esa-sceva/satcom-chunk-collection huggingface dataset:
# Prediction of PM2.5 Concentration on the Basis of Multitemporal Spatial Scale Fusion
## 3 Results
### Determination of Network Structure  
Different scales of characteristics can be extracted from the structure of many branches. The variance of characteristics gradually diminishes as the number of model branches rises, which lowers prediction precision. In order to identify the network topology, a network comparison experiment with several branches is created and its RMSE and MAE are compared. Our method is executed five times independently with identical settings to minimize the influence of network initialization on the prediction outcomes, and the final result is calculated based on the average value. The prediction accuracy of time series models usually decreases with the increase of time. We observe the prediction results of the model for the next day, three days, and seven days to verify its performance in short-term, medium-term, and long-term prediction tasks.  
In Table 2, the RMSE and MAE values for predicting PM2.5 levels one, three, and seven days ahead are displayed for a network with multiple branches. During the specified dates, it was found that the root mean square error (RMSE) and mean absolute error (MAE) of the prediction outcomes based on multi-scale features were lower compared to the RMSE and MAE of single-scale features. This distinction implies that multiscale characteristics may enhance PM2.5 forecast precision. The explanation might be that multi-scale characteristics represent various PM2.5 fluctuation patterns and can thus give more accurate information for PM2.5 prediction.  
Additionally, the network with three branches has the lowest RMSE and MAE during the next one, three, and seven days.  
This study shows that networks with three branches perform better than those with two and four branches. Table 2 displays the RMSE and MAE of PM2.5 prediction results for one, three, and seven days ahead when the network is extensive. The root mean square error (RMSE) and mean absolute error (MAE) for the multi-scale forecast on the selected dates were determined to be less than the single-scale forecast results.
# Attention-Guided Network Model for Image-Based Emotion Recognition
## 1 Introduction
### Related Work
#### 1.1.2 Attention Mechanisms  
Learning mechanisms have recently shown improvement in CNN representations by capturing spatial correlations between features [5]. In [5], the relations between channels in network design were investigated and, as a result, an SE block was introduced to improve the performance of networks by computing the interdependencies between the channels. The tests were conducted on the ImageNet 2012 [33] dataset using the architectures of VGGNet [2] and different residual networks. The results showed the SE blocks incorporated into the architecture outperformed the baseline models while slightly affecting computational performance. In [6], the CBAM was introduced, in which the work extended SE blocks by focusing on the spatial as well as the channel information, arguing spatial attention is important in deciding where the network must focus. The tests were conducted on the ImageNet 1K [34] database using ResNet50 [3] as the base architecture. The results showed better performance over both the base and the SE-base integrated models with the CBAM having finer attention than SE.  
In [7], two attention modules were proposed for spatial and channel features, which learn the relations between the inter-channels and inter-spatial dimensions sequentially and output refined features. Residual networks were used as the framework of the models with an additive angular margin loss function during training. Performance on the test dataset revealed enhanced performance. However, this strategy increased the computational time and power required. In [8], the attention branch network (ABN) is defined; an attention map from XAI is generated, which represents the regions of significance in an image; and the effective weight of the attention mechanism is extracted in a supervised learning approach. Results show that combining an ABN with base models improved performance and enhanced capabilities when incorporated with other attention-laced networks. This structure is somewhat complicated to add to an existing network and also adds more computational load.
## 2 Materials and Methods
### Antityrosine Activity  
The antityrosinase activity of AuNPs was analyzed using the method of [PERSON] et al. (2017) with modifications [PERSON] et al. (2015). First, AuNPs were dissolved in a dimethyl sulfoxide (DMSO) solution (1 g/L) and further diluted to different concentrations with DMSO. Second, 30 \(\mu\)L of the solution containing AuNPs was mixed with 970 \(\mu\)L of sodium phosphate buffer (0.05 mM). The mixture was subsequently added to a solution containing 1 mL of L-tyrosine (100 mg/L) and 1 mL of mushroom tyrosinase solution (350 units/mL). The absorbance of the solution was measured at 490 nm by using a UV-vis spectrophotometer before and after 20 min of incubation. The IC\({}_{50}\) value, at which half the original tyrosinase activity was inhibited, was analyzed through AuNPs treatment. The antityrosinase activity of AuNPs can be expressed as a percentage of tyrosinase inhibition by using the following formula:  
\[\text{Tyrosinase inhibition}\left(\%\right)=\frac{\left[\left(A-B\right)- \left(C-D\right)\right]}{\left(A-B\right)}\times 100 \tag{3}\]  
where \(A\) is the absorbance at 490 nm without AuNPs (control), \(B\) is the absorbance at 490 nm without AuNPs and tyrosinase (blank), \(C\) is the absorbance at 490 nm with AuNPs and tyrosinase (experimental group), and \(D\) is the absorbance at 490 nm without tyrosinase (blank of \(C\)).  
The antityrosinase activities of AuNPs in HEMn cells were analyzed as described previously [PERSON] et al. (2015). Briefly, HEMn cells (10\({}^{6}\) cells/mL) were cultured in 24-well plates, exposed to 100 nM \(\alpha\)-MSH for 48 h, and then treated with increasing doses of AuNPs for 24 h. Afterward, the cells were washed with PBS and lysed with 0.1 M PBS containing 1% Triton X-100 and protease inhibitors. The treated cells were then sonicated, and lysates were clarified through centrifugation at 9000\(\times\)\(g\) for 15 min. The cellular tyrosinase content was determined using a BCA Protein Assay Kit (Thermo Scientific, Vantaa, Finland). The resulting solution was added to 96-well plates, with each well containing 20 \(\upmu\)g of tyrosinase, 2.5 mM L-DOPA, and 0.1 M PBS. After incubation at 37 \({}^{\circ}\)C for 1 h, absorbance was measured at 475 nm by using an ELISA reader (Epoch 2 Bio-Tek Instruments, USA).
## 3 Data Preparation and Analysis
### Landslide Cataloging  
Landslide cataloging data are the prerequisite for landslide susceptibility evaluation, and the completeness and accuracy of the data is of great significance to landslide susceptibility evaluation. In this study, based on the topography, geological structure, and landslide ledger data of the study area, the landslide dataset was established through field validation by synthesizing a variety of new technological methods, such as InSAR deformation rate, high-resolution satellite remote sensing, and unmanned aerial vehicle (UAV) remote sensing. A total of 122 geologic landslides were identified (Figure 4), of which 70 landslides, accounting for 57.38% of the total number of landslides, had significant deformations.
# New Physically-Based Mathematical Model and Experiments for a Recently Invented Solar Pot
## 5 Conclusions  
In the paper, a new physically-based mathematical model was proposed and an experimental system was assembled for a recently invented solar pot. The solar pot, as an environmentally friendly technical tool, utilizes renewable solar heat, provided by a solar collector as the heat source, for cooking or heating foods, drinks or other liquids. Based on both the simulated and the measured results, the solar pot, containing an inner cooking tank (where the cooking or heating task is realized) and an outer mantle (connected directly to the solar collector), can be used successfully to cook or sterilize different dishes and liquids. In particular, based on measured data, the temperature level needed for heat treatment (75 \({}^{\circ}\)C) can be maintained in the cooking tank for several hours (\(\sim\)5 h, on the average) in a typical day in May in Hungary.  
Future research plans include the investigation of how long does it take for the solar pot-collector system to cook different dishes (like pasta, meat etc.) in different seasons and weather conditions. The possibility and relevance of different types of auxiliary (not solar) heating solutions (in addition to the solar collector) may also be examined, in order to extend the operating period of the solar pot. With respect to the proposed mathematical model, the establishment of a maximally precise version of it (considering sky effects, the effect of air under the cover, the temperature dependence of certain parameters, like the mass density and the specific heat capacity of water, etc.) may come into question in the future.  
**Author Contributions:** Conceptualization, M.R. and R.K.; methodology, M.R., R.K. and L.S.; software, M.R.; investigation, M.R., G.G. and R.K.; resources, M.R., G.G., R.K. and L.S.; data curation, M.R. and G.G.; writing--original draft preparation, M.R. and R.K.; writing--review and editing, M.R., G.G., R.K. and L.S.; visualization, M.R. and G.G.; supervision, R.K. and L.S.; project administration, M.R., G.G., R.K. and L.S.; funding acquisition, G.G. and L.S. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the project 'The feasibility of the circular economy during national defense activities' of 2021 Thematic Excellence Programme of the National Research, Development and Innovation Office under grant no.: TKP2021-NVA-22, led by the Centre for Circular Economy Analysis.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data used to support findings of this study are available from the corresponding author upon request.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Conclusions  
LCLD is a well-known selective deposition process because of its simplicity and cost-effectiveness. It can also fabricate quite small-sized conductive lines based on relatively inexpensive laser equipment. Despite the many advantages of the LCLD process, since it is based on a chemical reduction reaction by local heating, it has a fatal disadvantage: the process speed is very slow. Therefore, in this study, experiments were conducted to improve the process speed through various conditions change based on relatively high laser power.  
When the process speed was increased based on the horizontal line shape scan path, which was mainly used in previous studies, deposition was hardly performed due to insufficient time and thermal energy for a stable reduction reaction. When repeating the laser scan loop, it could be seen that the deposition structure was formed around the edge of the scan path. Utilizing this phenomenon, if laser scan proceeded in one direction with partially overlapped, the reduction reaction could be activated due to the increase in the thermal energy of the overlapping regions, enabling the formation of a dense deposited structure at the edge of the scan path. From this, as a result of conducting an experiment based on a scan path having a vertical line, triangular, and elliptical shape, the most stable deposition result was obtained at the elliptical scan path. The elliptical scan path was more advantageous in dispersing laser energy than the general line-based scan path. Thus, the activation region of the reduction reaction by selective heat up could be widened. This made it possible to secure the time required for the stable chemical reduction and reduce unwanted ablation phenomenon by excessive overlap. Therefore, the proposed fast LCLD process was able to fabricate a conductive line with a specific resistance of 26.1 \(\upmu\Omega\)-cm, while improving the process speed by 10 times more compared to the previous LCLD studies. It was also confirmed that the fabricated pattern could play the role of a circuit. That is, the proposed fast LCLD process was an inexpensive and low-temperature process that could quickly form a conductive pattern with a single process, and it was possible to realize excellent conductivity while minimizing the influence on other pre-mounted parts.  
Conceptualization, M.-S.P.; methodology, M.-S.P.; investigation, H.-G.K. and M.-S.P.; writing--original draft preparation, H.-G.K. and M.-S.P.; writing--review and editing, M.-S.P.; supervision, M.-S.P.; project administration, M.-S.P.; funding acquisition, M.-S.P. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the Research Program funded by SeoulTech (Seoul National University of Science and Technology).  
Not applicable.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
# Lightweight Transformer with Adaptive Rotational Convolutions for Aerial Object Detection
## 2 Background Research  
Oriented object detection in aerial imagery has garnered significant research attention due to its critical applications in urban planning, environmental monitoring, and disaster response. Existing approaches to this problem can be broadly categorized into three main areas: rotational invariance methods, semi-supervised learning techniques, and Vision Transformer-based architectures. This section reviews these areas, emphasizing their contributions and limitations within the context of oriented object detection.
###### Abstract  
Near infrared imaging (NIR) camera systems have been clinically deployed to visualize intravenous injected indocyanine green (ICG) spreading through the vascular bed, thereby creating the ability to assess tissue perfusion. While standardization is key to make fluorescence angiography (FA) comparable and reproducible, optical characteristics like field illumination homogeneity are often not considered. Therefore the aim of this study is to investigate light distribution and the center-periphery effect among five different NIR imaging devices in an indocyanine green phantom. A 13 \(\times\) 13 cm fluorescence phantom was created by diluting ICG in Intralipid (representing 0.1 mg/kg dose in an 80 kg reference male), to evaluate the overall spatial collection efficiency with fluorescent modalities of five different NIR camera systems using a 0-degree laparoscope. The fluorescence signal from the phantom was quantified at a fixed distance of 16 cm using tailor-made software in Python. The results showed considerable variability in regard to light distribution among the five camera systems, especially toward the periphery of the field of view. In conclusion, NIR signal distribution varies between different systems and within the same displayed image. The fluorescence intensity diminishes peripherally away from the center of the field of view. These optical phenomena need to be considered when clinically interpreting the signal and in the development of computational fluorescence quantification.  
near infrared imaging; phantom; image guided surgery; light distribution Article
# Defining the Influence of Fatigue Protocol on Kinematic Parameters of Ippon Seoi Nage
## 4 Discussion
Other authors [19; 39; 40] have studied the speed of the general center of gravity of the body and concluded that in the kuzushi and tsukuri phases, better judokas have a higher COM speed. However, they did not observe whether there is an influence of fatigue on their performance. [PERSON] et al. [23] also studied the joint speed in the kuzushi and tsukuri phases in from-the-spot throws between judokas of different quality. They found that there is a difference in the speed of the hip and ankle, but not in the speed of the shoulder and hand. In the present research, the speed of the hand was studied in each phase, and it was determined how fatigue affected this variable. It is interesting that there is a greater range in the studied velocity after the fatigue protocol with a greater minimum and maximum value. Some participants used their trunk to a greater extent by bending forward and less hand speed, while some used less forward bending and used their arms more for throwing. These differences confirm the assumption that better judokas manage to maintain the level of their technical efficiency at a higher level even in the fatigue phase. As this research mainly focused on the influence of fatigue protocol, the limitations of the study relate to the lack of physiological parameters observed in testing procedure. Fatigue protocol could be implemented via a simulated judo fight with additional physiological parameters, such as blood lactate, to obtain even better insight into the associations between fatigue and technique performance in judo. Additionally, the fact that the tori performs throws without the uke's resistance is a limiting factor to achieving more exact conclusions about the kinematically ideal throwing performance. Additionally, observing these parameters between high-level and low-level judokas would provide more detailed insight into the differences in relation to the level of technical excellence.
## 3 Results
### Result Validation by Borehole Drilling  
Drilling conducted at Borehole 3H by Isotope Ltd. (Cannot Industry zone, Gedera, Israel) adjacent to the depression near Line 0209 corroborates the geophysical findings:  
* 0-8 m: Fill materials of chalk and clay bundles (light blue in Figure 19).
* 8-45 m: Predominantly chalk (blue).
* 45-49 m: Karstic cavities (light green).
* 49-63 m: Severely weathered chalk with additional cavities (light green).
* 63-70 m: High-quality, continuous chalk (dark green and more profound).  
These combined resistivity measurements and drilling results reveal critical insights into the structural and compositional variability of the subsurface. Identifying karstic cavities and weathered zones, coupled with groundwater presence and heterogeneity in layer continuity, underscores the complex interplay of geological and hydrological factors contributing to subsurface instability. These findings offer a robust framework for further geological assessments and mitigation strategies.
## 2 Constellation Design and Data Simulation
### Simulation of Observations
The other errors, including the multipath and atmospheric residual errors, were taken from the actual residuals of multi-GNSS PPP performed on the above iGMAS stations and were added to the simulated code and carrier-phase measurements. The geometric models for the spaceborne observation simulations were nearly the same as those for the ground observations except that the tropospheric delay was not considered, nor was the first-order ionospheric delay because IF combination observations were applied [30]. However, the high-order ionospheric delays need to be treated carefully when encountering serious space weather such as geomagnetic storms. The PCO value was set to 0 for the LEO spaceborne observations and the PCVs were ignored. The pseudo-range and carrier-phase measurement noises were set to a zero-mean normal distribution with the standard deviation (STD) calculated from actual-observed onboard GPS data. The observation weighting was set dependent on the satellite elevation, \(E\), where the weighting was 1 if \(E>30^{\circ}\) and \(2\sin(E)\) otherwise. Similar to the ground observations, the other errors, i.e., the spaceborne atmospheric residual errors, were taken from actual-calculated spaceborne observation residuals and applied to the simulated observations. The onboard receiver clock offsets were taken from actual-processed receiver clock offsets onboard an LEO satellite in orbit. The ambiguities were simulated as an integer number of constant cycles for each continuous observation arc. The code and phase delays were set to float constants near zero. Some random cycles of cycle slips were introduced on certain epochs throughout the entire time series. As for the satellite clock offsets, GNSS satellites are equipped with highly stable atomic cesium or rubidium clocks (with long-term stability on the order of \(10^{-13}\) s) and the GeoForschungsZentrum (GFZ) 5-min interval multi-GNSS final clock offset products were used to simulate the BDS-3 satellite clock errors. The Earth orientation parameters (EOP) were taken from the IGS values.
# Coverage, Rate, and Last Hop Selection in Multi-Hop Communications in Highway Scenarios
## 2 System Model
### Metrics of Interest  
We consider the following system-level performance characteristics of multi-hop relaying bridges: (i) bridge availability at the given distance, (ii) attained data rate, and (iii) path usage probability. Here, bridge availability is estimated with respect to a certain distance to the BS and characterizes the probability that the connection to the BS can be established. The data rate is defined by the modulation and coding scheme (MCS) that is utilized for the hop with the worst channel quality among those that construct a relaying communication path.  
The final metric of interest is path usage. The path selection is always driven by the best channel conditions, i.e., we assumed that, when there are several feasible paths for a single hop, the path with the highest SINR is selected. This metric allows for a detailed analysis of antenna placement options revealing their advantages depending on traffic conditions.