esa-sceva/satcom-chunk-collection huggingface dataset:
# Decorrelation-Based Deep Learning for Bias Mitigation
## 4 Results
### Gender-Biased Adult Dataset  
The UCI adult dataset is used to classify income levels and we consider gender as bias. We use the same evaluation metrics as defined in Section 4.2.2 and compare with the same existing mitigation methods mentioned in Section 4.2.3 on a holdout testing dataset for the gender-biased adult dataset. We also compare the performance of our model with the method of fusion introduced in [34]. Authors used the fusion of different combinations of existing bias mitigation methods such as Disparate Impact Remover (DIR) [31], Adversarial Debiasing (Advers-Debias) [13], and Calibrated Equalized Odds (CEO) [35] to provide end-to-end bias mitigation. We use their best method for the comparison.  
The results for each method are displayed in Table 3. The results show that the DcANN model achieves the lowest EOD and AOD and highest DI amongst all methods while the balanced accuracy slightly decreases. The SPD and EOD scores of Adversarial Debiasing are almost similar to the DcANN method. However, as it is seen in the German dataset case, Adversarial Debiasing helps to reduce bias but at the cost of a significant reduction in the accuracy. The fusion model (IR + Advers-Debias + CEO) has the lowest SPD and highest accuracy but it does not perform well on other fairness metrics. Thus, the results suggest that DcANN reduces bias fairly by achieving good results on almost all fairness metrics without significantly compromising balanced accuracy.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Methods** & **SPD** & **EOD** & **AOD** & **DI** & **BA** \\ \hline Baseline & \(-0.3162\) & \(-0.318\) & \(-0.2876\) & \(0.3112\) & \(0.6534\) \\ Reweighing & \(-0.2049\) & \(-0.2318\) & \(-0.2016\) & \(0.6229\) & \(0.6687\) \\ Optimized pre & \(-0.0351\) & \(0.0254\) & \(-0.0639\) & \(0.9421\) & \(0.6872\) \\ Advers-Debias & \(0.0713\) & \(0.0393\) & \(0.0931\) & \(\mathbf{1.0834}\) & \(0.6633\) \\ B-DcANN (\(\lambda=0\)) & \(-0.1491\) & \(-0.1\) & \(-0.0642\) & \(0.7798\) & \(0.7262\) \\
**DcANN** & \(\mathbf{-0.03144}\) & \(\mathbf{-0.03918}\) & \(\mathbf{0.06223}\) & \(\mathbf{0.95927}\) & \(\mathbf{0.7093}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Fairness scores and Balanced accuracies of predictions for age-biased German dataset for different methods.
# A Novel Multi-Cell Interference-Aware Cooperative QoS-Based NOMA Group D2D System
## 4 Numerical Results
### Impact of \(M_{1}\) and \(R_{e}\) on Outage Probability  
The impact of varying the number of users in Phase I while varying the number of relays is investigated in Figure 3. The Monte-Carlo simulation was carried out to verify the analytical expression of the outage probability. The simulation and analytical results are in good agreement, validating the performance analysis. Results clearly show that increasing  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Parameter** & **Description** & **Value** \\ \hline \(M_{1}\) & Number of users in Phase I & 2 \\ \(M_{2}\) & Number of users in Phase II & 2 \\ \(N_{R_{e}}\) & Number of relays & 2 \\ \(\{\mathrm{B}_{j}\}_{j=1}^{M_{1}}\) & Users’ rates in Phase I & \{0.7, 1.2\} \\ \(\{\mathrm{B}_{j}\}_{j=1}^{M_{2}}\) & Users’ rates in Phase II & \{0.5, 1.1\} \\ \(c\) & Radius of coverage area & 10 m \\ \(\alpha\) & Path loss exponent & 4 \\ \(\lambda_{GTx}\) & Intensity of group transmitters & \(10^{-4}\) \\ \(d_{1}\) & Distance of group transmitter from relay in Phase I & 9 m \\ \(d_{2}\) & Distance of group transmitter from relay in Phase II & 8 m \\ \(P\) & Degree of Gauss–Laguerre polynomial & 5 \\ L, N, V, Q, S & Gaussian–Chebyshev parameters & 5 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters.  
Figure 2: Outage probability comparison of proposed Q-CNOMA with C-NOMA, Q-NOMA, NOMA and OMA.  
the number of users in a cell with NOMA transmission would increase the average outage probability of the system. However, it can be observed that increasing the number of relay nodes would improve the performance of the system.
## 3 Results and Discussions
### Reusability of the Sorbent  
Regeneration is one of the key factors for the evaluation of the performance of an adsorbent. For this purpose, the analytes were desorbed with 1.5 M nitric acid twice, and they were not detected at the second elution fraction, indicating no carry over after the elution step. Accordingly, the reusability of the sorbent was examined. The 10% recovery loss criterion was employed to evaluate the reusability of the sorbent. The loss of the initial recovery was less than 10% for all metals, as it can be observed in Figure S2. Compared with the initial values, the recovery after 10 cycles of adsorption and desorption was between 98.3 and 108.9%. As a result, with the use of 1.5 M nitric acid as eluent and distilled water (2 \(\times\) 10 mL) as washing agent, the NaGO sorbent can be reused more than 10 times. The addition of water after the acidic elution is important in order to remove traces of nitric acid possibly remaining at the surface of the material, that can alter the pH value of the adsorption solution.
## 1 Introduction
Finally we justify the application of VSN in different area such as in the battlefield scenario, in monitoring rock slides and animal crossing within a mountainous terrain, in designing and monitoring smart houses, structural mentoring, healthcare, vehicle telematics, agricultural monitoring and industrial monitoring. In the above mentioned application areas, the concept of VSN can be used to make the system cost effective. Although the application of VSN in a few of the areas such as agricultural monitoring may not be cost effective and suitable at present, with the evolution of the agricultural revolution it will be deemed appropriate in the near future. The main contributions of this paper are as follows:  
1. We have proposed a novel business model of virtualization of sensor networks. 2. We have surveyed the virtualization sensor networks in WSNs. 3. We have discussed the design goals of virtualization technology in wireless sensor networks. 4. We have studied and summarized the contemporary sensor network virtualization projects. 5. We have figured out the challenges and opportunities of virtualization in WSNs. 6. Finally we have depicted future research scopes and few major application areas of VSN. The remainder of the paper is organized as follows: Section 2 reviews the background related to virtual sensor network overlay sensor networks, VSN and its business models and the existing protocols to support VSN. In Section 3 we discuss VSN design, which consists of the design goals and challenges behind VSN. Section 4 describes related works and a few contemporary sensor network virtualization projects. Section 5 discusses a few opportunities provided by VSN. Section 6 depicts the typical application areas related to VSN. Section 7 focuses on some discussions that include available solutions, future research scope, open issues and finally Section 8 concludes the paper.
# A Novel NODE Approach Combined with LSTM for Short-Term Electricity Load Forecasting
## 4 Data and Methodology
### Forecasting Models  
The first group of comparative models includes ODE-CNN-BiLSTM-LSTM (OCBL) and CNN-BiLSTM-LSTM (CBL). CBL mainly consists of Conv1D layer, BiLSTM layer, and LSTM layer. OCBL is based on the CBL model, and an NODE layer is added in front of the Conv1D layer. Conv1D is a convolution layer generally used in series processing, which performs well in feature extraction. The model structures of OCBL and CBL are shown in Figure 6.  
Figure 5: The schematic diagram of the sliding window.  
The second group of comparative models is ODE-BiLSTM-stacked LSTM (OBLL) and BiLSTM-stacked LSTM (BLL). BLL combines one BiLSTM layer and two LSTM layers, and OBLL adds an NODE layer in front of the BiLSTM layer. The model structures of OBLL and BLL are shown in Figure 7.  
Figure 6: The model structures of OCBL and CBL.  
Figure 7: The model structures of OBLL and BLL.  
The last group of comparative models are ODE-stacked BiLSTM-stacked LSTM (OBBLL) and stacked BiLSTM-stacked LSTM (BBLL). This group is similar to the second group and the difference is that a BiLSTM layer is added in front of the original BiLSTM layer. The structures are shown in Figure 8.
## 3 Result and Discussion
Typically in the OLED device structure of glass/ITO/printed-PEDOT:PSS (\(w\)/EtOH 0%, 40%, 90%)/CBP:Ir(mppy)\({}_{3}\) (10% doped)/TPBi/LiF/Al, the turn on voltage is approximately 4 V. However, as seen in Figure 4a,b, the device samples fabricated by the nozzle printing process shifted to relatively higher voltage because the nozzle printing process had poor overall film uniformity compared with the spin-coating process. Figure 4c shows the current density-luminance data. As seen in the graph, when the EtOH percent was increased, a high value of luminance was shown in the same current density scale. The OLED device based on PEDOT:PSS with EtOH of 90% had 35,000 cd/m\({}^{2}\) maximum luminance at 300 mA/cm\({}^{2}\), and the OLED devices based on PEDOT:PSS with EtOH of 0% and 40% recorded values of about 17,000 cd/m\({}^{2}\) and 25,000 cd/m\({}^{2}\) at 300 mA/cm\({}^{2}\), respectively. Lastly, in Figure 4d, maximum current efficiency of 35 cd/A was recorded in the device sample of PEDOT:PSS-EtOH (90%) while PEDOT:PSS-EtOH (0%, 40%) showed values of 5 cd/A and 15 cd/A. This difference was caused by the film uniformity of the PEDOT:PSS layer with variation of the EtOH concentration. When a greater amount of EtOH (about 90%) was added to the PEDOT:PSS solution, spreading, shrinking, and drying behaviors were optimized for the formation of a uniform film layer. Figure 5 presents electro-luminescence (EL) camera images of individual device samples with voltage variation. The OLED device in Figure 5a was fabricated with pristine PEDOT:PSS and those in Figure 5b,c were made with PEDOT:PSS with 40% and 90% EtOH solvent. With bias voltage of 3.5, EtOH of 90% based pixel in OLED showed a clear green light image whereas non-uniform light with a defect pattern was observed for both pristine PEDOT:PSS and EtOH of 40% including in PEDOT:PSS based pixel. Figure 3: (**a**) Profile data of PEDOT:PSS patterns with including EtOH rate of 90% by measuring of SEM and scaling of Grey scale method. SEM cross-sectional (**b**) and top-view (**c**) images of PEDOT:PSS pattern. Figure 4: Organic light emitting diode (OLED) device performance graph of (**a**) Current Density-Voltage; (**b**) Luminance-Voltage; (**c**) Luminance-Current density; and (**d**) Current Efficiency-Luminance. Figure 5: Electro-luminescence (EL) images of OLED with various conditions of solvent ratio and voltage variations: (**a**) pristine PEDOT:PSS based EL image; (**b**) EtOH of 40% containing ratio in PEDOT:PSS based EL image; and (**c**) EtOH of 90% containing ratio in PEDOT:PSS based EL image.
# Clustering Approach for Reliable Wireless Communication
## 4 Results and Discussion  
This section outlines the simulation results. The performance of the system was evaluated by computing the BER variation with the SNR in different scenarios, and the improvement brought by the clusters division approach was highlighted. The simulations for a negative SNR were considered relevant for the system's behavior in a very noisy environment. The six types of scenarios are highlighted in Table 3.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline FFT length & 128 \\ Data subcarriers & 72 \\ SC spacing & 15 kHz \\ FFT sampling frequency & 15 kHz \(\times\) 128 = 1.92 MHz \\ Subcarrier indexes & \(-\)36 to \(-\)1 and 1 to 36 \\ OFDM symbol duration & 1/15 kHz = 66.7 μs \\ CP duration & 4.76 μs \\ Total symbol duration & 71.43 μs \\ \hline \hline \end{tabular}
\end{table}
Table 2: OFDM setup parameters.
# Band-Pass Sampling in High-Order BOC Signal Acquisition
## 5 Conclusions  
In this paper, the band-pass sampling technique for multiple signals is introduced to BOC signals to reduce the computational complexity. Using this technique, the sampling frequency is reduced significantly and only two secondary peaks remain in the ACF of the sampled signal. An acquisition  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Proposed** & **Dual-Side Band** & **Match Filter** \\ \hline \(f_{s}\) & 12.7875 MHz & 12.7875 MHz & 71.61 MHz \\ \hline Complexity & \(\frac{2\Delta t\cdot T_{p}}{T_{c}}\times 12.7875\times 10^{6}\) & \(\frac{2\Delta t\cdot T_{p}}{T_{c}}\times 12.7875\times 10^{6}\) & \(\frac{4\Delta t\Delta\cdot T_{p}}{nT_{c}}\times 71.61\times 10^{6}\) \\ \hline Ratio against proposed & 1 & 1 & 67.2 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Computational complexity.  
Figure 8: Frequency and time search results for BOC(15,2.5).  
method based on dual-loop structure is also proposed to remove the ambiguity completely and to compensate the subcarrier Doppler. The detection probability and computational complexity are analysed. The detection performance of the proposed method degrades a little compared to the match filter method, but nearly the same as DSB method. The computational complexity is assessed by the number of multiplies and adds required for the acquisition process. When the sampling frequency is 12.7875 MHz, the multiplies and adds required are 1/67.2 of the match filter method.  
This research was funded by National Natural Science Foundation of China, grant number 61601485.  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, and in the decision to publish the results.
## 6 Discussion  
Let us now discuss the theoretical and practical aspects of the proposed approach.  
An analysis of well-established approaches to implementing Montgomery multiplication in RNS reveals that two primary methods for computing the rank--an essential step in performing the critical base extension operations--are commonly employed [8; 9; 12; 14; 15; 16; 17].  
The first method enables the determination of the integer value of an RNS number by computing an integer correction factor, which essentially corresponds to the rank of the number. In this case, the implementation of the CRT yields an exact integer reconstruction. This approach involves the inclusion of an additional redundant modulus \(m_{k+1}\), which depends on the number \(k\) of primary RNS moduli, into the original moduli-set \(\{m_{1},m_{2},\ldots,m_{k}\}\).  
As a result, this method requires an additional modular channel with a width of \(\lfloor\log_{2}k\rfloor+1\) bits, along with redundant lookup tables.  
The main idea of an alternative approach is to represent the rank as the integer part of a sum of at most \(k\) proper fractions of the form \(\chi_{i,k}/m_{i}\), where \(i=1,2,\ldots,k\). The rank value is then estimated recursively by approximating these fractions. To eliminate division by the modulus \(m_{i}\), each denominator \(m_{i}\) is replaced by a power of 2, and the corresponding numerator \(\chi_{i,k}\) is approximated using its most significant bits. Since division by powers of 2 is equivalent to simple bit shifts, the rank computation is reduced to a sequence of additions.  
The main drawbacks of this method are as follows. First, it relies on recursive computations, as the algorithm evaluates the rank value in a sequential, bit-by-bit manner. Moreover, the number of required iterations depends on the bit length used for the approximation. As a result, this method leads to significantly prolonged computation times when dealing with large numbers. Additionally, due to the approximate nature of the algorithm, it does not always produce the correct rank value.
## 3 Results and Discussion
### Influence of Studied Saponins on Cell Viability
#### 3.1.3 Antiproliferative Activity of Saponins in Hep-2 Cells  
The MTT testsults for the analyzed standard saponins in Hep-2 tumor cells indicated that \(\alpha\)-hederin induced the most potent antitumoral effect (Figure 2). At a concentration of 2 \(\mu\)g/mL, \(\alpha\)-hederin was biocompatible in NCTC cells (99% cell viability), while in Hep-2 tumor cells cultivated in medium, it was antiproliferative (51% viability) after 24 h of treatment.  
The MTT assay results for hederagenin tested in Hep-2 cells cultivated in a FBS-free medium exerted a moderate cytotoxicity activity at 25-300 \(\mu\)g/mL and strong cytotoxicity at 400 \(\mu\)g/mL (52% cell viability). In cells cultivated in a medium with FBS, it was observed that hederagenin had no significant antitumor activity, with the viability of Hep-2 tumoral cells exceeding 80% within the entire range of concentrations (2-400 \(\mu\)g/mL).  
Hederacoside C was biocompatible within the entire range of concentrations (2-400 \(\mu\)g/mL), with no significant antitumoral effect when cultivated in medium with or without FBS (Figure 2).  
Our study confirmed that saponins tested in the medium containing FBS presented very low antiproliferative activity. Hederagenin in the medium with FBS did not present any cytotoxicity in Hep-2 tumor cells, compared to the experiment in medium without FBS.  
The antitumor activity of standard saponins was also calculated as the inhibitory concentration of compounds that killed 50% of cells (IC\({}_{50}\), \(\mu\)g/mL). The results are presented in Table 1.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Standard**} & \multicolumn{2}{c}{**IC\({}_{50}\) (\(\mu\)g/mL)**} \\ \cline{2-3}  & **Hep-2 MEM** & **Hep-2 MEM + FBS** \\ \hline \(\alpha\)**-Hederin** & 2 & 25 \\
**Hederagenin** & 413 & \(>\)500 \\
**Hederacoside C** & \(>\)400 & \(>\)400 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Values of IC\({}_{50}\) determined for the saponins cultivated in Hep-2 cell. Culture cultivated in medium with and without fetal bovine serum (FBS).  
Figure 2: _In vitro_ cytotoxicity of standard saponins (\(\alpha\)-hederin, hederagenin and hederacoside C) tested in fibroblasts cells (NCTC) and tumoral cells (Hep-2) tested in MEM culture medium or MEM supplemented with FBS (MEM + FBS), determinated by MTT assay. The values represent mean \(\pm\) SD (n = 3), \(p\)\(<\) 0.01.  
\(\alpha\)-Hederin presented the lowest value of IC\({}_{50}\) in Hep-2 cells in the medium without FBS (2 \(\mathrm{\SIUnitSymbolMicro\text{$\SIUnitSymbolMicro\text{$\SIUnitSymbolMicro \SIUnitSymbolMicro\text{$\SIUnitSymbolMicro\text{$\SIUnitSymbolMicro\text{$\SIUnitSymbolMicro \SIUnitSymbolMicro\text{$\SIUnitSymbolMicro\text{$\SIUnitSymbolMicro\text{$\SIUnitSymbolMicro \text{$\SIUnitSymbolMicro\text{$\SIUnitSymbolMicro
Variability in the Control of Type 2 Diabetes in Primary Care and Its Association with Hospital Admissions for Vascular Events. The APNA Study  
[PERSON]  
1  
[PERSON]  
2 Department of Health Sciences, Public University of Navarra (UPNA), 31008 Pamplona, Navarra, Spain; ablm4@[EMAIL_ADDRESS] (A.B.-L.); [EMAIL_ADDRESS] (L.A.-O.)  
[PERSON]  
2 Department of Health Sciences, Public University of Navarra (UPNA), 31008 Pamplona, Navarra, Spain; ablm4@[EMAIL_ADDRESS] (A.B.-L.); [EMAIL_ADDRESS] (L.A.-O.)  
[PERSON]  
2 Department of Education, Hospital Universitario de Navarra, 31008 Pamplona, Navarra, Spain; [EMAIL_ADDRESS] (L.A.-O.)  
[PERSON]  
3 Department of Education, Hospital Universitario de Navarra, 31008 Pamplona, Navarra, Spain; [EMAIL_ADDRESS] (A.B.-L.); [EMAIL_ADDRESS] (L.A.-O.)  
[PERSON]  
4 Instituto de Investigacion Santaria de Navarra (diSNA), 31008 Pamplona, Navarra, Spain; dellen.  
BP control and LDL-C can be used for evaluating T2D follow-up because of their association with cardiovascular events (CVEs) [19; 20]. Guidelines recommend maintaining BP \(<\) 140/90 mg/dL and LDL-C levels \(<\) 100 mg/dL [2; 4]. Despite pharmacological advances and new devices for treating and controlling T2D, clinical practice still varies.  
There is variability among countries, regions, and physicians who monitor T2D patients Patient care influences risk factors, control, and treatment compliance [21; 22; 23; 24]. The evolution of quality indicators in patients with T2D has been evaluated, including complications such as foot ulcers, amputations, and retinopathy [25; 26]. However, little has been studied regarding their influence on the development of CVEs. It is interesting to know the level of compliance achievable. Reaching full compliance with the indicators does not depend solely on the measures proposed by doctors. There are factors that they cannot control and that sometimes rely on their patient's adherence to treatment.  
Primary health care centers (PHCCs) care for T2D patients in Spain. All PHCCs belong to an administrative unit, a health area with an assigned referral hospital. In Navarra, there are three health areas (Pamplona, Tudela, and Estella). PHCCs coordinate with their referral hospital or outpatients' endocrinology services in complex patients. Interventions in health centers aim to treat and control the disease and act on modifiable factors, following the recommendations of the different scientific societies [2; 4; 20].  
In Navarra, PHCCs use a computerized medical records system, which was implemented in 2004 and has been in general use since 2012. Our study is part of the \"APNA Study\" (Navarra Primary Care Study). This prospective multipurpose cohort analyzes data from the computerized medical record registry of Navarra. Many studies are conducted with the data from this registry, which endorses the data quality in terms of T2D [27; 28; 29; 30].  
This study aimed to analyze how the variability of the control of HbA1c influences hospital admissions for CVEs.
## 3 Classification of UAVs
\begin{table}
\begin{tabular}{c l l} \hline \hline
**Categories** & **Strengths** & **Weak Points** \\ \hline \multirow{3}{*}{Single-rotor} & Heavy payload & \\  & Flight time & Mechanical system \\  & Hovering flight & Rotor size \\  & VTOL & \\ \hline \multirow{3}{*}{Multi-rotor} & Hovering flight & \\  & VTOL & \\  & Velocity & Flight time \\  & Agile maneuverability & \\  & Confined-space flying & \\ \hline \multirow{3}{*}{Fixed-wing} & Flight time & Complex aerofoil \\  & High Velocity & Limited payload \\  & Large-area coverage & No hovering flight \\  & Limited maneuverability \\ \hline \multirow{3}{*}{Hybrid} & Flight time & \\  & Hovering flight & Very expensive \\  & VTOL & Unstable transition mechanism from \\ \cline{1-1}  & Agile maneuverability & horizontal to vertical flight \\ \cline{1-1}  & Velocity & \\ \cline{1-1}  & Large-area coverage & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparative study of UAVs: advantages vs. disadvantages. The last class of UAVs is mainly used for military purposes. The large UAVs have a wide range and endurance. Furthermore, their designs are usually based on a fixed-wing structure, which allows them to carry heavy payloads over long distances while reaching a maximum altitude of 5.5 km. Some examples of these UAVs are the Czech Primoco UAV One 150 ([[https://uav-stol.com/primoco-uav-one-150/](https://uav-stol.com/primoco-uav-one-150/)]([https://uav-stol.com/primoco-uav-one-150/](https://uav-stol.com/primoco-uav-one-150/)), accessed on 15 March 2023) and the Chinese Feng Ru 3-100 ([[https://ev.buaa.edu.cn/info/1133/3165.htm](https://ev.buaa.edu.cn/info/1133/3165.htm)]([https://ev.buaa.edu.cn/info/1133/3165.htm](https://ev.buaa.edu.cn/info/1133/3165.htm)), accessed on 15 March 2023). Primoco is designed to fly for 15 h. It can carry a payload of 50 kg and has a radio range of 200 km. Feng Ru is designed for couriers; it has a wingspan of 19.6 m and can fly for 5 days. Currently, there is no standard classification of UAVs. In the case of this study, we have focused on size. However, other important parameters can be considered, such as autonomy, speed, range, altitude, and payload capacity.