esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Challenges and Future Work for SWE
### Facilitating the Integration of Sensors and Services  
The ability to dynamically integrate sensors is still an unresolved challenge within SWE. An on-the-fly integration of sensors into the Sensor Web with a minimum of human intervention is not straight- forward with the given methods. Especially in hazard or disaster situations, a live deployment or densification of sensor networks and an _ad-hoc_ integration of those sensors into the Sensor Web to allow multiple parties an easy access and usage of the sensors must be enabled.  
The SWE services are intentionally designed from an application-oriented perspective. Currently, sensors are usually connected by manually building adapters for each pair of web service and sensor type. Those adaption efforts are a key cost factor in large-scale sensor network systems [120]. Bridging this _interoperability gap_[121] between the Sensor Web layer and the lower-level sensor layer can be addressed from two directions.  
First, the interoperability on the sensor layer can be improved which is addressed by several standardization efforts. An example is the IEEE 1451 family of standards [122], a universal approach to connect sensors to diverse networks and systems. Another example is the PUCK protocol that extends the sensor firmware, and provides a means to retrieve a universally unique identifier, metadata and other information from the device itself through its communication interface [123]. It is envisaged to bring PUCK into the OGC standardization process.  
However, in today's real world applications a huge variety of sensor protocols (standardized or proprietary) are utilized. Thus, several projects are addressing the interoperability gap from the opposite direction, by introducing mechanisms to abstract from the variety of sensor protocols (e.g., AnySen [107], Sensor Abstraction Layer [124], or Sensor Bus [29]). However, those approaches still need manual creation of sensor adapters.  
A promising, universal approach is the Sensor Interface Descriptor (SID) model [62] which extends SensorML (Section 3.2.3). It can be utilized to formally describe a sensor's protocol. Graphical editors are in development [125] which can be utilized to create instances of the SID model. The generated sensor interface description is used as a platform independent sensor driver which contains the necessary information to integrate a sensor on demand by translating between sensor protocol and Sensor Web protocols. A still remaining open challenge is to include such a universal approach for the sensor interface abstraction, e.g., SID, in the standardization process and to develop tools which facilitate its usage. Semantic challenges which have to be tackled to enable an automatic sensor plug & play are discussed in [126]. Difficulties lie in establishing the semantic matching between SWEconcepts used for modelling sensors and observations (e.g., feature of interest or observed property) and the constructs of the lower sensor network layer.
## 3 Analytical Model
### Network Energy Efficiency  
The network EE can be defined as the ratio of the effective network throughput over the network total power consumption:  
\[EE=\frac{R_{total}}{P_{total}}=\frac{R_{total}}{\theta P_{abs}+\left(1-\theta \right)P_{non\_abs}}. \tag{13}\]  
For convenience of derivation, we set \(\alpha=4\), \(\sigma^{2}=0\). Then, combining Equations (8), (9)-(13), the expression of the network EE is obtained as follows:  
\[\begin{split} EE&=\frac{R_{total}}{P_{total}}=\frac{ \left(R_{m_{u}}A_{m_{u}}+R_{p_{c}}A_{p_{c}}+R_{p_{c}}A_{p_{c}}\right)\lambda_{ u}}{\theta P_{abs}^{\alpha}+\left(1-\theta\right)P_{non\_abs}}\\ &=\frac{\lambda_{u}}{P_{total}}\int_{0}^{\infty}\frac{\theta P_{ s}}{\mathcal{Q}\left(\mathcal{A},4\right)+p_{p,m}Q\left(P_{p}\mathcal{A},B_{p} \bar{P}_{p}\right)}\\ &\quad+\frac{\left(1-\theta\right)W/N_{p_{c}}}{\mathcal{Q}\left( \bar{P}_{m},4,\bar{P}_{m}\right)+p_{p,m}^{\top}Q\left(\mathcal{A},4\right)}\\ &\quad-\frac{\theta W/N_{p_{c}}}{\mathcal{Q}\left(\mathcal{A},4 \right)+\left(\bar{P}_{m}\right)^{1/2}\bar{P}_{p,m}^{-1}}\\ &\quad+\frac{\theta W/N_{p_{c}}}{\mathcal{Q}\left(\mathcal{A},4 \right)+\left(B_{p}^{-1}\bar{B}_{m}\right)^{1/2}\bar{P}_{p,m}^{-1}}dt,\end{split} \tag{14}\]  
where \(\lambda_{u}/P_{total}=\lambda_{u}/\big{\{}\lambda_{m}P_{m,s}+\lambda_{p}P_{p,s }+\theta A_{p_{c}}P_{p,t}\lambda_{u}\\ &\quad+\lambda_{u}\left(1-\theta\right)\left(A_{m}P_{m,t}\right. \left.+A_{p}P_{p,t}\right)\big{\}}\), \(\rho_{p,m}=\lambda_{p}/\lambda_{m}\).
# Unlocking Wellness: Probiotics as Key Drivers in Functional Food Innovation and Health Promotion
## 5 Technological Innovation of Probiotics in Functional Foods
### Personalized Strain Screening  
In the realm of personalized applications, probiotic technology continues to innovate, achieving enhanced efficacy through precise strain screening and the optimization of host suitability. Personalized strain screening for probiotics involves identifying the optimal probiotic strain for an individual from a diverse pool of candidates. This process considers the individual's specific requirements, physiological profile, current health condition, and genetic makeup to determine the most appropriate probiotic intervention [159]. [PERSON] et al. [159] isolated native probiotic strains from healthy host feces using selective media (MRS and BIM-25). They identified three host-adapted bacterial strains through simulated gastrointestinal fluid tolerance screening, antibiotic susceptibility testing, and RAPD-PCR genotyping. These strains were reintroduced into healthy mice and evaluated for protective effects in a DSS-induced colitis model. The results demonstrated that this personalized probiotic group significantly reduced the disease activity index by 42% comparedto commercial LGG, while being more effective in alleviating colitis symptoms, ameliorating histopathological damage, and modulating immune responses. [PERSON] et al. [160] further revealed gender dimorphism effects, where a multi-strain formulation (containing 14 _Lactobacillus_/ _Bifidobacterium_ strains) exhibited superior metabolic modulation in female MSG-obese rats. This formulation effectively prevented changes, including blocking weight gain, reducing inflammatory cell activation, and improving gut microbial community composition. The screening and application of personalized probiotics represent a current research hotspot in probiotic science, with the possibility of the development of more targeted and efficient probiotic products that address diverse individual needs.
## 4 The Rotational Orbit Based Inter Node Adjustment (ROBINA)
The inside circle shows the overall rotation of the path to avoid void holes and deploy the inter-node adjustment near the SNNs. The _'oval'_ legend in Figure 4 shows the working of the orbital routing path while the _'arrow'_ denotes the straight forward path adjustment of ROBINA. Further, the nodes closer to the destination take enough burden from the whole network communication and die early, which relay as void nodes (white in color). When these nodes are found frequently in network size, they become void regions isolated to some part of the network too. The main reason for this event is the absence of the candidate nodes responsible for those nodes that die or near death. From this reference, we introduce the idea of inter-node adjustment and formulate their path accordingly. Usually, in underwater situations, the path is horizontal, vertical, elliptical, atomic shaped, vector and depth-oriented, height and angle oriented, or etc. Due to the non-rotatable behavior of the path, all these schemes are not well performed. Therefore, a rotational-based path with an internode adjustment mechanism performs well when the area of interest is dense and shallow. The novel orbit-based path rotates with the adjacency of relay nodes, including some inter-nodes adjustment (where needed), making the communication secure and reliable. Figure 3: Acoustic Scenario with Path Adjustment of ROBINA.
## 3 Simulations Summary and Metrics to Evaluate the Results
For PV, since a gain block is included at the output of the subsystem, it could be used to model a partial loss of generation. \begin{table}
\begin{tabular}{c c} \hline \hline
**Simulation Group** & **Aim** \\ \hline Load active power step & Observing the frequency response of the system after a sudden \\ up/down & variation of the load power for different step magnitudes \\ \hline Small sinusoidal oscillations + step of load active power & Observing the frequency response of the system to small and continuous variations of the load, i.e., similar to the real \\  & behavior, and to a step if a part of the reserve is already in use to \\  & balance the small variations \\ \hline Variable environmental conditions (real wind speed profile, irradiance variations) & Understanding how the system responds to environmental \\  & condition changes, as well as to a sudden load power variation \\ \hline Variable participation factors & Understanding what is the impact of an increasing penetration \\  & of renewable sources on the system’s frequency stability \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation groups and aims. Before presenting the simulation results, it is important to define quantitative instruments that can help in interpreting them. Indeed, the next section includes both qualitative analysis on the results and quantitative observations to catch some important concepts. It is first of all required to report a definition of primary frequency adequacy. As stated in [37], a primary frequency control is adequate if it is able to ensure an uninterrupted delivery of electricity after a sudden imbalance between generation and demand, i.e., if it is capable of arresting and stabilizing the frequency deviation without exceeding the limits imposed by grid codes. In this work, the following metrics are used:  
* Frequency nadir [Hz]: it is a direct measure of the primary frequency control adequacy. It is calculated as the maximum/minimum value of frequency deviation occurring after an active power imbalance. The closer it is to the nominal frequency, the better. * RoCoF [Hz/s]: it is the time derivative of the system's frequency. The smaller it is, the better for the system. * _Nadir-based frequency response_: it expresses how good the primary frequency control has performed in stabilizing the frequency after a perturbation. It can be calculated as [37]: \[\text{Nadir-based frequency response}=\Delta P_{perturbation}/\Delta f_{nadir}.\] (14)
# RF Frequency Selective Switch by Multiple PMIM Conversions
## 2 Materials and Methods
The half-wave voltage of the modulator is about 4.5 V at 10 GHz, and the optical insertion loss is about 4 dB. Then, the generated multiple optically carried RF signals enter an optical ring resonator and are output from its throughput terminal. The loss of the periodic notch filter is about 6 dB, the bandwidth of 3 dB is about 50 MHz, and the FSR is about 50.05 GHz. The ring resonator employed in this system is a commercial product provided by Micro-Optics. The optical signal then enters an optical WSS and outputs from its various ports. A total of five output ports are used. The resolution of the optical WSS is 12.5 GHz and the insertion loss is about 5 dB. The optical WSS employed in our system is a commercial product (Finisar, 10 WSAA20 FLI), which is used to control the amplitude of each channel. Finally, the optical power entering the photodetector is about 5 dBm, and the RF output is obtained. In order to test the RF FSS, we use a vector network analyzer (VNA) to output a single-frequency sinusoidal wave, receive and analyze the corresponding output of the RF FSS, and obtain the frequency response of each channel of the RF FSS by scanning the frequency of the output tone. In the experiment, the comb spacing of the optical frequency comb is about 50 MHz larger than the FSR of the ring resonator, and the optical frequency of the comb at the center of the spectrum is about 10 GHz lower than the corresponding notch filter center frequency. The optical frequency comb is generated by cascaded modulators, which consists of two phase modulators and one intensity modulator. Finally, 21 comb lines are generated in our setup with flatness better than 3 dB. Moreover, the WSS is used to further flatten the comb lines. In this way, we can obtain a programmable microwave photonic frequency response with 50 MHz resolution in the RF frequency range from 9.5 GHz to 10.5 GHz. According to the principle, the bandwidth of the programmable frequency response demonstrated by us is only limited by the number of comb teeth of the optical frequency comb; At present, the number of comb teeth of an advanced optical frequency comb can be more than 100.
# A Trajectory Generation Method for Multi-Rotor UAV Based on Adaptive Adjustment Strategy
## 4 Experiment and Result
### Real-World Tasks
#### 4.2.2 Experimental Environment and Related Settings  
The test scene is indoors. The scene settings are shown in the Figure 12. The obstacle setting is shown in Tables 5 and 6. In the test, the UAV realized positioning and environment perception based on onboard sensors and flew around obstacles to the target point. In order to thoroughly verify the effectiveness of the algorithm, this paper sets two groups of tests with different dynamic constraints. The maximum flight speed of both groups of tests is set to 2.0 m/s, and the maximum acceleration is set to 2 m/s\({}^{2}\).  
The mapping algorithm parameters are set as follows: the camera resolution is 848 \(\times\) 480, the maximum measurement distance of the camera is 5.0 m, the minimum measurement distance is 0.3 m, and the obstacle determination threshold is 0.368. The parameters of the trajectory generation algorithm are set as follows: the optimization coefficients of the smooth item, the safety item, and the trajectory length item are set to 0.2, 0.15, and 0.025, respectively; the initial safety distance is set to 0.6 m; and the trajectory length penalty threshold is set to 0.2 m.  
This paper's perception, path planning, and trajectory generation algorithm can run in real time. Therefore, the experiment does not choose to conduct perceptual mapping and offline path planning in advance, but instead to sense in real-time and replan the trajectory by detecting collisions. In the initial stage, the unperceived area is the obstacle-free area by default. The system plans a safe path based on the \(A^{*}\) algorithm and then uses the trajectory optimization algorithm proposed in this paper to optimize the path to obtain a safe and smooth ideal trajectory. During the flight process, the multi-rotor UAV perceives the obstacles to update the occupied grid map and detect the collision between the trajectory and the obstacles in real time. If the trajectory collides with the obstacles, it must replan it. The replanned trajectory takes the current UAV state as the starting state and the terminal point state as the target state. Based on the \(A^{*}\) algorithm, the feasible path is re-searched, and then the algorithm proposed in this paper is used to obtain a safe and smooth trajectory to avoid obstacles. During the flight of the UAV, the trajectory safety is checked at the frequency of 10 Hz, and when the trajectory collides with the obstacle, it is replanned until the UAV reaches the target point.
# A Novel Technique for Semantic Segmentation of Hyperspectral Images Using Multi-View Features
## 5 Experimental Results and Discussion  
The proposed technique has been implemented using Python 3.10.9 on Jupyter Notebook IDE running on the Lenovo Legion 5 Pro system with an Intel Core i7 processor and 16 GB RAM, manufactured in India. The experiments have been performed on real Hyperspectral images which are landcover scenes i.e., IP, Pu and SA. To tackle such high dimension of spectral features, HSI has been employed in a new light of having multiple views and extracted features using CCA variants.
## 2 Study Site and Dataset Description
### Dataset Description
#### 2.2.2 IMERG GPM Products  
Rainfall measurements with 30-minute revisit time that were obtained from the GPM (Global Precipitation Measurements) sensor were considered in this study. The GPM mission is an international satellite mission initiated by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace and Exploration Agency (JAXA) to unify and advance global precipitation measurements from space [6]. GPM provides several precipitation records at different scales by using different sensor combinations. From the GPM mission, the IMERG (Integrated Multi-satellite Retrievals for GPM) data product was selected to perform our analysis. IMERG data offer global precipitation estimations in both real-time and late mode. While real-time IMERG data are proposed for disaster monitoring and flood risk assessment, the higher quality late IMERG data are intended for meteorological and climatological applications. The spatial resolution of IMERG maps is 0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\), which fully covers the globe between 60\({}^{\circ}\) N and 60\({}^{\circ}\) S. These data provide precipitation maps with several time intervals (30 minutes, 24 hours, three days... ). The NASA GPM program established several campaigns to collect ground-based observations to validate GPM products [21]. [PERSON] et al. [22] validated the accuracy of GPM-IMERG data over the Colorado River basin in Texas, and found that the GPM-IMREG slightly underestimates the precipitation over the basin. Several studies have also reported good correlation between GPM-IMREG products and rain gauges with small under or overestimation depending on the study site, and better estimation when compared to other precipitation products [23]. IMERG data at different spatial and temporal resolutions are available via the NASA Precipitation Measurements Mission (PMM) website ([[https://pmm.nasa.gov/data-access](https://pmm.nasa.gov/data-access)]([https://pmm.nasa.gov/data-access](https://pmm.nasa.gov/data-access))). In this study, the fifth version (V05) of GPM-IMERG products was used.
## 3 Security in SDNFV  
Information security has perennially been a critical concern in the digital era due to the paramount value of information and the imperative need for its protection. Information security encompasses preventive and responsive measures taken by individuals, organizations, and technological systems to safeguard and preserve the confidentiality, integrity, and availability of information, often referred to as the CIA triad. This triad serves as a foundational model guiding information security policies within organizations, as outlined in ISO/IEC 27000:2018 [23]:  
* Confidentiality: Ensures that information is not disclosed to unauthorized individuals, entities, or processes.
* Integrity: Ensures the accuracy and completeness of information.
* Availability: Ensures information is accessible and usable upon demand by authorized entities.  
While the CIA triad represents fundamental properties in information security, additional properties like authenticity, accountability, nonrepudiation, and reliability can also be critical.  
Networks play a key role in information systems, facilitating the exchange of information among various computers and resource distribution. A secure information system necessitates a secure network. The advent of novel network architectures has accommodated new business requisites; however, it has concurrently introduced fresh threats and vulnerabilities to the CIA triad that necessitate attention. For this reason, it is important to analyze vulnerabilities and threats associated with SDN and NFV architectures.
###### Abstract  
The study investigated the influence of genetic polymorphisms of the enzymes for DNA repair and detoxification of reactive intermediates on spontaneous and bleomycin-induced (BLM) genotoxic damage in 43 workers exposed to very low doses of ionizing radiation (IR) (mean cumulative dose 5.31 mSv) and 43 subjects with no occupational exposure to IR (controls). In all the subjects examined, the frequency of chromosome aberrations (CAs) and micronucleeli (MN), both spontaneous and BLM-induced, the Comet assay parameters (tail intensity), the genotypic variants of the DNA repair enzymes XRCC1 (Arg194 Trp, Arg280 His, Arg399 Gln), XRCC3 (Thr241 Met), XPD (Lys751 Gln), and of the detoxification enzymes GSTM1 and GST11 (null genotype) and BLMH (A1450G) were determined. Among the biomarkers considered, only the frequency of total CAs (\(p<0.05\)), and in particular of chromosome breaks (\(p<0.01\)), was found to be significantly higher in the exposed workers than the controls. The frequency of spontaneous MN was higher in subjects with at least one allelic variant in \(XRCC1\) than in carriers of the wild-type, but again only in exposed workers (\(p=0.046\)). Linear regression analysis showed a positive dependency of the frequency of spontaneous chromosome breaks on occupational exposure, and a dependency of the frequency of BLM-induced MN negative on occupational exposure and positive on alcohol consumption and the null _GSTM1_ genotype. In conclusion, the frequency of chromosome breaks seems to be a useful cytogenetic biomarker for exposure to very low doses of IR, while only the combined effect of different gene variants or genetic, occupational, and lifestyle habits factors seems to be able to modulate the genotoxic effect of very low doses of IR.  
chromoosome aberrations; micronucleeli; mutagen sensitivity
# Analysis of Influencing Characteristics of Biochars for Ammonium Adsorption
###### Abstract  
This article summarizes and performs a systematic analysis using experimental results from recent research on ammonium recovery from aqueous sources using biochar. Numerous studies have focused on using different materials to produce biochar adsorbents, and many have attempted to draw conclusions about the physical or chemical characteristics that dominate the adsorption to infer the mechanism. However, to date, there has not been statistical analysis performed on a large set of adsorption data and physical/chemical characteristics of chars to be able to draw conclusions about ammonium adsorption mechanisms. From this analysis, it was found that consistency in experimental methods and characteristic measurement reporting is lacking, and therefore it is difficult to perform metadata analysis and draw conclusions about ammonium adsorption on biochar. Among the important factors influencing ammonia recovery proposed in literature, the meta-analysis only strongly supports the effect of BET surface area and NH4+ concentration, with weaker support for the importance of cation exchange capacity and pyrolysis temperature. This suggests that standard procedures for biochar production, experiments and analysis of physical and chemical characteristics are needed to usefully compare results across different studies. Examples of the present difficulty in identifying trends across studies are shown by comparing clusters in the data identified by the analysis. The ability to make such comparisons would provide clearer direction in how best to further improve the adsorption capacity of biochars.  
Keywords:nitrogen; sorption; recovery; wastewater; fertilizer; circular economy +
Footnote †: journal: Applied