esa-sceva/satcom-chunk-collection huggingface dataset:
# An Experimental Study on the Reflection Characteristics of Laser Echo Light Waves
## 3 Experimental Scenario and Configuration  
We built an optical platform as shown in Figure 1. In order to maintain stability, the transmitting system and the receiving system were fixed on the same optical platform. In the transmitting system, we selected a solid laser with a wavelength of 532 nm, a transmitting power of 1 W, and a beam diameter of 5 mm as the light source. After the laser signal is emitted from the transmitting end, it first passes through a Maka optical telescope (i.e., Maksutov-Cassegrain optical telescope) with an aperture of 105 mm. The beam passes through the Maka optical telescope to collimate it, and the divergence angle becomes smaller. After the beam quality is improved, it is transmitted through the atmospheric channel. A corner reflector array is placed at the reflecting end to ensure that the laser return path is similar to the original transmission path. At the receiving end, the laser signal is focused again by the Maka optical telescope, and then directly incident on the PD300 optical power meter probe. The noise value of the PD optical power meter probe is \(\pm\)300 fW/s, the sampling frequency is 50 Hz, and the accuracy is \(\pm\)3%. When measuring the spot image, we replaced the optical power meter probe with a CCD camera; the sampling frequency of the CCD camera is 30 Hz, and the accuracy is \(\pm\)1%. The experiment was repeated several times. In addition, we also recorded the meteorological parameters during the experiment in detail to provide a reference for subsequent data processing and analysis. Laser spot drift may be caused by many factors, such as laser instability, optical system design, environmental vibration, and air disturbance. In order to study the influence of laser performance on spot stability, this study strictly controlled the experimental environment. In our experiment, we selected a laser with high stability to ensure the stability of the light intensity output by the laser and avoid fluctuations in laser performance caused by temperature changes. We used an optical platform with a shock-absorbing design. The optical platform was placed in the teaching building, and the environment was relatively stable. In order to minimize the interference of background light, we installed a filter behind the Maka optical telescope at the receiving end, placed the entire signal-receiving device in a self-made dark box, and selected a period of weak background light for the experiment, thereby ensuring an adequate signal-to-noise ratio of the signal.
## 5 Conclusions  
We presented observations of strain modification in T2 SLs InAs/InAsSb introduced by \(T_{growth}\) within 400-450 \({}^{\circ}\)C (optimal 425 \({}^{\circ}\)C) and presented the results of changes in energy bandgap, contributing to the changes in spectral responses. The growth temperature is believed to impact the Sb distribution at the interfaces, and an increase in \(T_{growth}\) led to a blueshift of the \(\lambda_{50\%\text{scut-off}}\). It was shown that the \(T_{growth}\) could be used to tune the operating wavelength in LWIR range (e.g., temperature growth change within the range 400-450 \({}^{\circ}\)C contributed to the \(\lambda_{50\%\text{scut-off}}\)\(\sim\) 11.6-8.3 \(\upmu\)m, estimated for operating temperature \(T\) = 230 K), while keeping the period and Sb composition constant, which provides much more flexibility in the device's design process without affecting T2 SLs' structural parameters--Sb composition and period.  
Figure 8: T2 SLs’ InAs/InAsSb bandgap and \(\lambda_{100\%\text{scut-off}}\) for Set I samples 4, 5, and 6 versus strain in InAsSb layer (in-plane strain in relation to the GaSb).  
**Author Contributions:** Conceptualization, P.M. and K.M.; methodology, K.M., L.K., J.J. and P.M.; validation, P.M. and K.M.; formal analysis, K.M. and P.M.; investigation, K.M., L.K. and J.J.; writing--original draft preparation, K.M. and P.M.; writing--review and editing, K.M. and P.M.; visualization, K.M. and P.M.; supervision, P.M.; project administration, P.M. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by Polish National Science Center, grant numbers OPUS 2018/31/B/ST7/01541 and HARMONIA 2018/30/M/ST7/00174[PERSON]  
**Data Availability Statement:** The data that support the findings of this study are available from the corresponding author upon reasonable request[PERSON]  
**Conflicts of Interest:** The authors declare no conflict of interest.
# A Chest Strap-Based System for Electrocardiogram Monitoring
## 1 Introduction
To address the limitations of current wearable ECG monitoring systems, this study aims to develop a real-time ECG monitoring system tailored for daily use and to construct an individualized exercise intensity assessment model, thereby enhancing the system's intelligence and practicality. To this end, we propose a chest strap design incorporating flexible textile electrodes and evaluate its feasibility and stability in physiological signal acquisition. Additionally, by integrating deep learning algorithms, we develop an exercise intensity assessment model that uses multiple ECG-derived features as inputs to assess a user's exercise intensity. The main contributions of this work are as follows:  
1. The development of a miniaturized, low-cost, and highly comfortable chest strap ECG monitoring system that meets the requirements for daily wearability. 2. The design of flexible textile electrodes fabricated by integrating silver-coated polyamide yarn with breathable and elastic substrates, offering excellent flexibility, comfort, and signal quality, significantly enhancing wearability and measurement performance. 3. The construction of a deep learning model for accurately assessing individual exercise intensity based on ECG signal features, thereby expanding the application potential of ECG signals in smart health monitoring. The remainder of this paper is organized as follows: Section 2 describes the methodology, including the system design, the signal conditioning circuit, and the deep learning model. Section 3 presents the experimental setup. Section 4 reports and discusses the results. Section 5 concludes the study.
## 4 Results and Discussion
### Experiment with Random Test Cases
#### 4.1.2 Pls  
In this study, regression models were also built using PLS. Figure 10 shows the estimated SEP against a different number of principal components (PCs) achieved for the PLS model built with different approaches. In general, there was a linear relationship between the number of PCs used and the corresponding SEP. It could be observed that the SEP increased with the increase in the number of principal components for the PLS model with the first derivative signal. SEP on the second component was 22.09 mg/dL which increased to 50.59 mg/dL for 11 PCs. After performing second derivative and building model based on this, the lowest SEP was recorded as 21.37 mg/dL on the second component. The SEP reduced even more when the PLS model was built with the help of first derivative characteristics points extracted from the preprocessed PPG, and it was 17.02 mg/dL for the second component.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Features** & **SEP (mg/dL)** & **Number of PCs** \\ \hline Del T & 21.3 & 2 \\
1 st Derivative & 18.33 & 5 \\
1 st Derivative Characteristics Points & 17.08 & 11 \\
2 nd Derivative & 18.27 & 5 \\
2 nd Derivative Characteristics Points & 22.95 & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of performances of different PCR models.  
Figure 9: Standard Error of Predictions (SEPs) against a different number of principal components (PCs) achieved for Principal Component Regression (PCR) model built with different preprocessing approaches.  
The comparison of performances among different PLS models in terms lowest SEP achieved and minimum no. of PCs required can be found in Table 3. It is important to note that with PLS-based models, all the lowest SEPs were achieved with just two principal components.
# Green Project Planning with Realistic Multi-Objective Consideration in Developing Sustainable Port
## 1 Introduction  
In the trend of sustainable economy and low-carbon development, it is crucial to achieve the green development goal by implementing various green projects, which results in a very important decision-making problem, green project planning (GPP) problems. The GPP problem is to determine the construction sequence and construction proportion of green projects per year, which is a complex combinatorial optimization problem. Effective GPP is helpful to improve the carbon emission reduction performance.  
The port industry is a high energy-consumption industry. Facing ever-increasing market competition as well as energy-saving and emission-reduction requirements, the port industry has a pressing demand to implement various green projects. In real-world GPP in a port, multiple objectives need to be considered simultaneously, including cost and carbon emission reduction performance with the constraint such as time window, budget and time sequence.  
This paper thus investigates a GPP problem with realistic multi-objective consideration in developing a sustainable port. The objectives of the investigated problem include maximizing the total CO\({}_{2}\) emission reduction and minimizing the total project construction cost. To solve this problem, a weight sets-based multi-objective evolutionary optimization approach is proposed. This approach integrates a single-objective evolution optimization process, novel solution encoding and decoding heuristics, and a non-dominated sort technique. We validated the effectiveness of this approach by aseries of numerical experiments. The experimental data were collected from a representative China coastal port.  
This paper contributes the literature by: (1) effectively handling a novel green project planning problem with realistic multi-objective consideration in developing sustainable port; and (2) developing a weight sets-based multi-objective evolutionary optimization approach to solve realistic multi-objective optimization problems.  
The rest of this paper is organized as follows. Section 2 reviews the relevant studies in the literature. Section 3 presents the problem description and mathematical model of the investigated GPP problem. In Section 4, a weight sets-based multi-objective evolutionary optimization approach is developed to solve the problem. In Section 5, experimental results to validate the performance of the proposed model are presented. Finally, this paper is summarized and future research direction is suggested in Section 6.
## 3 Results
### The Seaweed Extracts Induce NO, Ptsg2, and PGE2 Production in RAW 264.7 Cells  
As previously mentioned, NO, Ptsg2, and PGE2 are crucial factors in immune response. To determine whether these algal extracts have any significant immunomodulatory effects, RAW 264.7 cells were treated with 0, 50, 100, 200, and 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL of SH, UP, and SF separately for 24 h. It was found that all three algal extracts induced mRNA expression levels of Nos2 with respect to the control. However, only SH showed significantly upregulated expression of Nos2 at 50 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, whereas UP and SF showed upregulation only at concentrations at or above 100 \(\mathrm{\SIUnitSymbolMicro g}\)/mL. Only SH and UP showed promising results in inducing Ptsg2 expression levels significantly at 200-400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, but SF showed a significant upregulation of Ptsg2 at the 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL concentration (Figure 5a,b).  
Similar treatments were administered and NO and PGE2 production were measured using the Griess reagent assay and ELISA kits. It was found that SH and UP induced NO production significantly within the concentration range of 100-400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL. However, SF significantly induced NO only at 200 and 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL. When compared with PGE2 production levels, SH significantly upregulated PGE2 production at 100, 200, and 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, while UP did so at 50, 100, 200, and 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL. SF was found to be significantly effective only at 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL (Figure 6a,b). By comparing the effects of all three algal extracts (at 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) on NO production, a significant increase in NO production was observed in the sequence UP > SH > SF (Supplementary Figure S3). This indicates the high immunomodulatory effects of UP compared to SH and SF. In addition, the anti-inflammatory properties of these algal compounds in ameliorating NO production were also analyzed in the presence of LPS. Cells were co-treated with 1 \(\mathrm{\SIUnitSymbolMicro g}\)/mL of LPS and different concentrations (50, 100, 200, and 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) of SH, UP, and SF for 24 h. It was found that all the three compounds were able to downregulate LPS-induced NO levels at the concentration range of 100-400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL (Supplementary Figure S4a-c).  
Figure 5: Seaweed extracts induce Nos2 and Ptsg2 mRNA expression levels in RAW 264.7 cells. RAW 264.7 cells were exposed to 50, 100, 200, and 400 \(\mathrm{\SIUnitSymbolMicro g}\)/mL of SH, UP, and SF for 24 h. The mRNA expression levels of (**a**) Nos2 and (**b**) Ptsg2 were determined by RT-PCR. * \(p\) < 0.05, *** \(p\) < 0.001.
# A Mobility-Aware Adaptive Duty Cycling Mechanism for Tracking Objects during Tunnel Excavation
## 5 Conclusions  
Tunnel construction workers face dangers working in dark and restricted conditions. For safe tunneling, tracking mobile objects with low latency is critical to manage dangerous construction environments and to enhance safety during tunnel construction. In this paper, we designed a model to track objects during tunnel excavation based on the mobility-aware adaptive duty cycling mechanism. This mechanism employs an explicit strategy that maximizes the quality of tracking using high duty cycles when an object moves. To reduce energy consumption, the proposed mechanism minimizes the duty cycle by increasing the sleep time when the object is immobile.  
We have compared the proposed mechanism to the periodic duty cycle mechanism by analyzing the expected energy consumption and the latency. In the investigated case, both the sleep time adjusting factors of \(\alpha\) and \(\beta\) were employed, so the latency was adjusted by increase or decrease the sleep time, depending on the mobility condition of the node. The proposed mobility-aware adaptive duty cycling mechanism consumes less energy than the periodic duty cycling mechanism when Equation (6) is satisfied. In the simulated case of the dump truck tracking during the mucking process, the tunnel length for which the proposed mechanism would consume less energy than the periodic one was computed using the parameters of duty cycle, truck moving speed, and the time stopped.  
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014R1A1A1003402). Also, this study was supported by the Basic Research Laboratory Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (Project No. NRF 2015-041523).  
[PERSON] designed and conducted the experiments, analyzed the data, and improved the writing of the paper; [PERSON] designed and performed the experiments, and wrote the related works; and [PERSON] created the main ideas and edited the manuscript.  
The authors declare no conflict of interest.
# Joint Maintenance Strategy Optimization for Railway
## 4 Numerical Analysis
### Cost Comparison  
The proposed maintenance strategy was compared with two periodic inspection strategies. These two strategies are stated below.  
Strategy 1: Daily inspection of the wheelset, cleaned and maintained every 3 \(\times\) 10\({}^{4}\) km. The wheelset is reprofiled if the wheel flange thickness exceeds the limit. The wheelset is periodically reprofiled every 20 \(\times\) 10\({}^{4}\) km. If the wheel diameter exceeds the limit, the wheelset is replaced.  
Strategy 2: Daily inspection, periodic cleaning and maintenance every 3 \(\times\) 10\({}^{4}\) km. When the flange thickness exceeds the limit and reprofiling is implemented, the wheelset is replaced if the wheel diameter exceeds the limit.  
The obtained results were compared with the above two maintenance strategies, as shown in Table 7. Comparing the proposed joint maintenance strategy results with Strategy  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Number**} & \multirow{2}{*}{**Interval/\(\Delta t\)**} & **Reproffiling Strategy/** & **The Risk of** & **The Number of** & **Expected Life/** & **Cost Rate/** \\  & & (\(Sd_{L}\), \(Sd_{H}\)) & **Failure/\(\alpha\)** & **Reproffiling/Times** & **10,000 km** & **(CNY/10,000 km)** \\ \hline
1 & 6 & (28.5, 31) & \(10^{-6}\) & 5 & 284.99 & 78.12 \\
2 & 6.5 & (28, 31) & \(10^{-4}\) & 5 & 287.70 & 77.13 \\
3 & 7 & (28, 31) & \(10^{-2}\) & 5 & 287.83 & 76.58 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison of optimal strategies under different fault risks.  
Figure 12: The curve of the preventive maintenance probability.  
Figure 13: The curve of the corrective maintenance probability.  
1, life expectancy increased by 11.51%, and the cost rate decreased by 27.06%. Compared with Strategy 2, life expectancy increased by 11.98%, and the cost rate decreased by 12.0%. It can be seen that the proposed maintenance strategy prolongs life expectancy and reduces the cost rate effectively.
## 3 Results
### Performance Evaluation  
PRR was used to detect signals in datasets (D1, D2, D3, D4) generated by non-stratification, gender-stratification, age-stratification and decision tree-stratification. Signal sets (S1, S2, S3, S4) were generated (See Figure 1). The comparison results are shown in Table 4.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Male** & **Female** & **Young (\(\leq\)20)** & **Middle (21–60)** & **Senior (\(\geq\)61)** \\ \hline Antibiotics & 170,739 & 188,754 & 25,979 & 225,676 & 140,458 \\ Non-antibiotics & 194,618 & 197,495 & 70,145 & 209,886 & 79,462 \\ \(\chi^{2}\) & 343.42 & & & 36,435.81 & \\ \hline \hline \end{tabular}
\end{table}
Table 3: The contingency table of drug category with gender and age.  
Figure 3: Decision tree.  
As can be seen from Table 4, \(F\) of the three stratification methods has been improved. Among them, the \(F\) value obtained by decision tree-stratification is the largest, and the \(F\) value of decision tree-stratification is 1.93% higher than that of non-stratification. In addition, the \(R\) obtained by decision tree-stratification is significantly improved, which is 16.57% higher than that of non-stratification.
# Monitoring System Enhancing the Potential of Urban Bekeeping
## 2 Methods
### Monitoring System Overview
#### 2.2.4 Beehive Weight Scale  
The beehive weight scale was developed from scratch because the commercially available scales do not allow monitoring the beehive weight with high temporal resolution. The schema and technical realization of the beehive weight scale are shown in Figure 3.  
Figure 3: The beehive scale: (**a**) schema, and (**b**) technical realization.  
Two common industrial load cells (NA1, 35 kg per load cell) were installed on aluminium profiles and attached to the long sides of the rectangular beehive base. A developed PCB module of load cell amplifier, based on the hx711 module, uses the digital two-wire interface to communicate with RPi, and it is compatible with GPIO (like commercial RPi Huts). A miniature single-board computer RPi Zero W was used as a data processing unit to handle the amplifier for unification with the multi-sensor device placed inside the beehive. The electronic parts were secured by an IP68 enclosure. The unit is powered by a 12 V DC cable with a DCDC converter on board, and Wi-Fi is used for data transmission. The accuracy (non-linearity, hysteresis, repeatability, creep) of the load cell is declared at the level of 0.02% F.S., which is 7 g. The temperature affects both zero value and signal output (respectively, 0.003% F.S./\({}^{\circ}\)C and 0.002% F.S./\({}^{\circ}\)C). The measurement resolution of the scale is 0.1 g. Based on the performed measurements, the electronic noise of the measurement circuit can be neglected in comparison with disturbances resulting from the vibrations of the mounting platform.
# A Systematic Survey on 5G and 6G Security Considerations, Challenges, Trends, and Research Areas
## 1 Introduction
### Scope and Contributions  
This paper makes multiple significant contributions to the realm of 5G security research by providing a comprehensive survey of its current state and potential future directions. In this 5G survey, we seek to understand and showcase the research work that has taken place and new contributions in the realm of privacy and security of 5G networks. Security is of utmost importance when users all over the world are accessing these networks for their personal, business, or government use. We look into the vast amount of work that has been published in academia and industry regarding 5G security standards and compare and contrast relevant topics. The motivation for this survey is to bring to light the advantage of viewing 5G security through the lens of the Confidentiality, Integrity, and Availability model for highly sensitive information. As this survey represents a systematic review, it encompasses all major components of any 5G network: UE, the RAN and its gNodeB (gNB), and the Core Network. These three distinct aspects are further dissected into their constituent foundational considerations or features. For example, the Core Network portion goes in depth on authentication and network access along with Software-Defined Networking (SDN), Network Function Virtualization (NFV), Mobile Edge Computing (MEC, also known as Multi-access Edge Computing), and more.  
The survey looks into the current methods of security and then compares and contrasts innovative new security mechanisms, like post-quantum cryptography for 5G. Finally, the aspect of Zero Trust networks is explored, expressing yet another future implementation of 5G security with considerations for highly secure communications. A high-level breakdown of what is covered in this survey can be found in Figure 1. Gathering new and trusted methods for security mechanisms in 5G will allow for the recognition of areas where improvements are already available or where additional research is still needed in order to continue working toward a more secure and confidential system architecture.  
The remainder of the paper is organized as follows. In Section 2, we present a comprehensive review of related works. Section 3 presents the systematic approach taken by 5G in providing security mechanisms across its architecture, while the focus in Section 4 is specifically on Zero Trust Architecture considerations, and in Section 5, we review several suggested future security enhancements for 5G and beyond. Finally, in Section 6, we present our conclusions.