esa-sceva/satcom-chunk-collection huggingface dataset:
# Decimal Multiplication in FPGA with a Novel Decimal Adder/Subtractor
## 4 Decimal Multiplier
### Generation of Multiples  
The generation of partial products with one of the previous method is based on the availability of multiples A, 2A, 4A, 5A and 10A of the multiplicand in excess-3, Ae3, 2 Ae3, 4 Ae3, 5 Ae3 and 10 Ae3, respectively. Multiple 10 Ae3 is obtained from multiple Ae3 decimal shifted left one digit with the new least significant digit equal to three.  
Considering a number with \(n\) digits, A = \(a_{n-1}\ldots a_{0}\), where each digit has four bits, \(a_{i}=a_{i}[3]a_{i}[2]a_{i}[1]a_{i}[0]=a_{i}[3-0]\). Considering also the excess-3 of A, Ae3 = Y = \(y_{n-1}\ldots y_{0}\), where each digit has four bits, \(y_{i}=y_{i}[3]y_{i}[2]y_{i}[1]y_{i}[0]=y_{i}[3-0]\). Each digit \(y_{i}\) is obtained according to Table 7.  
Figure 6: Implementation for a single digit of block \(Sel-Add/Sub\) in method 2.  
\begin{table}
\begin{tabular}{l c c c} \hline
**a** & \(\mathbf{a_{i}[3-0]}\) & \(\mathbf{ae3_{i}[3-0]}\) & \(\mathbf{y_{i}[3-0]}\) \\ \hline
0 & 0000 & 0011 & 0011 \\
1 & 0001 & 0100 & 0100 \\
2 & 0010 & 0101 & 0101 \\
3 & 0011 & 0110 & 0110 \\
4 & 0100 & 0111 & 0111 \\
5 & 0101 & 1000 & 1000 \\
6 & 0110 & 1001 & 1001 \\
7 & 0111 & 1010 & 1010 \\
8 & 1000 & 1011 & 1011 \\
9 & 1001 & 1100 & 1100 \\ \hline \end{tabular} Considering now the excess-3 of 2A, 2 Ae3 = Y = \(y_{n-1}\ldots y_{0}\), each digit \(y_{i}\) is obtained according to Table 8.  
\end{table}
Table 7: Digit \(a_{i}\) in excess-3, \(y_{i}\).  
\begin{table}
\begin{tabular}{l c c c} \hline
**a** & \(\mathbf{2a_{i}[4-0]}\) & \(\mathbf{2 ae3_{i}[4-0]}\) & \(\mathbf{y_{i}[3-0]}\) \\ \hline  & & & \(\mathbf{a_{i-1}[4]=1}\) & \(\mathbf{a_{i-1}[4]=0}\) \\ \hline
0 & 0 0000 & 0 0011 & 0100 & 0011 \\
1 & 0 0010 & 0 0101 & 0110 & 0101 \\
2 & 0 0100 & 0 0111 & 1000 & 0111 \\
3 & 0 0110 & 0 1001 & 1010 & 1001 \\
4 & 0 1000 & 0 1011 & 1100 & 1011 \\
5 & 1 0000 & 1 0011 & 0100 & 0011 \\
6 & 1 0010 & 1 0101 & 0110 & 0101 \\
7 & 1 0100 & 1 0111 & 1000 & 0111 \\
8 & 1 0110 & 1 1001 & 1010 & 1001 \\
9 & 1 1000 & 1 1011 & 1100 & 1011 \\ \hline \end{tabular}
\end{table}
Table 8: Digit \(2a_{i}\) in excess-3, \(y_{i}\).  
The multiple \(5a_{i}\) of one digit results in two digits. The most significant digit is in [0 to 4] and the least significant digit is in [0 or 5], depending if digit \(a_{i}\) is even or odd, respectively. So, each digit \(y_{i}\) depends on input digit \(a_{i-1}\) and the least significant bit of digit \(a_{i}\), where \(a_{-1}=0000\). So, multiple 5A is generated in a single step without any carry propagation according to Table 9.  
All multiple generators assume that the input number is in BCD. To be more generic, all multiple generators were designed with an extra input (isbcd) to specify if the number is in BCD or excess-6. With generic multiple generators, the multipliers are also generic permitting to interconnect several adders/subtractors or multipliers without having to convert the output to BCD.
# A Secure Key Aggregate Searchable Encryption with Multi Delegation in Cloud Data Sharing Service
## 5 Security Analysis
### Informal Analysis
#### 5.1.4 Perfect Forward Secrecy  
In the data retrieve phase, suppose that an adversary obtains secret key \(A_{cs}\) of the cloud server. Then, the adversary is able to compute \(Verif_{j}\) and \(HID_{j}\). However, the adversary cannot compute \(VA_{cs}\) and \(AUTH_{cs}\) since the adversary cannot know a random nonce \(R_{cs}\). Thus, the data retrieve phase provides perfect forward secrecy. In the authentication for delegation phase, suppose that an adversary obtains secret key \(b_{a}\) or \(b_{b}\) of \(DU_{A}\) or \(DU_{B}\). The adversary cannot compute session key \(SK\) because the adversary cannot compute \(V_{A}\) or \(V_{B}\), which is dependent on random nonces \(r_{A}\) and \(r_{B}\). Therefore, our proposed scheme ensures perfect forward secrecy.
## 5 Conclusions  
Characteristic properties of mesenchymal stem cells isolated from chorion were confirmed along with phenotype, adherence to a plastic culture surface, fibroblast-like bipolar shape cells morphology and clonogenic potential. It was found that CMSCs interact with lymphocytes in co-cultivation. MSCs were demonstrated to be poor stimulators of an in vitro allogeneic T cells response and they fail to induce activation of allogenic T cells. MSCs were shown to suppress both naive and memory T lymphocyte activation and proliferation induced by alloantigens and mitogens [50]. Results indicate that that fetal MSCs affected the proliferation of activated lymphocytes. The immunomodulatory ability of CMSCs was compared and tested in activated lymphocyte co-cultivation. The proliferation of activated lymphocytes was suppressed. The extent of proliferation decline was determined by the fluorescence difference of CFDA-SE-labeled lymphocytes over four days of co-cultivation of lymphocytes and the CMSCs. During the co-cultivation, changes in the phenotype of CMSCs CD44 and CD54 adhesion molecules and IL-10 were observed. Higher expression of adhesion molecules was detected after co-cultivation with activated lymphocytes. Results show that CMSCs act as immunosuppressive on activated lymphocytes, with phenotype change and increase of adhesion molecules allowing direct intercellular contact of interacting cell populations. MSCs are positively capable of acting immunomodulatory through the release of bioactive molecules as well as through direct cell contact [51]. Overall, the ability of MSCs with immunomodulatory properties was observed to contribute to immune system homeostasis and balance in immunological activities. To conclude, CMSCs appear to be a highly promising source of multipotent mesenchymal cells in experiments and therapeutic use.  
Conceptualization, data curation, supervision, and funding acquisition, J.Z. and R.H.; methodology, validation, and project administration, M.T.; software, L.Z.; visualization, G.I.; formal analysis and investigation and writing--original draft preparation, D.B.; formal analysis, K.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Slovak Agency for Research and Development, grant number APVV-17-0278 and the Cultural Educational Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic, grant number KEGA 023 TUKE-4/2020, KEGA 041 TUKE-4/2019, IMTS 2622020185, ITMS2014+ 313011D103 and incentives for research and development Simuly BE 81 3 DP TISSUE.  
The authors thank [PERSON], Head of the Associated Tissue Bank, University Hospital of L. Pasteur Kosice for professional help and support within the project APVV-17-0118.  
The authors declare no conflict of interest.
## 1 Introduction  
Of the 1500 known active volcanoes on Earth, only 35 % are adequately monitored [1]. If and how extensively a volcano is monitored depends on many different aspects: the state of unrest of the volcano, the proximity to any population, the remoteness of the location, and the resources--both financial and in expertise--of the local government or responsible agency. Monitoring is the only way to gain knowledge on the state of the volcano, as magma intrusions and eruptions are usually preceded or accompanied by measurable signals, such as increased seismicity and/or surface deformation. Continuous (real-time) monitoring can help detect such precursory activity and thus aid in the mitigation of volcanic risk. In this paper, we describe the volcano monitoring network of Saba and St. Eustatius, in the Caribbean Netherlands, which started with seismic observations in 2006. We discuss the recent efforts to expand the network with Global Navigation Satellite System (GNSS) observations and temperature measurements of hot springs. We then examine the data quality, characteristics, and performance of the seismic network and finally, we make recommendations for future improvements.
###### Abstract  
This paper deals with a flux-controllable NI HTS flux-switching machine (FSM) for electric vehicle (EV) applications. In a variable-speed rotating machine for EVs, such as electric buses, electric aircraft and electric ships, an electric motor capable of regulating the flux offers the advantage of constant output operation. In general, conventional HTS rotating machines have excellent flux-regulation performance, because they excite an HTS field coil. However, it is difficult to ensure any flux-regulation capabilities in HTS rotating machines using HTS field coils that apply the no-insulation (NI) winding technique, due to the inherent charge and discharge delays in these machines. Nevertheless, the NI winding technique is being actively researched as a key technology for the successful development of HTS rotating machines, because it can dramatically improve the operational stability of HTS field coils. Therefore, research to implement an HTS rotating machine with flux-regulation capabilities, while improving the operating stability of the HTS field coil using the NI winding technique, is required for EV applications. In this paper, we propose an HTS rotating machine with a flux switching structure, a type of topology of a rotating machine that is being actively studied for application to the electric motors used in EVs. The proposed HTS flux-switching machine (FSM) uses NI field coils, but additional field windings are applied for flux regulation, which enables flux control. In this study, an NI HTS field coil was also fabricated and tested because the characteristic resistance value should be used for the design and characteristic analyses of machines which utilize an NI coil. The simulation model used to analyze the flux-regulation performance capabilities of the NI HTS FSM were devised based on the characteristic resistance values obtained from a charging test of the fabricated NI HTS field coil. This study can provide a good reference for further research, including work on the manufacturing of a prototype NI HTS FSM for EV applications, and it can be used as a reference for the development of other HTS rotating machines, such as those used in large-scale wind power generation, where flux-regulation capabilities are required.  
electric vehicle; flux regulation; flux-switching machine; HTS; no-insulation +
Footnote †: journal: Applied Physics Letters
# Radiator Enablers for Wireless Communication Evolution
## 3 Radiators' Novel Technologies, Design, and Implementation Issues
### gMIMO  
#### 3.1.1 General Description  
FR3 gMIMO expands the concept of MIMO for future 6G applications. It is able to use the previously unused upper-mid band, also known as FR3 of the frequency spectrum, to increase the capacity and coverage of existing systems by increasing the number of antenna elements in an antenna array (ref. [27]). Furthermore, in many design cases with a large array size (by operating in the near-field rather than the far-field region of the propagation area of a transmitting antenna array), it is possible to utilize the spherical waves of the near-field region to provide better localization techniques and focus the antenna beam in a more precise manner. Thus, more users can simultaneously use the upgraded network (refs. [27; 28]).
## 2 Experimental
### Electrochemical Tests  
For corrosion resistance evaluation of the obtained samples, electrochemical measurements including polarization curves and electrochemical impedance spectroscopy (EIS). All electrochemical measurements were performed using a CHI604E electrochemical workstation (Shanghai Chenghua Instrument Co., Ltd., Shanghai, China). A three-electrode device was used, with a platinum plate serving as an auxiliary electrode, a saturated calomel electrode serving as a reference electrode, and the test sample serving as a test electrode. The tested sample's exposure area was 1 cm\({}^{2}\). After immersing the sample in the corrosive medium for 30 min, open-circuit potential (OCP) was obtained for experiments.  
Polarization curves were obtained in 3.5 wt % NaCl solutions within a potential range of open circuit potential (OCP) \(\pm\) 250 mV at a scan rate of 1 mV s\({}^{-1}\). The corrosion current density (\(I_{\text{corr}}\)), corrosion potential (\(E_{\text{corr}}\)), and Tafel constant were determined using the extrapolation method. The polarization tests were repeated five times to confirm the dependability of the electrochemical parameters. EIS tests were conducted at open circuit potential (OCP) and the measuring frequency was ranged from 10\({}^{5}\) Hz down to 10\({}^{-2}\) Hz, with a sinusoidal signal amplitude of 10 mV.  
The samples were immersed in the corrosive medium for 30 min prior to the electrochemical tests.
# An Effective Sensor Architecture for Full-Attitude Determination in the HERMES Nano-Satellites
## 3 Sensor Selection  
The sensor selection process was carried out on a pool of COTS sensor components respecting the mass, volume, and power constraints for nano-satellites. Among these elements, the available performance was critically assessed also considering the cost limitations and the electrical and data interfaces' compatibility. Note that the requirements for COTS components came from the cost budget's limitations and from the philosophy driving nano-satellite missions. In this section, the selected sensors are presented with the details of the critical performance and of the analyses that led to their choice.
###### Abstract  
TMS contaminates concurrent EEG recordings with Auditory Evoked Potentials (AEPs), which are caused by the perceived impulsive acoustic noise of the TMS coils. We hereby introduce a novel and perceptually motivated/tuned method for the suppression of auditory evoked EEG artifacts of rTMS under the name of _\"Auditory Fine-Tuned Suppress of TMS-Clicks\" (TMS-click AFFS)_. The proposed method is based on the deployment of a psychophysically-matched wideband noise (WBN) masking stimulus, whose parametric synthesis and presentation are based upon adaptive psychophysical optimization. The masking stimulus is constructed individually for each patient/subject, thus facilitating aspects of precision medicine. A specially designed automation software is used for the realization of an adaptive procedure for optimal parameterization of masking noise level, optimizing both the subject's comfort and the degree of AEP reduction. The proposed adaptive procedure also takes into account the combined effect of TMS intensity level and can as well account for any possibly available subject's hearing acuity data. To assess the efficacy of the proposed method in reducing the acoustic effects of TMS, we performed TMS-EEG recordings with a 60 channel TMS-compatible EEG system in a cohort of healthy subjects (n = 10) and patients with epilepsy (n = 10) under four conditions (i.e., resting EEG with and without acoustic mask and sham TMS-EEG with and without acoustic mask at various stimulus intensity levels). The proposed approach shows promising results in terms of efficiency of AEP suppression and subject's comfort and warrants further investigation in research and clinical settings.  
TMS-EEG; acoustic artifact; AEP suppression Article
# Simulation of Wind Speeds with Spatio-Temporal Correlation
## 2 Methodology
### Modeling
#### 2.1.2 Data Filtering  
There are numerous possibilities of failures during the data collection period. There may be errors due to the meter, communication problems, adverse weather conditions, and others. In all these cases, it is impossible to characterize wind speed at the study points and, as a consequence, to accurately calculate the power that can be generated at each moment.  
To perform the filtering process, it is only necessary to discard invalid and suspicious values, and it is important to avoid removing spaces produced by wrong values so that the chronology of the collected sequences keeps unmodified. Therefore, the value 0 is imposed in all these cases [30].  
Figure 1: Steps in developing the problem, where steps from 1 to 5 correspond to the modeling stage and steps from 6 to 10, to the simulation stage.  
If the data collection height is not the same as that of the study, it is necessary to get the true value of the wind speed [15], and this is achieved by using Equation (1):  
\[v_{h}=v_{s}\left(\frac{h_{h}}{h_{s}}\right)^{\alpha} \tag{1}\]  
where \(v_{s}\) is the wind speed at the study height, \(v_{h}\) is the wind speed of the collected data, \(h_{h}\) is the height of the wind turbine hub, \(h_{s}\) is the height at which data were collected, and \(\alpha\) is the friction coefficient of the terrain.  
On the other hand, to avoid troubles and facilitate calculations, conversion factors are performed to obtain all the units in the international system.
# State of the Art and Trends Review of _Smart Metering_ in Electricity Grids
## 2 Trends of the _Smart Metering_ Systems
### Architecture of a Smart Metering System
#### 2.1.2 Data Concentrator  
The main function of the _DC_ is to gather metering data from the _SM_s. In addition, _DCs_ are usually the master node of a communication subnetwork formed by itself and a set of _SM_s, which implies that they also include an embedded communication node. _DCs_ are usually located inside _Power Transformers_ (_PT_s) and substations. Modern _DCs_ also include additional features such as _low-voltage_ (_LV_) supervision, since they include an embedded _SM_.
## 3 Examples of QS-Based Activities of _Pseudomonas_ spp. Affecting Spoilage of Fish
### QS and Lipolysis  
Fish muscle is characterized by a relatively higher content of lipids that accounts for 16% [4]. _Pseudomonas_ spp. produce lipolytic enzymes that catalyze the hydrolysis of triglycerides to glycerol and free fatty acids, resulting in unpleasant odors related to the development of aldehydes [2]. The lipolytic activity of fish-borne spoilers _Pseudomonas_ spp. was described by [PERSON] et al. [5] and [PERSON] et al. [37]. It has been established that QS-regulated _lipA_ and _lipB_ genes are responsible for fish spoilage [40]. The lipase encoded by _lipB_ is solely responsible for \"lipolytic phenotype\" of _P. fluorescens_, which leads to rancidity, a soapy off-flavor, and other quality defects of fish [41]. _lipA_ is located at the end of a polycistronic operon in the _apr_ gene cluster; its downregulation results in the loss or relatively low lipolytic activity of bacteria [42]. Moreover, studies performed by [PERSON] et al. [43] demonstrated that Lip exporter is regulated by the QS system; its function is essential for lipase secretion. Supplementation of the culture medium with AHLs increased transcription of _lipA_ and _lipB_ of bacteria [44]; the bacteria lost the ability to synthesize lipase since they contained a nonfunctional AHL of the QS system [45].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Microorganism** & **AHL** & **Phenotypes Regulated by QS** & **Reference** \\ \hline _P. aeruginosa_ & 3-oxo-C12-HSL & Pyoverdine production & [33] \\ \hline _P. psychrophilia_ & C4-HSL & Exoenzyme production & [34] \\ \hline _P. fluorescens_, _P. putida_ & 3-oxo-C6-HSL, C6-HSL, C8-HSL, C12-HSL & Proteolytic activity & [34] \\ \hline _Pseudomonas_ spp. & C4-HSL, 3-oxo-C6-HSL, C6-HSL, C8-HSL, C12-HSL & Slime formation & [13] \\ \hline _P. fluorescens_, _P. putida_ & 3-oxo-C6-HSL, C6-HSL, C8-HSL, C12-HSL & Proteolytic activity & [13] \\ \hline _P. fluorescens_ & C4-HSL & Biofilm formation, & [35] \\ \hline _P. fluorescens_ & C4-HSL & Biofilm formation & [19] \\ \hline _P. fluorescens_ & 3-oxo-C14-HSL, 3-oxo-C6-HSL, C4-HSL & Lipolytic activity & [5] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Examples of _Pseudomonas_ spp. phenotypes regulated by AHLs-mediated system.
# Potato Leaf Disease Segmentation Method Based on Improved UNet
## 2 Materials and Methods
### Methods  
#### 2.2.1 UNet Network Model  
The UNet architecture has wide applications in fields such as medical image segmentation and natural image segmentation. Its primary objective is a pixel-wise classification of input images to identify distinct objects or regions. It comprises two crucial components, the encoder and decoder, connected through skip connections, as depicted in Figure 4. This connection mechanism enables the decoder to effectively utilize feature information from different levels of the encoder, thereby enhancing segmentation accuracy [18]. This mechanism's role is to merge shallow and deep-level features, enabling the network to simultaneously learn local and global image information. UNet's design enables outstanding performance, especially in domains with limited data, such as medical imaging [19]. In each downsampling step, the feature dimensions double. Conversely, in the expansion or decoder path, upsampling is employed to reduce the feature dimensions and restore the image size to that of the original input image. Each upsampling step halves the feature  
Figure 3: Annotated Image Examples.  
Figure 2: Data Augmentation Examples.  
dimensions. To ensure the retention of critical details, connections to features from the downsampling path are considered during the upsampling process. Given the limitations of the original UNet architecture concerning the potato leaf disease spot image dataset and the diverse and small morphology of potato leaf disease spots, there is a risk of spatial information loss and incomplete recovery during upsampling. This can result in feature extraction that is blurry and insensitive to edge details in the leaf disease spot regions. Hence, improvements were made to UNet to fully leverage its capabilities and effectively combine shallow and deep-level features [20].
# Improving Landslide Recognition on UAV Data through Transfer Learning
## 5 Conclusions  
At present, UAV remote sensing is widely used, especially in the field of natural disasters and emergency rescue. Comparing it with the traditional methods, UAV has incomparable advantages. However, there are still some problems of poor effect of object detection and automatic information extraction from the remote sensing image. Deep learning methods are a research hotspot for artificial intelligence. In recent years, object detection and information extraction with deep learning has been used in many fields, and significantly improved efficiency.  
This paper focuses on landslide detection. We proposed a fast image-processing method based on UAV data and transfer learning for landslide recognition. The transfer learning method is proposed to overcome the shortcomings of small-sample datasets. We collected the training data by the UAV system and selected three public datasets suitable for scene detection as the source domain data. Comparing with the SSD model and the transfer learning model, the evaluation metrics showed that the transfer learning model outperforms the SSD model.  
For future work, we would like to integrate lightweight model to improve the detection speed. Since disaster relief requires faster response, it would be more efficient if the UAV flight control board could detect landslides in real time instead of data post processing. In addition, the rescue departments can make decisions faster based on the data and deploy forces to carry out disaster relief operations.  
The dataset, on the other hand, is the key for deep learning detection. With the wide application of UAV technology, the UAV remote sensing data is also enriched. The establishment of a public UAV remote sensing dataset will provide a good platform for researchers. We are trying to make some attempts in the field of environment and disaster.  
[PERSON] contributed to the method and the experiments; [PERSON] conducted the data analysis and validation; [PERSON] performed data processing and labeling; [PERSON] wrote the paper. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the Tianjin Natural Science Foundation (18 JCYBJC42300), and the Scientific Research Project of Tianjin Education Commission (2019 KJ143).  
Not applicable.  
The data that support the findings of this study are available from the corresponding author upon reasonable request.  
The authors declare no conflict of interest.