esa-sceva/satcom-chunk-collection huggingface dataset:
# Role of Nutribiotics in Skin Care
## 5 Nutribiotics: An Opportunity to Improve Skin Health  
The history of probiotics can be tracked back to ancient times, nearly 10,000 years ago, since probiotic microorganisms and fermented products, such as kefir, kumis, bread beer, and wine, were very frequently used for nutritional and therapeutic purposes [126]. Knowing that the composition of the human microbiota is directly linked with the development and function of the immune system, oral supplementation with prebiotics and probiotics could be a tool for improving overall human health, but more research is needed to better understand the interactions between the diet, the microbiome, and the immune system to design specific diets with the aim of treating various diseases [127]. [PERSON] et al. [128] explain the immunological pathway of oral probiotics as follows: when probiotics enter, the intestinal tract can interact with the host, improving intestinal homeostasis; moreover, they take part in immunomod, gut microbiota homeostasis, digestion, and the absorption of nutrients, improving the intestinal mucosal barrier. The use of probiotics in skin care is more recent since the gut-skin axis was investigated. [PERSON] et al. [129] revised the use of prebiotics and probiotics in chronic skin diseases, finding studies mainly on atopic dermatitis (children and adults) but also on acne, chronic ulcers, seborrheic dermatitis, and burns. Later on, in a similar revision, [PERSON] et al. [130] showed that the administration of prebiotics, probiotics, and synbiotics has auspicious effects on preventing and treating various inflammatory skin disorders, such as atopic dermatitis and acne [131; 132]. The oral administration of probiotics affects the intestinal microbiome and can improve skin conditions, such as atopic dermatitis, acne, or rosacea [133; 134]. Moreover, other studies showed that using probiotics during gestation and early life can reduce the incidence and severity of atopic dermatitis via immune modulation and by promoting the maturation of the gut barrier's function [130; 135; 136]. Additionally, probiotics were investigated to treat different allergy illnesses, including atopic dermatitis, asthma, allergic rhinitis, and food allergy [137]. Despite of this, [PERSON] and [PERSON] [138], after reviewing several studies, concluded that alterations in the intestinal microbiome play an important role not only in the development and aggravation of many skin diseases but also influence skin aging, although more research is necessary to evaluate the impact of probiotics. On the other hand, [PERSON] et al. [139] revised the health effects of postbiotics, including skin conditions both in vitro and in vivo, and [PERSON] et al. [25] discussed the potential of para-probiotics and postbiotics to modulate the immune system. There are also studies about the topical use of pre-, pro-, and postbiotics for skin care, but this issue exceeds the aim of this work. The following sections describe the use of pre-, pro-, syn-, post-, and para-probiotics in skin care. Table 2 summarizes the clinical studies.
## 4 Results and Discussions
Similarly, the classification results of the proposed second-stage MMDCNN obtained for MI localization using hold-out validation are shown in Table 7. It can be noted that the average IA values are more than 99% for AMI, IMLI, ALMI, ILMI, and IPLMI classes. For ASMI class, the IA value is 94.38%. The OA and kappa values obtained are 98.77% and 0.982, respectively, using the proposed second-stage MMDCNN model. The classification results of MMDCNN models evaluated using the selected modes of each lead VCG signal, and all modes of high-pass filtered VCG signals for MI detection with hold-out validation are shown in Table 9. It is observed that the average accuracy value of MMDCNN is 99.58% using mode 1 and mode 2 of each lead VCG signal. The average accuracy value remains the same as the accuracy of MMDCNN model using all modes of VCG signals for MI detection. Mode 1 and mode 2 capture the significant information of the VCG signal after decomposition using MVMD. Henceforth, the accuracy value remains the same for MI detection using selected modes and the MMDCNN classifier. Moreover, we have also evaluated the classification performance of the MMDCNN model using all modes of high-pass filtered VCG signal for MI detection. A high-pass Butterworth filter with a cut-off frequency of 0.5 Hz is applied to each lead VCG signal to remove baseline wondering artifacts [6; 28]. It is observed from Table 9 that average accuracy, average kappa score, average sensitivity, and average specificity values are improved after the filtering of baseline wandering artifact from VCG signals. In Table 10, we have shown the individual accuracy value for each MI class, OA, and kappa scores of MMDCNN classifier for MI localization using mode 1 and mode 2 of each lead VCG signal and all modes of high-pass filtered VCG signals, respectively. It is observed that the OA value obtained using the MMDCNN model is less using mode 1 and mode 2 of VCG signals as compared to all modes of VCG signals. Similarly, the OA and kappa values are improved using the modes of high-pass filtered VCG signals with the MMDCNN classifier. For MI localization, the IA values for ASNI, IMI, and ILMI classes are also improved using the \begin{table}
\begin{tabular}{c c} \hline
**Parameters** & **Value (\(\mu\pm\sigma\))** \\ \hline IA\({}_{\text{AMI}}\) (\%) & 99.79 \(\pm\) 0.35 \\ \hline IA\({}_{\text{ALMI}}\) (\%) & 99.64 \(\pm\) 0.31 \\ \hline IA\({}_{\text{ASMI}}\) (\%) & 94.38 \(\pm\) 5.56 \\ \hline IA\({}_{\text{IMI}}\) (\%) & 99.53 \(\pm\) 0.53 \\ \hline IA\({}_{\text{ILMI}}\) (\%) & 99.66 \(\pm\) 0.00 \\ \hline IA\({}_{\text{IPLMI}}\) (\%) & 99.66 \(\pm\) 0.57 \\ \hline OA (\%) & 98.77 \(\pm\) 0.96 \\ \hline Kappa & 0.982 \(\pm\) 0.014 \\ \hline \end{tabular}
\end{table} 
Table 7: Classification results obtained for MI localization using proposed MMDCNN model with hold-out validation.
## 2 Methodology and Data
### Satellite Data
#### 2.1.2 GOSAT Satellite Data  
GOSAT, the world's first satellite dedicated to global carbon monitoring, was launched by the Japan Aerospace Exploration Agency (JAXA) in January 2009. The primary payload on the GOSAT satellite, TANSO-FTS, is a Fourier Transform Spectrometer (FTS). This  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Satellite** & **Spatial Resolution** & **Revisit Period** & **Overpass Time** & **Orbit Altitude** & **Launch Date** \\ \hline Sentinel-5P & 7 km \(\times\) 7 km & daily & 13:30 & 824 km & 2017.10 \\ \hline GOSAT & 10.5 km diameter & 3 days & 13:00 & 666 km & 2009.01 \\ \hline GF-5 & 30 m & 2 days & 10:30 & 705 km & 2018.05 \\ \hline \end{tabular}
\end{table}
Table 1: Overview of Satellite XCH4 Products.  
dual-pendulum interferometer with two corner cube reflectors generates an optical path difference (OPD) of \(\pm\)2.5 cm, with a length four times that of the mechanical movement. The modulated light is collected into a circular stopper with a nominal footprint of 10.5 km for nadir pointing. The FTS mechanism allows TANSO-FTS to have a finer spectral resolution (0.2 cm\({}^{-1}\)) compared to the TROPOMI instrument, providing more accurate methane concentration retrievals. In this study, we acquired five years' worth of Level 2 XCH4 data from the GOSAT website, covering the period from 2019 to 2023.
# Ozonized Water Administration in Peri-Implant Mucositis Sites: A Randomized Clinical Trial
## 3 Results
### Plaque Index (PI%)  
PI significantly decreased after baseline in Group 1 at T1, whereas no difference was found in the range T1-T2. In Group 2, no significant differences were found between the time frames. No significant intergroup differences were assessed at any time frame. The results are shown in Table 3 and Figure 3.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Group** & **Time** & **Mean** & **St Dev** & **Min** & **Median** & **Max** & \
\begin{tabular}{c} **Intragroup** \\ **Differences** * \\ \end{tabular} &
\begin{tabular}{c} **Intergroup** \\ **Differences** * \\ \end{tabular} \\ \hline Trial Group & T0 & 4.65 & 0.57 & 4.00 & 4.70 & 5.71 & A & T0: ns \\  & T1 & 4.14 & 0.87 & 3.00 & 4.00 & 5.82 & B & T1: ns \\  & T2 & 3.84 & 0.67 & 3.00 & 3.63 & 5.24 & C & T2: \(p\) \(<\) 0.05 \\ Placebo Group & T0 & 4.67 & 0.75 & 4.00 & 4.50 & 6.33 & A & \\  & T1 & 4.55 & 0.66 & 3.33 & 4.75 & 5.54 & A & \\  & T2 & 4.66 & 0.96 & 3.25 & 4.34 & 6.91 & A & \\ \hline \hline \end{tabular}  
* Different letters show statistically significant differences among the time frames (\(p\)\(<\) 0.05);
* ns = not significant.  
\end{table}
Table 2: Descriptive statistics of Probing Pocket Depth measurements (PPD).  
Figure 2: Probing Pocket Depth measurements (mm): the figure shows the absence of intergroup differences at all the evaluation times (\(p\)\(>\) 0.05), except at T2 (\(p\)\(<\) 0.05). As to intragroup differences, a progressive significant reduction in the index was assessed in the trial group but not in the control one.
# Safety and Security Considerations for Online Laboratory Management Systems
## 3 Literature Review
### Legal Safety and Security Requirements and Regulations
#### 3.3.3 Prevention Through Design  
Prevention through design (PtD) [47], also called safety by design in Europe, involves employing strategies to mitigate occupational hazards at the initial stages of the design process. The primary focus is optimizing employees' well-being and safety throughout the entire life cycle of materials and processes. This concept and movement advocates for architects, engineers, and product designers to preemptively address health and safety risks during the developmental phase of designs. Unlike traditional hazard control methods that respond to incidents during construction projects, PtD takes a proactive position by addressing potential risks during the design phase. This methodology immediately eliminates potential health and safety hazards, reducing workers' dependence on personal protective equipment, which is considered the least effective measure in the hazard control hierarchy.  
Similar methodologies to control hazards were applied in different countries. For example, the UK government periodically revised the legislation, with the iteration of the Construction Design and Management Regulations [48], intensifying the focus on the responsibilities of principal designers to prevent injuries and fatalities throughout the project's design phase. The Work Health and Safety Act [38] includes provisions for employers, designers, and other parties' construction projects in Australia. This law prioritizes safety in all stages of the construction process. In Singapore, it is known as the Design for Safety (DfS) [49] regulation, which was introduced by the government's initiative in the Workplace Safety and Health Council [50]. This enables the Singapore government to accept construction projects executed with a strong emphasis on security.
## 2 Material and Methods
### TEC Driver
#### 2.1.5 Control Unit  
The control unit, as shown in Figure 5, constitutes the microcontroller, drivers, switching circuits, voltage regulation, and current protection circuits. The microcontroller used is a 32-bit ARM Cortex M4 device from ST-Microelectronics clocked at 100 MHz. It is connected to a SD card for local data logging and storing configurations and calibration data. A real-time clock (RTC) is used for time keeping and timestamps for logged data. Communication to external system is realized using UART to USB interface. The PWM peripheral pins drives the LED lighting system, TEC heating-cooling system, internal circulation fans, and external heat exchanger fan. General purpose input-output drives the electromechanical relays of the LED group switch and Pumps M1-M5. The entire system is designed to be operated using a single 12 V DC source and thus incorporates the necessary DC-DC step-down converter for supplying 5 V for low voltage electronic components (microcontroller, humidifier, etc.).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**ID** & **Part No.** & **Manufacturer** & **Interface** & **Parameters** & **Min** & **Max** & **Accuracy** & **Unit** \\ \hline S1 & SCD30 & Sensirion & I2C & \begin{tabular}{c} CO\({}_{2}\) \\ Temperature \\ Humidity \\ \end{tabular} & \begin{tabular}{c} 400 \\ 0 \\ 0 \\ \end{tabular} & \begin{tabular}{c} 10000 \\ 0.3 \\ 0.1 \\ \end{tabular} & \begin{tabular}{c} 30 \\ \%C \\ \%RH \\ \end{tabular} \\ \hline S2 & BME680 & BOSCH & I2C & \begin{tabular}{c} Temperature \\ Humidity \\ Pressure \\ \end{tabular} & \begin{tabular}{c} -40 \\ 10 \\ 100 \\ \end{tabular} & \
\begin{tabular}{c} 85 \\ 3 \\ 0.6 \\ \end{tabular} &
\begin{tabular}{c} 1 \\ \%C \\ \%RH \\ \end{tabular} \\ \hline S3 & SK25-F & Figaro & Analog & O\({}_{2}\) & 0 & 30 & 1 & \% \\ \hline S4 & DS18B20 & Dallas Semiconductor & 1-Wire & Temperature & \(-\)55 & 125 & 0.5 & \({}^{\circ}\)C \\ \hline S5 & SEN0193 & DFRobot & Analog & Moisture & 1.2 & 2.5 & – & V \\ \hline \end{tabular}
\end{table}
Table 1: List of sensors and sensor specification.  
Figure 5: Electronic components and communication interfaces: internal components of the control and sensor unit, external components, and the corresponding communication and electrical interfaces.
###### Abstract  
In the rapidly evolving landscape of drone technology, securing unmanned aerial vehicles (UAVs) presents critical challenges and demands unique solutions. This paper offers a thorough examination of the security requirements, threat models, and solutions pertinent to UAVs, emphasizing the importance of cybersecurity and drone forensics. This research addresses the unique requirements of UAV security, outlines various threat models, and explores diverse solutions to ensure data integrity. Drone forensics, a field dedicated to the investigation of security incidents involving UAVs, has been extensively examined and demonstrates its relevance in identifying attack origins or establishing accident causes. This paper further surveys artifacts, tools, and benchmark datasets that are critical in the domain of drone forensics, providing a comprehensive view of current capabilities. Acknowledging the ongoing challenges in UAV security, particularly given the pace of technological advancement and complex operational environments, this study underscores the need for increased collaboration, updated security protocols, and comprehensive regulatory frameworks. Ultimately, this research contributes to a deeper understanding of UAV cybersecurity and aids in fostering future research into the secure and reliable operation of drones.  
unmanned aerial vehicles (UAVs); drone cybersecurity; threat models; drone forensics; security challenges; forensic methodologies +
Footnote †: journal: _Future Internet_  
direct the flight of a drone and manage its functionalities. While the GCS provides a means to leverage the versatility of drones, it also exposes a vulnerable attack surface for cybercriminals. The vulnerabilities of the GCS and their implications for drone operation and security form an essential aspect of UAV security and forensics.  
The significance of drone forensics and security cannot be overstated in today's increasingly drone-dependent world. As drones continue to find applications in security-sensitive sectors, such as military surveillance, law enforcement, and delivery of goods, any security lapses could result in dire consequences, including threats to national security, invasion of personal privacy, and loss of valuable assets. This underscores the urgent need for robust cybersecurity measures and effective forensic methodologies that can secure UAVs against potential attacks and aid in the investigation post any security incidents.  
This paper used a systematic literature review to understand the field comprehensively. We searched Scopus and IEEE Xplore with keywords: \"Unmanned Aerial Vehicles (UAVs)\", \"Drone Cybersecurity\", \"Drone Cybersecurity Threat Models\", \"Drone Forensics\", \"Security\", and \"Drone Forensic Methodologies\" for articles published since 2018. By aggregating and analyzing scholarly articles, industry reports, case studies, and government publications, this paper presents a holistic view of current drone threat models, forensic approaches, and security challenges.
## 4 Conclusions  
To the best of our knowledge, this is the first study that isolated and identified LAB from the digestive tract of queen scallop _A. opercularis_, as well as further tested the best selected strain _Lpb. plantarum_ I on the growth health status of this bivalve. Five different LAB strains were successfully isolated from the scallops' digestive tract and identified with API and MALDI-TOF methods. Analysis of the strains indicated that _Lpb. plantarum_ I exhibits the most potent antimicrobial activity. Additionally, this particular strain demonstrates remarkable resilience to adverse conditions, such as low pH and a broad range of temperatures, in addition to fulfilling the necessary safety requirements for its application.  
_Lpb. plantarum_ I also showed a good effect on the health status of _A. opercularis_ during the one-month experiment in captivity. Our results suggest that the growth performance and commercial quality of the scallop _A. opercularis_ can be stimulated by adding _Lpb. plantarum_ I as food supplement in aquaculture during the one-month experiment in captivity. The findings presented in this study have significant value and can aid in gaining a better comprehension of the function of LAB in promoting shellfish health in both controlled and simulated conditions of climate change. As these changes are already occurring and inevitable, it is crucial to explore effective strategies for adapting to them. The use of protective LAB, particularly indigenous strains, could play a crucial role in controlling pathogens and promoting the growth of fish and shellfish culture and aquaculture in the future.  
Conceptualization, I.K., M.S. and J.F.; data curation, D.K.; formal analysis, I.C., I.K. and A.Z.; investigation, K.M. and P.B.; methodology, I.C., I.K. and A.Z.; resources, A.Z., Z.J. and N.I.; validation, K.M. and N.I.; visualization, Z.J. and D.K.; writing--original draft, I.C., I.K. and A.Z.; writing--review & editing, K.M., M.S., P.B. and J.F. All authors have read and agreed to the published version of the manuscript.  
This study was funded by the European Regional Development Fund [KK.05.1.1.02.0012] in the framework of the project \"Integrated system of shellfish farming under climate change conditions\".  
Not applicable.  
The data of this study are available from the corresponding author upon request ([EMAIL_ADDRESS]).  
The authors are grateful to Aquarium Pula for the use of their facilities.  
The authors declare no conflict of interest.  
Figure 5: Somatic indices: (**a**) muscle index (MI) and (**b**) gonadosomatic index (GSI), of the control (CON) _A. opercularis_ and those exposed to LAB isolates (LAB), over four weeks.
# An Overview of Design Techniques for Two-Dimensional Leaky-Wave Antennas
## 4 Radially Periodic Leaky-Wave Antennas
### Full-Wave Validation of the Theoretical Model  
In this subsection, the 3-D model of the radially periodic LWA studied in [87] is simulated in CST Microwave Studio with the aim of deriving its far-field radiation pattern. The results are reported in Figure 10 through 3-D radiation patterns normalized with respect to their maximum in a linear scale. As expected, the device generates a conical beam in the far-field region pointing at \(\theta_{0}\), which decreases as the frequency increases from 17 GHz to 20 GHz. This aspect is in perfect agreement with the dispersion curves reported in Figure 9 since the absolute value of \(\beta\) decreases in that frequency range and, thus, \(\theta_{0}\) decreases, as expected from (4).  
Figure 9: (**a**) Schematic representation of the full-wave model of the linearized counterpart of the radially periodic 2-D LWA constituted by a grounded dielectric slab (pink solid) with \(N\) unit cells of a metal strip grating on top (dark areas). The two rectangular areas delimited by light-gray lines represent the two considered waveguide ports. In one of them, the modal field distribution is reported through lines of force, showing the correct excitation of the TM\({}_{0}\) mode in the device. (**b–e**) Dispersion diagrams of the normalized leaky (**b,c**) phase \(\hat{\beta}\) and (**d,e**) attenuation \(\hat{A}\) constants. While the blue dashed lines represent the reference case obtained through an MoM approach [87], black dashed and dotted lines represent the limiting, unperturbed cases of a parallel-plate waveguide (PPW) and of a grounded dielectric slab (GDS) structure, respectively. The green and magenta colors represent two subsequent case studies: \(N=6\) and \(N=7\) for (**b,d**), and \(N=15\) and \(N=16\) for (**c,e**).
## 2 Analysis of Unbalanced NPV
### Effect of Different Voltage Vectors on NPV  
As can be seen in Figure 1, the current flows in different paths with the turn on/off of a phase switch \(S_{n}\), specifically path \(n\)-\(Po\), \(n\)-\(N\), or \(n\)-\(Pe\). For the convenience of analysis, another function \(SW_{n}\) is defined here for the switch \(S_{n}\), as shown in the following equation.  
\[SW_{n}=\left\{\begin{array}{l}\text{O}\quad\quad\quad\quad S_{n}\text{ is turned on, $s_{n}=1$, the current flows to $n-N$ path}\\ \text{P}\quad\quad\quad S_{n}\text{ is turned off, $s_{n}=0,i_{n}>0$, the current flows to $n-P_{o}$ path}\\ \text{N}\quad\quad S_{n}\text{ is turned off, $s_{n}=0,i_{n}<0$, the current flows to $n-N_{e}$ path}\end{array}\right. \tag{6}\]According to different switch states of the three-phase switch \(S_{n}\) and the flow path of the current, a total of 25 voltage vectors can be derived for the VIENNA circuit and can be divided into four main categories: zero-voltage vector, large-voltage vector, medium-voltage vector, and small-voltage vector. Among them, the small-voltage vector is composed of a positive small vector and negative small vector. Table 1 shows the neutral currents \(i_{N}\) corresponding to different vectors.  
The effect of different voltage vectors on the direction of \(i_{N}\) is expressed by using the current flowing into or out of the neutral point \(N\) on the DC side, so that the direction of flowing into the neutral point \(N\) is positive and the direction of flowing out of the neutral point \(N\) is negative. As seen from Table 1, the neutral point current \(i_{N}\) corresponding to the zero-voltage vector and large-voltage vector is 0, indicating that the zero-voltage vector and large-voltage vector have no effect on NPV and therefore NPV cannot be adjusted or controlled by the zero-voltage vector and large-voltage vector; the neutral point current \(i_{N}\) corresponding to the medium-voltage vector is not zero, indicating that the medium-voltage vector will have an effect on NPV; however, because different medium-voltage vectors have different effects on NPV, and there is no obvious law to be followed, it is not suitable to use the medium-voltage vector to adjust or control NPV; similarly, the neutral point current \(i_{N}\) corresponding to positive and negative small vectors is also not zero, so different small-voltage vectors will also have an effect on NPV. As can be seen in Table 1, the positive and negative vectors appear in pairs, with opposite effects on NPV; therefore, according to the characteristics of the positive and negative vectors, NPV can be adjusted or controlled by adjusting the selection method or operating time of the positive and negative vectors.  
Strategy for NPV Balance Control Based on Selection Method of Dynamical Adjustment for Small-Voltage Vector