esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract
A sufficiently wideband linear TIA is thus required to amplify this signal, which can then be demodulated by a high-speed envelope detector, avoiding in this way expensive and power-hungry digital signal processing (DSP) blocks. A clock and data recovery (CDR) circuit at the end of the receiver combines the detected signals for both polarizations. In [10], a quasi-coherent receiver was proposed achieving a sensitivity of \(-35.2\) dBm (BER = 1 \(\times\) 10\({}^{-3}\)) at a 10 Gbps data rate. Polarization diversity and transmission with a standard single-mode fiber (SSMF) up to 40 km were demonstrated with negligible penalties. More recently, transmission up to 40 km was reported at 25 Gbps, with a back-to-back receiver sensitivity of \(-20\) dBm (BER = 5 \(\times\) 10\({}^{-5}\)) and a 6.3 dB penalty for 40 km SSMF transmission [11]. In all cases, however, system demonstrations relied on costly wideband packaged photodetectors, preventing a more practical and cost-contained system implementation. In this article, we report the design and testing of a high-speed linear TIA enabling highly integrated quasi-coherent receivers at 10 and 25 Gbps data rates. The TIA shares the same 130 nm SiGe BiCMOS platform as that of an already existing high  
Figure 1: Block diagram of a quasi-coherent receiver architecture with polarization diversity. speed envelope detector block, aiming towards future integration of both functionalities into a single chip. A maximum differential transimpedance of 68 dB\(\Omega\) was measured, with a 3 dB response in the range of 5 to 50 GHz, and a maximum differential output swing of 896 \(mV_{pp}\) at the 1 dB compression point. We moreover report, for the first time, a quasi-coherent receiver based on a discrete vertical PIN photodiode (PD). A receiver sensitivity of \(-\)30.5 dBm and \(-\)26 dBm (BER = 1 \(\times\) 10\({}^{-3}\)) is demonstrated at 10 and at 25 Gbps, respectively. The following sections review the circuit design aspects, chip measurements, and the performed system experiments evaluating the TIA performance within a quasi-coherent receiver.
## 6 Future Research Directions
### Stability and Power Efficiency  
When there is a temporary blockage, DL can adaptively reconfigure traffic among integrated access and backhaul (IAB) nodes to keep the link stable. In 5G mobile, preserving battery life is a top priority. Power can be saved by minimizing processing demands at the receiver. The potential of DL in the realm of power efficiency is worth investigating.
## 4 Security Attacks
### Network Layer
#### 4.2.2 Eclipse Attack  
An eclipse attack [27; 29; 30; 32; 42] aims to isolate a targeted node by monopolizing its peer connections. In this attack, the adversary gains control over a large number of IP addresses and replaces the legitimate entries in the target node's address table. When the target node restarts, it connects exclusively to these malicious nodes, effectively isolating it from the rest of the network. As a result, the attacker can feed the victim false blockchain data and manipulate its view of the network.  
Figure 3 illustrates the process of an eclipse attack, a type of network-layer threat in blockchain systems where an attacker isolates a victim node from the rest of the network. The attack begins with malicious nodes that aim to cut off a victim node from the legitimate peer-to-peer network (top left). This is done by disconnecting the victim from honest peers, leading to the isolation of the victim (middle left). Once isolated, the attacker surrounds the victim with only malicious nodes and begins to send fake information (top right). Since the victim is now cut off from trustworthy sources, it relies entirely on the attacker-controlled nodes for blockchain data. As a result, the victim node is misled into accepting fake blockchain information, such as false transaction histories or manipulated block data. This can have serious consequences, including enabling double-spending or censoring transactions. The diagram clearly shows how isolation and misinformation are used together to compromise the victim's view of the blockchain.
# Combined Channel Estimation with Interference Suppression in CPSS
## 1 Introduction
While the channel estimation and interference suppression are implemented separately, the computational complexity is linear stacking in the signal detection, which increases the processing delay and the cost of hardware. Although there is some research named joint interference suppression and channel estimation, the technical relevance of conquering the two issues is not remarkable [18; 19; 20]. For the low-power and resource-constrained nodes in CPSS, few of the existing approaches can sufficiently conquer the issues of computational complexity, narrowband interference (NBI) and transmission fading simultaneously [21]. Inspired by the machine learning technology for channel estimation, the study aims to integrate interference suppression into channel estimation based on machine learning. The rest of this manuscript is organized as follows: Section 2 presents the signal model in complex electromagnetic environment. Section 3 proposes the scheme of channel estimation with interference suppression. Section 4 describes the complexity analysis as well as the simulation results. Section 5 presents the application of the proposed scheme. The conclusions and future work are presented in Section 6.
## 7 Performance Evaluation and Simulation Results
#### 7.2.1 Low Social Media Interaction. Node's Density = 100 Nodes/km\({}^{2}\)  
In Figure 8 we can see a percentage of packet losses between 20% and 24% for \(0\leq w_{TS}\leq 1\). Again, there is no much variation in the packet losses when we vary the  
Figure 5: Average end-to-end packet delay. Scenario with very low social media interaction (TS normal distribution with \(\mu=1\) and \(\sigma=1\)). Nodes’ density = 100 nodes/km\({}^{2}\).  
Figure 6: Percentage of packet losses and average tie strength of the forwarding path. Scenario with very low social media interaction (TS normal distribution with \(\mu=1\) and \(\sigma=1\)). Nodes’ density = 200 nodes/km\({}^{2}\).  
Figure 7: Average end-to-end packet delay. Scenario with very low social media interaction (TS normal distribution with \(\mu=1\) and \(\sigma=1\)). Nodes’ density = 200 nodes/km\({}^{2}\).  
weight \(w_{TS}\), since the TS values between pairs of neighbors are low. Consequently, the measured \(\overline{TS}\) of the established forwarding paths is low and quite stable for any \(w_{TS}\) (around 1.8, see blue line in Figure 8). A suitable value for \(w_{TS}\) could be 0.4, with a 21% of packet losses, an average confidence measured \(\overline{TS}\) = 1.8 and an average packet delay of 0.76 s.
## 3 MPC Controller Design and Longitudinal Speed Compensation
### Longitudinal Speed Compensation
#### 3.4.4 Asymptotic Stability of MPC Control System  
To prove the asymptotic stability of closed-loop discrete system formed by Equation (8), we assume the final target can be achieved, which is the error between the final predicted output and reference states become zero. The Lyapunov function \(V({\rm x}_{k})\) is defined by the objective function formed by Equation (12) at the sample time \(k\)[38; 39], which can be expressed as  
\[V(x_{k})=\sum_{i=1}^{Np}y_{k+i}^{T}Q_{1}y_{k+i}+\sum_{i=1}^{N_{\rm c}}\Delta u _{k+i}^{T}R_{1}\Delta u_{k+i} \tag{33}\]  
where \(Q_{1}\) and \(R_{1}\) are the nonnegative weighting coefficient.  
The Lyapunov function \(V({\rm x}_{k+1})\) at the next sample time \(k+1\) can be expressed as  
\[V(x_{k+1})=\sum_{i=1}^{Np}y_{k+1+i}^{T}Q_{1}y_{k+1+i}+\sum_{i=1}^{N_{\rm c}} \Delta u_{k+1+i}^{T}R_{1}\Delta u_{k+1+i} \tag{34}\]An intermediate function \(V_{\text{in}}\) is defined, which is obtained by shifting the optimal inputs sequence of \(V(\text{x}_{k})\) one step forward and setting its last input \(\Delta u_{k+\text{Nc}}\) as zero. The intermediate function is a non-optimal objective function comparing with \(V(\text{x}_{k+1})\), so we can obtain the inequality  
\[V(x_{k+1}) \leq V_{\text{in}} \tag{35}\] \[V(x_{k+1})-V(x_{k}) \leq V_{\text{in}}-V(x_{k}) \tag{36}\]  
According to definition of the intermediate function, \(V_{\text{in}}\) shares the same future inputs sequence and the predictive outputs sequence with \(V(\text{x}_{k})\) for the sample time \(k+1\),..., \(k+N_{c}-1\), the difference between these two functions can be expressed as  
\[V_{\text{in}}-V(x_{k})=y_{k+Np}^{T}Q_{1}y_{k+Np}-y_{k+1}^{T}Q_{1}y_{k+1}- \Delta u_{k}^{T}R_{1}\Delta u_{k} \tag{37}\]  
The error between the final predicted output and reference states is zero. Then, it can be obtained that  
\[V_{\text{in}}-V(x_{k})=-y_{k+1}^{T}Q_{1}y_{k+1}-\Delta u_{k}^{T}R_{1}\Delta u _{k} \tag{38}\]  
\[V(x_{k+1})-V(x_{k})\leq-y_{k+1}^{T}Q_{1}y_{k+1}-\Delta u_{k}^{T}R_{1}\Delta u _{k}\leq 0 \tag{39}\]  
Then the closed-loop system is asymptotic stable.
## 6 Conclusions  
An improved automatic workflow for generating VHR satellite orthoimages is proposed in this study. The procedure works with level 1 or level 2 images and it employs an automatic GCPs extraction procedure that is based on the multi-step matching of road network features that are derived from the input satellite image and reference data. In contrast to the previously implemented road extraction method, we utilize a fast segmentation-based method that includes a simple decision tree classification. The proposed method is focused on images that contain dense urban areas, where the extraction of road features is very challenging. To achieve a high density of extracted GCPs, it concentrates on predefined crossroads that are in urban environments present in high numbers. Thus, some GCPs are common to all images of the same area and they can therefore be used for a joint adjustment of a block of images.  
The performance of the processing procedure is tested on 14 Pleiades panchromatic images of two highly urban regions in Slovenia. The accuracy tests demonstrate the capability of the proposed procedure to achieve root mean square errors of approximately one pixel or even the sub-pixel level. The procedure is robust and also accurate for images of high off-nadir angles and various acquisition dates. Furthermore, the proposed extraction algorithm can retrieve a high number of very accurate GCPs, also in city areas with relatively high buildings that may occlude the road network themselves or indirectly (by their shadows).  
The developed procedure is currently functional with Pleiades imagery, but the testing of images of even higher resolution (e.g., WorldView satellite series) is in progress. Besides the basic aim of generating orthoimages, the procedure is also designed to support the creation of satellite true orthoimages--i.e., orthoimages where distortions due to high objects (e.g., high buildings) are also minimized. Although the development of this final stage is not yet completed, the first results are very promising.  
[PERSON] designed the algorithms for the proposed road extraction method and automatic geometric sensor model. He led the research. [PERSON] integrated the development of the processing workflow. Both authors contributed to the testing of the described algorithms, as well as to the writing, editing and reviewing of the manuscript.  
This research was funded by the Slovenian Research Agency project Z2-8193.  
The authors would like to thank the Slovenian Centre of Excellence for Space Sciences and Technologies (SPACE-SI) for its contribution in the development of the STORM processing chain. We appreciate the constructive comments and suggestions by editors and the anonymous reviewers.  
The authors declare no conflict of interest. The funders 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.
# A Bioinspired Humanoid Foot Mechanism
## 1 Introduction  
Humanoid robotics has fascinated and challenged scientists for decades [1]. The design of humanoid robots has evolved from the serial design of the first humanoids, such as WABOT (WAseda roBOT) [2], to more refined architectures [3; 4; 5; 6; 7; 8; 9; 10; 11; 12]. However, despite decades of research, the mobility of most of these robots is still limited to the legs, arms, hands, and head only, with very few examples including torso [10] and foot [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23] mobility, despite the feet and torso playing a key role in human motion [24]. The reduced mobility of humanoid robots in those regions hinders their capability to achieve balance and to perform complex dynamic tasks. Human foot architecture is characterized by three main segments--namely the heel, mid-foot, and toes--that fulfill distinct roles during bipedal locomotion [25].  
However, several humanoid robots use flat, one-segment feet [2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12]. Some famous examples include Honda's ASIMO (Advanced Step in Innovative Mobility) [3], the iCub design and its variants from the Italian Institute of Technology [7], and Softbank Robotics NAO [9]. Several research groups have tried to improve the foot performance by compensating a limited mechanical design with an enhanced sensing/control capability, which can be obtained by adding force/pressure sensors to the plant of the foot [26; 27; 28; 29; 30], with mixed results. Others kept a one-segment design, but moved from a flat rigid sole to a compliant one [13; 14; 15], obtaining significant results and increased performance (e.g., Boston Dynamics' Atlas [14]). Soft options have been also explored through designs with a highly elastic foot sole directly connected to the ankle joint [16].  
Some research groups investigated the possibility of using two-segment feet, with a heel segment and a toe segment [16; 17; 18; 19; 20]. Foot designs with three segments have been proposed to better mimic human-like motion [21; 22], but are usually characterized by active mechanisms that require a complex control and motion coordination with the rest of the body [21], or by planar rigid-body mechanisms [22] that achieve balance through spring-loaded joints only. While successful, the lack of compliance in these three-segment designs limits their behavior when obstacles introduce 3D torques and loads.  
In this paper, an innovative passive mechanism for robotic feet is presented, which is able to adapt to the environment without the need of external actuation thanks to joint elasticity. First, the mobility requirements to achieve human-like motion are extracted from medical literature and experimental gait analysis using a motion capture system. Then, the proposed design is introduced, along with its main characteristics and technical details. The foot mechanism is validated through numerical simulation with both Finite Element Analysis (FEA) and Multibody Dynamics, and a prototype is manufactured with 3D printing in order to prove the feasibility of the proposed mechanism on a range of terrains and obstacles.
# A Complete Pipeline for Heart Rate Extraction from Infant ECGs
## 2 Materials and Results
### The ECG Pipeline
#### 2.2.5 Square Wave Peak Correction  
While filter-based preprocessing deals with many sources of noise, any periodic non-ECG signal is likely to be preserved with the frequency-processing and EMD methods. Square waves were occasionally observed when recording was started prior to attaching the device to a subject. The nature of square waves is very likely dependent on the device, and square wave removal is highly recommended in these recordings. For the EgoActive sensor (University of York, UK) responsible for Dataset C, a median filter with a 101 sample width was used to exclude blocks of signals that were within 0.5% of a local maximum/minimum. The precise filter width and max/min margins depended on the gain and the sampling rate of the device used. This correction was applied post-peak detection to remove any peaks deemed to occur during these periods. Square wave correction was not required for Datasets A and B.
# Biosynthesis Progress of High-Energy-Density Liquid Fuels Derived from Terpenes
## 4 Strategies for Constructing Efficient Microbial Cell Factories for Terepenes  
The construction of efficient microbial cell factories is crucial for the green manufacturing of terpene fuels. The exogenous terpene synthesis pathway utilizes the precursors, energy and co-factors in the host to synthesize target products. However, the inefficient expression of the exogenous genes and the inhibition of the growth and metabolism of the host caused by exogenous pathways could severely limit the synthesis of a desired product. Therefore, the rational design, modification and reconstruction of microbial metabolic pathways are key issues in the industrial-scale production of terpene-derived fuels. This section focuses on the mining and engineering of terpene synthases, optimizing the metabolic pathways and redesigning chassis cells, providing an overview of the strategies for constructing efficient microbial cell factories for terpen synthesis.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Product** & **Chassis** & **Synthease** & **Conditions** & **Carbon Source** & **Production** & **Ref.** \\ \hline \multirow{2}{*}{\(\gamma\)-Bisabolene} & _S. cerevisiae_ & AcTIPS6 from & & & & \\  & CEN.PK2-1D & _Acremonium_ & & & & \\  & CEN.PK2-1D & _chrysogenum_ & & & & \\ \hline \multirow{2}{*}{Germancene A} & _Y. lipolytica_ & dIGAS from & & & & \\  & W29 & _Daldinia localata_ & & & & \\ \hline (-)-Germancrene D & _S. cerevisiae_ & AcTIPS1 from _A._ & & & & \\  & CEN.PK2-1D & _chrysogenum_ & & & & \\ \hline \multirow{2}{*}{\((+)\)-Bicyclogenmecrene} & _E. coli_ BL21(DE3) & & PeTS4 from & & & \\  & _Pentiillium_ & & & & \\  & _cryøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøøø
## 4 Experimental Validation Framework
Figure 11: PWM signals sent by FC aircraft in case of PTX6 functionality testing. Figure 12: Experimental testing of attitude control on PTX6 for the case of reference state tracking. Figure 10: System response of PTX6 functionality testing. Experimental tests are conducted in laboratory conditions without the presence of external disturbances. The system response is displayed using filtered readings from the Pixhawk FC built-in IMU sensors. Compared to conventional configurations, for the considered attitude control experiment, the largest difference is for the yaw angle control. In a fully actuated configuration with passively tilted rotors, the yaw moment is achieved mainly through the thrust forces generated by individual rotors. Considering that a thrust force is an order of magnitude greater than the drag torque (Figure 5), such configurations have a much better response to yaw angle tracking, as shown in Figure 13. The level of influence of thrust force and drag torque on yaw moment depends on the amount of tilt angle. With a higher tilt angle, the influence of the thrust force is greater and the drag torque becomes more negligible. The second experiment was related to the remote control of the PTX6 configuration. Compared to the first experiment, a 5000 mAh LiPo battery was used in the tests, and the landing gear was mounted to the aircraft assembly. The tests were conducted in laboratory-safe conditions since a safety net was installed, where a motion capture system was set to be installed on the existing structure. Since the remote-control joysticks had two control sticks, thus four control outputs, and the tested aircraft was fully actuated, the switching module was implemented into custom firmware. With the help of the module, it was possible to control the aircraft in a classic way, as with conventional aircraft, where the right stick was used to control the roll and pitch moments. The second case was when the right stick was used to control horizontal forces. Figure 14 shows a multirotor position in 3D space. On the test aircraft, the landing gear was rotated by 90 degrees since it was easier assembly. Figure 13: Experimental results of PTX6 configuration response for attitude control.
# Ice Production in Ross Ice Shelf Polynyas during 2017-2018 from Sentinel-1 SAR Images
## 3 Method
### Retrieval of Ice Thickness  
In this study, we use the AMSR2 brightness temperature at 89 and 36 GHz to derive thin ice thickness based on the algorithm in [19]. This algorithm was developed based on 186 MODIS ice thickness images and AMSR2 brightness temperatures in RISP, Ronne Ice Shelf Polynya, and Cape Darnley Polynya during April-September from 2013 to 2015. If the polarization ratio of 85 GHz (PR85) of a pixel is more than 0.062, the pixel is regarded as thin ice with thickness in the rage of 0-0.1 m, and the thickness H in meters is calculated using Equation (1). If the polarization ratio of 36 GHz (PR36) of a pixel is larger than 0.084, the pixel is regarded as thin ice with thicknesses ranging 0.1-0.2 m, and the thickness H in meters is calculated using Equation (2).  
\[\mathrm{H}=e^{\frac{1}{104+PR85-0.07}}-1.07,\ PR85=\frac{TB85V-TB85H}{TB85V+TB85H} \tag{1}\]  
\[\mathrm{H}=e^{\frac{1}{72+PR36}}-1.08,\ PR36=\frac{TB36V-TB36H}{TB36V+TB36H} \tag{2}\]  
where TB85V and TB85H are the microwave brightness temperatures at 85 GHz for vertical and horizontal polarizations, respectively. TB36V and TB36H are the microwave brightness temperatures at 36 GHz for vertical and horizontal polarizations, respectively. For H < 10 cm, the root-mean-square error (RMSE) of the derived ice thickness is 5.6 cm, and the biases range from 0.8 to 3.8 cm; for 10 cm < H < 20 cm, the RMSE is 5.8 cm, and the biases range from \(-\)3.6 to 1.6 cm [19]. For cases when the computed thickness is less than 0 m, the thickness is assumed to be 0.01 m.  
According to [19], the PMW method was only used for the derivation of ice thickness within 20 cm. Therefore, when ice thickness is larger than 20 cm based on Equations (1) and (2), the ice thickness is assumed to be 30 cm which is the average value of the observed ice thickness of more than 20 cm from the ship-based (ASPeCt) ice observations of PIPERS 2017 cruise during May/June 2017 in the RISP [51].