esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Literature Review on the Technological Interventions for COVID-19 Monitoring
### Literature Review Assessments  
A total of 30 research studies were reviewed, encompassing 1047 mobile apps. Among these studies, 83% (25 out of 30 studies) were conducted in developed countries, with the United States of America accounting for 40% (10 out of 25 studies). Other countries involved in the studies included the United Kingdom (UK), Germany, Spain, Denmark, France, Sweden, Norway, Switzerland, Australia, Korea, Hong Kong, India, Taiwan, and Japan. The participant demographics in these studies were diverse, covering variations in genders, age groups, ethnicities, professions, and health conditions, as discussed in Section 2.1. The participants in the studies were from various backgrounds, including:  
COVID-19 patients (87%) ([4; 6; 7; 8; 9; 10; 11; 12; 13; 15; 16; 17; 18]), global participants (67%) (references [4; 6; 7; 9; 10; 12; 14; 15; 17; 18]), healthcare workers (27%) ([4; 12; 13; 17; 18]), academics (staffs and students) (20%) (references [4; 11; 16]), elderly (13%) ([4; 9; 14; 16]), and adults with specific medical conditions (20%) ([8; 9; 13]). Furthermore, the mHealth tools and techniques utilized in these studies varied. Approximately 73% of the studies used mobile (iOS or Android) apps, while 3% utilized tablets and SMS. Additionally, 40% of the studies integrated wristbands or smartwatches with necessary apps. Table 1 summarizes the findings from the research studies. Table 1 presents the research results that focused on various participants from global populations aged 15 to over 80 years of age with diverse backgrounds, including healthcare professionals, patients, academics, and individuals from different countries, including Australia, Iran, India, USA, Germany, Singapore, Switzerland, and Pakistan. The performance metrics evaluated in the studies varied, including system availability, app uptake measures, feasibility, reliability, delay measures, technology acceptance, health data analysis, user experience, technology adoption, and system usability. The majority of the studies were based on bottom-up approaches, with a few including top-down approaches. The research method and tools used for data collection and analysis included: mobile applications, smartwatches, wristbands, web applications, and other mobile-based gadgets. In contrast to these studies, the proposed mPOC solution offers several unique features that set it apart from the systems and devices used in the reviewed studies. Firstly, it leverages the combination of a smartwatch and a smartphone app, with potential extensions to tablets and laptops/PCs without direct user interventions (apart from the initialization step) in a non-invasive approach. Secondly, the mPOC solution is designed to easily scale up to the population level. Thirdly, it is adaptive, meaning it can adapt to an individual user's physiological information, leading to higher accuracy compared to traditional systems and approaches. These distinguishing features will be discussed in detail in the subsequent sections.
# Pharmacokinetics of Pullulan-Dexamethasone Conjugates in Retinal Drug Delivery
## 3 Results  
### Synthesis and Characterization of Pullulan Conjugates  
Pullulan is a water-soluble polysaccharide but conjugation of pullulan with dexamethasone (DEX) as a hydrophobic molecule results in an amphiphilic derivative that undergoes self-assembly to nanoparticles. The self-assembled particles of Cy3-pullulan-DEX and BDP-pullulan-DEX were smaller than pullulan-DEX particles and all nanoparticles had negative zeta potentials (Table 1).  
The endotoxin level of formulations was measured. All tested concentrations (2.5, 1.25 and 0.63 mg/mL) of fluorescently labelled BDP-pullulan-DEX showed endotoxin levels below 0.03 mEU/\(\mu\)L. Thus, endotoxin levels in the formulations used for in vivo administration are at acceptable levels below 0.2 EU per injection [46; 47].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Sample**} & **Mean Size \(\pm\) SD** & **PDI** & **Zeta Potential** \\  & **(nm)** & & **(mV)** \\ \hline pullulan-DEX & 461 \(\pm\) 30 & 0.39 \(\pm\) 0.04 & \(-\)38.1 \(\pm\) 0.5 \\ Cy3-pullulan-DEX & 299 \(\pm\) 42 & 0.22 \(\pm\) 0.11 & \(-\)20.3 \(\pm\) 3.0 \\ BDP-pullulan-DEX & 219 \(\pm\) 15 & 0.25 \(\pm\) 0.07 & \(-\)40.9 \(\pm\) 1.1 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Intensity based mean sizes (\(\pm\)SD), polydispersity indices (PDI) and zeta potentials of the pullulan conjugate nanoparticles. The measurements were performed by dynamic light scattering.  
Figure 2: Scheme of the kinetic simulation model. The following parameters were used: K\({}_{r}\) (first-order release rate constant); K\({}_{p}\)D (elimination rate constant of free dexamethasone posteriorly from the vitreous); K\({}_{aD}\) (distribution rate constant of free dexamethasone from the vitreous to the anterior chamber); K\({}_{vP}\) (distribution rate constant of pullulan–dexamethasone from the vitreous to the anterior chamber); K\({}_{aphP}\) (elimination rate constant of pullulan–dexamethasone from the anterior chamber) and K\({}_{aphD}\) (elimination constant of dexamethasone from the anterior chamber). For detailed parameter values, see Supporting Information SI-4.
###### Abstract  
Background: Prostate cancer is a major cause of cancer-related mortality among men, with approximately 15% of newly diagnosed patients having pelvic lymph node metastasis (PLNM). For this reason, PLNM identification before localized PCa treatment would significantly impact treatment planning, clinical judgment, and patient outcome prediction. Radiomics has gained popularity for its ability to predict tumor behavior and prognosis without invasive procedures. Magnetic resonance imaging (MRI) is widely used in radiomic workups, particularly for prostate cancer. This study aims to predict lymph node invasion in prostate cancer patients using clinical information and mp-MRI radiomics features extracted from the suspicious nodule, prostate gland, and periprostatic adipose tissue (PPAT). Methods: A retrospective review of 85 patients who underwent mp-MRI at our radiology department between 2016 and 2022 was conducted. This study included patients who underwent prostatectomy and lymphadenectomy with complete histological examination and previous staging mp-MRI and were divided into two groups based on lymph node status (positive/negative). Data were collected from each patient, including clinical information, radiomics, and semantic data (such as tumor MRI characteristics, histological tumor details, and lymph node status (LNS)). MRI exams were conducted using a 1.5-T system and were used to study the prostate gland. A three-year resident manually segmented the prostate nodule, prostatic gland, and periprostatic tissue using an open-source segmentation program. A random forest (RF) machine learning model was developed and tested using Chat-GPT version 4.0 software. The model's performance in predicting LNS was assessed using accuracy, precision, recall, F1 score, and area under the curve (AUC) receiver operating characteristic (ROC), with sensitivity and specificity evaluated using [PERSON]'s test. Results: Random forest demonstrated the best performance in prediction considering features extracted from DWI nodules (67% of accuracy, 0.83 AUC), from T2 fat (78% of accuracy, 0.86 AUC), and from T2 glands (78% of accuracy, 0.97 AUC). The combination of the three sequences in the nodule evaluation was more accurate compared with the single sequences (88%). Combining all the nodule features with gland and PPAT features, an accuracy of 89% with AUC near 1 was obtained. Compared with the analysis of the nodule and the PPAT, the whole-gland evaluation had the best performance (\(p\leq 0.05\)) in predicting LNS when compared with the nodule. Conclusions: Precise nodal staging is essential for PCa patients' prognosis and therapeutic strategy. When compared with a radiologist's assessment, radiomics models enhance the diagnostic accuracy of lymph node staging for prostate cancer. Although data are still lacking, deep learning models may be able to further improve on this.  
**Keywords:** pelvic lymph node metastasis (PLNM); prostate cancer; radiomics; periprostatic adipose tissue (PPAT); machine learning; random forest
## 4 Discussion
### Limitations  
The findings of this study are less transferable to different populations, or training programmes with vastly different training philosophies or resources available. The data collection period of the 2020/2021 season was largely carried out under a host of changing government lockdown restrictions, while the 2021/2022 season was not impacted by government-imposed COVID-19 mandates. Recent research has shown the influence of the lockdown periods on athletes [44,45]. The collection of injury surveillance data through the COVID-19 pandemic provides key information during a crucial period in elite sport; however, the validity of extrapolating the findings to less volatile periods is a potential limitation of the study.
# A Real Case of Implementation of the Future 5G City
## 3 Future 5G City Use Cases
### The 5G Project Use Cases
#### 3.2.2 Smart Industry  
This use case is devoted to the development of a digital _smart industry_ platform able to meet the needs of industrial customers. The platform provides a complete portfolio of added value services as envisaged by the directive _Industry 4.0_ for the optimization of production processes, energy efficiency, maintenance, and operation. In particular, the experimentation proposes to realize an integrated IoT solution that allows one to manage data from various sensors/actuators and processes in the industrial sector. This allows one to create integrated Industry 4.0 systems that work in a manufacturing as a service (MaaS) perspective.  
\begin{table}
\begin{tabular}{c c c c} \hline
**KPI No.** & **Description** & **Value** & **Key Use Case** \\ \hline K1 & Density (devices/km\({}^{2}\)) & \(\geq\)10,000 & mMTC \\ K2 & Mobility (km/h) & up to 500 & eMBB \\ K3 & Peak data rate & DL:20 Gbps, UL:10 Gbps & eMBB \\ K4 & User Data Rate (Mbps) & DL:100, UL:50 & eMBB \\ K5 & User plane Latency (ms) & 4 (eMBB), 1 (URLL) & eMBB, URLL \\ K6 & Control plane Latency (ms) & 20 & eMBB, URLL \\ K7 & Reliability & frame error rate \(<\)10\({}^{-5}\) & URLL \\ K8 & Availability (\%) & \(>\)99 & URLL \\ \hline \end{tabular}
\end{table}
Table 1: KPIs to assess the performance of 5G use cases in the field trials.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Use Case** & **ITU Classes** & **KPIs** & **City** \\ \hline e-Health & eMBB, mMTC, URLLC & K4, K5, K6, K7, K8 & Prato, L’Aquila \\ Smart industry & mMTC, URLLC & K1, K5, K6, K7, K8 & Prato \\ Smart grid & mMTC & K1, K8 & Prato \\ IoT and sensors & mMTC & K1, K8 & Prato \\ City surveillance & eMBB & K3, K4, K8 & Prato \\ Virtual reality for cultural heritage & eMBB & K3, K4, K7 & Prato, L’Aquila \\ Structural health monitoring & eMBB, mMTC & K1, K3, K4, K5 & L’Aquila \\ Agriculture 2.0 & eMBB & K2, K4 & L’Aquila \\ Smart safety for smart city & eMBB & K3, K4, K8 & L’Aquila \\ Smart mobility: High connected EV road monitoring & mMTC, URLLC & K1, K2, K5, K6, K7, K8 & Prato \\ Smart mobility: advanced viability & mMTC, URLLC & K1, K2, K5, K6, K7, K8 & L’Aquila \\ \hline \end{tabular}
\end{table}
Table 2: Use cases in Prato and L’Aquila.
## 1 Introduction
Additionally, as a controller design method, we integrate a real-time estimator using an enhanced recursive least squares estimator (RLSE) with LSTM capabilities into the Smith Predictor control structure [20]. This estimator assesses SOPT model coefficients in real-time when external influences are significant. We propose an adaptive PID structure that dynamically adjusts parameter values based on this hybrid approach [21]. This paper consists of optimization PID controller design, optimization adaptive PID controller design incorporating LSTM networks, simulation and review of the hybrid approach, and conclusion of the enhanced Smith Predictor structure. Our simulation results demonstrate significant improvements in both control performance and computational efficiency compared to traditional methods.
# Hardware Prototyping and Validation of a W-\(\Delta\)DOR Digital Signal Processor
## 3 W-\(\Delta\)DOR Hardware Implementation
### W-\(\Delta\)DOR DSP Core Architecture Description
#### 3.1.2 Pseudo Noise Generator  
A set of two Linear Feedback Shift Registers (LFSRs) generates the PN sequences. The output registers are combined to obtain a Gold Code. The seeds and the generating polynomials are reconfigurable.
## 3 Results
### Comparison of the Performance of a Surge Arrester with a Degraded Cable and a Nominal One
The above values were then contrasted with the time waveforms. Since the differences in the critical parameters of the surge arrester between the degraded and the nominal cable did not exceed 10.09% (Table 6), the voltage waveform of a component with a large amplitude was chosen as an example to visualize the differences. For this purpose, the voltage at the input of the surge arrester (\(\text{U}_{\text{GDT}}\) (t) Figure 6) shown in Figure 11 was used. The voltage value for the degraded cable is +7.92 V (change of +1.14%) higher than the one for a cable with nominal parameters. The voltage waveform for the degraded cable has a similar shape (the rise has shifted) due to the influence of increased capacitance between the cable elements. The total of the \(P_{mean}\) for all the surge arrester's component used the cable with nominal parameters amounts to 1706.97 W, and compared with the degraded cable sum of 1669.61 W, the relative difference amounts to \(-2.19\%\) for the \(U_{WE2}=6\) kV test case. The small difference between the dissipated average power for the surge arrester with degraded and nominal cable parameters is most likely due to a small change in cable resistance (Table 5, +3.84%). Even though there is a shift in the rise of the surge at the input of the arrester, it is due to changes in the capacitive parameters of the cabling (Table 5), but in the case of the 10 m cable length, it is insignificant. However, the worst case to be considered in terms of the surge arrester's performance is a 10 m long connecting cable. Analyses related to the impact of longer cable sections are planned for the future.
# Electrically Tunable Perfect Terahertz Absorber Using Embedded Combine Graphene Layer
###### Abstract  
Graphene is a powerful 2-D matter with the capability of extraordinary transparency, and tunable conductivity is employed in emerging optoelectronics devices. In this article, the design of an electrically tunable graphene-based perfect terahertz absorber is proposed and evaluated numerically. The introduced structure is composed of two graphene layers with a sharp absorption peak in the terahertz band. These graphene layers are combine and stripline separated by the insulator substrate. The position of the absorption peak is tunable on the absorption band by means of manipulation in geometric parameters of the combline graphene layer. Furthermore, the intensity and frequency of the absorption peak can be flexibly modulated by varying Fermi potential of the combline graphene layer, which can be controlled through external DC voltages without the need of changing the geometry of the structure. It is shown that the absorption band can be tuned in the bandwidth from 5 to 15 in terahertz. The findings of this paper can promote a new perspective in designing perfect ribbon absorbers based on graphene properties that can be utilized for future photodetectors, solar cells, and thermal sensors with an absorption intensity above \(2\times 10^{5}\) (nm\({}^{2}\)) with narrow absorption bandwidth of 0.112 THz.  
graphene; perfect absorber; plasmon; fermi energy; tunable +
Footnote †: journal: Applied Physics Letters  
15 October 2021  
17 November 2021  
1
# Mineral Composition of _Chelidonium majus_ L. and Soils in Urban Areas
###### Abstract  
_Chelidonium majus_ L. is a species with a wide medicinal use, commonly found in anthropogenically degraded habitats, forest edges, and urban parks. This study aimed to determine the chemical composition of the leaves, stems, and roots of _Ch. majus_ and the soil in its rhizosphere in terms of the content of the main elements (Fe, Ca, P, Mg, Al, Na, K, S), trace elements and rare earth minerals (Ti, Mo, Ag, U, Au, Th, Sb, Bi, V, La, B, W, Sc, Tl, Se, Te, Ga, Cs, Ge, Hf, Nb, Rb, Sn, Ta, Zr, Y, Ce, In, Be, and Li), and their comparison in the parts analyzed. The study was conducted in five urban parks in southern Poland in a historically industrialized area. The results showed that Ca has the highest content among the macroelements. Its leaf content ranges from 24,700 to 40,700 mg\(\cdot\)kg\({}^{-1}\), while in soil, it ranges from 6500 to 15,000 mg\(\cdot\)kg\({}^{-1}\). In leaves, low values of Al (100-500 mg\(\cdot\)kg\({}^{-1}\)) and Na (100 mg\(\cdot\)kg\({}^{-1}\)) were found in comparison to the other elements tested, while high values of Al (5100-9800 mg\(\cdot\)kg\({}^{-1}\)) were found in soils. Among the macroelements in the _Ch. majus_ stems, K showed the highest concentration (>100,000 mg\(\cdot\)kg\({}^{-1}\)), while the Ca content was 3-4 times lower in the stems than in the leaves. Rhizomes of _Ch. majus_ accumulate the most K and Ca, in the range of 22,800-29,900 mg\(\cdot\)kg\({}^{-1}\) and 5400-8900 mg\(\cdot\)kg\({}^{-1}\), respectively. Fe and Al in all locations have higher values in the soil than in the tissues. In turn, the content of Ca, P, Mg, K, and S is higher in plants than in the soil. Determining the elemental content of medicinal plants is important information, as the plant draws these elements from the soil, and, at higher levels of toxicity, it may indicate that the plant should not be taken from this habitat for medicinal purposes.  
greater calendine; elemental composition; chemical composition of leaves; trace elements; urban soil +
Footnote †: journal: Applied Sciences
## 3 Results
### Fault Data Analysis using a Rose Diagram, Histogram, and Stereonet  
Once the fault surfaces are automatically generated, the immediate challenge is to reduce and simplify the structural framework by sorting, organizing and merging. To control the discontinuities, a filtering option is available with fault data analysis. Stereonet, Histogram, and Rose diagrams (dip and strike) (Figure 11) are very useful tools that offer a lot of customizable options to keep or eliminate discontinuities with full user control. These are interactive and provide control over discontinuities based on dip, azimuth, surface area, and confidence. For instance, the Rose diagrams (Figure 11a,b) record and show the number of samples which have a thinned fault likelihood value above a predefined threshold. The diagrams are divided into several sectors representing strike and/or dip angles/directions. The color, radius, and length of each sector signify the information like the number of samples, dip angle range, and sample count. The results of the extracted faults were displayed on the Stereonet (Figure 11c), which showed more than 500 fault patches scattered in different orientations. Based on various available filtering criteria like dip, azimuth, and surface area, the results showed that most patches were clustered in the north-south direction with a dip ranging from 60 to 90 degrees. The histogram shows (Figure 11d) that the surface area of the selected patches ranges from 8000-30,000 m\({}^{2}\). Figure 12a shows the application of these tools where the filter based on fault size and dip direction has eliminated all minor discontinuities, whereas major fault surfaces have been retained. Additionally, fault surfaces can also be picked/deleted and merged manually.  
Figure 11: Fault data analysis tools. (**a**) Rose diagram (strike) and (**b**) Rose diagram (dip) provide information about dip/strike angle and direction of fault patches based on sector division. (**c**) Stereonet shows orientation, dip, and the azimuth of the patches interactively. (**d**) Histogram offers the filter options like dip, azimuth, surface, and size of the patches. It can also be used interactively to filter the discontinuities based on the mentioned criteria.
# Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms
## 6 Conclusions and Future Work
### Conclusions  
SAR performed in two phases is summarized pictorially in Figure 20. The search starts with a victim being trapped in the maze-like environment, broadcasting an SOS signal. In Phase I, the search agents proactively explore the environment in search of the victim, using the iAA algorithm. Once the victim is spotted, the agents switch to the Phase II, and find the shortest routing path to communicate information about the victim's location to the base station, relying on specific implementation of Dijkstra algorithm and the results of the Phase-I search. Three different forms of the Ant Algorithm were explored and tested to devise the optimal search method. We studied the influence of the maze size and complexity, as well as the number of the search agents, together with the study of energy resources' dependence on problem and environment parameters. In ongoing efforts, we study the dynamic (time-varied) injection of the agents as a possible path towards additional performance improvement. We are in contact with agencies that may use this approach in their SAR training.
# BODIPY-Based Nanomaterials--Sensing and Biomedical Applications
## 2 Metallic Nanoparticles@BODIPY
### Cancer Diagnosis and Therapy
#### 2.2.4 Other Metallic Nanoparticles
The latter ones were decorated with assembled heretofore aza-BODIPY (AB) structures, resulting in 1.38 wt% loaded nanoplatforms (confirmed via thermal gravimetric analysis) used to arrange 5 mg/mL suspension for further experiments. SEM and TEM studies unveiled that these heterogeneous nanoplatforms constitute nanospheres rich in mesopores with an approximate size of 100 nm (the hydrodynamic size was 155 nm if dispersed in deionized water). At the same time, the Brunauer-Emmett-Teller (BET) method was availed of to determine their surface area and defined it as 126.5 m\({}^{2}\)/g. Additionally, the UV-vis absorption spectrum showed two distinctive peaks at 389 and 820 nm. Photothermal and photodynamic qualities were measured under single-wavelength NIR light laser irradiation. As a result, MTAB irradiated with 808 nm laser light (0.5 W/cm\({}^{2}\), 10 min) caused the most eminent effectiveness in terms of tumor cell extermination according to cytotoxicity outcomes, demonstrating 33.98% photothermal conversion efficiency and significant increase of ROS generation (observed via confocal fluorescence microscopy). Continuous (14 days) observation of mice inflicted with MTAB-mediated phototherapy led to the conclusion of a 94.8% tumor eradication rate, while the mice deprived of NIR irradiation suffered from cancer progression: without photocatalytic stimuli, MTAB did not provide any impact on the tumor growth [83]. To sum up:  
* Gold nanoparticles/BODIPY conjugates were applied in in vitro studies as Raman or fluorescent sensors or co-photosensitizers. * Fluorescent probes were obtained by combining magnetic nanoparticles and BODIPY dyes. * Zirconium-based metal-organic frameworks functionalized with BODIPY dyes were used as photosensizers in in vitro photocytotoxicity studies and revealed high photoactivity. Figure 25: Schematic representation of the chemical structure of “black” titanium(IV) oxide nanoparticle functionalized with aza-BODIPY dyes through adsorption of the dye on the nanoparticle surface [83]. * A high antibacterial effect was achieved with the use of Ag nanoparticles/BODIPY dyes in photodynamic inactivation in vitro tests.