esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Normally a small value is taken for the system noise covariance matrix \(\mathbf{Q}\)[3], thus \(\mathbf{Q}\) will have large error in a highly dynamic situation with large line-of-sight jerk, and a traditional Kalman-PLL will result in divergence. The inertial velocity and acceleration measurements could help to correct the relevant values of the Kalman states to a great extent, but if there is large offset in the aid information, Kalman-PLL will result in filter divergence. Hence, it is necessary to consider the influence of Doppler shift rate variation. Doppler shift rate value is relative to line-of-sight acceleration, so line-of-sight jerk can be considered as the coefficient of Kalman states or noise. Considering that increasing Kalman states will accordingly increase the computation burden and large jerk normally has short duration (for jerk 30 g/s, only 2 s are needed to reach an acceleration of 60 g), this paper takes line-of-sight jerk as the process noise. Then it is feasible to consider a new inertial aid method, using the line-of sight jerk as aid information to adjust the noise coefficient of the Doppler shift rate state in real time. Line-of-sight jerk can be acquired through time difference of line-of-sight acceleration calculated by inertial measurements and Compass ephemeris. The time difference method can eliminate the influence of acceleration offset or drift induced by INS bias, but the line-of-sight jerk acquired by the time differentiator will have a large noise. The nonlinear tracking differentiator presented by [PERSON] [16] in 1994 can implement the difference of any signal, and it has great filtering capacity. Nonlinear tracking differentiator has been efficiently applied to various fields, such as satellite navigation [17], magnetic suspension [18] and signal processing [19]. This paper refers to this method and its improved versions [20] for achieving smoothed line-of-sight jerk through the inertial acceleration with noise, and efficiently aiding high dynamic Compass signal tracking.
# An Analysis of MPTCP Congestion Control
## 7 MPTCP Congestion Control
### Analysing How Coupled CC Algorithms Perform
Figure 9: LIA—Competing Window Growth—Same RTT. and actively used in TCP due to its simplicity [39]. As a result, we did not simulate the wVegas algorithm. CUBIC is the current default TCP algorithm in Linux and outperforms NewReno in high bandwidth and long distance networks [40]. Given the current equation output, we would expect MPTCP subflows would perform even worse when competing with CUBIC CC. In this context, it should be noted that the estimation of the available capacity of the paths and their combination is simpler in this simulation than in the Internet where issues such as packet loss, queues and delay exist. The congestion window is the allowable amount of data to be transmitted in an RTT, which varies with the interval of ACKs. When subflows with different conditions share the same congestion window, they experience events that increase or decrease the window size with different intervals. Correlating different RTTs and loss events is difficult since not all flows sharing a link would necessarily experience loss during the same congestion episode. Coupling the _cvm_ can potentially address the fairness issue (flow level) where MPTCP and TCP connections share the same bottleneck. However, the throughput achieved by a subflow depends on the throughput of all the other subflows. This affects the fairness of CC to MPTCP itself (network level), especially when packets are sent via diverse paths. Coupling the _cvm_ could negatively impact protocol resource utilisation. The balance between how to allocate data to the disjoint subflows is difficult to achieve. Favouring a flow with higher bandwidth or reduced RTT could result in underutilised bandwidth if the chosen path is competing with other flows and the alternate - slower - path has no competition. Alternatively, favouring the slower path could result in low aggressiveness on the competitive path, leading to a reduced share of bandwidth. Ideally, MPTCP needs to understand when paths are disjoint to apply uncoupled CC in these cases, and utilise coupled CC only where paths share a bottleneck.
# Polarization Sensitive Imaging with Qubits
###### Abstract  
We compare reconstructed quantum state images of a birefringent sample using direct quantum state tomography and inverse numerical optimization technique. Qubits are used to characterize birefringence in a flat transparent plastic sample by means of polarization sensitive measurement using density matrices of two-level quantum entangled photons. Pairs of entangled photons are generated in a type-II nonlinear crystal. About half of the generated photons interact with a birefringent sample, and coincidence counts are recorded. Coincidence rates of entangled photons are measured for a set of sixteen polarization states. Tomographic and inverse numerical techniques are used to reconstruct the density matrix, the degree of entanglement, and concurrence for each pixel of the investigated sample. An inverse numerical optimization technique is used to obtain a density matrix from measured coincidence counts with the maximum probability. Presented results highlight the experimental noise reduction, greater density matrix estimation, and overall image enhancement. The outcome of the entanglement distillation through projective measurements is a superposition of Bell states with different amplitudes. These changes are used to characterize the birefringence of a 3M tape. Well-defined concurrence and entanglement images of the birefringence are presented. Our results show that inverse numerical techniques improve overall image quality and detail resolution. The technique described in this work has many potential applications.  
Keywords:quantum state tomography; quantum imaging; quantum entanglement; spontaneous parametric down-conversion +
Footnote †: journal: Applied
# Rural Healthcare IoT Architecture Based on Low-Energy LoRa
## 4 System Architecture
### LoRa and LoRaWAN  
LoRa is a proprietary radio modulation technology licensed by Semtech Corporation. LoRa uses unlicensed ISM bands: 868 MHz in Europe, 915 MHz in North America, and 433 MHz in Asia [5]. The Bidirectional communication is done using Chirp Spread Spectrum (CSS) modulation, or as defined by [21] a Frequency Shift Chirp Modulation (FSCM), where each symbol is sent using a wide frequency band. The advertised communication range of LoRa is more than 15 km for suburban environments [22]. The long-range and low-power nature of LoRa makes it a likely candidate for smart sensing technology for health monitoring and environment monitoring [23].  
There are three classes of end-devices (Class A, Class B, and Class C) which differ in the timings of the receive windows [24]. Class A has receiving windows after the send windows. Class B has received windows at timed intervals. Class C has continuous listening.  
There are five configuration parameters for LoRa radio: Transmission Power (TP), Carrier Frequency (CF), SF, Bandwidth (BW) and Coding Rate (CR) [22]. The rate at which the data is transmitted depends on three physical layers parameters: SF, BW, CR [24]. SF indicated how the signal is distributed in time. The more time it takes to send the packet, the lower the minimum RSSI. A higher coding rate increases redundant bits, thus making the transmission more reliable. However, it increases time and energy consumption. A higher bandwidth reduces the transmission time but at the cost of lowering the noise floor.  
On top of the physical layer, the MAC layer protocol defines the topology of the network. An analysis for the creation of ad-hoc MAC layers is presented in [25]. A synchronous-based, medium access control (MAC) protocol, MAC on Time (MoT) was studied with the potential to have reduced energy footprint [26]. An alternative MAC layer protocol named LoRaBlink was discussed in [27]. However, in this paper, we review only LoRaWAN, which uses a star topology and is most often used in LoRa deployments. The LoRa modulation is proprietary; however, the LoRaWAN is an open standard being developed by the LoRa Alliance. It is designed mainly for sensor networks, where sensors send data to the server infrequently (one transmission per hour or even days) [23]. LoRaWAN is based on the ALOHA protocol. The end devices communicate directly to an always-on gateway when they have data ready to send [28]. The downsides of this star topology include: cost of the base station(s); the need for more frequent battery replacement for remote nodes; and need for high SF and a higher chance of collisions for remote nodes [20].  
The analysis conducted in [29] shows that the long-range transmissions of LoRa are vulnerable to multiple security attacks. The possible attacks include compromising nodes to obtain network keys, jamming, replay, and wormhole attacks. The security measures in the LoRaWAN protocol are left to be implemented by developers and manufacturers, thus providing room for bad implementation in some devices to introduce risk for the network.
## 3 Results and Discussion
### Profiling of VOCs and Their Distribution
\begin{table}
\begin{tabular}{l l c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**Compound**} & \multirow{2}{*}{**RI 1**} & \multirow{2}{*}{**Classification**} & \multicolumn{4}{c}{**DAS 2**} \\ \cline{5-6}  & & & & **30** & **60** & **70** & **80** \\ \hline
1 & (E)-2-Hexanal & 857 & Aldehyde & 1.52 \(\pm\) 0.26 a & 0.16 \(\pm\) 0.02 b & 0.23 \(\pm\) 0.06 b & 0.19 \(\pm\) 0.04 b \\
2 & 1-Octen-3-ol & 981 & Fatty alcohol & 0.13 \(\pm\) 0.03 b & 0.27 \(\pm\) 0.02 ab & 0.23 \(\pm\) 0.01 ab & 0.32 \(\pm\) 0.05 a \\
3 & Limonene & 1031 & Monoterpene & 0.50 \(\pm\) 0.07 ab & 1.10 \(\pm\) 0.39 a & 0.16 \(\pm\) 0.01 b & 0.23 \(\pm\) 0.03 ab \\
4 & 4-Methyl benzaldehyde & 1079 & Aldehydes & 0.51 \(\pm\) 0.04 a & 0.44 \(\pm\) 0.11 a & 0.02 \(\pm\) 0.00 b & 0.03 \(\pm\) 0.01 b \\
5 & Linalool & 1101 & Terpene alcohol & ND 2 & 0.10 \(\pm\) 0.00 ab & 0.15 \(\pm\) 0.04 a & 0.02 \(\pm\) 0.00 b \\
6 & Isopulegone & 1179 & Monoterpene & 0.04 \(\pm\) 0.00 a & 0.04 \(\pm\) 0.01 a & 0.02 \(\pm\) 0.00 a & 0.03 \(\pm\) 0.00 a \\
7 & Estragole & 1198 & Phenylpropene & 20.25 \(\pm\) 7.88 a & 234.33 \(\pm\) 11.97 a & 69.99 \(\pm\) 4.21 b & 92.05 \(\pm\) 6.40 b \\
8 & (Z)-Neral & 1243 & Monoterpene & ND & 0.84 \(\pm\) 0.11 a & 0.16 \(\pm\) 0.04 b & 0.16 \(\pm\) 0.01 b \\
9 & p-Chavicol & 1257 & Phenylpropene & 0.04 \(\pm\) 0.00 a & 0.02 \(\pm\) 0.00 b & ND & ND \\
10 & Gerani & 1271 & Monoterpene & ND & 1.46 \(\pm\) 0.19 a & 0.29 \(\pm\) 0.09 b & 0.26 \(\pm\) 0.02 b \\
11 & Anethole & 1289 & Phenylpropene & 1.14 \(\pm\) 0.31 b & 2.20 \(\pm\) 0.04 a & 0.20 \(\pm\) 0.02 c & 0.31 \(\pm\) 0.04 c \\
12 & Methyleugenol & 1408 & Phenylpropene & 0.04 \(\pm\) 0.01 b & 0.04 \(\pm\) 0.00 b & 0.09 \(\pm\) 0.01 a & 0.06 \(\pm\) 0.01 ab \\
13 & Caryophyllene & 1423 & Sesquiterpene & 0.42 \(\pm\) 0.05 ab & 1.07 \(\pm\) 0.20 a & 0.10 \(\pm\) 0.03 b & 0.48 \(\pm\) 0.27 ab \\
14 & (E)-\(\beta\)-Famesene & 1459 & Sesquiterpene & 0.07 \(\pm\) 0.04 a & ND & ND & ND \\
15 & 8-Caulienne & 1527 & Sesquiterpene & 0.12 \(\pm\) 0.01 ab & 0.23 \(\pm\) 0.04 a & 0.05 \(\pm\) 0.01 b & 0.10 \(\pm\) 0.04 b \\
16 & Spathuelon & 1579 & Terpene alcohol & 0.07 \(\pm\) 0.00 a & 0.07 \(\pm\) 0.01 a & ND & ND \\ \hline \hline \end{tabular}  
* Values were expressed as mean \(\pm\) standard error and experiments were conducted with repetitive analyses. An ANOVA test was performed with [PERSON]’s multiple-range test using the SPSS program and the result was expressed as different letters (a–c). 1 RI: retention index; 2 ND: not detected.  
\end{table} 
Table 3: VOCs’ profiling change (ng/mg) of AR following the DAS.
## 5 Conclusions  
Protective coatings have a significant role in metallic cultural heritage preservation. The evaluation of layer features, such as thickness estimation, fractures or interstice identification, and the detection of chemical changes, contributes to the monitoring of their performance. The three techniques tested in this work are not interchangeable and each one showed specific advantages and disadvantages, such as the possibility to identify detailed layer features or the identification of chemical composition. The results of the two optical techniques (OCT and CRM) are in reasonable agreement and revealed the layers' inhomogeneity; their image and graphical outputs are easy and fast to interpret but require corrections considering the refractive index of the polymer. In contrast, CRM, as used in this study, is not portable and the object's size and shape may therefore limit its employment. However, the recent advances in portable Raman instrumentation may allow the in situ analysis of coatings using the confocal modality.  
The EC measurements agree with the other two techniques when homogeneous layers are tested; however, the main issue with ECs is that the results are averaged over a relatively big area, thus hampering the detectability of microscale inhomogeneities and defects in the polymer coatings. Additionally, corrosion products and deposits over the surface can interfere with thickness estimation.  
All in all, compared to electrochemical methods, the optical techniques allow for more features from the polymeric layers to be registered yet require specialized instrumentation. In the future, this issue might be solved by more user-friendly systems being made available to conservators.  
Conceptualization, R.F. and J.S.; methodology, A.D.F., R.F. and J.S.; formal analysis, D.Q.B., A.D.F., D.P., A.C., S.P., R.F. and J.S.; investigation, D.Q.B. and D.P.; data curation, D.Q.B., R.F. and J.S.; writing--original draft preparation, D.Q.B. and J.S.; writing--review and editing, D.Q.B., A.D.F., D.P., A.C., S.P., R.F. and J.S.; supervision, R.F. and J.S.; project administration, R.F. and J.S.; funding acquisition, R.F. and J.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Regione Toscana (FOR FSE 2014-2020, \"Giovanisi\", Intervention Program \"CNR4C\", RS4 Art and SuperTech3D projects, CUP B15J19001040004).  
Not applicable.  
The data presented in this study are available on reasonable request from the corresponding author.  
The authors declare no conflict of interest.
## 2 Materials and Methods  
### Materials  
Surface sediments (5 cm in depth) were collected from the Songhua River in Northeastern China. A part of the sediments was freeze-dried and ground to pass through a 0.15 mm sieve for BC extraction. The extraction procedure of BC from sediments was referred by [PERSON] et al. [20]. In brief, the procedure was as follows: (1) added 15 mL of 3 mol\(\cdot\)L\({}^{-1}\) HCl to 3 g sediments, reacted for 24 h to remove carbonates; (2) added 20 mL of mixed solution of 10 mol\(\cdot\)L\({}^{-1}\) HF and 1 mol\(\cdot\)L\({}^{-1}\) HCl, reacted for 12 h to remove silicates; (3) added 15 mL of 10 mol\(\cdot\)L\({}^{-1}\) HCl and reacted for 24 h to remove CaF\({}_{2}\); (4) added 20 mL of mixed solution of 0.1 mol\(\cdot\)L\({}^{-1}\) K\({}_{2}\)Cr\({}_{2}\)O\({}_{7}\) and 2 mol\(\cdot\)L\({}^{-1}\) H\({}_{2}\)SO\({}_{4}\), reacted at 55 \({}^{\circ}\)C for 60 h to remove the active organic carbon; (5) dried at 60 \({}^{\circ}\)C in a drying oven to attain constant weight. The obtained residue comprised the BC samples, which was recorded as SC. The extracted samples were placed in a crucible and fired in a muffle furnace at 375 \({}^{\circ}\)C for 4 h. The BC contents recorded as \(f_{\text{CM}}\) were measured through determining the total organic carbon (TOC) contents of the residue.  
Rice straws were collected from the riverine farmland of the Songhua River. The BC preparation from the rice straws was referred by [PERSON] et al. [21]. The burning temperatures were 450 and 850 \({}^{\circ}\)C, and the BC produced under the two temperatures were recorded as BC450 and BC850, respectively. AC was purchased from Guangfu Technology Co. Ltd. (Tianjin, China, 2010). Lindane (99% purity) and \(p\),\(p\)'-DDE (98% purity) were purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany, 2010). The basic physicochemical properties of lindane and \(p\),\(p\)'-DDE are listed in Table 1. Methanol was used in the preparation of standards of lindane and \(p\),\(p\)'-DDE. All of the other reagents and chemicals used were of analytical grade and purchased from Sinopharm Chemical Reagent Co., Ltd., Shanghai, China,2010. The water used in the experiment was Milli-Q water. Chromosulfuric acid was used to clean the laboratory glassware.  
The specific surface area (SSA), pore size, and TOC contents of the sediments and the four CMs were characterized by SSA and pore size distribution analyzer (NOVA-2000E, Quantachrome Instruments, Boynton Beach, FL, USA, 2005), and TOC analyzer (TOC-VCPH, Shimadzu, Tokyo, Japan, 2006), respectively, as described in our previous studies [14; 22]. The values of SSA were calculated using the BET multipoint method.
# Impact of Visual Kinesthetic Illusions on Reciprocal Inhibition and Motor Function
## 4 Discussion
### Motor Function  
The results of experiment 2 indicated that enhancing D1 inhibition through the visual kinesthetic illusion improves motor function, particularly to reduce the activity of the antagonist's muscles. This study showed that the visual kinesthetic illusion related to RPM influenced spinal and motor functions.  
In the EMD, correlations between the change in muscle activity and the change in the enhancement of D1 inhibition were observed. This implies that the visual kinesthetic illusion enhances RI, reducing the excessive co-contraction of the antagonist muscles and enabling smoother joint movement. RI aids in achieving fluid joint movement by inhibiting the stretch reflex of the antagonist muscle at the start of movement [9]. A previous study examined whether ankle dorsiflexion function improved after RPM and revealed that enhancing RI favored TA muscle activity [13]; these findings were consistent with those of the present study. As a factor of this improvement, RI would inhibit the stretch reflex on antagonist muscle. The spinal cord excitability of Sol begins to decline as TA muscle activity occurs on dorsiflexion. Conversely, Sol's spinal cord excitability reportedly increases approximately 60 ms after TA muscle activity begins [38]. Sol spinal cord excitability enhancement is believed to result from a stretch reflex in the triceps surae. The present study suggested that as the RI increased, the stretch reflex of the antagonist muscle Sol diminished at beginning joint movement, causing a further reduction in Sol muscle activity.  
Sol significantly dominated muscle activity in PF due to the visual kinesthetic illusion. This finding indicates that, similar to dorsiflexion EMD, the visual kinesthetic illusion of RPM largely influences muscle activation during plantar flexion, making agonist muscles predominant. This phenomenon may stem from enhanced RI adjustment functions caused by the visual kinesthetic illusion. During plantar flexion, the RI from TA to Sol decreases due to descending inputs from supraspinal control on RI interneurons [9]. Consequently, plantar flexion increases the excitability of alpha motor neurons in the Sol, leading to increased activation of the Sol muscle. The current research assessed the RI from the TA to the Sol. However, it is important to note that RI also occurs from the Sol to the TA in vivo, with evidence suggesting that this inhibition is more pronounced than that from the TA to the Sol [39]. The strong inhibition from Sol to TA is thought to prevent hindrance in the muscle activity of the triceps surae, an antigravity muscle. The present study indicated that the visual kinesthetic illusion enhanced the modulatory function of RI and increased alpha motor neuron excitability in the Sol during PF. Moreover, this modulatory function may be more pronounced in the Sol, which is more susceptible to the effects of RI.
# Real-Time Tomography of Gas-Jets with a Wollaston Interferometer
## 2 The Single Beam Wollaston Interferometer Setup
### Experimental Setup for Gas Density Measurements
#### 2.3.1 Wollaston Interferometer  
The interferometer is depicted schematically in Figures 4 and 5. A linearly-polarized continuous He:Ne laser with a wavelength \(\lambda_{I}=632.8\) nm and an output power of 21 mW is used as a coherent light source for the interferometer. To prevent up-streaming air due to the heat of the laser from causing unwanted phase shifts, the laser is placed outside of the black cardboard box that contains the interferometer. The box reduces noise as it minimizes the airflow in the whole experiment, as well as external photons hitting the charge-coupled device (CCD) sensor. The initial laser diameter is 0.7 mm (\(1/e^{2}\) width). The telescope (20\(\times\)) attached to the laser provides a beam with a diameter of 14 mm, which is suitable to backlight a gas jet with a diameter of a few millimeters. The noise of the acquired images is expected to be lowest in the center of the beam due to the higher intensity of the laser in that region. The He:Ne laser enters and leaves the vacuum chamber through two windows, and the gas  
Figure 3: Estimation of the on-axis density \(\rho\) for different backing pressures. This model is based on the ideal gas law, i.e., independent of the gas species.  
Figure 2: Sketch of a conical nozzle. The quantities for the solenoid valve are \(d=500\) μm, \(L=250\) μm and \(\theta=45^{\circ}\).  
flows in perpendicular direction, downwards towards the vacuum pump. The Parker solenoid valve (Figure 6A) is operated at 0.5-3 Hz and with opening times \(T\leq 12\) ms to reduce the gas load on the pump. The Wollaston prism is placed between two crossed polarizers, such that the interference fringes are parallel to the jet. The interference pattern is captured with a CCD camera and an f = 200 mm camera lens. The minimal exposure time of the camera is 18 us. The exposure time is set to 30 us in order to obtain an image with good contrast without reaching saturation of the sensor.  
Figure 6B shows a typical interference pattern of the undisturbed gas jet. The change of the fringes due to the gas distribution is clearly observable when the Parker solenoid valve is operated at 35 bar backing pressure.  
Figure 4: Sketch of the interferometric setup using a Wollaston prism. The dashed line represents the breadboard with the shielding box. The Wollaston prism is mounted on a linear stage, such that the parameter \(b\) and therefore the fringe spacing \(S\) can be changed (see Section 2). A Nikon imaging lens is attached to the CCD camera.  
Figure 5: Experimental setup for Wollaston interferometry. The expanded beam passes through the gas jet, the first polarizer, the lens, the Wollaston prism and the second polarizer. The lens images the gas jet onto the CCD by a 200-mm imaging lens (AF Micro–Nikkor 200 mm f/4D IF–ED).