esa-sceva/satcom-chunk-collection huggingface dataset:
# A Dosimetric Analysis of Reduction Cardiac Dose with Lead Shielding in Breast Cancer Radiotherapy
## 2 Materials and Methods
### Optically Stimulated Luminescence Dosimeter System  
The dosimetry equipment used in this study was the nanoDot OSLD and the InLight(tm) MicroStar reader manufactured by Landuauer USA (Landauer Inc., Glenwood, IL, USA). The nanoDot OSL dosimeter was made of 5 mm diameter and 0.2 mm thick plastic disks infused with Al\({}_{2}\)O\({}_{3}\):C. The disks are encased in 10 \(\times\) 10 \(\times\) 2 mm\({}^{3}\) light-tight plastic holders having a density of 1.03 g/cm\({}^{3}\). Prior to measurements, the OSLDs were screened to reduce measurement errors. This study decided not to use the cumulative dose feature of the OSLD for dose calculation. Therefore, the OSLDs were annealed after each measurement to remove the previous dose reading. Incandescent light was used for annealing, as literature indicated that its annealing efficiency was better than that of fluorescent light. Once the residual signal was removed after 24 h of illumination, the reading of the OSLD without any dose was recorded as the background reference.  
Figure 3: Treatment planning using volumetric-modulated arc therapy (VMAT) (**a**) Whole breast irradiation scheme. (Multi fields). (**b**) Dose distribution image. Yellow planning targeting area, purple tumor bed.  
Before the experiment, the OSLDs were exposed to doses in the range of 10-100 Gy in a stepwise manner of 10 cGy doses each, so as to confirm whether the correlation between the dosimeter reading and the actual dose was linear.
## 4 Results
### Influence of Distance Matrix Upload on Optimizer Cost Reduction
The values of the _Gain_ coefficient were calculated for any cases. Table 1, presents the calculated values of the cost reduction (_Gain_) for selected distance matrices  
Particularly in the case of the Wise RS algorithm, it is noted that the mixed-matrix containing the 50% update of the smallest coefficients exhibits similar properties to the _DistOSRM_ target matrix. In contrast, the mixed-matrix containing 50% of the highest index updates has the characteristics of the _DistEuclCorr_ temporary matrix. More detailed results are represented in Figure 5, where an evolution of the calculated _Gain_ value is presented. For all cases, the cross-section (represented by the trend lines--fit of 6-order polynomial) takes the form of a characteristic hysteresis. The trend-line for the series \"from lowest\" seems to be clearly more favorable from the point of view of stabilizing the expected value of the _Gain_ coefficient. In fact, with about 40-50% of updates, the Mixed Matrix exhibits the characteristics of the target matrix. On the other hand, updating the matrix in the \"from highest\" variant seems to be the wrong approach. It turns out that even with an 80-90% update level, the expected results are significantly different from the final one. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Algorithms:** & **DistEuclCorr** & \
\begin{tabular}{c} **Mixed-Matrix** \\ **(50\% from Lowest)** \\ \end{tabular} &
\begin{tabular}{c} **Mixed-Matrix** \\ **(50\% from Highest)** \\ \end{tabular} & _DistOSRM_ \\ \hline Greedy Only & \(-1.38\%\) & \(1.31\%\) & \(-2.90\%\) & \(0.29\%\) \\ Simple RS & 2.62\% & 5.43\% & 2.64\% & \(6.00\%\) \\ Wise RS & 7.96\% & 11.03\% & 7.54\% & \(11.10\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cost reduction for different distance matrix types.
## 3 Methods and Materials
### Software Architecture  
The system software is the core of the entire system, as shown in Figure 3. In fact, it allows interfacing the user and driving the manipulator according to the conceptual architecture shown in Figure 1 by using the information provided by the sensors described in Section 3.1.  
To increase the modularity of the system, the software architecture has been divided into three different levels of abstraction:  
* **Hardware layer**
* **Application Logic Unit Layer**
* **Human-Machine Interface Layer**  
The different sections of the code have been implemented in order to be modular and independent from the others. In particular, each section can be substituted without changing the remaining code. Each layer communicates only with its neighbor; the _HMI Layer_ is the only one that interacts with the user.  
To maintain a good scalability and efficiency, ROS [12] is used. It is a collection of software to develop robotic systems. The main features of ROS are the independence from platform, the support of several programming languages and the possibility of exchanging data independently from the  
Figure 3: Layered structure of the system software.  
physical nodes distribution. The standard topology of a ROS system is star-topology where the central node is the ROSCORE and all other nodes are the leaves attached to it. ROS offers two different communication paradigms: _topics_ and _services_. _Topics_ are a continuous stream of data that are received by the ROSCORE and exposed to all the interested nodes. Instead, _services_ are offered by a node, and they are on-demand functions, even if the connection is handled by the ROSCORE.  
To keep the desired modularity, it is necessary that every layer produces its outputs as requested by the adjacent layer, as shown in Figure 4. Details on each layer are provided in Sections 3.3-3.5 and shown in Figure 3.
## 2 Test Samples and Experimental Methods Description
### Experimental Methods Description  
#### 2.3.1 Microscopic Characterization  
Microscopic characterization by TESCAN ORSAY (VEGA3) Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray Spectroscopy (EDS) and optical microscope EUROMEX ISCOPE were manipulated to visualize the morphology of samples. The analysis of different spots in the glass surrounding the concrete-based composite was carried out by SEM-EDS. It is a procedure in which characteristic X-rays generated from the electron beam-sample interaction are analyzed to provide elemental composition of the sample. Their results are in the form of spectra (histograms) in which individual elements can be identified. It provides quantitative chemical characterization of the samples.  
The observation of adhesion between RWG and cement paste and the evaluation of damage caused by ASR reaction was achieved by EUROMEX ISCOPE. This technique is supplied with a pair of 10\(\times\)/20 mm (\(\O\) 30 mm tube) eyepieces. It has also an intensity adjustable 3 W illumination with internal 100-240 V power supply. For this purpose, thin blade samples with thickness of 30 \(\upmu\)m for MRWG50 (Mortar reinforced with 50% of RWG) and CRWG50 were prepared, as shown in Figure 4. The preparation of these thin blades consisted, in a first step, in sawing a piece of a control sample with diamond saw until reaching a thickness of 2 to 1 mm. Thereafter, a blade glass was fixed on the sample's flat surface by a lapping machine and pressed at 80 \({}^{\circ}\)C during 1 h. The obtained blade was then maintained in the machine by an aspiration system to be cut in a parallel plan to glass blade at thickness of 2 to 1 of tenth of millimeter. Finally, the lapping device lasted one hour to rotate and abrade the blade with abrasive powder of silicon carbide until achieving a thickness of 30 \(\upmu\)m.  
Figure 3: Preparation of specimen: (**a**) cement mixer machine, (**b**) mixing of concrete, (**c**) slump measurement, (**d**) filled molds, (**e**) samples after demolding operation, and (**f**) specimens in fresh water.
## 5 Challenges and Future Research Directions
The mobile management and HO operation challenges can be controlled by RRC. Being a layer three network protocol, it is located between UE and BS nodes, used in UMTS, LTE and 5G and considered as a part of air interface control plane. Consequently, RRC has a potential to enhance the latency, power, and energy consumption in UD 5G cellular networks. Some other functions include transferring system information, initiating or emancipating RRC connections, paging, transferring nonaccess stratum (NAS) messages essential to handle communication between user equipment and core nets [127].
###### Abstract  
Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% (\(n=35\), \(p<0.05\), RMSE = 2.20 kg/m\({}^{2}\)) and 85% (\(n=100\), \(p<0.01\), RMSE = 1.71 kg/m\({}^{2}\)) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.  
process-based model; NPP; AGB; BEPS; ALS +
Footnote †: journal: Sensors
# Feed Rate Variation Strategy for Semi-Conical Shell Workpiece in Ball Head End Milling Process
## 4 Experiment Results and Validation
The surface roughness at the middle of each contour are large because the adjacent contour paths are distributed sparsely. However, they almost stay the same with the use of DFV since the feed rate here is still small. Figure 16: Time-domain vibration signals for a single contour line: (**a**,**b**) contour at HP; (**c**,**d**) contour at MP; (**e**,**f**) contour at LP; (**a**,_c**,_e_) contour without feed rate variation; (**b**,**d**,**f**) contour with the feed rate variation. Combining the results from Figures 16 and 17, the influence of the feed rate variation on the contours from different heights is discussed in detail. It should be pointed out that the reductions of consuming time from each position are all by 25% no matter the heights the contour is located. Because the piecewise method of DFV is based on the ratio of the total length of each contour, this is very convenient for practical conditions. As for the contour path at the HP, the maximum vibration acceleration is increased by 30%, while the largest increase of the surface roughness is 2.2%. The maximum vibration acceleration of the contour at MP is increased by 15%, while the largest increase of the surface roughness is 2.81%. The vibration amplitudes of the contour at LP also have two sudden increases, and consuming time is reduced by 25%. There is an increase by 4.65% of the surface roughness at the 2/6 position of the contour where the feed rate is high, and the surface roughness increases of the contour at the 1/6 and the latter half are less than 1%, as shown in Figure 17. Considering the cutting force is large at the middle of the contour, and the vibration amplitude is large at the beginning, and the end of the contour, both cutting force and vibration amplitude can affect the surface roughness, and both of them should be considered in the feed rate planning for the special thin-walled parts like the semi-conical shell workpiece in this paper.
## 3 Methodology
### Simulation of the Geothermal Source  
#### 4.1.1 Analysis of Ground Temperature Variation  
From the Santa Rosalia meteorological station, we obtained the daily surface air temperature data for the year 2017 to calculate the parameters from Equation (3). The ground temperature variation from depth \(Z=0\) to \(Z=100\) m was calculated considering the daily temperature means to be \(T_{m}=28.35\)\({}^{\circ}\)C and \(A_{0}=8.31\)\({}^{\circ}\)C. The parameter \(\gamma\) (m\(-\)1) was estimated using the thermophysical properties of the rocks from W1 (Table 1), the period \(P=8760\) h (365 days), and \(t_{0}=1728\) h (this value correspondedto the 72 nd day of the year). Substituting all of these into Equation (3), the thermal ground variation from La Reforma caldera was estimated by the following equation:  
\[T(Z,t)=28.35+8.31 exp^{-\gamma Z}\sin\left[\frac{2\pi}{8760}(t-1728)-\gamma Z\right] +0.43\ ^{\circ}\mathrm{C}/\mathrm{m}, \tag{35}\]  
Figure 6 shows the thermal profile of the ground temperature for depths between 0 and 100 m for each month of the year. We found that the seasonal thermal effect reached depths between 15 and 18 m, and that the simulated temperature for \(Z\) = 50 m (depth of drilled W1) corresponded to \(T\) = 48.6 \({}^{\circ}\mathrm{C}\) and \(Z\) = 100 m to \(T\) = 68.6 \({}^{\circ}\mathrm{C}\).
# Drying Behaviour of Western Hemlock with Schedules Developed for Norway Spruce and Scots Pine
## 3 Results and Discussions  
### Average MC Loss  
The average MC loss during the drying runs I, II, and III is shown in Figure 4. As expected, Scots pine sapwood dries faster than hemlock to the target MC (Figure 4a), while for hemlock, it did not reach even FSP, which was reported to be around 17% [22]. It can be observed that below the FSP, the steepness of the MC curve for pine is reduced, showing the lower drying rate of the diffusion regime. Figure 4b indicates that the slope of the MC loss curves for hemlock and spruce heartwood is similar, while spruce heartwood reached the target MC faster than the hemlock heartwood. The specimen of hemlock sapwood cracked significantly during the drying test, which meant that the moisture content could not be calculated reliably based on the CT measurements. Therefore, this specimen has been excluded from the results analysis, as can be seen in Figure 4c. There is, however, an evident difference in drying behaviour between spruce heartwood and spruce sapwood, where the sapwood drying occurred initially under the effect of heat transfer with the evaporation of free liquid water, while in heartwood, most of the time, it is a diffusion regime where there is no free water (Figure 4b,c).  
Table 2 shows the comparison of green MC measurements obtained through the gravimetric method and CT method for the three drying runs according to Equation (2), which shows the differences between the two methods. Error values are below 4.5% between the gravimetrically measured MC calculation and the average MC from CT image processing. As already mentioned, substantial cracks appeared during the drying of hemlock sapwood in drying run III, which makes it not feasible to analyse the MC changes with good precision, and CT images could not be processed for bringing into the discussions.  
Figure 4: Average MC distribution for (**a**) hemlock/pine sapwood, (**b**) hemlock/spruce heartwood, and (**c**) spruce sapwood.
Based on the above reasons, the paper proposes the method of bearing fault diagnosis based on DWSC and MSDWF. The general idea of the method is as follows: the time series data obtained by different sensors are weighted by the self-attention method (SAM). The similarity matrix of time series data is extracted from the data themselves by SAM to achieve the weighting of the original data, which strengthens the weak features in the signal and weakens the influence of the interference information caused by the strong noise and variable working conditions. DWSC equipped with residual connection is to perform depth-wise convolutions (DWC) and point-wise convolutions (PWC) on the weighted multi-sensor data. Among them, the DWC uses a convolution kernel to process the data of one sensor to realize the decoupling of channel correlation, and then PWC is used to process all data. Through the affine transformation of the features, PWC not only decreases the number of parameters involved in the whole operation but also realizes the decoupling of spatial correlation. In MCCNN, one convolution kernel is used to process data of multiple channels, so only incomplete decoupling of the channel and spatial correlation can be achieved, which is the most significant difference between them. The method based on MSDWF and SAM obtains the utmost out of the spatial and temporal information in multi-sensor data and can realize end-to-end fault diagnosis effectively and efficiently.
## 4 Simulation Results and Discussion
The observers also show promising performance Figure 6, where it is noticeable that the estimations of the drag coefficients are very close to the actual optimal values as stated before in Figure 4. This is a reasonable outcome since it is proved that if the estimations are correct and if fine-tuning has been conducted to the parameters of the ESCWAO part, the algorithm should be able to seek and detect any change in the coefficients that leads to the optimal distance. Figure 7 shows the evolution of the position errors \(e_{p_{i}}(t),\ i=1,2,3,4\), along with the corresponding performance functions. It seems that the algorithm not only can maintain the formation of the vehicles despite the lack of knowledge of their dynamic models but also is in place to track the desired distances even when the ESCWAO have not converged yet and formulate correctly all the vehicles along the simulation with prescribed transient and steady-state performance. The zoomed plots in the same figure provide a better insight into the last statement. Figure 4: The real drag coefficient relation to the inter-vehicular distance for each follower vehicle in the platoon. Figure 5: The convergence of the desired distance, \(\Delta_{i-1,i}\), for each platoon member under ESCWAO with zoomed plots to clarify the transient state. Figure 6: The change in the observed drag coefficient throughout the simulation for each vehicle.
###### Abstract  
The present study has a dual aim of supporting magnetic nanoparticles over the nanolayers of LDHs and designing two-dimensional magnetic nano-nets of cobalt ferrite. In this trend, nanoparticles of CoFe\({}_{2}\)O\({}_{4}\) were prepared and supported by Co-Fe LDH through urea hydrolysis. The nanolayered structures of Co-Fe LDH were confirmed by X-ray diffraction, energy-dispersive X-ray spectrometry, FT-IR spectra, thermal analyses, and transmission electron microscopy. In addition, they indicated that 13.2% CoFe\({}_{2}\)O\({}_{4}\) were supported over Co-Fe LDH. Transformation of the nanolayered structures of Co-Fe LDH to nano-nets was achieved by the catalytic effect of the supported CoFe\({}_{2}\)O\({}_{4}\) nanoparticles through solvent thermal technique. X-ray diffraction patterns and transmission electron microscopy images confirmed the transformation of the supported Co-Fe LDH to nano-nets of cobalt ferrite. In order to indicate the effect of the LDH for designing the nano-nets, nanoparticles of cobalt ferrite were prepared by the same technique without LDH. The magnetic behavior of the nano-nets and the supported Co-Fe LDH were measured and compared with the nanoparticles through vibrating sample magnetometer technique. The magnetic parameters indicated that the prepared nano-nets have ferromagnetic behavior and high coercivity. However, the prepared nanoparticles revealed a superparamagnetic state and low coercivity. The experimental results concluded that the incorporation of nanoparticles with nanowires into nano-net structures has been found to be an efficient way to improve their magnetic properties and prevent their agglomerations. Finally, layered double hydroxides are an important source for constructing magnetic nanolayered structures and nano-nets.  
magnetic cobalt ferrite nano-nets; magnetic layered double hydroxides; cobalt ferrite nanoparticles; magnetic measurements; transmission electron microscopy
## 3 Results  
### Validation of Satellite-Derived Phenometrics with Field Investigation  
The transplanting date, tillering stage, heading stage, maturity stage, and harvesting date (the end of the maturity stage) acquired from the field survey are shown in Figure 5. The lengths of the actual growth season (from transplanting date to harvesting date) were nearly the same for the 10 sample plots. The timing of transplanting was generally earlier in Site A (from DOY 148 to DOY 153) than in Site B (from DOY 154 to DOY 160), which caused the whole growth season of rice paddies in Site B to lag behind those in Site A. We chose to qualitatively validate the derived phenometrics with the survey data. Specifically, the satellite-derived \(D_{tilt}\), \(D_{head}\), and \(D_{mat}\) were validated against the stages of tillering, heading, and maturity collected by field survey. The NDVI- and phase-space-based phenometrics all lay within the corresponding rice growth stage, which indicated that satellite-derived phenometrics are reasonable.
## 3 Proposed Methodology
### Proposed System Model
It should be noted that while Figure 1 provides a high-level representation of the network structure, the specific channel assignments to PUs can vary dynamically. Depending on the scenario, channels may be either exclusively allocated to individual PUs or shared/overlapping among multiple PUs. These variations are reflected in the simulation scenarios, which assess the effectiveness of the proposed method across various spectrum occupancy scenarios. This dynamic nature of channel utilization aligns with practical cognitive radio environments where spectral resources are often reused or reassigned based on availability and interference constraints. Figure 1: Proposed system model.
## 3 Remote Sensing of Ecosystem Health
### Remote Sensing of Organization
#### 3.2.1 Species Richness and Biodiversity
In addition, ancillary data, such as temperature, precipitation, and topography, can significantly contribute to species richness estimation [117].
## 7 Future Prospects
Comprehensive virtual health platforms are expected to emerge, offering a holistic approach to healthcare that combines real-time monitoring with remote consultations, fostering a more patient-centric and accessible healthcare model [130]. While technological advancements are at the forefront of future prospects, ethical considerations, and human-centric design principles play equally critical roles [136]. The responsible development and implementation of real-time patient monitoring technologies require careful attention to ethical standards, ensuring that patient privacy is upheld and data are used responsibly. Human-centric design ensures that these technologies are accessible, user-friendly, and tailored to the diverse needs of individuals, fostering inclusivity in healthcare. The future of real-time patient monitoring presents a multifaceted landscape characterized by advancements in biosensor technologies, the integration of cutting-edge communications technologies, and the transformative impact of AI. These developments collectively promise to redefine healthcare, ushering in an era marked by personalized, technologically advanced, and ethically sound practices. The potential benefits extend from individual health management to broader health initiatives, setting the stage for a holistic and interconnected healthcare ecosystem. Conceptualization, R.U. and I.K. ; methodology, R.U. ; validation, I.K. ; formal analysis, R.U. ; investigation, R.U. ; writing--original draft, R.U; writing--review and editing, I.K. ; visualization, R.U. ; supervision, I.K. ; project administration, I.K. ; funding acquisition, I.K. All authors have read and agreed to the published version of the manuscript. This work was supported in part by the National Research Foundation of Korea (NRF) through the Korean Government's Ministry of Science and ICT (MSIT) under Grant NRF-2021R1A2B5 B01001721, and in part by the Regional Innovation Strategy (RIS) through the NRF funded by the Ministry of Education (MOE) under Grant 2021 RIS-003. Not applicable. The authors declare no conflicts of interest.