esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Proposed Circuit with ASK Modulation
### Design Procedure  
The power transmission of IMDs, such as cochlear implants, is typically less than 100 mW [22]. Hence, the output power of the IMD in this study is selected to be close to 100 mW. The receiver load \(R_{\mathrm{o}}\) is chosen to be 1 k\(\Omega\). The \(R_{\mathrm{L}}\) can be calculated as follows [28].  
\[R_{L}=\frac{1}{2}(1+\frac{V_{\mathrm{diode}}}{V_{\mathrm{rec}}})R_{\mathrm{o}} \tag{22}\]  
Where \(R_{\mathrm{o}}\) denotes the implant load, \(V_{\mathrm{rec}}\) represents the rectifier voltage, and \(V_{\mathrm{diode}}\) refers to the diode's forward voltage. In this article, the value of the \(V_{\mathrm{diode}}\) is approximately 0.4 V, while \(V_{\mathrm{rec}}\) is set at 5 V. Consequently, the \(R_{\mathrm{L}}\) is about 540 \(\Omega\).  
The cochlear implant is employed as a demonstration application to validate the research in this article. Based on the proposed coil design in [28], the circular planar spiral coil implemented on PCB emerges as a suitable candidate for WPDT. The values of \(L_{\mathrm{t}}\) and \(L_{\mathrm{r}}\) are designed to be 3 uH and 1 uH, and their equivalent series resistances \(r_{\mathrm{t}}\) and \(r_{\mathrm{r}}\) at 16 MHz are 0.44 \(\Omega\) and 0.36 \(\Omega\), respectively. Additionally, the transmitter and receiver coils turn numbers are eight and five, respectively.  
The value of \(C_{\mathrm{r}}\), which resonates with \(L_{\mathrm{r}}\) at 16 MHz, was calculated to be 100 pF. Based on the aforementioned, the Class-E PA operates in an optimally tuned state when the data signal is at a high level. Hence, the value of \(C_{\mathrm{p}}\) and \(C_{\mathrm{t}}\) can be determined using (9) as follows: \(C_{\mathrm{p}}\) is calculated to be 29 pF, and \(C_{\mathrm{t}}\) is calculated to be 40 pF. Also, the value of \(R_{\mathrm{ref}}\) is calculated to be 44 \(\Omega\) using Equation (4).  
When the data signal is at a low level, the \(L_{\mathrm{a}}\) is added to the load network. By substituting \(R_{\mathrm{eq}}\), 10% for MI, and 2\(\pi\)\(\times\) 16 \(\times\) 10\({}^{6}\) for \(\omega_{0}\) in (21), \(L_{\mathrm{a}}\) is calculated to be 0.2 uH. According to Equation (19), the value of \(\varphi\) is approximately 55\({}^{\circ}\), which satisfies the constraint requirement of \(\varphi\).
# Control of _Francisella tulareis_ Virulence at Gene Level: Network of Transcription Factors
## 3 Regulators Participating in the Oxidative and Nitrosative Stress Responses  
### OxyR Regulates Genes Involved in the Oxidative Stress Response  
The OxyR (hydrogen peroxide-inducible genes activator) transcription factor is a member of the LysR transcriptional regulator family. Similar to other regulatory DNA-binding proteins, members of this family possess the helix-turn-helix (HTH) domain. OxyR is a well-known regulatory protein in _E. coli_, where its activity counteracts the actions of reactive oxygen species and regulates the expression of many genes in response to a variety of stress stimuli [78]. OxyR is important for _F. tulareis_ subsp. _holarctica_ LVS strain during the oxidative stress response. It was found that the loss of OxyR leads to a lower ability to grow inside macrophages and attenuated virulence in mice [49]. OxyR regulates the expression of the _alpC_, _katG_, and superoxide dismutase _(sodB)_ genes, which act as antioxidant enzymes in Francisella. It is able to bind directly to the promoter of _alpC_ and _katG_[49; 50]. Mainly, KatG and OxyR work together and constitute an important system for defense against oxidative stress [79].
# An Audio Watermarking Algorithm Based on Adversarial Perturbation +
## 3 The Proposed Methodology
### Watermark Embedding and Attack Simulation Layer  
#### 3.4.1 Theoretical Description  
In the framework of the AAW algorithm of Figure 2 (the attack simulation layer is ignored here for the moment), the output of the whitening layer \(\mathbf{o}_{wl}\) can be expressed as  
\[\mathbf{o}_{wl}=f_{wl}(f_{ptm}(\mathbf{x}(n)+\delta(n))) \tag{7}\]  
where \(\mathbf{x}(n)\) is the given host audio and both \(f_{ptm}\) and \(f_{wl}\) are parameter-fixed in the watermarking system. It can be concluded that \(\mathbf{o}_{wl}\) is a function of \(\delta\). Thus, Equation (7) can be rewritten as  
\[\mathbf{o}_{wl}=f_{\Theta}(\mathbf{x}+\delta(n)) \tag{8}\]  
where \(\Theta\) denotes all other parameters, including those of all modules. The index identifier (\(n\)) of the audio sequence is omitted here. It is noted that \(f_{ptm}\) and \(f_{wl}\) are all differentiable functions, so \(\mathbf{o}_{wl}\) is differentiable with respect to \(\delta\).  
The loss function \(\mathcal{L}(\mathbf{o}_{wl},\mathbf{w})\), which evaluates the distance between the output of the whitening layer and the watermark, is also a differentiable function. Thus, there are  
\[\frac{\partial\mathcal{L}}{\partial\delta}=\frac{\partial\mathcal{L}}{\partial \mathbf{o}_{wl}}\frac{\partial\mathbf{o}_{wl}}{\partial\delta} \tag{9}\]  
Equation (9) shows that tiny perturbations \(\delta(n)\) can be optimized by backpropagation to reduce loss \(\mathcal{L}\).
# Combining Dilution of Precision and Kalman Filtering for UWB Positioning in a Narrow Space
###### Abstract  
Affected by the spatial environment, the accuracy and stability of ultra-wideband (UWB) positioning in a narrow space are significantly lower than those in the general indoor environment, which limits navigation and positioning services in a complex scene. To improve the positioning accuracy and stability of a narrow space, this study proposed a positioning algorithm by combining Kalman filter (KF) and dilution of precision (DOP). Firstly, we calculated the DOP values of the target narrow space by changing the location of the test nodes throughout the space. Secondly, the initial coordinate values of the test nodes were calculated by the weighted least squares (WLS) positioning algorithm and were used as the observation values of KF. Finally, the DOP values were adaptively introduced into KF to update the coordinates of the nodes to be tested. The proposed algorithm was tested in two narrow scenes with different length-width ratios. The experimental results showed that the DOP values of the narrow space were much higher than that of the wide space. Furthermore, even if the ranging error was low, the positioning error was high in the narrow space. The proposed fusion positioning algorithm reported a higher positioning accuracy in the narrow space, and the higher DOP values of the scene, the greater the accuracy improvement of the algorithm. This study reveals that no matter how the base stations are configured, the DOP values of the narrow space are much higher than that of the wide space, thus causing larger positioning errors. The proposed positioning algorithm can effectively suppress the positioning error caused by the narrow spatial structure, so as to improve the positioning accuracy and stability.  
U  
; narrow space; Kalman filter; dilution of precision; fusion positioning algorithm 2022
###### Abstract  
The advent of Additive Manufacturing (AM) is uncovering the limits of the current CAD systems and, at the same time, is highlighting the potentials of the Topology Optimization (TO) and Generative Design (GD) tools that had not been fully exploited until now. Differently from the traditional design approach in which designers occupy a predominant role in each stage of the design process, the introduction of such tools in the product development process pushes toward simulation-driven design approaches which imply a significant change in the role of the designer. To this end, the paper presents a comparison of two different design methods for Additive Manufacturing based on the adoption of TO and GD tools. The comparison aims to offer a reflection on the evolution of the traditional approach when TO and GD tools are used, and to highlight the potential and limitations of these optimization tools when adopted in an integrated manner with the CAD systems. Furthermore, this comparative study can be a useful and practical source for designers to identify the most appropriate approach to adopt based on their needs and project resources. The comparative study is carried out through the design study of a prototype of a rocker arm and a brake pedal for the Formula Student race car. Their results, compared in terms of mechanical performances, show that both TO and especially GD tools can be efficiently adopted early in a design process oriented to AM to redesign components to make them lighter and stronger.  
A 2022 20  
product optimized for a specific application without regard for the restrictions of assembly, part standardization, or traditionally restricted geometries [3].  
Although it is a relatively recent technology, created in the 80s and emerged in the 90s, AM was reserved only for prototype fabrication in the beginning, instead now it is used to manufacture operable parts in many industrial fields such as aerospace, automotive, medical, and consumer products [4; 5; 6; 7; 8; 9]. It is therefore evident how necessary and urgent expanding the capabilities and functionalities of current CAD systems is by facilitating and encouraging an even easier and more efficient integration with TO and GD tools. Furthermore, AM technologies are giving greater importance to and promoting these tools to support the concept and modeling design stages too rather than for validation and optimization only.  
On the basis of these considerations, the paper presents a comparison of two different design methods for Additive Manufacturing based on the adoption of Generative Design and Topology Optimization tools. The comparison is carried out through the design study of a prototype of a rocker arm and a brake pedal for the Formula Student race car that allows to highlight the potentials and limits of these optimization tools when adopted in an integrated manner with the CAD system. The paper also provides a practical and useful input for reflection on the use of TO and GD tools to support designers' work and how they influence the design process.
# A Quantum Approach for Exploring the Numerical Results of the Heat Equation
## 3 Results
From the data provided, it is clear that the simulators have different performance and relative errors depending on the number of qubits. For the simulator ibmq_qasm_simulator, which is generic and context-aware, the relative error decreases as the number of qubits increases. For example, when using 3 qubits, the error is about 12.5%, and when using 7 qubits, the error is already reduced to approximately 0.29%. The simulator simulator_statevector, which simulates the Schrodinger wave function, also shows a decrease in the relative error with an increasing number of qubits. For example, when using 3 qubits, the error is about 12.5%; when using 15 qubits, the error drops to about 0.015%. In the case of a real quantum computer from IBM, the designated ibm_osaka with the \"Eagle r3\" architecture, the relative error also depends on the number of qubits. For example, when using 5 qubits, the relative error is about 16.58%; when using 10 qubits, the error drops to about 0.47%. These results show that when simulating or using quantum devices, both simulators and real quantum computers, it is important to consider the number of qubits and their characteristics, as this significantly affects the accuracy of the results. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Device** & **Characteristic** & **Number of Qubits** & **Relative Error** \\ \hline ibmq\_qasm\_simulator & General, context-aware & 32 & 0.0029296875 \\ simulator\_statevector & Schrödinger wavefunction & 32 & 0.0023456456 \\ ibm\_osaka & Eagle r3 & 127 & 0.0254375 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Relative error results on various quantum devices. Figure 6: Graph of error versus number of qubits. The algorithm offers several advantages, including high accuracy compared to classical numerical simulation methods, efficiency for large systems with many parameters, and versatility for solving other problems involving partial differential equations. However, it also faces limitations such as implementation complexity due to the complex nature of quantum computing, system size limitations imposed by the limited number of qubits in quantum devices, and susceptibility to noise, which can affect the accuracy of the results.
# Detection of Bovine Mastitis in Raw Milk, Using a Low-Cost NIR Spectrometer and k-NN Algorithm
## 2 Materials and Methods
### Autoscaling of the Data  
Once the data has been captured and enhanced, the result is a dataset in which different features can be on different scales. It is at this point when the centering and normalization of the data became a key step in the whole process. Although the normalization of the data is not a requirement in machine learning, when k-NN is used, this strategy becomes very important. As was aforementioned, the inputs can be on different scales, resulting in a higher weight of the inputs with higher absolute values when the Euclidean distance is computed. To solve this undesired situation, all inputs can be set on the same scale, usually between 1 and \(-1\), resulting in an improvement in the performance of the k-NN algorithm.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**CMT** & **Interpretation** & **Class** & **Number of Samples** \\ \hline
0 & Negative & Negative & 130 \\ + & Trace & Weak Positive & 57 \\ +++ & Distinctive positive & Strong Positive & 23 \\ ++++ & Strong positive & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Interpretation of results of CMT and grouping for classification algorithm.  
To perform this process, each of the inputs is independently processed using the following equation, where xi(n) is the ith input of the nth data point:  
\[\text{xi(n)}^{\prime}=\text{xi(n)}-\text{mean(xi)std(xi)} \tag{1}\]
## 1 Introduction
Then, a theoretical verification is demonstrated analytically with closed expressions of the transition trend of the probability mean of the soft decoding metrics by the Gaussian approximation. In addition, an efficient numerical technique of approximate stochastic gradient descent is employed to solve the above optimization problem of excellent timing recovery with rational computations. Finally, a traditional M&M timing recovery algorithm [16] is adopted to rectify residual timing errors by using the LDPC code words as the anticipated data needed in timing track loops. Thus, it also saves some more bandwidth resources brought by trained data in traditional timing recovery schemes, which endows it more pragmatic in spectrum efficient satellite communications. The remainder of the paper is organized as follows. In Section 2, the concept of the timing error model is introduced. Section 3 gives the principle of the suggested iterative timing recovery with soft LDPC decoding metrics. In this section, Gaussian approximation method is employed to explain the evolution trend of the soft metrics, which are influenced by the timing errors. The proposed iterative timing recovery scheme, accompanied by the traditional M&M timing track algorithm, is stated in Section 4 for the final timing synchronization scheme. In Section 5, the numerical simulations are given to manifest the good performance of the proposed scheme. In this section, we also analyze the possible reasons for the good performance of our proposed scheme and evaluate the computation complexity. Finally, the conclusion is drawn in Section 6.
# Domain Adaptation for Satellite-Borne Multispectral Cloud Detection
## 9 Discussion
### Preprocessing  
The impact of data preprocessing on the domain gap and domain adaptation has not been explored. Relevant to our study, in aspects of preprocessing, are multiple projects \"harmonising\" Landsat and Sentinel-2 EO data into a single analysis-ready \"virtual constellation\" dataset [76; 77]. Harmonisation involves applying a range of geometric, atmospheric, spectral and directional effect correction operations to data products from multiple sources to create a time-series dataset suitable for continuous Earth surface monitoring [76; 77]. These harmonisation operations can potentially be used to provide training data for onboard cloud detectors, with the benefit of reducing the domain gap better than the preprocessing steps described in Section 4, but this hypothesis has yet to be systematically explored.
# A Rectangular Toroidal Current-Based Approach for Lung Biopsy Needle Tracking
###### Abstract  
Biopsy remains the gold standard for diagnosing lung cancer, with high-quality tissue samples being critical for accurate results. To improve puncture accuracy, reduce reliance on CT imaging, and minimize procedural complications, it is essential to address the challenges of tracking the biopsy needle's trajectory and providing real-time positional guidance to physicians. In this study, we propose a tracking model based on a rectangular toroidal current distribution to determine the biopsy needle's relative position within the electromagnetic tracking system. A printed circuit board (PCB) is used as the platform for generating the rectangular circulating magnetic field. An alternating electromagnetic field (~70 kHz) is modeled based on the Biot-Savart law. Induced voltages from multiple transmitting coils are processed using Fourier transform algorithms to separate frequencies, enabling the independent extraction of each coil's signal. A least squares method is employed to solve the five-degree-of-freedom electromagnetic positioning equations for the receiving coils. The objective is to establish a precise and computationally efficient electromagnetic localization model for the biopsy needle. An experimental setup simulating lung biopsy procedures is implemented, utilizing the proposed rectangular toroidal current configuration. Results demonstrate an average localization error of less than 1.76 mm, validating the effectiveness of the system in addressing the challenges of real-time biopsy needle tracking.  
Keywords:electromagnetic tracking; biopsy needle tracking; rectangular circulation model 5-D algorithm +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Effect of KKD-ZnO-NPs on Gene Expression of Apoptosis Regulator  
The production of ROS by cells is essential for redox signaling, while _p53_ (tumor suppressor protein) is a redox active transcription factor. ROS can activate _p53_ and mediates apoptosis on cancer cells [60; 61]. _p53_ regulates the expression of several microRNA species, including miR-34, which is known to target the pro-survival _bcl2_ gene. _bcl2_ regulated pathway is one of the apoptosis pathways that is activated by stress conditions such as cytokine deprivation or DNA damage [62].  
The RT-PCR (Figure 9) showed upregulation of _p53_ and downregulation of _bcl2_ gene expression in a dose-dependent manner by KKD-ZnO-NPs compared to Kakadu plum extract only. This phenomenon may be due to the activation of mitochondrial-mediated apoptosis, which is characterized by the downregulation of _bcl2_, followed by an increase in Bax, allowing cytochrome C release into the cytosol, and finally, the caspase 9/3 signaling cascade [63; 64]. However, quantitative analysis and further investigation of the molecular mechanisms are needed to clarify the cellular pathways.  
Figure 8: In A549 cells, the ability of KKD-Ext, and KKD-ZnO-NPs to generate intercellular reactive oxygen species (ROS) was compared to a positive control (cisplatin). Graph shows mean \(\pm\) SD values of three replicates. **_p_\(<\) 0.05; ***_p_\(<\) 0.001 indicates significant differences from control groups.
# Camera-Based Continuous Heart and Respiration Rate Monitoring in the ICU
## 2 Materials and Methods
### Respiration Rate Extraction
#### 2.5.5 Detection of Breathing Motion Errors
To detect the presence of non-breathing motion using the residual error regardless of the contribution of measurement error, we used a sliding window with a 6-s duration and 1-frame stride to measure residual error standard deviation. If a segment's standard deviation surpassed a threshold, it was marked as having non-breathing motion. In addition, we also discarded a segment if no motion was detected in it at all. To do this, any segment where the standard deviation of the measured breathing motion was below a threshold of 0.02 was also discarded. To show how well this approach can work, we plotted the 3 RPM agreement, MAE, and coverage of the respiration rate over a range of thresholds. Since both NIR- and RGB-based respiration rate extraction use grayscale images, the same methodology can be applied to both; however, since the hardware and settings differ between the cameras, they must be evaluated separately.
# Experimental Analysis of Transformer Core Vibration and Noise under Inter-Harmonic Excitation
## 3 Results and Discussion
### Inter-Harmonic Content Influence on Core Vibration  
In the excitation, the inter-harmonics with the same frequency and different content are added respectively. The comparison results of the peak-to-peak displacement of the transformer core under the same voltage amplitude are shown in Tables 4 and 5.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Inter-Harmonic Frequency in Excitation (Hz)** & **Inter-Harmonic Frequency in Vibration (Hz)** \\ \hline
2 & 48, 52, 96, 104, 148, 152, 196, 204 \(\ldots\) \\ \hline
7 & 43, 57, 86, 114, 143, 157, 186, 214 \(\ldots\) \\ \hline
10 & 40, 60, 80, 120, 140, 160, 180, 220 \(\ldots\) \\ \hline
15 & 35, 65, 70, 130, 135, 165, 170, 230 \(\ldots\) \\ \hline
20 & 30, 70, 60, 140, 130, 170, 160, 240 \(\ldots\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Inter-harmonic frequency in vibration.  
Figure 9: Vibration displacement of iron core with 5 Hz inter-harmonics in excitation; **(a)** time-domain waveform; **(b)** spectrum analysis.  
It can be seen that the vibration of measuring point 1 and measuring point 3 is more severe than measuring point 2, but from the general trend of the three measuring points, the same conclusion is obtained: when the inter-harmonic content increases, the vibration displacement gradually increases, especially when the frequency is less than 20 Hz inter-harmonic excitation, and the increasing speed will be more obvious when the voltage amplitude is large. For example, when the voltage amplitude is 41.18 V, when the excitation contains 5 Hz inter-harmonics, the peak-to-peak vibration displacement of 5% of the harmonic content is 1.8 times that of the content of 1%. In contrast, the 20 Hz inter-harmonics reaches 1.34 times. The 40 Hz inter-harmonic is only 1.17 times. When the voltage amplitude is 44.12 V, the above-mentioned ratio reaches 2.17 times, 1.49 times, and 1.35 times.