bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of JAK2 Haplotype GGCC_46/1 with the Response to Onco-Drug in MPNs Patients Positive for JAK2V617F Mutation
Authors: Perrone Michela , Sergio Sara , Tarantino Amalia , Loglisci Giuseppina , Matera Rosella , Seripa Davide , Maffia Michele , Di Renzo Nicola
Published: September 2024

Background: JAK2 V617F is a somatic mutation associated with myeloproliferative neoplasms (MPNs) including polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). In MPNs, this mutation is associated with the germline GGCC (46/1) haplotype. Several studies associated JAK2 haplotype GGCC_46/1 with some MPNs clinical parameters, but not one explore the link between JAK2 haplotype GGCC_46/1 and onco-drug resistance. Thus, we assessed for the JAK2 46/1 haplotype’s correlation with therapy response in JAK2 V617F-positive patients. Methods: Patients with MPN, selected by the Hematology Laboratory of “V. Fazzi” Hospital (LE), were analyzed with RLFP-PCR assay with rs10974944 SNP. Results: Results show how the majority of patients had PV (63%) or PMF (61%) and that 58% of patients who developed drug resistance had the C/G genotype, while only 11% had the G/G allele. While no direct correlation between JAK2 46/1 haplotype variants and drug resistance was found, the G/G allele was associated with disease progression to myelofibrosis and certain resistance-related clinical parameters (p = 0.002449, odds ratio = 3.701209). Conclusions: Although other analyses are required, due to the narrow cardinality of sample, our findings suggest how the G/G allele could be useful for MPNs diagnosis and for the prediction of the disease outcome.
Ionic Liquid-Based Grapeseed Oil Emulsion for Enhanced Anti-Wrinkle Treatment
Authors: Yang Bo , Zhang Xu , Zhang Liguo , Wu Jinjin , Wang Wei , Huang Qiaomei , Wang Zhenyuan , Zhang Jichuan , Xu Tongjie , Wu Chengyu , Zhang Jiaheng
Published: September 2024

Objectives: To address the poor efficacy and percutaneous penetration of grape seed oil, ionic liquids and nanotechnology were combined to prepare a grape seed oil emulsion. Methods: A novel Menthol-CoQ10 ionic liquid and ionic liquid based grapeseed oil emulsion were prepared and confirmed. Results: The average size of the grapeseed oil emulsion was 218 nm, and its zeta potential was −33.5 mV. The ionic liquid-based grape seed oil emulsion exhibited a transdermal penetration effect 4.63-fold higher than that of ordinary grape seed oil emulsion. Ionic liquid also displayed enhanced efficiency both in vitro and in vivo. It significantly inhibited the production of DPPH free radicals and tyrosinase, inhibited melanin and matrix metalloproteinase-1 (MMP-1) produced by cells, and promoted type I collagen expression in fibroblasts. After 28 days of continuous use, the grapeseed oil emulsion improved the water content of the stratum corneum and the rate of transepidermal water loss, enhanced the firmness and elasticity of the skin, and significantly improved the total number and length of under-eye lines, tail lines, nasolabial folds, and marionette lines on the face. Conclusions: Menthol-CoQ10 ionic liquid is a promising functional excipient for both transdermal delivery increase and efficient enhancement. Ionic liquid and nanotechnology for grape seed oil facial mask displayed significantly enhanced efficacy and permeability.
Singlet Oxygen in Photodynamic Therapy
Authors: Cui Shengdong , Guo Xingran , Wang Sen , Wei Zhe , Huang Deliang , Zhang Xianzeng , Zhu Timothy C. , Huang Zheng
Published: September 2024

Photodynamic therapy (PDT) is a therapeutic modality that depends on the interaction of light, photosensitizers, and oxygen. The photon absorption and energy transfer process can lead to the Type II photochemical reaction of the photosensitizer and the production of singlet oxygen (1O2), which strongly oxidizes and reacts with biomolecules, ultimately causing oxidative damage to the target cells. Therefore, 1O2 is regarded as the key photocytotoxic species accountable for the initial photodynamic reactions for Type II photosensitizers. This article will provide a comprehensive review of 1O2 properties, 1O2 production, and 1O2 detection in the PDT process. The available 1O2 data of regulatory-approved photosensitizing drugs will also be discussed.
Optimization and Appraisal of Nintedanib-Loaded Mixed Polymeric Micelles as a Potential Nanovector for Non-Invasive Pulmonary Fibrosis Mitigation
Authors: Aboud Heba M. , El Menshawe Shahira F. , Mohammed Nada H. , Tulbah Alaa S. , Ali Adel A.
Published: September 2024

Background/Objectives: Nintedanib (NTD), a triple tyrosine kinase receptor inhibitor, is the recommended first-line tackling option for idiopathic pulmonary fibrosis (IPF). Nevertheless, the adequacy of NTD is curtailed by issues associated with its low solubility, first-pass effect, poor bioavailability, and liver toxicity. The objective of our work was to develop a non-invasive intratracheal (i.t.) nanoparadigm based on NTD-loaded polymeric mixed micelles (NTD-PMMs) that can effectively treat IPF by sustaining the release of NTD, and snowballing its bioavailability, solubility, and efficacy. Methods: Design-Expert® software was used to optimize various NTD-PMMs formulations via Box–Behnken design adopting the thin-film hydration technique. The optimum formulation was chosen and in vivo tested in a rat model to explore its comparative bioavailability and toxicity. Results: The formulation composition with 309.217 mg of Soluplus, 150 mg of Tween 80, and 40 mg of sodium deoxycholate was found to fulfill the requisites of an optimum NTD-PMMs formulation. The optimum NTD-PMMs formulation divulged 90.26% entrapment efficiency with a surface charge of −14.72 mV and a nanoscale diameter of 61.36 nm. Also, it substantially sustained the release of NTD by 66.84% after 24 h and manifested a pronounced stability. In vivo histopathology investigations verified the safety of NTD-PMMs delivered intratracheally. Moreover, pharmacokinetic analyses disclosed accentuated relative bioavailability of the optimized NTD-PMMs by 2.4- and 3.82-fold as compared with both the i.t. and oral crude NTD suspensions, respectively. Conclusions: Overall, the current results elicited the potential of PMMs to serve as a promising pulmonary nanovector for the targeted delivery of NTD.
‘Show Don’t Tell’: What Creative Writing Has to Teach Philosophy
Authors: Musgrave David
Published: September 2024

Poetry and philosophy have had a close but uneasy relationship in the western tradition. Both share an eschewal of the discovery of novel facts, but are somewhat opposed in that discovery is a central aim of poetry, but not at all the aim of philosophy. Through a close reading of W.H. Auden’s ‘In Memory of W.B. Yeats’ and a versification of part of G.E. Moore’s ‘A Defence of Common Sense’, I argue that what poetry shows corresponds, in a broadly symbolist sense, to Wittgenstein’s understanding of the miraculous nature of the world. In this regard, poetry can offer philosophy clarity, in the form of its tonal architecture, value, and ethics, and may also constitute a perspicuous representation. Poetry remains in a perpetual mode of potential, as well as being possessed of a vatic autonomy.
High-Precision Tracking of Free-Space Optical Communication System on Mobile Platforms
Authors: Sun Ning , Wang Yuehui , Wu Yuanda , Liu Jianguo
Published: September 2024

We propose a new free-space optical (FSO) communication system for moving platform tracking, which can achieve high precision aiming and tracking. Our prototype system consists of three parts. As a coarse sighting structure, the electro-optical pod module is used for target searching and coarse sighting in the initial stage. As a precise aiming structure, the precise targeting loads module located inside the electro-optical pod module uses miniaturized tubular folding optical path technology for high-precision alignment and tracking. The bottom module of the system is used for communication. In the tracking process, the control unit uses spot offset collected by CCD to perform decoupling calculation and then compensates the offset by swinging tracking and aiming structure. We did track experiments on a mobile platform. The experiment successfully tracked a moving target at 100 m distance, and the tracking error was less than 1 mrad. The proposed system can provide stable communication links between the mobile platforms.
Impact of Corn, Bean, and Semolina Flour Blends and Processing Methods on the Physical Properties and Antioxidant Activity of Instant Noodles
Authors: Aviles-Simental Diana , Gallegos-Infante Jose Alberto , Rocha-Guzmán Nuria Elizabeth , Pérez-Lozano Alejandro , Ochoa-Martínez Luz Araceli
Published: September 2024

The main objective was to evaluate the use of common bean flour (CBF), corn flour, and semolina to obtain instant noodles by means of a hot dry and frying process. The hot drying process was conducted at 60 °C for 4 h, and frying was conducted at 140 °C and 160 °C for 1 and 3 min. Proximate analysis, total phenolic content (TPC), the 2,2-diphenyl-1-picrylhydrazyl (DPPH) test, the oxygen radical absorbance capacity (ORAC) assay, phenolic acids and flavonoids profile by UPLC-ESI-MS/MS, the optimal cooking time (OCT), and color and texture analysis (TPA) were conducted. The general linear model and regression analysis were used. The incorporation of CBF resulted in an elevated protein content and TPC of the noodles. The noodles (hot dry) with CBF exhibited an enhanced antioxidant capacity. The adhesiveness has a direct correlation with the cinnamic, chlorogenic, and caffeic acid content (r2 = 0.95 or higher), as well as an inverse relationship with the vanillic, ferulic, and sinapic acids (r2 = −0.80 to −0.85). The dry hot noodles exhibited the lowest value of hardness (31.0 ± 1.5 N). The incorporation of common bean flour and corn flour enhances the nutritional profile of noodles. However, hot dry process affects their mechanical characteristics in comparison to the frying process.
Alleviating Effects of Methyl Jasmonate on Pepper (Capsicum annuum L.) Seedlings under Low-Temperature Combined with Low-Light Stress
Authors: Pu Kaiguo , Li Nenghui , Gao Yanqiang , Zhang Miao , Wang Tiantian , Xie Jianming , Li Jing
Published: September 2024

Low temperature combined with low light (LL) is an important factor limiting pepper quality and yield. ‘Hang Jiao No. 2′ were used as experimental materials, and different concentrations of MeJA (T1 (0 μM), T2 (100 μM), T3 (150 μM), T4 (200 μM), T5 (250 μM) and T6 (300 μM)) were sprayed under LL stress to explore the positive effect of exogenous methyl jasmonate (MeJA) on peppers under LL stress. The photosynthetic properties, osmoregulatory substance, reactive oxygen species, antioxidant enzyme activities, and related gene expressions of the peppers were measured. Our results demonstrated that 200 μM MeJA treatment significantly increased chlorophyll content, light quantum flux per active RC electron transfer (Eto/RC), maximum captured photonic flux per active RC (TRo/RC), energy flux for electron transfer in the excitation cross section (Eto/CSm), energy flux captured by absorption in the excitation cross section (TRo/CSm), soluble protein, and soluble sugar content. Moreover, it significantly improved the maximum photochemical efficiency of PSII (Fv/Fm) and performance index based on absorbed light energy (PI (abs)) by 56.77% and 67.00%, respectively, and significantly decreased malondialdehyde (MDA) content and relative conductivity by 30.55% and 28.17%, respectively. Additionally, antioxidant enzyme activities were elevated, and the expression of the related genes was activated in pepper seedlings under stress, leading to a significant reduction in reactive oxygen species content. In conclusion, our findings confirmed that 200 μM MeJA could reduce the injury of LL to pepper leaves to the photosynthetic organs of pepper leaves, protect the integrity of the cell membrane, and further improve the tolerance of pepper seedlings to LL.
Exploring Experimental Isotope Scaling and Density Limit in Tokamak Transport
Authors: Weiland Jan , Rafiq Tariq , Schuster Eugenio
Published: September 2024

As it turns out, both isotope scaling and density limits are phenomena closely linked to fluid closure. The necessity to include ion viscosity arises for both phenomena. Thus, we have added ion viscosity to our model. The experimental isotope scaling has been successfully recovered in our fluid model through parameter scans. Although ion viscosity typically exerts a small effect, the density limit is manifested by increasing the density by approximately tenfold from the typical experimental density. In our case, this increase originates from the density in the Cyclone base case. Notably, these phenomena would not manifest with a gyro-Landau fluid closure. The isotope scaling is nullified by the addition of a gyro-Landau term, while the density limit results from permitting ion viscosity to become comparable to the gyro-Landau term. The mechanism of zonal flows, demonstrated analytically for the Dimits upshift, yields insights into the isotope scaling observed in experiments. In our approach, ion viscosity is introduced in place of the Landau fluid resonances found in some fluid models. This implies that the mechanism of isotope scaling operates at the level of fluid closure in connection with the generation of zonal flows. The strength of zonal flows in our model has been verified, particularly in connection with the successful simulation of the nonlinear Dimits shift. Consequently, a role is played by our approach in the temperature perturbation part of the Reynolds stress.
Effect of Phase Structure on the Viscoelasticity and Mechanical Properties of Isotactic Polypropylene Multicomponents Polymerized with Non-Conjugated α,ω-Diene
Authors: Zhao Songmei , Dong Jin-Yong , Qin Yawei , Zhao Chuanzhuang , Yu Yuan , Liu Weili
Published: September 2024

Increasing of rubber content in isotactic polypropylene/ethylene–propylene rubber (iPP/EPR) alloys can extend the applications of this kind of polyolefin. The EPR content and phase structure of isotactic polypropylene multicomponents have great effect on the viscoelasticity and mechanical properties. iPP/EPR in-reactor alloys with a high EPR content were obtained through the in situ crosslinking of EPR chains with α,ω-diene. The morphological observation results indicate that the crosslinked iPP/EPR in-reactor alloys have a good spherical shape with clean and rough external surfaces. The high EPR content is finely dispersed in the crosslinked iPP/EPR alloys in areas ranging in size from tens of nanometers to several micrometers, which implies that a sufficient crosslinking degree of EPR chains can effectively prevent their aggregation and restrict macro-phase separation. The rheological results show a clear plateau in the terminal region, which reveals an entangled polymer chain network in the crosslinked iPP/EPR alloys. The well-dispersed EPR and the bi-continuous phase structure have a great effect on the mechanical properties of the isotactic polypropylene multicomponent which were assessed.
Investigation of the Interfacial Fusion Bonding on Hybrid Additively Manufactured Components under Torsional Load
Authors: Kizak Melike , von Bartschikowski Anna , Trauth Anna , Heigl Christian , Drechsler Klaus
Published: September 2024

Hybrid manufacturing processes integrate multiple manufacturing techniques to leverage their respective advantages and mitigate their limitations. This study combines additive manufacturing and injection molding, aiming to efficiently produce components with extensive design flexibility and functional integration. The research explores the interfacial fusion bonding of hybrid additively manufactured components under torsional loading. Specifically, it examines the impact of various surface treatments on injection molded parts and the influence of different build chamber temperatures during additive manufacturing on torsional strength. Polycarbonate components, neat, with glass or carbon fiber-reinforcement, are produced and assessed for dimensional accuracy, torsional strength, and fracture behavior. The findings emphasize the critical role of surface treatment for the injection molded components before additive manufacturing. Additionally, the study identifies the influence of chamber temperatures on both dimensional accuracy and torsional strength. Among all investigated materials, plasma-treated neat samples exhibited the best torsional strength. The torsional strength was increased by up to 87% by actively heating the build chamber to 186 °C for neat polycarbonate. These insights aim to advance the quality and performance of hybrid additively manufactured components, broadening their application potential across diverse fields.
Influence of Graphene Nanoplatelets and Post-Curing Conditions on the Mechanical and Viscoelastic Properties of Stereolithography 3D-Printed Nanocomposites
Authors: Ahmad Khalid Haj , Mohamad Zurina , Khan Zahid Iqbal
Published: September 2024

This study presents an innovative approach to improving the mechanical and viscoelastic properties of 3D-printed stereolithography (SLA) nanocomposites by incorporating graphene nanoplatelets (xGNP) into photopolymer matrices. Utilizing an SLA 3D printer, photopolymer formulations with xGNP concentrations of up to 0.25 wt% were successfully produced. Post-print curing was carried out using two different methods: ultraviolet (UV) curing and high-temperature curing at 160 °C. Mechanical characterization using nanoindentation showed a significant increase in elastic modulus by 104% and an increase in hardness by 85% for nanocomposites containing 0.25 wt% xGNP. Furthermore, dynamic mechanical analysis (DMA) revealed a 39% improvement in storage modulus for samples without post-curing and an improvement of approximately 30% for samples subjected to high-temperature curing. These significant improvements highlight xGNP’s potential to not only increase the performance of SLA 3D-printed components but also streamline the manufacturing process by reducing or eliminating energy-intensive post-curing steps. This innovative integration of graphene nanoplatelets paves the way for the production of high-performance, functional 3D-printed products and offers significant advances for various industries with a high impact. The results highlight the transformative role of nanomaterials in additive manufacturing and position this work at the forefront of materials science and 3D printing technology.
A Description of the Isothermal Ageing Creep Process in Polymethyl Methacrylate Using Fractional Differential Models
Authors: Wang Chuhong , Chen Xin
Published: September 2024

Fractional differential viscoelastic models can describe complex material behaviours and fit experimental data well; however, the physical significance of model parameters is difficult to express. In this study, the fractional differential Maxwell, Kelvin, and Zener models were used to fit the short-term creep compliance curves of polymethyl methacrylate at different ageing times. The model fits were in good agreement with the experimental data. As the ageing time increased, the fractional differential Zener model showed a relative increase in the modulus parameter of the spring and a relative decrease in the modulus parameter reflecting the viscosity of the spring-pot, which indicated that physical ageing made the material more elastic. The relaxation time of the material increased, which indicated that the physical ageing reduced the free volume of the material, hindered the movement of molecules/segments, and increased the time required for the material to reach equilibrium. The fractional order of the model decreased, which reflected the phenomenon that physical ageing reduced the creep compliance of the material. Using the relaxation time as the time scale, the creep curves at different ageing times under the same stress level could be superimposed, naturally presenting the time–ageing time equivalence principle.
Adolescent Suicides in the Western Pacific Region Have Become a More Serious Public Health Problem than in Other Regions
Authors: Okubo Ruri , Matsumoto Ryusuke , Motomura Eishi , Okada Motohiro
Published: September 2024

Globally, suicide mortality rates have decreased in this century; however, it has been reported that the decreasing trends of some subgroups were attenuated in the late 2010s. These tendencies are pronounced among adolescents. In this study, the temporal fluctuations of the age-standardized death rate of suicide (ASDR-suicide), crude mortality rate of suicide (CMR-suicide), and percentage of suicides per total deaths (PTD-suicide) among adolescents (10–24 years) in the global high-income and middle-income countries and in the Western Pacific Region (WPR) from 1990 to 2019, as well as the fixed effects of communication factors (penetration of cellular telephones and the Internet) on the ASDR-suicide/CMR-suicide/PTD-suicide of adolescents, were analyzed using the WHO Mortality Database. The male ASDR-suicide in global middle-income countries decreased, and those of males in global high-income countries and females in middle-income countries were unchanged, while the rate of other groups (males in the WPR and females in high-income countries and the WPR) increased. The ASDR-suicide of adolescent males in the WPR was almost equivalent to that of males in global high-income and middle-income countries in the 1990s but was higher than the rate in the 2010s. The ASDR-suicide of adolescent females in the WPR was consistently higher than that of females in global high-income and middle-income countries from 1990 to 2019, but the differences widened over time. The PTD-suicide of both males and females in middle-income countries was unchanged, whereas the PTD-suicide in global high-income countries and the WPR increased over time. The PTD-suicide in the WPR markedly increased by >40% in the late 2010s. The fixed effects of cellular telephone and Internet penetrations were negatively and positively related to adolescent suicide in the WPR, respectively. Therefore, these results suggest that, in this century, suicide prevention in adolescent health activities has been increasing in importance in the WPR compared with other regions.
Eschatologia Iranica I: From Zoroastrian Cosmos to Abbasid Madīnat al-Salām: A Journey through Utopia and Heterotopia
Authors: Rezania Kianoosh
Published: September 2024

The history of imperial dynasties in West Asia is replete with examples of remarkable urban foundations. Two notable instances are the Sasanian Ardašīr-xwarrah and the Abbasid Madīnat al-Salām, which can be classified as cosmic cities or heterotopias. This article examines the utopian foundations of these heterotopias. To this end, it analyzes four religious and imperial spaces: the representation of the earth and sky in the Zoroastrian cosmography, Yima’s Vara according to the Avestan texts, Ardašīr-xwarrah, and finally, Madīnat al-Salām. This investigation aims to ascertain the extent to which the spatial characteristics of each of these spaces have been utilized in the production of the subsequent architectural forms. Similarly, it examines the development of the cosmological and eschatological paradise in relation to the Achaemenian and Sasanian royal gardens. The theoretical framework of this study is based on Michael Foucault’s notion of heterotopia, which has been further developed by Henri Lefebvre’s theory of space. The conceptual metaphor theory offers a cognitive linguistic foundation for elucidating the projections of utopias and heterotopias onto one another. To this end, the article focuses on the conceptual metaphor GOD IS A KING.
Selkea! Memories of Eating Non-Kosher Food among the Spanish–Moroccan Jewish Diaspora in Israel
Authors: Cohen Angy , Moreno Aviad
Published: September 2024

Drawing on life-story interviews and ethnography conducted in Israel from 2009 to 2023, this article examines how members of the Spanish-speaking Moroccan–Jewish diaspora in Israel recalled their habits of eating non-kosher food in Morocco. We explore how these memories emerged in response to commonplace discourses that depict Moroccan Jews as a distinctly religious-traditional ethnic group, untouched by European secular influences, and dichotomous to modern secular cultures in Israel. Contrary to this image, members of the community whom we interviewed highlighted a Jewish Moroccan life that was deeply connected to Spanish colonialism and the broader Hispanic and Sephardi worlds. We focus specifically on the concept of selkear, a Haketia (Judeo-Spanish) term meaning to let something go, make an exception, or turn a blind eye. Our analysis of our participants’ memories provides a nuanced understanding of Jewish religiosity in the context of colonialism and of how Mizrahi–Sephardi immigrants in Israel reclaimed their Judaism. Highlighting the practice of eating non-kosher food is thus a strategy used to challenge dominant notions of rigid religious commitment within the Sephardi diaspora and their interpretation in Israel.
Environment as Palimpsest: Layers of Buddhist Imagery on Kyŏngju Namsan during the Unified Silla (668–935 CE) Period
Authors: Lee Elizabeth
Published: September 2024

This study unpacks the Buddhist assimilation of Namsan (South Mountain) in Kyŏngju through the creation and aggregation of Buddhist sculptures and structures on its slopes during the seventh to tenth centuries. Though steeped in native lore regarding nature deities and efficacious rocks, auspicious geological features such as Namsan were recast as part of a Buddhist landscape filled with manifestations of the Buddha and his attendants. These images served to demarcate claims of Buddhism’s place in the peninsula and were situated within sites that were previously marked and claimed by indigenous systems of belief. Employing an approach that draws parallels with David Harvey’s concept of urban environments as palimpsests, this paper reveals that Namsan was a multifaceted site, with military fortifications, temples, and rock-carved sculptures augmenting its spiritual and political significance. The repeated installation of Buddhist imagery ‘recovered’ the mountain, subsuming indigenous beliefs under Buddhist practices. This research finds that Namsan’s landscape was purposefully layered, reflecting the dialectical relationship between various communities and their religious and social practices over time. Analyzing Namsan as a palimpsest underscores the strategic appropriation of the mountain’s materiality and sacrality to establish a Buddhist territory deeply intertwined with the Silla elite’s politics and ideologies.
Transmuted Distortion Functions for Measuring Risks
Authors: Alkasasbeh Muna , Lee Carl , Famoye Felix
Published: September 2024

This paper introduces a new family of distortion functions for measuring risks, developed using transmutation techniques. We identify the parameter spaces where the proposed distortions exhibit concavity. Considering that the choice of distortion parameters can be influenced by political factors or users’ risk aversion levels, we generate plots of the distortion functions to examine how these parameters impact the tasks and users’ attitudes toward risk. The coherent properties of the resulting risk measures are explored, outlining the conditions under which the transmuted Kumaraswamy and transmuted truncated normal distortions ensure coherence. Numerical analyses demonstrate the effects of parameter variations on the derived risk measures, highlighting the effectiveness of the proposed distortion functions in accurately assessing risk.
InSAR Integrated Machine Learning Approach for Landslide Susceptibility Mapping in California
Authors: Vaka Divya Sekhar , Yaragunda Vishnuvardhan Reddy , Perdikou Skevi , Papanicolaou Alexandra
Published: September 2024

Landslides pose significant threats to life and property, particularly in mountainous regions. To address this, this study develops a landslide susceptibility model integrating Earth Observation (EO) data, historical data, and Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) ground movement results. The model categorizes areas into four susceptibility classes (from Class 1 to Class 4) using a multi-class classification approach. Results indicate that the Xtreme Gradient Boosting (XGB) model effectively predicts landslide susceptibility with area under the curve (AUC) values ranging from 0.93 to 0.97, with high accuracy of 0.89 and a balanced performance across different susceptibility classes. The integration of MT-InSAR data enhances the model’s ability to capture dynamic ground movement and improves landslide mapping. The landslide susceptibility map generated by the XGB model indicates high susceptibility along the Pacific coast. The optimal model was validated against 272 historical landslide occurrences, with predictions distributed as follows: 68 occurrences (25%) in Class 1, 142 occurrences (52%) in Class 2, 58 occurrences (21.5%) in Class 3, and 4 occurrences (1.5%) in Class 4. This study highlights the importance of considering temporal changes in environmental conditions such as precipitation, distance to streams, and changes in vegetation for accurate landslide susceptibility assessment.
Lidar-Observed Diel Vertical Variations of Inland Chlorophyll a Concentration
Authors: Zhao Hongkai , Zhou Yudi , Gu Qiuling , Han Yicai , Wu Hongda , Xu Peituo , Lin Lei , Lv Weige , Wu Lan , Wu Lingyun , Jiang Chengchong , Chen Yang , Yuan Mingzhu , Sun Wenbo , Liu Chong , Liu Dong
Published: September 2024

The diel vertical variations of chlorophyll a (Chl-a) concentration are thought of primarily as an external manifestation of regulating phytoplankton’s biomass, which is essential for dynamically estimating the biogeochemical cycle in inland waters. However, information on these variations is limited due to insufficient measurements. Undersampled observations lead to delayed responses in phytoplankton assessment, impacting accurate evaluations of carbon export and water quality in dynamic inland waters. Here, we report the first lidar-observed diel vertical variations of inland Chl-a concentration. Strong agreement with r2 of 0.83 and a root mean square relative difference (RMSRD) of 9.0% between the lidar-retrieved and in situ measured Chl-a concentration verified the feasibility of the Mie–fluorescence–Raman lidar (MFRL). An experiment conducted at a fixed observatory demonstrated the lidar-observed diel Chl-a concentration variations. The results showed that diel variations of Chl-a and the formation of subsurface phytoplankton layers were driven by light availability and variations in water temperature. Furthermore, the facilitation from solar radiation-regulated water temperature on the phytoplankton growth rate was revealed by the high correlation between water temperature and Chl-a concentration anomalies. Lidar technology is expected to provide new insights into continuous three-dimension observations and be of great importance in dynamic inland water ecosystems.
Landslide Susceptibility Assessment in Yulong County Using Contribution Degree Clustering Method and Stacking Ensemble Coupled Model Based on Certainty Factor
Authors: Qin Yang , Zhao Zhifang , Zhou Dingyi , Chang Kangtai , Mou Qiaomu , Yang Yonglin , Hu Yunfei
Published: September 2024

To address the subjectivity of traditional factor attribute grading methods and the weak predictive capabilities of single-model classifications, this study focused on Yulong County; the Contribution Degree Clustering Method (CDCM) utilizes the Certainty Factor (CF) as the contribution index to partition continuous factor attribute intervals. Additionally, the Sparrow Search Optimization Algorithm (SSA) is employed for hyperparameter tuning. The CF is incorporated into Support Vector Machine (SVM), Back Propagation Neural Network (BPNN), and Random Forest (RF) models to form the CF-SSA-SVM, CF-SSA-BPNN, and CF-SSA-RF coupling models, respectively. These basic coupling models are further integrated using the Stacking algorithm to create the CF-SSA-Stacking integrated coupling model for constructing a landslide susceptibility assessment system. The results indicate that the CF-SSA-Stacking integrated coupling model achieves the highest accuracy, F1 score, Kappa coefficient, and AUC value, with values of 0.89375, 0.89172, 0.787500, and 0.9522, respectively. These metrics are significantly superior to those of the three basic coupling models, demonstrating better generalization capability and reliability. This suggests that the model can identify more historical landslide occurrences using fewer grid areas classified as extremely-high- or high-susceptibility zones. It is suitable as an effective regional landslide susceptibility assessment method for practical disaster prevention and mitigation applications. Further studies could explore the model’s performance across varying geological settings or with different datasets, providing a roadmap for future research and development in landslide susceptibility assessment.
MDSCNN: Remote Sensing Image Spatial–Spectral Fusion Method via Multi-Scale Dual-Stream Convolutional Neural Network
Authors: Wang Wenqing , Jia Fei , Yang Yifei , Mu Kunpeng , Liu Han
Published: September 2024

Pansharpening refers to enhancing the spatial resolution of multispectral images through panchromatic images while preserving their spectral features. However, existing traditional methods or deep learning methods always have certain distortions in the spatial or spectral dimensions. This paper proposes a remote sensing spatial–spectral fusion method based on a multi-scale dual-stream convolutional neural network, which includes feature extraction, feature fusion, and image reconstruction modules for each scale. In terms of feature fusion, we propose a multi cascade module to better fuse image features. We also design a new loss function aim at enhancing the high degree of consistency between fused images and reference images in terms of spatial details and spectral information. To validate its effectiveness, we conduct thorough experimental analyses on two widely used remote sensing datasets: GeoEye-1 and Ikonos. Compared with the nine leading pansharpening techniques, the proposed method demonstrates superior performance in multiple key evaluation metrics.
A Comprehensive Comparison of Far-Field and Near-Field Imaging Radiometry in Synthetic Aperture Interferometry
Authors: Anterrieu Eric , Yu Louise , Jeannin Nicolas
Published: September 2024

Synthetic aperture interferometry (SAI) is a signal processing technique that mixes the signals collected by pairs of elementary antennas to obtain high-resolution images with the aid of a computer. This note aims at studying the effects of the distance between the synthetic aperture interferometer and an observed scene with respect to the size of the antenna array onto the imaging capabilities of the instrument. Far-field conditions and near-field ones are compared from an algebraic perspective with the aid of simulations conducted at microwave frequencies with the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) onboard the Soil Moisture and Ocean Salinity (SMOS) mission. Although in both cases the signals kept by pairs of elementary antennas are cross-correlated to obtain complex visibilities, there are several differences that deserve attention at the modeling level, as well as at the imaging one. These particularities are clearly identified, and they are all taken into account in this study: near-field imaging is investigated with spherical waves, without neglecting any terms, whereas far-field imaging approximation is considered with plane waves according to the Van–Citter Zernike theorem. From an algebraic point of view, although the corresponding modeling matrices are both rank-deficient, we explain why the singular value distributions of these matrices are different. It is also shown how the angular synthesized point-spread function of the antenna array, whose shape varies with the distance to the instrument, can be helpful for estimating the boundary between the Fresnel region and the Fraunhofer one. Finally, whatever the region concerned by the aperture synthesis operation, it is shown that the imaging capabilities and the performances in the near-field and far-field regions are almost the same, provided the appropriate modeling matrix is taken into account.
Spatiotemporal Variations and Characteristics of CO, H2CO and HCN Emissions from Biomass Burning Monitored by FTIR Spectroscopy
Authors: Zhu Qianqian , Wang Wei , Shan Changgong , Xie Yu , Wu Peng , Liang Bin , Peng Xuan , Qian Zhengwei , Liu Cheng
Published: September 2024

Studies of the impact of biomass burning and the emissions of trace gases from biomass burning, especially using long-term observations, are scarce in China. We utilize solar absorption spectra obtained via ground-based high-resolution Fourier transform infrared (FTIR) spectroscopy to retrieve the atmospheric total columns and vertical profiles of carbon monoxide (CO), formaldehyde (H2CO), and hydrogen cyanide (HCN) in Hefei, China. Seasonal and interannual variability in the three gases from 2016 to 2022 are analyzed. Atmospheric CO shows significant seasonal variations, peaking during spring and winter, and declining during summer, with a seasonal amplitude of 8.07 × 1017 molecules cm−2 and a seasonal variability of 29.35%. H2CO and HCN have similar seasonal patterns to each other, with high concentrations in summer and low concentrations in winter. The seasonal amplitude of H2CO and HCN are 1.89 × 1016 molecules cm−2 and 2.32 × 1015 molecules cm−2, respectively, with a seasonal variability of 133.07% and 34.69%, respectively. The means of the annual variation rate for CO, H2CO, and HCN are (−2.67 ± 2.88)% yr−1, (2.52 ± 12.48)% yr−1 and (−3.48 ± 7.26)% yr−1, respectively. To assess the influence of biomass burning on the variations in column concentrations of the three gases, the correlation between CO, H2CO, and HCN was analyzed. The months during which the monthly correlation coefficient between CO and H2CO with HCN exceeds 0.8, and the fire radiative power (FRP) observed by satellites is larger than its monthly average are regarded as a biomass-burning occurrence in Anhui province. Additionally, the enhancement ratios of ΔH2CO/ΔCO and ΔHCN/ΔCO were calculated for the periods impacted by the biomass burning. Finally, backward trajectory cluster analysis and the potential source contribution function (PSCF) calculation identified the air mass transport pathways and the potential source areas at the Hefei site.
Assessing the Potential of UAV for Large-Scale Fractional Vegetation Cover Mapping with Satellite Data and Machine Learning
Authors: Chen Xunlong , Sun Yiming , Qin Xinyue , Cai Jianwei , Cai Minghui , Hou Xiaolong , Yang Kaijie , Zhang Houxi
Published: September 2024

Fractional vegetation cover (FVC) is an essential metric for valuating ecosystem health and soil erosion. Traditional ground-measuring methods are inadequate for large-scale FVC monitoring, while remote sensing-based estimation approaches face issues such as spatial scale discrepancies between ground truth data and image pixels, as well as limited sample representativeness. This study proposes a method for FVC estimation integrating uncrewed aerial vehicle (UAV) and satellite imagery using machine learning (ML) models. First, we assess the vegetation extraction performance of three classification methods (OBIA-RF, threshold, and K-means) under UAV imagery. The optimal method is then selected for binary classification and aggregated to generate high-accuracy FVC reference data matching the spatial resolutions of different satellite images. Subsequently, we construct FVC estimation models using four ML algorithms (KNN, MLP, RF, and XGBoost) and utilize the SHapley Additive exPlanation (SHAP) method to assess the impact of spectral features and vegetation indices (VIs) on model predictions. Finally, the best model is used to map FVC in the study region. Our results indicate that the OBIA-RF method effectively extract vegetation information from UAV images, achieving an average precision and recall of 0.906 and 0.929, respectively. This method effectively generates high-accuracy FVC reference data. With the improvement in the spatial resolution of satellite images, the variability of FVC data decreases and spatial continuity increases. The RF model outperforms others in FVC estimation at 10 m and 20 m resolutions, with R2 values of 0.827 and 0.929, respectively. Conversely, the XGBoost model achieves the highest accuracy at a 30 m resolution, with an R2 of 0.847. This study also found that FVC was significantly related to a number of satellite image VIs (including red edge and near-infrared bands), and this correlation was enhanced in coarser resolution images. The method proposed in this study effectively addresses the shortcomings of conventional FVC estimation methods, improves the accuracy of FVC monitoring in soil erosion areas, and serves as a reference for large-scale ecological environment monitoring using UAV technology.
A Fast Sequential Similarity Detection Algorithm for Multi-Source Image Matching
Authors: Wu Quan , Yu Qida
Published: September 2024

Robust and efficient multi-source image matching remains a challenging task due to nonlinear radiometric differences between image features. This paper proposes a pixel-level matching framework for multi-source images to overcome this issue. Firstly, a novel descriptor called channel features of phase congruency (CFPC) is first derived at each control point to create a pixelwise feature representation. The proposed CFPC is not only simple to construct but is also highly efficient and somewhat insensitive to noise and intensity changes. Then, a Fast Sequential Similarity Detection Algorithm (F-SSDA) is proposed to further improve the matching efficiency. Comparative experiments are conducted by matching different types of multi-source images (e.g., Visible–SAR; LiDAR–Visible; visible–infrared). The experimental results demonstrate that the proposed method can achieve pixel-level matching accuracy with high computational efficiency.
Dual-Domain Fusion Network Based on Wavelet Frequency Decomposition and Fuzzy Spatial Constraint for Remote Sensing Image Segmentation
Authors: Wei Guangyi , Xu Jindong , Yan Weiqing , Chong Qianpeng , Xing Haihua , Ni Mengying
Published: September 2024

Semantic segmentation is crucial for a wide range of downstream applications in remote sensing, aiming to classify pixels in remote sensing images (RSIs) at the semantic level. The dramatic variations in grayscale and the stacking of categories within RSIs lead to unstable inter-class variance and exacerbate the uncertainty around category boundaries. However, existing methods typically emphasize spatial information while overlooking frequency insights, making it difficult to achieve desirable results. To address these challenges, we propose a novel dual-domain fusion network that integrates both spatial and frequency features. For grayscale variations, a multi-level wavelet frequency decomposition module (MWFD) is introduced to extract and integrate multi-level frequency features to enhance the distinctiveness between spatially similar categories. To mitigate the uncertainty of boundaries, a type-2 fuzzy spatial constraint module (T2FSC) is proposed to achieve flexible higher-order fuzzy modeling to adaptively constrain the boundary features in the spatial by constructing upper and lower membership functions. Furthermore, a dual-domain feature fusion (DFF) module bridges the semantic gap between the frequency and spatial features, effectively realizes semantic alignment and feature fusion between the dual domains, which further improves the accuracy of segmentation results. We conduct comprehensive experiments and extensive ablation studies on three well-known datasets: Vaihingen, Potsdam, and GID. In these three datasets, our method achieved 74.56%, 73.60%, and 81.01% mIoU, respectively. Quantitative and qualitative results demonstrate that the proposed method significantly outperforms state-of-the-art methods, achieving an excellent balance between segmentation accuracy and computational overhead.
SOD-YOLOv8—Enhancing YOLOv8 for Small Object Detection in Aerial Imagery and Traffic Scenes
Authors: Khalili Boshra , Smyth Andrew W.
Published: September 2024

Object detection, as a crucial aspect of computer vision, plays a vital role in traffic management, emergency response, autonomous vehicles, and smart cities. Despite the significant advancements in object detection, detecting small objects in images captured by high-altitude cameras remains challenging, due to factors such as object size, distance from the camera, varied shapes, and cluttered backgrounds. To address these challenges, we propose small object detection YOLOv8 (SOD-YOLOv8), a novel model specifically designed for scenarios involving numerous small objects. Inspired by efficient generalized feature pyramid networks (GFPNs), we enhance multi-path fusion within YOLOv8 to integrate features across different levels, preserving details from shallower layers and improving small object detection accuracy. Additionally, we introduce a fourth detection layer to effectively utilize high-resolution spatial information. The efficient multi-scale attention module (EMA) in the C2f-EMA module further enhances feature extraction by redistributing weights and prioritizing relevant features. We introduce powerful-IoU (PIoU) as a replacement for CIoU, focusing on moderate quality anchor boxes and adding a penalty based on differences between predicted and ground truth bounding box corners. This approach simplifies calculations, speeds up convergence, and enhances detection accuracy. SOD-YOLOv8 significantly improves small object detection, surpassing widely used models across various metrics, without substantially increasing the computational cost or latency compared to YOLOv8s. Specifically, it increased recall from 40.1% to 43.9%, precision from 51.2% to 53.9%, mAP0.5 from 40.6% to 45.1%, and mAP0.5:0.95 from 24% to 26.6%. Furthermore, experiments conducted in dynamic real-world traffic scenes illustrated SOD-YOLOv8’s significant enhancements across diverse environmental conditions, highlighting its reliability and effective object detection capabilities in challenging scenarios.
Feasibility of Early Assessment for Psychological Distress: HRV-Based Evaluation Using IR-UWB Radar
Authors: Lee Yuna , Lee Kounseok , Ahmed Sarfaraz , Cho Sung Ho
Published: September 2024

Mental distress-induced imbalances in autonomic nervous system activities adversely affect the electrical stability of the cardiac system, with heart rate variability (HRV) identified as a related indicator. Traditional HRV measurements use electrocardiography (ECG), but impulse radio ultra-wideband (IR-UWB) radar has shown potential in HRV measurement, although it is rarely applied to psychological studies. This study aimed to assess early high levels of mental distress using HRV indices obtained using radar through modified signal processing tailored to reduce phase noise and improve positional accuracy. We conducted 120 evaluations on 15 office workers from a software startup, with each 5 min evaluation using both radar and ECG. Visual analog scale (VAS) scores were collected to assess mental distress, with evaluations scoring 7.5 or higher classified as high-mental distress group, while the remainder formed the control group. Evaluations indicating high levels of mental distress showed significantly lower HRV compared to the control group, with radar-derived indices correlating strongly with ECG results. The radar-based analysis demonstrated a significant ability to differentiate high mental distress, supported by receiver operating characteristic (ROC) analysis. These findings suggest that IR-UWB radar could be a supportive tool for distinguishing high levels of mental stress, offering clinicians complementary diagnostic insights.