esa-sceva/satcom-chunk-collection huggingface dataset:
## Material and Methods
### Forms of Aluminium  
The forms of aluminium extracted and the method can be found in Table 1. Several fractions of aluminium were extracted from the soil solid fraction using different reagents. Aluminium was extracted with acid ammonium oxalate (Al\({}_{0}\)) as an estimate of total non-crystalline Al [28]; sodium pyrophosphate [29] estimates the organically bound Al (Al\({}_{\text{p}}\)), while 0.5 M CuCl\({}_{2}\) estimates the organo-aluminium complexes of low and medium stability (Al\({}_{\text{Cu}}\)). Moreover, the difference between Al\({}_{\text{p}}\) and Al\({}_{\text{Cu}}\) was used as an estimate of the Al forming high-stability complexes with organic matter [30], while the difference between Al\({}_{0}\) and Al\({}_{\text{p}}\) was used as an estimation of the inorganic, non-crystalline Al [31]. Exchangeable aluminium was extracted by NH\({}_{4}\)Cl [32] and CaCl\({}_{2}\)[33].  
For the extractions of Al, the following procedures were used:  
1. Extraction with acid ammonium oxalate (Al\({}_{0}\)): The Al extracted with acid ammonium oxalate (Al\({}_{0}\)) (ratio soil: extractant 1:100, with 4 h shaking in the dark).
2. Extraction with sodium pyrophosphate (Al\({}_{\text{p}}\)): Extraction with 0.1 M Na-pyrophosphate (pH 10) with soil:solution ratio 1:100; shaking for 16 h. Suspension was centrifuged (15 min at 2500 rpm, with three drops of \"superfloc\") [29] and the supernatant filtered as previously described.
3. Extraction with CuCl\({}_{2}\) (Al\({}_{\text{Cu}}\)): 5 g of soil was shaken for 5 min with 50 mL of 0.5 M CuCl\({}_{2}\) (pH 2.8); then the suspension was allowed to equilibrate for 12 h and was shaken again for 30 min, filtered through acid-washed paper and the soil in the filter washed with CuCl\({}_{2}\) to a volume of 100 mL [34].
4. Extraction with NH\({}_{4}\)Cl: The exchangeable Al was extracted with unbuffered NH\({}_{4}\)Cl with ratio soil:extractant 1:20, and contact time of 12 h [32].
5. Extraction with CaCl\({}_{2}\): 10 g of air-dried soil was shaken with 20 mL of 0.02M CaCl\({}_{2}\) in an end-over-end shaker for 1 h, centrifuged (9000 rpm for 5 min) and filtered ([PERSON] no. 42 filter paper). The resulting solution was analysed using by atomic absorption spectrophotometry.  
In all cases, aluminium was determined in the extracts with a Perkin Elmer Analyst 400 Atomic Absorption Spectrophotometer. Forms of aluminium extracted and the method can be seen in Table 1.
# Enhanced Design of a Soft Thin-Film Vibrotactile Actuator Based on PVC Gel
## 2 Design of PVC Gel Vibrotactile Actuator  
To fabricate a wave-shaped polyvinyl chloride (PVC) gel (PVC gel), we prepared purified PVC powder, acetyl tributyl citrate (ATBC) plasticizer, and tetrahydrofuran (THF). The purified PVC powder and the ATBC plasticizer were dissolved in the THF solution during 4 h to incorporate the ATBC plasticizer completely into the PVC. The uniformly mixed PVC/ATBC solution was poured into a Teflon dish that was carved into a wave-shaped form. After sufficiently evaporatingthe THF in the PVC/ATBC solution at room temperature for 72 h, a wave-shaped PVC gel was obtained. Figure 1 shows the fabrication process of the wave-shaped PVC gel. Using the obtained wave-shaped PVC gel, a soft vibrotactile actuator was presented as shown in Figure 2. The actuator was composed of an upper layer, a wave-shaped PVC gel layer, and a lower layer. The upper layer was composed of an actuation part, bars, and a flexible supporter. The thickness of the wave-shaped PVC gel was 400 \(\upmu\)m, and the width of the wave was 1 mm.  
The behavior of the PVC gel under voltage input is different from the conventional non-ionic EAPs. When voltage input is applied to the PVC gel, the PVC gel deforms toward an anode by moving the dipoles with PVC chains as shown in Figure 3. Detailed information about the mechanism of the PVC gel can be found in our previous work [15]. In the previous work, a wave shape of the PVC gel was considered for maximizing the elastic restoring force because the elastic restoring force is proportional to the displacement. There is considerable deformation in the ridges of the wave-shaped PVC gel, whereas there is little deformation in the valleys as we can see in Figure 3. In Figure 3, \(\mathrm{d}_{\mathrm{r}}\), and \(\mathrm{d}_{\mathrm{v}}\) are displacements of a ridge and a valley, respectively. From the Figure 3, most input energy applied to the valleys at the wave-shaped PVC gel scarcely affected to the operation of the wave-shaped PVC gel. To overcome the limitation of our previous work, we designed a new structure for concentrating most of electric energy on the actuation.  
Figure 1: Fabrication process of wave-shaped PVC gel.  
Figure 2: Structure of the previously developed PVC gel vibrotactile actuator.
# A Multipath Data-Scheduling Strategy Based on Path Correlation for Information-Centric Networking
## 5 Evaluation
### Basic Performance Evaluation  
As shown in Figure 4, we first apply our proposal to a simple multipath topology. Source node A and destination node B are connected to edge routers E1 and E2, respectively. There are two disjoint multipaths between E1 and E2, namely, E1-R1-R2-E2 and E1-R3-R4-E2. The default bandwidth, delay and loss rate of path E1-R1-R2-E2 have been marked in the figure, and the default bandwidth, delay, and packet loss rate of path E1-R3-R4-E2 will be set as required in subsequent experiments. The default chunk size is set to 2 MB, the packet size is set to 1250 bytes and each router can accommodate 200 packets. In order to fully evaluate the performance of each method, we compare four data-scheduling strategies, namely, Round-Robin Data Scheduling (denoted as RRDS), Lowest RTT First Data Scheduling (denoted as LRFDS) [26], Forward Delay-based Packet Scheduling (denoted as FDPS) [27] and our proposed Path-State-Based Data Scheduling (denoted as PSDS). RRDS indicates that the chunk to be transferred is distributed to each sub-path in polling mode; LRFDS indicates that the chunk to be transferred is preferentially distributed to the sub-path with the lowest RTT; FDPS indicates that the chunk to be transferred is preferentially distributed to the sub-path with the lowest forward delay.
## 4 Thermal Network Correction
### Thermal Network Structure Correction  
A comparative analysis of the temperature change trend at each node following the termination of the heating process reveals a discrepancy between the calculated and measured temperature curves for the window barrel. Figure 6 presents a comparison between the calculated temperature and the corresponding measured temperature. From the figure, it can be observed that the calculated temperature curve for the window and the corresponding measured temperature curve exhibit a similar trend. Both curves demonstrate a continuous rise within the first 2500 s, after which they gradually decline and reach a state of stability. In contrast, the trend of the calculated temperature curve of the window barrel and the measured temperature curve is markedly disparate. The calculated temperature declines continuously from the outset until the point of stabilization, whereas the measured temperature rises steadily from 0 to 2500 s before gradually decreasing and stabilizing.  
It is evident that the positioning of the heating zone on the lens barrel results in an elevated temperature of the lens relative to that of the window component, which encompasses the window and window barrel. Subsequent to the termination of the heating process, the lens persists in the emission of heat via convection and thermal radiation, which is subsequently absorbed by the window component. Consequently, the temperature of the window component does not immediately decline, but rather continues to increase. As the heat from the lens gradually dissipates, the temperature of the lens and the window component will tend towards equilibrium. In the absence of a source of heat, the temperature of the window component will decline until it reaches the ambient temperature.  
However, the modeling of the thermal network did not take into account the convection and radiation heat transfer between the window barrel and the lens. Consequently, the heat from lens 1 could not be transferred to the window barrel. This resulted in the calculated temperature continuing to decrease. It is therefore necessary to increase the convective and radiative heat transfer between the window barrel and nodes on lens 1, as well as the corresponding nodes on the lens barrel. The corrected thermal network structure is illustrated in Figure 7.  
Figure 5: Sketch of the experimental arrangement.  
Figure 8 depicts the calculated and measured temperature curves of the window and the window barrel subsequent to the implementation of structure correction to the thermal network. It can be observed that the calculated temperature values of both the window and the window barrel are in alignment with the measured values, thereby indicating that the structure correction has been effective.  
Figure 6: Calculated and measured temperatures before correction of thermal network structure: (**a**) window; (**b**) window barrel.  
Figure 7: Corrected thermal network of the aerial camera.
## 5 Conclusions  
In this work, the SBS induced nonlinear distortion for 10 Gbaud and 28 Gbaud SSB QAM16 transmission over an 80 km SSMF based on a KK receiver is experimentally observed and investigated for the first time. Significantly reduced BER can be induced along with the increase in CSPR due to SBS, which makes SBS an unneglectable issue for KK receiver-based systems. An SBS threshold of about 7 dBm is detected for such an 80 km SSMF link. Different nonlinear distortion performances are found for LSB and RSB signals, and LSB performs better than RSB. Here, a \(\sim\)2 dB power tolerance improvement is achieved by LSB with optical filtering to remove the SBS. The proof-of-concept results in this work unfold an important issue of SBS-induced nonlinear distortion, which would be of great significance for KK receiver-based optical transmission applications.  
Conceptualization, J.D. and Y.Z.; methodology, J.D. and Y.Z.; experiment investigation, Y.Z. and W.S.; writing--original draft preparation, Y.Z.; writing--review and editing, J.D. and Z.H.; supervision, J.D. and Z.H. All authors have read and agreed to the published version of the manuscript.  
This work is supported by National Key R&D Program of China (2018 YFB1801804), National Natural Science Foundation of China (NSFC) (61935011, 61875124).  
Not applicable.  
Thanks to all the reviewers and editors for their careful work and pertinent suggestions.  
The authors declare no conflict of interest.
# Device-Free Indoor Location Estimation System Using Commodity Wireless LANs
## 2 Channel Sounding Using IEEE 802.11n Wireless LANs  
### IEEE 802.11n  
IEEE 802.11n has been standardized [19] as a MIMO-OFDM-based wireless LAN standard and is the successor to IEEE 802.11a/g. The backward compatibility of existing standards provides a mixed mode [20] to achieve MIMO transmission, extending the legacy mode. The frame format of the mixed mode is shown in Figure 1. After L-SIG (legacy signal field), which sends wireless LAN frame information such as the total length of the wireless LAN frame, it sends the HT-SIG (high-throughput signal field), which includes transmission parameters for spatial multiplexing transmission. Furthermore, after HT-STF (high-throughput short training field) and HT-LTF (high-throughput long training field), it estimates the CSI, which is necessary for spatial multiplexing transmission. In IEEE 802.11n, the number of subcarriers over the 20 MHz bandwidth is increased from 54 to 56. Furthermore, it provides a 40 MHz-mode using channel bonding as an option.  
Consequently, by four-stream spatial multiplexing with a 40 MHz bandwidth, it can achieve transmission throughput up to 600 Mbps (64 QAM, Code Rate 5/6).
# Physicochemical Properties and In Vivo Hepatoprotective Effect of Polysaccharides from Grape Pomace
## 3 Results and Discussion
### Evaluation of In Vivo Hepatoprotective Activity of GPPs
#### 3.5.4 Effects of GPPs on Morphology in Mice and Liver Index  
CCI\({}_{\rm z}\)-induced liver injury in vivo is related to the oxidative stress mechanism. In this study, the antioxidant effect was further verified using CCl\({}_{4}\)-induced acute liver injury in mice [40]. The main bioactive substances of silymarin are considered to have antioxidant activity [41; 42]. As shown in Figure 5A, compared with the normal control, the liver of the CCl\({}_{4}\) model group was enlarged, with vacuolar degeneration and fibrous hyperplasia, and the texture was rough. In the low-dose group, the texture became soft and dispersed. There was an insignificant difference among the high-dose group, positive control group and normal group. Compared with the model group, the prophylactic administration of GPPs at 100 and 200 mg/kg body weight concentrations could significantly reduce the liver index of mice (\(p<0.05\)) (Figure 5B), and the liver index of the GPP-L and GPP-H groups significantly decreased to 5.56 \(\pm\) 0.46% and 4.94 \(\pm\) 0.23%, respectively. Interestingly,  
Figure 4: **(A,B)** The secretion of inflammatory cytokines (TNF-\(\alpha\) and IL-6), **(C–H)** enzyme activity (ALT, AST, SOD, CAT and GSH) and lipid metabolite contents (MDA) in mice were measured. SOD, CAT, MDA and GSH in liver tissues were measured. Compared with the model group, * in the same column indicates significant difference (\(p<0.05\)). Compared with the normal group, # means significant difference (\(p<0.05\)). Values are presented as means \(\pm\) SDs (\(n=3\)).  
treatment with 200 mg/kg body weight alone showed no significant differences when comparing the normal control and positive control groups. The results demonstrate that a high dose (200 mg/kg body weight) of GPPs could improve the swelling and inflammatory infiltration of liver tissue induced by CCl4 and had a certain hepatotoxicity effect.
## 2 Problem Statement  
### Rational Basis for Archaeological Marks  
Past human occupation and activities have left traces and marks on the territory including landscape alterations and environmental changes that can be recognized even after centuries and millennia. These are generally subtle traces due, for example, to the presence of scattered remains, such as artifacts, bone, pottery or clusters of building materials, which can still cause alterations that indicate the presence of archaeological sites. Of course, deposit and erosion processes and/or alluvial phenomena tend to mask these marks, which can be more easily detected from a \"bird's eye view\" rather than from _in situ_ studies.  
Aerial or satellite data are able to provide a synoptic view of the area and therefore make the recognition of patterns possible, facilitating the interpretation of single features. Moreover, human presence can also produce more subtle changes, such as those linked to the occurrence of organic material or ash introduced by prehistoric occupants and still visible today in terms of alteration to the soil composition and/or moisture content.  
All these marks can be detected from space, since the alteration they produce can be revealed by satellite sensors as they can influence spectral response and radar return. Considering radar microwave systems, responses mainly depend on the superficial roughness, structure (shape and orientation), type and status of material, especially on dielectric properties. In particular, the main variations in dielectric property are principally due to soil moisture and the conductivity of target material.
## 3 Results and Discussion
### Cytotoxicity of EEP on Cancer Cells  
Cytotoxicity was expressed as the percentage grow inhibition of C6, HeLa, SiHa, and CaSki cells treated with EEP. In all the cases, EEP shows a cytotoxicity concentration-depended manner. In Table 3, we show the IC\({}_{50}\) value of EEP over four cancer cell lines. Those results show that EEP restricts glioblastoma cells (C6 cell cancer line) proliferation in vitro as efficiently as temozolomide (reference drug), whereas, for cervical cancer cell lines, it requires a higher concentration of the EEP compared to cisplatin.  
There are a few studies of beneficial properties of Mexican propolisis. [PERSON] et al. (2017) reported that three of the 39 compounds isolated from the methanolic extract of Mexican propolisis exhibited a potent cytotoxic effect in a colon, melanoma, lung, cervix, and fibrosarcoma cancer cell lines. [PERSON] et al. reported the isolation of flavonoids from methanolic extract of Mexican propolisis, and one of them revealed significant cytotoxic effect against pancreatic human cancer cell line with IC\({}_{50}\) values of 4 uM ([PERSON] et al., 2018). Other studies described the potent cytotoxic activity of galangin (**3**); ferulic acid (**10**); syringe acid (**11**); and caffe acid (**12**) against different cancer cell lines ([PERSON] et al., 2018). Interestingly, a few researchers reported that these compounds could be useful for therapeutic treatments. For example, [PERSON] et al. (2018) reported that ethanolic extract of Algerian propolisis (EEP) and galangin (**3**) decreased the number of B16F1 melanoma cells in vitro compared to control. [PERSON] et al. (2018) state that the ethanolic extract of propolisis isolated abundant polyphenic compounds such as ferulic acid (**10**) and caffe acid (**12**) revealed pro-apoptotic activity on human tongue squamous carcinoma cells (CAL-27). From this information, we emphasized that EEP and compounds possesses anti-cancer effects against cancer cell lines.
# A Lightweight Model for DDoS Attack Detection Using Machine Learning Techniques
## 3 Proposed Lightweight Model for Intrusion Detection
### BoT-IoT Dataset  
The BoT-IoT dataset was created in the Cyber Range Lab of UNSW Canberra by designing a realistic network environment. This environment includes both normal and botnet traffic. The dataset is available in multiple file formats, such as pcap, argus, and CSV.  
Figure 2: Proposed lightweight model for intrusion detection.  
The files are categorized based on attack types and subcategories to facilitate the labeling process. The dataset covers various attack categories, including DDoS, DoS, OS and service scan, keylogging, and data exfiltration. DDoS and DoS attacks are further organized based on the protocol used. A 5% sample was extracted using MySQL queries to make the dataset more manageable.  
This paper specifically uses the extracted 5%, which consists of four files totaling approximately 1.07 GB in size. It contains around 3 million records with 46 different features for training and testing. The features in the dataset include information such as packet sequence ID, timestamps, flags, protocols, source and destination addresses, packet and byte counts, connection states, durations, statistical values, and various network metrics. Additionally, the dataset provides attributes related to attack labels, categories, and subcategories.  
In summary, the BoT-IoT dataset is a comprehensive collection of network traffic data created in a realistic environment. It contains a subset of records from various attack categories and subcategories, enabling researchers to train and test cybersecurity models. The dataset's features cover a wide range of network-related attributes, facilitating the analysis and development of effective defense mechanisms against different types of attacks.
# A Non-Smooth Numerical Optimization Approach to the Three-Point Dubins Problem (3 PDP)
## 4 Derivatives of the Optimal Lengths
### Derivatives of the LSR and RSL Cases  
We compute herein the partial derivatives of the optimal lengths for the CSC\({}^{-}\)case given in (19) with respect to \(\alpha\) or \(\beta\):  
\[\begin{split}\partial_{\alpha}(\ell_{1}^{\text{CSC}^{-}}+\ell_{ 3}^{\text{CSC}^{-}})&=2\,s\,\partial_{\alpha}\theta_{S}^{\text{ CSC}^{-}}-s,\\ \partial_{\beta}(\ell_{1}^{\text{CSC}^{-}}+\ell_{3}^{\text{CSC}^{- }})&=2\,s\,\partial_{\beta}\theta_{S}^{\text{CSC}^{-}}-s.\end{split} \tag{39}\]Then, using (6) and (14), we have  
\[\partial_{\alpha}\ell_{2}^{\text{SC}^{-}} =\partial_{\alpha}\Big{(}(d+s\,\delta^{+})\cos\theta_{5}^{\text{ CSC}^{-}}-s\,C^{+}\sin\theta_{S}^{\text{CSC}^{-}}\Big{)} \tag{40}\] \[=s\cos(\alpha-\theta_{5}^{\text{CSC}^{-}})-\Big{(}(d+s\,\delta^{+} )\sin\theta_{S}^{\text{CSC}^{-}}+s\,C^{+}\cos\theta_{S}^{\text{CSC}^{-}}\Big{)} \partial_{\alpha}\theta_{S}^{\text{CSC}^{-}}\] \[=s\cos\ell_{1}^{\text{CSC}^{-}}-2\,s\,\partial_{\alpha}\theta_{5} ^{\text{CSC}^{-}},\] \[\partial_{\beta}\ell_{2}^{\text{CSC}^{-}} =\partial_{\beta}\Big{(}(d+s\,\delta^{+})\cos\theta_{5}^{\text{ CSC}^{-}}-s\,C^{+}\sin\theta_{S}^{\text{CSC}^{-}}\Big{)}\] \[=s\cos(\beta-\theta_{5}^{\text{CSC}^{-}})-\Big{(}(d+s\,\delta^{+} )\sin\theta_{S}^{\text{CSC}^{-}}+s\,C^{+}\cos\theta_{S}^{\text{CSC}^{-}} \Big{)}\partial_{\beta}\theta_{S}^{\text{CSC}^{-}}\] \[=s\cos\ell_{3}^{\text{CSC}^{-}}-2\,s\,\partial_{\alpha}\theta_{5 }^{\text{CSC}^{-}}.\]  
In this case, the partial derivatives of the sum of the lengths cancel out the contribution of the partial derivative of \(\theta_{S}\), yielding a simplified expression derived from (39) and (40):  
\[\partial_{\alpha}(\ell_{1}^{\text{CSC}^{-}}+\ell_{2}^{\text{CSC} ^{-}}+\ell_{3}^{\text{CSC}^{-}}) =s(\cos\ell_{1}^{\text{CSC}^{-}}-1), \tag{41}\] \[\partial_{\beta}(\ell_{1}^{\text{CSC}^{-}}+\ell_{2}^{\text{CSC} ^{-}}+\ell_{3}^{\text{CSC}^{-}}) =s(\cos\ell_{3}^{\text{CSC}^{-}}-1).\]  
Substituting the lengths into their expression from (19), we can write the partial derivatives of the sum of the lengths from (41) as  
\[\partial_{\alpha}(\ell^{\text{CSC}^{-}}) =s(\cos(\theta_{S}^{\text{CSC}^{-}}-\alpha)-1), \tag{42}\] \[\partial_{\beta}(\ell^{\text{CSC}^{-}}) =s(\cos(\theta_{S}^{\text{CSC}^{-}}-\beta)-1).\]  
The upper bound of the derivative and thus of the Lipschitz constant is 2.
# Application of a New Enhanced Deconvolution Method in Gearbox Fault Diagnosis
###### Abstract  
When the mechanical transmission mechanism fails, such as gears and bearings in the gearbox, its vibration signal often appears as a periodic impact. Considering the influence of noise, however, the fault signal is often submerged in the noise, so it is necessary to propose a feasible and effective fault extraction method. MOMEDA (multipoint optimal minimum entropy deconvolution adjusted) overcomes the tedious iterative process of MED (minimum entropy deconvolution) and overcomes the resampling trouble in MCKD (maximum correlated kurtosis deconvolution). It is suitable for dealing with periodic impact signal. Besides, aiming at the poor ability of MOMEDA to capture the deconvolution result of target function in a strong noise environment, this paper proposes an improved MOMEDA gearbox fault feature extraction method. Considering that MOMEDA has poor anti-noise performance and can easily cause misdiagnosis in a strong noisy environment, this paper constructs an autoregressive mean sliding model to improve the noise immunity of MOMEDA. Firstly, the stability of the test signal is judged by the autocorrelation coefficient (ACF) and the partial correlation coefficient (PACF). Secondly, the ARMA (autoregressive moving average) model is constructed and a set of optimal model coefficients are obtained to filter the signal, which greatly improves MOMEDA's ability to capture fault features. Thirdly, the fault feature is extracted by MOMEDA, and the fault information is extracted accurately under a strong noise environment. Finally, compared with AR-MED, ARMAMED, and other methods, the advantages of ARMAMOMEDA are verified. Moreover, the effectiveness and superiority of the proposed method are verified by simulation signals and experimental data from the Case Western Reserve University Bearing Data Center.  
autoregressive moving average model; multipoint optimal minimum entropy deconvolution adjusted; feature extraction; rotating machinery +
Footnote †: journal: Applied Sciences