Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Bidirectional High Gain DC-DC Converter with Active Switched Inductor and Wide Voltage Conversion Ratio

Energy storage devices are indispensable for ensuring voltage and frequency stability in renewable energy sources such as solar and wind. Distributed generation systems necessitate bidirectional DC-DC converters to facilitate charge and discharge operations in accordance with operational requirements. In this paper, we introduce a new bidirectional DC-DC converter tailored to achieve substantial voltage gain while minimizing switch stress and maintaining a minimal component count. The proposed converter operates in buck mode for one power flow direction and boost mode for the other, ensuring continuous input and output current and reduced charging/discharging ripple. Comprehensive details regarding the derivation, operational principles, and meticulous steady-state analysis of the proposed converter are presented in this paper. Furthermore, a dynamic model of the converter is provided, and the design of closed-loop controllers for current control modes is outlined. We present extensive analysis and simulation results to illustrate the efficacy and performance of this novel topology. In summary, this converter offers a promising solution for achieving high-efficiency energy transfer with significant voltage gain, making it suitable for a wide array of applications.
Inductive Low-cost System to Measure the Volume Variation of Prismatic Lithium-ion Cells

Battery use is continuously on the rise for several applications as proven by the rapid growth of electric vehicles market. The development of more accurate battery control and estimation algorithms is an essential requirement to enhance battery performance. Sensor fusion techniques promise to improve control and estimation algorithms by combining the currently used electric and thermal measured data with physical and chemical ones. In particular, the cell volume variation appears to be connected to both State of Charge and State of Health. In this work, an inductive sensor, based on eddy currents, is used to develop a low-cost system to measure the volume variation of prismatic lithium-ion cells. The developed system consists of a cell holder structure, similar to the one used in commercial batteries, equipped with eddy current sensors. The system is applied to both fresh and aged cells. The obtained results prove that the proposed measurement system is able to track the cell expansions due to both the thermal and State of Charge variations. Furthermore, the volume variations found are comparable to literature experiments, in which expensive laboratory equipment is used.
Medical Metaverse: A New Virtual Health Experience

Ahstract- This work examines the impact of the medical metaverse on traditional medicine and the integration of various technologies that have greatly enhanced its capabilities. Technologies such as artificial intelligence (AI), blockchain, Internet of Things (IoT), augmented reality (AR), virtual reality (VR), 5G, big data, natural language processing, and digital twins have facilitated virtual healthcare delivery, allowing clinicians to diagnose patients regardless of distance and receive real-time data. The integration of these technologies has also improved healthcare outcomes and created new healthcare experiences. This paper highlights how the adoption of these technologies has improved healthcare by enhancing patient experiences and outcomes, especially in disease management and specialized care settings. However, the use of the medical metaverse is not without challenges, and this work offers solutions to address them. Despite the potential issues, the medical metaverse offers a new way of delivering healthcare services. Further development and optimization are necessary to realize the full potential of the medical metaverse, but it is a promising and exciting area of healthcare that is worth exploring.
AttentionFractalCovNet Architecture for Breast Ultrasound Image Segmentation

Tumor in the breast is a significant cause of unhealthiness among women. It is primarily the malignant-natured lesions that are a big reason for death via cancer among females. Segmentation of the tumor is complex due to the hazy boundaries and non-identical shapes and sizes. In this paper, an attention-based architecture, called AttentionFractalCovNet(AttFCN) architecture is proposed for the accurate and automatic segmentation of tumors. It takes inspiration from FractalCovNet architecture that forms a W-shape rather than the U-shape of the UNet architecture. Convolution blocks along with Attention Gates(AG) in the second decoding layer are used for achieving better segmentation results. Breast Ultrasound (BUS) images are used as input to segment out the lesions. Various matrices like Accuracy, MSE, Dice Coefficient(DC), Recall, Intersection over Union(IoU), Precision, and F1 Score(F1) were calculated for all the implemented architectures. It achieves higher DC and IoU values as compared to other architectures like SegNet, UNet, Re-sUNet, AttentionUNet(AU), and FractalCovNet(FracCN). Thus, the model is more suitable for the segmentation of tumors and can give better results than the existing architectures mentioned above.
Spatial Econometrics From Cross Sectional Data To Spatial Panels

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Comparison of spatial interpolation techniques to generate high‐resolution climate surfaces for Nigeria

Climate datagaps are a major challenge for understanding the impacts of climate change on ecosystems, particularly in highly climate vulnerable countries such as Nigeria. The generation of gridded climate data sets in the form of interpolated surfaces may help to fill climate datagaps and in turns enable climate change impact assessments. This article generates climate surfaces of monthly total precipitation and minimum and maximum temperatures for Nigeria at 0.001° spatial resolution by comparing two spatial interpolation techniques, i.e. kriging with external drifts and thin plate splines. Climate data from 43 meteorological stations covering the period of 1960–2012 were used to generate climate surfaces fitting the longitude, latitude, elevation and distance to coastline of the stations as independent variables. Three model error statistics, i.e. root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE) and index of agreement (d), were used to evaluate and compare the performances of interpolation techniques. The second‐order and third‐order partial thin plate splines were identified as the optimal models for generating precipitation, and minimum and maximum temperatures surfaces, respectively. The best‐fit surfaces yielded an average RMSE, NSE and d of 14.98, 0.87 and 0.97 for precipitation, 0.42, 0.91 and 0.98 for minimum temperature and 0.52, 0.89 and 0.97 for maximum temperature. Our high‐resolution climate surfaces are freely available from an online repository and widely applicable for climate change analysis as well as for biological, forestry and agricultural studies in Nigeria.
A Cordoned Urn burial with faience from 102 Findhorn, Moray

Report on the discovery of a large Cordoned Urn containing the cremated remains of an adult female and a neonate or foetal infant. The urn also contained twenty-two mostly fragmentary segmented beads and one star-shaped bead, all faience. The urn had been inverted in a pit and pyre debris placed over the upper fill of the pit. This deposit contained a further two faience beads, one star-shaped and incomplete, the other quoit-shaped, and a small chunk of flint. The urn and beads are similar to those found on Culbin Sands nearby during the nineteenth century. Charcoal from the pyre debris was radiocarbon dated to c.3410 BP.
Evaluation of the influence of non-conventional sources of emissions on ambient air pollutant concentrations in north Texas

Emissions of air pollutants from non-conventional sources have been on the rise in the North Texas area over the past decade. These include primary pollutants such as volatile organic compound (VOC) and oxides of nitrogen (NOx) which also act as precursors in the formation of ozone. Most of these have been attributed to a significant increase in oil and gas production activities since 2000 within the Barnett Shale region adjacent to the Dallas-Fort Worth metroplex region. In this study, air quality concentrations measured at the Denton Airport and Dallas Hinton monitoring sites operated by the Texas Commission on Environmental Quality (TCEQ) were evaluated. VOC concentration data from canister-based sampling along with continuous measurement of oxides of nitrogen (NOx), ozone (O3), particulate matter (PM2.5), and meteorological conditions at these two sites spanning from 2000 through 2014 were employed in this study. The Dallas site is located within the urban core of one of the fastest growing cities in the United States, while the Denton site is an exurban site with rural characteristics to it. The Denton Airport site was influenced by natural gas pads surrounding it while there are very few natural gas production facilities within close proximity to the Dallas Hinton site. As of 2013, there were 1362 gas pads within a 10 mile radius to the Denton Airport site but there were only 2 within a 10 mile radius to Dallas Hinton site. The Dallas site displayed higher concentrations of NOx and much lower concentrations of VOC than the Denton site. Extremely high levels of VOC measured at the Denton site corresponded with the increase in oil and gas production activities in close proximity to the monitoring site. Ethane and propane are two major contributors to the measured VOC concentration, suggesting the influence of fugitive emissions of natural gas. In Dallas, the mean and maximum values of ozone had decreased since 2000 by about 2% and 25%, respectively. Similarly NOx decreased by 50% and 18% in the mean and maximum values. However, the mean VOC value showed a 21% decrease while the maximum value increased by about 46%. In Denton, the change in percentage of ozone and NOx were similar to Dallas but the mean VOC concentration increased by about 620% while the max value increased 1960%. Source apportionment analysis confirmed the findings by identifying the production of natural gas to be the primary source of VOC emissions in Denton, while traffic sources were more influential near the Dallas site. In light of the recent proposal by EPA to revise the ozone standard, the influence of these new unconventional sources should be further evaluated.
Two-Stage Domain Adaptation Based on Image and Feature Levels for Cloud Detection in Cross-Spatiotemporal Domain

Cloud detection in high-resolution remote sensing images (HRSIs) is widely applied to cross-spatiotemporal domains with various scenarios change. However, cloud detection semantic segmentation models based on limited samples cannot ensure the consistency of data distribution between the source domain (SD) and the target domain (TD), resulting in a decrease in cross-domain segmentation accuracy and robust ability. Therefore, this article proposed a two-stage domain adaptation based on the image and feature levels (TDAIF) cloud detection framework. TDAIF designs a pseudo-TD data generator (PTDDG) at the image level to fuse the SD foreground and TD background information effectively, assisting the model in mining invariant semantic knowledge of the TD. Then, a domain discriminator and self-ensembling joint (DDSEJ) framework is explored at the feature level to implicitly handle the alignment of global features and the optimization of decision boundaries-local features. TDAIF ultimately weakens the impact of image radiation diversity and scale divergence and improves the adaptive processing capabilities for cross-spatiotemporal data. Horizontal and internal comparative experiments on TDAIF were conducted on three domain transfer data. Experimental results show that TDAIF dramatically reduces the network accuracy loss in cross-domain. Compared with CycleGAN and AdaptSegNet, the IoU is improved by about 30%. TDAIF performs better than state-of-the-art computational visual domain adaptation (DA) methods, indicating that hierarchical data alignment from the image to the feature level is very effective.
Two-Stage Progressive Underwater Image Enhancement

Underwater image enhancement (UIE) is a challenging problem involving various aspects of image degradation, such as color scattering, low contrast, and haziness. In this study, we present a method named two-stage progressive enhancement network (TPENet) to address these issues. We outline the challenges faced in UIE and introduce how TPENet tackles them. TPENet adopts a two-stage network architecture that combines the extensive context learning capabilities of encoders–decoders and the spatial-detail preservation capabilities of the original resolution network. In the first stage, we design a densely fused encoder–decoder subnetwork that focuses on addressing color distortion and low contrast issues. In the second stage, we introduce an original resolution subnetwork (ORSNet) and tackle the haziness problem in underwater images through an image dehazing auxiliary task. To highlight local features and pass them for further enhancement in the next stage, we also introduce a multicolor space supervised attention module. Through extensive experimental results, we validate the outstanding performance, generalization ability, and positive impact on other visual tasks of the proposed method. Additionally, we conduct ablation studies to demonstrate the contributions of key components.
Morphological evolution of the debris cover on Khumbu Glacier, Nepal, between 1978 and 1995

The debris-covered area of Khumbu Glacier was topographically mapped in 1995 and the morphological evolution was determined by comparing the 1995 maps with those made in 1978. There had been significant changes in the surface morphology during this 17-year period: the area with a rough uneven surface with large relative relief had extended both upglacier and downglacier, and area of high ablation had increased. The glacier shrinkage in the ablation area where there was a thick debris cover was associated with an increase in surface relief and relative height, mainly caused by rapid ablation on exposed ice and lateral erosion at streams and ponds.
Input Transformation for Pre-Trained-Model-Based Cross-Language Code Search

Cross-language code-to-code search has great po-tential to boost software development and software mainte-nance. However, performing this task is nontrivial since it requires to accurately understand the semantics of code written in different programming languages. To address this challenge, a natural idea is to leverage the power of pretrained language models trained on diverse languages and have shown great potential in producing high-quality representations for code across different languages. A dominating way of utilizing pretrained models is to directly use code token sequences as the inputs, due to their Transformer-based architectures. Nonetheless, beyond the lexical information, code snippets inherently contain rich semantic information, which may not be adequately captured through the token sequence. To overcome this limitation, we propose an input transformation approach that, given a code snippet, can generate a sequence with semantic information as the input to the pretrained model, which enables us to effectively obtain the representations of the code. Our key insight is that code snippets in different languages that implement the identical functionality, although may differ significantly with respect to the token sequences or the syntactic structures, could share certain similarities regarding to their Program Dependency Graphs (PDGs). Therefore, instead of directly using the token sequence, we propose to first build the semantic graph that can model the semantics of code in different languages based on the data flow and control flow information by optimizing the PDGs. After that, a graph to sequence transformation module is designed and the final transformation result can be obtained. Finally, the contrastive learning is exploited to fine-tune the model. Our large-scale evaluation results show that our method can achieve promising effectiveness because it consistently outperforms the state-of-the-art C4 approach by at least 6% with respect to the Mean Reciprocal Rank (MRR) value, under six different settings.
Distribution and Utilization of Vitamin E in Different Organs of Wild Bats from Different Food Groups

In this work, we examined the levels of vitamin E in the heart, liver, and kidneys of four species of adult male bats with distinct feeding habits. Our results indicate consistent vitamin E levels in the heart across all four bat species, suggesting the presence of regulatory mechanisms. Additionally, the liver displayed notably higher vitamin E levels in nectarivorous and frugivorous bats, while hematophagous bats exhibited lower levels, indicating a link between dietary intake and liver vitamin E levels. Furthermore, correlation analysis provided additional insights into the relationships between vitamin E and key antioxidant parameters in the livers of bats. On the other hand, no correlation was observed between vitamin E and key antioxidant parameters in the heart. Intriguingly, vitamin E was not detected in the kidneys, likely due to physiological factors and the prioritization of vitamin E mobilization in the heart, where it serves critical physiological functions. This unexpected absence of vitamin E in bat kidneys highlights the unique metabolic demands and prioritization of vitamin mobilization in wild animals like bats, compared to conventional animal models. These findings provide insight into the intricate distribution and utilization of vitamin E in bats, emphasizing the influence of dietary intake and metabolic adaptations on vitamin E levels in different organs.
North Atlantic hotspot-ridge interaction near Jan Mayen Island

At slow to ultraslow spreading rates along mid-ocean ridges, thicker lithosphere typically impedes magma generation and tectonic extension can play a more significant role in crustal production (Dick et al., 2003). The source of anomalously high magma supply thus remains unclear along ridges with ultraslow-spreading rates adjacent to Jan Mayen Island in the North Atlantic (Neumann and Schilling, 1984; Mertz et al., 1991; Haase et al., 1996; Schilling et al., 1999; Tronnes et al., 1999; Haase et al., 2003; Mertz et al., 2004; Blichert-Toft et al., 2005; Debaille et al., 2009). Here we show that Jan Mayen volcanism is likely the surface expression of a small mantle plume, which exerts significant influence on nearby mid-ocean ridge tectonics and volcanism. Progressive dilution of Jan Mayen geochemical signatures with distance from the hotspot is observed in lava samples from the immediately adjacent Mohns Ridge, and morphological indicators of enhanced magma supply are observed on both the Mohns Ridge and the nearby Kolbeinsey Ridge, which additionally locally overlies a highly heterogeneous, eclogite-bearing mantle source. These morphological and geochemical influences underscore the importance of heterogeneous mantle sources in modifying melt supply and thus the local expression of tectonic boundaries.
A reanalysis of Bernissartia fagesii, with comments on its Phylogenetic position and its bearing on the origin and diagnosis of the Eusuchia

The precise affinities of the small Early Cretaceous crocodylomorph Bernissartia fagesii DOLLO, 1883 have been unclear. We review the anatomy of B. fagesii and present evidence that it is closely related to the Eusuchia, as was originally suggested by DOLLO but contrary to the hypothesis of BUFFETAUT. Revised diagnoses of B. fagesii and of the Eusuchia are presented, and the implications of Bernissartia fagesii as an outgroup to the Eusuchia are discussed with regard to phylogenetic relationships among living crocodylians
The Genome of Plasmodium gonderi: Insights into the Evolution of Human Malaria Parasites

Abstract Plasmodium species causing malaria in humans are not monophyletic, sharing common ancestors with nonhuman primate parasites. Plasmodium gonderi is one of the few known Plasmodium species infecting African old-world monkeys that are not found in apes. This study reports a de novo assembled P. gonderi genome with complete chromosomes. The P. gonderi genome shares codon usage, syntenic blocks, and other characteristics with the human parasites Plasmodium ovale s.l. and Plasmodium malariae, also of African origin, and the human parasite Plasmodium vivax and species found in nonhuman primates from Southeast Asia. Using phylogenetically aware methods, newly identified syntenic blocks were found enriched with conserved metabolic genes. Regions outside those blocks harbored genes encoding proteins involved in the vertebrate host-Plasmodium relationship undergoing faster evolution. Such genome architecture may have facilitated colonizing vertebrate hosts. Phylogenomic analyses estimated the common ancestor between P. vivax and an African ape parasite P. vivax-like, within the Asian nonhuman primates parasites clade. Time estimates incorporating P. gonderi placed the P. vivax and P. vivax-like common ancestor in the late Pleistocene, a time of active migration of hominids between Africa and Asia. Thus, phylogenomic and time-tree analyses are consistent with an Asian origin for P. vivax and an introduction of P. vivax-like into Africa. Unlike other studies, time estimates for the clade with Plasmodium falciparum, the most lethal human malaria parasite, coincide with their host species radiation, African hominids. Overall, the newly assembled genome presented here has the quality to support comparative genomic investigations in Plasmodium.
A border regions typology in the enlarged European Union

Abstract The processes of European Union (EU) integration and enlargement have produced a new regional socioeconomic map in Europe. Border regions, in particular, have been put in a state of flux. The re‐allocation of activities, opportunities and threats is changing their socioeconomic role and significance. Thus, border regions have become an issue of great importance during the last fifteen years in both the areas of scientific research and policy making. The overall picture of the actual dynamics occurring at the border regions, however, when economic barriers have been abolished, remains rather unclear. The absence of an appropriate methodological framework for the study of the impact of EU integration and enlargement dynamics on border regions is evident. The paper proposes a typology for the EU NUTS III border regions, interpreting the socioeconomic dynamics occurring within the enlarged EU space. Primary and secondary data, incorporating quantitative and qualitative determinants for border regions, were elaborated with integrated factor and fuzzy clustering analysis techniques. The proposed border regions typology provides a framework to assess the relative position of each EU border region in the EU space.