esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Improvements and Comparative Analysis of IEEE 802.11 bd  
### Background of IEEE 802.11p and IEEE 802.11 bd  
IEEE 802.11p stands as the world's first V2X communication standard, serving as the underlying protocol for DSRC and garnering extensive deployment and application over the past decade. Operating within the 5.9 GHz frequency band reserved specifically for vehicular communication, it utilizes a 10 MHz channel width. This standard is an improvement and extension of the 802.11 standard to suit the vehicular communication environment. At the physical layer, it employs Orthogonal Frequency-Division Multiplexing (OFDM) modulation, capable of delivering higher data transmission rates and enhanced resistance to multipath propagation. Through techniques such as power control adjustment and antenna design optimization, it refines the communication range and coverage, ensuring robust vehicular communication performance. At the MAC layer, the standard incorporates rapid channel-switching technology and priority management mechanisms, enhancing the communication efficiency and safeguarding the reliability of safety-critical communications.  
After more than a decade of testing and application, 802.11p has amassed a broad user base, with its effective reliability and scalability fully validated. However, with the rapid advancement of intelligent vehicles, 802.11p falls short of meeting the rapidly increasing quality of service demands, such as faster data transfer rates, greater data throughput, and higher data transmission reliability. The official release of the C-V2X technology in 2017 also challenged the status of 802.11p [27]. In response to these challenges, 802.11 bd [12] was officially introduced in 2023, incorporating and enhancing wireless communication technologies that have matured over the past decade. Due to the maturity of high-frequency communication technology, 802.11 bd can stably operate in the 60 GHz frequency band, thereby obtaining a 20 MHz communication bandwidth. At the physical layer, 802.11 bd still adopts OFDM modulation, but introduces LDPC coding to enhance the data transmission reliability. Improvements in data frame formats, such as variable Long Training Field (LTF) formats and midamble, facilitate the better estimation of rapidly changing communication channels by vehicles, further stabilizing the data transmission reliability. Advancements in data transmission modes also enable 802.11 bd to utilize denser MCS and higher coding rates to increase the data transfer rates. In terms of antennas, 802.11 bd improves the beamforming technology and introduces Multiple-Input Multiple-Output (MIMO) antenna modes to greatly enhance the data throughput. At the MAC layer, 802.11 bd also introduces many new mechanisms to adapt to the rapid development of vehicular communication, including adaptive MCS and intelligent spectrum sensing, improving the system scalability. In the following subsections, we will delve into these technical improvements in detail and evaluate the gains in V2X performance from the key improvements.
## 2 Related Work
For example, we put the training of the offloading scheduler on the cloud for execution. MEC systems mentioned in the literature allow Cloud and edge collaboration [19,20,23,24,25,26,27], and mobile devices can adaptively offload dependent tasks to MEC or Cloud. [PERSON] et al. [24] studied a multi-layer task offloading framework for MEC, which not only uses the collaboration between Cloud and MEC but also offloads tasks to other mobile devices through D2D links. [PERSON] et al. [25] considered an MEC dependency sensing offloading scheme based on edge cloud collaboration under the constraint of task dependence. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Approaches** & **Advantages** & **Disadvantages** \\ \hline Convex relaxation approaches [9] or heuristic local search approaches [4,10] & Closer to the optimal offloading solution. & It is easy to fall into the local optima, and it is necessary to re-solve the optimization problem when the external environment changes. \\ DQN-based approaches [9, 10, 11, 12, 13] & Suitable for dynamic environments. & When the number of wireless devices grows exponentially, these approaches are expensive. The sample efficiency is low and requires a large number of samples, which is not suitable for actual application scenarios. \\ PDO-based approaches [16,17] & Good effect, and it can realize discrete control and continuous control. & When the number of wireless devices grows exponentially, these approaches are expensive. The sample efficiency is low and requires a large number of samples, which is not suitable for actual application scenarios. \\ DDPG-based approaches [18,19] & High efficiency. & The explorability, stability, and robustness of this method are not good enough. \\ \hline \end{tabular}
\end{table} 
Table 1: Comparison of Approaches.
## 3 Method
### Problem Setting  
Suppose that we have an annotated dataset \(D\), which is divided into two distinct cohorts: the base classes \(D_{\text{base}}\) and the novel classes \(D_{\text{novel}}\), with a null intersection, i.e., \(D_{\text{base}}\cap D_{\text{novel}}=\emptyset\).  
\[D_{\text{base}}=\{(X_{\text{base}},Y_{\text{base}})\mid X_{\text{base}}\in I _{\text{base}},Y_{\text{base}}\in L_{\text{base}}\} \tag{1}\]  
\[D_{\text{novel}}=\{(X_{\text{novel}},Y_{\text{novel}})\mid X_{\text{novel}}\in I _{\text{novel}},Y_{\text{novel}}\in L_{\text{novel}}\} \tag{2}\]  
In this notation, \(X\) represents an instance within the image space \(I\), while \(Y=\{C,B\}\) corresponds to the label in the label space \(L\). \(C\) is the class of instance \(X\), and \(B=\{x,y,h,w\}\) is the bounding box associated with \(X\). \(D_{\text{base}}\) refers to the dataset for base classes while \(D_{\text{novel}}\) represents the dataset for the novel classes.  
In this context, the annotated data in \(D_{\text{base}}\) are abundant, whereas those in \(D_{\text{novel}}\) are scarce. The few-shot scenario can be effectively described using the N-Way-K-Shot terminology. Here, N represents the number of novel classes within the dataset \(D_{\text{novel}}\), and K denotes the limited number of annotated samples available for each of these novel classes. The core of FSOD lies in achieving accurate classification and location of novel classes with a limited number of annotated samples. To achieve this aim, we adopt a two-stage training strategy. Initially, a base detector is trained on the dataset \(D_{\text{base}}\), which comprises abundant annotated data from base classes. Subsequently, this base detector is fine-tuned on a balanced dataset \(D_{\text{bal}}\), which is formed by selecting k instances from each class in both \(D_{\text{base}}\) and \(D_{\text{novel}}\). This approach yields a detector that can accurately identify novel classes.
## 4 Fabrication and Measurement
### PTE Performance Verification
The simulated and measured performance comparisons of the maximum PTEs are listed in Table 1. Overall, the WPTS with the proposed IML-based AMC design can provide a better power transmission characteristic than the WPTS without AMCs and with the ferrite-only-based magnetic shielding, in both the simulations and measurements. For the ferrite-only case, the PTE was almost half that in the case without shielding. For the  
Figure 8: Procedure for assembling the AMC unit cell layers. (**a**) Ground plane. (**b**) Arrangement of ferrite and marking of the position of the hole. (**c**) Soldering the via pin on the ground plane using the marked position. (**d**) Rearrangement of ferrite on the via pin-connected ground plane. (**e**) Top view of the IML-based AMC. (**f**) Side view of the IML-based AMC. measured results of the IML case, the efficiency was slightly lower than the simulation results. The difference between the simulation and measurements could be due to the frequency shift of the Tx coil and AMCs and the losses from the core and additional lumped capacitors. Although the possible losses could degrade the PTE performance of the proposed AMC design in a real-time experimental environment, the PTE value was still higher than that in the case of the ferrite-only-based magnetic shielding structure.
# Iterative Positioning Algorithm for Indoor Node Based on Distance Correction in WSNs
## 6 Conclusions  
With the development of wireless communication technology, the position information of data is playing an increasingly important role. There are errors in node positioning due to various interferences in the data transmission process. As an alternative to this problem, a node iterative positioning algorithm based on distance correction is proposed in this paper to help users obtain accurate position information. Contributions include the following aspects:  
1. The noise impact factor \(F_{N}\) has been derived based on the original log-distance distribution model, which is used to describe the corresponding relationship between the noise impact factor \(F_{N}\) and the measured distance. Proposing a noise impact factor provides a novel method for analyzing the influence of noise on the distance measurement between nodes in WSN.
2. The median of the distance deviation coefficient has been constructed to characterize the deviation degree of the whole measured distances and used to correct the range from the last positioning. The triangle centroid localization algorithm has been iteratively conducted based on the adjusted new distance value to improve the node positioning accuracy.  
Experimental results show that the node iterative positioning algorithm based on distance correction can reduce the positioning error of unknown target nodes in wireless sensor networks effectively and help users obtain more accurate node coordinates. In the future, based on the node iterative positioning algorithm proposed in this paper, we will move forward with related research including real-time tracking and path planning of moving nodes in WSNs.  
Conceptualization, J.C., S.W., and K.-C.L.; methodology, all authors; software, J.C., M.O., and K.-C.L.; validation, J.C. and Y.X.; formal analysis, J.C., S.W., and Y.X.; investigation, J.C. and M.O.; resources, J.C., S.W., and K.-C.L.; data curation, S.W., K.-C.L., and Y.X.; writing--original draft preparation, J.C., M.O., and K.-C.L.; writing--review and editing, J.C., S.W., and M.O.; visualization, J.C. and K.-C.L.; supervision, J.C. and K.-C.L.; project administration, J.C. and M.O.; funding acquisition, J.C.  
This research was funded by the Natural Science Foundation of the Education Department of Anhui province (KJ2018A0087) and the Natural Science Foundation of China (51874010).  
The authors declare no conflict of interest.
## 3 Results
### Flow Profile
The characterization of the flow profile in our device guarantees a convenient and accurate control of the flow. We therefore modeled the shear stress values to which the cells are exposed, according to their position on the membrane. The graph in Figure 2e depicts the distribution of the shear stress above the cells (i.e., for all \(x\), \(y=-a\)) for the minimum and maximum flow rates and for our experiment at 10 dyn\(\cdot\)cm\({}^{-2}\). We observed flat flow profiles due to the low \(h/w\) channel ratio, showing that most of the cells are exposed to the predicted shear stress. By granting a variability of 5%, only the cells located at \(\leq\)450 \(\upmu\)m of the side walls will experience a lower shear stress than the other cells. In our device, the correct shear stress covers 82% of the entire cell monolayer, independently of the flow rate configured. We studied the shear stress distribution for other BBB devices to compare our data. We revealed large differences in percentages of shear stress homogeneity due to the high variety of channel dimensions. A very good shear stress homogeneity of 90% was predicted for one device [30], while other devices present identical [31] or lower [32; 33; 34; 35; 36; 37; 38; 39; 40] homogeneity percentages compared to ours. This comparison allows us to support the fact that our device presents one of the larger areas of homogenous shear stress. (Supplementary Data S2 provides more detailed information about these calculations). Laminarity:  
In physiological condition, the blood flow circulates laminarly throughout most of the circulatory system [29]. The Reynold's (_Re_) number determines whether the fluid flow is laminar or turbulent in our device. The dimensionless _Re_ is expressed as:  
\[Re=\frac{\rho Vh}{\mu}\]  
with  
\[V=\frac{Q}{hw}\]  
where  
\(\rho\): culture medium density (993 kg\(\cdot\)m\({}^{-3}\))  
\(V\): flow velocity (in m\(\cdot\)s\({}^{-1}\))  
\(h\): channel height (0.5 \(\times\) 10\({}^{-3}\) m)  
\(w\): channel width (5 \(\times\) 10\({}^{-3}\) m)  
The result gives _Re_ numbers from 0.30 to 174 for the flow rate panel ranging from 0.055 to 32.3 dyn\(\cdot\)cm\({}^{-2}\). For an experiment at 10 dyn\(\cdot\)cm\({}^{-2}\), the Re number is 54.2. The transition to the turbulence typically appears when the Re number exceeds 1400 [41]. Here, the values stay sufficiently below this threshold, proving that the flow is laminar over the entire cell monolayer, whatever the configured flow rates.
## 6 Discussion  
Multi-constellation receivers are widely used nowadays, which causes the number of visible GNSS satellites to increase and effectively improves the performance of satellite positioning. However, under the urban canyon environment, the number of satellites can meet the requirement of obtaining the positioning result but the poor configuration will bring multipath effect and interference, which still brings serious challenges to the application under a complex environment. Our experimental results show that although the simulation results with one reference member in Figure 24 are not as good as those with large numbers, it is still helpful to use belief propagation cooperative positioning. Since the NLOS error will have a serious impact on localization results even causing the results to be worse than with no cooperation, it is necessary to use the method proposed in this article to identify and separate NLOS. It can be seen that after using the NLOS identification method proposed in this article, the position error of UGV1 is significantly reduced compared to no NLOS identification and without cooperation. By taking the  
Figure 24: Localization error under five reference members.  
relative range of reference members into consideration, our method has better NLOS signal identification and separation accuracy than the traditional NLOS identification method. Therefore, the method proposed in this article can effectively improve cooperative navigation and positioning in complex terrain environments. However, our research is currently limited to simulation. To build on the findings of this research, future studies will focus on implementing and testing the proposed method in real-world environments to validate the simulation results and assess performance under actual operational conditions.
###### Abstract  
Using aggregates from alternative sources has been considerably encouraged in recent decades. Reducing the consumption of natural aggregates from quarties (which have a substantial economic, visual, and environmental impact) is increasingly a concern. These needs have led to the broader use of more sustainable aggregates, increasing the incorporation percentages and extending their use to more demanding pavement layers (e.g., surface). In order to prove the efficiency of recycled concrete aggregates (RCAs) under such conditions, the \"_CirMat_\" project was developed. Among other works and tests, an asphalt concrete (AC) incorporating 52.3% RCA was characterized mechanically and environmentally. Empirical properties were evaluated, including the Marshall test (S = 20.2 kN; F = 2.9 mm) and resistance to permanent deformation (WTS = 0.10 mm/\(10^{3}\) cycles), as well as a life cycle assessment (LCA), which confirmed that nine indicators were improved (from 1% to 93%). The test samples were taken from mixtures produced in the laboratory and at a plant (after which they were applied on a construction site). Comparing the results with those obtained in a reference AC (with natural aggregates), it was possible to conclude that the performance of the AC with RCAs was very similar. Therefore, the use of these aggregates, at high rates, does not represent additional risks for asphalt mixtures and has lower environmental impacts in most categories.  
Keywords:asphalt concrete; environmental product declaration; life cycle assessment; Marshall test; permanent deformation resistance; recycled concrete aggregate; water sensitivity +
Footnote †: journal: _Sustainability_
## 3 Results  
Effects of Indirubin, Indigo, and Tryptanthrin on Pro-Inflammatory Cytokine/Chemokine Production and Oxidative Stress in IL-22-Treated HaCaT Cells  
The beneficial effects of indigo naturalis can be primarily attributed to three of its components: indirubin, indigo, and tryptanthrin [23; 24]. As shown in Figure 2A, none of these compounds was found to be cytotoxic at concentrations from 1 to 30 uM (cell viabilities were >80% vs. vehicle-treated controls). Based on these results, each compound was used at 30 uM in the following experiments. To evaluate the anti-inflammatory activity, the TNF-\(\alpha\), ICAM-1, IL-6, and IL-8 levels were measured in the conditioned media of IL-22-treated HaCaT cells. Treatment with IL-22 increased the secretions of TNF-\(\alpha\), IL-6, and ICAM-1 by the HaCaT cells (Figure 2B). Indirubin and indigo suppressed the secretion of TNF-\(\alpha\), but only indirubin reduced ICAM-1 and IL-6 production in the IL-22-treated cells. IL-22 treatment did not significantly increase IL-8 secretion, and no significant change was produced by indirubin, indigo, or tryptanthrin. Interestingly, IL-22 increased the intracellular ROS generation in HaCaT cells, while a pre-treatment with indirubin significantly reduced the ROS level. Indigo and tryptanthrin did not have any significant effects on the IL-22-induced ROS generation in the HaCaT cells (Figure 2C). However,indirubin, indigo, and tryptanthrin did not alter ROS production or inflammatory cytokine secretion in non-IL-22 treated HaCaT cells (Figure S1). These findings indicate that under normal conditions, the three indigo naturalis components did not produce inflammation or irritation.  
Figure 2: \(Cont.\)  
Figure 2: **(A) Effect of indiribin, indigo, and tryptanthrin on the viability of HaCaT cells. The cells were treated with 0, 1, 10, 30, 50, or 100 \(\upmu\)M of indiribin, indigo, or tryptanthrin for 24 h. The visibilities were measured using an XTT assay and are defined as percentages of the vehicle-treated controls. **(B)** Effect of indiribin, indigo, and tryptanthrin on the production of pro-inflammatory cytokines/chemokines in IL-22-treated HaCaT cells. The cells were treated with indiribin, indigo, and tryptanthrin (30 \(\upmu\)M) for 1 h and incubated with 100 ng/mL of IL-22 for 48 h. The levels of human TNF-\(\upalpha\), ICAM-1, IL-6, and IL-8 in conditioned medium were evaluated using ELISA assays. **(C)** Effect of indiribin, indigo, and tryptanthrin on ROS levels in IL-22-treated HaCaT cells. The cells were incubated with 30 \(\upmu\)M of indiribin, indigo, and tryptanthrin for 1 h, followed by incubation with 100 ng/mL of IL-22 for 24 h. The percentages of ROS-positive cells were evaluated by an oxidative stress kit. Data represent the means \(\pm\) SDs (n = 3). # \(p\) < 0.05 vs. vehicle-treated controls (NC), *_p_ < 0.05 vs. IL-22-treated cells.
# Deep Learning-Based Next-Generation Waveform for Multiuser VLC Systems
###### Abstract  
Due to the growing number of users, power, and spectral effectiveness, most communication systems are complex and difficult to implement on a large scale. Artificial Intelligence (AI) has played an outstanding role in the implementation of theoretical systems in the real world, with less complexity achieving better results. In this direction, we compare the Non-Orthogonal Multiple Access (NOMA) technique for a multiuser Visible Light Communication (VLC) system with Successive Interference Cancellation (SIC) for two types of detectors: (1) the deep learning-based system and (2) the traditional maximum likelihood (ML) decoder-based system. For multiplexing, we compare the variations of novel Orbital Angular Momentum (OAM) multiplexing and Orthogonal Frequency Division Multiplexing (OFDM) with Index Modulation (IM). In this article, we implement OFDM-IM and OAM-IM for four users for the Gaussian fading MIMO Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) VLC channels. The suggested systems' bit error rate (BER) performances are compared in simulations for a wide range of Signal-to-Noise Ratios (SNRs), which shows that deep learning-based systems outperform the ML-based system for both users to ensure better decoding at the receiver end, especially at higher SNR values. The detection error is lower in a deep learning-based system at around 20% and around 30% for low SNR and high SNR values, respectively.  
beamforming; deep learning; maximum likelihood; new technologies used in massive MIMO; orbital angular momentum +
Footnote †: journal: Physics Letters A
###### Abstract  
The influence of modifier oxides (TiO\({}_{2}\), ZnO, BaO, and PbO) on the mechanical and radiation shielding properties of boro-telurate glasses is investigated. Samples with a composition of B\({}_{2}\)O\({}_{3}\)-SrO-TeO\({}_{2}\)-RO (RO represents the modifier oxides) were fabricated using the melt quench method, and their physical, mechanical, and radiation attenuation parameters were reported. For this aim, Monte Carlo simulation was employed to predict the radiation attenuation parameters, while the Makishima-Mackenzie model was adopted to determine the mechanical properties. The tightly packed structure with better cross-linkage density is possessed by the Ti-containing glass (SBT-Ti) system among the titled glass batch. The higher Poisson and micro-hardness values of the SBT-Ti glass indicate its structure's reduced free volume and better compactness. For the glass with PbO, the linear and mass attenuation coefficients are highly increased compared to those glasses doped with TiO\({}_{2}\), ZnO, and BaO. The thinner half-value layer was reported at 0.015 MeV, taking values 0.006, 0.005, 0.004, and 0.002 for samples with TiO\({}_{2}\), ZnO, BaO, and PbO, respectively. SBT-Pb sample (with PbO) has a thinner HVL compared to other fabricated glass samples. The fabricated glasses' thickness (Deq) equivalent to 1 cm of lead (Pb) was reported. The results demonstrated that Deq is high at low energy and equals 11.62, 8.81, 7.61, 4.56 cm for SBT-Ti, SBT-Zn, SBT-Ba, and SBT-Pb glass samples, respectively. According to the Deq results, the fabricated glasses have a shielding capacity between 30 and 43% compared to the pure Pb at gamma-ray energy of 1.5 MeV. At high energy (8 MeV), the transmission factor values for a thickness of 1 cm of the fabricated samples reach 88.68, 87.83, 85.95, and 83.11% for glasses SBT-Ti, SBT-Zn, SBT-Ba, and SBT-Pb, respectively.  
radiation shielding; monte carlo simulation; melt-quench technique; mechanical properties 4.0/. +
Footnote †: journal: Applied Sci. 2021, 11, 10904. [[https://doi.org/10.3390/app112210904](https://doi.org/10.3390/app112210904)]([https://doi.org/10.3390/app112210904](https://doi.org/10.3390/app112210904))