This work examines the potential of some of the Gulf Cooperation Council countries (GCC) (Saudi Arabia (KSA), the United Arab Emirates (UAE), Qatar (QA), Bahrain (BH), Oman (OM)), Yemen (YE), Iraq (IQ), and Jordan (JO) to use their abundant solar radiation to generate electricity through PV technology. The study is structured to help decision-makers access the necessary data related to the status of solar-energy infrastructure and power production in the study region. The study investigates current efforts to establish PV technology and the challenges hindering the development of this technology. These efforts and challenges are then benchmarked against their status in Australia, which has climate and landscape conditions similar to those of the countries in the study region. It was found that Australia is successfully adopting solar energy in households and industrial locations despite its historical reliance on fossil fuels for energy production. This offers a potential avenue for replicating the Australian model of PV development in the study region. This work also addresses the effect of natural and anthropogenic aerosols on the performance of the PV panels. Meanwhile, it also proposes a conceptual model to help local governments and decision-makers in adopting solar-energy projects in the study region. Additionally, a preliminary carbon-footprint analysis of avoided emissions from PV energy utilization compared to national grid intensity was performed for each country. Findings show that the countries in the study region have great potential for using solar energy to gradually replace fossil fuels and protect the environment. It is observed that more hours of daylight and clear-to-scattered cloud coverage help increase solar irradiance near the ground all year around. Dust and aerosol loadings, however, were found to greatly reduce solar irradiance over the GCC area, especially during large dust events. Despite the high potential for harvesting solar energy in the study region, only a handful of PV plants and infrastructural facilities have been established, mostly in the KSA, the UAE, and Jordan. It was found that there is a critical need to put in place regulations, policies, and near-future vision to support solar energy generation and reduce reliance on fossil fuels for electricity production. Full article

The dependence of photochemistry on excitation wavelength is not a recently observed phenomenon; nonetheless, it has, surprisingly enough, been largely ignored in the field. The reasons for this situation are not fully understood but might be related to a provisional extension of Kasha’s rule to photochemistry, or perhaps to a difficulty to justify the kind of short time-scales implied in such photochemistry, that challenges the usually held view giving predominance to fast internal conversion and vibrational relaxation. Regardless of the reasons, it is still a matter of fact that a complete and satisfactory interpretation for experimentally proven wavelength-dependent photochemistry is not yet available and the community endeavor to build a holistic understanding and a comprehensive view of the phenomenon. The present review is a non-exhaustive overview of the published data in the field, reporting on some of the most prominent features, issues, and interpretations. Full article

The purpose of this study was to determine Turkish physical education (PE) teachers’ level of technological innovation use and attitudes regarding their applications and diffusion. This study consisted of 678 Turkish PE teachers. In total, 265 (39.1%) of the PE teachers were female, and 413 (60.9%) were male. A sequential explanatory mixed-methods design was used in this study. “The Applying and Diffusing Technological Innovations Scale for Teachers” was used for data collection. The results showed that the main obstacles the PE teachers face in using technological innovations were the cost of products; security and privacy problems; the need for new versions and technical support; the lack of time; the lack of interest; difficulty in accessing technology; and the lack of understanding. Moreover, there was a significant difference in the tendency to apply and diffuse technological innovations in terms of gender, school type, and school level. We found that the “ability to use innovations” sub-dimension affects the PE teachers’ tendencies to apply and diffuse technology. As a result, we recommend providing various training programs on technological innovations to the older/longer-serving PE teachers, especially those working in public schools and secondary schools. Full article

Sesame is an important oilseed crop grown for human consumption in many countries, with a high commercial value due to its high oleic/linoleic acid ratio (O/L ratio). However, its properties may vary among different accessions. In the current study, 282 sesame accessions were evaluated to determine the effects of agronomic traits and genotypes on the O/L ratio. The O/L ratio was positively correlated with the oleic acid (C18:1), stearic acid (C18:0), and myristic acid (C14:0) concentrations, as well as the capsule zone length (CZL), capsule width (CW), and capsule length (CL), and negatively correlated with the linoleic acid (C18:2) and linolenic acid (C18:3) concentrations, the days to maturity (DTM), days to flowering (DTF), and the height of the first capsule-bearing node (HFC) (p < 0.05). In addition, the O/L ratio was affected by the FAD2 haplotype, as the Hap2 and Hap3 sesame accessions had lower O/L ratios. Therefore, we suggest that the increase and decrease in the contents of C18:1 and C18:2 are associated with the FAD2 haplotype. A total of 25 agronomic traits and fatty acid compositions were compared via statistical analysis, and accessions with a high O/L ratio were selected. The results of this study can be used as a basis for further research on the development of new sesame varieties through enhancing nutritional functionality. Full article

Over recent decades, Landsat satellite data has evolved into a highly valuable resource across diverse fields. Long-term satellite data records with integrity and consistency, such as the Landsat series, provide indispensable data for many applications. However, the malfunction of the Scan Line Corrector (SLC) on the Landsat 7 satellite in 2003 resulted in stripping in subsequent images, compromising the temporal consistency and data quality of Landsat time-series data. While various methods have been proposed to improve the quality of Landsat 7 SLC-off data, existing gap-filling methods fail to enhance the temporal resolution of reconstructed images, and spatiotemporal fusion methods encounter challenges in managing large-scale datasets. Therefore, we propose a method for reconstructing dense time series from SLC-off data. This method utilizes the Neighborhood Similar Pixel Interpolator to fill in missing values and leverages the time-series information to reconstruct high-resolution images. Taking the blue band as an example, the surface reflectance verification results show that the Mean Absolute Error (MAE) and BIAS reach minimum values of 0.0069 and 0.0014, respectively, with the Correlation Coefficient (CC) and Structural Similarity Index Metric (SSIM) reaching 0.93 and 0.94. The proposed method exhibits advantages in repairing SLC-off data and reconstructing dense time-series data, enabling enhanced remote sensing applications and reliable Earth’s surface reflectance data reconstruction. Full article

To characterize transforming growth factor-β (TGF-β) isoform (TGF-β1~3)-b’s biological effects on the human retinal pigment epithelium (RPE) under normoxia and hypoxia conditions, ARPE19 cells cultured by 2D (two-dimensional) and 3D (three-dimensional) conditions were subjected to various analyses, including (1) an analysis of barrier function by trans-epithelial electrical resistance (TEER) measurements; (2) qPCR analysis of major ECM molecules including collagen 1 (COL1), COL4, and COL6; α-smooth muscle actin (αSMA); hypoxia-inducible factor 1α (HIF1α); and peroxisome proliferator-activated receptor-gamma coactivator (PGC1α), a master regulator for mitochondrial respiration;, tight junction-related molecules, Zonula occludens-1 (ZO1) and E-cadherin; and vascular endothelial growth factor (VEGF); (3) physical property measurements of 3D spheroids; and (4) cellular metabolic analysis. Diverse effects among TGF-β isoforms were observed, and those effects were also different between normoxia and hypoxia conditions: (1) TGF-β1 and TGF-β3 caused a marked increase in TEER values, and TGF-β2 caused a substantial increase in TEER values under normoxia conditions and hypoxia conditions, respectively; (2) the results of qPCR analysis supported data obtained by TEER; (3) 3D spheroid sizes were decreased by TGF-β isoforms, among which TGF-β1 had the most potent effect under both oxygen conditions; (4) 3D spheroid stiffness was increased by TGF-β2 and TGF-β3 or by TGF-β1 and TGF-β3 under normoxia conditions and hypoxia conditions, respectively; and (5) the TGF-β isoform altered mitochondrial and glycolytic functions differently under oxygen conditions and/or culture conditions. These collective findings indicate that the TGF-β-induced biological effects of 2D and 3D cultures of ARPE19 cells were substantially diverse depending on the three TGF-β isoforms and oxygen levels, suggesting that pathological conditions including epithelial–mesenchymal transition (EMT) of the RPE may be exclusively modulated by both factors. Full article

This study introduces an advanced ensemble methodology employing lightweight neural network models for identifying severe convective clouds from FY-4B geostationary meteorological satellite imagery. We have constructed a FY-4B based severe convective cloud dataset by a combination of algorithms and expert judgment. Through the ablation study of a model ensembling combination of multiple specialized lightweight architectures—ENet, ESPNet, Fast-SCNN, ICNet, and MobileNetV2—the optimal EFNet (ENet- and Fast-SCNN-based network) not only achieves real-time processing capabilities but also ensures high accuracy in severe weather detection. EFNet consistently outperformed traditional, heavier models across several key performance indicators: achieving an accuracy of 0.9941, precision of 0.9391, recall of 0.9201, F1 score of 0.9295, and computing time of 18.65 s over the test dataset of 300 images (~0.06 s per 512 × 512 pic). ENet shows high precision but misses subtle clouds, while Fast-SCNN has high sensitivity but lower precision, leading to misclassifications. EFNet’s ensemble approach balances these traits, enhancing overall predictive accuracy. The ensemble method of lightweight models effectively aggregates the diverse strengths of the individual models, optimizing both speed and predictive performance. Full article

Due to the advantages of coastal areas in the fields of agriculture, transport, and fishing, increasingly more people are moving to these areas. Sea level information is important for these people to survive after extreme sea level events. With the recent improvements in computing and storage capacities, image analysis as a new measuring method is being rapidly developed and widely applied. In this paper, a multi-camera-based sea level height measuring system was built along Japan’s coast and a deep-learning-based stereo matching method has been proposed for this system to complete 3D measurements. In this system, cameras are set with long base distances to ensure the long-distance monitoring system’s precision, which causes a huge difference between the fields of view of the left and right cameras. Since most common network structures complete stereo matching by depth-wise cross-correlation between left and right images, they rely too much on the high-quality rectification of two images and fail on our long-distance sea surface images. We established a feature detection and matching network to realize sea wave extraction and sparse stereo matching for the system. Based on our previous result using the traditional method, the initial disparity was computed to reduce the search range of stereo matching. A training set with 785 pairs of sea surface images and 10,172 pairs of well-matched sea wave images was constructed to supervise the network. The experimental results verified that the proposed method can realize sea wave extraction and mask generation. It can also realize sparse matching of sea surface images regardless of poor rectification. Full article

The synergistic effect of sodium dodecyl benzene sulfonate (SDBS) on the flotation separation of magnesite and dolomite using sodium oleate (NaOL) as a collector has been studied through flotation experiments, zeta potential measurements, contact angle measurements, Fourier transformation infrared spectroscopy analysis (FT-IR), particle size measurements and transmittance measurements. The flotation experiments show that when the synergist, SDBS, is added to the collector, NaOL, the collecting ability and ion resistance of NaOL can be improved so that the flotation separation of magnesite and dolomite can be realized. Zeta potential measurements, contact angle measurements and FT-IR analysis indicate that SDBS and NaOL can co-adsorb on the surface of magnesite. Particle size measurements and transmittance measurements show that SDBS can also improve the dispersion and solubility of NaOL in an aqueous solution, so as to achieve a synergistic effect. Full article

The progress in hyperspectral image (HSI) classification owes much to the integration of various deep learning techniques. However, the inherent 3D cube structure of HSIs presents a unique challenge, necessitating an innovative approach for the efficient utilization of spectral data in classification tasks. This research focuses on HSI classification through the adoption of a recently validated deep-learning methodology. Challenges in HSI classification encompass issues related to dimensionality, data redundancy, and computational expenses, with CNN-based methods prevailing due to architectural limitations. In response to these challenges, we introduce a groundbreaking model known as “Crossover Dimensionality Reduction and Multi-branch Deep Learning” (CMD) for hyperspectral image classification. The CMD model employs a multi-branch deep learning architecture incorporating Factor Analysis and MNF for crossover feature extraction, with the selection of optimal features from each technique. Experimental findings underscore the CMD model’s superiority over existing methods, emphasizing its potential to enhance HSI classification outcomes. Notably, the CMD model exhibits exceptional performance on benchmark datasets such as Salinas Scene (SC), Pavia University (PU), Kennedy Space Center (KSC), and Indian Pines (IP), achieving impressive overall accuracy rates of 99.35% and 99.18% using only 5% of the training data. Full article

Several cases reported in the literature have confirmed the link between pulmonary aspergillosis and various malignant diseases. Furthermore, it has been observed that the correlation between carcinoid tumor and lung adenocarcinoma is quite uncommon. The etiopathogenic mechanisms underlying these correlations remain poorly defined. We present the case of a patient with three of these diseases: a lung adenocarcinoma with a lepidic pattern, a typical carcinoid, and pulmonary aspergillosis. An additional noteworthy aspect of this case pertains to the timely detection of both lung malignancies. Thus, the necessity for further investigation to ascertain the pathogenic connection among the three diseases is underscored. The ultimate objective is to enhance the prognosis of individuals diagnosed with lung cancer, which is a prevailing malignant disease on a global scale. Full article

Various vaccine platforms have been approved for broad use to prevent the transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. However, these vaccines exhibit distinct differences in immunogenicity and efficacy, which decline after vaccination and are further exacerbated by the emergence of virus variants and mutants. This study reports the immunization outcomes against the SARS-CoV-2 virus by assessing the immune responses and safety of different SARS-CoV-2 vaccines co-administered in BALB/c mice. Vaccine combinations comprising mRNA/adenovirus26-vector, mRNA/inactivated, adenovirus26-vector/inactivated, and mRNA/adenovirus26-vector/inactivated vaccines were prepared in optimized doses, and their activities upon immunization evaluated in comparison with individual mRNA, adenovirus26-vectored, and inactivated vaccines. Fourteen- and 28-days post-immunization, we measured spike-specific IgG response using Enzyme-Linked Immunosorbent Assay (ELISA), cytokine expression profiles through Quantitative real-time polymerase chain reaction (RT-PCR), and evaluated safety through histopathological examination. The mRNA/Vector/Inactivated group exhibited slightly higher anti-spike IgG levels, albeit not statistically significant (p > 0.132). Importantly, this regimen induced elevated IL-6 and IFN-γ mRNA expression levels (p < 0.0001) compared to immunization with individual vaccines. In summary, this study demonstrated that co-administering the mRNA/adenovirus26 vector/inactivated SARS-CoV-2 vaccines improved spike-specific IgG response, triggered significantly enhanced IL-6 and IFN-γ mRNA expression levels, and proved safe in mice. Full article

With the development of computer vision and Unmanned Aerial Vehicles (UAVs) technology, visual object tracking has become an indispensable core technology for UAVs, and it has been widely used in both civil and military fields. Visual object tracking from the UAV perspective experiences interference from various complex conditions such as background clutter, occlusion, and being out of view, which can easily lead to tracking drift. Once tracking drift occurs, it will lead to almost complete failure of the subsequent tracking. Currently, few trackers have been designed to solve the tracking drift problem. Thus, this paper proposes a tracking algorithm based on motion prediction and block search to address the tracking drift problem caused by various complex conditions. Specifically, when the tracker experiences tracking drift, we first use a Kalman filter to predict the motion state of the target, and then use a block search module to relocate the target. In addition, to improve the tracker’s ability to adapt to changes in the target’s appearance and the environment, we propose a dynamic template updating network (DTUN) that allows the tracker to make appropriate template decisions based on various tracking conditions. We also introduce three tracking evaluation metrics: namely, average peak correlation energy, size change ratio, and tracking score. They serve as prior information for tracking status identification in the DTUN and the block prediction module. Extensive experiments and comparisons with many competitive algorithms on five aerial benchmarks, UAV20L, UAV123, UAVDT, DTB70, and VisDrone2018-SOT, demonstrate that our method achieves significant performance improvements. Especially in UAV20L long-term tracking, our method outperforms the baseline in terms of success rate and accuracy by 19.1% and 20.8%, respectively. This demonstrates the superior performance of our method in the task of long-term tracking from the UAV perspective, and we achieve a real-time speed of 43 FPS. Full article

The low rehydration properties of commercial soy protein powder (SPI), a major plant−based food ingredient, have limited the development of plant−based foods. The present study proposes a treatment of soy lecithin modification combined with Alcalase hydrolysis to improve the rehydration of soy protein powder, as well as other processing properties (emulsification, viscosity). The results show that the soy protein–soy lecithin complex powder, which is hydrolyzed for 30 min (SPH–SL−30), has the smallest particle size, the smallest zeta potential, the highest surface hydrophobicity, and a uniform microstructure. In addition, the value of the ratio of the α−helical structure/β−folded structure was the smallest in the SPH–SL−30. After measuring the rehydration properties, emulsification properties, and viscosity, it was found that the SPH–SL−30 has the shortest wetting time of 3.04 min, the shortest dispersion time of 12.29 s, the highest solubility of 93.17%, the highest emulsifying activity of 32.42 m²/g, the highest emulsifying stability of 98.33 min, and the lowest viscosity of 0.98 pa.s. This indicates that the treatment of soy lecithin modification combined with Alcalase hydrolysis destroys the structure of soy protein, changes its physicochemical properties, and improves its functional properties. In this study, soy protein was modified by the treatment of soy lecithin modification combined with Alcalase hydrolysis to improve the processing characteristics of soy protein powders and to provide a theoretical basis for its high−value utilization in the plant−based food field. Full article

This paper presents a historical overview of conceptions about the Sun in Western astronomical and cosmological traditions before the advent of spectroscopy and astrophysics. Rather than studying general cultural ideas, we focus on the concepts developed by astronomers or by natural philosophers impacting astronomy. The ideas we investigate, from the works of Plato and Aristotle to William Herschel and his contemporaries, do not line up into a continuous and integrated narrative, since the nature of the Sun was not a genuine scientific topic before the nineteenth century. However, the question recurringly arose as embedded in cosmological and physical contexts. By outlining this heterogeneous story that spreads from transcendence to materiality, from metaphysics to physics, from divinity to solar inhabitants, we receive insight into some major themes and trends both in the general development of astronomical and cosmological thought and in the prehistory of modern solar science. Full article

Muscular dystrophies present diagnostic challenges, requiring accurate classification for effective diagnosis and treatment. This study investigates the efficacy of deep learning methodologies in classifying these disorders using skeletal muscle MRI scans. Specifically, we assess the performance of the Swin Transformer (SwinT) architecture against traditional convolutional neural networks (CNNs) in distinguishing between healthy individuals, Becker muscular dystrophy (BMD), and limb–girdle muscular Dystrophy type 2 (LGMD2) patients. Moreover, 3T MRI scans from a retrospective dataset of 75 scans (from 54 subjects) were utilized, with multiparametric protocols capturing various MRI contrasts, including T1-weighted and Dixon sequences. The dataset included 17 scans from healthy volunteers, 27 from BMD patients, and 31 from LGMD2 patients. SwinT and CNNs were trained and validated using a subset of the dataset, with the performance evaluated based on accuracy and F-score. Results indicate the superior accuracy of SwinT (0.96), particularly when employing fat fraction (FF) images as input; it served as a valuable parameter for enhancing classification accuracy. Despite limitations, including a modest cohort size, this study provides valuable insights into the application of AI-driven approaches for precise neuromuscular disorder classification, with potential implications for improving patient care. Full article

In this paper, a new methodology is developed for modeling and analyzing a full-duplex UAV-assisted relay system to facilitate solving the problems of UAV energy constraints and the vulnerability of UAVs to eavesdropping in the air. Combining simultaneous wireless information and power transfer (SWIPT) technology, we model the downlink UAV eavesdropping channel and propose a secure transmission protocol for a full-duplex UAV-assisted relay system. Using this transmission protocol, we analyze and derive the connectivity and security of the entire communication link, including connection probability and lower bounds on secrecy outage probability. A key intermediate step in our analysis is to derive the signal-to-digital noise ratio of the destination and eavesdropping nodes of the full-duplex UAV relay link. The analyses show that the power allocation factor is a trade-off between system connectivity and security, while greater eavesdropping interference needs to be sacrificed for an equal magnitude of security performance improvement under high security demand conditions. Full article

Supercritical carbon dioxide (CO₂) has extremely important applications in the extraction of unconventional oil and gas, especially in fracturing and enhanced oil recovery (EOR) technologies. It can not only relieve water resource wastage and environmental pollution caused by traditional mining methods, but also effectively store CO₂ and mitigate the greenhouse effect. However, the low viscosity nature of supercritical CO₂ gives rise to challenges such as viscosity fingering, limited sand–carrying capacity, high filtration loss, low oil and gas recovery efficiency, and potential rock adsorption. To overcome these challenges, low–rock–adsorption thickeners are required to enhance the viscosity of supercritical CO₂. Through research into the literature, this article reviews the solubility and thickening characteristics of four types of polymer thickeners, namely surfactants, hydrocarbons, fluorinated polymers, and silicone polymers in supercritical CO₂. The thickening mechanisms of polymer thickeners were also analyzed, including intermolecular interactions, LA–LB interactions, hydrogen bonding, and functionalized polymers, and so on. Full article

Providing user confidence in mobile government services (MGS) is essential for the success of mobile government. This study aimed to test the moderating role of techno-skepticism in the impact of crisis management on mobile government. Due to several inadequacies, citizens seem to respond negatively to the use of certain public technological services, leading them to develop a perspective of techno-skepticism. This issue has been cited in numerous scholarly studies as a critical component in the effective implementation of technological innovations. The effectiveness of digital technology in the procurement of public services is highly dependent on the perceptions and behaviors of its users. In this context, this study measured the attitudes of the participants and the connections between techno-skepticism, mobile government use, and crisis management among Northern Cyprus residents over 18 years old. The study employed a quantitative approach. A five-point Likert scale was used to collect data by modifying the survey questions to fit the scope of the study. The study participants were selected using the random sampling method to acquire data from a total of 402 citizens. The study findings revealed that techno-skepticism mediates the impact of crisis management on mobile government. As a result, techno-skepticism is a critical and decisive factor in citizens’ mobile government use, affecting its utilization frequency. Techno-skepticism was also found to play a vital role in mobile government use. The current study represents a pioneering effort in testing the moderating role of techno-skepticism in the impact of crisis management on mobile government. It also provides various contributions to theory and practice, particularly in the fields of mobile government and the use of digital technologies. Full article

The impact of climate on construction site safety varies significantly depending on subcontractor types due to the diverse nature of workplaces and work methods. This study introduces a novel approach by categorizing construction work according to subcontractor types and assessing accident risk probabilistically through the Physiologically Equivalent Temperature (PET), an outdoor thermal comfort index. Additionally, a Hidden Markov Model (HMM)-based clustering methodology was proposed to classify new groups using PET and accident probability. This study proceeded in the following sequence: (i) collection and classification of data, (ii) PET calculation, (iii) calculation of accident probability, and (iv) clustering and Pearson correlation coefficient analysis. As a result of clustering, each group was classified according to the workplace. Groups 2 and 3 demonstrated a strong positive correlation between accident probability and PET, with correlation coefficients of 0.837 and 0.772, while Group 1 exhibited a moderately positive correlation of 0.474. This study quantitatively evaluated the impact of climate on workers for each subcontractor type using PET, an outdoor thermal comfort index for construction work, and accident probability, resulting in the identification of new groups. The findings of this study may serve as novel benchmarks for safety management in construction worker safety based on PET. Full article

Fluctuations are omnipresent; they exist in any matter, due either to its quantum nature or to its nonzero temperature. In the current review, we briefly cover the quantum electrodynamic Casimir (QED) force as well as the critical Casimir (CC) and Helmholtz (HF) forces. In the QED case, the medium is usually a vacuum and the massless excitations are photons, while in the CC and HF cases the medium is usually a critical or correlated fluid and the fluctuations of the order parameter are the cause of the force between the macroscopic or mesoscopic bodies immersed in it. We discuss the importance of the presented results for nanotechnology, especially for devising and assembling micro- or nano-scale systems. Several important problems for nanotechnology following from the currently available experimental findings are spelled out, and possible strategies for overcoming them are sketched. Regarding the example of HF, we explicitly demonstrate that when a given integral quantity characterizing the fluid is conserved, it has an essential influence on the behavior of the corresponding fluctuation-induced force. Full article

In Xingxue cushu, Aleni devotes himself to elucidating Aristotle’s theory of perception as presented in De Anima and Parva Naturalia. The challenge in this endeavor lies in understanding the essence of Aristotle’s perception, with physicalism and spiritualism holding opposite positions. To reconcile this contradiction, some scholars approach it from the perspective of dualism and the impurity principle. Nevertheless, these interpretations fail to resolve the inherent dilemma of perception. This article employs the pattern of combination and separation to propose that Aleni’s interpretation of this dilemma is effective and clarifies the controversy. Perception encompasses both psychological and physical dimensions, and the two are based on each other in the process of actualization. Nonetheless, psychological and physical activities are separated in the definition. Influenced by Confucianism, Aleni associates human perception with morality, further emphasizing the necessity of definitional separation. Full article