bluuebunny/crossref_metadata_2025 huggingface dataset:
Dose-Volume Histogram Parameters and Quality of Life in Patients with Prostate Cancer Treated with Surgery and High-Dose Volumetric-Intensity-Modulated Arc Therapy to the Prostate Bed
Authors: Hanke Luca , Tang Hongjian , Schröder Christina , Windisch Paul , Kudura Ken , Shelan Mohamed , Buchali André , Bodis Stephan , Förster Robert , Zwahlen Daniel
Published: July 2023

Introduction: Prostate bed radiotherapy (RT) is a major affecter of patients’ long-term quality of life (QoL). To ensure the best possible outcome of these patients, dose constraints are key for optimal RT planning and delivery. However, establishing refined dose constraints requires access to patient-level data. Therefore, we aimed to provide such data on the relationship between OAR and gastrointestinal (GI) as well as genitourinary (GU) QoL outcomes of a homogenous patient cohort who received dose-intensified post-operative RT to the prostate bed. Furthermore, we aimed to conduct an exploratory analysis of the resulting data. Methods: Patients who were treated with prostate bed RT between 2010 and 2020 were inquired about their QoL based on the Expanded Prostate Cancer Index Composite (EPIC). Those (n = 99) who received volumetric arc therapy (VMAT) of at least 70 Gy to the prostate bed were included. Dose-volume histogram (DVH) parameters were gathered and correlated with the EPIC scores. Results: The median age at the time of prostate bed RT was 68.9 years, and patients were inquired about their QoL in the median 2.3 years after RT. The median pre-RT prostate-specific antigen (PSA) serum level was 0.35 ng/mL. The median duration between surgery and RT was 1.5 years. The median prescribed dose to the prostate bed was 72 Gy. A total of 61.6% received prostate bed RT only. For the bladder, the highest level of statistical correlation (p < 0.01) was seen for V10-20Gy, Dmean and Dmedian with urinary QoL. For bladder wall, the highest level of statistically significant correlation (p < 0.01) was seen for V5-25Gy, Dmean and Dmedian with urinary QoL. Penile bulb V70Gy was statistically significantly correlated with sexual QoL (p < 0.05). A larger rectal volume was significantly correlated with improved bowel QoL (p < 0.05). Sigmoid and urethral DVH parameters as well as the surgical approach were not statistically significantly correlated with QoL. Conclusion: Specific dose constraints for bladder volumes receiving low doses seem desirable for the further optimization of prostate bed RT. This may be particularly relevant in the context of the aspiration of establishing focal RT of prostate cancer and its local recurrences. Our comprehensive dataset may aid future researchers in achieving these goals.
The Influence of Carboxyl-Functionalized Carbon Dots on Ethanol Selectivity in Gas Sensing
Authors: Tian Futong , Ma Guoxing , Zhao Xing , Gao Jie , Zhang Jingwen , Suo Hui , Zhao Chun
Published: July 2023

For semiconductor tin dioxide (SnO2) materials, the oxygen adsorption theory often struggles to explain their selectivity towards specific gases. Therefore, it is worth considering altering the surface functional groups of SnO2 to modify its surface state and enhance its selectivity towards specific gases. Due to the rich functional groups on the surfaces of carbon dots, this study employed a hydrothermal method to prepare three types of carbon dots with varying carboxyl functional group contents by adjusting the hydrothermal time. These carbon dots were then used as dopants and combined with SnO2 to create composite gas-sensitive devices. The gas-sensing test results indicate that the introduction of carboxyl functional groups can enhance the selectivity of SnO2 towards ethanol. Furthermore, at any operating temperature within the range of 150–300 °C, the higher the carboxyl functional group content on the surface of carbon dot-doped SnO2, the higher the sensitivity towards ethanol. By employing density functional theory (DFT), the interaction energies between the surfaces of carbon dots and surface carboxyl groups with the target gas were calculated. These calculations validated the gas-sensing test results, confirming that the presence of carboxyl functional groups enhances the selectivity towards ethanol. The results of this study can provide new insights into the research on the selective mechanism of gas-sensitive materials.
Our Experiences with Asparaginase Activity Measurements in Children with Lymphoblastic Diseases
Authors: Müller Judit , Egyed Petra , Erdelyi Daniel , Kovacs Krisztian , Mudra Katalin , Szabo Sandor , Egyed Balint , Gabor Kovacs
Published: July 2023

Background: Asparaginase is a key component of chemotherapy protocols for the treatment of lymphoblastic malignancies among children. Adequate asparagine depletion is an important factor to achieve optimal therapeutic outcomes. Methods: Over a 3.5 year period, 106 patients were monitored for asparaginase activity (329 samples) in a single center of the Hungarian Pediatric Oncology–Hematology Group. In Hungary, three asparaginase products are available: native E. coli ASNase (Kidrolase), a pegylated form of this enzyme (Pegaspargase) and another native product from Erwinia chrysanthemi (Erwinase). A retrospective data analysis was performed. Results: In 81% (268/329) of our patients, AEA levels were in the optimal therapeutic range of over 100 IU/L. Of 106 patients, 13 (12%) were diagnosed with ‘silent inactivation’. Conclusions: Monitoring of AEA can help to identify patients with ‘silent inactivation’ and their asparaginase therapy can thus be optimized.
Antimicrobial Peptides and Interleukins in Cleft Soft Palate
Authors: Deņisova Arina , Pilmane Māra , Kažoka Dzintra
Published: July 2023

Cleft palate is one of the most common and well-studied congenital anomalies; however, the role of protective tissue factors in its pathophysiology is still debated. The aim of our study was to evaluate interleukin and antimicrobial peptide appearance and distribution in cleft palate. Eight soft palate samples were obtained during veloplasty procedures. Immunohistochemical staining was applied to detect HBD-2-, HBD-3-, HBD-4-, LL-37-, IL-10-, and CD-163-positive cells via light microscopy. For statistical evaluation, the Mann–Whitney U test and Spearman’s rank correlation coefficient were used. A significant difference between study groups was observed for HBD-2 and IL-10 in epithelial and connective tissue as well as HBD-4 in connective tissue. The number of HBD-3-positive cells was moderate in the patients, and few were observed in the controls. The number of LL-37-positive cells varied from a moderate amount to a numerous amount in both study groups, whilst CD-163 marked a moderate number of positive cells in patients, and a few-to-moderate amount was observed in the controls. Numerous correlations between studied factors were revealed in cleft tissues. The increase in antimicrobial peptides HBD-2 and HBD-4 and anti-inflammatory cytokine IL-10 suggested a wide compensatory elevation of the local immune system against cleft-raised tissue changes. The correlations between the studied factors (HBD-2, HBD-3, HBD-4, LL-37, and IL-10) proved the synergistic involvement of common local defense factors in postnatal cleft palate morphopathogenesis.
Microbiomic and Metabolomic Analyses Unveil the Protective Effect of Saffron in a Mouse Colitis Model
Authors: Singh Gulshan , Brim Hassan , Haileselassie Yeneneh , Varma Sudhir , Habtezion Aida , Rashid Mudasir , Sinha Sidhartha R. , Ashktorab Hassan
Published: July 2023

Despite the existence of effective drugs used to treat inflammatory bowel disease (IBD), many patients fail to respond or lose response over time. Further, many drugs can carry serious adverse effects, including increased risk of infections and malignancies. Saffron (Crocus sativus) has been reported to have anti-inflammatory properties. Its protective role in IBD and how the microbiome and metabolome play a role has not been explored extensively. We aimed to establish whether saffron treatment modulates the host microbiome and metabolic profile in experimental colitis. Colitis was induced in C57BL/6 mice with 3% DSS and treated with either saffron in a dose of 20 mg/kg body weight or vehicle through daily gavage. On day 10, stool pellets from mice were collected and analyzed to assess saffron’s effect on fecal microbiota and metabolites through 16S rRNA sequencing and untargeted primary metabolite analysis. Saffron treatment maintained gut microbiota homeostasis by counter-selecting pro-inflammatory bacteria and maintained Firmicutes/Bacteroides ratio, which was otherwise disturbed by DSS treatment. Several metabolites (uric acid, cholesterol, 2 hydroxyglutaric acid, allantoic acid, 2 hydroxyhexanoic acid) were altered significantly with saffron treatment in DSS-treated mice, and this might play a role in mediating saffron’s colitis-mitigating effects. These data demonstrate saffron’s therapeutic potential, and its protective role is modulated by gut microbiota, potentially acting through changes in metabolites.
Pathology and Molecular Biology of Melanoma
Authors: Timis Tanase , Bergthorsson Jon Thor , Greiff Victor , Cenariu Mihai , Cenariu Diana
Published: July 2023

Almost every death in young patients with an advanced skin tumor is caused by melanoma. Today, with the help of modern treatments, these patients survive longer or can even achieve a cure. Advanced stage melanoma is frequently related with poor prognosis and physicians still find this disease difficult to manage due to the absence of a lasting response to initial treatment regimens and the lack of randomized clinical trials in post immunotherapy/targeted molecular therapy settings. New therapeutic targets are emerging from preclinical data on the genetic profile of melanocytes and from the identification of molecular factors involved in the pathogenesis of malignant transformation. In the current paper, we present the diagnostic challenges, molecular biology and genetics of malignant melanoma, as well as the current therapeutic options for patients with this diagnosis.
Effect of Nb Content on Phase Transformation and Comprehensive Properties of TiNb Alloy Coating
Authors: Zheng Yu , Xu Peng
Published: July 2023

As a β phase transformation promoting element of titanium alloy, the Nb element can induce different phase transformations of the alloy, improving the comprehensive properties of the alloy. However, the research on the effect of Nb content on the properties of TiNb alloy coating during laser cladding is not comprehensive. Herein, TixNb (x = 32.5~62.5 wt.%) alloy coatings were prepared by laser cladding technology, and their mechanical properties, corrosion resistance, and biocompatibility were analyzed. The results show that the Nb element promotes the precipitation of different phase components in the phase transformation-induced coating of titanium alloy. The grain refinement during the laser cladding process effectively improves the microhardness of the TiNb alloy coating. At the same time, the wear resistance of the α″ + β dual-phase Ti32.5Nb alloy is enhanced. In addition, with the increase in Nb content, the coating exhibits better corrosion resistance. In vitro cell experiments showed that the TiNb alloy coating had excellent biocompatibility compared to the TC4 substrate. Therefore, the laser-clad TiNb alloy coating has high comprehensive performance and has reference value in the field of biological implantation.
Unleashing the Power of Graphene-Based Nanomaterials for Chromium(VI) Ion Elimination from Water
Authors: Jibin Keloth , Augustine Silpa , Velayudhan Prajitha , George Jesiya , Krishnageham Sidharthan Sisanth , Paulose Sylas , Thomas Sabu
Published: July 2023

Graphene-oxide-based nanomaterials have gained attention in recent years in the field of heavy metal removal. In this work, graphene oxide (GO) and graphene-oxide-coated silica nanoparticles (GO/SiO2) were synthesized for the efficient removal of Cr(VI) ions from water. Synthesized nanosorbents were characterized by FTIR, Raman spectroscopy, and Transmission Electron Microscopy (TEM). The effects of the pH and the concentration of Cr(VI) ions in adsorption, using GO and GO/SiO2, was studied using the batch process. The results of the study indicated that the maximum removal percentage was shown at pH 3 for both adsorbents. Comparatively, GO/SiO2 showed a higher removal percentage (92.28%) than GO (86.15%) for Cr(VI) at a concentration of 50 ppm. The results validate that the removal of Cr(VI) ions is highly concentration-dependent and pH-dependent. This study shows that GO and GO/SiO2 are efficient adsorbents and that GO/SiO2 has great potential over GO for the removal of Cr(VI) ions from water.
Chemical Composition and Spectroscopic Characteristics of Heat-Treated Rubies from Madagascar, Mozambique and Tanzania
Authors: Yang Ling , Lu Qi , Ma Di , Zheng Hairong , Hu Ruoshui , Shi Zhuohang , Qin Binrong
Published: July 2023

The chemical composition and spectra of rubies heat-treated with high temperatures (above 1200 °C) from Madagascar, Mozambique and Tanzania were analyzed by electron microprobe, LA-ICP-MS, Fourier transform infrared spectroscopy, Raman spectroscopy and UV-VIS spectroscopy. Compared with untreated rubies, the red hue of treated ruby intensifies while its blue tint diminishes, leading to increased cracks. The infrared spectra exhibit a distinct absorption peak at 3738 cm−1, attributed to water because of thermal treatment. After heat treatment, the absorption intensity decreases. Ultraviolet radiation reveals an enhancement in the electron transition of Cr3+ and ion transition of Fe3+ and Fe2+, with a shift towards shorter wavelengths observed in the absorption bandwidth. These can be utilized to indicate the basis of ruby identification through heat treatment.
Toxicity Profile of Chimeric Antigen Receptor T-Cell and Bispecific Antibody Therapies in Multiple Myeloma: Pathogenesis, Prevention and Management
Authors: Markouli Mariam , Ullah Fauzia , Unlu Serhan , Omar Najiullah , Lopetegui-Lia Nerea , Duco Marissa , Anwer Faiz , Raza Shahzad , Dima Danai
Published: July 2023

Multiple myeloma is the second-most common hematologic malignancy in adults worldwide. Despite ongoing advancement in therapeutic modalities, it remains an incurable disease with a 5-year survival rate of approximately 50%. The recent development and introduction of anti-BCMA immunotherapies into clinical practice, including chimeric antigen receptor T-cell (CAR-T) therapies and bispecific antibodies, has radically shifted the treatment paradigm. However, despite the promising potential of these therapies for broader application, frequent and significant adverse effects have been reported, both in short- and in long-term settings, requiring increasing awareness and vigilance in the treating team, close monitoring, and prompt interventions with a multidisciplinary approach. In this review, we will discuss the toxicities associated with CAR-T cell and bispecific antibody therapies, focusing on results from major clinical studies and real-world observations. In addition, we will emphasize on effective strategies for prevention, monitoring and management, and provide expert recommendations.
Germination and Early Seedling Growth of High Andean Native Plants under Heavy Metal Stress
Authors: Parera Victoria , Parera Carlos Alberto , Feresin Gabriela Egly
Published: July 2023

The development of large-scale mining activity along the Central Andes of Argentina (CAA) has generated significant amounts of waste materials containing heavy metals. Phytoremediation is a promising eco-friendly, low-cost, and effective technology for the removal of heavy metals. The present study aimed to identify two native dominant species from the CCA, Adesmia subterranea and A. pinifolia, as metal-tolerant plant species for the first time, by evaluating the germination and early seedling growth at different concentrations (ppm) of Cd (3, 4.5 and 6), Ni (150, 225 and 300), As (20, 30 and 40), and Hg (0.8, 1.2 and 1.6) Early seedling growth was found to be more sensitive to heavy metals than germination. Ni and As exhibited the greatest inhibitory effect on both species’ germination percentages. In contrast, with Cd and Hg, no inhibitory effect was recorded. Root length, metal tolerance index, and fresh and dry weight were stimulated with Hg. However, the phytotoxic effect was greater as the concentration of Ni, As, and Cd increased. As an overall conclusion, the order of toxicity for these species can be classified as Ni > As > Cd > Hg. Therefore, Adesmia species could be considered as candidates for phytoremediation of soils contaminated with Hg and low concentrations of Cd.
Landscape and Marine Environmental Factors Jointly Regulate the Intertidal Species Richness and Community Structure in the Islands of South Korea
Authors: Lee Min-Ki , Lee Yong-Ju , Lee Chang-Bae
Published: July 2023

Most studies on island biogeography have focused on the terrestrial taxa; however, there are few studies on the drivers of diversity and community structure of intertidal organisms on islands. We evaluated the effect of landscape and marine environmental factors on the species richness (SR), functional diversity (FD), and community structure (SES.MFD) of intertidal invertebrates among the overall, inhabited, and uninhabited islands. Using the data on the intertidal organisms from 78 islands in South Korea, we implemented variable selection and piecewise structural equation modeling to determine the causal relationships between the SR, FD, and SES.MFD with four landscapes (i.e., island area, coastline length, distance from the mainland, and structural connectivity) and three marine environment factors (i.e., mean annual sea surface temperature variation, wind speed, and evapotranspiration). The coastline length had a positive effect on the SR and SES.MFD in the overall islands including inhabited and uninhabited islands. The SR and FD were negatively affected by the variation in sea surface temperature. The relative importance of the landscape and marine environmental factors differed between the inhabited and uninhabited islands. That is, the inhabited islands were mainly affected by the coastline length, whereas uninhabited islands were regulated by marine environmental factors. Our results demonstrated that the biotic factors of the island intertidal ecosystems are controlled by the interactions between the biotic and various environmental factors. Moreover, the results emphasize that the water stress on the intertidal organisms due to climate change may lead to a loss of biodiversity and functional clustering.
Pleistocene Glacial Refugia in the Don River Basin: Witness from the Endangered Depressed River Mussel
Authors: Vikhrev Ilya V. , Yunitsyna Olesya A. , Kondakov Alexander V. , Pestova Elizaveta P. , Bovykina Galina V. , Konopleva Ekaterina S. , Kruk Darya V. , Lyubas Artem A. , Soboleva Alena A. , Bolotov Ivan N.
Published: July 2023

The depressed river mussel Pseudanodonta complanata (Rossmässler, 1835) is an endangered freshwater bivalve with sparse distribution across Europe. Despite its high conservation priority, available data on the current population genetics and biogeography of P. complanata are very limited. In this paper, we studied the genetic diversity and differentiation of P. complanata based on newly sequenced COI and ND1 gene fragments, and on available sequences from the NCBI GenBank. We discovered a localized and highly divergent lineage in the Don River basin and a widespread but low diversified lineage distributed from the Volga River basin to the Oise River in France. A star-like haplotype network, results of mismatch analysis, and significant negative values of neutrality tests reveal that the pan-European lineage went through a bottleneck event. The discovery of the separate lineage in the Don River basin is and additional evidence of the existence of Pleistocene glacial refugia in the south of the Russian Plain. Moreover, this finding confirms the significance of the Azov Sea drainage as a freshwater biodiversity hotspot of great conservation importance.
Assessment of Maize Silage Quality under Different Pre-Ensiling Conditions
Authors: Serva Lorenzo , Andrighetto Igino , Segato Severino , Marchesini Giorgio , Chinello Maria , Magrin Luisa
Published: July 2023

Maize silage suffers from several factors that affect the final quality and, to some extent, pre-ensiled conditions that can be potentially tuned during harvesting. After assessing new indices for silage quality under lab-scale conditions, several trials have been conducted to find associations between fresh maize characteristics and silage features. Among the first, we included field input levels, FAO class, maturity stage, use of bacterial inoculants, sealing delay and chemical traits, whereas, among the latter, we assessed density and porosity, pH, fermentative profile, dry matter loss and aerobic stability. The trials were conducted using vacuum bags or mini silo buckets. More than 1500 maize samples harvested in Northeast Italy were analysed during the 2016–2022 period. Moreover, to evaluate silage aerobic stability, the fermentative profile and temperature were measured 14 days after the opening of the silo. The association between silage quality and aerobic stability was assessed, and a prognostic risk score was used to calculate the probability of aerobic instability. The dataset could provide baseline information to promote the continuous improvement of maize silage management from different botanical and crop fields, thus improving agronomic and animal farm resource allocation from a precision agriculture perspective.
Clinical Course and Outcome of Prenatally Detected 22q11.2 Deletion Syndrome—A Retrospective Analysis
Authors: Paternostro Chiara , Springer Stephanie , Kasprian Gregor , Yerlikaya-Schatten Gülen , Reischer Theresa
Published: July 2023

The 22q11.2 deletion syndrome (22q11.2 DS) is known as the most common microdeletion syndrome. Due to its variable clinical phenotype, prenatal diagnosis can be challenging. The aim of this retrospective study was to evaluate the clinical course and pregnancy outcome of cases with prenatally diagnosed 22q11.2 deletion syndrome (DS) as well as to evaluate the role of prenatal magnetic resonance imaging (MRI) and postmortem examination. In total, 21 cases who underwent prenatal ultrasound examination and pregnancy care at the Department of Obstetrics and Gynecology at the Medical University of Vienna between 2012 and 2022 were included. The majority of the cases were genetically diagnosed using fluorescent in situ hybridization (FISH). The median gestational age (GA) at genetic diagnosis was 23.0 weeks (IQR 21.4–24.8 weeks). CHDs were detected in all fetuses and the most common extracardiac manifestation was thymus hypo/aplasia followed by genitourinary anomalies. Prenatal magnetic resonance imaging (MRI) revealed additional diagnostic information in three of ten cases. Overall, 14 patients opted for drug-induced TOP, of which 9 cases had a feticide prior to the induction of labor. The majority of craniofacial malformations were only detected by autopsy. In conclusion, the majority of cases prenatally diagnosed with 22q11.2 DS had an absent or hypoplastic thymus noted antenatally in addition to the detected CHD, and almost half of the cases had another extracardiac malformation of predominantly genitourinary origin. Furthermore, prenatal MRIs confirmed previously detected malformations, but only provided additional diagnostic information in three out of ten cases, whereas postmortem examination diagnosed most of the craniofacial anomalies and should always be conducted, serving as an important quality indicator for prenatal imaging.
SARS-CoV-2 Testing of Emergency Department Patients Using cobas® Liat® and eazyplex® Rapid Molecular Assays
Authors: Egerer Renate , Edel Birgit , Hornung Franziska , Deinhardt-Emmer Stefanie , Baier Michael , Lewejohann Jan-Christoph , Pfister Wolfgang , Löffler Bettina , Rödel Jürgen
Published: July 2023

Rapid testing for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) of patients presenting to emergency departments (EDs) facilitates the decision for isolation on admission to hospital wards. Differences in the sensitivity of molecular assays have implications for diagnostic workflows. This study evaluated the performance of the cobas® Liat® RT-PCR, which is routinely used as the initial test for ED patients in our hospitals, compared with the eazyplex® RT-LAMP. A total of 378 oropharyngeal and nasal swabs with positive Liat® results were analysed. Residual sample aliquots were tested using NeuMoDx™, cobas® RT-PCR, and the eazyplex® assay. Patients were divided into asymptomatic (n = 157) and symptomatic (n = 221) groups according to the WHO case definition. Overall, 14% of positive Liat® results were not confirmed by RT-PCR. These samples were mainly attributed to 26.8% of asymptomatic patients, compared to 3.8% of the symptomatic group. Therefore, positive Liat® results were used to provisionally isolate patients in the ED until RT-PCR results were available. The eazyplex® assay identified 62% and 90.6% of RT-PCR-confirmed cases in asymptomatic and symptomatic patients, respectively. False-negative eazyplex® results were associated with RT-PCR Ct values > 30, and were more frequent in the asymptomatic group than in the symptomatic group (38.1% vs. 5.1%, respectively). Both the Liat® and eazyplex® assays are suitable for testing symptomatic patients. Their use in screening asymptomatic patients depends on the need to exclude any infection or identify those at high risk of transmission.
Object Detection Models and Optimizations: A Bird’s-Eye View on Real-Time Medical Mask Detection
Authors: Koutsomitropoulos Dimitrios A. , Gogou Ioanna C.
Published: July 2023

Convolutional Neural Networks (CNNs) are well-studied and commonly used for the problem of object detection thanks to their increased accuracy. However, high accuracy on its own says little about the effective performance of CNN-based models, especially when real-time detection tasks are involved. To the best of our knowledge, there has not been sufficient evaluation of the available methods in terms of their speed/accuracy trade-off. This work performs a review and hands-on evaluation of the most fundamental object detection models on the Common Objects in Context (COCO) dataset with respect to this trade-off, their memory footprint, and computational and storage costs. In addition, we review available datasets for medical mask detection and train YOLOv5 on the Properly Wearing Masked Faces Dataset (PWMFD). Next, we test and evaluate a set of specific optimization techniques, transfer learning, data augmentations, and attention mechanisms, and we report on their effect for real-time mask detection. Based on our findings, we propose an optimized model based on YOLOv5s using transfer learning for the detection of correctly and incorrectly worn medical masks that surpassed more than two times in speed (69 frames per second) the state-of-the-art model SE-YOLOv3 on the PWMFD while maintaining the same level of mean Average Precision (67%).
‘Just Another Outing in a Boat’: Findings from the Evaluation of the Mixed Ability Sport Development Programme
Authors: Dyer Jen , Sandford Rachel
Published: July 2023

Article 30 (5a) of the UNCRPD states that participation in mainstream sport should be a right for all individuals. However, many disabled people still face barriers to participation, and provision remains segregated and/or determined, at least in part, by the nature and degree of impairment. This paper explores the Mixed Ability (MA) model as an innovative approach to facilitating disabled people’s participation in, and engagement with, mainstream sport. It outlines findings from an evaluation of the Sport England-funded Mixed Ability Sport Development Programme, which saw the MA model trialed in a variety of sports. A participatory research design was employed to generate data with key stakeholder groups involved in the design and delivery of programme activities, as well as with MA participants. Analysis of the data identified three core themes: (i) defining MA sport; (ii) the impacts of MA sport; and (iii) challenges and enablers of MA sport. In discussing these, it is argued that the MA model can be a powerful approach to inclusion and help to shape meaningful change. Indeed, the data suggest that the impacts of MA activities can extend beyond the individual level and influence shifts in both sports club culture and wider perceptions around disability. The paper closes by considering the implications of the research and outlines recommendations for future practice in this area.
Drone Optimization in Factory: Exploring the Minimal Level Vehicle Routing Problem for Efficient Material Distribution
Authors: Derpich Ivan , Rey Carlos
Published: July 2023

The efficient movement of raw materials within organizations is fundamental to maintaining the seamless progression of production processes. However, these logistical operations can inadvertently compromise overall company efficiency, primarily due to the substantial time invested in transporting materials. This paper introduces an innovative mathematical model specifically designed to optimize the transport of raw materials via drones across multiple workstations. This model employs a novel modification of the traditional multi-level Vehicle Routing Problem by incorporating an additional index and accounting for the drone’s energy consumption. We employ a widely-recognized solver for practical resolution and compare it with a heuristic algorithm. The resultant strategies offer promising prospects for the organization studied, introducing robust solutions for elevating the efficiency of raw material transportation.
An Augmented Sliding Mode Control for Fixed-Wing UAVs with External Disturbances and Model Uncertainties
Authors: Pan Yu , Li Ni , Zou Wanyong , Wang Ban , Wang Kaibo , Tang Xiaojun , Bu Shuhui , Qin Ling
Published: July 2023

Model uncertainties and external disturbances present significant challenges for controlling fixed-wing unmanned aerial vehicles (UAVs). An adaptive smooth second-order time-varying nonsingular fast terminal sliding mode control method is proposed in this paper for attitude and airspeed control of fixed-wing UAVs with model uncertainties and external disturbances. This control method does not require information about the bounds of disturbances and can avoid overestimation of the control gains. A radial basis function neural network observer is designed to mitigate the influence caused by sudden disturbances. The convergence of the attitude and airspeed controllers is proven by using the Lyapunov stability theory. Simulation results demonstrate the effectiveness of the proposed method for controlling a six-degrees-of-freedom fixed-wing UAV.
Decomposing and Tracing Mutual Information by Quantifying Reachable Decision Regions
Authors: Mages Tobias , Rohner Christian
Published: July 2023

The idea of a partial information decomposition (PID) gained significant attention for attributing the components of mutual information from multiple variables about a target to being unique, redundant/shared or synergetic. Since the original measure for this analysis was criticized, several alternatives have been proposed but have failed to satisfy the desired axioms, an inclusion–exclusion principle or have resulted in negative partial information components. For constructing a measure, we interpret the achievable type I/II error pairs for predicting each state of a target variable (reachable decision regions) as notions of pointwise uncertainty. For this representation of uncertainty, we construct a distributive lattice with mutual information as consistent valuation and obtain an algebra for the constructed measure. The resulting definition satisfies the original axioms, an inclusion–exclusion principle and provides a non-negative decomposition for an arbitrary number of variables. We demonstrate practical applications of this approach by tracing the flow of information through Markov chains. This can be used to model and analyze the flow of information in communication networks or data processing systems.
Spatio-Temporal Fractal Dimension Analysis from Resting State EEG Signals in Parkinson’s Disease
Authors: Ruiz de Miras Juan , Derchi Chiara-Camilla , Atzori Tiziana , Mazza Alice , Arcuri Pietro , Salvatore Anna , Navarro Jorge , Saibene Francesca Lea , Meloni Mario , Comanducci Angela
Published: July 2023

Complexity analysis of electroencephalogram (EEG) signals has emerged as a valuable tool for characterizing Parkinson’s disease (PD). Fractal dimension (FD) is a widely employed method for measuring the complexity of shapes with many applications in neurodegenerative disorders. Nevertheless, very little is known on the fractal characteristics of EEG in PD measured by FD. In this study we performed a spatio-temporal analysis of EEG in PD using FD in four dimensions (4DFD). We analyzed 42 resting-state EEG recordings comprising two groups: 27 PD patients without dementia and 15 healthy control subjects (HC). From the original resting-state EEG we derived the cortical activations defined by a source reconstruction at each time sample, generating point clouds in three dimensions. Then, a sliding window of one second (the fourth dimension) was used to compute the value of 4DFD by means of the box-counting algorithm. Our results showed a significantly higher value of 4DFD in the PD group (p < 0.001). Moreover, as a diagnostic classifier of PD, 4DFD obtained an area under curve value of 0.97 for a receiver operating characteristic curve analysis. These results suggest that 4DFD could be a promising method for characterizing the specific changes in the brain dynamics associated with PD.
Exploring the Affordances of Place-Based Education for Advancing Sustainability Education: The Role of Cognitive, Socio-Emotional and Behavioural Learning
Authors: Hernandez Gonzalez Felicity
Published: July 2023

The present paper explores the affordances of place-based education (PBE) to enhance the goals of sustainability education (SE). UNESCO, the leading international body responsible for advancing SE, assigns a central role to the three dimensions of cognitive, socio-emotional and behavioural learning as a means for advancing sustainability and the seventeen Sustainable Development Goals. Thus far, little research attention has been given to examining pedagogical approaches that may be effective in supporting these learning dimensions. PBE has risen over the past years as a holistic educational approach that may be well situated for supporting SE goals. To evaluate its affordances, the study put forward the objectives to (i) examine the application of cognitive, socio-emotional and behavioural learning dimensions in empirical studies employing PBE; and (ii) examine the overall contribution of PBE to developing students’ sustainability awareness, as reflected in the PBE case-study literature. Multiple case-study analysis was employed for examining secondary resources, comprised of four PBE case studies reported in the literature. It was found that the implementation of PBE in the context of SE produced holistic learning outcomes across the three dimensions, as early as in kindergarten students. Through direct content with nature and the local community, students’ agency, voice and action competence increased, having ripple effects across the community, connecting the local with the global. PBE advanced inter-cultural sensitivity and promoted the inclusion of Indigenous knowledge in SE.
An Adaptive Remote Sensing Image-Matching Network Based on Cross Attention and Deformable Convolution
Authors: Chen Peiyan , Fu Ying , Hu Jinrong , He Bing , Wu Xi , Zhou Jiliu
Published: July 2023

There are significant background changes and complex spatial correspondences between multi-modal remote sensing images, and it is difficult for existing methods to extract common features between images effectively, leading to poor matching results. In order to improve the matching effect, features with high robustness are extracted; this paper proposes a multi-temporal remote sensing matching algorithm CMRM (CNN multi-modal remote sensing matching) based on deformable convolution and cross-attention. First, based on the VGG16 backbone network, Deformable VGG16 (DeVgg) is constructed by introducing deformable convolutions to adapt to significant geometric distortions in remote sensing images of different shapes and scales; second, the features extracted from DeVgg are input to the cross-attention module to better capture the spatial correspondence of images with background changes; and finally, the key points and corresponding descriptors are extracted from the output feature map. In the feature matching stage, in order to solve the problem of poor matching quality of feature points, BFMatcher is used for rough registration, and then the RANSAC algorithm with adaptive threshold is used for constraint. The proposed algorithm in this paper performs well on the public dataset HPatches, with MMA values of 0.672, 0.710, and 0.785 when the threshold is selected as 3–5. The results show that compared to existing methods, our method improves the matching accuracy of multi-modal remote sensing images.
Sequenced Steering Vector Estimation for Eigen-Subspace Projection-Based Robust Adaptive Beamformer
Authors: Chen Xiangwei , Sheng Weixing
Published: July 2023

Robust adaptive beamforming (RAB) is essential in many applications to ensure signal-receiving quality when model errors exist. Eigen-subspace projection (ESP), one of the most popular RAB methods, can be used when there are arbitrary model errors. However, a major challenge of ESP is projection subspace selection. Traditional ESP (TESP) treats the signal subspace as the projection subspace; thus, source enumeration is required to obtain prior information. Another inherent defect is its poor performance at low signal-to-noise ratios (SNRs). To overcome these drawbacks, two improved ESP-based RAB methods are proposed in this study. Considering that a reliable signal-of-interest steering vector needs to be obtained via the subspace projection, the main idea underlying the proposed methods is to use sequenced steering vector estimation to invert the subspace dimension estimate for an arranged eigenvector matrix. As the proposed methods do not require source enumeration, they are simple to implement. Numerical examples demonstrate the effectiveness and robustness of the proposed methods in terms of output signal-to-interference-plus-noise ratio performance. Specifically, compared with TESP, the proposed methods present at least a 2.6 dB improvement at low SNRs regardless of the error models.
A Formal Approach to the Extraction of Permittivity and Permeability of Isotropic and Anisotropic Media Using the TM11 Mode in Rectangular Waveguides
Authors: Susek Waldemar , Dukata Andrzej , Pomarańska Patrycja
Published: July 2023

Based on our previous work on the propagation of electromagnetic waves in a layered medium placed in a rectangular waveguide, we present the theory of using the TE10 and TM11 modes to determine the complex parameters of isotropic and anisotropic media. The Nicolson–Ross–Weir method was used. The cases of isotropic, uniaxial, and biaxial materials were considered. It has been shown that the TM11 mode can be used to extract parameters of non-magnetic uniaxial anisotropy media by a single measurement, without changing the sample position. This is not possible with the previously used TE10 mode. It is also possible to use the TM11 mode to quickly determine whether a material is isotropic or not. Experimental results are presented for some isotropic materials.
A Survey on the Development of Network Protocol Fuzzing Techniques
Authors: Zhang Zhaowei , Zhang Hongzheng , Zhao Jinjing , Yin Yanfei
Published: July 2023

Network protocols, as the communication rules among computer network devices, are the foundation for the normal operation of networks. However, security issues arising from design flaws and implementation vulnerabilities in network protocols pose significant risks to network operations and security. Network protocol fuzzing is an effective technique for discovering and mitigating security flaws in network protocols. It offers unparalleled advantages compared to other security analysis techniques thanks to the minimal requirement for prior knowledge of the target and low deployment complexity. Nevertheless, the randomness in test case generation, uncontrollable test coverage, and unstable testing efficiency introduce challenges in ensuring the controllability of the testing process and results. In order to comprehensively survey the development of network protocol fuzzing techniques and analyze their advantages and existing issues, in this paper, we categorized and summarized the protocol fuzzing and its related techniques based on the generation methods of test cases and testing conditions. Specifically, we overviewed the development trajectory and patterns of these techniques over the past two decades according to chronological order. Based on this analysis, we further predict the future directions of fuzzing techniques.
A Physics-Informed Recurrent Neural Network for RRAM Modeling
Authors: Sha Yanliang , Lan Jun , Li Yida , Chen Quan
Published: July 2023

Extracting behavioral models of RRAM devices is challenging due to their unique “memory” behaviors and rapid developments, for which well-established modeling frameworks and systematic parameter extraction processes are not available. In this work, we propose a physics-informed recurrent neural network (PiRNN) methodology to generate behavioral models of RRAM devices from practical measurement/simulation data. The proposed framework can faithfully capture the evolution of internal state and its impacts on the output. A series of modifications informed by the RRAM device physics are proposed to enhance the modeling capabilities. The integration strategy of Verilog-A equivalent circuits, is also developed for compatibility with existing general-purpose circuit simulators. The Verilog-A model can be easily adopted into the SPICE-type simulator for the circuit design with a variable step that differs from the training process. Numerical experiments with real RRAM devices data demonstrate the feasibility and advantages of the proposed methodology.
Quality of Life Prediction on Walking Scenes Using Deep Neural Networks and Performance Improvement Using Knowledge Distillation
Authors: Rithanasophon Thanasit , Thitisiriwech Kitsaphon , Kantavat Pittipol , Kijsirikul Boonserm , Iwahori Yuji , Fukui Shinji , Nakamura Kazuki , Hayashi Yoshitsugu
Published: July 2023

The well-being of residents is a top priority for megacities, which is why urban design and sustainable development are crucial topics. Quality of Life (QoL) is used as an effective key performance index (KPI) to measure the efficiency of a city plan’s quantity and quality factors. For city dwellers, QoL for pedestrians is also significant. The walkability concept evaluates and analyzes the QoL in a walking scene. However, the traditional questionnaire survey approach is costly, time-consuming, and limited in its evaluation area. To overcome these limitations, the paper proposes using artificial intelligence (AI) technology to evaluate walkability data collected through a questionnaire survey using virtual reality (VR) tools. The proposed method involves knowledge extraction using deep convolutional neural networks (DCNNs) for information extraction and deep learning (DL) models to infer QoL scores. Knowledge distillation (KD) is also applied to reduce the model size and improve real-time performance. The experiment results demonstrate that the proposed approach is practical and can be considered an alternative method for acquiring QoL.
Intelligent Embedded Systems Platform for Vehicular Cyber-Physical Systems
Authors: Conrad Christopher , Al-Rubaye Saba , Tsourdos Antonios
Published: July 2023

Intelligent vehicular cyber-physical systems (ICPSs) increase the reliability, efficiency and adaptability of urban mobility systems. Notably, ICPSs enable autonomous transportation in smart cities, exemplified by the emerging fields of self-driving cars and advanced air mobility. Nonetheless, the deployment of ICPSs raises legitimate concerns surrounding safety assurance, cybersecurity threats, communication reliability, and data management. Addressing these issues often necessitates specialised platforms to cater to the heterogeneity and complexity of ICPSs. To address this challenge, this paper presents a comprehensive CPS to explore, develop and test ICPSs and intelligent vehicular algorithms. A customisable embedded system is realised using a field programmable gate array, which is connected to a supervisory computer to enable networked operations and support advanced multi-agent algorithms. The platform remains compatible with multiple vehicular sensors, communication protocols and human–machine interfaces, essential for a vehicle to perceive its surroundings, communicate with collaborative systems, and interact with its occupants. The proposed CPS thereby offers a practical resource to advance ICPS development, comprehension, and experimentation in both educational and research settings. By bridging the gap between theory and practice, this tool empowers users to overcome the complexities of ICPSs and contribute to the emerging fields of autonomous transportation and intelligent vehicular systems.
Domain Adaptive Few-Shot Learning for ISAR Aircraft Recognition with Transferred Attention and Weighting Importance
Authors: Li Binquan , Yao Yuan , Wang Qiao
Published: July 2023

With the enhancement of air-based and space-based perception capabilities, space-aeronautics incorporation and integration is growing in importance. Full domain awareness is crucial for integrated perception systems, in which domain adaptation is one of the key problems in improving the performance of cross-domain perception. Deep learning is currently an advanced technique for complex inverse synthetic aperture radar (ISAR) object recognition. However, the training procedure needs many annotated samples, which is insufficient for certain targets, such as aircraft. Few-shot learning provides a new approach to solving the above problem by transferring useful knowledge from other domains, such as optical images from satellites. Nevertheless, it fails to fully consider the domain shift between the source and target domains, generally neglecting the transferability of training samples in the learning process. Consequently, it produces suboptimal recognition accuracy. To address the composite problems mentioned above, we propose a domain adaptive few-shot learning method from satellites to an ISAR called S2I-DAFSL for aircraft recognition tasks. Furthermore, unlike conventional domain adaptation methods that directly align the distributions, the attention transferred importance-weighting network (ATIN) is proposed to improve the transferability in the domain adaptation procedure. Compared with state-of-the-art methods, it shows that the proposed method achieves better performance, increasing the accuracy and effectiveness of classification, which is more suitable for cross-domain few-shot ISAR aircraft recognition tasks.