bluuebunny/crossref_metadata_2025 huggingface dataset:
Fabrication and Properties of Superhydrophobic Colored Stainless Steel Surface for Decoration and Anti-Corrosion
Authors: Fan Changfeng , Wang Xue , Wang Wei , Meng Dechao , Zhan Xianghua , Yin Xiaoli , Liu Yancong
Published: September 2024

A colored superhydrophobic surface on a stainless steel substrate was achieved by means of high temperature oxidation combined with subsequent spraying modification by superhydrophobic nano-silica film. Comprehensive characterizations of the surface were performed in terms of color, morphology, composition, wettability, and corrosion resistance by optical microscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), contact angle, potentiodynamic polarization, and electrochemical impedance spectroscopy measurement. At 400 °C, the surface was pale yellow, gradually turning yellow and then red as the temperature increased. At 700 °C and 800 °C, the surface colors were blue and dark brown, respectively. The samples with oxide films demonstrated lower contact angles, specifically 80.5° ± 2.5 at 400 °C, 79.1° ± 2.8 at 500 °C, and 75.6° ± 3.4 at 600 °C. The polarization resistance measured on the oxidized film formed at 600 °C exceeded 7.93 × 104 Ω·cm2. After spraying the treatment, these colorful surfaces exhibited superhydrophobicity, they were self-cleaning, and they satisfied anti-corrosion properties. The treatment performs as an excellent barrier and exhibits a high corrosion resistance of 4.68 × 106 Ω·cm2. The successful preparation of superhydrophobic colored surfaces offers the possibility of providing stainless steel with both decoration value and self-cleaning function simultaneously by our proposed chromium-free fabrication process.
Rapid Synthesis and Sintering of La2O2S and Its Physical, Optical, and Mechanical Properties
Authors: Chen Yuqi , Li Liang , Li Jin , Han Kun
Published: September 2024

Rare-earth oxysulfides are a class of functional ceramic materials with excellent physico-chemical properties and rich functionality. In this study, La2O2S powders were prepared from La2S3 and La2O3 powders at 1000 °C by pressureless sintering. La2O2S compacts were synthesized from La2S3 and La2O3 powders at 800–1600 °C by spark plasma sintering. The influences of sintering temperature and time on the preparation of La2O2S were studied. XRD results indicated that La2O2S ceramics were synthesized successfully and that the lattice constants of La2O2S were close to the theoretical values. SEM showed that the microstructure of La2O2S compacts was homogeneous. The specific heat of La2O2S mainly came from lattice contribution, and its Debye temperature was 237 K. The UV–visible absorption spectra showed different absorption levels in the 240–300 nm range. Raman spectroscopy revealed distinct peaks at different temperatures, indicating changes in the covalence band. The relative density of La2O2S ceramics was 92% and lower than theoretical values. Hardness of the synthesized La2O2S was greater than that of Gd2O2S ceramics.
Micro-Nano Dual-Scale Coatings Prepared by Suspension Precursor Plasma Spraying for Resisting Molten Silicate Deposit
Authors: Liu Yangguang , Wang Yihao , Wang Weize , Zhang Wenkang , Wang Junhao , Li Kaibin , Li Hongchen , Liu Pengpeng , Yang Shilong , Zhang Chengcheng
Published: September 2024

Yb-doped Y2O3 stabilized ZrO2 (YbYSZ) coatings, developed through solution precursor plasma spraying (SPPS), are engineered to resist calcium–magnesium–alumino–silicate (CMAS) infiltration by leveraging their unique micro-nano structures. This provides superior anti-wetting properties, crucial for preventing CMAS penetration at high temperatures. The investigation focused on the structural and compositional changes in YbYSZ-SPPS coatings subjected to prolonged thermal exposure at 1300 °C. Results indicate that while the coatings undergo significant sintering, leading to densification and microstructural evolution, the elemental composition and phase stability remain largely intact after up to 8 h of heat treatment. Despite some reduction in CMAS resistance, the coatings maintained their overall protective performance, demonstrating the potential of SPPS coatings for long-term use in high-temperature environments where CMAS infiltration is a concern. These findings contribute to the development of more durable TBCs for advanced thermal protection applications.
Interlayer Adhesion of Coating System in Analogue and Digital Printing Technologies Formed on Lightweight Honeycomb Furniture Panels
Authors: Tokarczyk Maciej , Lis Barbara , Krystofiak Tomasz
Published: September 2024

This article concerns research into the influence of the energy dose distributed by UV lamps on selected parameters of varnish coatings formed during the varnishing process of lightweight cellular panels. The lightweight cellular board used in the study was made according to an innovative solution. The surface finishing of the boards was carried out using the roller method in combination with digital and analogue printing under industrial conditions. Contact angle measurements of the obtained varnish coatings were carried out, from which the surface free energy was calculated. In addition, interlayer adhesion was assessed by pull-off tests. Irrespective of the radiation dose, higher contact angle values (54.3–89.9°) were recorded for the last two applied layers (base coat 2 and base coat 3) than for the other coatings (39.6–64.1°). For all systems tested, the γsp component showed lower values (2.25–28.99 mJ/m2) than γsd (28.66–32.80 mJ/m2). The adhesion test results ranged from 0.5 to 0.9 MPa, although with varying types of delamination. Based on the test results, the most favourable variants from the furniture manufacturer’s point of view were selected that provided the desired level of adhesion, in which cohesive damage located within the substrate (A) predominated.
Enhancing Flame-Retardant Properties of Polyurethane Composites Using N-β-(Aminoethyl)-γ-aminopropyl Trimethoxysilane and Carbon Black Co-Modified Ammonium Polyphosphate
Authors: Fu Lisha , Hao Wanjun , Xu Baoluo , Zhang Kexi , Bi Jianhua , Wu Jingxing , Wang Zhong
Published: September 2024

The search for a straightforward method to obtain efficient, affordable, and long-lasting flame retardants with both desirable flame-retardant and mechanical properties for polyurethane (PU) composites remains a significant challenge. In this study, the surface of ammonium polyphosphate (APP) was modified using N-β-(aminoethyl)-γ-aminopropyl trimethoxysilane (KH792) via an ion-exchange reaction, and the modified APP was coated with nanoscale carbon black (CB) to obtain CBAPP. CBAPP demonstrated good compatibility within the PU matrix and notably increased the tensile strength of the PU composites. Furthermore, CBAPP significantly enhanced the flame-retardant properties of the PU composites. The CBAPP/PU composite with a CBAPP mass fraction of 20% achieved a limiting oxygen index of 41.5% and a UL-94 class of V-0. According to the results of this study, our modification approach can be applied to develop other high-performance flame-retardant polymer-based composites, representing a significant contribution to the field of fire safety materials.
Niobium Oxide Thin Films Grown on Flexible ITO-Coated PET Substrates
Authors: Marciel Alice , Bastos Alexandre , Pereira Luiz , Jakka Suresh Kumar , Borges Joel , Vaz Filipe , Peres Marco , Lorenz Katharina , Bafti Arijeta , Pavić Luka , Silva Rui , Graça Manuel
Published: September 2024

Niobium oxide thin films were grown on both rigid and flexible substrates using DC magnetron sputtering for electrochromic applications. Three experimental series were conducted, varying the oxygen to argon flow rate ratio and deposition time. In the first series, the oxygen to argon ratio was adjusted from 0 to 0.32 while maintaining a constant growth time of 30 min. For the second and third series, the oxygen to argon ratios were fixed at 0.40 and 0.56, respectively, with deposition times ranging from 15 to 60 min. A structural transition from crystalline to amorphous was observed at an oxygen to argon flow rate ratio of 0.32. This transition coincided with a change in appearance, from non-transparent with metallic-like electrical conductivity to transparent with dielectric behavior. The transparent niobium oxide films exhibited thicknesses between 51 nm and 198 nm, with a compact, dense, and featureless morphology, as evidenced by both top-view and cross-sectional images. Films deposited on flexible indium tin oxide (ITO)-coated polyethylene terephthalate (PET) substrates displayed a maximum surface roughness (Sq) of 9 nm and a maximum optical transmission of 83% in the visible range. The electrochromic response of niobium oxide thin films on ITO-coated PET substrates demonstrated a maximum coloration efficiency of 30 cm2 C−1 and a reversibility of 96%. Mechanical performance was assessed through bending tests. The ITO-coated PET substrate exhibited a critical bending radius of 6.5 mm. Upon the addition of the niobium oxide layer, this decreased to 5 mm. Electrical resistance measurements indicated that the niobium oxide film mitigated rapid mechanical degradation of the underlying ITO electrode beyond the critical bending radius.
On the Impact of Discrete Atomic Compression on Image Classification by Convolutional Neural Networks
Authors: Makarichev Viktor , Lukin Vladimir , Brysina Iryna
Published: September 2024

Digital images play a particular role in a wide range of systems. Image processing, storing and transferring via networks require a lot of memory, time and traffic. Also, appropriate protection is required in the case of confidential data. Discrete atomic compression (DAC) is an approach providing image compression and encryption simultaneously. It has two processing modes: lossless and lossy. The latter one ensures a higher compression ratio in combination with inevitable quality loss that may affect decompressed image analysis, in particular, classification. In this paper, we explore the impact of distortions produced by DAC on performance of several state-of-the-art classifiers based on convolutional neural networks (CNNs). The classic, block-splitting and chroma subsampling modes of DAC are considered. It is shown that each of them produces a quite small effect on MobileNetV2, VGG16, VGG19, ResNet50, NASNetMobile and NASNetLarge models. This research shows that, using the DAC approach, memory expenses can be reduced without significant degradation of performance of the aforementioned CNN-based classifiers.
The Diversity of Archaeological Animal and Plant Remains Discovered at 18th–19th-Century Sites in Iași City (NE Romania)
Authors: Stanc Margareta Simina , Bilavschi George , Bacumenco-Pîrnău Ludmila , Aparaschivei Dan , Bejenaru Luminița , Danu Mihaela
Published: September 2024

Animal and plant remains recovered from two archaeological sites in Iași city (NE Romania) were analyzed in this work. The aim of this study was to contribute to the economic and environmental evaluation of an old urban settlement. The analyzed sites, both of value in archaeological preventive research, are dated to the 18th–19th centuries. The archaeozoological analysis consisted of anatomical, taxonomic, and taphonomic identifications, quantification, estimations of age at slaughter and sex, and osteometry. The results revealed that the animal remains are of domestic origin, as indicated by traces of butchering, and can be mainly described in terms of their frequencies (i.e., number of identified specimens and minimum number of individuals), selection for slaughter, morphology, and size. The results show that animal husbandry (e.g., cattle, sheep/goat, pig, and horse) had significant importance in the economy of the settlement, and cattle were preferred for consumption. Few remains were identified for wild mammals (i.e., red deer, wild boar, and hare), birds, and mollusks. The phytolith analysis indicated that some plant resources were used in the economy of this settlement. The identification of opal silica bodies revealed the presence of grasses and cultivated cereals.
Spatiotemporal Distribution and Dispersal Pattern of Early Life Stages of the Small Yellow Croaker (Larimichthys Polyactis) in the Southern Yellow Sea
Authors: Song Xiaojing , Hu Fen , Xu Min , Zhang Yi , Jin Yan , Gao Xiaodi , Liu Zunlei , Ling Jianzhong , Li Shengfa , Cheng Jiahua
Published: September 2024

Nursery habitats play a significant role in completing fish life cycles, and they are now recognized as essential habitats. Monthly variations in nursery ground distributions of Larimichthys polyactis were investigated in the southern Yellow Sea in 2019. Bayesian hierarchical models with integrated nested Laplace approximation were utilized to model the preferential nursery habitats of L. polyactis larvae. The study analyzed the spatial and temporal distributions of the larvae and juveniles based on three environmental variables: sea surface temperature, sea surface salinity, and depth. Additionally, this study examined the utilization of habitats by different fish life stages and ontogenetic shifts. A total of 3240 individuals were collected from April to June, with the peak occurring in May (0.05 ind./m3), and the distribution areas varied between different months. The prediction of the model reveals the ecological adaptability of L. polyactis to temperature variations. The optimal temperature for L. polyactis density ranges from 12.5 °C to 16.5 °C in April and 16.5 °C to 17.5 °C in May, demonstrating a broad temperature tolerance for L. polyactis survival. In addition, there are variations in distribution patterns among different developmental stages. Larimichthys polyactis spawn in the inshore and nearshore waters, and after hatching, larvae in the pre-flexion stage tend to remain aggregated near the spawning beds. However, larvae in the advanced development stage (post-flexion) and juveniles move towards the sandy ridge habitats along the coast and start to migrate offshore in June. This study provides valuable insights for the effective management of fishery resources in the area and can be utilized to identify marine areas with specific habitat features that require conservation.
Correlation Analysis among the Various Inbreeding Coefficients of Pannon Ka Rabbits
Authors: Nagy István , Bokor Árpád , Farkas János , Nguyen Anh Thi , Posta János , Kövér György
Published: September 2024

In a closed population with a limited population size, mating of related animals is unavoidable. In this study, the genealogy data of a synthetic maternal rabbit breed called Pannon Ka were used to calculate different inbreeding coefficients. The evaluated animals were born between 1995 and 2020, and the pedigree consisted of 5819 animals that originated from 4205 rabbit does and from 1314 rabbit bucks. The pedigree was further extended with 16,013 dummy progeny records in order to calculate litter inbreeding coefficients. Besides the conventional Wright inbreeding coefficients, the so-called ancestral and new inbreeding coefficients were also calculated using the gene dropping method. By the end of the evaluated period, the litter inbreeding increased to almost 11 and 60% for Wright and Ballou inbreeding, while the Kalinowski and the Kalinowski new inbreeding coefficients were 9.25 and 16.67%, respectively. Correlation coefficients were calculated for the does and for the litters. Finally, the effects of pedigree length and completeness were also taken into account using the complete generation equivalents in a partial correlation analysis. Based on the results, it could be seen that the different ancestral inbreeding coefficients had high correlation. Similarly, the conventional Wright inbreeding coefficients showed strong correlation with the new inbreeding coefficients. On the contrary, the correlation between ancestral and new inbreeding coefficients was low. Taking the complete generation equivalent into account did not give unambiguous results. It could be concluded that the different inbreeding coefficients are based on different concepts, and they are clearly different population parameters.
Environmental DNA as Early Warning for Alien Species in Mediterranean Coastal Lagoons: Implications for Conservation and Management
Authors: Zangaro Francesco , Pinna Maurizio , Specchia Valeria
Published: September 2024

Non-indigenous species (NIS) introduction notoriously threatens the Mediterranean Sea. In addition, Mediterranean coastal lagoons play a crucial role as nurseries for marine species, which new NIS arrivals can threaten. Therefore, monitoring and early warning of NIS presence is essential in preserving biodiversity. An innovative technique for rapid and accurate species identification and biodiversity screening is the application of environmental DNA (eDNA) metabarcoding. In this research, different Penaeidae (Arthropoda, Crustacea, Decapoda) NIS specimens were collected from a Mediterranean coastal lagoon after an early warning about a potentially invasive NIS arising from next-generation sequencing data. DNA barcoding of the DNA extracted from tissue samples and amplified with specifically designed primer pairs led to the recognition of Penaeus aztecus in this NATURA 2000 protected ecosystem for the first time. DNA barcoding from DNA isolated from the water where the living specimens were stored further validated the possibility of identifying P. aztecus starting from eDNA. This approach demonstrated the validity of environmental DNA analysis in the early screening of potentially invasive NIS presence in Mediterranean protected areas and ecosystems. This work describes an applicative example of the efficacy in improving the biomonitoring of lagoon ecosystems using molecular tools and it represents a guideline for the validation of eDNA metabarcoding data for the presence of potentially invasive species.
Flourishing in Darkness: Protist Communities of Water Sites in Shulgan-Tash Cave (Southern Urals, Russia)
Authors: Gogoleva Natalia E. , Nasyrova Marina A. , Balkin Alexander S. , Chervyatsova Olga Ya. , Kuzmina Lyudmila Yu. , Shagimardanova Elena I. , Gogolev Yuri V. , Plotnikov Andrey O.
Published: September 2024

Karst caves, formed by the erosion of soluble carbonate rocks, provide unique ecosystems characterized by stable temperatures and high humidity. These conditions support diverse microbial communities, including wall microbial fouling, aquatic biofilms, and planktonic communities. This study discloses the taxonomic diversity of protists in aquatic biotopes of Shulgan-Tash Cave, a culturally significant site and popular tourist destination, by 18S rRNA gene metabarcoding. Our findings reveal the rich protist communities in the cave’s aquatic biotopes, with the highest diversity observed in Blue Lake at the cave entrance. In contrast, Distant Lake in the depth of the cave was inhabited by specific communities of plankton, mats, and pool fingers, which exhibited lower richness and evenness, and were adapted to extreme conditions (cold, darkness, and limited nutrients). High-rank taxa including Opisthokonta, Stramenopiles, and Rhizaria dominated all biotopes, aligning with observations from other subterranean environments. Specific communities of biotopes inside the cave featured distinct dominant taxa: amoeboid stramenopile (Synchromophyceae) and flagellates (Choanoflagellatea and Sandona) in mats; flagellates (Choanoflagellatea, Bicoecaceae, Ancyromonadida) and amoeboid protists (Filasterea) in pool fingers; flagellates (Ochromonadales, Glissomonadida, Synchromophyceae), fungi-like protists (Peronosporomycetes), and fungi (Ustilaginomycotina) in plankton. The specificity of the communities was supported by LEfSe analysis, which revealed enriched or differentially abundant protist taxa in each type of biotope. The predominance of Choanoflagellatea in the communities of cave mats and pool fingers, as well as the predominance of Synchromophyceae in the cave mats, appears to be a unique feature of Shulgan-Tash Cave. The cold-tolerant yeast Malassezia recorded in other caves was present in both plankton and biofilm communities, suggesting its resilience to low temperatures. However, no potentially harmful fungi were detected, positioning this research as a baseline for future monitoring. Our results emphasize the need for ongoing surveillance and conservation efforts to protect the fragile ecosystems of Shulgan-Tash Cave from human-induced disturbances and microbial invasions.
Recruitment of the Basket Star Astrospartus mediterraneus (Risso, 1826) (Ophiuroidea, Gorgonocephalidae)
Authors: Canessa Martina , Trainito Egidio , Bavestrello Giorgio
Published: September 2024

The occurrence and abundance of Astrospartus mediterraneus (Risso, 1826) have significantly increased in the last three decades in several areas of the Mediterranean Sea. In the Tavolara–Punta Coda Cavallo Marine Protected Area (NE Sardinia, Tyrrhenian Sea, Mediterranean Sea), 60 specimens were observed mainly on the granitic shoals of the Tavolara Channel, an area characterized by very intense currents and high sedimentation. The basket stars were mainly found living as epibionts of gorgonians (Eunicella verrucosa, Paramuricea clavata and Leptogorgia sarmentosa) and massive sponges (Spongia officinalis, S. lamella, Sarcotragus foetidus). We also documented 21 small specimens (3–20 mm in diameter of the oral disc) observed in June 2024 between 27 and 52 m depth on E. verrucosa and P. clavata colonies. The bimodal size-frequency distribution of these specimens suggested that, probably, specimens belong to two different reproductive events occurring in spring 2023 and 2024.
Coahuilasaurus lipani, a New Kritosaurin Hadrosaurid from the Upper Campanian Cerro Del Pueblo Formation, Northern Mexico
Authors: Longrich Nicholas R. , Ramirez Velasco Angel Alejandro , Kirkland Jim , Bermúdez Torres Andrés Eduardo , Serrano-Brañas Claudia Inés
Published: September 2024

The Late Cretaceous of Western North America (Laramidia) supported a diverse dinosaur fauna, with duckbilled dinosaurs (Hadrosauridae) being among the most speciose and abundant members of this assemblage. Historically, collecting and preservational biases have meant that dinosaurs from Mexico and the American Southwest are poorly known compared to those of the northern Great Plains. However, evidence increasingly suggests that distinct species and clades inhabited southern Laramidia. Here, a new kritosaurin hadrosaurid, represented by the anterior part of a skull, is reported from the late Campanian of the Cerro del Pueblo Formation, ~72.5 Ma, in Coahuila, Mexico. The Cerro del Pueblo Formation kritosaur was originally considered to represent the same species as a saurolophine from the Olmos Formation of Sabinas, but the Sabinas hadrosaur is now considered a distinct taxon. More recently, the Cerro del Pueblo Formation kritosaur has been referred to Kritosaurus navajovius. We show it represents a new species related to Gryposaurus. The new species is distinguished by its large size, the shape of the premaxillary nasal process, the strongly downturned dentary, and massive denticles on the premaxilla’s palatal surface, supporting recognition of a new taxon, Coahuilasaurus lipani. The dinosaur assemblage of the Cerro del Pueblo Formation shows higher diversity than the contemporaneous fauna of the Horseshoe Canyon Formation in Alberta. Furthermore, Kritosaurini, Lambeosaurini, and Parasaurolophini all persist into the latest Campanian in southern Laramidia after disappearing from northern Laramidia. These patterns suggest declining herbivore diversity seen at high latitudes may be a local, rather than global phenomenon, perhaps driven by cooling at high latitudes in the Late Campanian and Maastrichtian.
Pan Trapping and Malaise Trapping: A Comparison of Bee Collection Techniques in Subalpine Meadows
Authors: Anderson Nicholas , Petersen Steven , Johnson Robert , Terry Tyson , Kunzelman Jacqueline , Lariviere David , Anderson Val
Published: September 2024

Public lands, managed for multiple uses such as logging, mining, grazing, and recreation, also support vital environmental services like wild bee pollination. A trending decline in wild bees has heightened interest in documenting these key pollinators in their native habitats. Accurate assessment of pollinator community diversity is crucial for population monitoring and informing land management practices. In this study, we evaluate the efficiency of Malaise traps and pan traps in sampling wild bees over three growing seasons in subalpine meadow communities in central Utah. Sixteen trapping sites were established, each with a Malaise trap and an array of blue, white, and yellow pan traps, nine at each site. Weekly collections were made through summer months and a comparison of their effectiveness in capturing bee abundance and species richness was made. Malaise traps captured significantly greater abundance of bees on average, though this was species-dependent. Malaise traps were especially effective at capturing Bombus spp. and larger species. Pan traps were generally more effective with smaller species such as Hylaeus spp. White pan traps outperformed yellow and blue pan traps in terms of abundance and only yellow pan traps in terms of richness. Both methods contributed unique species to the overall collection effort, suggesting that a combination of trapping methods provides a more comprehensive understanding of bee communities. Species accumulation curves indicate that species existing within the community went unencountered in our samples and that more time or perhaps additional methods could aid in best describing the entire community.
TM–IoV: A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles
Authors: Wang Yingxun , Mahmood Adnan , Sabri Mohamad Faizrizwan Mohd , Zen Hushairi
Published: September 2024

The emerging and promising paradigm of the Internet of Vehicles (IoV) employ vehicle-to-everything communication for facilitating vehicles to not only communicate with one another but also with the supporting roadside infrastructure, vulnerable pedestrians, and the backbone network in a bid to primarily address a number of safety-critical vehicular applications. Nevertheless, owing to the inherent characteristics of IoV networks, in particular, of being (a) highly dynamic in nature and which results in a continual change in the network topology and (b) non-deterministic owing to the intricate nature of its entities and their interrelationships, they are susceptible to a number of malicious attacks. Such kinds of attacks, if and when materialized, jeopardizes the entire IoV network, thereby putting human lives at risk. Whilst the cryptographic-based mechanisms are capable of mitigating the external attacks, the internal attacks are extremely hard to tackle. Trust, therefore, is an indispensable tool since it facilitates in the timely identification and eradication of malicious entities responsible for launching internal attacks in an IoV network. To date, there is no dataset pertinent to trust management in the context of IoV networks and the same has proven to be a bottleneck for conducting an in-depth research in this domain. The manuscript-at-hand, accordingly, presents a first of its kind trust-based IoV dataset encompassing 96,707 interactions amongst 79 vehicles at different time instances. The dataset involves nine salient trust parameters, i.e., packet delivery ratio, similarity, external similarity, internal similarity, familiarity, external familiarity, internal familiarity, reward/punishment, and context, which play a considerable role in ascertaining the trust of a vehicle within an IoV network.
Interruption Audio & Transcript: Derived from Group Affect and Performance Dataset
Authors: Doyle Daniel , Şerban Ovidiu
Published: September 2024

Despite the widespread development and use of chatbots, there is a lack of audio-based interruption datasets. This study provides a dataset of 200 manually annotated interruptions from a broader set of 355 data points of overlapping utterances. The dataset is derived from the Group Affect and Performance dataset managed by the University of the Fraser Valley, Canada. It includes both audio files and transcripts, allowing for multi-modal analysis. Given the extensive literature and the varied definitions of interruptions, it was necessary to establish precise definitions. The study aims to provide a comprehensive dataset for researchers to build and improve interruption prediction models. The findings demonstrate that classification models can generalize well to identify interruptions based on this dataset’s audio. This opens up research avenues with respect to interruption-related topics, ranging from multi-modal interruption classification using text and audio modalities to the analysis of group dynamics.
Juvenile Osteochondritis Dissecans: A Case Report
Authors: Nudelman Hermann , Lőrincz Aba , Kassai Tamás , Józsa Gergő
Published: September 2024

(1) Background: This report aims to illustrate the development, progression, diagnosis, and treatment of chronically present articular surface lesions. (2) Methods: In this report, two patients are described from the point of the initial presentation of symptoms to surgical consultation based on radiologic findings. These patients underwent corrective surgery in the form of mosaicplasty to repair lesions present on the articular surface and the underlying subchondral bone. (3) Discussion: Diagnosing juvenile OCD remains challenging due to its variable clinical presentation and minute radiologic discoveries. X-rays are useful; however, the gold standard remains arthroscopy, which can be both diagnostic and therapeutic. Future prospects include the use of novel sonographic methods and the use of artificial intelligence within the given modalities. (4) Conclusions: The detailed imaging provided by MRI, combined with the insights from X-rays and potentially other modalities, allows for a nuanced understanding of this disease. This comprehensive approach ensures that treatment decisions are well-informed, optimising outcomes for young patients with this condition.
Early-Stage Prototype Assessment of Cost-Effective Non-Intrusive Wearable Device for Instant Home Fetal Movement and Distress Detection: A Pilot Study
Authors: Mohamed Hana , Kathriarachchi Suresh , Kahatapitiya Nipun , Silva Bhagya , Kalupahana Deshan , Edirisinghe Sajith , Wijenayake Udaya , Ravichandran Naresh , Wijesinghe Ruchire
Published: September 2024

Clinical fetal monitoring devices can only be operated by medical professionals and are overly costly, prone to detrimental false positives, and emit radiation. Thus, highly accurate, easily accessible, simplified, and cost-effective fetal monitoring devices have gained an enormous interest in obstetrics. In this study, a cost-effective and user-friendly wearable home fetal movement and distress detection device is developed and assessed for early-stage design progression by facilitating continuous, comfortable, and non-invasive monitoring of the fetus during the final trimester. The functionality of the developed prototype is mainly based on a microcontroller, a single accelerometer, and a specialized fetal phonocardiography (fPCG) acquisition board with a low-cost microphone. The developed system is capable of identifying fetal movement and monitors fetal heart rhythm owing to its considerable sensitivity. Further, the device includes a Global System for Mobile Communication (GSM)-based alert system for instant distress notifications to the mother, proxy, and emergency services. By incorporating digital signal processing, the system achieves zero false negatives in detecting fetal movements, which was validated against an open-source database. The acquired results clearly substantiated the efficacy of the fPCG acquisition board and alarm system, ensuring the prompt identification of fetal distress.
Perceived Enablers of and Barriers to Serious Game as Oral Histology Learning Strategy for Undergraduate Dental Students
Authors: Amir Lisa R. , Dewatmoko Salsabila N. , Leonardy Irene C. , Yanuar Rezon , Suniarti Dewi F. , Idrus Erik , Sipiyaruk Kawin , Puspitawati Ria , Wimardhani Yuniardini
Published: September 2024

Previously, we reported the serious game HistoRM as an innovative learning approach for an oral histology course. This study aimed to examine the impact of HistoRM on summative assessment and the enablers and barriers factors affecting HistoRM as an interactive learning strategy in an oral histology course. A crossover randomized controlled trial was performed. Study participants were first-year dental students at the Universitas Indonesia. The average final grades of students who participated in HistoRM serious game were significantly higher than those of students who did not participate in this trial (p < 0.001). Positive responses of HistoRM were observed in the learning content, games and learning experience domains. The enabler factors most recognized by the students were the game method, which helped students to understand the learning materials; the immediate feedback provided following each gameplay; as well as the fun and interesting gameplay. The barrier factors most recognized by the students were some challenges of the gameplay, which resulted in a longer time needed to study. While the HistoRM serious game can stimulate student motivation and engagement in learning oral histology, overcoming the barriers is essential for the implementation of serious games as a complementary learning approach in the dental curriculum.
Traumatic Dental Injuries among Adolescents and Young Adults in Iași, Romania: Legal and Medical Perspectives
Authors: Răzvan Giuvara Constantin , Costan Victor Vlad , Boisteanu Otilia , Armencia Adina , Ciofu Mihai , Balcos Carina , Calin Gabriela , Iliescu Diana Bulgaru , Hurjui Loredana Liliana
Published: September 2024

Adolescents and young adults’ active lifestyles make dental trauma a significant medical concern. Aim: This study aims to assess the etiology, frequency, and localization of dental and periodontal trauma in adolescents and young adults, along with these individuals’ predisposition based on age, gender, and residence. Materials and Methods This retrospective study included 109 adolescents and young adults from a database of the Emergency and Oral and Maxillofacial Surgery department at “Sf. Spiridon” Hospital, Iasi, Romania. The collected data included demographic details, mechanisms of dental and periodontal trauma, treatment approaches, and clinical outcomes. Statistical analysis was performed using SPSS 26.0, with comparisons based on age, gender, and residence. Results: Enamel fractures (23.9%) and enamel-dentin fractures without pulp exposure (20.2%) were the most frequent dental injuries. Concussion (58.7%), subluxation (21.1%), luxation, avulsion (7.3%), and extrusion (5.5%) were common periodontal injuries. The anterior region of the dental arch accounted for the majority (60.6%) of injuries. Adolescents under 17 years were more prone to enamel-dentin fractures without pulp exposure (23.8%), enamel-dentin fractures with pulp exposure (20.6%), and root fractures (20.6%), while young adults over 18 years had a higher incidence of enamel fractures (32.6%) and crown-root fractures (30.4%). Falls (66.7%) were the predominant cause of trauma for female patients, whereas male patients were more often injured during sports activities (49.3%). The younger age group was 0.29 times more likely to sustain enamel-dentin fractures without pulp exposure (p = 0.049, OR = 0.291) and root fractures (p = 0.047, OR = 0.241). Conclusions: Traumatic dental injuries are more prevalent in young adults compared to adolescents, with falls and sports activities being the most common causes, particularly among males. These findings emphasize the need for targeted preventive programs aimed at reducing the incidence of dento-periodontal trauma in these age groups.
Applications of GANs to Aid Target Detection in SAR Operations: A Systematic Literature Review
Authors: Correa Vinícius , Funk Peter , Sundelius Nils , Sohlberg Rickard , Ramos Alexandre
Published: September 2024

Research on unmanned autonomous vehicles (UAVs) for search and rescue (SAR) missions is widespread due to its cost-effectiveness and enhancement of security and flexibility in operations. However, a significant challenge arises from the quality of sensors, terrain variability, noise, and the sizes of targets in the images and videos taken by them. Generative adversarial networks (GANs), introduced by Ian Goodfellow, among their variations, can offer excellent solutions for improving the quality of sensors, regarding super-resolution, noise removal, and other image processing issues. To identify new insights and guidance on how to apply GANs to detect living beings in SAR operations, a PRISMA-oriented systematic literature review was conducted to analyze primary studies that explore the usage of GANs for edge or object detection in images captured by drones. The results demonstrate the utilization of GAN algorithms in the realm of image enhancement for object detection, along with the metrics employed for tool validation. These findings provide insights on how to apply or modify them to aid in target identification during search stages.
Multi-Node Joint Jamming Scheme for Secure UAV-Aided NOMA-CDRT Systems: Performance Analysis and Optimization
Authors: Xu Yao , Jia Shaobo , Guo Jichong , Zhu Jianyue , Liu Lilan , Zhang Zhizhong
Published: September 2024

Unmanned aerial vehicle (UAV) communication using non-orthogonal multiple access-based coordinated direct and relay transmission (NOMA-CDRT) supports both massive connectivity and wide-area coverage, becoming a key technology for future emergency rescue communications. However, relay forwarding and high-quality line-of-sight links may subject UAV-aided NOMA-CDRT to multiple eavesdropping attempts by saboteurs. Therefore, we propose a multi-node joint jamming scheme using artificial noise (AN) for the UAV-assisted NOMA-CDRT to improve the system’s physical layer security. In the proposed scheme, the base station directly serves a nearby user while using a UAV relay to serve a disaster-affected user, and both the users and the UAV relay utilize AN to jointly interfere with eavesdroppers around the users. To accurately characterize and maximize the ergodic secrecy sum rate (ESSR) of the proposed scheme, we derive the corresponding closed-form expressions and design a joint power allocation and interference control (JPAIC) algorithm using particle swarm optimization. Simulations verify the correctness of the theoretical analysis, the ESSR advantage of the proposed scheme compared with the conventional NOMA-CDRT, and the effectiveness of the proposed JPAIC.
Tiny-Object Detection Based on Optimized YOLO-CSQ for Accurate Drone Detection in Wildfire Scenarios
Authors: Luan Tian , Zhou Shixiong , Liu Lifeng , Pan Weijun
Published: September 2024

Wildfires, which are distinguished by their destructive nature and challenging suppression, present a significant threat to ecological environments and socioeconomic systems. In order to address this issue, the development of efficient and accurate fire detection technologies for early warning and timely response is essential. This paper addresses the complexity of forest and mountain fire detection by proposing YOLO-CSQ, a drone-based fire detection method built upon an improved YOLOv8 algorithm. Firstly, we introduce the CBAM attention mechanism, which enhances the model’s multi-scale fire feature extraction capabilities by adaptively adjusting weights in both the channel and spatial dimensions of feature maps, thereby improving detection accuracy. Secondly, we propose an improved ShuffleNetV2 backbone network structure, which significantly reduces the model’s parameter count and computational complexity while maintaining feature extraction capabilities. This results in a more lightweight and efficient model. Thirdly, to address the challenges of varying fire scales and numerous weak emission targets in mountain fires, we propose a Quadrupled-ASFF detection head for weighted feature fusion. This enhances the model’s robustness in detecting targets of different scales. Finally, we introduce the WIoU loss function to replace the traditional CIoU object detection loss function, thereby enhancing the model’s localization accuracy. The experimental results demonstrate that the improved model achieves an mAP@50 of 96.87%, which is superior to the original YOLOV8, YOLOV9, and YOLOV10 by 10.9, 11.66, and 13.33 percentage points, respectively. Moreover, it exhibits significant advantages over other classic algorithms in key evaluation metrics such as precision, recall, and F1 score. These findings validate the effectiveness of the improved model in mountain fire detection scenarios, offering a novel solution for early warning and intelligent monitoring of mountain wildfires.
HDCCT: Hybrid Densely Connected CNN and Transformer for Infrared and Visible Image Fusion
Authors: Li Xue , He Hui , Shi Jin
Published: September 2024

Multi-modal image fusion is a methodology that combines image features from multiple types of sensors, effectively improving the quality and content of fused images. However, most existing deep learning fusion methods need to integrate global or local features, restricting the representation of feature information. To address this issue, a hybrid densely connected CNN and transformer (HDCCT) fusion framework is proposed. In the proposed HDCCT framework, the network of the CNN-based blocks obtain the local structure of the input data, and the transformer-based blocks obtain the global structure of the original data, significantly improving the feature representation. In the fused image, the proposed encoder–decoder architecture is designed for both the CNN and transformer blocks to reduce feature loss while preserving the characterization of all-level features. In addition, the cross-coupled framework facilitates the flow of feature structures, retains the uniqueness of information, and makes the transform model long-range dependencies based on the local features already extracted by the CNN. Meanwhile, to retain the information in the source images, the hybrid structural similarity (SSIM) and mean square error (MSE) loss functions are introduced. The qualitative and quantitative comparisons of grayscale images with infrared and visible image fusion indicate that the suggested method outperforms related works.
The Impact of the Weather Forecast Model on Improving AI-Based Power Generation Predictions through BiLSTM Networks
Authors: Jankauskas Mindaugas , Serackis Artūras , Paulauskas Nerijus , Pomarnacki Raimondas , Hyunh Van Khang
Published: September 2024

This study aims to comprehensively analyze five weather forecasting models obtained from the Open-Meteo historical data repository, with a specific emphasis on evaluating their impact in predicting wind power generation. Given the increasing focus on renewable energy, namely, wind power, accurate weather forecasting plays a crucial role in optimizing energy generation and ensuring the stability of the power system. The analysis conducted in this study incorporates a range of models, namely, ICOsahedral Nonhydrostatic (ICON), the Global Environmental Multiscale Model (GEM Global), Meteo France, the Global Forecast System (GSF Global), and the Best Match technique. The Best Match approach is a distinctive solution available from the weather forecast provider that combines the data from all available models to generate the most precise forecast for a particular area. The performance of these models was evaluated using various important metrics, including the mean squared error, the root mean squared error, the mean absolute error, the mean absolute percentage error, the coefficient of determination, and the normalized mean absolute error. The weather forecast model output was used as an essential input for the power generation prediction models during the evaluation process. This method was confirmed by comparing the predictions of these models with actual data on wind power generation. The ICON model, for example, outscored others with a root mean squared error of 1.7565, which is a tiny but essential improvement over Best Match, which had a root mean squared error of 1.7604. GEM Global and Gsf Global showed more dramatic changes, with root mean squared errors (RMSEs) of 2.0086 and 2.0242, respectively, indicating a loss in prediction accuracy of around 24% to 31% compared to ICON. Our findings reveal significant disparities in the precision of the various models used, and certain models exhibited significantly higher predictive precision.
DynER: Optimized Test Case Generation for Representational State Transfer (REST)ful Application Programming Interface (API) Fuzzers Guided by Dynamic Error Responses
Authors: Chen Juxing , Chen Yuanchao , Pan Zulie , Chen Yu , Li Yuwei , Li Yang , Zhang Min , Shen Yi
Published: September 2024

Modern web services widely provide RESTful APIs for clients to access their functionality programmatically. Fuzzing is an emerging technique for ensuring the reliability of RESTful APIs. However, the existing RESTful API fuzzers repeatedly generate invalid requests due to unawareness of errors in the invalid tested requests and lack of effective strategy to generate legal value for the incorrect parameters. Such limitations severely hinder the fuzzing performance. In this paper, we propose DynER, a new test case generation method guided by dynamic error responses during fuzzing. DynER designs two strategies of parameter value generation for purposefully revising the incorrect parameters of invalid tested requests to generate new test requests. The strategies are, respectively, based on prompting Large Language Model (LLM) to understand the semantics information in error responses and actively accessing API-related resources. We apply DynER to the state-of-the-art fuzzer RESTler and implement DynER-RESTler. DynER-RESTler outperforms foREST on two real-world RESTful services, WordPress and GitLab with a 41.21% and 26.33% higher average pass rate for test requests and a 12.50% and 22.80% higher average number of unique request types successfully tested, respectively. The experimental results demonstrate that DynER significantly improves the effectiveness of test cases and fuzzing performance. Additionally, DynER-RESTler finds three new bugs.
A Novel Clark Distance-Based Decision-Making Algorithm on Intuitionistic Fuzzy Sets
Authors: Wu Yuchen , Wang Ziwen , Zhang Lei
Published: September 2024

Fuzzy sets possess remarkable abilities in expressing and handling information uncertainty, which has resulted in their widespread application in various fields. Nevertheless, distance measurement between IFSs for quantitating their differences and levels of differentiation has remained an open problem that deserves attention. Despite the development of various metrics, they either lack intuitive insight or do not satisfy the axioms of distance measurement, leading to counterintuitive results. To address these issues, this paper proposed a distance measurement method based on Clark divergence, which satisfies the distance measurement axioms and exhibits nonlinearity. Numerical examples demonstrate that our method effectively distinguishes different indicators, yielding more reasonable results. Moreover, when comparing relative differences of the results, our method demonstrated superior adaptability to complex environmental decision-making, providing decision-makers with more accurate and confidential judgments. In our numerical and pattern classification application tests, we achieve an accuracy of 98%, a 40% increase in computing time efficiency and a relative diversity improvement of 35%. The pattern classification algorithm designed in this paper will offer a promising solution to inference problems.