esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Compared with the former two beam shaping elements, a Powell lens is a more sophisticated optical scribing prism, which can transform the circular laser spot into a straight line with more uniform optical density, better stability and linearity. The relevant principles of Powell lenses are described in the following section. A distinct advantage of the QEPAS technique is the linear relationship between the sensitivity and the incident laser power, which allows the performance of QEPAS based sensors to benefit from the novel high-power excitation laser source. Up to now, high-power laser and ultra-fast pulse laser have become the future trends with the development of laser techniques, such as high-power laser diodes (LD), light emitting diodes (LED) and high energy pulsed terahertz (THz) lasers. In order to improve the lateral mode and restrict the carriers in both directions parallel and perpendicular to the PN (positive-negative) junction plane so as to enhance the optical gain, the strip structure is manufactured and applied to some high-power lasers resulting in a stripe laser spot [30]. In the traditional QEPAS system, these stripe spot require a pair of wedge prisms or other complex shaping systems to converge the laser beam into a circular spot with small size to pass through the gap of QTF, resulting in the complexity of the QEPAS system and insufficient utilization of the QTF inner surface. In this work, we report a QEPAS sensor based on a Powell lens to compare the effect of circular beam and strip beam illuminating the QTF prong spacing. Resulting from the strip laser spot which is shaped by Powell lens to make the inner surface areas of the QTF prongs be fully exploited, a better QEPAS signal can be obtained. In addition, the work verified the feasibility of the combination of the QEPAS technique and the diverging laser sources or light sources with broad emitting stripes, which means that we do not need to waste excessive time and money in circularizing laser beams. This result provides the premise for the application of QEPAS sensors based on novel laser sources with a strip laser beam.
# Damage Detection of Insulators in Catenary Based on Deep Learning and Zernike Moment Algorithms
## 4 Experimental Testing and Analysis
### Damage Detection of Insulators
It can be seen that the distance between the seventh contour and the eighth contour is more than 90, which is much larger than the distance between other pieces, so it also can be judged that the insulator is damaged. Figure 14: Insulator with large damage range and its contour extraction results. Figure 13: Similarity standard deviation and similarity value between pieces of damaged insulator shown in Figure 11b. The test results of insulator damage-detection method based on Zernike moment on the dataset covering 512 images are shown in Table 4, including 30 false positives and four false negatives, and the accuracy of damage detection based on Zernike moment is 93.36%. While the test results of insulator damage-detection method based on Hu moment on the dataset covering 512 images are shown in Table 5, including 86 false positives and four false negatives. The accuracy of damaged detection base on Hu moment is 82.42%. It can be seen that, compared with the two characteristic moments, Zernike moment has higher accuracy in detecting damaged insulators of the catenary. It is analyzed that the main reason for the misjudgment is that the captured insulator image is blurry and the extracted contour is inaccurate.
## 3 Results
### Friction Force Results  
A comparison of the vibration levels in the system before applying additional mass and friction is shown in Figure 7a. The root mean square values for the three acceleration conditions (free, unbalanced, and unbalanced with friction) were 0.017, 0.18, and 1.260, respectively. The friction force in the measurement system has a nonlinear behavior which is shown in Figure 7b. This figure gives the mean friction force for each speed that for this experiment was changed from 700 to 1800 in 100-rpm steps. At the beginning, the friction force was the lowest (0.09 N), then it increased with speed up to 1400 rpm (0.88 N). Between 1500 and 1800 rpm, it decreased to 0.44 N and stabilized.
## 3 Results
### Device Performance  
The photovoltaic performance of the dyes in Family 1 and Family 2 compared to both benchmarks, **1a** and **2a**, are displayed in Table 2. DSSC cell fabrication and testing details (dark and illuminated J-V curves and electrochemical impedance spectroscopy) have been included in the supporting information. Device construction was done by hand, in ambient conditions, so multiple cells were made and averages and standard deviations from these cells are used in our table below. The number of cells that make up the averages and standard deviations are shown as column 'N' in Table 2.  
A quick glance at the data in Table 2 and the story is clear; all ferrocene derivatives drastically underperformed when compared to our benchmark dyes, and the device performance was inversely proportional to the amount of ferrocene present. This was a little disappointing particularly for **2c**, which exhibited similar optical and electrochemical behavior to **2a**. While the DSSC dye interface represents a complicated collection of competing rates (recombination, injection, regeneration, etc.), it is clear that the inclusion of ferrocene units in this family of dyes follows what was previously reported by [PERSON] et al. [50,51]. In their work (see cited entries in Table 2), there was a significant decrease in performance when conjugating ferrocene to the organic dye scaffold of **1a**. The recombination rates for **1c** (TiO2 to Fc+) were determined to be 300 ps, while for **1a** (TiO2 to TPA+), the rate was 12 ns. The authors concluded that this faster recombination rate for the ferrocene derivatives was a result of the twisted intramolecular charge transfer state being disrupted by the intramolecular electron transfer from ferrocene, leading to poor device performance. We anticipated that our dyes possessing two TPA rings and greater charge separation would mitigate this deleterious behavior, but our device data is consistent with [PERSON] and this seems to suggest that our ferrocene dyes (**2b-2e**) are also unsuitable for DSSC devices. However, the ferrocene potentials are different for our new family of dyes, and spectroelectrochemical measurements suggest there is another reason for our dyes' deleterious behavior in devices.
## 2 Materials and Methods  
### Study Sites and Environmental Variables  
The study area contains eight EC flux sites located in Denmark, Finland and Sweden, at latitudes from 55\({}^{\circ}\) N to 68\({}^{\circ}\) N (Figure 1). The flux sites belong to the ICOS infrastructure ([[https://www.icos-ri.eu](https://www.icos-ri.eu)]([https://www.icos-ri.eu](https://www.icos-ri.eu))) and follow the ICOS measurement protocols [50]. We analyzed data from 2016 to 2017, except at the SE-Svb site where we used only the data from 2016. There is an air-temperature gradient from south to north across the eight sites, with climate zones ranging from temperate in the south, through hemiboreal and boreal, and up to the northernmost subarctic landscapes. The sites cover diverse and major Nordic land cover types: evergreen forest, deciduous forest, wetlands, and agriculture (Table 1).  
At the ICOS sites, auxiliary meteorological parameters, such as photosynthetically active radiation (PAR), air temperature (T\({}_{\mathrm{a}}\)) and water vapor pressure deficit (VPD) are measured using standardized methodology [51; 52]. PAR is measured as instantaneous photosynthetic photon flux density (PFFD, \(\mathrm{\mu mol}\) m\({}^{-2}\) s\({}^{-1}\)) at the sites and was summed to daily total PFFD (\(\mathrm{\mu mol}\) m\({}^{-2}\) d\({}^{-1}\)). The measurements of T\({}_{\mathrm{a}}\) (\({}^{\circ}\)C), relative humidity, wind components and gas concentrations were located above the canopies at the forest sites and at around 2 m above the ground at the agriculture and wetland sites. VPD (hPa) is estimated from T\({}_{\mathrm{a}}\) and relative humidity. The VPD and T\({}_{\mathrm{a}}\) data used in the study were daily averages.  
The net ecosystem exchange of CO\({}_{2}\) (NEE) at ICOS sites is measured by the EC method, with standardized methods and data processing [53; 54]. GPP (g C m\({}^{-2}\) day\({}^{-1}\)) was estimated by partitioning the NEE, with the help of auxiliary in situ environmental variables, such as global radiation, air or soil temperature, and VPD, by using the REd-dyProc tool [55; 56], implemented as an online tool ([[https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProCWeb](https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProCWeb)]([https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProCWeb](https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProCWeb))).
# Scheduling of Industrial Control Traffic for Dynamic RAN Slicing with Distributed Massive MIMO +
## 6 Numerical Experiments
### Formulations  
To formulate our optimization problems, we will use mixed-integer programming [35; 36]. We ran each of the experiments described above using each of the two formulations: FPRM/1 and FPRM/2. We will first give the results using the general formulation (FPRM/2), as this gives a ground truth for the optimal frame length for each traffic profile and the number of nodes, up to the maximum frame length. The fixed frame length formulation (FRM/2) was then run iteratively, with the frame length starting at 1 slot and increasing to the maximum of 15 slots. This gives an alternative method to find the optimal frame length, meaning that the fixed frame length formulation can be used both in cases where the frame length is indeed static, and in cases where the frame length can vary. In our results, we compare the total solution time for these two approaches to find the optimal frame length, using the general (variable frame length) formulation directly, or iteratively applying the fixed frame length formulation.  
In solving the individual optimization problems, we do not specify a solution algorithm but simply invoke the solver, CPLEX. However, CPLEX internally uses branch-and-bound, which, in the worst case, has exponential complexity, although it is lower in the average case. We can thus see the trade-off in complexity for our iterative vs. direct solution method; solving each problem will, in the worst case, take an exponentially longer time as the number of nodes increases, and using the iterative approach then wraps this in a loop (linear complexity) proportional to the number of nodes. This should, in theory, make the iterative method slower; however, as we will see, in practice, FPRM/1 solves much faster than FPRM/2. Here, then, as sometimes occurs with these types of problems, theoretical complexity does not always translate to performance in practice.
# An Accurate, Efficient, and Stable Perspective-n-Point Algorithm in 3D Space
## 4 Conclusions and Prospects  
The PnP solution, based on a projective imaging model of 3D points, fails to cover accuracy, robustness, and efficiency simultaneously because of the diverse spatial distribution and quantity of 3D reference points, which prompted us to propose a new method for solving the PnP problem, the Hidden PnP. The Hidden PnP employs the CGR parameter to parameterize the rotation matrix. Differing from the best matrix synthesis technique, the Grobner technique, the method reduces computational burdens, as it does not require construction of a large matrix elimination template in the polynomial solution phase. The CGR parameter matrix was solved by the hidden variable method, and the Gauss-Newton method was adopted for rapid and accurate location of a solution. The comparison test demonstrated that the Hidden PnP outperformed eight other algorithms in solution accuracy, stability, anti-noise ability, and calculation speed, in both synthetic data and real experiments, which supported its application to high precision position measurement in a common environment. Future work will, therefore, involve applying this algorithm to vision-based navigation for intelligent vehicles and UAVs with real-time positional measurement techniques. Conceptualization, R.Q., G.X., P.W. and Y.C. ; Methodology, R.Q. and P.W. ; Resources, G.X., Y.C. and W.D. ; Software, R.Q. and P.W. ; formal analysis, R.Q., G.X. and P.W. ; Writing--original draft, R.Q. ; Writing--review and editing, G.X., P.W. and R.Q. All authors have read and agreed to the published version of the manuscript. This work was supported, in part, by the National Key Research and Development Plan, under Grant 2018 YFB2003803, and, in part, by the National Natural Science Foundation of China, under Grants 62073161, 61905112 and U1804157.
# A Novel Visual SLAM Based on Multiple Deep Neural Networks
## 5 Conclusions  
In this paper, we proposed a novel Visual Odometry combining a SG-Detector, a SG-Matcher and a se(3)-based pose fusion estimation algorithms and a deep LoopClosing module based on SG-Matcher and Seq-CALC networks. Then, a complete visual SLAM system was designed using them.  
Our proposed system achieves better performance than ORB-SLAM2, LSD-SLAM and DSV-SLAM on most sequences of the KITTI odometry dataset. For example, the estimation error is generally reduced by 0.1 m, and it can run in real time at 0.08 s per frame on GeForce RTX 3060 Mobile GPU and Intel Core i7-11800H CPU.  
The experimental results indicated that corresponding feature matchers should be introduced in visual SLAM systems using deep features, since traditional matching methods for hand-crafted features do not match well the deep feature descriptors with the deep feature extractor.  
Although our system is currently only tested on the KITTI odometry dataset, the experimental results do yield some indications on the superiority, feasibility and, particularly, the practicality of the proposed SLAM system. This is because the KITTI odometry dataset is real-time data derived from real scenes. In future work, we will focus on the lightweighting of the deep feature matcher and deep feature extractor because these two deep neural network models require a lot of memory and occupy most of the running time of the whole system. If a more lightweight network structure can be designed, it will enable our proposed system to migrate to run in real time in an embedded system. This allows an easier integration of our system into the existing mobile robotics, MAVs, autonomous driving and augmented reality systems.  
[PERSON] performed the experiments, wrote and revised the manuscript; [PERSON] and [PERSON] managed the project, acquired the fund, conceived the work, designed the experiments, guided and revised the manuscript; [PERSON] and [PERSON] analyzed the experimental results and revised the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research was funded by \"Pioneer\" and \"Leading Goose\" R&D Program of Zhejiang Province (2022C04012), the Key R&D Program of Zhejiang Province (2021C04030), the Natural Science Foundation of Zhejiang Province (LGG20F020007) and the Public Welfare Technology Application Research Project of Zhejiang Province (LGF22F030005).  
Not applicable.  
The authors declare no conflict of interest.
# A Framework for Market State Prediction with Ontological Asset Selection: A Multimodal Approach
## 7 Conclusions
### Limitations of the Study  
While the results are promising, this study has certain limitations that need to be addressed in future research:  
* Data Dependence: The model's performance heavily depends on the availability and quality of financial news and real-time financial indicators. For example, inaccuracies or delays in financial news sentiment analysis could lead to misclassification of market states, particularly during high-volatility periods. Similarly, errors in real-time indicators such as the Illiquidity Index (ILLIQ) may introduce noise into the predictive framework, reducing its overall accuracy. Future work should explore robust preprocessing techniques to filter out noise and inconsistencies and consider redundant data streams for greater reliability.  
* Threshold Selection: The fixed threshold (0.5) for stock classification, while practical, may not adapt optimally to market conditions. Dynamic or data-driven threshold selection based on market trends could yield more accurate and flexible classifications.
* Market Regime Generalization: The classification of market states (bull, bear, neutral) relies on predefined percentage change thresholds that may not fully capture regime-specific behaviors, especially in extreme or volatile conditions. Incorporating adaptive regime classification methods could improve model accuracy.
* Computational Costs: The integration of multiple models (NMC, BERT, LSTM) is computationally intensive, which may limit scalability for real-time applications. Further research into model compression techniques or optimized architectures is necessary to address this limitation.
# Simulation of Nuclear Quantum Effects in Condensed Matter Systems via Quantum Baths
## 5 Applications of Quantum Baths to Realistic Systems
### Structural and Thermodynamic Properties
#### 5.1.1 MgO  
[PERSON] and coworkers [12] showed that the QTB reproduces the experimental trends of the lattice parameter and the heat capacity of the MgO crystal as a function of temperature. While recovering the classical limit for temperatures close to or above the Debye temperature (\(\Theta_{D}\simeq 940\) K in MgO), the specific heat follows the expected quantum behavior at low temperatures (\(C_{V}\to 0\) as \(T\to 0\)), in excellent agreement with experimental data.
## 2 Methodology
### Chemicals Screening
#### 2.5.4 Static Adsorption Study  
The retention of surfactant on the reservoir rock surface and within the pores, known as adsorption, is a well-recognized challenge in chemical EOR methods. To investigate this phenomenon, static adsorption studies are widely employed, wherein the accumulation of surfactant molecules on sand grain surfaces is examined. In this research, the adsorption behavior of the screened surfactant on Field A rock was thoroughly analyzed, focusing on the impact of mixing time. Furthermore, the study explored the effects of alkali and nanoparticles on surfactant adsorption through static adsorption experiments utilizing NP-surfactant and alkali-surfactant solutions. Specifically, two alkalis were chosen for the surfactant-alkali solutions: sodium carbonate (Na\({}_{2}\)CO\({}_{3}\)) and sodium hydroxide (NaOH), each at concentrations of 0.01 wt%, 0.015 wt%, and 0.02 wt%. Silica nanoparticles were used at concentrations of 0.05 wt% and 0.1 wt% for the surfactant-nanoparticle solution. These concentrations were selected based on the aqueous stability and transparency of alkali-surfactant and NP-surfactant solutions. The alkali-surfactant and NPs-surfactant solutions prepared at different concentrations were placed in 10 mL glass vials and were kept at room temperature and in the oven at 63 \({}^{\circ}\)C. After three and seven days the samples were assessed for the transparency of the solutions and the precipitation appearance. The samples with precipitation were dropped and not studied for static adsorption of surfactant.  
The stable surfactant-alkali solutions or surfactant-nanoparticle solutions were mixed in the rotary oven at room temperature with crushed Field A sandstone at a mass ratio of 4:1. Such a proportion was chosen to ensure complete adsorption on the sandstone particles. The aging process continued for different time periods: 4 h, 12 h, 24 h, 36 h, and 72 h. The samples were diluted 100 times and subsequently analyzed using a UV-Vis spectrophotometer. This dilution process was necessary due to the resolution limits of the apparatus, which allow for more precise and accurate results, particularly for lower solution concentrations of up to 500 ppm.  
Figure 1: Schematic illustration of IFT apparatus.
# Classification and Analysis of Malicious Code Detection Techniques Based on the APT Attack
## 5 Classification and Analysis of Malicious Code Detection Methods
### Anomalous Symptom Detection Method  
Existing pattern-based, heuristic-based, reputation-based, behavior-based, and virtualization-based detection methods can detect and prevent malicious codes. However, existing methods cannot adequately defend against penetrating attacks that utilize unknown attack techniques, such as APT attacks, as these methods require a lot of time to collect various types of information. To solve these problems, a method for detecting anomalous symptoms in the system has been proposed. This method uses correlation analysis to detect anomalous symptoms by collecting and integrating logs of activity in the system. In particular, this requires detection techniques at a stage where the system is infected by malicious code, the detection of unknown new malicious code, and techniques to determine whether traffic is benign or abnormal. To achieve this, techniques for analyzing network behavior and state have emerged, as have intelligent security technologies. The technique for analyzing network behavior is a method of detecting malicious behavior based on the behavior of a large-capacity and real-time network of various systems, protocols, and users. The technique for analyzing network state is a method of analyzing malicious behavior based on the system of the presently connected or requesting network and its state changes. Modern intelligent security technology analyzes threats in real time by integrating these types of information and methods. Therefore, certain information must be collected before this method can be used. The characteristics of this information are defined by applying statistical techniques to data, such as a profiling technique for the extraction of meaningful information and a data mining technique for the extraction of statistical rule patterns from a large amount of data. Nevertheless, despite these advantages, it is technically difficult to collect large-capacity and high-speed traffic from a network or to analyze the correlations in this traffic, because the system is exposed to threats if the security system is not capable of real-time processing [13].