esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Transformation of Diclofenac via UVA Light in the Presence of PVDF  
Diclofenac is transformed in the presence of UVA light (see Figure 4). Within a time of 90 min, diclofenac is eliminated from the tested solution (Figure 4a). The total organic carbon (TOC) is removed to a lower degree (Figure 4b). After 18 h of irradiation with UVA light, only 17.8% (\(SD\) = 2.7%) of TOC is mineralized. Overall, phototransformation depends on many parameters like molar absorption coefficient, quantum yield, intensity of emitted irradiation (incident photon flux), radiation wavelength and photoreceptor design. Thus, direct comparison with literature values is difficult. Diclofenac (30 and 10 mg L\({}^{-1}\)) is transformed by UVC irradiation (254 nm) within 9 min [52] and 6 min [53], respectively. Complete phototransformation of diclofenac (30 mg L\({}^{-1}\)) via UVA (365 nm) is reported to take 29 h [52]. UVA irradiation of diclofenac (0.5 mg L\({}^{-1}\)) with similar wavelengths (313-578 nm) results in lower transformation of 20% after 60 min [28] compared to over 90% in this study. Diclofenac is excited by light up to wavelengths of 320 nm with an absorption maximum at 278 nm (see Figure 3b). Thus, the difference in phototransformation kinetics in literature to the here reached values is due to (amongst others) the applied irradiation wavelength. The TOC removal after complete diclofenac transformation is higher in this study compared to literature value of \(<\) 10% for UVA and UVC irradiation [52].  
Adding PVDF increases the reaction rate of diclofenac transformation and TOC removal. After 20 min of transformation, only 64.9% (\(SD\) = 0.2%) of diclofenac is transformed without, compared to 72.3% (\(SD\) = 0.2%) of diclofenac elimination with PVDF present during UVA irradiation. The adsorption of diclofenac itself at PVDF is neglectable [44] with 4% (\(SD\) = 0.4%). The TOC is also removed to a higher value when PVDF is present during UVA irradiation. Again, adsorption of diclofenac itself is insignificant. The removal of TOC increases from 17.8% (\(SD\) = 2.7%) to 54.0% (\(SD\) = 1.3%) when PVDF is present during 18 h of UVA light irradiation. Adding PVDF after 18 h of photoreaction to the irradiated solution leads to a removal of 37.5% (\(SD\) = 2.4%) of TOC. TOC removal via UVA irradiation is highly increased with PVDF present. Even strong UVC irradiation by [PERSON] et al. [52] resulted in lower TOC removal of 10% after 100 min of irradiation compared to values of 26% and 40% after 60 min and 120 min in this study, respectively.  
Figure 3: (**a**) Simulated absorption spectrum of diclofenac and selected transformation products (II–X). (**b**) Measured absorption spectrum of diclofenac at different irradiation times. The UVA lamp light emission ranges from 309–400 nm.
# An Enhanced Energy Balanced Data Transmission Protocol for Underwater Acoustic Sensor Networks
## 4 EBET and EEBET: Proposed Techniques  
Provided a target network area, the sensor nodes are deployed in a random-uniform way and the sink node is placed at the center of the network field. By random uniform we mean; (i) same number of nodes are deployed in each ring sector; and (ii) the deployment of nodes within a given ring sector is random. The assumptions and descriptions are as follows.  
* All sensor nodes are homogeneous with limited battery power and are location-aware using existing positioning method (Received Signal Strength Indicator (RSSI) as location finder [21], and NoteTrack location identification scheme [22]). By location aware we mean that each sensor node knows its location.
* The sensor nodes always have data to send.
* The data reporting mechanism is periodic.
* The static sink resides on the surface of water.  
Location awareness (Equations (8) and (10) are used to find the neighbors of a node. Once the neighbors are identified, suitable relays are needed to forward the data from source to destination. In order to select/choose the relays, the network area is divided into regions known as Ring Sectors \(Sr\). The maximum number of ring sectors \(Sr_{max}\) depends on the network radius \(R\) and the optimum transmission distance threshold \(O_{t}\). Relation between \(R\) and \(O_{t}\) can be found from Equations (13) and (16) in [9]. Using these two equations, we find \(O_{t}\) for different \(R\). Using values of \(O_{t}\), we find \(Sr_{max}=\frac{R}{O_{t}}\). The slice containing sink is denoted by \(Sr_{1}\) with radius \(r\). Next to \(Sr_{i-1}\) is \(Sr_{i}\) where \(i=1-Sr_{max}\) with radius \((i-1)\times r\) and \(i\times r\), respectively, as shown in Figure 3. The total number of nodes in each Ring Sector is \(n\) such that the total number of nodes in the network is \(N\) (\(N=Sr_{max}\times n\)).
# Low-Frequency Magnetic Field Exposure System for Cells Electromagnetic Biocompatibility Studies
## 4 Construction of Exposure System  
The construction of a designed exposure system for cell electromagnetic biocompatibility studies consists of constructing of a support system for Erlenmeyer flasks and of the construction of coils, the exposure one and the control one. The construction is followed by measuring of the magnetic flux density of both coils for verification of the numerical results.  
The resistance to temperature, acids, alkalis, alcohol, and inflammability is considered when selecting the material of the coil support structure. Polytetrafluoroethylene (PTFE) meets the specified requirements--it has high thermal stability from \(-200\)\({}^{\circ}\)C to \(+260\)\({}^{\circ}\)C, is chemically inert, nonflammable, and tolerated by living organisms [42].  
The location of the irradiated samples is defined by exact positions by a support system (SpS). The SpS is designed and modelled in Inventor(r) 3D CAD software. Therefore, it is necessary to make two support systems for each coil separately. The individual parts of the SpS are made of polyethylene (PE). Since the PTFE has a high surface tension, the SpS made from PE can be easily inserted into the coil cavity. The whole construction of SpS consists of four guide rails and five shelves. The SpS should secure safe handling with the yeast samples in the Erlenmeyer flasks.  
After the suitable simulation of the exposure system, technical documentation is prepared for processing the material and producing a supporting structure of the coils. The supporting structure of the coil is made of PTFE, composed of parts--semi-finished products in the form of eight hollow cylinders. The purchased semi-finished parts are processed on a lathe to the required size and then assembled into the final shape. Enameled copper wire of 1 mm diameter in a total length of 912 m for each coil is wound onto the coils supporting structure using the lathe. The completed pair of coils is shown in Figure 7. The location of the irradiated samples is defined on exact positions by a support system (SpS), also presented in Figure 7. The parts of the SpS are not permanently connected, the construction can be divided into individual parts and possibly modified. The SpS also provides easy and safe handling of the samples.  
Figure 6: Spatial temperature distribution, data from COMSOL Multiphysics.
## 2 Proposed Equations
\[K_{L}\ u(t)+C\ \ddot{u}(t)+M\ \ddot{u}(t)+r_{N}(t)=-M\ddot{u}_{g}(t) \tag{10}\]  
where \(K_{L}\) is the stiffness matrix for the linear elastic elements (all elements except for the gap and support elements); \(C\) is the proportional damping matrix; \(M\) is the diagonal mass matrix; \(r_{N}(t)\) is the vector of forces from the nonlinear degrees of freedom (gap and support elements); \(u(t)\), \(\dot{u}(t)\), and \(\ddot{u}(t)\) are vectors of the relative displacements, velocities, and accelerations with respect to the ground; and \(\ddot{u}_{g}(t)\) is the vector of ground motion accelerations. In this study, as no gap elements have been used, the nonlinearity has been considered only for the support elements. Also, \(r_{N}(t)\) in Equation (10) is the vector of forces from the nonlinear degrees of freedom for the support elements. A time step of 0.001 s has been used in this study since it is considered to be small enough to satisfy the conditions of numerical stability and accuracy during collisions between adjacent buildings. It should be highlighted at the end that all the buildings considered in this study are concrete buildings and the cases involve floor-to-floor bounding in both symmetric and torsional bounding. Steel and timber buildings were not considered in this study. Therefore, the proposed equations are valid for all kinds of concrete buildings that respond in the linear elastic range: in the cases of symmetric and torsional bounding and for all ranges of stiffnesses, masses, and damping ratios.
## 2 Materials and Methods
### Types of Algorithms Used for the Classification
In this work, a distance metric dedicated to time series, the so-called Dynamic Time Warping (DTW), was used, which is an algorithm for measuring the similarity between two temporal linear sequences. DTW is an algorithm for finding an optimal alignment between two sequences and a useful distance metric, which possesses the capacity to cope with changes in data over time. The DTW Barycentre Averaging (DBA) algorithm minimises the sum of the squared DTW distance between the barycentre and the series in the group. As a result, the centroids have an average shape that mimics the shape of the group members, regardless of where temporal changes occur among the samples [44; 45; 46; 47]. Given two time series \(x\) = (\(x_{0}\),..., \(x_{n}\)) and \(y\) = (\(y_{0}\),..., \(y_{m}\)), with lengths \(n\) and \(m\) respectively, the distance DTW from \(x\) to \(y\) is thus stated as an optimisation problem, such that,  
\[DTW(x,y)=min_{\pi}\sqrt{\sum_{(i,j)\in\pi}d(x_{i},y_{j})^{2}}, \tag{2}\]  
where \(d\) is the Euclidean distance between two points in the series and \(\pi=[\pi_{0},\ldots,\pi_{k}]\) is a path that satisfies a number of properties. On the one hand, \(\pi_{k}=(i_{k},\ j_{k})\) represents pairs of indices such that \(0\leq i_{k}\ <n\) and \(0\leq\ j_{k}<m\). As boundary conditions \(\pi_{0}=(0,0)\) and \(\pi_{k}=(n-1,\ m-1)\) are considered. As a continuity condition, it is stated that for all \(k>0\), if \(\pi_{k}=(i_{k},\ j_{k})\) and \(\pi_{k-1}=(i_{k-1},\ j_{k-1})\), it has to be fulfilled that \(i_{k-1}\leq i_{k}\leq i_{k-1}+1\) and \(j_{k-1}\leq j_{k}\leq j_{k-1}+1\). Therefore, the path is a temporal alignment of time series such that Euclidean distance between aligned or resampled time series is minimal [48]. In this way, the k-means clustering method applied to time series, in this case applied to daily irradiance profiles, using the DTW metric, created groups of irradiance daily profiles with similar shapes, and the centres or centroids of the clusters were calculated as barycentres or average sequences of a group of irradiance time series considered within the same group.
# Automated Chest X-Ray Diagnosis Report Generation with Cross-Attention Mechanism
## 2 Materials and Methods
### Visualization Method for Comparing the Effects of Visual Feature Extractors  
In this study, we use the Grad-CAM++ [19] method to visually compare the performance of different visual feature extractors (such as ResNet, ResNet_CBAM, etc.). Class Activation Map (CAM) [20] is a classic interpretability technique that generates a heat map by calculating the weights of the feature map to intuitively display the areas in the input image that contribute most to the model prediction results. The CAM method relies on global average pooling (GAP) to calculate weights, but requires modification of the network structure, which has certain limitations in some applications.  
To solve this problem, the Grad-CAM [21] method was proposed, which calculates the weights of the feature map in the convolution layer through gradient backpropagation, avoiding the modification of the network structure, and is suitable for a wider range of deep learning models. However, Grad-CAM has a low resolution when processing complex scenes or small targets, and may not be able to accurately locate fine-grained feature areas.  
In response to the above shortcomings, Grad-CAM++, as a further improvement of Grad-CAM, generates more refined class activation maps by optimizing the weighting mechanism of the gradient. Grad-CAM++ can better capture the features of multiple target areas in an image, especially in complex backgrounds or multitarget scenes. In this study, we used the Grad-CAM++ method to generate heat maps, selected the convolution layer close to the output of the model as the feature extraction layer, and generated an intuitive heat map by calculating the weights of the feature map and weighted normalizing the results. This process can accurately show the model's focus areas on key anatomical structures (such as lungs, heart, trachea, etc.) in chest X-ray images.  
Grad-CAM++ not only provides important support for the evaluation of model performance, but also provides a reliable basis for the interpretability study of different feature extractors in medical image analysis tasks.
# Coverage Extension for the UK Smart Meter Implementation Programme Using Mesh Connectivity
## 3 Results and Discussion
Due to these findings and solutions provided as discussed here, Zigbee is used by the Smart Meter Implementation Programme (SMIP) to provide a Local Area Network connecting smart Gas Meter and in-home display to electric meters and the Communication Hub. Figure 7: Line-of-sight test at 2.44 GHz ZigBee radio.
# Learning Part-Based Features for Vehicle Re-Identification with Global Context
## 4 Experimental Results and Analysis  
We conducted a series of experiments on the VeRi and VehicleId datasets using the proposed method. The input images were resized to 384 \(\times\) 192 during the training and evaluation stages. The training batch size was set to 32. We performed uniform partitioning in the horizontal dimension with six parts. Training was conducted for 60 epochs in the first cycle and another 10 epochs in the second cycle using the VeRi dataset, and for 60 epochs using the VehicleId dataset. This was due to the larger size of the VehicleId dataset. The plots of the loss values on the training set and the mAP values on the testing set for the VeRi dataset are given in Figures 4 and 5, respectively. It can be seen from the plots that the model was trained to convergence. For our experiments, we used the inverse function \(f\) in the second cycle such that \(f(x)=1/x\). We also conducted experiments using only the first cycle for 120 epochs on both datasets as a baseline and compared the results with those of the proposed method. We also used re-ranking with k-reciprocal nearest neighbors as a post-processing step during evaluation. This step generated a ranked list of gallery output images for each query image using a mixture of Euclidean and Jaccard distances, following the process described in [46]. Figure 4: Loss values of the training set on the VeRi dataset. Figure 5: mAP values on the testing set of the VeRi dataset. This method has been shown to improve accuracy in the existing literature. In line with conventional re-identification works in the literature, we used mean average precision and Rank-1, Rank-5, and Rank-10 accuracies for both datasets. Table 1 compares the results of our proposed method with those of the baseline on the VeRi and VehicleId datasets. Tables 2 and 3 compare the results of our proposed method with those of other works on the VeRi and VehicleId datasets, respectively. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Dataset** & **Model** & **mAP** & **Rank-1** & **Rank-5** & **Rank-10** \\ \hline VeRi Dataset & GLSIPNet & 76.76 & 94.63 & 97.55 & 98.92 \\  & Baseline & 74.17 & 94.04 & 97.37 & 98.56 \\  & GLSIPNet-RR & 80.99 & 95.70 & 97.55 & 98.68 \\  & Baseline-RR & 78.75 & 94.69 & 96.36 & 97.67 \\ \hline VehicleId Dataset (Small) & GLSIPNet & 88.46 & 85.78 & 98.34 & 99.24 \\  & Baseline & 86.01 & 82.90 & 97.15 & 98.68 \\  & GLSIPNet-RR & 88.84 & 86.26 & 98.26 & 99.29 \\  & Baseline-RR & 86.54 & 83.48 & 97.36 & 98.71 \\ \hline VehicleId Dataset (Medium) & GLSIPNet & 85.08 & 82.21 & 95.73 & 98.00 \\  & Baseline & 81.78 & 78.55 & 93.78 & 96.92 \\  & GLSIPNet-RR & 85.08 & 82.15 & 95.92 & 98.04 \\  & Baseline-RR & 82.04 & 78.78 & 94.04 & 97.07 \\ \hline VehicleId Dataset (Large) & GLSIPNet & 82.66 & 79.63 & 93.88 & 96.98 \\  & Baseline & 79.87 & 76.81 & 91.16 & 95.52 \\  & GLSIPNet-RR & 83.01 & 80.12 & 93.80 & 97.02 \\  & Baseline-RR & 80.16 & 77.13 & 91.22 & 95.58 \\ \hline \end{tabular}
\end{table} 
Table 1: Comparison of GLSIPNet with the baseline on the VeRi and VehicleId datasets.
# A 100 Gb/s Quad-Lane SerDes Receiver with a PI-Based Quarter-Rate All-Digital CDR
## 2 Proposed Multi-Lane SerDes Receiver Architecture  
The proposed SerDes link is for the duplex interface structure with four data lanes and one clock lane. Figure 3 shows a block diagram of the proposed 100 Gb/s quad-lane (25 Gb/s/lane \(\times\) 4 differential lanes) SerDes receiver architecture. Here, it is assumed that a forwarded clock in which a low-frequency clock (= 625 MHz) is transmitted through a separate differential lane without equalization, so the tracking of a data jitter in a wide frequency range is possible. The multi-lane interface architecture presented in this paper is based on source synchronous clocking. Moreover, the proposed CDR structure can be applied to plesiochronous systems in which the Tx and the Rx use separate independent low-frequency quartz-based reference clocks.  
Figure 2: Typical multi-lane high-speed source synchronous serial-link architecture (**a**) without PLL (**b**) with PLL (**c**) with equalizers, PLLs, and CDRs.  
The proposed SerDes receiver core consists of a shared multi-phase MDLL, an all-digital PI-based quarter-rate CDR, and a CTLE. The shared MDLL receives a 625 MHz reference clock and provides eight-phase (= p0-p7) quarter-rate (= 6.25 GHz) clocks multiplied by ten times (\(n=10\)) and distributes them to each CDR block. The use of the proposed multi-phase MDLL has the advantage of the area and power reduction by simultaneously performing frequency multiplication and multi-phase clock generation. The CTLE is designed to compensate for a channel loss of about 19.7 dB at 12.5 GHz. The channel loss of the 40 cm transmission line used in this paper is about 22.6 dB at 12.5 GHz. This channel loss value is similar to those shown by a typical chip-to-chip and midrange backplane interface below 50 cm long [30]. The proposed CDR includes four data samplers and four edge samplers, and performs a 1-to-4 de-multiplexing operation at a quarter-rate using a 2x-oversampling technology. A total of eight samplers (four corresponding to the data samples and four corresponding to the edge samples) recover 6.25 Gb/s four-bit parallel data (D\(<\)3:0\(>\)) and four 6.25 GHz clocks (Dclk0-Dclk 3) from 25 Gb/s random data input through the CTLE. To perform this operation, this CDR includes a phase interpolator (PI), a phase selector (PS), and a PI controller to provide phase-adjusted driving clocks for each data sampler and an edge sampler. In particular, a new initial phase tracker inside the PI controller is used to speed up the lock time and to provide a constant data output sequence. Detailed CDR configuration and operation are described in the following section.
## 5 Performance Analysis
### Secrecy Rate
#### 5.2.2 Multi-Carrier DM Scheme  
Likewise, according to Equation (26), the SINR of the LU for the \(l\)th transmit antenna array in the multi-carrier DM scheme can be calculated by  
\[\gamma^{mc,LU}_{l}=\frac{P_{s}\beta_{1}^{2}}{\sigma^{2}}=r^{mc,LU}. \tag{42}\]  
By means of Equation (42), the achievable rate of the link from the \(l\)th transmit antenna array to the LU in the multi-carrier DM scheme can be written as  
\[R^{mc,LU}_{l}=\log_{2}(1+\gamma^{mc,LU}_{l}). \tag{43}\]  
Using Equation (28), the SINR of the Eve for the \(l\)th transmit antenna array in the multi-carrier DM scheme can be derived as  
\[\gamma^{mc,E}_{l}=\frac{P_{s}\beta_{1}^{2}|\mathbf{h}^{H}(\theta_{e})\mathbf{ h}(\theta_{dl})|^{2}}{P_{s}\beta_{2}^{2}|\mathbf{h}^{H}(\theta_{e})\mathbf{T}_{l} \mathbf{z}_{l}|^{2}+\sum\limits_{k=1,k\
eq l}^{K}|\mathbf{h}^{H}(\theta_{e}) \mathbf{u}_{k}|^{2}+\sigma^{2}}. \tag{44}\]  
Furthermore, from Equation (44), the achievable rate of the link between the \(l\)th transmit antenna array and the Eve in the multi-carrier DM scheme can be expressed as  
\[R^{mc,E}_{l}=\log_{2}(1+\gamma^{mc,E}_{l}). \tag{45}\]  
Therefore, the secrecy rate of the proposed multi-carrier DM Scheme can be defined as [24]  
\[R^{mc}=\sum\limits_{l=1}^{K}{[R^{mc,LU}_{l}-R^{mc,E}_{l}]}^{\dagger}. \tag{46}\]
# Numerical Simulation of Liquid Film Characteristics during Atomization of Aluminum Alloy Powder
###### Abstract  
The process of atomizing aluminum alloy powder using a rotating disk was studied by numerical simulation and experimental verification. The motion characteristics of the molten metal thin liquid film and the evolution law of atomization into droplets were systematically studied with different disk shapes and speeds. The results showed that the slippage of the liquid film on the surface of the spherical disk was smaller, the liquid film spread more evenly, and the velocity distribution was more uniform. Under the same working condition, the boundary diameter of the continuous liquid film on the spherical disk was 21-29% larger, and the maximum liquid film velocity increased by approximately 19%. In other words, the liquid film obtained more energy at the same rotational speed, the energy utilization rate was higher, and the liquid filaments produced by the splitting region of the disk surface were finer and greater in number. The data showed that the average thickness of the liquid film on the surfaces of different disk shapes was more affected by the speed of the flat disk, and the thickness on the spherical disk was relatively stable and uniform, but the difference in thickness between the two disk shapes decreased from 4.2 \(\upmu\)m to 0.3 \(\upmu\)m when the speed increased from 10,000 rpm to 60,000 rpm. In particular, the influence of the disk shape on the liquid film thickness became smaller when the speed increased to a certain range. At the same time, the characteristics of the liquid film during the spreading movement of molten metal on the disk and the mechanisms of the primary and secondary breakage of the liquid film were obtained through this simulation study.  
rotating disk atomization; aluminum alloy powder; numerical simulation +
Footnote †: journal: Applied Sciences