results give insights into the generation techniques and usefulness of synthetic data in the context of increasing ODD coverage. They indicate that the different types of synthetic images vary in their suitability but that augmentations seem to be particularly promising when there is not enough real-world data to cover the whole ODD. By doing so, our results contribute towards the adoption of ML technology in aviation and the reduction of data requirements for ML perception systems.
Smart Grid Security: An Effective Hybrid CNN-Based Approach for Detecting Energy Theft Using Consumption Patterns
Authors: Gunduz Muhammed Zekeriya , Das Resul
Published: February 2024

In Internet of Things-based smart grids, smart meters record and report a massive number of power consumption data at certain intervals to the data center of the utility for load monitoring and energy management. Energy theft is a big problem for smart meters and causes non-technical losses. Energy theft attacks can be launched by malicious consumers by compromising the smart meters to report manipulated consumption data for less billing. It is a global issue causing technical and financial damage to governments and operators. Deep learning-based techniques can effectively identify consumers involved in energy theft through power consumption data. In this study, a hybrid convolutional neural network (CNN)-based energy-theft-detection system is proposed to detect data-tampering cyber-attack vectors. CNN is a commonly employed method that automates the extraction of features and the classification process. We employed CNN for feature extraction and traditional machine learning algorithms for classification. In this work, honest data were obtained from a real dataset. Six attack vectors causing data tampering were utilized. Tampered data were synthetically generated through these attack vectors. Six separate datasets were created for each attack vector to design a specialized detector tailored for that specific attack. Additionally, a dataset containing all attack vectors was also generated for the purpose of designing a general detector. Furthermore, the imbalanced dataset problem was addressed through the application of the generative adversarial network (GAN) method. GAN was chosen due to its ability to generate new data closely resembling real data, and its application in this field has not been extensively explored. The data generated with GAN ensured better training for the hybrid CNN-based detector on honest and malicious consumption patterns. Finally, the results indicate that the proposed general detector could classify both honest and malicious users with satisfactory accuracy.