esa-sceva/satcom-chunk-collection huggingface dataset:
# Order-Based Schedule of Dynamic Topology for Recurrent Neural Network
## 2 Theoretical Frameworks
### Practical Method for Determining the Minimal Embedding Dimension of a Scalar Time Series  
This method, proposed by [PERSON] [14], eliminates the need to make use of the threshold parameter used by the FNN algorithm (\(Rotol\)), which determines if the neighbor of a point is false or not, by describing it as a subjective parameter.  
Let \(X=x_{1},x_{2},x_{3},...,x_{N}\) be a time series, and \(y\) a \(d\)-dimensional vector defined as.  
\[y_{i}(d)=\Big{[}x_{i},x_{i+\tau},\ldots,x_{i+(d-1)\tau}\Big{]}i=1,2,\ldots,N-(d- 1)\tau \tag{1}\]  
where both \(i\) and \(\tau\) are values indicating the index of the original series data, where \(\tau\) is the shift in the data and \(d\) is the dimension under analyzed. Similar to the FNN algorithm is defined:  
\[a(i,d)=\frac{\Big{|}\Big{|}y_{i}(d+1)-y_{r(i,d)}(d+1)\Big{|}\Big{|}}{\Big{|} \Big{|}y_{i}(d)-y_{r(i,d)}(d)\Big{|}\Big{|}}i=1,2,\ldots,N-d\tau \tag{2}\]  
Being the relationship between the distance of a point and its nearest neighbor in a larger dimension \((d+1)\) and the distance between the same points (anchor point and its neighbor) but in the dimension of analysis \((d)\). If \(d\) qualifies as an embedded dimension, then any pair of close points in d must remain close in \(d+1\), if this is true these two points will be described as true neighbors, otherwise, they will be false neighbors. This is the base of the FNN algorithm. From this result, FNN determines the status of the neighbors by comparing the change ratio between both points with respect to a threshold \((Rotol)\), so [PERSON] substituted this threshold by implementing the following equation:  
\[E(d)=\frac{1}{N-d\tau}\sum_{i=1}^{N-d\tau}a(i,d) \tag{3}\]  
This is the average of all distance ratios \((a(i,d))\). Where \(E(d)\) only depends on \(d\) and \(\tau\). In turn, \(E1(d)\) is defined, which shows the variation of the averages during the expansions that exist from \(d\) to \(d+1\).  
\[E_{1}(d)=\frac{E(d+1)}{E(d)} \tag{4}\]  
where instead of using the threshold proposed in FNN, this method observes \(E1(d)\), which will stop changing when d is greater than a correct embed dimension \((dx)\) so the minimum dimension will be \((dx+1)\).
# A Local Feature Engineering Strategy to Improve Network Anomaly Detection +
###### Abstract  
The dramatic increase in devices and services that has characterized modern societies in recent decades, boosted by the exponential growth of ever faster network connections and the predominant use of wireless connection technologies, has materialized a very crucial challenge in terms of security. The anomaly-based intrusion detection systems, which for a long time have represented some of the most efficient solutions to detect intrusion attempts on a network, have to face this new and more complicated scenario. Well-known problems, such as the difficulty of distinguishing legitimate activities from illegitimate ones due to their similar characteristics and their high degree of heterogeneity, today have become even more complex, considering the increase in the network activity. After providing an extensive overview of the scenario under consideration, this work proposes a Local Feature Engineering (LFE) strategy aimed to face such problems through the adoption of a data preprocessing strategy that reduces the number of possible network event patterns, increasing at the same time their characterization. Unlike the canonical feature engineering approaches, which take into account the entire dataset, it operates locally in the feature space of each single event. The experiments conducted on real-world data showed that this strategy, which is based on the introduction of new features and the discretization of their values, improves the performance of the canonical state-of-the-art solutions.  
Keywords: intrusion detection; anomaly detection; networking; data preprocessing; machine learning +
Footnote †: journal: Computer Science
## 6 Verification and Results
### Episode 1: Packet Forwarding and Provisioning (req: i, iii, iv, vi)
#### 6.1.3 Summary  
The overall results show that the solution is fulfilling the following requirements:  
**Req i \(\checkmark\)**: We have shown that the architecture provides hop-by-hop encryption by monitoring the traffic flows before and after the provisioning of the EFs. In addition, small network outages during re-keying confirm that the encrypted links are running and that the key change is working.  
**Req iii \(\checkmark\)**: The fact that requirement i is fulfilled also confirms that the forwarding of the new packet header is possible when the Virtual Links are encrypted. Hence, the new SFC header is not encrypted. This is also confirmed by analysing SFC packets.  
**Req iv \(\checkmark\)**: By running provisioning and alternating different network topologies, we have shown that a RESTconf based control plane in a multi-tenant environment is capable of distributing micro-segmented flow rules according to the requirements.  
**Req vi \(\checkmark\)**: By applying the NSH header in an interconnected multi-tenant data centre, we have shown that the new NSH header is easily adaptable (Section 4.1). This is because the NSH header is applied in an overlay network. Throughput tests have shown that a single EF does not degrade the throughput performance more than a single SF. However, due to the lack of an effective P4 virtualisation platform in our implementation, the performance significantly degrades when the number of SFs increase. Hence, the adoption of P4 in NFV is highly dependent on hardware accelerators.
## 3 Experiment Results and Analysis
### Visual Presentation of Experimental Results
#### 3.4.2 Visual Presentation of Multi-Source Trajectory Data Set  
Figure 20 shows the centers of the clustering results for each algorithm in multi-source trajectory data set. On the corresponding map, we intuitively perceive the distribution of clustering results based on various algorithms.
## 3 Results and Discussion
It is found that the surface roughness of the ETL influences the grains size and topography of the perovskite film as it acts a seeding substrate during the deposition of the perovskite active layer [9]. In addition, the interface between the ETL and active perovskite film is also affected. Perovskite films with large grains size has produced lower series resistance of the active layer, leading to improvement in the performance of PSCs [17]. Recent researches have shown that the existence of large-sized perovskite grains enhance the mobility of charge carrier and decreases recombination of bulk defects [18; 19]. The highest conversion efficiency in this study was achieved using M-TiO\({}_{2}\) doped with FK209 due to its lowest surface roughness and largest grains size perovskite films. \begin{table}
\begin{tabular}{c c c c c} \hline
**Name** & **Conductivity (\(\alpha\))** & **Bulk Resitivity** & **Mobility (u)** & **Carrier Density** \\  & \(\times\) 10\({}^{3}\) **1/1/1.cm]** & **(\(\phi\)) \(\times\) 10\({}^{-4}\) [\(\Omega\).cm]** & \(\times\) 10\({}^{3}\) [cm\({}^{2}\)/vs]** & \(\times\) 10\({}^{3}\) [cm\({}^{-3}\)] \\ \hline M-TiO\({}_{2}\) control & 22 & 0.45 & 1.23 & 11.29 \\ M-TiO\({}_{2}\) + Li\({}^{+}\) salt & 23.5 & 0.42 & 1.73 & 8.6 \\ M-TiO\({}_{2}\) + FK209 cobalt & 30 & 0.33 & 8.32 & 2.27 \\ M-TiO\({}_{2}\) + FK209/Li\({}^{+}\) & 26.3 & 0.38 & 6.2 & 2.65 \\ \hline \end{tabular}
\end{table} 
Table 1: Electrical properties of the undoped M-TiO\({}_{2}\) control and M-TiO\({}_{2}\) doped with FK209, FK209/Li\({}^{+}\) and Li\({}^{+}\). Figure 1: Left, AFM images of the surface morphology structure and roughness of the (**a**) undoped mesoporous TiO\({}_{2}\), RMS = 34.5 nm; (**b**) M-TiO\({}_{2}\) doped with FK209, RMS = 16 nm; (**c**) FK209/Li\({}^{+}\), RMS = 22.75 nm; (**d**) Li\({}^{+}\), RMS = 25.46 nm. Right, contact angle measurement of (**a**) undoped M-TiO\({}_{2}\), \(\theta\) = 14\({}^{\circ}\); (**b**) M-TiO\({}_{2}\) doped with FK209, \(\theta\) = 4.2\({}^{\circ}\); (**c**) FK209/Li\({}^{+}\), \(\theta\) = 9\({}^{\circ}\); (**d**) Li\({}^{+}\), \(\theta\) = 13\({}^{\circ}\). Figure 2: Cont. ImageJ software was used to calculate the grains size and Origin9 software was used to plot their histogram. The SEM images in Figure 2 show that using M-TiO\({}_{2}\) doped with FK209 provides a uniform perovskite films with an average grains size of 242 nm, which is larger than grains size of perovskite deposited on M-TiO\({}_{2}\) doped with Li\({}^{+}\) or FK209/Li\({}^{+}\). The average grains size of perovskite deposited on M-TiO\({}_{2}\) doped with FK209/Li\({}^{+}\) decreased to 210 nm, whereas, perovskite films deposited on M-TiO\({}_{2}\) doped with Li\({}^{+}\) has an average grains size of 205 nm as shown in the histogram of Figure 2. Our results demonstrate that perovskite deposited on M-TiO\({}_{2}\) doped with FK209 have the largest grains size and possess less defects compared with perovskite deposited on ETL with the other dopants. Larger grains results in a dense structure and improved crystallization allowing for enhanced conduction properties [20].
## 3 Results and Discussion
### Blowing Ratio \(M=1.0\)
In Figure 15a at 1/4 T, inadequate cooling is observed in the region directly behind the film hole due to the upward movement of the cooling jet. However, at subsequent time intervals (3/4 T or T), enhanced cooling performance is evident immediately behind the hole, attributed to the influence of the incoming wake, which directs the cooling jet to adhere to the bottom wall. Similarly, in Figure 15b-d, insufficient cooling is observed in the regions behind the hole. Furthermore, a decrease in the exit velocity of the pulsating jet results in reduced coverage and intensity of the cooling protection. Figure 16 illustrates the streamwise distribution of the time-averaged film cooling efficiency. It is evident that the immediate region behind the film hole (denoted as 0) experiences suboptimal lower wall cooling due to the uplifting effect of the cooling jet. The phase delay between the incoming wake and the pulsating jet notably influences film cooling effectiveness. Our study reveals that a decreased phase delay, as defined herein, results in higher cooling efficiency for the pulsating jet compared to steady cooling. Conversely, the cooling efficiency diminishes as the phase delay increases. A detailed comparison of the results in Figures 8, 12 and 16 reveals the relationship between the time-mean span averaged film cooling efficiency and varying blowing ratios. At a low blowing ratio of M = 0.3, the relationship between wake-jet coupling and cooling efficiency is notably intricate, as significant phase lag influences the coverage of the coolant jet. When the blowing ratio increases to M = 0.5, the effect of the plane's induced lift due to the wake becomes more prominent, thereby impacting cooling efficiency through the interaction between jet lift and fluctuations in the blowing ratio. At M = 1.0, the elevated blowing ratio results in a substantial jet lift, with the influence of the wake primarily observed at the leading and trailing edges of the elevated region. Although a zero-phase lag consistently produces the highest cooling efficiency across all blowing ratios, the underlying mechanisms and the extent of the efficiency changes depend on the specific blowing ratios employed. Figure 13: Contours of temperature in one period for different phase lags in \(Z=0\) at M = 1.0. Figure 14: Cont. Figure 14: Contours of vorticity in one period for different phase lags in \(Z=0\) at M = 1.0. Figure 15: Cont. Figure 11:0 Streamwise distribution of time-mean span averaged film cooling efficiency at M = 1.0. Figure 11:1 Contours of temperature on the bottom wall in one period for different phase lags at M = 1.0.
# Management of Acute Life-Threatening Asthma Exacerbations in the Intensive Care Unit
## 4 Acute Life-Threatening Asthma Advanced Management in the ICU
### Extracorporeal CO\({}_{2}\) Removal (ECCO\({}_{2}\)R)  
Extracorporeal carbon dioxide removal (ECCO\({}_{2}\)R) provides a means of fast and effective treatment of CO\({}_{2}\) removal in acute hypercapnic respiratory failure; however, in comparison to extracorporeal membrane oxygenation (ECMO), the blood is not oxygenated before returning to the body [102, 103]. Given the solubility and diffusion characteristics of carbon dioxide compared to oxygen, ECCO\({}_{2}\)R requires much lower blood flow rates. Utilising this system, the deleterious effects of IMV can be lessened [104, 105]. Several case reports have demonstrated the efficacy of ECCO\({}_{2}\)R in the adult asthma population [106, 107, 108]; however, only limited comparative robust data exist on this topic. [PERSON] et al. retrospectively analysed 26 adult patients from a single centre who required ECCO\({}_{2}\)R for status asthmatics, demonstrating 100% survival to hospital discharge with significant improvements in tidal volumes, respiratory rate, intrinsic PEEP, peak and plateau pressures, and acidosis following one day of ECCO\({}_{2}\)R [109]. Additionally, the use of vasopressors was significantly reduced after ECCO\({}_{2}\)R initiation, highlighting that correction of acidosis with subsequent reduction in ventilator pressures can improve hemodynamic stability. Additionally, 76.9% of patients were able to be exubated whilst ECCO\({}_{2}\)R was being delivered, further reducing the incidence of ventilator-associated lung injuries commonly seen in asthma [109].  
The REST randomised trial investigated the use of ECCO\({}_{2}\)R in acute hypoxic respiratory failure. In this trial, 412 patients were randomised to ECCO\({}_{2}\)R with reduced tidal volume ventilation or standard intensive therapy. There was no difference in 90-day mortality; however, ECCO\({}_{2}\)R was associated with significantly reduced ventilator-free days and a much higher incidence of serious adverse complications (31% versus 9%), including intracranial haemorrhage. This trial was subsequently terminated early, and therefore, despite these concerning initial results, the study may have been too underpowered to show any potential benefit [110]. More research is required in this area, and in the UK, NICE guidelines support the use of ECCO\({}_{2}\)R only in the context of a clinical trial [111].
###### Abstract  
The Shuangjianzishan silver polymetallic deposit is located in the copper-tin-lead-zinc-silver polymetallic metallogenic belt in the Southern Great Xing'an Range, with silver resources of more than 18,000 t, which is the largest silver polymetallic deposit in Asia. Early studies concluded that the Shuangjianzishan deposit is typically an epithermal Ag-Pb-Zn deposit that lacks a high-temperature mineralization stage. In recent years, with the deepening of research, a large amount of Cu-Sn mineralization has been found in the deep part of the Shuangjianzishan deposit, but it is less studied. The laser-ablation inductively coupled mass spectroscopy (LA-ICP-MS) technique is used to investigate the distribution and substitution of trace elements in chalcopyrite and cassiterite. In this paper, the trace element study of chalcopyrite and cassiterite from the Shuangjianzishan deposit reveals that Sn, In, As, Se, Sb, and Tl mainly exist in chalcopyrite in isomorphic form, while Pb, Bi, and Ni mainly exist in chalcopyrite in the form of mineral inclusions. The enrichment of the high-temperature elements Sn and Se in chalcopyrite, and the deficit of the middle- and low-temperature elements Ga, Sb, etc., reflect that the chalcopyrite in the Shuangjianzishan deposit was formed in a middle- and high-temperature environment, and it also indicates that the early one-forming hydrothermal solution may be rich in Sn. Fe, In, Co, and Ni mainly exist in cassiterite in isomorphic form, and the content of W in cassiterite is high. There are two main forms, one is isomorphic and the other is wolframite inclusion. Cassiterite has Fe-rich and W-U-poor characteristics, indicating that cassiterite from the Shuangjianzishan deposit was formed under relatively oxidized conditions, and the relative enrichment of elements such as Fe, W, Zr, and Hf indicates that the temperature of cassiterite formation was high. The elemental content and inter-ionic coupling relationships suggest that the cassiterite from the Shuangjianzishan deposit may have an elemental replacement mechanism of W\({}^{6+}\) Fe\({}^{2+}\)\(\leftrightarrow\)2 Sn\({}^{4+}\) or Fe\({}^{3+}\) OH\({}^{-}\)\(\leftrightarrow\) Sn\({}^{4+}\)\(+\) O\({}^{2-}\). The trace elements in cassiterite of the Shuangjianzishan deposit are rich in Fe and Mn and depleted in Nb and Ta, according to the Fe-W diagram, and the tin mineralization of the Shuangjianzishan deposit belongs to cassiterite-sulfide-type tin mineralization. Chalcopyrite Co/Ni ratios \(>\)1 are consistent with the characteristics of chalcopyrite genesis in hydrothermal deposits.  
the Shuangjianzishan deposit; tin mineralization; deposit genesis; trace element +
Footnote †: journal: Applied Sciences
_Applied_  
_sciences_  
_Article_  
**Damage Assessment Using Information Entropy of Individual Acoustic Emission Waveforms during Cyclic Fatigue Loading**  
**[PERSON] \({}^{\star}\), [PERSON], [PERSON] and [PERSON]**  
Center for Risk and Reliability, Department of Mechanical Engineering, University of Maryland, 2181 Glenn L. Martin Hall, 4298 Campus Dr., College Park, MD 20742, USA; [EMAIL_ADDRESS] (A.K.);  
[PERSON]L_ADDRESS] (H.Y.); [PERSON]DDRESS] (M.M.)  
\({}^{\star}\) Correspondence: [PERSON]RESS]  
Academic Editors: [PERSON] and [PERSON]  
Received: 24 February 2017; Accepted: 25 May 2017; Published: 30 May 2017  
**Featured Application: The work presented in this paper outlines three methods to analyze individual acoustic emission waves emitted within a cyclically-loaded metallic structure. Upon further development, one potential application of the proposed analysis methods would be to aid in estimating the remaining useful life of aircraft structures.**  
**Abstract:** Information entropy measured from acoustic emission (AE) waveforms is shown to be an indicator of fatigue damage in a high-strength aluminum alloy. Three methods of measuring the AE information entropy, regarded as a direct measure of microstructural disorder, are proposed and compared with traditional damage-related AE features. Several tension-tension fatigue experiments were performed with dogbone samples of aluminum 7075-T6, a commonly used material in aerospace structures. Unlike previous studies in which fatigue damage is measured based on visible crack growth, this work investigated fatigue damage both prior to and after crack initiation through the use of instantaneous elastic modulus degradation. Results show that one of the three entropy measurement methods appears to better assess the damage than the traditional AE features, whereas the other two entropies have unique trends that can differentiate between small and large cracks.  
**Keywords:** information entropy; acoustic emission; fatigue; damage
# Considering the Life-Cycle Cost of Distributed Energy-Storage Planning in Distribution Grids
## Nomenclature  
### \(Ah_{1}\)  
\begin{tabular}{l l l l} \(Ah_{1}\) & the charging energy during event \(I\). & \(P_{S}\) & the active power of main grid \\ \(Cost\) & the average annual cost of the ESS within & \(P_{L}\) & the active power of load \\  & project planning period & & \\  & the capital investment of ESS in the first-stage & \(P_{lass}\) & the active power of line loss \\ \(Cost1\) & optimization & & \\  & the LCC of ESS in the second-stage & \(P_{jmin}\) & the lower active power limits of line \(ij\) \\ \(C_{spin}\) & the annual average capital cost of ESS & \(P_{jmax}\) & the upper active power limits of line \(ij\) \\ \(C_{bat}\) & the cost of storage unit & \(P_{jj}\) & the actual active power on line \(ij\) \\ \(C_{E}\) & the price of capacity per kW-h & \(P_{ESS,trate}\) & the rated power of ESS at node \(i\) \\ \(C_{PCS}\) & the cost of the PCS & \(P_{ESS,i}\) & The output power of ESS at node \(i\) \\ \(C_{P}\) & the charging cost at per kW of \(C_{PCS}\) & \(P_{ESS,t}\)(t) & the real charging/discharging power of node \(i\) \\ \(C_{BOP}\) & the cost of the necessary supporting facilities & \(P_{ESS,attr}\) & at time \(t\) \\ \(C_{B}\) & the cost per kW-h of the necessary supporting & & \\  & facilities & & \\ \(C_{lass}\) & the cost of line losses & \(R_{th}\) & the empirical constant \\ \(C_{prut}\) & the cost of punishment & \(SOC_{max}\) & the upper limits of the SOC \\ \(C_{TOP}\) & the fixed operation and maintenance cost & \(SOC_{min}\) & the lower limits of the SOC \\ \(C_{f}\) & the operation and maintenance cost per kW & \(SOC_{i}\) & the SOC value of node \(i\) \\ \(C_{VOM}\) & the variable operation and maintenance cost & \(SOC_{msg,l}\) & the average SOC during the event \(I\) \\ \(C_{c}\) & the electricity cost & \(SOC_{tx,l}\) & the SOC deviation during the event \(I\) \\ \(C_{rep}\) & the annual average replacement cost & \(SOC(I)\) & the SOC in time \(t\) \\ \(C_{dis}\) & the annual average disposal cost & \(T\) & the initial temperature of annealing \\ \(C_{d}\) & the specific disposal cost per kW of the battery \(T_{ref}\) & the reference temperature in the operation \\ \(COE\) & the cost per kW-h of ESS. & \(T_{I}\) & the temperature of ESS in event \(I\) \\ \(D\) & the maximum depth of discharging & \(V_{max}\) & the upper voltage limits \\  & the capacity of ESS at node \(i\) in the first-stage & \(V_{min}\) & the lower voltage limits \\ \(E_{i}\) & optimization & & \\  & the minimum capacity that must meet ESSs\({}^{\prime}\) & \(V_{j}\) & the actual voltage magnitude at node \(j\) \\ \(E_{0,i}\) & output & & \\ \(E_{rate}\) & the rated capacity of ESS & \(Y\) & the project cycle (year) \\ \(E_{ESS,i}\)(t) & the energy fluctuation relative to the initial & \(\beta\) & the average annual decline rate of ESS capital \\ \(E_{ESS,i}\)(t) & state of ESS at every installation nodes & cost & \\ \(E_{r}\) & the energy rate of the ESS (\(kW/kW\)-h) & \(\eta\) & the overall round-trip efficiency \\ \(E_{E}\) & the activation energy & & \\ \end{tabular}
###### Abstract  
Intensive development of many industries, including textile, paper, plastic or food, generate huge amounts of wastewaters containing not only toxic dyes but also harmful auxiliaries such as salts, acid, bases, surfactants, oxidants, heavy metal ions. The search for effective pollutant adsorbents is a huge challenge for scientists. Synthesis of divinylbenzene copolymer with glycolidyl methacrylate functionalized with triethylenettermine (DVB-_co_-GMA-TETA) resin was performed and the obtained microspheres were evaluated as a potential adsorbent for acid dye removal from dyeing effluents. The sorption capacities were equal to 142.4 mg/g for C.I. Acid Green 16 (AG16), 172 mg/g for C.I. Acid Violet 1 (AV1) and 216.3 mg/g for C.I. Acid Red 18 (AR18). Non-linear fitting of the Freundlich isotherm to experimental data was confirmed rather than the Langmuir, Temkin and Dubinin-Radushkevich. The kinetic studies revealed that intraparticle diffusion is the rate-limiting step during dye adsorption. Auxiliaries such as Na\({}_{2}\)SO\({}_{4}\) (5-25 g/L), CH\({}_{3}\)COOH (0.25-1.5 g/L) and anionic surfactant (0.1-0.5 g/L) present in the dyeing baths enhance the dye adsorption by the resin in most cases. Regeneration of DVB-_co_-GMA-TETA is possible using 1 M NaCl-50% _vv_ CH\({}_{3}\)OH.  
polymeric resin; dye removal; sorption; Acid Violet 1; Acid Green 16; Acid Red 18
# TRAP: A Three-Way Handshake Server for TCP Connection Establishment
## 2 Background
### TCP Options  
Internet Assigned Numbers Authority (IANA) has defined various TCP options in the TCP connection headers, including window scale, selective ACK (SACK) implementation, and maximum segment sizes (MSS) in RFC2780 [12].  
As Figure 3, TCP options is defined in three fields: a type number, option length, and option data. In total, TCP options can store up to 40 bytes of data.  
Some of the commonly used option numbers are maximum segment size (0x02), windows scale (0x03), selective acknowledgement number (0x04), and TCP timestamps (0x08).