esa-sceva/satcom-chunk-collection huggingface dataset:
# An Anti-Interference Method Based on Energy Residual Searching in GNSS Positioning Applications
## 6 Conclusions  
The overall computational complexity of our method is as follows: the FrFT has a complexity of \(O(NlogN)\), the optimization process employs a variant of the Fibonacci search with a complexity of \(O(logN)\), and the energy residual calculation has a linear complexity of \(O(N)\). Given these complexity levels, the combined approach can be efficiently executed on platforms with moderate computational capabilities, ensuring feasibility for applications that require real-time or near-real-time processing.  
This paper presents an anti-interference method based on energy residual searching to counteract the impact of LFM interference on GNSS signals. By systematically analyzing and optimizing the fractional-order parameters, the method effectively suppresses LFM interference, thereby enhancing the anti-jamming performance of GNSS signals. In our study, we first decomposed the signal, using the FrFT, which clustered LFM interference in the transform domain without significantly affecting the GNSS signals and noise. The N-sigma method calculated a threshold for the spectral component removal, eliminating high-amplitude LFM interference components. The energy residuals, defined as the difference in signal energy before and after component removal, were optimized to obtain the optimal fractional order. Our experimental results demonstrate that this approach significantly suppresses LFM interference, improving GNSS signal quality and resilience. This research offers an effective strategy for mitigating LFM interference and lays the groundwork for further studies and applications.  
Figure 9: The interference-mitigation performance of the proposed method in different scenarios.  
**Author Contributions:** Conceptualization, X.J.; Methodology, X.J., M.L. and Y.N.; Software, M.L. and J.W.; Validation, Y.N.; Formal analysis, J.W.; Investigation, N.X.; Resources, X.J.; Writing--original draft, Y.N.; Writing--review & editing, M.L. and N.X.; Project administration, N.X.; Funding acquisition, X.J. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the State Grid Corporation of China Headquarters Technology Project under Grant 5500-202440171A-1-2N.  
The data presented in this study are openly available through TEXBAT, which can be accessed at [[https://radionavlab.ae.utexas.edu/texbat](https://radionavlab.ae.utexas.edu/texbat)]([https://radionavlab.ae.utexas.edu/texbat](https://radionavlab.ae.utexas.edu/texbat)) (accessed on 10 November 2024).  
Author [PERSON] was employed by the company State Grid Electric Power Research Institute Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 1 Introduction  
In recent years, orthopaedic surgeons worldwide have given significant importance to lower extremity alignment when implanting a total knee arthroplasty. However, in recent studies, little attention has been paid to the precision with which implants have been positioned using conventional cutting guides. The substantial number of patients arriving at medical institutions with this medical condition has pushed the orthopaedic surgeon towards finding ways to solve this problem in the most adequate manner. Total knee arthroplasty (TKA) is the gold standard for the definitive treatment of late-stage osteoarthritis [1,2].  
One crucial aspect in the implantation of a TKA is the precise orientation of the femoral and tibial components [3]. The incorrect placement of the prosthetic components or poor coverage of bone surfaces [4,5] and the subsequent incorrect postoperative alignment can lead to a poor functional result and aseptic loosening of the implant due to inadequate biomechanical functioning and the subsequent increased wear of the polyethylene [6, 7, 8]. In addition, several authors suggested that an alignment within 3\({}^{\circ}\) of the vurus or valgus provides the best long-term TKA survivorship [9,10].  
For this reason, some authors have proposed various studies to assess the effectiveness and accuracy of bone cuts when TKAs are performed. Navigation and patient-specific instrumentation (PSI) were once considered newer and more precise alternatives to conventional cutting guides [8,11].  
However, the percentage of cases that fall outside the accepted values are between 5% and 21% when we use navigation as an additional guidance method to perform bone cutting [8,12,13]. In the same way, some authors also think that PSI does not translate into greater precision and that it does not make for better clinical or radiological results [14].  
Over the years, some surgeons have considered modifying the distal femoral bone cut to improve implant stability [15]. However, it is especially important that this modification be translated into the final radiological result to assess whether it is crucial to achieving said objective or, on the contrary, if this stabilization is produced by other compensation mechanisms, meaning that modifying the cutting angle is not necessary. The authors of this study consider it important to assess the difference found between the intraoperative planning and the final radiological result and to be aware of the need to perform these calculations. If the difference between the planned and actual is very great, it probably does not make sense to justify this coronal alignment philosophy.  
The main purpose of the present study is to assess, in patients undergoing total knee replacement, whether the difference between the planned angulation in the distal femoral cut and proximal tibial cut and the angulation obtained in the postoperative radiological control is low enough to consider the conventional bone-cutting guides reliable. The secondary objective of the present study is to identify if there is a particular pattern in our patients that makes it to observe this difference.
## 4 Simulations and Results
### Results
#### 4.2.2 Multiple Criteria  
If there is more than one user with a shortage of energy then, according to this approach, priority is given to the user who contributes more in 24 h in terms of multiple parameters. In the current implementation, the contribution is defined on the basis of renewable capacity, selling price and contribution of surplus energy, as given in Equation (11). The values of weights \(P_{1}\), \(P_{2}\) and \(P_{3}\) in our implementation are same i.e.,  
\[P_{1}=P_{2}=P_{3}=1/3 \tag{13}\]  
The surplus energy price associated with all users is according to Figure 4 while the contribution in terms of surplus energy is given in Figure 8.  
Figure 8: Contribution of surplus energy.  
Figure 7: Price of surplus energy allocated by optimization algorithm.  
Surplus and shortage of energy after optimization is shown in Figure 9 while price of allocated surplus energy is shown in Figure 10. A shortage reduction of 44.13% has been observed using this approach for the same scenario used in single criterion approach. The total price of allocated surplus energy is calculated by the algorithm as 534.4 PKR. These results are better than the single criterion approach in terms of reduction in shortage, however note that the results are heavily dependent on the initial surplus/shortage scenario.  
Note that the value of variable '\(w\)' in above mentioned simulations (see Equation (8)) is taken as zero, which means the results in Sections 4.2.1 and 4.2.2 give maximum possible utilization of surplus energy for the given scenario. In order to see the effect of '\(w\)', we have simulated the multiple criteria approach with different '\(w\)' values; the results are presented in Table 2.  
The increasing value of '\(w\)' reduces the price but at the same time decreases the amount of surplus energy to be allocated to users with shortage. This has a negative impact on shortage reduction. A small value of '\(w\)' (between 0 and 0.1) biases the optimization algorithm slightly in the favor of low price options while keeping the shortage reduction near to optimal.  
Figure 10: Price of allocated surplus energy.  
Figure 9: Optimized shortage and surplus energy according to multiple criteria approach.
## 4 Simulations Results Using Actual Industrial Data  
In this section, 164 sets of actual industrial data collected from a Chinese dressing plant are used for simulation to verify the effectiveness and performance of the proposed algorithm preliminarily. The actual production data are expanded with the GAN and optimize the feeding value with the proposed method. In order to verify the accuracy of this algorithm, this algorithm is compared with the SVM, ELM, and traditional CBR algorithms.
## Materials and Methods
### Crystal Violet (CV) Staining Assay  
The cytotoxic effects of MnTrHex alone in both NSCLC cell lines were first evaluated by the CV staining assay, following a previously described protocol [42]. Briefly, cells were seeded at 3 \(\times\) 10\({}^{3}\) cells/well in 200 \(\upmu\)L of a complete medium in 96-well plates and incubated for 24 h at 37 \({}^{\circ}\)C under a 5% CO\({}_{2}\) atmosphere. After the 24 h period, the culture medium was renewed, and the cells were incubated with a range of MnTrHex (0.5\(-\)25 \(\upmu\)M) concentrations for 72 h. Cells were also incubated with 50 \(\upmu\)M of cisplatin as a positive control. After incubation, cells were washed with PBS to remove non-adherent cells (non-viable cells). The adherent cells were fixed with ice-cold 96% ethanol for 15 min and stained with 0.1% CV for 5 min. After washing the microplate with tap water, the stained cells were resuspended in 200 \(\upmu\)L of 96% ethanol/1% acetic acid. The absorbance was measured at 595 nm (OD595) using a SPECTROstar OMEGA microplate reader (BMG Labtech, Offen  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Primer Sequence** & **Reference** & **Accession Number** \\ \hline \multirow{2}{*}{CAT} & F: TGGAGCTGTAACCCAGTAGG & [38] & NM\_001752.4 \\  & R: CCTTTGCCTTGGAGTTTTGGTA & & \\ \hline \multirow{2}{*}{GPX1} & F: GCCTTCCAGACCATTGCACT & [39] & NM\_000581.4 \\  & R: CGAGGTTGATTTTCTGTAAGATCA & [40] & NM\_001202431.2 \\ \hline \multirow{2}{*}{PRDX1} & F: CCACCGGAGATCATTGCTTCA & [41] & NM\_001202431.2 \\  & R: AGGTGATTGACCCATGCTAGAT & [40] & NM\_005809.6 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Primers used for qRT-PCR characterization of NSCLC cells.  
burg, Germany). Absorbance values presented by control cells corresponded to 100% of cell viability. Three independent experiments were performed, and six replicates were used for each condition in each independent experiment. The half-maximal inhibitory concentration (IC\({}_{50}\)) was calculated based on the concentration-response curve using GraphPad Prism(r) 7.0 (GraphPad Software, Inc., La Jolla, CA, USA). Image acquisition was performed using a Motic AE2000 Inverted Phase Contrast Microscope and a 40 \(\times\) objective.
## 2 Literature Review
### Scheduling of Bottling Operations  
There has been significant interest in researching the final stage of beverage production from a tactical perspective. The General Lot Sizing and Scheduling Problem (GLSP), introduced by [PERSON] (1988), laid the foundation for addressing production quantities and scheduling decisions sequentially. [PERSON] (2000) [PERSON] (2000) expanded this model to include sequence-dependent setup times (GLSPST), where setup costs vary with the processing order, and later extended it to parallel production lines (GLSPPL) for high-volume operations ([PERSON], 2001).  
In a historical context, the Simultaneous Lot Sizing and Scheduling Problem (SLS), formulated later by [PERSON] (2000) [PERSON] (2000), integrates lot sizing and scheduling decisions into a single model. Additionally, [PERSON]'s extension in 2011 [PERSON] (2011) incorporates time-dependentsetups and period overlapping, further adapting the model to real production systems where both time and sequence are critical.  
These models have proven valuable in bottling operations across various industries, including the works of [PERSON] et al. (2012) [22] and [PERSON] et al. (2015) [23] in the soft-drink and mineral-water sectors, as well as studies on beer by [PERSON] et al. (2017) [24] and [PERSON] et al. (2019) on fruit-based beverages [25]. [PERSON] et al. (2020) [26] emphasize that efficient synchronization between preparation and bottling stages is essential to minimizing idle time and ensuring continuous production flows.  
In the specific case of wine-bottling operations, however, the available models are more limited. [PERSON] et al. (2006) [27] propose a simple scheduling model for a single production line with multiple products that primarily considers personnel capacity via normal and overtime hours, lacking flexibility in team allocation. [PERSON] and [PERSON] (2017) [28] introduced an MIP formulation to address bottling scheduling, while [PERSON] (2020) [29] proposed a collaborative approach to scheduling in this context. [PERSON] et al. (2022) [30] further contributed by developing a robust scheduling method for large-scale wine-bottling operations, employing decomposition techniques to efficiently handle the complexities of sequence-dependent setups and reconfiguration processes. These contributions underscore the need for an integrated, advanced scheduling model that can effectively address the challenges unique to wine-bottling operations.
# An Energy Demodulation Based Fiber Optic Sensing System for Landslide Early-Warning
## 5 Features
### Grading the Demodulation Alarm  
Different geological conditions and external environments impact on landslides differently. A common reason for the high rate of false alarm in other systems is the lack of customizing to these conditions. The FOS-LW alarm threshold can be graded in multiple levels, with different alarms responding according to the specific grades. In this way, the accuracy of the early-warning system can be greatly improved. Meanwhile, the system does not measure specific values of the deformation; thus, significantly reducing the computing efforts behind the scene. As soon as the light intensity is lower than the threshold level, the system alarm is triggered.
### Experimental Results  
The results of the different performed experiments were analyzed using the DIC technique. In this paragraph, the focus is on the out-of-plane displacement and the in-plane strains due to the impact of the FSPs. The fundamental principles of the method are well described in [25]. A parametric study was conducted to choose the optimal parameters for the DIC analysis. The choice of the subset size influences the deformation results. On one hand, choosing a high subset value leads to a loss of spatial information around the impact zone. On the other hand, choosing a smaller subset size leads to noisy results or even to an impossibility of calculating the deformations. For example, Figure 3 compares the out-of-plane displacement field obtained using subsets of 9 and 21, respectively. The subset spacing was set to 5. The strain filter size defines the gauge length that is considered for the strains calculation. If the filter size is small, a higher resolution and noisier data are obtained and vice versa. A pixel subset of 21, a subset spacing of 5, and a strain filter size of 15 are finally considered for result analysis.
# Recent Advances and Applications of Semiconductor Photocatalytic Technology
## 3 Common Classification of Photocatalysts
### Non-Oxide Photocatalyst  
Many non-oxides also have good photocatalytic properties [94; 95]. Among them, semiconductor metal sulfides have attracted intense attention because of their special structure and excellent physical and chemical properties. Some such non-oxides include as molybdenum sulfide (MoS\({}_{2}\)), tungsten sulfide (WS), copper sulfide (CuS) [96], zinc sulfide (ZnS) [97; 98], and cadmium sulfide (CdS) [99]. Of course, in addition to the sulfides, nitrides, such as C\({}_{3}\)N\({}_{4}\), also show excellent photocatalytic properties.  
Next, we will take CdS, CuS, ZnS, and C\({}_{3}\)N\({}_{4}\) as examples to demonstrate their applications in photocatalysis.
# A Low-Profile Ferrite Dipole VHF Antenna for Integrated Mast Applications
## 2 Antenna Design
Figure 2: Complex permeability and magnetic loss tangent properties of the MP2106-0M0 ferrite. side portions of the ferrite dipole. The magnetic field distribution for the 1-loop feed has a triangular distribution, like the electric field of a small dipole, which results in low radiation efficiency of the antenna. As shown in Figure 3c,d, as the number of loop feeds increases and the magnetic fields become evenly distributed. The 5-loop feed structure is suitable to realize a uniform magnetic field distribution over the entire ferrite dipole, and therefore maximizes the radiation efficiency of the antenna. The simulated magnetic field distributions obtained along the length of the dipole (\(x\)-axis) are shown in Figure 3e for the 1-loop feed and 5-loop feed. Clearly, the magnetic field distribution for the 1-loop feed has a triangular distribution while that for the 5-loop feed has a nearly uniform distribution. Figure 4 plots the simulated realized vertical-polarization gains at the main beam direction (\(+z\)) for the ferrite dipole antenna on a finite ground plane with a size of 900 mm \(\times\) 900 mm with different numbers of loop feeds (see Figure 3a). The gains of the dipole antenna with the 1-loop feed and the 5-loop feed vary from \(-\)31.9 to \(-\)7.5 dBi and \(-\)31 to \(-\)1.28 dBi, respectively, in the operating band. Obviously, when the loop feed structure increases, the radiation efficiency of the antenna is increased  
Figure 3: Magnetic field distribution of the ferrite dipole antenna at 150 MHz. (**a**) Geometry of the antenna with different numbers of loop feeds: (**b**) 1-loop feed, (**c**) 3-loop feed, (**d**) and 5-loop feed. (**e**) Simulated magnetic field distribution along the length of the dipole. due to the change in the magnetic field distribution. The gain of the dipole antenna with the 5-loop feed is improved considerably compared to that of the 1-loop feed due to the quasi-uniform magnetic field distribution. The maximum gain improvement is 6.4 dB at 280 MHz. The gain of the dipole antenna with the 5-loop feed is approximately 0.8 dB more than that of the dipole antenna with the 3-loop feed in the middle of its operating band.
# Electrospinning-Based Carbon Nanofibers for Energy and Sensor Applications
## 2 Electrospinning of Carbon Precursor Polymer
### Polymer Nanofibers for Carbon Nanofibers  
#### 2.2.1. Polyacrylonitrile-Based Carbon Nanofibers  
Polyacrylonitrile (PAN) has been used as a precursor for many carbon materials because of its unique properties including hardness, relative insolubility, and high melting temperature [35]. The high-performance properties of PAN make it an ideal candidate for electrospinning and fiber fabrication. In fact, it has been proven that the carbon fabricated from PAN has a higher melting point and carbon yield than some of the well-known precursors such as pitch or crayon [36; 37]. The most commented solution used in the case of PAN is dimethylformamide (DMF). The change of PAN to carbon consists of a three-step heating process, that is, stabilization, carbonization, and orientation improvements (graphitization) [38]. During the carbonization step, an inert gas (such as argon or nitrogen) flows to protect the decomposition of the polymer chain (Figure 2) [10; 11]. In most research, the stabilized PAN fiber was carbonized and retained in the carbonization process due to the limited state of laboratories. Although the process stopped at such an early stage, at around 850 \({}^{\circ}\)C, the final product can still give excellent outcomes in applications such as energy storage or the use of sensors [39; 40].  
Figure 1: Description of structure and components of electrospinning equipment.  
Figure 2: Chemical structure of sp\({}^{2}\) carbon produced after heat treatment of PAN.
## 3 System Design and the Proposed SEAC-Based Resource Allocation Methodology
### SEAC-Based Resource Allocation Algorithm
Soft updates are applied to the target policy network and the target value network, ensuring smooth transitions and stable learning by gradually moving the parameters toward those of the online networks. To ensure training stability, the parameter update for the critic's value network is given by  
\[\theta^{Q}=\ \theta^{Q}+\alpha\delta_{t}\
abla_{\theta_{Q}}Q\Big{(}s,\ a,\ \theta^{Q}\Big{)} \tag{6}\]  
where  
* \(\alpha\) is the learning rate;
* \(\
abla_{\theta_{Q}}Q(s,\ a,\ \theta^{Q})\) represents the gradient of the value function with respect to its parameters. Similarly, the update for the actor network parameters is  
\[\theta^{\mu}\leftarrow\theta^{\mu}+\alpha\delta_{t}\
abla_{\theta_{\mu}}\log \pi(a_{t}|s_{t},\ \theta^{\mu}) \tag{7}\]  
where  
* \(\pi(a_{t}|s_{t},\ \theta^{\mu})\) is the policy, which represents the probability of taking action \(a_{t}\) given state \(a_{t}\). To ensure stability during training, soft updates are performed on the target networks, gradually moving their parameters closer to those of the online networks:  
\[\theta^{\mu^{\prime}} \leftarrow\tau\theta^{\mu}+(1-\tau)\theta^{\mu^{\prime}} \tag{8}\] \[\theta^{Q^{\prime}} \leftarrow\tau\theta^{Q}+(1-\tau)\theta^{Q^{\prime}} \tag{9}\]  
where\(\tau\) is a small positive value representing the soft update rate. The actor and critic networks work together, with the critic providing feedback via the TD error to guide the actor's policy adjustments and to refine the value function. By leveraging both the local and shared experiences, the SEAC framework enables vehicles to improve their decision making for resource allocation in the 5G-NR-V2X networks. Soft updates maintain network stability by preventing drastic changes to the parameters of the target networks. This method allows the SEAC model to manage resource allocation effectively, minimizing collisions and congestion in high-traffic environments. By continuously sharing experiences and adjusting policies based on feedback, the framework adapts to varying traffic conditions and optimizes communication channels in dynamic V2X environments.