bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of the Most Suitable Mobile Apps to Support Dietary Approaches to Stop Hypertension (DASH) Diet Self-Management: Systematic Search of App Stores and Content Analysis
Authors: Alnooh Ghadah , Alessa Tourkiah , Noorwali Essra , Albar Salwa , Williams Elizabeth , de Witte Luc P. , Hawley Mark S.
Published: August 2023

Smartphone apps might provide an opportunity to support the Dietary Approaches to Stop Hypertension (DASH) diet, a healthy diet designed to help lower blood pressure. This study evaluated DASH diet self-management apps based on their quality, likely effectiveness, and data privacy/security to identify the most suitable app(s). A systematic search and content analysis were conducted of all DASH diet apps available in Google Play and the Apple App Store in the UK in November 2022. Apps were included if they provided DASH diet tracking. A previous systematic literature review found some commercial apps not found in the app store search, and these were also included in this review. Three reviewers used the App Quality Evaluation Tool (AQEL) to assess each app’s quality across seven domains: knowledge acquisition, skill development, behaviour change, purpose, functionality, and appropriateness for adults with hypertension. Domains with a score of 8 or higher were considered high-quality. Two reviewers assessed the apps’ data privacy and security and then coded Behaviour change techniques (BCTs) linked to the Theoretical Domain Framework (TDF) underpinning the likely effectiveness of the apps. Seven DASH diet apps were assessed, showing the limited availability of apps supporting DASH diet self-management. The AQEL assessment showed that three apps scored higher than eight in most of the AQEL domains. Nineteen BCTs were used across the apps, linked to nine TDF action mechanisms that may support DASH diet self-management behaviours. Four apps met standards for privacy and security. All seven apps with self-monitoring functionality had sufficient theoretical basis to demonstrate likely effectiveness. However, most had significant quality and data security shortcomings. Only two apps, NOOM and DASH To TEN, were found to have both adequate quality and security and were thus deemed suitable to support DASH diet self-management.
25(OH)D Concentration in Neonates, Infants, Toddlers, Older Children and Teenagers from Poland—Evaluation of Trends during Years 2014–2019
Authors: Wójcik Marek , Jaworski Maciej , Płudowski Paweł
Published: August 2023

Introduction: Local and international guidelines have provided schedules for the vitamin D supplementation of general populations of different ages, including children. Our study aimed to assess 25(OH)D concentration and its potential change during a growth and maturation period, adding parameters that reflect the risk of hypercalcemia. Materials and methods: The available 25(OH)D concentration values (n = 17,636; 7.8 ± 6.0 years), calcium (n = 2673; 16.3 ± 6.1 years) and phosphate (n = 2830; 3.8 ± 5.2 years) metabolism markers were analyzed in a studied group of patients (0–18 years). Results: In the studied group the mean 25(OH)D concentration was 29.4 ± 11.7 ng/mL. Concentrations of 25(OH)D < 10 ng/mL were observed in 1.7% of patients (n = 292), 10–20 ng/mL in 17.2% (n = 3039), 20–30 ng/mL in 39.5% (n = 6960) and 30–50 ng/mL in 37.2% (n = 6567). In patients with a 25(OH)D concentration <10 ng/mL, normal calcemia (2.25–2.65 mmol/L) was observed in 29.5% of cases (n = 86). Three patients had 25(OH)D concentrations above 100 ng/mL with co-existing hypercalcemia; the mean was Ca = 3.40 mmol/L. Hypocalcemia (Ca < 2.25 mmol/L) was observed in 10,4% of patients (n = 2797). Furthermore, 5.0% of patients showed an increased calcium concentration >2.65 mmol/L (n = 1327). The highest mean 25(OH)D concentration of 32.1 ng/mL ± 12.9 was noted in the years 2018–2019 (n = 3931) and the lowest in the year 2015 (27.2 ng/mL ± 11.0; n = 2822). Conclusions: Vitamin D deficiency (<20 ng/mL) was noted in 18,9% of subjects in the years 2014–2019. An effective prevention of vitamin D deficiency was observed in children aged 3 years and younger. A relationship between the concentrations of calcium and 25(OH)D was not observed.
Cultural and Contextual Drivers of Triple Burden of Malnutrition among Children in India
Authors: Singh Shri Kant , Chauhan Alka , Sharma Santosh Kumar , Puri Parul , Pedgaonkar Sarang , Dwivedi Laxmi Kant , Taillie Lindsey Smith
Published: August 2023

This study examines malnutrition’s triple burden, including anaemia, overweight, and stunting, among children aged 6–59 months. Using data from the National Family Health Survey-5 (2019–2021), the study identifies risk factors and assesses their contribution at different levels to existing malnutrition burden. A random intercept multilevel logistic regression model and spatial analysis are employed to identify child, maternal, and household level risk factors for stunting, overweight, and anaemia. The study finds that 34% of children were stunted, 4% were overweight, and 66% were anaemic. Stunting and anaemia prevalence were higher in central and eastern regions, while overweight was more prevalent in the north-eastern and northern regions. At the macro-level, the coexistence of stunting, overweight, and anaemia circumstantiates the triple burden of childhood malnutrition with substantial spatial variation (Moran’s I: stunting-0.53, overweight-0.41, and anaemia-0.53). Multilevel analysis reveals that child, maternal, and household variables play a substantial role in determining malnutrition burden in India. The nutritional health is significantly influenced by a wide range of determinants, necessitating multilevel treatments targeting households to address this diverse group of coexisting factors. Given the intra-country spatial heterogeneity, the treatment also needs to be tailor-made for various disaggregated levels.
Kiluluma ceratotherii (Nematoda: Strongylida) in a White Rhinoceros (Ceratotherium simum) from the United States: Case Report
Authors: Quintana Theresa A. , Miller Kamilyah R. , Hill-Thimmesch Kristen J. , Schieferecke Grace , Johnson William L. , Herrin Brian H. , Jesudoss Chelladurai Jeba R. J.
Published: August 2023

Nematodes of the genus Kiluluma (Strongylidae, Cyathostominae) parasitize African rhinoceros. We describe the case of a one-year-old male white rhinoceros calf that presented with colonic inflammation and hemorrhage at necropsy. The animal had died following a neurological episode. We recovered and identified adult nematodes from the colon using morphology and ITS2 gene sequences as Kiluluma ceratotherii. We also generated nuclear ITS1, 5.8S, ITS2, and mitochondrial cox1 sequences for future studies and deposited them in GenBank (OR142644–OR142653). Since the animal was born in the same zoo and never transported, infection likely originated within the herd. This is the first report of this nematode from a white rhinoceros in the United States.
An ARMS-Multiplex PCR Targeting SARS-CoV-2 Omicron Sub-Variants
Authors: Bozidis Petros , Petridi Eleni , Gartzonika Konstantina
Published: August 2023

As of November 2021, the SARS-CoV-2 Omicron variant had made its appearance, gradually replacing the predominant Delta variant. Since its emergence, the Omicron variant has been continuously evolving through more than 500 strains, most of which belong to five sub-variants known as BA.1, BA.2, BA.3, BA.4, and BA.5. The aim of this study was to develop a multiplex polymerase chain reaction (PCR) that will be able to distinguish the basic sub-variants of Omicron in a rapid and specific way. Full genome sequences of Omicron strains with high frequency and wide geographical distribution were retrieved by the NCBI Virus and ENA databases. These sequences were compared to each other in order to locate single nucleotide polymorphisms common to all strains of the same sub-variant. These polymorphisms should also be capable of distinguishing Omicron sub-variants not only from each other but from previously circulating variants of SARS-CoV-2 as well. Thus, specific primers targeting characteristic polymorphisms of the four Omicron main branches BA.1, BA.2, BA.4, and BA.5 were designed according to the principles of the amplification refractory mutation system (ARMS) and with the ability to react under multiplex PCR conditions. According to our results, the ARMS-multiplex PCR could successfully distinguish all Omicron sub-variants that carry the corresponding mutations.
Semperivium Ruthenicum Koch Extract-Loaded Bio-Adhesive Formulation: A Novel Oral Antioxidant Delivery System for Oxidative Stress Reduction
Authors: Mihai Sebastian , Dumitrescu Denisa Elena , Popescu Antoanela , Stoicescu Iuliana , Matroud Nadia , Răducanu Ana-Mădălina , Mititelu Magdalena
Published: August 2023

Periodontitis is a chronic inflammatory disease that affects the oral cavity and can ultimately lead to tooth loss. Oxidative stress has been identified as a key factor in the development of periodontitis. In recent years, natural polyphenols have gained attention for their anti-inflammatory and antioxidant effects. This study aims to evaluate the potential of a bio-adhesive patch loaded with Semperivium ruthenicum Koch extract, rich in polyphenols, as a novel oral antioxidant delivery system for reducing oxidative stress in periodontitis. The plant extracts were prepared by maceration and were subjected to HPLC analysis for the identification and quantification of polyphenols. The bio-adhesive patches were prepared using a solvent-casting technique and characterized for their technical characteristics and release kinetics. The patches demonstrated satisfactory technical characteristics and followed Korsmeyer–Peppas release kinetics, with the active ingredients diffusing non-Fickian from the polymer matrix as it eroded over time. The bio-adhesive strength of the patches was comparable to other similar formulations, suggesting that the obtained patches can be tested in vivo conditions. The results suggest that treating oral periodontitis with natural polyphenols may effectively scavenge free radicals and regulate cytokine activity, leading to a reduction in oxidative stress. The non-smoking group had a mean saliva antioxidant activity of 7.86 ± 0.66% while the smoking group had a mean value of 4.53 ± 0.15%. Furthermore, treating oral oxidative stress may also contribute to overall gut health, as studies have shown a correlation between oral and gut microbiomes. Therefore, the use of bio-adhesive patches containing polyphenols may provide a promising approach for the treatment of periodontitis and its associated complications.
Membrane-Active Peptides and Their Potential Biomedical Application
Authors: Gostaviceanu Andreea , Gavrilaş Simona , Copolovici Lucian , Copolovici Dana Maria
Published: August 2023

Membrane-active peptides (MAPs) possess unique properties that make them valuable tools for studying membrane structure and function and promising candidates for therapeutic applications. This review paper provides an overview of the fundamental aspects of MAPs, focusing on their membrane interaction mechanisms and potential applications. MAPs exhibit various structural features, including amphipathic structures and specific amino acid residues, enabling selective interaction with multiple membranes. Their mechanisms of action involve disrupting lipid bilayers through different pathways, depending on peptide properties and membrane composition. The therapeutic potential of MAPs is significant. They have demonstrated antimicrobial activity against bacteria and fungi, making them promising alternatives to conventional antibiotics. MAPs can selectively target cancer cells and induce apoptosis, opening new avenues in cancer therapeutics. Additionally, MAPs serve as drug delivery vectors, facilitating the transport of therapeutic cargoes across cell membranes. They represent a fascinating class of biomolecules with significant potential in basic research and clinical applications. Understanding their mechanisms of action and designing peptides with enhanced selectivity and efficacy will further expand their utility in diverse fields. Exploring MAPs holds promise for developing novel therapeutic strategies against infections, cancer, and drug delivery challenges.
PlantMetSuite: A User-Friendly Web-Based Tool for Metabolomics Analysis and Visualisation
Authors: Liu Yu , Liu Hao-Zhuo , Chen Ding-Kang , Zeng Hong-Yun , Chen Yi-Li , Yao Nan
Published: August 2023

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored to plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user’s browser without the need for installation or programming skills. The tool is freely available and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool’s significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.
Saline–Alkaline Stress Resistance of Cabernet Sauvignon Grapes Grafted on Different Rootstocks and Rootstock Combinations
Authors: Zhao Baolong , Liu Zhiyu , Zhu Chunmei , Zhang Zhijun , Shi Wenchao , Lu Qianjun , Sun Junli
Published: August 2023

Grafting the wine grape variety Cabernet Sauvignon onto salinity-tolerant rootstocks can improve salinity tolerance and grape yields in regions with high salinity soils. In this experiment, the effects of different rootstocks and rootstock combinations on the saline–alkaline stress (modified Hoagland nutrient solution + 50 mmol L−1 (NaCl + NaHCO3)) of Cabernet Sauvignon were studied. Correlation and principal component analyses were conducted on several physiological indicators of saline–alkaline stress. Salinity limited biomass accumulation, induced damage to the plant membrane, reduced the chlorophyll content and photosynthetic capacity of plants, and increased the content of malondialdehyde, sodium (Na+)/potassium (K+) ratio, and antioxidant enzyme activities (superoxide dismutase, peroxidase, and catalase). Significant differences in several indicators were observed among the experimental groups. The results indicate that the saline–alkaline tolerance of Cabernet Sauvignon after grafting was the same as that of the rootstock, indicating that the increased resistance of Cabernet Sauvignon grapes to saline–alkaline stress stems from the transferability of the saline–alkaline stress resistance of the rootstock to the scion.
Effect of Preheating Whey Protein Concentrate on the Stability of Purple Sweet Potato Anthocyanins
Authors: Zhang Shuo , Deng Guowei , Wang Fang , Xu Haiyan , Li Jiagen , Liu Jialei , Wu Dengfeng , Lan Shitao
Published: August 2023

Anthocyanins (ANs) have strong antioxidant activities and can inhibit chronic diseases, but the instability of ANs limits their applications. The conservation of preheating whey protein concentrate (WPC) on the stability of purple sweet potato ANs was investigated. The retention of ANs in WPC-ANs was 85.88% after storage at 25 °C for 5 h. WPC-ANs had higher retention of ANs in heating treatment. The retention rates of ANs in WPC-ANs exposed to light and UV lamps for 6 h were 78.72% and 85.76%, respectively. When the concentration of H2O2 was 0.50%, the retention rate of ANs in the complexes was 62.04%. WPC-ANs’ stability and antioxidant activity were improved in simulated digestive juice. The WPC-ANs connection was static quenching, and the binding force between them was a hydrophobic interaction at one binding site, according to the fluorescence quenching spectroscopy. UV-visible absorption spectroscopy and Fourier transform infrared spectroscopy (FTIR) analysis further indicated that the secondary structure and microenvironment of amino acid residues in WPC can be impacted by the preheating temperature and preheating times of WPC. In conclusion, preheating WPC can successfully preserve the stability of purple sweet potato ANs by binding to them through a non-covalent interaction.
Effect of Sterilization on the Dimensional and Mechanical Behavior of Polylactic Acid Pieces Produced by Fused Deposition Modeling
Authors: Garnica-Bohórquez Israel , Güiza-Argüello Viviana R. , López-Gualdrón Clara I.
Published: August 2023

To successfully implement additive manufacturing (AM) techniques for custom medical device (MD) production with low-cost resources, it is imperative to understand the effect of common and affordable sterilization processes, such as formaldehyde or steam sterilization, on pieces manufactured by AM. In this way, the performance of low-risk MDs, such as biomodels and surgical guides, could be assessed for complying with safety, precision, and MD delivery requirements. In this context, the aim of the present work was to evaluate the effect of formaldehyde and steam sterilization on the dimensional and mechanical stability of standard polylactic acid (PLA) test pieces produced by fused deposition modeling (FDM). To achieve this, PLA samples were sterilized according to the sterilization protocol of a public hospital in the city of Bucaramanga, Colombia. Significant changes regarding mechanical and dimensional properties were found as a function of manufacturing parameters. This research attempts to contribute to the development of affordable approaches for the fabrication of functional and customized medical devices through AM technologies, an issue of particular interest for low- and middle-income countries.
Joint Durability of Steam-Treated Beech Wood
Authors: Mihulja Goran , Poljak Dominik , Sedlar Tomislav
Published: August 2023

Steaming beech wood is one of the most commonly used eco-based processes for wood color equilibration. In addition to color equalization, steaming has also been noticed to stabilize the final product (solid wood panels). The beech wood samples used in this study were steamed for two different periods. PVAc and polyurethane (PU) adhesives were used to analyze bonding strength and durability. The bonding strength was measured according to the EN 13354 standard. The samples were treated before testing according to the first part of the standard, i.e., immersion in water. The durability of the bonded joint was tested according to the ISO 9142 standard. The samples were treated before testing with two methods. The results of the bonding strength show the influence of the steaming process on the bonded joint. Short exposure to steam decreased bonding strength, and prolonged exposure increased bonding strength. From the results given and the statistical analysis, it can be concluded that a prolonged steaming period increases the stability of the beech wood and thus the durability of the bonded joints.
Numerical Simulation of Flashing Flows in a Converging–Diverging Nozzle with Interfacial Area Transport Equation
Authors: Li Jiadong , Liao Yixiang , Zhou Ping , Lucas Dirk , Gong Liang
Published: August 2023

Flashing flows of initially sub-cooled water in a converging–diverging nozzle is investigated numerically in the framework of the two-fluid model (TFM). The thermal non-equilibrium effect of phase change is considered by an interfacial heat transfer model, while the pressure jump across the interface is ignored. The bubble size distribution induced by nucleation, bubble growth/shrinkage, coalescence, and breakup is described based on the interfacial area transport equation (IATE) and constant bubble number density model (CBND), respectively. The results are compared with the experimental data. Satisfactory prediction of the axial pressure distribution along the nozzle as well as the flashing inception, is achieved by the TFM-IATE coupling method. It was also found that the vapor production in the diverging section was overpredicted, and the radial gas volume fraction distribution deviated from the experiment. The radial diameter profiles exhibit opposite patterns at the nozzle throat and near the outlet, and similar trends can be observed for the superheated degree. A poly-disperse method is suggested to be introduced to describe the evolution of interfacial area concentration.
Modified Model and Simulation Verification of Rock-Fatigue Damage Considering Repeated Discharge Impact
Authors: Guo Jianchun , Li Xinyang , Lu Cong , Zhu Xinlei , Huang Kun , Xu Shiqian
Published: August 2023

The existing rock-fatigue-damage constitutive model fails to consider the influence of discharge energy and discharge times on the effect of rock damage under discharge impact. In this regard, the impact load test of sandstone was carried out. Based on the test results, the quantitative characterization formula of different discharge parameters on the weakening degree of rock compressive strength was established. Based on the TCK (Taylor–Chen–Kuszmaul) model, a constitutive model considering the mechanical properties of rock and the dynamic hange of micro-crack geometric size is established, and the cohesive model is proposed to calculate the crack size. The constitutive model includes the relationship between crack width, crack number, and rock compressive strength, and the change of damage factor D is used to consider the fatigue-damage effect of discharge shock on the rock. The results show that the modified model can quantitatively and accurately reflect the dynamic damage and failure process of rock and that the weakening of rock mechanical properties and the development of micro-cracks can be controlled by designing different discharge parameters.
Mixing Characteristics and Parameter Effects on the Mixing Efficiency of High-Viscosity Solid–Liquid Mixtures under High-Intensity Acoustic Vibration
Authors: Zhan Xiaobin , Yu Lei , Jiang Yalong , Jiang Qiankun , Shi Tielin
Published: August 2023

High-intensity acoustic vibration is a new technology for solving the problem of uniform dispersion of highly viscous materials. In this study, we investigate the mixing characteristics of high-viscosity solid–liquid phases under high-intensity acoustic vibration and explore the effect of vibration parameters on the mixing efficiency. A numerical simulation model of solid–liquid–gas multiphase flow, employing the volume of fluid (VOF) and discrete phase model (DPM), was developed and subsequently validated through experimental verification. The results show that the movement and deformation of the gas–liquid surface over the entire field are critical for achieving rapid and uniform mixing of the solid–liquid phases under acoustic vibration. Increasing the amplitude or frequency of vibration can intensify the movement and deformation of the free surface of gas and liquid, improve the mixing efficiency, and shorten the mixing time. Under the condition of constant acceleration, the mixing efficiency of materials is higher at low frequency and high amplitude. Further, we define a relationship that predicts desirable mixing conditions as a function of amplitude and frequency. This serves as a valuable reference guide for evaluating the minimum requirements when selecting operating parameters.
Vegetation Dynamics and Its Response to Extreme Climate on the Inner Mongolian Plateau during 1982–2020
Authors: Su Rihan , Guo Enliang , Wang Yongfang , Yin Shan , Bao Yulong , Sun Zhongyi , Mandula Naren , Bao Yuhai
Published: August 2023

The impact of extreme climate change on terrestrial ecosystems continues to intensify. This study was conducted to understand extreme climate–vegetation interactions under exacerbated frequency, severity, and duration of extreme climatic events. The Inner Mongolian Plateau (IMP) was selected due to its sensitive natural location, which is particularly vulnerable to climate change. Based on the Normalized Difference Vegetation Index (NDVI) and daily meteorological station data from 1982 to 2020, changes in the patterns of vegetation and extreme climate in the three ecological zones (forest, steppe, and desert steppe) of the IMP were identified. Furthermore, the effects of extreme climate on vegetation were quantified using correlation analysis and a geographical detector. The results showed that the annual NDVI of 95.1%, 50.6%, and 19.5% of the area increased significantly in the forest, steppe, and desert steppe, respectively. The Tx90p (warm days) and Tn90p (warm nights) increased significantly at the rate of 0.21 and 0.235 day·yr−1, respectively, while the Tx10p (cold days) and Tn10p (cold nights) showed a significantly decreasing trend at the rate of −0.105 and −0.117 day·yr−1. An extreme warming phenomenon was observed in all extreme temperature indices on the IMP. The results of both the correlation analysis and factor detector indicated that extreme temperature intensity and frequency greatly affected forest vegetation. In contrast, extreme precipitation intensity and frequency were relatively more important to the vegetation of the desert steppe. The lag in NDVI response to extreme temperature intensity was not less than three months in the IMP; however, extreme precipitation intensity exhibited a two-month time lag in the NDVI. This study can improve our understanding of extreme climate–vegetation interactions, provide theoretical support for disaster mitigation, and aid in understanding the ecological environment of the IMP.
I–D Threshold Analysis of Rainfall-Triggered Landslides Based on TRMM Precipitation Data in Wudu, China
Authors: Ning Shan , Ge Yonggang , Bai Shibiao , Ma Chicheng , Sun Yiran
Published: August 2023

This study explored the applicability of TRMM, TRMM nonlinear downscaling, and ANUSPLIN (ANU) interpolation of three different types of precipitation data to define regional-scale rainfall-triggered landslide thresholds. The spatial resolution of TRMM precipitation data was downscaled from 0.25° to 500 m by the downscaling model considering the relationship between humidity, NDVI, and numerous topographic factors and precipitation. The rainfall threshold was calculated using the rainfall intensity–duration threshold model. The calculation showed that TRMM downscaled precipitation data have better detection capability for extreme precipitation events than the other two, the TRMM downscaling threshold was better than the ANU interpolation, and the cumulative effective rainfall of TRMM downscaling was preferred as the macroscopic critical rainfall-triggered landslide threshold for the early warning of the Wudu. The predictive performance of the rainfall threshold of 50% was better than the other two (10% and 90%). When the probability of landslide occurrence was 50%, the TRMM downscaled threshold curve was given by I50=21.03×D−1.004. The authors also analyzed the influence of factors such as topography landform and soil type on the rainfall threshold of landslides in the study area. The rainfall intensity of small undulating mountains was higher than that of medium and large undulating mountains, and the rainfall intensity of landslides peaks at high altitude mountains of 3500–5000 m.
Validation of MODIS Temperature and Emissivity Products Based on Ground-Based Mid-Wave Hyperspectral Imaging Measurement in the Northwestern Plateau Region of Qinghai, China
Authors: Jiang Yuepeng , Cao Yunhua , Wu Zhensen , Cao Yisen
Published: August 2023

The climatic fluctuations in northern China exhibit remarkable variability, making it imperative to harness the power of MODIS data for conducting comprehensive investigations into the influences of desertification, desert expansion, and snow and ice melting phenomena. Consequently, the rigorous evaluation of MODIS land surface temperature (LST) and land surface emissivity (LSE) products takes on a momentous role, as this provides an essential means to ensure data accuracy, thereby instilling confidence in the robustness of scientific analyses. In this study, a high-resolution hyperspectral imaging instrument was utilized to measure mid-wave hyperspectral images of grasslands and deserts in the northwest plateau region of Qinghai, China. The measured data were processed in order to remove the effects of sensor noise, atmospheric radiation, transmission attenuation, and scattering caused by sunlight and atmospheric radiation. Inversion of the temperature field and spectral emissivity was performed on the measured data. The inverted data were compared and validated against MODIS land surface temperature and emissivity products. The validation results showed that the absolute errors of emissivity of grassland backgrounds provided by MCD11C1 in the three mid-wave infrared bands (3.66–3.840 μm, 3.929–3.989 μm, and 4.010–4.080 μm) were 0.0376, 0.0191, and 0.0429, with relative errors of 3.9%, 2.1%, and 4.8%, respectively. For desert backgrounds, the absolute errors of emissivity were 0.0057, 0.0458, and 0.0412, with relative errors of 0.4%, 4.9%, and 3.9%, respectively. The relative errors for each channel were all within 5%. Regarding the temperature data products, compared to the inverted temperatures of the deserts and grasslands, the remote sensing temperatures provided by MOD11L2 had absolute errors of ±2.3 K and ±4.1 K, with relative errors of 1.4% and 0.7%, respectively. The relative errors for the temperature products were all within 2%.
Using Local Knowledge and Remote Sensing in the Identification of Informal Settlements in Riyadh City, Saudi Arabia
Authors: Alrasheedi Khlood Ghalib , Dewan Ashraf , El-Mowafy Ahmed
Published: August 2023

Urban planning within Riyadh, the capital of Saudi Arabia, has been impacted by the presence of informal settlements. An understanding of the spatial distribution of these settlements is essential in developing urban policies. This study used remotely sensed imagery to evaluate and characterize informal settlements within the city, both with and without expert knowledge of the study area (defined as expert knowledge, EK). An informal settlement ontology for four study sites within Riyadh City was developed using an analytical hierarchy process (AHP). Local knowledge was translated into a ruleset to identify and map settlement areas using spatial, spectral, textural, and geometric techniques. These were combined with an object-based image analysis (OBIA) approach. The study demonstrated that combining expert knowledge and remotely sensed data can efficiently and accurately identify informal settlements. Two classified images were produced, one with EK, and one without EK, to investigate how a detailed understanding of local conditions could affect the final image classification. Overall accuracy when using EK was 94%, with a kappa coefficient of 89%, while without EK accuracy was 68% (kappa coefficient of 61%). The final OBIA classes included formal and informal settlements, road networks, vacant blocks, shaded areas, and vegetation. This study demonstrated that local expert knowledge and OBIA helpful in urban mapping. It also indicated the value of integrating a local ontological process during digital image classification. This work provided improved techniques for mapping informal settlements in Middle Eastern cities.
DAFNet: A Novel Change-Detection Model for High-Resolution Remote-Sensing Imagery Based on Feature Difference and Attention Mechanism
Authors: Ma Chong , Yin Hongyang , Weng Liguo , Xia Min , Lin Haifeng
Published: August 2023

Change detection is an important component in the field of remote sensing. At present, deep-learning-based change-detection methods have acquired many breakthrough results. However, current algorithms still present issues such as target misdetection, false alarms, and blurry edges. To alleviate these problems, this work proposes a network based on feature differences and attention mechanisms. This network includes a Siamese architecture-encoding network that encodes images at different times, a Difference Feature-Extraction Module (DFEM) for extracting difference features from bitemporal images, an Attention-Regulation Module (ARM) for optimizing the extracted difference features through attention, and a Cross-Scale Feature-Fusion Module (CSFM) for merging features from different encoding stages. Experimental results demonstrate that this method effectively alleviates issues of target misdetection, false alarms, and blurry edges.
Ecological Fall Prediction Sensitivity, Specificity, and Accuracy in Patients with Mild Cognitive Impairment at a High Risk of Falls
Authors: Kim Chaesu , Park Haeun , You Joshua (Sung)
Published: August 2023

While falls among patients with mild cognitive impairment (MCI) have been closely associated with an increased postural sway during ecological activities of daily living, there is a dearth of postural sway detection (PSD) research in ecological environments. The present study aimed to investigate the fall sensitivity, specificity, and accuracy of our PSD system. Forty healthy young and older adults with MCI at a high risk of falls underwent the sensitivity, specificity, and accuracy tests for PSD by simultaneously recording the Berg Balance Scale and Timed Up and Go in ecological environments, and the data were analyzed using the receiver operating characteristic curve and area under the curve. The fall prediction sensitivity ranged from 0.82 to 0.99, specificity ranged from 0.69 to 0.90, and accuracy ranged from 0.53 to 0.81. The PSD system’s fall prediction sensitivity, specificity, and accuracy data suggest a reasonable discriminative capacity for distinguishing between fallers and non-fallers as well as predicting falls in older adults with MCI in ecological testing environments.
Strategies for Bacterial Eradication from Human and Animal Semen Samples: Current Options and Future Alternatives
Authors: Ďuračka Michal , Benko Filip , Chňapek Milan , Tvrdá Eva
Published: August 2023

The primary role of semen processing and preservation is to maintain a high proportion of structurally and functionally competent and mature spermatozoa, that may be used for the purposes of artificial reproduction when needed, whilst minimizing any potential causes of sperm deterioration during ex vivo semen handling. Out of a multitude of variables determining the success of sperm preservation, bacterial contamination has been acknowledged with an increased interest because of its often unpredictable and complex effects on semen quality. Whilst antibiotics are usually the most straight-forward option to prevent the bacterial contamination of semen, antimicrobial resistance has become a serious threat requiring widespread attention. As such, besides discussing the consequences of bacteriospermia on the sperm vitality and the risks of antibiotic overuse in andrology, this paper summarizes the currently available evidence on alternative strategies to prevent bacterial contamination of semen prior to, during, and following sperm processing, selection, and preservation. Alternative antibacterial supplements are reviewed, and emphasis is given to modern methods of sperm selection that may be combined by the physical removal of bacteria prior to sperm preservation or by use in assisted reproductive technologies.
Enhancing Smart Home Security: Anomaly Detection and Face Recognition in Smart Home IoT Devices Using Logit-Boosted CNN Models
Authors: Rahim Asif , Zhong Yanru , Ahmad Tariq , Ahmad Sadique , Pławiak Paweł , Hammad Mohamed
Published: August 2023

Internet of Things (IoT) devices for the home have made a lot of people’s lives better, but their popularity has also raised privacy and safety concerns. This study explores the application of deep learning models for anomaly detection and face recognition in IoT devices within the context of smart homes. Six models, namely, LR-XGB-CNN, LR-GBC-CNN, LR-CBC-CNN, LR-HGBC-CNN, LR-ABC-CNN, and LR-LGBM-CNN, were proposed and evaluated for their performance. The models were trained and tested on labeled datasets of sensor readings and face images, using a range of performance metrics to assess their effectiveness. Performance evaluations were conducted for each of the proposed models, revealing their strengths and areas for improvement. Comparative analysis of the models showed that the LR-HGBC-CNN model consistently outperformed the others in both anomaly detection and face recognition tasks, achieving high accuracy, precision, recall, F1 score, and AUC-ROC values. For anomaly detection, the LR-HGBC-CNN model achieved an accuracy of 94%, a precision of 91%, a recall of 96%, an F1 score of 93%, and an AUC-ROC of 0.96. In face recognition, the LR-HGBC-CNN model demonstrated an accuracy of 88%, precision of 86%, recall of 90%, F1 score of 88%, and an AUC-ROC of 0.92. The models exhibited promising capabilities in detecting anomalies, recognizing faces, and integrating these functionalities within smart home IoT devices. The study’s findings underscore the potential of deep learning approaches for enhancing security and privacy in smart homes. However, further research is warranted to evaluate the models’ generalizability, explore advanced techniques such as transfer learning and hybrid methods, investigate privacy-preserving mechanisms, and address deployment challenges.
Boosting Semantic Segmentation by Conditioning the Backbone with Semantic Boundaries
Authors: Ishikawa Haruya , Aoki Yoshimitsu
Published: August 2023

In this paper, we propose the Semantic-Boundary-Conditioned Backbone (SBCB) framework, an effective approach to enhancing semantic segmentation performance, particularly around mask boundaries, while maintaining compatibility with various segmentation architectures. Our objective is to improve existing models by leveraging semantic boundary information as an auxiliary task. The SBCB framework incorporates a complementary semantic boundary detection (SBD) task with a multi-task learning approach. It enhances the segmentation backbone without introducing additional parameters during inference or relying on independent post-processing modules. The SBD head utilizes multi-scale features from the backbone, learning low-level features in early stages and understanding high-level semantics in later stages. This complements common semantic segmentation architectures, where features from later stages are used for classification. Extensive evaluations using popular segmentation heads and backbones demonstrate the effectiveness of the SBCB. It leads to an average improvement of 1.2% in IoU and a 2.6% gain in the boundary F-score on the Cityscapes dataset. The SBCB framework also improves over- and under-segmentation characteristics. Furthermore, the SBCB adapts well to customized backbones and emerging vision transformer models, consistently achieving superior performance. In summary, the SBCB framework significantly boosts segmentation performance, especially around boundaries, without introducing complexity to the models. Leveraging the SBD task as an auxiliary objective, our approach demonstrates consistent improvements on various benchmarks, confirming its potential for advancing the field of semantic segmentation.
A Multi-Channel Borehole Strain Measurement and Acquisition System Based on FPGA
Authors: Xu Xin , Chen Zheng , Li Hong , Zhan Weiwei , Wang Wenbo , Dong Yunkai , Wu Liheng , Li Xiang
Published: August 2023

In this study, an FPGA(Field Programmable Gate Array)-based borehole strain measurement system was designed that makes extensive use of digital signal processing operations to replace analog circuits. Through the formidable operational capability of FPGA, the sampled data were filtered and denoised to improve the signal-to-noise ratios. Then, with the goal of not reducing observational accuracy, the signal amplification circuit was removed, the excitation voltage was reduced, and the dynamic range of the primary adjustments was expanded to 130 dB. The system’s online compilation function made it more flexible to changes in measurement parameters, allowing it to adapt to various needs. In addition, the efficiency of the equipment use was enhanced. The actual observational results showed that this study’s FPGA-based borehole strain measurement system had a voltage resolution higher than 1 μV. Clear solid tides were successfully recorded in low-frequency bands, and seismic wave strain was accurately recorded in high-frequency bands. The arrival times and seismic phases of the seismic waves S and P were clearly recorded, which met the requirements for geophysical field deformation observations. Therefore, the system proposed in this study is of major significance for future analyses of geophysical and crust deformation observations.
Defect Detection in Steel Using a Hybrid Attention Network
Authors: Zhou Mudan , Lu Wentao , Xia Jingbo , Wang Yuhao
Published: August 2023

Defect detection in steel surface focuses on accurately identifying and precisely locating defects on the surface of steel materials. Methods of defect detection with deep learning have gained significant attention in research. Existing algorithms can achieve satisfactory results, but the accuracy of defect detection still needs to be improved. Aiming at this issue, a hybrid attention network is proposed in this paper. Firstly, a CBAM attention module is used to enhance the model’s ability to learn effective features. Secondly, an adaptively spatial feature fusion (ASFF) module is used to improve the accuracy by extracting multi-scale information of defects. Finally, the CIOU algorithm is introduced to optimize the training loss of the baseline model. The experimental results show that the performance of our method in this work is superior on the NEU-DET dataset, with an 8.34% improvement in mAP. Compared with major algorithms of object detection such as SSD, EfficientNet, YOLOV3, and YOLOV5, the mAP was improved by 16.36%, 41.68%, 20.79%, and 13.96%, respectively. This demonstrates that the mAP of our proposed method is higher than other major algorithms.
Exploring Biomarkers of Mental Flexibility in Healthy Aging: A Computational Psychometric Study
Authors: Borghesi Francesca , Chirico Alice , Pedroli Elisa , Cipriani Giuseppina Elena , Canessa Nicola , Amanzio Martina , Cipresso Pietro
Published: August 2023

Mental flexibility (MF) has long been defined as cognitive flexibility. Specifically, it has been mainly studied within the executive functions domain. However, there has recently been increased attention towards its affective and physiological aspects. As a result, MF has been described as an ecological and cross-subject skill consisting of responding variably and flexibly to environmental cognitive-affective demands. Cross-sectional studies have mainly focused on samples composed of healthy individual and of patients with chronic conditions such as Mild Cognitive Impairment and Parkinson’s, emphasizing their behavioral rigidity. Our study is the first to consider a sample of healthy older subjects and to outline physiological and psychological markers typical of mental flexibility, to identify functional biomarkers associated with successful aging. Our results reveal that biomarkers (respiratory and heart rate variability assessments) distinguished between individuals high vs. low in mental flexibility more reliably than traditional neuropsychological tests. This unveiled the multifaceted nature of mental flexibility composed of both cognitive and affective aspects, which emerged only if non-linear multi-variate analytic approaches, such as Supervised Machine Learning, were used.
Direction of Arrival Estimation of Coherent Wideband Sources Using Nested Array
Authors: Tang Yawei , Deng Weiming , Li Jianfeng , Zhang Xiaofei
Published: August 2023

Due to their ability to achieve higher DOA estimation accuracy and larger degrees of freedom (DOF) using a fixed number of antennas, sparse arrays, etc., nested and coprime arrays have attracted a lot of attention in relation to research into direction of arrival (DOA) estimation. However, the usage of the sparse array is based on the assumption that the signals are independent of each other, which is hard to guarantee in practice due to the complex propagation environment. To address the challenge of sparse arrays struggling to handle coherent wideband signals, we propose the following method. Firstly, we exploit the coherent signal subspace method (CSSM) to focus the wideband signals on the reference frequency and assist in the decorrelation process, which can be implemented without any pre-estimations. Then, we virtualize the covariance matrix of sparse array due to the decorrelation operation. Next, an enhanced spatial smoothing algorithm is applied to make full use of the information available in the data covariance matrix, as well as to improve the decorrelation effect, after which stage the multiple signal classification (MUSIC) algorithm is used to obtain DOA estimations. In the simulation, with reference to the root mean square error (RMSE) that varies in tandem with the signal-to-noise ratio (SNR), the algorithm achieves satisfactory results compared to other state-of-the-art algorithms, including sparse arrays using the traditional incoherent signal subspace method (ISSM), the coherent signal subspace method (CSSM), spatial smoothing algorithms, etc. Furthermore, the proposed method is also validated via real data tests, and the error value is only 0.2 degrees in real data tests, which is lower than those of the other methods in real data tests.
A Novel Monopole Ultra-Wide-Band Multiple-Input Multiple-Output Antenna with Triple-Notched Characteristics for Enhanced Wireless Communication and Portable Systems
Authors: Basir Shahid , Qureshi Ubaid Ur Rahman , Subhan Fazal , Khan Muhammad Asghar , Mohsan Syed Agha Hassnain , Ghadi Yazeed Yasin , Ouahada Khmaies , Hamam Habib , Noor Fazal
Published: August 2023

This study introduces a monopole 4 × 4 Ultra-Wide-Band (UWB) Multiple-Input Multiple-Output (MIMO) antenna system with a novel structure and outstanding performance. The proposed design has triple-notched characteristics due to CSRR etching and a C-shaped curve. The notching occurs in 4.5 GHz, 5.5 GHz, and 8.8 GHz frequencies in the C-band, WLAN band, and satellite network, respectively. Complementary Split-Ring Resonators (CSRR) are etched at the feed line and ground plane, and a C-shaped curve is used to reduce interference between the ultra-wide band and narrowband. The mutual coupling of CSRR enables the MIMO architecture to achieve high isolation and polarisation diversity. With prototype dimensions of (60.4 × 60.4) mm2, the proposed antenna design is small. The simulated and measured results show good agreement, indicating the effectiveness of the UWB-MIMO antenna for wireless communication and portable systems.
Multimodal Federated Learning: A Survey
Authors: Che Liwei , Wang Jiaqi , Zhou Yao , Ma Fenglong
Published: August 2023

Federated learning (FL), which provides a collaborative training scheme for distributed data sources with privacy concerns, has become a burgeoning and attractive research area. Most existing FL studies focus on taking unimodal data, such as image and text, as the model input and resolving the heterogeneity challenge, i.e., the challenge of non-identical distribution (non-IID) caused by a data distribution imbalance related to data labels and data amount. In real-world applications, data are usually described by multiple modalities. However, to the best of our knowledge, only a handful of studies have been conducted to improve system performance utilizing multimodal data. In this survey paper, we identify the significance of this emerging research topic of multimodal federated learning (MFL) and present a literature review on the state-of-art MFL methods. Furthermore, we categorize multimodal federated learning into congruent and incongruent multimodal federated learning based on whether all clients possess the same modal combinations. We investigate the feasible application tasks and related benchmarks for MFL. Lastly, we summarize the promising directions and fundamental challenges in this field for future research.