esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
Gelatin-based functional films incorporated with CuSNP were prepared for active food packaging use. The inclusion of CuSNP improved the mechanical properties of the gelatin film by more than 40% and amplified the water vapor barrier properties by more than 25%. Moreover, the addition of CuSNP improved the UV-shielding effect of the gelatin film by 90% or more. CuSNP was well dispersed between gelatin polymers to make a composite film with high compatibility with gelatin. However, FTIR results displayed that the addition of CuSNP did not modify the chemical structure of the gelatin film. The thermal stability of the film was slightly improved, which may have been due to the crosslinking interaction between CuSNP and gelatin. The gelatin/CuSNP films also presented potent antimicrobial activity against foodborne pathogenic bacteria, _E. coli_, and some action against _L. monocytogenes_. The functional gelatin/CuSNP films with antibacterial and UV-blocking properties are expected to be useful in active food packaging applications.  
Conceptualization, investigation, data curation, and writing--original draft preparation, S.R.; resources, review and editing, project administration, and supervision, J.-W.R. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A2C2084221).  
Not applicable.  
The authors declare no conflict of interest.
# From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
## 5 QAOA Mappings: Orderings and Schedules
### SMS, with Release Dates  
Problem. \((1|d_{j},r_{j}|*)\). Given a set of jobs with integer processing times \(\mathbf{p}\), deadlines \(\mathbf{d}\), release times \(\mathbf{r}\), and weights \(\mathbf{w}\), find a schedule that minimizes some function of the tardiness, such that each job starts no earlier than its release time.  
We considered SMS problems with release times \(r_{j}\). We do not specify the objective function here, as any of those used in previous sections are still applicable. Our focus in this section is to introduce a modification of the time-swap mixer that preserves feasibility with release times.  
Let the horizon \(h\) be some upper bound on the maximum completion time, e.g., \(\max_{j}d_{j}+\sum_{j}p_{j}\). Let \(b_{j}=h+\sum_{i=1}^{j-1}p_{i}\) be a special \"buffer\" time for job \(j\). Let \(W_{j}=[r_{j},h-p_{j}]\) be the window of times in which job \(j\) can start.  
Consider the configuration space \(\times_{j=1}^{n}\left[W_{j}\cup\{b_{j}\}\right]\), i.e., schedules \(\{\mathbf{s}\}\) in which a job is scheduled either between its release time and the horizon or at its buffer time slot. The domain is the subset of the configuration space that satisfies the problem constraint that no two jobs overlap.
## 4 The Proposed Nonlinear Higher-Order Extended State Observer (NHOESO)
### Justification for Adding an Additional Augmented State
\tag{18}\]  
It is shown in Theorem 1 that \(\lim\limits_{t\to\infty}\bigl{|}\dot{\xi}_{1}-\dot{\xi}_{1}\bigr{|}=\frac{1}{ \omega\varphi^{t+2}}\frac{2M_{h}\lambda^{2}_{max}(P)}{\lambda_{min}(P)}\), where the R.H.S is a constant (\(\rho\), \(\omega_{0}\), \(\lambda_{min}(P)\), \(\lambda_{max}(P)\), and \(M_{h}\) are constants). So, given that \(y=\dot{\xi}_{1}\) and if Equation (23) has integration term \(\beta_{4}\int_{0}^{t}\big{(}y-\dot{\xi}_{1}\big{)}\ dt\), then, the result of the integration will be constant too. It can be noticed in (16) that the estimated generalized disturbance \(\dot{\xi}_{3}\) is a function of the error \(e_{1}=y-\dot{\xi}_{1}\) and will change in accordance with the error. It will settle to its actual value \(\dot{\xi}_{3}\) when the estimation error \(y-\dot{\xi}_{1}\) becomes zero. Meanwhile, in the NHOESO (18), and due to the integration term \(\beta_{4}\int_{0}^{t}\big{(}y-\dot{\xi}_{1}\big{)}\ dt\), the estimated generalized disturbance \(\dot{\xi}_{3}\) of the NHOESO will take a longer time to settle to its actual value \(\dot{\xi}_{3}\), which requires the following condition:  
\[\beta_{4}\int_{0}^{t}\big{(}y-\dot{\xi}_{1}\big{)}\ dt+\beta_{3}\big{(}y-\dot{ \xi}_{1}\big{)}=0 \tag{19}\]  
Letting \(e_{1}=y-\dot{\xi}_{1}\), (19) can be expressed as  
\[\beta_{4}\int_{0}^{t}e_{1}\ dt+\beta_{3}e_{1}=0 \tag{20}\]  
Taking the derivative of (20) w.r.t \(t\), we obtain  
\[\dot{e}_{1}=-\frac{\beta_{4}}{\beta_{3}}e_{1} \tag{21}\]  
Solving (21) w.r.t \(t\), yields  
\[e_{1}(t)=e_{1}(0)exp\bigg{(}-\frac{\beta_{4}}{\beta_{3}}t\bigg{)}\]  
Therefore, the condition (19) will be satisfied at \(t\to\infty\) _(i.e., \(t=-\frac{\beta_{3}}{\beta_{4}}ln\Big{(}\frac{e_{1}(t)}{e_{1}(0)}\Big{)}\) when \(e_{1}(t)\) has a very small value), or as the ratio \(\frac{\beta_{4}}{\beta_{3}}\) is large enough, where \(e_{1}(t)=e_{1}(0)exp\Big{(}-\frac{\beta_{4}}{\beta_{3}}t\Big{)}\) will decay faster to zero.
# Design and Simulation of Electromagnetic Linear Actuators for Jet Dispensers
## 2 Analysis Method for Electromagnetic Actuators and Design Process  
### Simplified Electromagnetic Actuators' Model  
The actuators considered in the present study (SA, MCA, and MMA) are all linear electromagnetic actuators (EMAs), which operate based on the force interaction between magnetic fields. The basic configurations of the three actuators are shown in Figure 2a-c, respectively. For all three actuators, the structure comprises two main parts, namely an electric part and a magnetic part. The electric part consists of a current-carrying coil fixed within a coil holder, while the latter part contains a frame/shell and a plunger (SA), fixed magnets (MCA), or movable magnets (MMA). For all three actuators, the movable parts move freely along the z-axis (vertical) direction. When a current is passed through the coil, a magnetic field is produced with poles determined by the direction in which the current flows. The current-induced magnetic field then prompts a motion of the movable parts, as described in the following.  
For the SA, the iron plunger is located within the cylindrical coil and is moved toward the mid-point position of the coil under the effects of the electromagnetic force produced by the actuating current. As the iron plunger moves, it compresses the spring. When the current is subsequently removed, the linear restoring force of the compressed spring pushes the plunger in the opposite direction, producing an actuating effect [39; 40].  
For the MCA and MMA, the interaction between the permanent magnet and the current-carrying coil generates an electromagnetic force pair that exerts a force of the same magnitude, but in the opposite direction, on the magnetic part and electric part, respectively. The strength of the thrust force depends on both the field strength of the permanent magnet and the magnitude of the excitation current. Moreover, the motion direction of the movable parts depends on the current direction. In other words, both actuators (MCA and MMA) are bi-directional, and may or may not use a return spring to drive the movable parts during the dispensing stage.  
As described in the following, the electromagnetic force along the z-axis of the SA, MCA, and MMA considered in the present study are investigated by means of finite element analysis (FEA) simulations.  
Figure 2: Basic configurations of electromagnetic actuators. (**a**) Solenoid actuator (SA); (**b**) moving coil actuator (MCA), and (**c**) moving magnet actuator (MMA). 1. Iron shell/frame; 2. coil; 3. spring; 4. plunger; 5. flange; 6. magnet; and 7. coil holder.
## 3 Results and Discussion
### LID Scenario Analysis and Benefit Evaluation
#### 3.4.2 Simulation Effects of the LID Plans Under Different Rainfall Scenarios  
After obtaining the optimal structural parameters, the concave green space is placed under moderate rain and heavy rain, with a recurrence period of 5a and 10a to simulate runoff control benefits, so as to explore the applicable scope of the precipitation intensity of LID facilities. The results showed that the flood peak reduction rate, delay rate, and total runoff control rate were 61.97%, 56.25%, and 67.39%, respectively, in the precipitation scenario with a recurrence period of 1a, and 88.93%, 51.11%, and 78.76% in the precipitation scenario with a recurrence period of 5a. The recurrence period of 10a was 70.41%, 9.18%, and 64.75%. Therefore, the runoff regulation effect of the down-concave green space is the best under precipitation events, with a recurrence period of 5a (Figure 6). Excessive  
Figure 5: Total overflow flow of concave green space and corresponding hardened surface in different schemes. (**a**) Default parameter scheme; (**b**) A 10% reduction in planting soil thickness program; (**c**) A 10% slope reduction program for planted soil; (**d**) A 10% increase in planted soil program; (**e**) A 10% slope increase program for planted soil.  
rainfall can easily make the runoff discharge too large and the velocity too fast, and the bearing capacity of the concave green space can be exceeded, so that the regulation effect of stormwater runoff does not continue to grow or even reverse.
# Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China
###### Abstract  
Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20 th century and early 21 st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO\({}_{2}\) concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO\({}_{2}\) dry air mole fraction (XCO\({}_{2}\)) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO\({}_{2}\) changes during growing season for 13 years. We derived a relationship between XCO\({}_{2}\) and surface net CO\({}_{2}\) fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO\({}_{2}\) flux enhancement based on satellite observed XCO\({}_{2}\) changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO\({}_{2}\) emissions, we estimated an enhanced XCO\({}_{2}\) drawdown during the GP of \(-0.070\) to \(-0.084\) ppm yr\({}^{-1}\). Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2-3% of EC's annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO\({}_{2}\) to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord.  
N  
DVI; EVI; column CO\({}_{2}\); carbon sink; China; satellite
## 3 Results
### Model 1, Pulse Experiment  
For the pulse experiment, the Model 1 forecasts for ZA and antigen concentration in cells as well as theexperimental observations from [39; 40] are reported in Figure 3a,b. The estimated parameter values are shown in Tables 2 and 4.  
Pulse exposure to ZA for 1 h with 25 \(\upmu M\) was sufficient to induce IPP accumulation after drug removal both in MCF-7 breast cancer cells (observation period 0 to 48 h) and in T47D cells (0 to 42 h). The IPP accumulation in ZA-treated T47D cells was time-dependent, reaching a maximum concentration at 12 h, as shown in [39] (9.2 pmol/mgprot) and in [40] (1052 pmol/mgprot) and gradually decreasing until end of the experiment.  
We independently approximated the relationship between the rate of decay of antigen concentration in the medium and the prevalent concentration of ZA by considering Figure 2b from the published work of [PERSON] et al. From the data reported in this work, it can be seen that absent ZA in the medium, the level of antigen between 24 h and 44 h decreased from around 800 to around 400 pmol/mgprot. We, therefore, could assume a spontaneous decay half-life of the antigen of approximately 20 h, corresponding to an elimination rate of approximately 3.5% absent ZA. In fact, the estimated value of the elimination rate (\(k_{XG}^{tot}=2.3911\), see Table 4) is close to what can be empirically deduced from the published data, which confirms the robustness of the approach.  
The transfer rate of zoldronate from the cell to the medium (\(k_{YZ}\)) appeared to be equal to 18.0644 /h in the pulse experiment. This value is much higher than the value estimated from the continuous experiment data. This difference might be attributed to the fact that after internalization through endocytosis, N-BPs enter the cytosol thanks to SLC3A3 and ATRAID proteins [20]. They form a lysosome complex and are responsible for releasing N-BP molecules from the lumen into the cytosol [20; 44]. We can speculate that this mechanism could not be activated entirely during the short time of ZA treatment, thereby favouring the outflow of ZA from cells. This aspect could explain why the \(k_{YZ}\) rate  
Figure 3: Model 1 simulation trend in the pulse experiment. Panel (**a**) shows the simulated zoldronate (\(ZA\)) trend over time; panel (**b**) shows the simulated antigen (\(IPP\)) trend over time. The continuous blue line represents the model forecast, while red asterisks represent the experimental data obtained by [39] and red circles represent the experimental data obtained by [40].  
in pulse vs. continuous experiments is increased. The transport mechanisms of N-BPs are a current research topic [44], and our modelling results also suggest the need for further careful assays.  
Regarding the dynamics of the IPP it is possible to note (Table 4) that the antigen production rate (\(k_{G}=k_{XG}^{tot}G_{0}\)) in the pulse experiment assumes a significantly lower value than in the continuous experiment.  
Notice that the indicator variable \(\chi_{pulse}=1\) (Equation (1)) in this experimental situation, and \(t^{*}=1\)\(h\) as mentioned in MM section.
## 6 The GNSS Meaconing as a Terrorist Attack on USVs  
A GNSS Macon (the little brother of spoofing in Figure 7) is a system which receives GNSS signals, introducing the same delays into each of the satellite channels (the delay is determined by the difference in the GNSS signal paths from the satellites and from the meaconer to the GNSS navigator antenna), and retransmitting them on the same frequency, which is aimed at misleading GNSS receivers and creating a false PVT solution. i.e., GNSS navigators determine their position with some error, usually known to the spoofer. The properties of such a spoofer have been carefully studied. In particular, the term repeater was often used and is still used today as a synonym for meaconer [23].  
A meaconer receives, amplifies, and retransmits radio signals. The spoof signal delay is equal to the sum of the delay at the spoofer's receiving antenna, processing delay, and propagation delay from the spoofer to the victim. The victim locates the same location as the spoofer receiving antenna. Meaconing is relatively often used for geo-fencing of a some especially dangerous areas or water areas from unmanned technical means. For example, it has reported incidents in the Black Sea that occurred in 2017, when GPS receivers on board more than 20 ships showed the position of Gelendzhik airport [24]. Another well-known example of geo-fencing describes a similar behaviour of GPS receivers in the vicinity of Moscow's Red Square, which showed the positions of Vnukovo airport [25].
## 3 Study Area and Methodologies
### Methodologies
#### 3.2.6 Coordination Degree Model of the Eco-Economic System  
This study referred to the research of existing literature [38] and constructed the regional eco-economic harmony (\(EEH\)). The calculation formula was as follows:  
\[EEH=\frac{ESV_{pj}-ESV_{pi}}{ESV_{pi}}\Bigg{/}\frac{GDP_{pj}-GDP_{pi}}{GDP_{pi}} \tag{4}\]  
where \(EEH\) refers to the regional eco-economic harmony; \(ESV_{pi}\) and \(ESV_{pi}\) represent the ESV per unit area (\(10^{4}\) CNY/hm\({}^{2}\)) at the beginning and end of a period, respectively; \(GDP_{pi}\) and \(GDP_{pi}\) represent GDP per unit area (\(10^{4}\) CNY/hm\({}^{2}\)) at the beginning and end of a period, respectively.  
Since there is no unified standard for the classification of \(EEH\), the study drew on previous research experience and divided the \(EEH\) into 10 levels. The details are shown in Table 3.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**TCES** & **SCES** & **CL** & **FL** & **OL** & **GL** & **WB** & **BL** & **UL** \\ \hline \multirow{3}{*}{PS} & FP & 2645.66 & 604.55 & 1625.10 & 558.66 & 1915.41 & 23.94 & 23.94 \\  & MP & 586.59 & 1388.67 & 987.63 & 822.03 & 550.68 & 0.00 & 71.83 \\  & WS & \(-3124.51\) & 718.28 & \(-1203.12\) & 454.91 & 19848.41 & \(-17980.88\) & 47.89 \\ \hline \multirow{3}{*}{RS} & GS & 2130.89 & 4567.05 & 3348.97 & 2889.07 & 1843.58 & \(-5794.11\) & 263.37 \\  & CR & 1113.33 & 13665.23 & 7389.28 & 7637.69 & 5482.85 & 0.00 & 239.43 \\  & PE & 323.22 & 4004.40 & 2163.81 & 2521.95 & 13288.14 & \(-5889.88\) & 742.22 \\  & HD & 3579.42 & 8942.56 & 6260.99 & 5594.59 & 244789.04 & 0.00 & 502.79 \\ \hline \multirow{3}{*}{SS} & SC & 1245.01 & 5560.67 & 3402.84 & 3519.56 & 2226.66 & 47.89 & 311.25 \\  & MNC & 371.11 & 424.98 & 398.05 & 271.35 & 167.60 & 0.00 & 23.94 \\  & BD & 407.02 & 5063.86 & 2735.44 & 3200.33 & 6105.36 & 814.05 & 287.31 \\ \hline CS & AL & 179.57 & 2220.68 & 1200.12 & 1412.61 & 4525.15 & 23.94 & 119.71 \\ \hline \end{tabular} Notes: The meanings of the TCES and SCES are shown in Table 1. CL: cultivated land, FL: forest land, OL: orchard land, GL: grassland, WB: water body, BL: built-up land, and UL: unutilized land. Sources: Drawings from this study.  
\end{table}
Table 2: ESV equivalent per unit area in Putian City (unit: CNY/hm\({}^{2}\)-a).
## 3 Countermeasures
### Intrusion Detection-Based Countermeasures  
Researchers perform several solutions and evaluations to formulate mechanisms related to threat detection schemes in 6G networks. In [88], the authors presented a simplified threat matrix to define risks posed in the emerging 6G era. The threat matrix acts as a threat library for efficient detection and categorization. However, the proposed scheme requires common agreement to maintain the threat library in a distributed heterogenous network, otherwise this scheme will surface several compatibility issues. Likewise, the authors in [89] suggested a Non-Orthogonal Multiple Access (NOMA) sparse signatures matrix for the 6G network that can act as a threat detection system. However, the proposed solution covers only the wireless domain; therefore, coordination with the upper layer may become complex in multi-tier heterogeneous networks. Moreover, this solution is probable to cause compatibility issues with non-NOMA IoTs. Similarly, In [90], the authors proposed an unconventional security scheme for detecting and identifying malicious maneuvers of flooding attacks in the 6G network. The solution is based on a routing scheme to improve Low Energy Adaptive Clustering Hierarchy (LEACH) protocol performance with minimum resource utilization. The scheme detects the flow pattern to identify the least data transmissions to the flooding attacker. However, the research has focused only on flooding attacks, and further research is required to cover all possible attacks through the same approach. In [91], the authors presented a Channel State Information (CSI)-based authentication scheme for 6G security; the same can be employed for intrusion detection in a cyber-secure 6G network. However, the solution is suitable for wireless domain only. The scheme will cause backward compatibility issues and processing overheads. Moreover, the solution is susceptible to low performance due to degradation in interference/jamming. The authors in [92] present a short survey for using AI and ML to establish a secure intrusion detection system capable for use in a 6G-enabled network domain in intelligent and secure vehicular communications. The Deep Learning (DL) technique is widely researched for secure network domains with intrusion detection capabilities [93; 94]. Moreover, AI/ML-enabled authentication and privacy-preserving solutions are increasingly suggested for
# A Spectrum Correction Method Based on Optimizing Turbulence Intensity
###### Abstract  
Based on the classical spectral representation method of simulating turbulent wind speed fluctuation, a harmonic superposition algorithm was introduced in detail to calculate the homogeneous turbulence wind field simulation in space. From the view of the validity of the numerical simulation results in MATLAB and the simulation efficiency, this paper discussed the reason for the bias existing between three types of turbulence intensity involved in the whole simulation process: simulated turbulence intensity, setting reference turbulence intensity, and theoretical turbulence intensity. Therefore, a novel spectral correction method of a standard deviation compensation coefficient was proposed. The simulation verification of the correction method was carried out based on the Kaimal spectrum recommended by IEC61400-1 by simulating the uniform turbulent wind field in one-dimensional space at the height of the hub of a 15 MW wind turbine and in two-dimensional space in the rotor swept area. The results showed that the spectral correction method proposed in this paper can effectively optimize the turbulence intensity of the simulated wind field, generate more effective simulation points, and significantly improve the simulation efficiency.  
uniform wind field simulation; turbulence intensity; deviation of standard deviation; spectral representation +
Footnote †: journal: Applied sciences