bluuebunny/crossref_metadata_2025 huggingface dataset:
Functionalization of Fluorine on the Surface of SnO2–Mg Nanocomposite as an Efficient Photocatalyst for Toxic Dye Degradation
Authors: Velmurugan G. , Ganapathi Raman R. , Sivaprakash P. , Viji A. , Cho Shin Hum , Kim Ikhyun
Published: September 2023

This work reports on the photocatalytic activity of tin oxide (SnO2)-doped magnesium (Mg) and fluorine (F) nanoparticles for methyl orange and safranin dye degradation under sunlight irradiation. Nanocatalysis-induced dye degradation was examined using UV–visible spectroscopy and a pseudo-first-order kinetics model. The results indicate that the prepared nanoparticles exhibit superior photocatalytic activity, and the degradation of methyl orange (MO) dye is approximately 82%. In contrast, the degradation of safranin dye is 96% in the same time interval of 105 min. The calculated crystallite size of the SnO2–Mg–F nanocomposite is 29.5 nm, which respects the particle size found in the DLS analysis with a tetragonal structure and spherical morphology affirmed. The optical characteristics were assessed, and their respective bandgap energies were determined to be 3.6 eV. The influence of F in Mg and SnO2 is recognized with the XRD and FT-IR spectra of the prepared particles.
Suspended-Load Backpacks to Reduce the Cost of Carrying Loads with Energy Scavenging Potential—Part 2: Bio-Inspired Pre-Rotation Design
Authors: Zhang Maoyi , Guo Liang , Hu Jihai , Wang Xingquan , Yang Ya , Su Yewang
Published: September 2023

Backpack transportation is everywhere in daily life. Suspended-load backpacks (SUSBs) based on forced vibration have attracted lots of attention because of their ability to effectively reduce the cost on the body during motion. The smaller the natural frequency of SUSBs, the better the cost reduction. The natural frequency is determined by the elastic components of SUSBs. It is currently common to use rubber ropes and pulleys as elastic components. In the first part of this paper, we propose a pre-compression design for SUSBs, which has a simple structure and breaks through the limitation of rubber material. To make the natural frequency small enough, rubber ropes and compression springs require sufficient space. This leads to the current SUSBs being large and, therefore, not suitable for children to carry. Inspired by biology, here we propose a new design strategy of pre-rotation with pre-rotation spiral springs as elastic components. The pre-rotation design not only has the advantages of avoiding the inconvenience of material aging and the ability to adjust the downward sliding distance of the backpack but also greatly saves the space occupied by the elastic components, which can be adopted by small SUSBs. We have developed a theoretical model of the pre-rotation SUSBs and experimentally confirmed the performance of the pre-rotation SUSBs. This work provides a unique design approach for small SUSBs and small suspended-load devices. And the relative motion between the components inside the SUSB has a huge potential to be used by triboelectric nanogenerators for energy scavenging.
The Geriatric Nutritional Risk Index Is an Optimal Evaluation Parameter for Predicting Mortality in Adult All Ages Hemodialysis Patients: A Korean Population-Based Study
Authors: Kim Do Hyoung , Lee Young-Ki , Park Hayne Cho , Kim Bo Yeon , Lee Miri , Kim Gui Ok , Kim Jinseog , Cho Ajin
Published: September 2023

The Geriatric Nutritional Risk Index (GNRI) is a nutritional screening tool used for predicting mortality in patients undergoing hemodialysis (HD). This study investigated the cutoff values for the GNRI for predicting mortality in HD patients using Korean HD quality assessment data from 2015. To identify the optimal GNRI cutoff value, we used Harrell’s C-index with multivariate Cox regression models. The highest value of C-index was identified as the cutoff value of GNRI for all-cause mortality in this population. In total, 34,933 patients were included; 90.8 of GNRI was the highest value of C-index, and it was used as a cutoff value to predict mortality; 3311 patients (9.5%) had GNRI values < 90.8, and there were 12,499 deaths during the study period. The mean follow-up period was 53.7 months. The crude mortality rates in patients with GNRI values < 90.8 and ≥ 90.8 were 160.4/1000 and 73.2/1000 person-years respectively. In the fully adjusted Cox model, patients with a GNRI < 90.8 had a 1.78 times higher risk of mortality than those with a GNRI ≥ 90.8. These findings suggest that the optimal GNRI cutoff value is 90.8 for predicting mortality in maintenance HD patients.
Magnetic Resonance Imaging Can Be Used to Assess Sarcopenia in Children with Newly Diagnosed Crohn’s Disease
Authors: Blagec Paola , Sara Sila , Tripalo Batoš Ana , Trivić Mažuranić Ivana , Močić Pavić Ana , Mišak Zrinjka , Hojsak Iva
Published: September 2023

Background: This study aimed to determine the proportion of patients with sarcopenia diagnosed by MRI and compare these results to bioelectrical impedance analysis (BIA). Methods: Children with newly diagnosed Crohn’s disease (CD) who had MRI enterography (MRE) and BIA and had at least 12 months of follow-up were included. Total psoas muscle area (TPMA) and total paravertebral muscle (TPVM) were measured and compared to subjects’ lean mass and the lean mass body index (LMBI) was assessed by BIA. Results: 30 newly diagnosed children with CD were included (mean age 14.2 years, 53% male). Sarcopenia was found in 13 (43%) children; mean TPMA was 15.2 (1.1 SD) cm2 and TPVM 30.95 (1.7 SD) cm2. A highly positive correlation was shown for lean mass assessed by BIA and TPMA (0.706, p < 0.001) and TPVM (0.75, p < 0.001). Sarcopenia was more prevalent in boys (77% vs. 24%, p = 0.004), patients with the perianal disease (69% vs. 29%, p = 0.03), and children with sarcopenia were likely to receive anti-TNF (77% vs. 41%, p = 0.05). During the follow-up period, 16 (53%) children experienced a relapse. TPMA (HR 0.99, p = 0.018) and TPVM (HR 0.99, p = 0.031) values were statistically significant risk factors for relapse. Conclusion: A high proportion of patients with CD have sarcopenia at the time of the diagnosis. There is a good correlation between muscle mass assessed by MRI and BIA. Because MRI is performed in a great proportion of newly diagnosed CD patients it can also be used to assess the presence of sarcopenia.
Evaluation of Non-Alcoholic Beverages and the Risk Related to Consumer Health among the Romanian Population
Authors: Mititelu Magdalena , Oancea Carmen-Nicoleta , Neacșu Sorinel Marius , Olteanu Gabriel , Cîrțu Alexandru-Tiberiu , Hîncu Lucian , Gheonea Theodora Claudia , Stanciu Tiberius Iustinian , Rogoveanu Ion , Hashemi Fallah , Stanciu Gabriela , Ioniță-Mîndrican Corina-Bianca , Angelica Caunii , Măru Nicoleta , Lupu Sergiu , Lupu Carmen Elena
Published: September 2023

The range of non-alcoholic drinks is very varied both from a compositional point of view and from a caloric and nutritional point of view. The excessive consumption of sweetened non-alcoholic beverages represents an important risk factor for health, especially when it is accompanied by an unbalanced diet and a disordered lifestyle. In order to evaluate the consumption of non-alcoholic beverages correlated with the evaluation of the main lifestyle factors that can affect the state of health among Romanians, a cross-sectional observational study was carried out based on a questionnaire. The results of the study indicate that among the most consumed non-alcoholic drinks are coffee and sweetened carbonated and non-carbonated drinks, which are indicated as being responsible for the development of consumption addictions: 44% for coffee, 16.5% for sweetened or tonic carbonated drinks and 12% for sweetened non-carbonated drinks. Considering that the consumption of coffee is usually associated with sweeteners, there is a risk of excessive caffeine and caloric intake in a context where a lack of exercise predominates (59.98%) among respondents declaring that they do sports rarely or not at all, which can lead, in the long term, to the appearance of imbalances either of a psycho-emotional nature or of a metabolic nature. A significant link was found between sports activity and the environment in which they work (χ2 = 51.33, p = 0.05). Respondents with a daily activity that involves movement (working outdoors, working on a construction site) are also those who usually do sports, while 60.67% of the respondents who work a lot in front of the computer declared that they do sports very rarely or not at all. Reducing the excessive consumption of sweetened drinks can be achieved through an appropriate consumption of water and fruits and by intensifying physical activity as a way of counterbalancing the excess caloric intake.
Exploring Taiwanese Consumer Dietary Preferences for Various Vinegar Condiments: Novel Dietary Patterns across Diverse Cultural Contexts
Authors: Ker Jung-Kuei , Lee Ching-Sung , Chen Yen-Cheng , Chiang Ming-Chen
Published: September 2023

The use of vinegar as a culinary seasoning in various global cuisines to enhance the taste characteristics and profiles of foods has been extensively documented in the culinary literature. Particularly notable is traditional Taiwanese-style thick soup, where the incorporation of vinegar plays a fundamental role in imparting distinct flavors. In the context of this experimental investigation, the foundational base of Taiwanese-style thick soup serves as the platform for a meticulously planned sensory and dietary behavior evaluation. Our research methodology combines the use of survey questionnaires and experimental techniques, employing purposive sampling and snowball sampling methods to recruit participants. The central focus of this study is to understand consumers’ culinary preferences when presented with a choice between two contrasting types of vinegar—specifically, black vinegar and balsamic vinegar—as alternative gastronomic enhancements. This precise orchestration of data collection and systematic evaluation provides a perceptive window into participants’ culinary inclinations and food choices, resulting in a detailed and profound understanding of their taste preferences. The empirical findings stemming from this experimentation reveal notably significant differences in the sensory assessments among participants engaging in diverse culinary experiences. Notably, distinct variations are observed in terms of visual perceptions, olfactory distinctions, and overall sensory satisfaction. This study occupies a crucial position within existing research paradigms by strategically expanding the scope of sensory investigations within the realm of Taiwanese-style thick soup. This introduces an innovative aspect represented by the introduction of balsamic vinegar as a compelling alternative to the customary black vinegar. As a result, the emerging findings not only offer compelling insights into the nuanced food choice and taste preferences of consumers, but also open up new and innovative directions within the complex tapestry of Chinese gastronomy.
Efficacy of Boswellia serrata Extract and/or an Omega-3-Based Product for Improving Pain and Function in People Older Than 40 Years with Persistent Knee Pain: A Randomized Double-Blind Controlled Clinical Trial
Authors: Pérez-Piñero Silvia , Muñoz-Carrillo Juan Carlos , Victoria-Montesinos Desirée , García-Muñoz Ana María , Andreu-Caravaca Luis , Gómez Mario , Schölzel Melanie , García-Guillén Ana I. , López-Román Francisco Javier
Published: September 2023

A single-center, randomized, double-blind, controlled clinical trial with four arms was conducted in healthy subjects with persistent knee discomfort (pain intensity on 1–10 cm visual analog scale (VAS) > 3) aged 40 years and older treated with a dietary supplement for 8 weeks. The study groups were Boswellia serrata extract (n = 29), an omega-3-based product (AvailOm® 50 High EPA) (n = 31), Boswellia + AvailOm® (n = 30), and placebo (n = 30). The intake of Boswellia + AvailOm® improved the quality of life (QoL) (WOMAC index) and some variables of muscle strength. Statistically significant differences between the AvailOm® and the placebo groups in the decrease of pain intensity were found. Weekly VAS scores showed a significant decrease in pain perception when comparing the AvailOm® product to the placebo, with the lowest VAS scores at week 8. Consumption of Boswellia improved sleep latency. The time to perform the Up and Go test decreased after the intake of AvailOm®. There was an increase in the omega-3 fatty acids, with the greatest increase in the Boswellia + AvailOm® group. AvailOm® was safe and effective in reducing pain and improving the QoL and functionality of subjects over 40 years with persistent knee pain.
Antihypertensive and Vasorelaxant Effects of Citric Acid and Lemon Juice in Spontaneously Hypertensive Rats: In Vivo and Ex Vivo Studies
Authors: Nakamura Kozo , Suzuki Yumiko , Goto Kazuma , Yamaguchi Shohei , Hiramitsu Masanori
Published: September 2023

Hypertension is a key risk factor for heart, brain, and kidney disease development. Fruit consumption has been associated with a decrease in blood pressure. Lemon juice, which contains antihypertensive compounds, may exert antihypertensive effects. However, no research has verified the antihypertensive effects of citric acid, the most abundant ingredient in lemon juice. In the present study, we demonstrated the antihypertensive effects of citric acid and lemon juice by performing single oral administration tests and the aortic ring assay using spontaneously hypertensive rats (SHRs). Single oral doses of both agents markedly reduced the systolic and diastolic blood pressures in the SHRs. In addition, both these agents relaxed the thoracic aorta from the SHRs; however, these effects were notably attenuated by the removal of the aortic endothelium. Orally administered citric acid was rapidly absorbed and metabolized in vivo. Among the functional compounds in lemon juice, citric acid was identified as the primary antihypertensive component. Although more detailed studies are required to validate our findings, the novel functional attributes of citric acid can achieve the normalization of blood pressure when it is consumed via diet.
Fatty Acids Profile and the Relevance of Membranes as the Target of Nutrition-Based Strategies in Atopic Dermatitis: A Narrative Review
Authors: Olejnik Anna , Gornowicz-Porowska Justyna , Jenerowicz Dorota , Polańska Adriana , Dobrzyńska Małgorzata , Przysławski Juliusz , Sansone Anna , Ferreri Carla
Published: September 2023

Recently, the prevalence of atopic dermatitis has increased drastically, especially in urban populations. This multifactorial skin disease is caused by complex interactions between various factors including genetics, environment, lifestyle, and diet. In eczema, apart from using an elimination diet, the adequate content of fatty acids from foods (saturated, monounsaturated, and polyunsaturated fatty acids) plays an important role as an immunomodulatory agent. Different aspects regarding atopic dermatitis include connections between lipid metabolism in atopic dermatitis, with the importance of the MUFA levels, as well as of the omega-6/omega-3 balance that affects the formation of long-chain (C20 eicosanoic and C22 docosaenoic) fatty acids and bioactive lipids from them (such as prostaglandins). Impair/repair of the functioning of epidermal barrier is influenced by these fatty acid levels. The purpose of this review is to drive attention to membrane fatty acid composition and its involvement as the target of fatty acid supplementation. The membrane-targeted strategy indicates the future direction for dermatological research regarding the use of nutritional synergies, in particular using red blood cell fatty acid profiles as a tool for checking the effects of supplementations to reach the target and influence the inflammatory/anti-inflammatory balance of lipid mediators. This knowledge gives the opportunity to develop personalized strategies to create a healthy balance by nutrition with an anti-inflammatory outcome in skin disorders.
Modern Approaches in Wounds Management
Authors: Tatarusanu Simona-Maria , Lupascu Florentina-Geanina , Profire Bianca-Stefania , Szilagyi Andrei , Gardikiotis Ioannis , Iacob Andreea-Teodora , Caluian Iulian , Herciu Lorena , Giscă Tudor-Catalin , Baican Mihaela-Cristina , Crivoi Florina , Profire Lenuta
Published: September 2023

Wound management represents a well-known continuous challenge and concern of the global healthcare systems worldwide. The challenge is on the one hand related to the accurate diagnosis, and on the other hand to establishing an effective treatment plan and choosing appropriate wound care products in order to maximize the healing outcome and minimize the financial cost. The market of wound dressings is a dynamic field which grows and evolves continuously as a result of extensive research on developing versatile formulations with innovative properties. Hydrogels are one of the most attractive wound care products which, in many aspects, are considered ideal for wound treatment and are widely exploited for extension of their advantages in healing process. Smart hydrogels (SHs) offer the opportunities of the modulation physico-chemical properties of hydrogels in response to external stimuli (light, pressure, pH variations, magnetic/electric field, etc.) in order to achieve innovative behavior of their three-dimensional matrix (gel–sol transitions, self-healing and self-adapting abilities, controlled release of drugs). The SHs response to different triggers depends on their composition, cross-linking method, and manufacturing process approach. Both native or functionalized natural and synthetic polymers may be used to develop stimuli-responsive matrices, while the mandatory characteristics of hydrogels (biocompatibility, water permeability, bioadhesion) are preserved. In this review, we briefly present the physiopathology and healing mechanisms of chronic wounds, as well as current therapeutic approaches. The rational of using traditional hydrogels and SHs in wound healing, as well as the current research directions for developing SHs with innovative features, are addressed and discussed along with their limitations and perspectives in industrial-scale manufacturing.
Internet Addiction and Depression among Syrian College Students: A Cross-Sectional Study
Authors: Swed Sarya , Bohsas Haidara , Alibrahim Hidar , Rais Mohammed Amir , Elsayed Mohamed , Nashwan Abdulqadir J. , Hasan Mohammad Mehedi , Nour Nasif Mohamad , Sawaf Bisher , Albuni Mhd Kutaiba , Battikh Elias , Abo Kash Rawan , Shoib Sheikh
Published: September 2023

Background: Problematic internet use (PIU) or internet addiction has become increasingly prevalent, and concerns about its impact on mental health and social functioning have grown. This study aimed to investigate the prevalence of PIU among Syrian university students and its relationship with their demographics, internet user behavior, and mental health. Methods: A cross-sectional study was conducted among undergraduate medical students in Syrian government universities between 12 April and 29 May 2022. The survey included the Beck Depression Inventory and the Internet Addiction Scale. Results: Out of 2891 participants, 75.2% were female, with an average age of 21.87. The average Internet Addiction Test (IAT) score was 49.4, and the overall prevalence of PIU was 89%. Furthermore, 93.0% of participants displayed possible signs and symptoms of depression. PIU was significantly linked with physical abuse (p = 0.001) and mental stress (p = 0.0001). Internet addiction is (AOR:1.723, COR:2.289) fold more likely to occur in those with more than 8 h of sleep per night than in those who sleep for less than 6 h (p-value < 0.05). Unadjusted regression analysis showed that 13 predictors of the independent variables were statistically significant in predicting the presence of internet addiction, such as participants who suffered from a breakup (COR:2.039), domestic violence (COR:2.136), physical abuse (COR:2.190), or mental stress (COR:2.621) were more likely to be affected by internet addiction than those who did not (p-value < 0.05). Conclusions: The study found a high rate of internet addiction among Syrian medical students, with those experiencing mental health problems and depression symptoms more likely to be internet addicts. To prevent PIU, students should be encouraged to participate in extracurricular activities, such as sports, and awareness programs should be enhanced to highlight the negative effects of internet addiction.
A Novel Approach to Predicting Urban Expansion by the Urban Scaling Law at a Single-City Scale
Authors: Ye Haipeng , Zheng Zhuofan , Liu Xintong , Wang Shu , Zhao Hongrui
Published: September 2023

Rapid urban expansion caused by vigorous urban population growth brought up various socioeconomic and eco-environmental problems, which have important ramifications for sustainable development across the world. Along with the accelerated urbanization process, accurate and realistic prediction of urban expansion is of great importance to optimize urban planning and urban development. This study proposed a new hybrid model, which combined the urban scaling law (USL) with the ANN-CA model to predict urban expansion. To employ urban scaling law in the model, we innovatively calculated the law exponent at a single-city scale. Based on USL, we estimated urban land demand in the future by panel data regression. Finally, we added the area constraint and ecological constraint into the ANN-CA model to simulate urban expansion spatially. This frame of urban expansion has been successfully applied in Shenzhen, of which the urban land area would increase from 816.45 km2 in 2020 to 842.48 km2 in 2025. By comparing this model with the traditional prediction method, we proved its effectiveness and accuracy. Besides, we found that the scaling exponent can reflect urbanization level and distinguish overconstructed cities.
Spatiotemporal Variation in Driving Factors of Vegetation Dynamics in the Yellow River Delta Estuarine Wetlands from 2000 to 2020
Authors: Niu Zhongen , Si Bingcheng , Li Dong , Zhao Ying , Hou Xiyong , Li Linlin , Wang Bin , Song Bing , Zhang Mengyu , Li Xiyu , Zeng Na , Zhu Xiaobo , Lv Yan , Mai Ziqi
Published: September 2023

Previous studies of vegetation dynamics in the Yellow River Delta (YRD) predominantly relied on sparse time series or coarse-resolution images, which not only overlooked the rapid and spatially heterogeneous changes, but also limited our understanding of driving mechanisms. Here, employing spatiotemporal data fusion methods, we constructed a novel fused enhanced vegetation index (EVI) dataset with a high spatiotemporal resolution (30-meter and 8-day resolution) for the YRD from 2000 to 2020, and we analyzed the vegetation variations and their driving factors within and outside the YRD Nation Natural Reserve (YRDNRR). The fused EVI effectively captured spatiotemporal vegetation dynamics. Notably, within the YRDNRR core area, the fused EVI showed no significant trend before 2010, while a significant increase emerged post-2010, with an annual growth of 7%, the invasion of Spartina alterniflora explained 78% of this EVI increment. In the YRDNRR experimental area, the fused EVI exhibited a distinct interannual trend, which was characterized by an initial increase (2000–2006, p < 0.01), followed by a subsequent decrease (2006–2011, p < 0.01) and, ultimately, a renewed increase (2011–2020, p > 0.05); the dynamics of the fused EVI were mainly affected by the spring runoff (R2 = 0.71), while in years with lower runoff, it was also affected by the spring precipitation (R2 = 0.70). Outside of the protected area, the fused EVI demonstrated a substantial increase from 2000 to 2010 due to agricultural land expansion and human management practices, followed by stabilization post-2010. These findings enhance our comprehension of intricate vegetation dynamics in the YRD, holding significant relevance in terms of wetland preservation and management.
Ship Detection via Multi-Scale Deformation Modeling and Fine Region Highlight-Based Loss Function
Authors: Li Chao , Hu Jianming , Wang Dawei , Li Hanfu , Wang Zhile
Published: September 2023

Ship detection in optical remote sensing images plays a vital role in numerous civil and military applications, encompassing maritime rescue, port management and sea area surveillance. However, the multi-scale and deformation characteristics of ships in remote sensing images, as well as complex scene interferences such as varying degrees of clouds, obvious shadows, and complex port facilities, pose challenges for ship detection performance. To address these problems, we propose a novel ship detection method by combining multi-scale deformation modeling and fine region highlight-based loss function. First, a visual saliency extraction network based on multiple receptive field and deformable convolution is proposed, which employs multiple receptive fields to mine the difference between the target and the background, and accurately extracts the complete features of the target through deformable convolution, thus improving the ability to distinguish the target from the complex background. Then, a customized loss function for the fine target region highlight is employed, which comprehensively considers the brightness, contrast and structural characteristics of ship targets, thus improving the classification performance in complex scenes with interferences. The experimental results on a high-quality ship dataset indicate that our method realizes state-of-the-art performance compared to eleven considered detection models.
Research on Soil Moisture Inversion Method for Canal Slope of the Middle Route Project of the South to North Water Transfer Based on GNSS-R and Deep Learning
Authors: Hu Qingfeng , Li Yifan , Liu Wenkai , Lu Weiqiang , Hai Hongxin , He Peipei , Liu Xianlin , Ma Kaifeng , Zhu Dantong , Wang Peng , Kou Yingchao
Published: September 2023

The soil moisture from the South-to-North Water Diversion Middle Route Project is assessed in this study. Complex and variable geological conditions complicate the prediction of soil moisture in the study area. To achieve this aim, we carried out research on soil moisture inversion methods for channel slopes in the study area using massive monitoring data from multiple GNSS observatories on channel slopes, incorporating GNSS-R techniques and deep learning algorithms. To address the issue of low accuracy in linear inversion when using a single satellite, this study proposes a multi-satellite and multi-frequency data fusion technique. Furthermore, three soil moisture inversion models, namely, the linear model, BP neural network model, and GA-BP neural network model, are established by incorporating deep learning techniques. In comparison with single-satellite data inversion, with the data fusion technique proposed in this study, the correlation is improved by 12.7%, the root mean square error is reduced by 0.217, the mean square error is decreased by 0.884, and the mean absolute error is decreased by 0.243 with the linear model. With the BP neural network model, the correlation is increased by 15.4%, the root mean square error is decreased by 0.395, the mean square error is decreased by 0.465, and the mean absolute error is reduced by 0.353. Moreover, with the GA-BP neural network model, the correlation is improved by 6.3%, the root mean square error is decreased by 1.207, the mean square error is decreased by 0.196, and the mean absolute error is reduced by 0.155. The results indicate that performing data fusion by using multiple satellites and multi-frequency bands is a feasible approach for improving the accuracy of soil moisture inversion. These research findings provide new technical means for the risk analysis of deformation disasters in the expansive soil channel slopes of the South-to-North Water Diversion Middle Route Project.
Insight into the 1 December 2016 Mw 6.2 Juliaca Earthquake, Southern Peru, by InSAR Observations and Field Investigation
Authors: Hu Qingfeng , Jia Weiwei , Yang Jiuyuan , Zhao Yanling
Published: September 2023

On 1 December 2016, an Mw 6.2 earthquake characterized by normal faulting occurred in the highlands of the central Andes in southern Peru, marking the region’s largest shallow event. The occurrence of the earthquake provides a significant chance to gain insight into the regional tectonic deformation and the seismogenic mechanism of the shallow normal-faulting earthquake, as well as the regional potential seismic risk. Here, we first utilize Sentinel-1A interferometric synthetic aperture radar (InSAR) data to extract the coseismic and postseismic deformation associated with this earthquake and then determine the detailed coseismic slip and postseismic afterslip distribution of this event. Coseismic modeling results indicate that the coseismic rupture is mainly characterized by normal faulting with some dextral strike-slip components. Most coseismic slip is confined to a depth range of 2–12 km, indicating an obvious slip deficit area in the shallow fault part. Further postseismic modeling reveals that the majority of afterslip is concentrated at depths of 0 to 5.4 km. The relatively shallow postseismic afterslip makes up for the coseismic slip deficit area to some extent. Through a joint analysis of the inversions, seismic data, and regional geology and geomorphology, we infer that the occurrence of this 2016 normal-faulting event is a result of regional gravitational collapse. In addition, we investigate the relationship between the 2016 earthquake and great historical earthquakes near the subduction zone of the central Andes and find that the 2016 event is likely promoted in advance by these events through our calculations of the coseismic and postseismic Coulomb stress changes. Finally, we should pay more attention to the nearby Falla Huaytacucho-Condoroma fault and the western segment of the Vilcanota Fault because of their relatively high stress loading.
Single Object Tracking in Satellite Videos Based on Feature Enhancement and Multi-Level Matching Strategy
Authors: Yang Jianwei , Pan Zongxu , Liu Yuhan , Niu Ben , Lei Bin
Published: September 2023

Despite significant advancements in remote sensing object tracking (RSOT) in recent years, achieving accurate and continuous tracking of tiny-sized targets remains a challenging task due to similar object interference and other related issues. In this paper, from the perspective of feature enhancement and a better feature matching strategy, we present a tracker SiamTM specifically designed for RSOT, which is mainly based on a new target information enhancement (TIE) module and a multi-level matching strategy. First, we propose a TIE module to address the challenge of tiny object sizes in satellite videos. The proposed TIE module goes along two spatial directions to capture orientation and position-aware information, respectively, while capturing inter-channel information at the global 2D image level. The TIE module enables the network to extract discriminative features of the targets more effectively from satellite images. Furthermore, we introduce a multi-level matching (MM) module that is better suited for satellite video targets. The MM module firstly embeds the target feature map after ROI Align into each position of the search region feature map to obtain a preliminary response map. Subsequently, the preliminary response map and the template region feature map are subjected to the Depth-wise Cross Correlation operation to get a more refined response map. Through this coarse-to-fine approach, the tracker obtains a response map with a more accurate position, which lays a good foundation for the prediction operation of the subsequent sub-networks. We conducted extensive experiments on two large satellite video single-object tracking datasets: SatSOT and SV248S. Without bells and whistles, the proposed tracker SiamTM achieved competitive results on both datasets while running at real-time speed.
Qualitative Classification of Proximal Femoral Bone Using Geometric Features and Texture Analysis in Collected MRI Images for Bone Density Evaluation
Authors: Najafi Mojtaba , Yousefi Rezaii Tohid , Danishvar Sebelan , Razavi Seyed Naser
Published: September 2023

The aim of this study was to use geometric features and texture analysis to discriminate between healthy and unhealthy femurs and to identify the most influential features. We scanned proximal femoral bone (PFB) of 284 Iranian cases (21 to 83 years old) using different dual-energy X-ray absorptiometry (DEXA) scanners and magnetic resonance imaging (MRI) machines. Subjects were labeled as “healthy” (T-score > −0.9) and “unhealthy” based on the results of DEXA scans. Based on the geometry and texture of the PFB in MRI, 204 features were retrieved. We used support vector machine (SVM) with different kernels, decision tree, and logistic regression algorithms as classifiers and the Genetic algorithm (GA) to select the best set of features and to maximize accuracy. There were 185 participants classified as healthy and 99 as unhealthy. The SVM with radial basis function kernels had the best performance (89.08%) and the most influential features were geometrical ones. Even though our findings show the high performance of this model, further investigation with more subjects is suggested. To our knowledge, this is the first study that investigates qualitative classification of PFBs based on MRI with reference to DEXA scans using machine learning methods and the GA.
Performance Analysis of UAV-Assisted Hybrid FSO/RF Communication Systems under Various Weather Conditions
Authors: Wu Yan , Kong Dejin , Wang Qian , Li Gang
Published: September 2023

Nowadays, unmanned aerial vehicle (UAV) communication systems are commonly considered as one of the key enabling technologies for 6G. The hybrid free space optical (FSO)/radio frequency (RF) system has the advantages of both FSO and RF links to improve communication system performance, and the relay-assisted system adopts multi-hop transmission and cooperative diversity methods to extend communication coverage. Thus, a joint consideration of UAV-assistedUAV assisted relay in hybrid FSO/RF transmission is meaningful. In this paper, we aim to analyze the performance of UAV-assisted multi-hop parallel hybrid FSO/RF communication systems with and without pointing errors (PE) in terms of Bit Error Rate (BER) and outage probability. In our considered system, the FSO sub-link adopts the Exponential Weibull turbulence model and the RF sub-link suffers the Nakagami fading model. With these, new mathematical formulas of both BER and outage probability are derived under the UAV-assisted hybrid FSO/RF with different modulation methods. Through numerical evaluationnumerical simulations, the performances of UAV-assisted hybrid FSO/RF systems are analyzed under different weather conditions, modulation methods, optical receiver aperture, RF fading parameters, pointing errors, and relay structures. The results demonstrate that (1) compared to hybrid FSO/RF direct links, UAV-assisted hybrid FSO/RF systems can further improve system performance; (2) the performance of UAV-assisted hybrid FSO/RF systems varies with different relay structures; (3) large receiver aperture and RF fading parameters can further improve the communication performance of hybrid FSO/RF direct links and UAV-assisted hybrid FSO/RF systems.
Sar Ship Detection Based on Convnext with Multi-Pooling Channel Attention and Feature Intensification Pyramid Network
Authors: Wei Fanming , Wang Xiao
Published: September 2023

The advancements in ship detection technology using convolutional neural networks (CNNs) regarding synthetic aperture radar (SAR) images have been significant. Yet, there are still some limitations in the existing detection algorithms. First, the backbones cannot generate high-quality multiscale feature maps. Second, there is a lack of suitable attention mechanisms to suppress false alarms. Third, the current feature intensification algorithms are unable to effectively enhance the shallow feature’s semantic information, which hinders the detection of small ships. Fourth, top-level feature maps have rich semantic information; however, as a result of the reduction of channels, the semantic information is weakened. These four problems lead to poor performance in SAR ship detection and recognition. To address the mentioned issues, we put forward a new approach that has the following characteristics. First, we use Convnext as the backbone to generate high-quality multiscale feature maps. Second, to suppress false alarms, the multi-pooling channel attention (MPCA) is designed to generate a corresponding weight for each channel, suppressing redundant feature maps, and further optimizing the feature maps generated by Convnext. Third, a feature intensification pyramid network (FIPN) is specifically designed to intensify the feature maps, especially the shallow feature maps. Fourth, a top-level feature intensification (TLFI) is also proposed to compensate for semantic information loss within the top-level feature maps by utilizing semantic information from different spaces. The experimental dataset employed is the SAR Ship Detection Dataset (SSDD), and the experimental findings display that our approach exhibits superiority compared to other advanced approaches. The overall Average Precision (AP) reaches up to 95.6% on the SSDD, which improves the accuracy by at least 1.7% compared to the current excellent methods.
Secrecy Performance Analysis of Cooperative Multihop Transmission for WSNs under Eavesdropping Attacks
Authors: Triwidyastuti Yosefine , Perdana Ridho Hendra Yoga , Shim Kyusung , An Beongku
Published: September 2023

Multihop transmission is one of the important techniques to overcome the transmission coverage of each node in wireless sensor networks (WSNs). However, multihop transmission has a security issue due to the nature of a wireless medium. Additionally, the eavesdropper also attempts to interrupt the legitimate users’ transmission. Thus, in this paper, we study the secrecy performance of a multihop transmission under various eavesdropping attacks for WSNs. To improve the secrecy performance, we propose two node selection schemes in each cluster, namely, minimum node selection (MNS) and optimal node selection (ONS) schemes. To exploit the impact of the network parameters on the secrecy performance, we derive the closed-form expression of the secrecy outage probability (SOP) under different eavesdropping attacks. From the numerical results, the ONS scheme shows the most robust secrecy performance compared with the other schemes. However, the ONS scheme requires a lot of channel information to select the node in each cluster and transmit information. On the other side, the MNS scheme can reduce the amount of channel information compared with the ONS scheme, while the MNS scheme still provides secure transmission. In addition, the impact of the network parameters on the secrecy performance is also insightfully discussed in this paper. Moreover, we evaluate the trade-off of the proposed schemes between secrecy performance and computational complexity.
Smart Temperature Sensor Design and High-Density Water Temperature Monitoring in Estuarine and Coastal Areas
Authors: Wang Bozhi , Cai Huayang , Jia Qi , Pan Huimin , Li Bo , Fu Linxi
Published: September 2023

Acquiring in situ water temperature data is an indispensable and important component for analyzing thermal dynamics in estuarine and coastal areas. However, the long-term and high-density monitoring of water temperature is costly and technically challenging. In this paper, we present the design, calibration, and application of the smart temperature sensor TS-V1, a low-power yet low-cost temperature sensor for monitoring the spatial–temporal variations of surface water temperatures and air temperatures in estuarine and coastal areas. The temperature output of the TS-V1 sensor was calibrated against the Fluke-1551A sensor developed in the United States and the CTD-Diver sensor developed in the Netherlands. The results show that the accuracy of the TS-V1 sensor is 0.08 °C, while sensitivity tests suggest that the TS-V1 sensor (comprising a titanium alloy shell with a thermal conductivity of 7.6 W/(m °C)) is approximately 0.31~0.54 s/°C slower than the CTD-Diver sensor (zirconia shell with thermal conductivity of 3 W/(m °C)) in measuring water temperatures but 6.92~10.12 s/°C faster than the CTD-Diver sensor in measuring air temperatures. In addition, the price of the proposed TS-V1 sensor is only approximately 1 and 0.3 times as much as the established commercial sensors, respectively. The TS-V1 sensor was used to collect surface water temperature and air temperature in the western part of the Pearl River Estuary from July 2022 to September 2022. These data wells captured water and air temperature changes, frequency distributions, and temperature characteristics. Our sensor is, thus, particularly useful for the study of thermal dynamics in estuarine and coastal areas.
Efficacy of Metarhizium anisopliae against the Greater Pumpkin Fly Dacus bivitattus
Authors: Dubois Thomas , Onsongo Susan K. , Omuse Evanson R. , Odhiambo Joseph A. , Akutse Komivi S. , Mohamed Samira A.
Published: September 2023

The greater pumpkin fly Dacus bivittatus (Bigot) is a fruit fly indigenous to Africa, which causes extensive damage to Cucurbitaceae. To control this pest, farmers rely on synthetic chemicals, often organophosphates, which have negative effects on human health and the environment. However, the sustainable management of D. bivittatus may be obtained through integrated pest management (IPM) practices, with the use of biopesticides as a key component. In this study, the effect of nine isolates of the entomopathogenic fungus Metarhizium anisopliae (Metschnikoff) Sorokin (ICIPE 18, ICIPE 20, ICIPE 30, ICIPE 48, ICIPE 62, ICIPE 69, ICIPE 84, ICIPE 91 and ICIPE 94) was directly evaluated on adult D. bivittatus mortality. Adult flies were allowed to walk for 5 min on 0.3 g of dry conidia of each isolate and monitored daily for 10 days. We also evaluated the effect of sand inoculated with M. anisopliae on larval and pupal mortality and adult eclosion and mortality in three replicated experiments. Larvae were exposed to the same isolates at a concentration of 1 × 107 conidia/mL in sterile sand, and adult eclosion and mortality were monitored for 15 days. The median lethal time (LT50) of adults after direct exposure was shortest for ICIPE 18, ICIPE 20, ICIPE 30 and ICIPE 69 (3.11–3.52 days). In infested sand, larval mortality was highest for ICIPE 18 and ICIPE 20 (≥42.50%), while pupal mortality was highest for ICIPE 30 (≥41.25%). The lowest eclosion was observed for ICIPE 18, ICIPE 20, ICIPE 30 and ICIPE 69 (≤40.00%). The LT50 of adults eclosed from infested sand was shortest for ICIPE 18, ICIPE 20 and ICIPE 30 (4.48–6.95 days). ICIPE 18, ICIPE 20, ICIPE 30 and ICIPE 69 are, therefore, potential isolates for subsequent field testing on D. bivittatus populations.
Outgrowing the Private Car—Learnings from a Mobility-as-a-Service Intervention in Greater Copenhagen
Authors: Freudendal-Pedersen Malene , Lindberg Malene Rudolf , Hartmann-Petersen Katrine , Christensen Toke Haunstrup
Published: September 2023

This article discusses the potentials of reorienting traditional rational transport planning towards a mobilities approach that includes social perspectives of practices in everyday lives. Empirically, the discussion is based on results from a MaaS intervention project in two urban areas and one sub-urban area in Greater Copenhagen. This article argues that attention to context, experience, storytelling, identity, and inequality are fundamental in changing interlocked, non-sustainable practices. Achieving a sustainable transformation of transportation, including promoting shared mobility and MaaS solutions as alternatives to private car use, requires a holistic view of the role and organization of everyday mobilities as more than just a technological issue. This article concludes that MaaS has the potential to be a strong tool, but technologies and short experiments are not enough. New MaaS solutions need time to implement, and relying on the free market as a way forward is potentially problematic when this can lead to mobility inequalities between different areas.
ISLKG: The Construction of Island Knowledge Graph and Knowledge Reasoning
Authors: He Qi , Yu Chenyang , Song Wei , Jiang Xiaoyi , Song Lili , Wang Jian
Published: September 2023

Islands with both land and sea characteristics provide the foundation for protecting the marine environment, preserving the ecological balance of the ocean, and fostering sustainable economic and social growth. Advanced monitoring technologies have boosted the collection of multi-source data of islands, but the isolation and insufficiency of data are harmful to the development and management of islands. To form a coherent and complete understanding of islands, it is necessary to convert the multi-source data into knowledge-based information. This paper proposes an island knowledge graph construction method based on the combination of entity dictionary and rule patterns, and builds the island knowledge graph (ISLKG) from the top to bottom. An ontology layer is initially created to standardize island knowledge, followed by the collection, transformation, and extraction of entities and relationships from multi-source data in order to construct an island knowledge graph. Then, a knowledge reasoning model based on knowledge graph embedding is used for knowledge completion, improving the ISLKG. Finally, the knowledge inference model was verified based on the constructed island knowledge graph. The results indicate that the model can effectively predict missing entities and complement the island knowledge graph.
Evaluating the Cultural Sustainability of the Adaptive Reuse of Al-Nabulsi Traditional House into a Cultural Center in Irbid, Jordan
Authors: Amro Dana Khalid , Sukkar Ahmad , Yahia Moohammed Wasim , Abukeshek Mohammad Khaleel
Published: September 2023

Adaptive reuse maintains cultural sustainability by adapting heritage buildings for new functions while retaining their original structure. The al-Nabulsi’s traditional courtyard house in Irbid, northern Jordan, represents the city’s dominant residential heritage building typology from the 1920s. It has been adapted and reused to preserve cultural sustainability by providing a visitor experience pertinent to the local tangible and intangible cultural heritage. This article evaluates the effect of the house’s adaptive reuse into a cultural visitor center on the local community’s cultural sustainability between 2018 and 2023 through the user experience. Through a review of the literature on cultural sustainability and adaptive reuse and deploying mixed qualitative and quantitative methodology of field observation, statistical analysis, and critical reflections on interviews and Google Travel’s reviews of the building, the research presents the project phases, resolutions, and challenges, contextualizing them in the modern debate on tangible and intangible heritage. The article used the Quintuple Helix Model as an analytical framework to explain the interactions between societal systems that directly and indirectly affect the Sustainable Development Goals (SDGs). The findings revealed that in 2018, the center’s conservation and adaptation relatively enhanced the local community’s cultural sustainability and feeling of its identity. However, in 2023, further actions are needed to enhance the visitor experience and spread awareness of its significance. Enrichments in government, education, and civil society systems have been moderate, and further improvements in economic and environmental systems are essential to meet the potential goals of the SDGs. No research to date has evaluated the cultural sustainability of the adaptive reuse of this significant house/center, providing insights into a notable example of the conditions surrounding adaptive reuse in Jordan and Arab Middle Eastern countries.