esa-sceva/satcom-chunk-collection huggingface dataset:
# Multistage Smoothing Compressor for Multistep Pulse Compressors
## 5 Discussion and Conclusions  
Owing to the fixed and random hotspots induced by diffractions from dust, defects in the optics, and the spatially inhomogeneous pump beam, the LSIM of an amplified laser in a PW laser system is usually very high. To avoid laser-induced damage to important optics, especially gratings, the laser fluence on the grating must usually be kept below half of its damage threshold, which undoubtedly affects the maximum output pulse energy of a compressor. Aside from the peak power, the operating safety is also very important to maintain an economical PW laser system and increase its experimental efficiency.  
As an improvement of MPC, the MS-MPC was proven to be able to achieve laser pulses with 10 s to 100 PW using a single laser beam. Based on the spatial chirp induced by grating pairs or prism pairs, both the LSIM in the near field and wavefront-aberration-induced hotspots in the far field can be effectively smoothed. Thus, the MS-MPC design can significantly improve the operating safety and increase the output peak power of PW laser systems. The proposed MS-MPC can directly protect important optics, such as the large crystal, all four gold-coated gratings, and deformable mirrors, from laser induced damage. Since the distances of the prism pairs or grating pairs can be easily varied, compressed laser beams with different spatial chirp widths can be conveniently achieved; these may induce different laser fields around the focal point and benefit laser physics experiments. Furthermore, this MS-MPC optical design can be easily applied to all existing PW laser facilities to improve their output pulse energy and operational safety.  
Conceptualization, S.D. and X.S.; Methodology, S.D. and J.L.; Software, S.D. and X.S.; Validation, S.D. and W.L.; Formal analysis, S.D.; Investigation, P.W.; Writing--original draft, S.D.; Writing--review & editing, J.L.; Project administration, J.L.; Funding acquisition, J.L. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the National Natural Science Foundation of China (NSFC) (61527821, 61905257, and U1930115) and the Shanghai Municipal Science and Technology Major Project (2017 SHZDZX02).  
Not applicable.  
The authors declare no conflict of interest.
## 2 Supplementary Cemertitious Material (SCM)
### Limestone-Calcined Clay Cement (LC\({}^{3}\))
#### 2.1.2 Durability and Microstructure of LC\({}^{3}\) Cement Binder  
In LC\({}^{3}\) technology, not only can the larger amount of OPC be replaced by SCMs to enhance the mechanical properties and reduce GHG emission, but also carbo-aluminate hydrates are generated,  
Figure 1: Compressive strength of concrete containing calcined clay with different metakaolin content [65].  
which can occupy the capillary pores [45]. Considerable incorporation of aluminum is discovered for LC\({}^{3}\) blends compared to the OPC and the C-A-S-H gel of LC\({}^{3}\) system shows significant variations in the composition. The kaolinite content of calcined clay has the main role of increasing the aluminum incorporation and its integration [39]. Furthermore, the chemical composition of calcium carbonate and alumina creates supplemental aluminate ferrite monosulfate (AFm) phases and stabilizes ettringite [52].  
LC\({}^{3}\) has shown considerable improvement in chloride resistance of concrete compared to the other mixes with similar compressive strength [67; 68]. This is mainly due to the creation of a large quantity of C-A-S-H and a synergetic impact between limestone and calcined clay [52; 69]. Resistance against chloride ingress is tested by using high to intermediate grades of kaolinite content in clay and where it was found that chloride resistance of clay containing intermediate amount of kaolinite was in a similar range to high kaolinite content (which is an expensive choice) [66]. Furthermore, studies indicated that the chloride penetration in OPC mortar after two years of exposure was four times higher than the LC\({}^{3}\) mixtures (of 50% and higher kaolinite content) [66]. The main reason for this feature was ascribed to the denser structure of the LC\({}^{3}\) compared to OPC. The action against capillary water absorption and gas permeability indicates that LC\({}^{3}\) can provide significant performance in comparison to OPC. Moreover, using hydrophobic agents can lead to a material with considerably higher resistance to moisture ingress [70; 71; 72; 73; 74] meaning that LC\({}^{3}\) concrete has the potential to be exploited at environmental conditions where there is a risk of chloride ingress, including marine environments [67].  
Furthermore, sulfate attack and Alkali-Silica Reaction (ASR) could both be mitigated by the LC\({}^{3}\) binder. A minimum quantity of limestone and calcined clay (around 30%) is reported to mitigate the sulfate attack [75]. [PERSON] et al. suggested that LC\({}^{3}\) could be involved in standards as an innovative kind of sulfate-resisting Portland pozzolan cement [48].
## 3 Beamforming of the Miniaturized L-Array
### Adaptive Beamforming
#### 3.3.1 The Sampling Matrix Inversion Beamformer  
The basic idea of the SMI algorithm is to minimize the total output power of the entire array while keeping the signal energy in the desired direction constant. It is an optimal beamformer under the linear constrained minimum variance criterion. SMI beamformer sets the constraint conditions of weight vector as Equation (11).  
\[\min_{w}E[\left|y(t)^{2}\right|]=\min_{w}\left\{w^{H}Rw\right\},\ s.t.w^{H}a( \theta_{d},\varphi_{d})=1 \tag{11}\]  
For this constraint problem, the weight vector can be solved by Lagrange multiplier method. When Equation (12) is defined as the objective function, the solution of the optimal weight vector \(w_{opt}\) can be expressed as Equation (13) [27].  
\[L(w)=w^{H}Rw+\lambda^{\prime}\left[w^{H}a(\theta_{d},\varphi_{d})-1\right] \tag{12}\]  
\[w_{opt}=\mu R^{-1}a(\theta_{d},\varphi_{d}),\mu=\frac{1}{a^{H}(\theta_{d}, \varphi_{d})R^{-1}a(\theta_{d},\varphi_{d})} \tag{13}\]  
In order to investigate the application effect of SMI algorithm on the miniaturized L-array, a simulation experiment was carried out. Under the condition that an interference signal with the same power level as the desired signal comes from \(\varphi=270^{\circ}\), \(\theta=80^{\circ}\), a random azimuth with an elevation that approximates the vertical sounding echoes. The signal-to-noise ratio (SNR) is set at 5 dB. The simulation results employing SMI beamformer at the frequency point of 15 MHz can be shown as Figure 6.  
Employing the SMI beamformer, the intensity of the desired signal is also effectively maintained, and the maximum gain point of the pattern is still at \(\varphi=113^{\circ},\ \theta=35^{\circ}\). Different from the conventional beamforming, there is a deep zero depression at the incident direction of the interference signal. In elevation, at \(\theta=80^{\circ}\), the normalized level of pattern decreases from 0.377 to 0.055. The influence of the vertical sounding signals and its 2-hop echoes caused by the side lobe of the transmitting antenna can be reduced greatly. In an ideal case, if the 2-hop vertical echoes are considered to be suppressed below the level of the oblique backscatter signals, then the low frequency part of the  
Figure 6: (**a**) is the top view of Figure 5g, (**b**,**c**) are sections of \(\varphi=270^{\circ}\) and \(\theta=80^{\circ}\), respectively. (**d**–**f**) are the corresponding results of using SMI optimal beamformer.  
oblique backscatter ionogram do not have to be deducted in the inversion process, which is actually expanding sounding cover range [28]. In azimuth, at \(\varphi=270^{\circ}\), the normalized level drops from 0.373 to 0.053. The interference signals from this direction can be effectively suppressed without affecting the extraction of the desired signals. The simulation results show that the SMI algorithm is still applicable to the miniaturized L-array, with an ideal spatial filtering effect.
## 1 Introduction  
The Glaser-Hay reaction involves the coupling of terminal alkynes to afford polyynes in good to excellent yields [1; 2; 3; 4]. These polyynes are found in various applications ranging from biologically active natural products to optical materials [5; 6; 7; 8]. A substantial hurdle to the widespread application of the Glaser-Hay reaction in synthetic organic chemistry is its lack of chemoselectivity, as the coupling of two unique terminal alkynes typically results in a mixture of homodimer and heterodimer products (Figure 1). While some chemoselective alkyne couplings have been elucidated, the simplicity of the Glaser-Hay reaction makes it a desirable choice in the synthesis of polyynes [9; 10; 11; 12; 13; 14; 15]. To this end, we have recently reported the chemoselective Glaser-Hay reaction via the immobilization of one terminal alkyne [16,17]. Immobilization of the alkyne precludes its homodimerization, and dimerization of the soluble alkyne can be rapidly washed away. This affords a facile synthesis of the heterodimeric product in good yields and excellent purities.  
While the previous chemoselective reaction involving the solid support is useful, the 16 h reaction time is synthetically limiting when preparing large libraries of molecules. To overcome this issue, we set forth to investigate the potential rate enhancement that could be obtained by the utilization of microwave chemistry. Microwave irradiation induces molecular motion via the alignment of ions or dipoles with the oscillating electromagnetic field, and has been demonstrated to increase reaction yields and to decrease reaction times [18,19]. Because the microwaves interact directly with the reagents and solvent, instead of by convection, they afford efficient heating of the reactions, cleaner reaction conditions, and in some cases, facilitate reactions that are not achievable by conventional thermal heating [20,21]. By translating the previously described Glaser-Hay reaction to the microwave, we aim to increase its synthetic utility even further. Previous research has successfully translated a Glaser-Hay macrocyclization to the microwave, resulting in the standard reaction time of 48 h to be decreased to 1-6 h [22]. Similarly, we aim to decrease the reaction times of the reported solid-supported Glaser-Hay coupling from 16 h to 10-20 min.
# Unmanned Vehicles' Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles
## 6 Proposed Algorithm: Communication Optimisation Integration  
### Optimum UV Placement and Great Circle Path  
The problem of finding the optimum location of a mobile node is an NP-hard (Non-deterministic Polynomial) problem that is very demanding from the point of view of computational resources. The great circle path or orthodrome, which is the shortest path between two points on a circle (in our case, the gateway and the served WSN), is widely used in navigation, but for the first time, according to our knowledge, we propose the use of this concept as a method to reduce the number of possible locations a UV can have, and thus, the complexity of the NP-hard problem. Consequently, before proposing the placement optimisation algorithm, one requires the presentation of great circle method and its corresponding algorithm. We assume there are \(n_{cn}\) virtual nodes with the same propagation characteristics that could ensure communication between the gateway and served WSN. The virtual nodes are equally spaced on the great circle path (Figure 10) that links the gateway found on point P1 (\(\phi_{1},\lambda_{1}\)) and the served WSN placed on P2 (\(\phi_{2},\lambda_{2}\)). To ensure their positioning on the great circle path, we computed the forward azimuth (\(\theta\)) between the two terminal nodes (P1 and P2) computed following Equation (24) [79]. \[ \begin{gathered}\theta[^{\circ}]=\left(\frac{180\arctan(y,x)}{ \pi}+360\right)\mod 360\\ y=\sin(\lambda_{2}-\lambda_{1})\cos(\phi_{2})\\ x=\cos(\phi_{1})\sin(\phi_{2})-\sin(\phi_{1})\cos(\phi_{2})\cos( \lambda_{2}-\lambda_{1})\end{gathered}  \tag{24}\]  
The imposed distance, \(d_{cn}\), between two virtual nodes is computed based on Equation (25). \[d_{cn}=\frac{d}{N_{cn}+1} \tag{25}\]  
Based on an imposed distance between virtual nodes (\(d_{cn}\)) and computed forward azimuth, we can compute the location of the virtual nodes points (Equation (26) and (27) [79]). Figure 10: Great circle path between GW (\(P_{1}\)) and WSN (\(P_{2}\)) adapted from [78]. \[\phi_{i+1}=\arcsin\left(\sin\phi_{i}\cos\left(\frac{d_{\mathit{v}n}}{R}\right)+ \cos\phi_{i}\sin\left(\frac{d_{\mathit{v}n}}{R}\right)\cos\theta\right) \tag{26}\]  
\[\lambda_{i+1}=\lambda_{i}+\arctan\left(\sin\theta\sin\left(\frac{d_{\mathit{v}n }}{R}\right)\cos\phi_{i},\cos\left(\frac{d_{\mathit{v}n}}{R}\right)-\sin\phi_{ i}\sin\phi_{i+1}\right) \tag{27}\]  
where \(R\) is the Earth radius (\(R=6.371\) km). Further, we propose Algorithm 1 to determine the closest real nodes to virtual nodes. Algorithm 1 is used to determine the real UV nodes (\(\mathit{rn}\)) that are closer to the virtual nodes (\(\mathit{v}n\)) such that one minimises the distance travelled by real nodes to the positions of the virtual nodes.
# Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity
###### Abstract
A comprehensive comparison between RIS and relay based systems over realistic mmWave channels has been presented in [17]. Dual connectivity (DC) has been introduced in [18] for cellular networks to improve per-user rate. The user in DC utilizes radio resources from two BSs and serve the users. There are two BSs involved in DC. One is the primary BS (PBS) where the user is associated based on its maximum received power. The other one is secondary BS (SBS) from where the user receives its second maximum SINR. The eligible DC user is able to receive different traffic from these two BSs. The first step of this to ensure the amount of traffic routed from OBS to the user via SBS. The downlink traffic scheduling and the SBS traffic routing to SBS in DC has been derived and presented in [19]. The performance comparison between CoMP and DC based system for different users and BS density scenarios have been presented in [20]. RIS-assisted wireless communication requires significant attention when it comes to the multi cell connectivity. The multi connectivity with multiple RIS-assisted CoMP has been evaluated in the literature [11]. The different scheduling and traffic routing schemes of DC have also have been analyzed in [19; 20]. The RIS-assisted CoMP architectures are expected to improve coverage if the two RIS or BSs are in proximity. The CoMP in general requires resources to be reserved for the CoMP users that give rise to coverage throughput trade-off [21]. Most of the literature considers either RIS-aided wireless systems or DC systems separately. To the best of our knowledge, this is the first work that proposes RIS-assisted DC where the eligible user is expected to utilize radio resources from two BSs via two RIS deployed in proximity. Based on the above motivation, the following contributions are made as follows. * The RIS-assisted DC architecture is proposed, which utilizes radio resources from two different BSs via two different RISs. * The joint resource allocation of RIS-assisted DC is formulated as an optimization problem and the optimal user scheduling time fraction for RIS-assisted DC systems for an \(\alpha\)-fair scheduler is derived. * The formulated joint problem is decomposed and the optimal user scheduling time fraction is derived using Karush-Kuhn-Tucker (KKT) conditions. A heuristic for solving the overall optimization problem with the derived scheduling time fraction is also presented. * Exhaustive simulation results are presented for distributed RIS architecture with varying densities of users, BSs, and blockage densities are presented. The paper is organized as follows. The system model with various parameters is presented in Section 2. The joint problem formulation of RIS-assisted DC is presented in Section 3. The heuristic for solving RIS-assisted DC problems is presented in Section 4. The evaluated numerical results are presented in Section 5. The conclusion and future work is given in Section 6. The system model is presented next.
## 2 Materials and Methods
### AFM Setup  
Figure 2a shows the experimental setup of the AFM system for this study. The system incorporates a replaceable microscope objective lens (Achrovid: \(5\times\) infinity objective) which can be used to focus the laser beam to the back of a cantilever and to enable an optical view with high magnification. A standard 635 nm, 4.5 mW laser diode module (Thorlabs: CPS196) is used. The collimated laser beam is directed through a polarizing beam splitter (PBS) to the objective lens. The PBS and objective lens are attached to an \(XYZ\) translation stage (Thorlabs: MT3/M) so that the laser spot can be adjusted precisely to the back of the cantilever, prior to imaging the experiment. Another smaller \(XYZ\) translation stage (Thorlabs: MS3/M) is required for fine-tuning of the reflected laser beam onto the photodiode module. A flexure-stage based piezo positioning system (Thorlabs: MDT630B/M) is used in the AFM setup. This bundle includes a piezo controller and differential micrometers for coarse adjustment.  
Figure 2: Atomic force microscopy (AFM) system: (**a**) Experimental setup. The system consists of several major sections. A laser diode module, a polarizing beam splitter (PBS) and an objective lens are attached together with custom parts and fixed to an \(XYZ\) translation stage. This section is responsible to align the laser spot onto the back of a cantilever. A smaller \(XYZ\) translation stage is required to hold the photodiode module. Signals from the photodiode module are fed into the signal conditioning module. A piezo positioning stage sits on top of a custom part which is attached to another \(XYZ\) translation stage so that the height can be adjusted; (**b**) Custom-built mechanical parts. Detailed drawings are presented in the Supplementary Materials (Figures S1–S24).  
Several custom-built mechanical parts are necessary to incorporate off-the-shelf components as mentioned above. However, the design of these parts iskept as simple as possible. As can be seen in Figure 2b, almost all parts are in the shape of a square or rectangular, which can easily be designed by undergraduate engineering students. The detailed drawings of the custom-built mechanical parts are presented in the Supplementary Materials (Figures S1-S24).
# Device-Free Indoor Activity Recognition System
## 4 Discussion  
As shown in the results section, the achieved results have gained a high accuracy rate in both LOS and NLOS scenarios. However, we also tried to test a single user activity with less training samples, we train the classifier for each individual user with 50 samples of each activity, and we test 100 samples of each activity. Figure 8 shows that the system still has stability and gained high accuracy, Thus, the proposed method is capable and may improve the human activity classification technology based only on wireless signals without special devices.  
Moreover, it is very important to demonstrate the system accuracy in case the testing samples do not overlap with training samples. We train the classifier with 100 samples of each activity collected from User 1 and User 2. We test 50 samples of each activity collected from User 3 during two sessions. In addition, we decrease the training samples collected from User 1 and User 2 to 50 samples of each activity, and we test 100 samples collected from User 3. As shown in Figure 9, the accuracy slightly decreased.  
Figure 8: Classification accuracy results with less training samples. (**a**) the results in LOS scenario; and (**b**) the results in NLOS scenario.  
Figure 9: Classification accuracy results with 100 and 50 training samples.  
By observing the results in Figures 8 and 9, we noticed that, in Figure 8, although the samples are 50, each user activity classification accuracy has gained higher accuracy rates because the classifier has been trained with samples that included samples from the target user. Whereas in Figure 9, the classifier has not been trained with samples collected from the target users. Thus, the accuracy slightly decreased. Overall results show that the system has a high accuracy rate under different conditions.  
Furthermore, to approve the validity of our feature extraction method, we compare our feature-based classification methodology (SRC with feature extraction) with the featureless-SRC methodology. [PERSON] et al. [25] proposed a device-free human activity system by leveraging the fluctuation of CSI, and they adopted SRC to classify several activities. Unlike our system, [PERSON] et al. used SRC without the feature extraction method. They relied on the main superiority of SRC, which is featureless. They built training sets from CSI measurements without feature extraction. However, this methodology is not robust to environment changes or electromagnetic noise, and it leads to false detection. The result in Figure 10 shows that our system outperforms the SRC-featureless method. Thus, the feature extraction method promotes the classification accuracy and improved the whole sensing process.  
Furthermore, it should be noticed that in each evaluated session the proposed activities must be implemented in a fixed position to be correctly detected. Thus, CSI-based activity classification techniques can be considered as location-based because the CSI value is different in different positions.
# Transmission Lines Small-Target Detection Algorithm Research Based on YOLOv5
## 2 Related Work
(2020) aimed to achieve high-precision identification and detection of small tower targets in remote sensing images. They conducted integrated modeling based on YOLOv5s and YOLOv5x algorithms and introduced the weighted boxes fusion (WBF) reasoning mechanism for model training and testing using a high-resolution remote sensing tower image data set. Additionally, they applied test-time augmentation (TTA) to the data set. Experimental results indicate that the integrated YOLOv5 model outperforms single model recognition in terms of accuracy. The model demonstrates excellent recognition capabilities and robustness even under complex backgrounds. At present, [PERSON] et al. (2021) have proposed an automatic detection method for infrared small targets under complex backgrounds and conducted extensive experiments on the public data sets NUDT-SIRST and NUAA-SIRST. The results show that the proposed detection method exhibits excellent performance. In summary, it is evident that the aforementioned research fails to achieve a balance between detection accuracy and detection speed, which is essential for small-target detection in transformation lines. The YOLOv5 detection model is widely used in small object detection tasks due to its high detection accuracy and fast detection speed. Therefore, this article aims to improve the YOLOv5 detection model and proposes the P2E-YOLOv5 detection method, which achieves high detection accuracy while maintaining real-time detection.