esa-sceva/satcom-chunk-collection huggingface dataset:
# A Peak Absorption Filtering Method for Radiated EMI from a High-Speed PWM Fan
## 5 Conclusions  
EMC standards require stricter radiated emission limits for a PWM axial fan and its drive system. Meanwhile, due to the limited internal space of the small fan, there are also certain size requirements for the interference suppression measures. Therefore, this paper aimed to identify the main sources of radiated interference in PWM-regulated fans through measurements and simulations of radiated emissions. Additionally, a radiated interference suppression method that can be integrated into a PCB was proposed.  
The propagation paths of the interference were determined through the study of the fan speed control mechanism. By modeling the radiated interference of individual components in the fan, the primary sources of radiated interference were identified. Subsequently, a small-sized peak-absorbing circuit was designed to address the issue. Experimental verification was conducted to assess the effectiveness of the radiated interference suppression measures. The experimental results demonstrate that the integrated non-inductive RC filter effectively suppressed peak radiated interference from the fan without impacting the fan's speed. The insertion loss achieved by the designed filter for radiated interference reached 41.9 dB.  
Conceptualization, J.Y., Formal analysis, Y.W.; Investigation, C.W.; Methodology, J.Y. and X.Z.; Resources, X.Z.; Supervision, P.D., Validation, J.Y. and Y.W., Writing--original draft, J.Y., Writing--review & editing, P.D. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China under Grant 52175218.  
Not applicable.  
The data supporting the findings of this study are available from the corresponding author upon reasonable request.  
The authors declare no conflict of interest.
## 6 Conclusions  
We analyze the problem from the overall performance of the system. The model presented in this paper has been developed for a microcell environment which has a quasi-static channel. A cluster based WSN architecture has been assumed at the transmission side. The cluster head is assumed to be surrounded by local scatterers giving rise to multipath and fading. At the receiver, receiving arrays are used to collect all the multipath components of the signal effectively. The advantage of using smart antennas in a cluster based WSN model has been demonstrated where performance improvements can be realized in terms of received SNR. The numerical simulations based on the variations in receiver height reveal that the performance of the system increases if the receiver height is increased above ground level. Also the numerical simulations based on maximum multipath delay shows that the semi-major and semi-minor axis of the ellipse changes with variations in the maximum multipath delay, hence affecting the performance of the overall system. The performance of the system is also improved as the transmission power increases. Since the cluster head is located very near to the sensor nodes, the sensor nodes do not require high transmission powers so they do not face the reachback problem. The paper justifies the use of receive diversity at the receiver for reliable communication between the cluster head and the receiving arrays and proves that MRC provides the best performance when applying receive diversity. We also quantify the fact that with the increase in the number of antenna elements, we are able to increase the reliability and robustness of the system. The number of  
\begin{table}
\begin{tabular}{|c|c|c|c|c|c|c|} \hline \(N_{r}\) & \(P_{T}\) & \(\tau\) (\(\mu\)s) & \(H_{R}\) (\(m\)) & \multicolumn{3}{c|}{SNR/BER} \\ \cline{4-7}  & (W) & (\(\mu\)s) & (\(m\)) & **0** & **3** & **6** \\ \hline  & & & 2 & 0.000834 & 0.000218 & 2.07e–05 \\ \cline{3-7}  & 10 & 8 & 5 & 0.000702 & 0.000143 & 9.7e–06 \\ \cline{3-7}  & & & 10 & 0.000607 & 0.000103 & 6.3e–06 \\ \cline{  
antenna elements has been kept low while solving our problem. However, they can be extended to higher number of receive antennas for a large receiving array.
## 2 Methods
### Path-Planning Improvement
#### 2.2.1 Fan-Shaped Goal Orientation
This aids in enhancing the effectiveness of path-planning algorithms and the quality of path planning in intricate settings.
## 2 Methods
### CFD Method
#### 2.1.3. Rotor Performance  
The most notable performance metrics of a compressor are the mass flow \(\dot{m}\), pressure ratio \(\pi\), efficiency \(\eta\), and stability margin \(SM\) extracted from the operating characteristic curve. The back pressure \(p_{out}\) was changed according to a geometric progression distribution, decreasing the pressure interval near the stall pressure. A typical operating characteristic curve generated by CFD is shown in Figure 7. The peak efficiency point was selected as the working point, and then the mass flow \(\dot{m}_{W}\), pressure ratio \(\pi_{W}\), and efficiency \(\eta_{W}\) were determined.  
Furthermore, several variables were defined to evaluate the whole operating characteristic curve generated by CFD. A range of satisfactory efficiency \([\dot{m}_{I},\dot{m}_{h}]\) was defined after setting an efficiency threshold \(\eta_{I}\), as shown in Figure 7. The criteria involved the numerical  
Figure 6: Variable distributions in the span of the experiment [33] and CFD: (**a**) pressure distribution in the span; (**b**) temperature distribution in the span.  
Figure 7: Typical operating characteristics calculated by CFD, with the definition of 7 selected performance variables.  
stall feature of the rotors, so these criteria were used to replace the exact stall point when training agents, saving computational resources.  
Then, the integral efficiency \(\hat{\eta}\) and pressure ratio \(\hat{\pi}\) were expressed as shown in Equations (1) and (2) to indicate the efficiency and pressure ratio of the whole operating characteristic curve, respectively. The rotor performance was ultimately described by 7 dimensions, denoted by \(p_{i}\in\mathbb{P}=\left\{\hat{m_{l}},\hat{m_{h}},\hat{\eta},\hat{\pi},\hat{m_{ W}},\pi_{W},\eta_{W}\right\}\), \(i=1,2,\ldots,7\).  
\[\hat{\eta}=\frac{\int\limits_{m_{l}}^{\hat{m_{h}}}\eta(\hat{m})d\hat{m}}{m_{h} -m_{l}} \tag{1}\]  
\[\hat{\pi}=\frac{\int\limits_{m_{l}}^{\hat{m_{h}}}\pi(\hat{m})d\hat{m}}{\hat{m_{ h}}-\hat{m_{l}}} \tag{2}\]
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Patient 1** & **Patient 2** \\ \hline
**Age/sex** & 44/M & 37/F \\ \hline
**Induction therapy** & CY-steroids & CY-steroids \\ \hline
**Time from diagnosis to 1 st AECT (months)** & 4 & 3 \\ \hline
**Response prior to 1 st AECT** & PR & PR \\ \hline
**Conditioning regimen of 1 st AECT** & Mel 200 & Mel 200 \\ \hline
**Infused CD34+ cells (\(\times\)106/kg)** & 5.43 & 2.99 \\ \hline
**Response after 1 st AECT** & VGPR & VGPR \\ \hline
**Time from 1 st AECT to relapse or progression (months)** & 73 & 43 \\ \hline
**Salvage therapy** & Rd plus radiotherapy & Rd \\  & and CyBorD & \\ \hline
**Age at the 2 nd AECT** & 54 & 45 \\ \hline
**Time from 1 st to 2 nd AECT (months)** & 115 & 68 \\ \hline
**Response prior to 2 nd AECT** & CR & Clinical PD \\ \hline
**Conditioning regimen** & Mel 140 & Mel 200 \\ \hline
**Infused CD34+ cells (\(\times\)106/kg)** & 1.85 & 2.89 \\ \hline
**Response after 2 nd AECT** & CR & CR \\ \hline
**Relapse or progression** & No & No \\ \hline
**Follow up from 2 nd AECT (months)** & 86 & 11 \\ \hline
**Outcome** & Alive & Alive \\ \hline \hline \end{tabular} CR, complete response; PR, partial response; VGPR, very good partial response; PD, progressive disease; CY, cyclophosphamide; Rd, lenalidomide and dexamethasone; CyBorD, cyclophosphamide, bortezomib, and dexamethasone; Mel 140, melphalan 140 mg/m\({}^{2}\); Mel 200, melphalan 200 mg/m\({}^{2}\).  
\end{table} 
Table 1: Patients characteristics. CD34 + collection, and 200 mg/m\({}^{2}\) in Patient 2. The infused cell dose was 1.85 and 2.89 \(\times\) 10\({}^{6}\) CD34 + cell/kg body weight, respectively. Both patients achieved a successful engraftment: the median time to 500 polymorphonuclear (PMN)/\(\mu\)L was 12 and 11 days, respectively and to 1000 PMN/\(\mu\)L 13 days for both patients. The median time to 25 \(\times\) 10\({}^{9}\) platelets/L was 17 and 13 days; the median time to 50 \(\times\) 10\({}^{9}\) platelets/L was 25 and 17 days. Patient 2 experienced a grade 2 febrile neutropenia, but no other adverse events including engraftment syndrome were registered. After the second AACT, both patients achieved a complete response with immune-fixation negativity, an improvement in POEMS syndrome features, and VEGF dosages were negative in both patients. The two patients are alive, treatment- and progression-free, at 91 and 17 months, respectively from the second AACT. No secondary malignancy or myelodysplastic syndrome has occurred. The two subjects signed the informed consent and the study was conducted in accordance with the Declaration of Helsinki and the Institutional Review Board (IRB).
## 4 Antiviral Activity of the Styrylquinoline Integrase Inhibitor Class
### Modulation of the ancillary ring  
While all compounds bearing a simple phenyl or a heteroaromatic ring **(77a-77d)** have proved to be good integrase inhibitors, they were found either toxic or inactive in cell cultures assays. As their unsubstituted counterpart, the monosubstituted styrylquinolines **77e-77j** were found inactive, regardless of the nature of the substituent on the ancillary ring (Table 11). As a general rule, only compounds bearing a hydroxyl group at the _para_ position and an other oxygenated function at C-3' possessed a promising activity. This result confirmed that structural requirement for _ex vivo_ activity are much more stringent that for _in vitro_ integrase inhibition. The higher the number of hydroxyl groups on the ancillary ring, the better the antiviral activity. However, the presence of three hydroxyl groups **(77t)** induced some cytotoxicity. In this respect, styrylquinoline **77u** constituted the best compromise.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline _Compd._ & \multicolumn{2}{c}{_Antiviral Activity on CEM cells IC\({}_{30}\)_} & \multicolumn{2}{c}{_Cytotoxicity IC\({}_{50}\) (\(\mu\)M)_} & _Reference_ \\  & \multicolumn{2}{c}{(\(\mu\)M)_} & \\ \hline
**3b** & \(>\)100.00 & \(>\)100.00 & 14 \\
**7** & \(>\)100.00 & 500.00 & 19 \\
**14** & 5.00\({}^{\rm a}\) & 1.25 & 22 \\
**22** & 3.60 & 8.10 & 14 \\
**26** & 12.00 & \(>\)100.00 & 25 \\
**27** & 50.00 & \(>\)100.00 & 25 \\
**28** & 20.00 & \(>\)100.00 & 25 \\
**29** & 20.00 & 20–30.00 & 25 \\
**30** & 15.00 & \(>\)100.00 & 25 \\
**32** & 4.00 & 200.00 & 19 \\
**34** & NR & 6.20 & 14 \\
**35** & 1.30 & 120.00 & 14 \\
**42** & 10.00 & 30.00 & 30 \\
**43** & \(>\)100.00 & \(>\)100.00 & 30 \\
**46** & \(>\)100.00 & \(>\)100.00 & 30 \\
**47** & 10.00 & 50.00 & 32 \\
**53** & 95.00 & \(>\)100.00 & 14 \\
**54** & NR & 9.20 & 26 \\
**59d** & NR & 12.50 & 35 \\
**59m** & 40.00 & 80.00 & 33 \\
**59n** & 63.00 & \(>\)100.00 & 33 \\
**59o** & 35.00 & \(>\)100.00 & 33 \\
**60** & NR & 17.00 & 14 \\
**61** & 0.80 & 10.00 & 19 \\
**62** & 40.00 & 150.00 & 19 \\
**63** & 1.60 & 60.00 & 34 \\
**64** & 35.00 & \(>\)100.00 & 34 \\ \hline \hline \end{tabular} \({}^{\rm a}\) MT-4 T-lymphoid cells, NR: not reached.  
\end{table}
Table 10: Antiviral activity and cytotoxicity of the (3’,4’-dihydroxyphenyl)styrylquinoline derivatives.
## 2 Optical Frequency Comb Self-Referencing
### Coherent Supercontinuum Spectrum Generation
It was shown that a coherent SC spectrum requires a soliton order \(N_{\rm sol}<10\) at the input of the nonlinear fiber [19, 41]. An incoherent regime is achieved when \(N_{\rm sol}>10\) as a result of modulation instabilities that amplify small noise at the fiber input to cause large deviation of the intensity, timing, and phase of the output SC spectrum. Therefore, SC generation for frequency comb self-referencing always requires a soliton order \(N_{\rm sol}<10\). Besides the use of HNLFs and PCFs, an integrated silicon-nitride (Si\({}_{3}\)N\({}_{4}\)) waveguide embedded in SiO\({}_{2}\) recently proved to constitute a powerful nonlinear medium for coherent SC generation for frequency combs [42]. Using Yb femtosecond DPSSLs in the 1 \(\upmu\)m spectral range with 100 MHz and 1 GHz repetition rates, [PERSON] _et al._, obtained a coherent SC spectrum enabling CEO detection by _f_-to-2\(f\) interferometry with \(>\)25 dB SNR for the 100 MHz laser (and \(>\)30 dB for the 1 GHz laser). These results were achieved with a peak power lowered by more than a factor 10 compared to the use of a commercial PCF and in a length shorter than 10 mm (compared to typically 1 m for the PCF), as a result of the high nonlinear refractive index of Si\({}_{3}\)N\({}_{4}\) that is 10 times larger than for silica.
## Literature Review
### Reputation and Rating Schemes  
The sixth trend is about research proposing ways to evaluate application trust in some aspects. [PERSON] et al. [47] put in place a private cloud to control user installations of Android applications and to keep track of feedbacks from users. They evaluate qualitative reputation of applications based on feedbacks, vendor's reputation and number of users who run the same application. This work holds for a private cloud, so customers are already known and their interests too. Their proposal does not propose formal scheme. It is subjective and somehow more related to permissions than feedbacks and is just informative. Our work deals with crowd users in Google Play whose interests are understood through reviews. Our proposal is formal based on sentiment analysis of comments provided by users in Google Play. In [48], authors provided a mechanism to rate apps based on static analysis of flows related to required permissions and sentiment analysis of reviews. Sentiments related to confidentiality are evaluated from reviews and internal abilities of the application to make possible data disclosure. It is unclear how they proceed with keywords and polarities. As result, they obtain a rate of app meaning trust that the app does not disclose critical data. Unlike our scheme which considers four security aspects confidentiality, integrity, authentication and availability, their keywords only relate confidentiality. In our work, we are able to determine global security-related reputation and reputation for each of CIAA services. SERS appears to be similar to ours since it computes a value indicating the nature of apps. A global rating scheme is provided in popular app stores (such as Google Play and iOS store) to make customers evaluating based on their experience with an app. This per-user evaluation is expressed as number on a scale between one and five in the corresponding app and the system aggregates as the cumulative average of all individual user ratings over all the versions. The global rating value refers to satisfaction one could have after using an app or to a kind of reputation that users associate to an application. As reported in [24], different users with the same experience may provide different star ratings. Google rating is subject to inconsistencies across user perceptions. In our proposal, we take into account the current reviews to remove old reviews which may have been considered in previous versions. Moreover, our reputation relies on reviews.
## 5 Debris Management and Related Hazards in the Earthquake-Affected Provines in Turkey
### Debris Management and Related Hazards in the Earthquake-Affected Provinces in Turkey
#### 5.2.4 Golbasq Disposal Site
In terms of proximity to a residential area, this site is less than 200 m from the aforementioned recreational facilities and less than 1 km from the first residential buildings in the northeastern part of the town. Furthermore, the eastern boundary of the site is the D.850 state road that passes through the area (Figure 11). This road was very busy, especially during the emergency response after the earthquakes and then during the recovery phase. From the above, it is concluded that the site is in a location that can adversely affect both public health and the natural environment. Public health may be directly affected by the dust clouds formed by the constant movement of heavy machinery in the site and along the local road network with effects comprising respiratory diseases among others as well as other long-term effects such as lung cancer attributed to the released asbestos fibers  
Figure 11: Characteristic drone views of the Gölbasi disposal site on 2 April 2023. (**a**) View from north to south. The Gölbasi town is located south of the site. The site has been set up next to the D.850 state road and at a former swamp area (**b**), very close to the lake. Furthermore, a stream flows at a small distance from the site into the lake (white dotted line) (**c**,**d**). during the debris treatment. The natural environment and in particular the surrounding streams and the lake can suffer water contamination with heavy metals and oils through surface drainage, which will degrade the surface water quality with adverse effects on the riverine and lake area. These hazardous materials may also adversely and significantly impact the groundwater of the surrounding area. As an area in which a large lake has been formed and in which extensive liquefaction and lateral spreading phenomena have occurred, it could be concluded that the groundwater level is high and can be quickly affected by the hazardous materials, which can dissolve into the groundwater, resulting in degradation of the groundwater quality and subsequent impact on public health as this lake is an important source of both water supply and irrigation for the area. These impacts may be expanded to the flora and the fauna that not only live in the lake and its shore but also use the lake for migration, temporary residence, and breeding. They may include the disruption of ecological processes, the introduction of new non-native and invasive species to the area, and even the destruction of the natural ecosystem.
# Utilization of Phosphogypsum and Sediment in Subgrade Material for Pavement Construction
## 3 Results
### Physical-Mechanical Characterization
#### 3.2.4 California Bearing Ratio (CBR)  
The California Bearing Ratio (CBR) measures the resistance of a piston as it is pressed into a soil sample. In this study, three samples were tested: one made of pure sediment (0% phosphogypsum), one with 3% phosphogypsum added, and one with 5% phosphogypsum added. When preparing samples for CBR, the following optimal material humidity was used (Table 8).  
The test results for these prepared samples are displayed in Figure 10. As shown in Figure 10, increasing the amount of binder correlates with a rise in the California Bearing Index values. The mixtures of phosphogypsum and sediment demonstrated promising results, with a CBR value of 12.5% for the 3% phosphogypsum mixture and 22.9% for the  
Figure 10: California bearing ratio.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Samples** & **Sediment (0\%)** & **3\%** & **5\%** \\ \hline Optimum humidity & 12.7 & 13.1 & 13.9 \\ \hline Maximum volumetric mass & 1.60 & 1.65 & 1.67 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Maximum volumetric mass and optimum humidity.  
Figure 9: (**a**) Compressive strength—uniaxial strength after 7 and (**b**) compressive strength—uniaxial strength after 28 days (right image).  
5% phosphogypsum mixture. In contrast, clean sediment alone exhibited a CBR value of 5.1%. According to the technical specifications set forth by the Roads of Serbia, the minimum CBR value required for the construction of road embankments is 5%. Based on this criterion, all three mixtures can be utilized in road embankment construction. Moreover, while some local studies report lower CBR values (typically ranging from 4% to 8%) for phosphogypsum-stabilized soils with higher binder contents (10-30%), the values obtained in this study suggest that even at relatively low binder contents (3% and 5%), phosphogypsum can significantly enhance the material's performance, making it a promising option for soil stabilization in road construction [55].  
This increase in CBR values is directly correlated with the effectiveness of phosphogypsum as a binder in stabilizing the sediment. Phosphogypsum works by facilitating the formation of ettringe crystals, which bind the particles together, filling voids, and improving the overall compaction and load-bearing capacity of the material.  
The increased UCS values observed with higher phosphogypsum content (from 0.30 N/mm\({}^{2}\) at 3% binder to 0.36 N/mm\({}^{2}\) at 5% binder after 7 days) suggest that the material becomes progressively more compact and stronger, a trend consistent with the CBR findings. The improvements in UCS and CBR values indicate that the material becomes more resistant to deformation under load, which is critical for its use in road embankments.
## 2 Methodology
### Model Development
#### 2.4.1 Model Architecture  
CNN models primarily consist of a feature extraction section, comprising of convolution and subsampling or pooling blocks, followed by a classifier section of dense layers. Here, twelve CNN architectures have been considered and a standardized naming convention to describe these architectures has been used as shown in Table 2. For example, C2f3k3_API_D48_L1_R50_D12 refers to a deep neural network consisting of two convolutional layers each with three filters of kernel size three, one subsampling or pooling layer between the convolutional layers, followed by flattened dense layer, a hidden layer with 48 neurons and the output layer with 12 neurons corresponding to each molecule. The prefix L and R refers to L2 and dropout regularized models. Models are also identified by roman numerals in Figures 4 and 5. The loss and accuracy on training and validation data for the twelve CNN architectures considered are shown in Figures 4 and 5. The simplest model consisting of one convolutional layer with a single filter and kernel size of three, followed by pooling, flattening, and a 12 neuron dense layer minimizes the sparse categorical crossentropy loss and achieves accuracy above 90%. The convolution and the pooling layer extracts relevant features from the input spectrum consisting of 229 absorbance values corresponding to the 0.016 cm\({}^{-1}\) resolution. All other model architectures are constructed incrementally and regularization is added for certain models. In constructing models, simplicity was preferred and a balance of network width and depth was maintained. The penultimate layer in each model outputs raw scores that are then converted to a probability distribution using a softmax layer. Figure 4: Loss on training and validation data for the considered CNN model architectures. In Table 2, a brief description of the performance of the considered CNN models is noted in the remarks column, while max pooling improves performance, it increases the emphasis of model decision making on very strong transitions within each spectrum and, thus, weak but important transitions for defining spectral fingerprints may be ignored. Hence, we kept average pooling to preserve as much information from the raw spectrum for feature extraction. Adding additional filters, convolutional blocks, pooling layers generally improves accuracy, but is likely to result in a model that overfits the data. We also found that dropout regularization of model weights work best for this classification task compared to L2 regularized weights and combined L2 with dropout regularization. Having a second convolutional layer and/or increasing the number of filters from one to three improves the performance on the training and the validation set. After consideration of these observations regarding performance of the various CNN model architectures, the C2f3k3_API_D48_RD50_D12 model was selected, given its training and validation (generalization) losses are closely matched and this model does not overfit the simulated dataset, as shown in Figures 4 and 5.