esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion  
The need to utilize a streamlined, quick, consistent, sensitive, and precise process of quantifying MEM trapped in a polymer layer is of utmost importance to analyze its sustained release and the sterilization effect of cobalt 60 gamma irradiation. The drug integration into the coatings and the quantity of drug release from the coatings are two key determinants that can significantly affect the efficacy of MEM. Biodegradable PLGA and CH polymers were used as coatings to fulfil those requirements [31]. Consequently, the present experiment was conducted to quantify the drug release profiles of sterile and non-sterile coated titanium plates using UPLC to evaluate the probability of delayed drug release within the copolymer layer over time. Possessing a locally present antibiotic with delayed release to prevent bacterial colonization on the titanium plate surface may be the answer to reduce and possibly eliminate the need for additional surgery to remove the source of infection. As bacteria that form biofilm are more resistant to antimicrobial treatment than their planktonic counterparts, standard antibiotic treatments are typically ineffective at reducing infection. To date, there are no reasonable methods for eradicating the infection after it has taken place, and hardware removal is frequently the most effective solution. [32; 33; 34]. On day 1, it was noted that all three materials (M, MP, MC) exhibited similar levels of MEM release. However, the sterile group did show a slightly higher level of drug release compared to its non-sterile counterpart. This phenomenon can be explained by the inherent nature of polymeric carriers (PLGA and CH), which are known for their ability to act as a delayed drug release vessel as one of their prominent properties. This observation is supported by previous studies [27]. Additionally, the potential effect of cobalt 60 gamma irradiation on the sterile group cannot be ruled out as a contributing factor to the increased drug release rate. Overall, these findings suggest that the use of polymeric carriers may be a viable option for controlled drug release applications, with careful consideration given to the effects of sterilization techniques. A statistically significant increase of MEM release from MP and MC groups occurred on day 3 and day 7 in both sterile and non-sterile samples. This is attributed to the interaction of the properties of meropenem hydrophilic nature and small molecular size [35] and the hydrophilic properties of CH. This amalgamation of CH nanospheres and MEM showed that the CH matrix would boost the drug encapsulation and retard drug release [36]. That said, PLGA has some of the characteristics of its two monomers, including the extensibility, substantially reduced hydrophobicity, and quicker disintegration of glycolic acid and the sturdiness, hydrophobicity, and slow degradation of lactic acid; thus, it showed delayed drug release on day 3 and 7 compared to day 1 [37]. A 7-day time frame was chosen to allow leeway to combat the biofilm formation ability of different bacteria such as _Staphylococcus aureus_ and _Pseudomonas aeruginosa_[38; 39].
## 1 Introduction
This one is focused on boosting the accuracy of detection while at the same time making the process efficient and at the same time secure in a way that the information being searched will not be altered or the privacy of certain patients compromised. The main objectives of this research are as follows:  
1. Develop an effective feature selection method that uses the Gini index to determine which features are most important for detecting DDoS attacks. 2. Implement Federated Learning to enable privacy-preserving, scalable, and adaptive model training in IoV environments. 3. Evaluate the performance of the suggested approach in terms of accuracy, privacy preservation, and computational efficiency. 4. Compare the effectiveness of the proposed method against traditional centralized methods and other machine learning approaches to highlight the improvements in detection capabilities and operational efficiency. While numerous studies have addressed DDoS attacks within the Internet of Vehicles (IoV) landscape, there remains a need for integrating advanced feature selection methods with privacy-preserving learning frameworks. The following literature review provides an overview of recent developments in the field and identifies the gaps that our proposed methodology seeks to fill. DDoS attack detection operations in an IoV network are shown in Figure 2. It begins with an attacker using a botnet to generate infected traffic in the network for it to be assaulted. The key elements of the system can be classified into vehicles, roadside units (RSUs), and cloud servers, where each of them performs functions of communication and data processing. Within this network, the detection system comprises a traffic monitor, detection algorithm, and response mechanism. This traffic monitor is meant to track the network activity while the detection is being performed on the data for the DDoS attacks. This response mechanism is utilized to counter the attacks once they are detected. In this way, the IoV can be effectively guarded against different kinds of threats, which might be used against the network. Figure 2: IoV network attack detection system. The organization of the paper goes as follows: In Section 2, a critical understanding of previous work in the field is presented, which includes pieces from the literature related to the subject of the thesis; Section 3 justifies the way selected features are transmitted and explains Federated Learning. The results achieved in the experiments are presented in Section 4, and conclusions are drawn in Section 5 of the paper. Finally, Section 6 is the conclusion of the paper with all the recommendations made, which can be attributed to the author. Looking to solve these problems concerning Cybersecurity, this study aims at fortifying the IoV systems as well as bringing up advanced smart transportation.
# Controllable Height Hopping of a Parallel Legged Robot
## 4 Control Strategy
### State Machine Design and Height Measurement  
Each hopping motion period can be divided into three sections with different movement situations. In experiments, we used only the encoder and the current sensor to measure the leg's posture parameters and estimate the robot's state. Figure 6 shows a schematic of the hopping control architecture in three states of one hopping period. In the figure, contact detection was implemented via the toe's position variation, which is deduced from the joint angle. When the leg length is compressed to a specified value, the robot can be considered to have reached the stance phase. The bottom position detection is according to toe's vertical velocity (which has the same absolute value with CoM velocity). When the absolute value of toe velocity is less than a threshold (e.g., 0.01 m/s) for a certain time, the robot could be considered as reaching the bottom position.  
For height measurement in each jump, we used time difference in the flight phase to deduce the actually reached summit height. In the experiments, we measured \(\Delta T\) between adjacent takeoff and touchdown moments, and then used Equation (13), deduced from basic distance calculation formula, to compute the summit height.  
\[h_{smt}=\frac{1}{2}g^{\prime}\cdot\left(\frac{\Delta T}{2}-\frac{\Delta h_{LT }}{g^{\prime}\Delta T}\right)^{2} \tag{13}\]  
where \(\Delta h_{LT}\) is the height difference between the takeoff and touchdown moments, which can be calculated through input virtual coefficient.
## 1 Introduction
The extra PEMS measurement uncertainty compared to the well-established and more accurate legislated method (measurement of bags from a full dilution tunnel) is covered by a margin that determines the conformity factor. The conformity factor defines the maximum allowed emission levels of the vehicles on the road. The comparison between the PEMS and laboratory equipment over a test cycle (called validation test) is a check of the proper setup and functioning of the PEMS. The permissible differences are given in the regulation (e.g., 15% or 15 mg/km for NOx, 10% or 10 g/km for CO\({}_{2}\), whichever is larger). Only a few studies have addressed the differences found between the PEMS and laboratory grade equipment for the latest generation RDE compliant PEMS. Comparisons (validations) of PEMS on the chassis dynamometers with the bags (from the full dilution tunnel with Constant Volume Sampling [CVS]) using various driving cycles were in good agreement in most studies [10, 11, 12]; however, in some cases, the differences were high and exceeded the permissible tolerances [13]. However, none of these studies conducted a detailed analysis using two PEMS simultaneously, by comparing them with both the legislated method and laboratory grade analyzers at the tailpipe. Based on this background, it was deemed important to further evaluate the PEMS measurement uncertainty by direct comparison with laboratory grade equipment. Three different PEMS were evaluated in this work, performing the WLTC and a predetermined RDE cycle under laboratory conditions (lab-RDE) for two different vehicles, one spark-ignition (SI) internal combustion engine powered vehicle and one compression-ignition (CI) vehicle. The results are also compared with the above-mentioned studies [10; 11; 12; 13].
# A Review of Sharp-Switching Band-Modulation Devices  
[PERSON]  
1 IMEP-LAHC, Universite Grenoble Alpes, Grenoble INP & CNRS, 3 [PERSON], CS 50257, CEDEX 1, 38016 Grenoble, France; [EMAIL_ADDRESS] (H.E.D.); [EMAIL_ADDRESS] (K.L.)  
[PERSON]  
2 CEA, LETI, MINATEC Campus, Universite Grenoble Alpes, 17 Rue des Martyrs, CEDEX 9, 38054 Grenoble, France; [PERSON]SS] (J.L.); [PERSON].M.)  
[PERSON]  
2 CEA, LETI, MINATEC Campus, Universite Grenoble Alpes, 17 Rue des Martyrs, CEDEX 9, 38054 Grenoble, France; [PERSON]SS] (J.L.); [PERSON].M.)  
[PERSON]  
3 Nanoletronics Research Group, CITIC-UGR, University of Granada, 18071 Granada, Spain; carlons@ugares.cs (K.N.); fjamiz@ugares (G.C.);  
[PERSON]  
4 State Key Lab of ASIC and System, School of Information Science and Engineering, Fudan University, Shanghai 200433, China; [EMAIL_ADDRESS]  
[PERSON]  
1 IMEP-LAHC, Universite Grenoble Alpes, Grenoble INP & CNRS, 3 [PERSON], CS 50257, CEDEX 1, 38016 Grenoble, France; [EMAIL_ADDRESS] (H.E.D.); [EMAIL_ADDRESS] (K.L.)  
[PERSON]  
1 IMEP-LAHC, Universite Grenoble Alpes, Grenoble INP & CNRS, 3 [PERSON], CS 50257, CEDEX 1, 38016 Grenoble, France; [EMAIL_ADDRESS] (H.E.D.); [EMAIL_ADDRESS] (K.L.)  
[PERSON]  
5 Department of Physics and School of Engineering, Brown University, Providence, RI 02912, USA; [PERSON]#### Abstract  
This paper reviews the recently-developed class of band-modulation devices, born from the recent progress in fully-depleted silicon-on-insulator (FD-SOI) and other ultrathin-body technologies, which have enabled the concept of gate-controlled electrostatic doping. In a lateral PIN diode, two additional gates can construct a reconfigurable PNPN structure with unrivalled sharp-switching capability. We describe the implementation, operation, and various applications of these band-modulation devices. Physical and compact models are presented to explain the output and transfer characteristics in both steady-state and transient modes. Not only can band-modulation devices be used for quasi-vertical current switching, but they also show promise for compact capacitorless memories, electrostatic discharge (ESD) protection, sensing, and reconfigurable circuits, while retaining full compatibility with modern silicon processing and standard room-temperature low-voltage operation.  
nanoelectronics; SOI; FDSOI; electrostatic doping; band modulation; sharp switching; ultrathin body; memory; ESD; sensors; reconfigurable device; Esaki diode +
Footnote †: journal:
# Low-Cost IoT Air Quality Monitoring Station Using Cloud Platform and Blockchain Technology
## 3 Methodology
### Hardware Setup  
The Arduino Uno R3 microcontroller board is based on the ATmega328. A replaceable chip was used as the central execution device. Thanks to its open-source platform, community, and ease of use, we could manage multiple sensors in parallel. The Arduino Uno R3 has general-purpose input/output (GPIO) pins, and numerous peripherals can be connected to them. Its low power consumption and cost made it a suitable controller board for this research, as sensors can be easily connected and used with it, along with Internet connectivity via Wi-Fi using ESP01S, which includes the ESP 8266 Wi FI module. The MQ-135 Gas sensor, the MQ-7 Gas sensor, and the DHT11 temperature and humidity sensor were responsible for the data acquisition of carbon dioxide, carbon monoxide, and temperature and humidity, respectively. This is available in the 3-pin version. This setup was used to collect the measurements of the air quality station and send them via Wi-Fi directly to the cloud solution platform ThingSpeak. The experimental setup is shown in Figures 8 and 9. The hardware implementation of the air quality monitoring station is illustrated in Figure 10.  
Figure 6: Arduino Uno board.  
Figure 7: ESP8266 Wi-Fi module.  
The data collection environment:  
The experimental data were obtained before sunset and sunrise close to the location of the university campus in normal room conditions. The room had fresh air flow and a window overlooking a moderately crowded street. It was connected to a 4 g connection with a download speed of 56.6 Mbps and an uploading speed 15.3 Mbps.  
Figure 8: Experimental setup.  
Figure 10: Hardware implementation of the air quality monitoring station.  
Figure 9: Circuit diagram of the air quality monitoring station.
# Adaptive Network Routing Technology for Near-Moon Space Cross-Domain Transmission
## 5 Conclusions  
The proposed cross-domain network transmission routing method for near-lunar space fully considers the various limitations and characteristics of heterogeneous networks such as the lunar surface, lunar surface, and relay transmission, and establishes a comprehensive hybrid link resource prediction and scheduling model. In order to simplify the research problem, we focus on cross-domain network networking and routing. From the perspective of the near-lunar space system network level, we designed time-varying and fixed topology network subnet clustering methods to reduce the complexity of routing algorithms. Combined with hierarchical routing search, an effective routing scheduling algorithm is proposed. During the experiment and comparison process, attention was paid to the performance of link stability, service latency, and other aspects. The experimental results indicate that our proposed method has significant advantages in solving the problem of cross-domain network transmission in space near the Moon. The link load rate was increased by 31% compared to previous design methods, and the average service delay was reduced by 8%. The link stability and load rate were greatly improved compared to previous designs. In addition, a compromise was made for the communication relay channel and rate limit of the relay satellite, taking into account the established chain time window and communication rate limit. Through simulation verification, the designed method can effectively address these challenges and achieve more efficient network transmission. The method proposed in this article has certain innovation and practicality in the field of cross-domain network transmission in near-lunar space, providing an effective solution for improving the transmission interaction efficiency of the entire heterogeneous network.  
Conceptualization, J.Y. and D.H.; methodology, J.Y. and W.L.; software, J.Y., X.W., Q.X. and X.S.; resources, J.Y. and D.H.; writing--original draft preparation, J.Y.; writing--review and editing, J.Y. and Q.X. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
Dataset available upon request to the authors.  
Conflicts of Interest: [PERSON] was employed by the company China Research and Development Academy of Machinery Equipment. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Hybrid GA-SOCP Approach for Placement and
## 3 Proposed Hybrid GA-SOCP Optimization Approach
### Master Stage: Genetic Algorithm
#### 3.2.4 Recombination  
The recombination is a heuristic procedure where the genetic information of the parents is crossed to generate offsprings. To present this procedure, let us consider two parents that are provided by the selection stage as follows:  
\[W_{i}^{t}=\left[1\ 0\ 1\ 1\ 0\ 1\ 1\ 0\ 0\ 0\ \right] \tag{20}\] \[W_{j}^{t}=\left[0\ 0\ 1\ 0\ 0\ 0\ 1\ 0\ 1\ 1\right]. \tag{21}\]  
Note that, in this example, the each parent has 10 genes (\(n=10\)). To make the recombination it is generate a random number between 1 and \(n-1\). Consider that this number is 6. With this number is make the recombination procedure by adding the first 6 genes of the individual \(W_{i}^{t}\) with the last 4 genes of \(W_{j}^{t}\); in addition, the first 6 genes of the individual \(W_{j}^{t}\) are added to the last 4 genes of \(W_{i}^{t}\). The resulting offsprings (\(\text{Os}_{i}^{t}\) and \(\text{Os}_{j}^{t}\)) are presented below.  
\[\text{Os}_{i}^{t} =\left[1\ 0\ 1\ 1\ 0\ 1\ 1\ 0\ 1\ 1\right], \tag{22}\] \[\text{Os}_{j}^{t} =\left[0\ 0\ 1\ 0\ 0\ 0\ 1\ 0\ 0\ 0\right]. \tag{23}\]
## 2 Theoretical Foundation
### Continuous Wavelet Transform  
CWT provides basis functions with specific time and frequency resolutions to analyze time-varying fault signals. CWT features multi-resolution analysis, where the low-frequency components of the vibration signal have a higher frequency resolution, and the high-frequency components have a higher time resolution. This effectively captures the local time-frequency characteristics of the vibration signal. The equation for CWT is as follows [20]:  
\[W_{x}(a,b)=\frac{1}{\sqrt{a}}\int_{-\infty}^{+\infty}x(t)\psi^{*}\bigg{(}\frac {t-b}{a}\bigg{)}dt \tag{1}\]  
where \(a\) denotes the scale factor, and \(b\) represents the translation factor. In this paper, the Morlet wavelet is chosen as the mother wavelet for the continuous transform.  
Figure 1: Domain adaptation.
## 6 Simulation Results
### Degree Distributions  
For a two-source network with \(n=2\) and \(t=1\), we assume that each source uses \(\mathrm{RSD}(k,c,\
u)\) as its degree distribution \(\Phi_{i}(x_{i})\) with the same parameters \(k=100\), \(c=0.9\), and \(\
u=0.5\). The degree distributions of relays are set up as \(\Gamma_{1}(x)=0.8x+0.2x^{2}\) and \(\Gamma_{2}(x)=x\). Figure 4a,b compare the theoretical overall degree distributions \(\Omega_{i}(\overset{\rightharpoonup}{x})\) and the actual overall degree distributions obtained from the simulations, and Figure 4c depicts the absolute values of errors between them. Since the values of degree distribution are mainly located at small degrees, we only depict the distributions for degrees below 50. As shown in Figure 4, the actual overall degree distributions are basically the same as the theoretical ones. The errors between them are less than \(3\times 10^{-4}\), and the mean square errors of \(\Omega_{1}(\overset{\rightharpoonup}{x})\) and \(\Omega_{2}(\overset{\rightharpoonup}{x})\) are \(3.67\times 10^{-7}\) and \(2.28\times 10^{-7}\), respectively. It reveals that the simulated overall degree distributions are consistent with the theoretical ones, which verifies the analysis and derivation in Section 4.1.  
Figure 4: (**a**) The comparison of theoretical values and simulated values of the overall degree distribution \(\Omega_{1}(\overset{\rightharpoonup}{x})\); (**b**) the comparison of theoretical values and simulated values of the overall degree distribution \(\Omega_{2}(\overset{\rightharpoonup}{x})\); (**c**) the absolute values of errors between theoretical and simulated overall degree distributions.  
Setting \(m=1000\), \(\delta=0.01\), and initial degree distribution RSD(100, 0.9, 0.5) for each source, Table 1 shows the optimized degree distributions for different values of source number \(n\) by using the joint iterative optimization method in Section 5 with only one iteration. Note that \(\Phi_{2}(x_{2})=\Phi_{3}(x_{3})\) when source number \(n=3\), and \(\Phi_{1}(x_{1})=\Phi_{2}(x_{2})\), \(\Phi_{3}(x_{3})=\Phi_{4}(x_{4})\) when \(n=4\). For simplicity, we only give the values greater than 0.005 in Table 1.
## 1 Introduction
Furthermore, we recorded ongoing changes in skin conductance level (SCL) and heart rate (HR) to define states of arousal related while being exposed to different environments. [PERSON] and associates [21-23] extensively demonstrated the modulation of the startle reflex to a sudden acoustic probe (white noise delivered through headphones) by ongoing emotional states. Emotional states have mostly been elicited using pictures as lead stimuli [22] although some studies demonstrated startle reflex modulation using more complex stimuli such as music [24], film-clips [25], odors [26] and food [27]. Pleasant states diminish the startle response while it is enhanced in an aversive state. According to [PERSON] and colleagues [22] emotions are organized around the two strategic dimensions valence and arousal. Internal and environmental stimuli induce an affective state along these dimensions which guides subsequent behavior within a particular environment by priming according reflexes. More concretely, this implies that a place that makes us feel uneasy would automatically enhance defensive reflexes such as startle or flight in response to sudden stimuli while a place that makes us feel comfortable and safe would foster an appetitive behavioral repertoire including procreation and nurturance while the exact reason for this emotion might be outside awareness which seems in accordance with subjective experience. The present study makes use of the StreetView tool of Google Maps, an interactive internet mapping service. StreetView is a novel feature of Google Maps which allows for 360\({}^{\circ}\) panoramic views on the street level. Subjects can look around at whatever they are interested in by making use of the 360\({}^{\circ}\) panoramic feature thus allowing for an experience more alike being at the actual place than photographs or VR models could. Furthermore, we draw on an external criterion-the median real estate price of a given urban area-as an indicator of valence. Average real estate price is thought to be influenced in part by the affective evaluation of a neighborhood by the city's inhabitants. The exact mechanisms determining a neighborhood's real estate price are certainly more complex, involving aesthetic, social, infrastructural and other variables. Nevertheless, these variables might be partially accessible through StreetView, as subjects can not only view physical features like building exteriors but also environmental aspects such as signs of deterioration, the type of people present in the scene _etc_. which might serve as indicators for latent social and infrastructural characteristics. Thus we hypothesize that the more expensive areas do not only cause higher ratings of pleasantness but also an attenuated startle reactivity as indicated by the eye-blink EMG.