esa-sceva/satcom-chunk-collection huggingface dataset:
# Effectiveness of High-Intensity Therapy in Rehabilitation of Parkinson's Disease Patients
## 4 Results  
To evaluate the effects of high-intensity training on patients with [PERSON]'s disease, all statistical analyses were conducted using R software (R 4.5.0) and SPSS software (30.0.0). The study population was divided into four intervention groups, each receiving a specific type of training: Exergame, Cycling, Agility, and Robot (Cmill). These interventions aimed to assess improvements in motor function, balance, postural stability, and overall quality of life. A comprehensive statistical approach was applied, utilizing various analytical methods. T-tests were used to compare pre- and post-intervention outcomes within each group. [PERSON]'s effect size was used to determine the magnitude of observed differences. One-way ANOVA was used to evaluate differences between intervention groups. Tukey-HSD post-hoc tests were used for pairwise group comparisons. The Shapiro-Wilk normality test was used to assess data distribution. The Wilcoxon test for non-parametric comparisons where normality assumptions were violated. Correlation analysis was used to explore associations between disease severity, functional scores, and quality of life indicators. Borg Scale Analysis was used to measure perceived exertion during training interventions. This structured data analysis approach provided robust insights into the therapeutic efficacy of each intervention, allowing for a detailed evaluation of their impact on functional performance and quality of life in patients with Parkinson's disease. To enhance the interpretability of results, 95% confidence intervals (CIs) were calculated and reported for all key outcomes, including gait speed, balance (Berg), functional independence (FIM), posturography sway metrics, and perceived exertion (Borg RPE scores).
# LoRa Mobile-To-Base-Station Channel Characterization in the Antarctic
## 1 Introduction
Another field test [6] compares LoRa specifications to other standards operating in the sub-GHz frequency bands, such as Sigfox [7] and DASH7 [8]. Ref. [9] describes outdoor and indoor lab measurements to determine Doppler robustness, scalability, and coverage. Interestingly, the latter paper obtains reasonable performance up to 30 km range over water, which is comparable to the range observed in our measurements over snow and ice. Ref. [10] evaluates interference when performing LoRa transmissions in the 868 MHz band. Crowded environments suffer from high interference probabilities, resulting in performance degradation. LoRa scalability tests--also based on interference measurements--are analyzed more thoroughly in [11]. The paper is further organized as follows. The equipment used for the measurements is documented in Section 2, followed by the measurement results in Section 3. The discussion and conclusions follow in Sections 4 and 5.
## 3 Results and Discussion of RSM Experiments
### Plackett-Burman Design and Significance Analysis
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Final Number**} & \multicolumn{5}{c}{**Test Parameters**} & \multicolumn{5}{c}{**Stacking Angle(\({}^{\circ}\))**} \\ \cline{2-7}  & **A** & **B** & **C** & **D** & **E** & **F** & **G** & **Angle(\({}^{\circ}\))** \\ \hline
1 & 1 & 1 & 1 & \(-1\) & \(-1\) & \(-1\) & 1 & 47.62 \\ \hline
2 & \(-1\) & \(-1\) & \(-1\) & \(-1\) & \(-1\) & \(-1\) & 38.93 \\ \hline
3 & \(-1\) & 1 & \(-1\) & \(1\) & \(1\) & \(-1\) & 1 & 44.74 \\ \hline
4 & 1 & 1 & \(-1\) & \(-1\) & \(-1\) & 1 & \(-1\) & 35.38 \\ \hline
5 & 1 & 1 & \(-1\) & \(1\) & \(1\) & \(1\) & \(-1\) & 40.58 \\ \hline
6 & 1 & \(-1\) & \(-1\) & \(-1\) & \(1\) & \(-1\) & 1 & 44.90 \\ \hline
7 & \(-1\) & 1 & 1 & \(1\) & \(-1\) & \(-1\) & \(-1\) & 40.71 \\ \hline
8 & 1 & \(-1\) & 1 & \(1\) & \(-1\) & \(1\) & 1 & 49.25 \\ \hline
9 & \(-1\) & 1 & 1 & \(-1\) & \(1\) & \(1\) & 1 & 52.18 \\ \hline
10 & 1 & \(-1\) & 1 & 1 & \(1\) & \(-1\) & \(-1\) & 46.35 \\ \hline
11 & \(-1\) & \(-1\) & \(-1\) & \(1\) & \(-1\) & 1 & 1 & 38.86 \\ \hline
12 & \(-1\) & \(-1\) & \(1\) & \(-1\) & \(1\) & \(1\) & \(-1\) & 44.51 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Plackett–Burman test protocol and results. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & **Sum of** & **Degrees of Freedom** & **Mean Square** & **F-Value** & \(p\)**-Value** & **Significance Ranking** \\ \hline Models & 241.21 & 7 & 34.64 & 6.52 & 0.0446 \({}^{*}\) \\ A & 1.44 & 1 & 1.44 & 0.2716 & 0.6298 & 4 \\ B & 0.2107 & 1 & 0.2107 & 0.0399 & 0.8851 & 8 \\ C & 115.51 & 1 & 115.51 & 21.86 & 0.0095 \({}^{**}\) & 1 \\ D & 0.7651 & 1 & 0.7651 & 0.1448 & 0.7229 & 5 \\ E & 42.23 & 1 & 42.23 & 7.99 & 0.0475 \({}^{*}\) & 3 \\ F & 0.5167 & 1 & 0.5167 & 0.0978 & 0.7701 & 6 \\ G & 80.55 & 1 & 80.55 & 15.25 & 0.0175 \({}^{*}\) & 2 \\ \hline \hline \end{tabular}  
* Notes: ** indicates highly significant effects (\(p<0.01\)), \({}^{*}\) denotes significant effects (\(p<0.05\)).  
\end{table} 
Table 7: Significance analysis of the Plackett–Burman test. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Test Parameters**} & **Low Level (\(-1\))** & **High Level (\(+1\))** \\ \hline Straw–straw coefficient of restitution A & 0.25 & 0.33 \\ Straw–straw static friction coefficient B & 0.46 & 0.62 \\ Straw–straw rolling friction coefficient C & 0.14 & 0.29 \\ Straw–steel coefficient of restitution D & 0.41 & 0.54 \\ Straw–steel static friction coefficient E & 0.43 & 0.53 \\ Straw–steel rolling friction coefficient F & 0.11 & 0.27 \\ JKR surface energy (\(\cdot\)m\({}^{2}\)) G & 0.01 & 0.11 \\ \hline \end{tabular}  
* Notes: A–G are the codes for each parameter, and in the following text, the parameters will be replaced by their codes.  
\end{table} 
Table 5: Table of values for the screening parameters.
## 4 Vector Harmonics of Floquet--Electromagnetic Field Representation in the Plane (\(x\),\(y\))  
The electromagnetic field at any point of the previously defined multi-layer antenna structure can be decomposed into two independent field components distinguished by their polarization with respect to the antenna plane normal, i.e., TE field with an electric field vector perpendicular to the \(z\) direction: \(\underline{E}(x,y,z)=(\underline{E}_{t},E_{z})\) and the TM field with the magnetic field vector perpendicular to the \(z\) direction: \(\underline{H}(x,y,z)=(\underline{H}_{t},H_{z})\). As part of this division, we will define the distributions of the transverse electric field into vector Floquet harmonics, characterizing the mode structure of the electromagnetic field of an unlimited, multi-layer periodic structure. It should be noted that with the assumed losslessness of the upper (incident) medium, the above-analyzed tangents (to the (\(x\),\(y\)) plane) coordinates of the propagation vector corresponding to the incident field harmonics remain real in every element of the antenna structure, both lossy and lossless.
## 1 Introduction
Despite the frequent use of biostimulation in the field of bioremediation, the use of the biostimulation technique for enabling MICP is more limited [5; 27; 28; 29; 30; 31; 32]. Biostimulated MICP in desert soils is more challenging than in most soils as the total carbon content is low [33], and the bacterial population is considerably smaller. For example, in coastal sands from southern Israel (31.61\({}^{\circ}\)N, 34.50\({}^{\circ}\)E), the in situ bacterial population was found to be in the order of 10\({}^{4}\) cells/g [31], three to four orders of magnitude lower than in semiarid soils [34]. For this reason, MICP in low-carbon soils were typically attempted via bioaugmentation [35; 36]. In this paper, we present the results of a research aimed to study the biostimulation potential in desert soil from the northern Negev Desert, Israel. The results reported here are part of an ongoing research project aimed to develop a MICP-based technique for the mitigation of topsoil erosion in arid environments and is planned to be followed by laboratory and field experiments. We envision different applications for MICP-based topsoil stabilization, such as the suppression of dust emission from vehicles in construction sites and open-pit mines, improving the efficiency of solar energy facilities and the mitigation of erosion by flush flood, among others. Biostimulation for ureolytic MICP was confirmed at laboratory conditions by incubating soil samples in urea and enrichment media and monitoring urea depletion and pH evolution within a few days. Precipitation experiments using the indigenous, biostimulated bacteria demonstrated that calcite precipitation could be readily induced. Altogether, we report that urea-hydrolyzing bacteria are naturally present in the topsoil sampled from the northern Negev Desert and that these bacteria can be effectively stimulated to induce calcite precipitation.
## 5 Discussion
### Operational Services
Finally, the comparison of pre-fire and post-fire conditions can be used to monitor ecosystem responses through the restoration of vegetation and to account for environmental losses, such as habitat loss or changes in ecosystem services. Since no in situ information related to pre-fire conditions can be collected after the wildfires take place, the development of procedures to generate land cover maps and habitat maps using exclusively remote sensing data and ancillary information is recommended. The designed procedure can be further improved in order to be implemented as downstreaming operational service that, taking advantages from Sentinel-2 medium-high spatial resolution and revisit time, could support knowledge about wildfire occurrences with medium-high resolution maps of burned areas.
# Photonics-Based Microwave Image-Reject Mixer
## 5 Discussions and Conclusions  
In conclusion, we reviewed recent advances in photonics-based microwave IRMs. Two typical methods to realize the photonic IRM, i.e., pre-filtering method and phase cancellation method, were introduced. Application of the photonics-based microwave IRM in electronic warfare, radar and satellite systems, was also described.  
Currently, photonics-based microwave IRMs are mainly realized using discrete components, so their performance will be affected by environmental vibration, leading to serious problems for practical applications [46]. For example, the lengths of the two paths constructed by discrete components are difficult to keep stable, introducing amplitude and/or phase variation of the signals transmitted through them. To realize compact photonics-based microwave IRMs with high stability, integrated microwave photonic technology can be applied [47; 48; 49; 50]. Integrated components including modulators, 90\({}^{\circ}\) optical hybrids, PDs [47; 48; 49], optical oscillators and circulators [50], integrated sub-systems (such as lasers) [51], microwave photonic spectrum shapers [52], phase shifters [53], delay lines [54], filters [55] and processors [56; 57; 58; 59] have been widely investigated, and great progress has been made. In addition, incorporation of new materials, such as graphene [60], to the field of integrated microwave photonics, brings new advantages, such as  
Figure 10: Schematic diagram of the RF front-end based on microwave photonics. OFC: optical frequency comb; MZM: Mach-Zehnder modulator; LPF: low pass filter; ADC: analog to digital conversion [35].  
fast tuning speed, high nonlinearity and so on. Therefore, integrating photonics-based microwave IRM in a chip is possible, which is expected to achieve better performance for practical applications.  
This work is supported by the Natural Science Foundation of Jiangsu Province (BK20160082), the Jiangsu Provincial Program for High-level Talents in Six Areas (DZXX-030), and the Fundamental Research Funds for Central Universities.  
This article was jointly written by and proof-read by all authors. All authors contributed in various degrees to the review.  
The authors declare no conflict of interest.
## 2 NOMA System Model  
### System Design  
As shown in Figure 1, an indoor NOMA-VLC system uses the SIC technique in both uplink and downlink data detection, for which the interference coefficient is precisely estimated. In the indoor environment, with the uplink NOMA system in the lower left corner, User 1 and User 2 use NOMA power allocation coding to transmit signals to the receiver. The receiver uses SIC detection technology after photoelectric detection to sort users according to their distance to the transmitter and performs interference cancellation detection. In the lower right corner is the downlink NOMA-VLC system, where the transmitter adjusts the transmitting power in the electrical domain according to the location of the receiving users, such that different users receive different optical powers. The SIC detection method presented in this paper is suitable for signal detection of indoor uplink and downlink data transmission scenarios. The difference is that the uplink NOMA only requires the base station to have an SIC receiver, while the downlink NOMA requires each user to have an SIC receiver.
## 3 Results and Discussion
### SERS Applications
#### 3.2.1 Methylene Blue SERS Detection with Cyclodextrin-Capped NPs  
Methylene blue (MB) is a molecule that is quite often used in SERS due to its high Raman cross-section and its cationic nature, being able to attach to anionic plasmonic NPs. The SERS spectrum of MB is strongly dependent on its orientation based on the Raman selection rules [44]. The usual SERS spectrum of MB is dominated by the vibrations recorded at 450 cm\({}^{-1}\), 504 cm\({}^{-1}\), 774 cm\({}^{-1}\), 1397 cm\({}^{-1}\), and 1621 cm\({}^{-1}\). In a previous paper [45], we reported for the first time that, for polyethylene glycol-mediated synthesis of AuNPs, new intense vibrational bands are detectable in the MB SERS spectrum. We also observed that these new vibration bands can also be detected in the MB SERS for both Au and Ag colloids in an alkaline environment. We provide, in Figure 9a, the MB SERS spectra obtained on citrate-reduced Au colloids both at a neutral pH and after adding 50 \(\mu\)L of NaOH to 0.5 mL of colloid solution. One can notice an increase in the intensity of the SERS spectrum but also the appearance of new intense vibrations at 540 cm\({}^{-1}\), 604 cm\({}^{-1}\), 885 cm\({}^{-1}\), 1033 cm\({}^{-1}\), 1121 cm\({}^{-1}\), 1325 cm\({}^{-1}\), and the shift of the band at 1397 cm\({}^{-1}\) to 1400 cm\({}^{-1}\), which might be all explained by a change in the geometry of the molecule relative to the metallic surface.  
Figure 8: DLS data for AuNPs synthesized using \(\beta\)-CD as a reducing and capping agent in **(a)** microwaves, **(b)** ultrasound, and **(c)** at room temperature.  
In the case of AuNPs synthesized according to the present study in alkaline conditions with \(\beta\)-CD (Figure 9b), apart from an increase in the SERS intensity, there is no significant change in the recorded spectrum. This result shows that in the case of \(\beta\)-CD-capped AuNPs, a change in the pH cannot induce changes in the molecule's orientation relative to the metallic surface and, thus, the spectrum remains practically unchanged. This result is also proof that MB molecules approach the metallic surface inside the CD cavity, which does not allow for a change in its orientation relative to the metallic surface. This result also suggests that the AuNPs were successfully coated with CDs.
## 5 Results and Discussion
### Characterization of Archaeological Stone Materials by XRD  
X-ray diffraction (XRD) measurements carried out on all the samples, revealed the presence of several mineralogical phases according to the different materials sampled, as summarized in Table 3. As regards mosaic _tesserae_, the data show that (a) the white and pinkish _tesserae_, both original (TTB1; TTB2; TTB3; TTB4; TTB5; TTB6; TTR1 and TTR2) and used for restorations (TTRi1; TBI1 and TBI2), are sedimentary rocks with a predominant calcite component, sometimes with accessory phases such as quartz and albite; (b) the black _tesserae_, belonging to the original mosaic (TTN1; TTN2; TTN3 and TTN4), have the typical mineralogical composition of volcanic rocks, with a predominance of feldspars (Sanidine; Orthoclase); amphibole (Hornblende); pyroxene (Clinopyroxene); plagioclase (Albite); followed by Calcite and Forsterite; (c) the black and dark greyish tiles used during the restoration (TTGi1 and TTNi1) are also sedimentary rocks, thus attesting to the use of a different material from the original one. Regarding the bricks, sampled both from the _calarium_ and in adjacent masonry structures, mineralogical analyses reveal a similar mineralogical composition in all the samples, characterized by the predominant presence of calcite, quartz and feldspars. Additionally, the detection of neoformation mineralogical phases such as Diopside and Gehlenite, only in samples (i.e., TL1; TL3 and TL8), suggest their higher firing temperatures (generally \(>\) 850 \({}^{\circ}\)C) [3; 41; 42; 43]. As regards the two veined white marbles taken from the _calarium_ floor, respectively, TLM1 and TLM2, they display a calcitic composition with traces of quartz. Finally, the analysis carried out on the only cementitious sample (i.e., TC1) revealed that it was mainly characterized by dominant calcite and quartz, followed by lower intensity diffraction peaks of feldspars.
## 7 Risk Analysis
### Edge Gateway
#### 7.6.1 Tampering  
1. **Component**  
_Security risk_: The risk associated with tampering with the edge gateway presents a threat with far-reaching implications. In this context, the edge gateway lacks a validation mechanism for incoming information, leaving it vulnerable to being tampered with by malicious actors. This vulnerability opens the door for attackers to manipulate the information before it reaches the edge gateway, enabling them to introduce erroneous data into the system. This lack of integrity checks introduces a severe risk, as the compromised information could potentially mislead emergency services, causing incorrect actions to be taken based on the tampered-with data.  
_Security measures_: To counter the risk of data tampering, implementing data integrity verification mechanisms is essential. Employing techniques like message authentication codes media access controls (MACs) or digital signatures can ensure that the information received by the edge gateway remains unaltered and originates from a trusted source.
## 2 Results and Discussion
### Role of Leptospiral ECF\(\sigma\) Factors in ClpB\({}_{Li}\) Gene Expression
It has been proposed that an increase in activity of \(\sigma^{\text{E}}\) promoters during stationary phase results from elevation in the ppGpp level in this growth phase. To examine whether ppGpp could have an impact on the \(clpB_{Li}\) promoter's transcriptional activity and, therefore, on \(clpB_{Li}\) expression, the activity of luciferase was determined in both the wild-type strain (MG1655) and its derivative, i.e., the \(\Delta rel\Delta\Delta spoT\) mutant strain lacking ppGpp. We observed (Figure 6) that in the \(\Delta rel\Delta\Delta spoT\) mutant strain, the luciferase activity was significantly lower in the stationary phase than in the wild-type strain, while the opposite was observed in the logarithmic phase of growth. This observation suggests that the \(clpB_{Li}P1\) promoter may be differently regulated by ppGpp during growth--it is repressed in the exponential phase and activated in the stationary phase. It is known that ppGpp is a key factor of the stringent response, which is a widespread response to changing environmental conditions found in all bacterial species tested so far [30]. Importantly, ppGpp is necessary for bacterial virulence and pathogenicity [31]. Presence of a single Rel-like bifunctional protein with (p) ppGpp-hydrolase/synthesize activity, \(\text{Rel}_{\text{Lin}}\), in _L. interrogans_ points to the existence of the stringent response in this bacterium [32] and corroborates our findings. Still, although ppGpp regulation of \(clpB_{Li}P1\) in _Leptospira_ is very likely, it cannot be excluded that the promoter transcriptional activity observed in _E. coli_ does not reflect regulation in _Leptospira_. The contribution of the stringent response to _Leptospira_ zoonotic lifecycle is yet to be examined. Figure 5: Transcriptional activity of the \(clpB_{Li}P1\) promoter in the presence of leptospinal ECF \(\sigma\) (\(\sigma^{\text{E}}\)) factors during the exponential and stationary phase of growth. _E. coli_ MG1655 cultures carrying the \(clpB_{Li}P1\)-\(luxAB\) (\(luxAB\)) transcriptional fusion or a two-plasmid system (\(pclpB_{Li}P1\)-\(luxAB\) and an appropriate _LIC_ gene coding \(\sigma^{\text{E}}\) factor) were grow in LB at 30 \({}^{\circ}\)C to OD\({}_{600\text{ nm}}\) of 0.45–0.5 and expression of _LIC_ genes was induced by addition of 0.02% arabinose for 1–3 h (for exponential-phase culture) or 6 h (for early-stationary-phase culture), then the luciferase reporter assay was carried out. The luciferase activity (relative luminescence units/OD\({}_{600\text{ nm}}\)) in the _E. coli_ strain without _LIC_ genes and 1 h after arabinose addition is taken as 100% (*); bars represent the percentage of luciferase activity normalized to that in the _E. coli_ strain without \(\sigma^{\text{E}}\) overexpression (*); the results are presented as the average of three independent experiments, each performed with duplicate cultures, with standard deviations indicated. The paired _t_-test result: *** \(p<0.001\) calculated with GraphPad Prism software.
# Deep Learning-Based Portable Device for Audio Distress Signal Recognition in Urban Areas
## 2 Materials and Methods
### Prototype Design  
The general design of the prototype is shown in Figure 1. It consists of a condenser microphone and a Raspberry Pi located at a two meter tall structure.  
We used a Raspberry Pi 4 model B, which has a 64-bit quad-core processor and up to 4 GB of RAM. The source code was written in Python, containing a copy of the trained model of the convolutional neural network that was uploaded trough GitHub. The chosen audio sensing device is the Snowball iCE Condenser microphone. It is important to note that this is a low-cost device. The reach of this microphone is defined by the cardioid polar pattern shown in [15].  
The total cost of implementation is around $150 USD, which includes the microphone ($50 USD), the Raspberry Pi device ($60 USD), and additional elements such as a micro-sd card, case, and stand. Comparing this cost to the audio device used in [8], which is above $450 USD dollars (high-quality microphone), our device can be considered as a low-cost one.