esa-sceva/satcom-chunk-collection huggingface dataset:
# Study of a Miniaturizable System for Optical Sensing Application to Human Cells
## 3 Results
### Tumor Cell Fluorescent Time-Lapse Analysis  
#### 3.2.1 LoVo Uptake of Ru(bpy)\({}_{3}\)\({}^{2+}\)  
After the definition and full characterization of a valid approach for the cellular uptake of Ru(bpy)\({}_{3}\)\({}^{2+}\) in HDFs, we moved to a first application of this intracellular sensing method to a human tumor analysis across time, by using the epithelial cells of colon adenocarcinoma LoVo.  
To this purpose, we labeled LoVo cells with the same protocol used for HDFs, getting the results below. Fluorescence microscopy images of LoVo cells exposed to Ru(bpy)\({}_{3}\)\({}^{2+}\) are shown in Figure 8. Control cells (Figure 8A) exhibited only the intrinsic weak green signal after excitation with blue light (488 nm), while cells treated with the fluorophore (Figure 8B) showed the Ru(bpy)\({}_{3}\)\({}^{2+}\) fluorescent signal.  
The magnification of microscopy revealed the intracellular distribution of fluorophore, confirming the success of the uptake procedure and its reproducibility in a different cell model.
## 2 Types of Nanomaterials Used in Cosmetic Formulations
### Dendrimers  
Dendrimers are highly branched nanostructures, consisting of a central core, branches, and terminal functional groups at the outer surface that govern their complexation with the payload [73]. As they show the capacity to modify the release profile of loaded APIs, they have been proposed as carriers in cosmetic formulations. Additional properties that make them interesting delivery systems are the monodispersity, polyvalence, stability, and the easy functionalization. Besides, during synthesis their molecular weight and size can be controlled, together with the degradation profile of the final assembly. Due to the dendrimers' versatility, both hydrophilic and hydrophobic APIs, either incorporated in the inner core or attached onto the surface [74]. The company L'Oreal Paris developed a formulation that contains hyperbranched polymers capable to form a film if deposited on a substrate which can be used in some cosmetics, for example, eye mascara or in the nail polish products [75]. L'Oreal has other formulation with dendrimers in the composition, as is the case for a taming agent used in the artificial skin tanning. Another company, Unilever, developed dendrimers hydroxyl-functionalized to produce formulations to be used in different ways, such as sprays, gels, or lotions [76].
# An Empirical Study on Software Defect Prediction Using CodeBERT Model
## 8 Threats to Validity  
Programming language. Our dataset comes from the PROMISE repository, which is written in Java. However, our method is not limited to programming languages.  
Dataset size. Our dataset uses a subset of the PROMISE repository, which is also used in previous work. Due to the limit that the project must be open-source, some datasets, i.e., the NASA dataset, are unavailable.  
Selection of the CodeBERT model. We choose the standard CodeBERT model based on the RoBERTa architecture. Although other forms of CodeBERT models are available, e.g., graphCodeBERT, we believe the chosen model is powerful enough in our study.
## 3 Results and Discussion
### Melissopanlyological Analysis
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**ID** & **Declared Honey Type** & \begin{tabular}{c} **Actual Pollen Identified Confirming** \\ **the Sample Labels (\%)** \\ \end{tabular} & \begin{tabular}{c} **Other Types of Pollen Identified in** \\ **the Samples** \\ \end{tabular} \\ \hline H1 & Linden, Organic & Malvaceae: _Tilia_ spp. 83.65\% & Astragalus, Asteraceae, Apiaceae, Fabaceae, _Robinia pseudoacia_ \\ \hline H2 & Mixture & \begin{tabular}{c} Brasiscaceae: _Brassica_ 20\%, Asteraceae \\ 20\%, Rosaceae 15\%, Fabaceae 10\%, Apiaceae 2\% \\ \end{tabular} & \\ \hline H3 & Acacia & Fabaceae: _Robinia pseudoacia_ 21.0\% & Rosaceae, Apiaceae, Brassicaceae, Lamiaceae \\ \hline H4 & Mountain Honey & \
\begin{tabular}{c} Brasiscaceae: _Brassica_ sp. 15\%, \\ Fabaceae 25\%, Rosaceae 5\%, Asteraceae 8\%, Lamiaceae 10\%, Plantaginaceae 2\%, Linaceae 1\%, Apiaceae 4\%, Solanaceae 2\%, Scrophulariaceae: _Verhascum phlomoides_ 3\% \\ \end{tabular} &
\begin{tabular}{c} Rosaceae, Apiaceae, Brassicaceae, \\ Lamiaceae \\ \end{tabular} \\ \hline H5 & Citrus & Rutaceae: _Citrus_ 57.60\% \\ \hline H6 & Raspberry & Rosaceae: _Rubus laevis_ 26\% \\ \hline H7 & Knoted & Poligonaceae: _Fallopia_ sp. 13.86\% & Tiliaceae, Asteraceae \\ \hline H8 & Linden & Malvaceae: _Tilia_ sp. 2.10\% \\ \hline H9 & Oak Honey (Honeydew) & Fagaceae: _Quercus_ sp. \\ \hline H10 & Thyme & Lamiaceae: _Thymus_ sp. 8.10\% \\ \hline H11 & Linden & Malvaceae: _Tilia_ 5.40\% \\ \hline H12 & Linden & Malvaceae: _Tilia_ 5.10\% \\ \hline H13 & Chestnut & Fagaceae: _Castanea sativa_ 81.80\% \\ \hline H14 & Chestnut & Fagaceae: _Castanea sativa_ 75.30\% \\ \hline H15 & Chestnut & Fagaceae: _Castanea sativa_ 81.30\% \\ \hline H16 & Chestnut & Fagaceae: _Castanea sativa_ 79.10\% \\ \hline H17 & Chestnut & Fagaceae: _Castanea sativa_ 71.40\% \\ \hline H18 & Oak Honey (Honeydew) & Fagaceae: _Quercus_ sp. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The results of melissopalynological analyses, compared to the described label of the commercial samples and the actual content of predominant pollen. to the Romanian legislation standard for quality requirements at delivery by producers (SR 784-1:2009) which specifies a minimum of 20% pollen content, with 20% for acacia and 25% for linden honeys [36].
# RPC-EAU: Radar Plot Classification Algorithm Based on Evidence Adaptive Updating
## 3 Proposed Method
### Design and Update of Confidence Classification Network  
In traditional typical radar plot recognition algorithms, the binary classification is widely studied. These algorithms are rapid and simple in determining whether a certain radar plot is target or clutter in [3; 4; 5; 6; 7]. Of course, such rapid decision making inevitably increases some misjudgments. So, we added an uncertain class to this radar plot classification problem by drawing on the concept of belief functions. In this way, radar plots that are difficult to make decisions can be first classified as uncertain. Then, through further in-depth data feature analysis or classifier optimization, more reasonable judgments can be made. Therefore, the classifier design and optimization in the proposed algorithm are presented in detail here.
# Performance Analysis of On-Demand Scheduling with and without Network Coding in Wireless Broadcast
## 4 Proposed Heuristic Coding-Based On-Demand Broadcast
### Scheduling Algorithms with Heuristic Coding Implementation
#### 4.2.3 Stretch Optimal Algorithms  
* LTSF [29]: LTSF broadcasts the data item with the largest total current stretch. The network coding version of LTSF, needs to select the largest clique \(\delta\) with the maximum \(\frac{\sum_{v_{i}\in\delta}t_{i}}{max_{v_{i}\in\delta}\{\frac{1}{B}\}}\) value, where \(\sum_{v_{i}\in\delta}t_{i}\) is the total waiting time of the vertices in \(\delta\) and \(max_{v_{1}\in\delta}\{\frac{1}{B}\}\) is the service time of the vertices in \(\delta\). Please note that the service time of the coded packet will be the service time of the largest data item in the clique. In the heuristic coding implementation (denoted by LTSF_N), the system first finds the selected vertex \(v_{ps}\) with the largest total current stretch \(\left(max\left\{\frac{\sum t(d_{s})}{\frac{1}{B}}\right\}\right)\) for the data item \(d_{s}\). In Step 2 of Algorithm 1, the \(v_{ps}\) selection is done by finding the vertex with the maximum \(\left\{\frac{\sum t(d_{s})}{\frac{1}{B}}\right\}\) value, i.e., \(v_{ps}=\left\{v_{ij}|\left\{\frac{\sum t(d_{j})}{\frac{1}{B}}\right\}\right\}= max\left\{\left\{\frac{\sum t(d_{1})}{\frac{1}{B}}\right\},\left\{\frac{\sum t(d_{2})}{ \frac{1}{B}}\right\},\cdots,\left\{\frac{\sum t(d_{m})}{\frac{1}{B}}\right\},1 \leq i\leq n\right\}\right\}\). Then Step 3 searches for the maximal clique \(\delta_{max}^{v_{ps}}\) to ensure that the encoded packet \(\beta(\delta_{max}^{v_{ps}})\) consists the requested data item with the largest total current stretch.
* STOBS [28]: STOBS broadcasts the data item with the largest \(\frac{R\times W}{S}\) value, where \(R\), \(W\) and \(S\) denote, respectively, the number of pending requests, waiting time of the earliest pending request and the item size. The network coding version of STOBS, needs to find the largest clique \(\delta\) with the maximum \(\frac{|\delta|*max_{v_{i}\in\delta}t_{i}}{max_{v_{i}\in\delta}t_{i}}\) value, where \(max_{v_{1}\in\delta}t_{i}\) and \(max_{v_{1}\in\delta}t_{i}\) are respectively the maximum waiting time and the maximum item size among all the vertices in \(\delta\). Please note that also denotes the size of the encoded packet. In the heuristic coding implementation (denoted by STOBS_N), the system first finds the selected vertex \(v_{ps}\) with the maximum \(\frac{N(d_{s})\times t_{p}}{l_{s}}\) value. In Step 2 of Algorithm 1, the \(v_{ps}\) selection is done by finding the vertex with the maximum \(\frac{N(d_{s})\times t_{p}}{l_{s}}\) value, i.e., \(v_{ps}=\bigg{\{}v_{ij}\,|\,\frac{N(d_{j})\times t_{i}}{l_{j}}=max\bigg{\{} \frac{N(d_{(r_{1})})\times t_{1}}{l_{r(1)}},\frac{N(d_{(r_{2})})\times t_{2}}{ l_{r(2)}},\cdots,\frac{N(d_{r(n)})\times t_{n}}{l_{r(n)}},1\leq r,j\leq m\bigg{\}} \bigg{\}}\). Then Step 3 searches for the maximal clique \(\delta^{v_{ps}}_{max}\) to ensure that the encoded packet \(\beta(\delta^{v_{ps}}_{max})\) consists the requested data item with the largest \(\frac{R\times W}{S}\) value.
# Hybrid Modulation Strategy to Eliminate Current Distortion for PV Grid-Tied H6 Inverter
## 1 Introduction
To address these requirements this paper presents a hybrid modulation scheme for a H6 inverter, which allows for high efficiency, elimination of common mode leakage currents, and provision of reactive power with low current distortion. It can also be shown that the hybrid modulation scheme can be applied to other topologies such as the H5 (topology name) and HERIC (topology name) [13]. The paper is structured as follows: Section 2 reviews the operation of the H6 inverter topology with Modulation Mode I (MMI) as previously proposed in [11] and illustrates why this modulation mode cannot output reactive current without zero crossing distortion. Section 3 introduces the new hybrid modulation scheme which can achieve reactive current output under the full power factor range without distortion. The application of the hybrid modulation scheme to the H5 and HERIC converter topologies is also discussed. Simulations and experimental results to validate the approach are presented in Sections 4 and 5 respectively. Finally, Section 6 discusses the conclusions of the paper and scope for future work.
# Polymeric Nanoparticles--Tools in a Drug Delivery System in Selected Cancer Therapies
## 3 Nanoparticles in Cancer Therapy--Passive and Active Mechanisms
### Passive Mechanism  
As a tumor grows, the architecture at the tumor site is rearranged [31]. A so-called tumor microenvironment (TME) emerges, which is composed of multiple cell types, i.e., fibroblast-associated cells (CAFs), tumor-associated macrophages (TAMs) and other immune cells [31]. The possibility of tumor proliferation and the influx of cells into the TME is mainly due to the formation of new blood vessels [23; 31; 32]. The rate of their formation is rapid as a result of the irresistible need to supply nutrients and oxygen necessary for its growth [23; 32]. The consequence of this is the appearance of abnormalities in the endothelium of blood vessels [23; 32]. They become more permeable, allowing polymeric nanoparticles to enter the tumor more efficiently. Increased lymphatic drainage due to abnormal vascular structure further contributes to prolonged retention of the nanoparticle inside the tumor structure [21; 23; 32]. Both of these processes contribute to the so-called enhanced permeability and retention (EPR) effect, which directs polymeric nanoparticles to the tumor site [21; 23; 32]. PNPs up to 200 nm in size are assumed to diffuse best through the damaged endothelium [15]. However, this mechanism has its limitations mainly due to individual occurrences (differences in vascular permeability, cell receptor expression, etc., between patients with the same type of cancer), in which the EPR effect may not be present in humans in solid tumors or insufficiently so that diffusion of nanoparticles
# Resilience in the Cyberworld: Definitions, Features and Models
## 3 Key Actions and Attributes
[PERSON] [13] also mentions diversity as another important basic property. Diversity can be understood here as a basic idea of redundancy, because according to [PERSON], diversity in a system (of hardware components, for example) should prevent the occurrence of single point of failure. In [16], it is also described that reliability is a key feature of resilience. The ability to detect a fault before it occurs is also essential. However, this only refers to faults that can be anticipated on the basis of existing information. A resilient system must be able to minimize the negative effects of a disturbance by anticipating it. This is achieved by constantly updating information about the disturbances that have already occurred and been treated. This process can be understood as the ability to evolve. According to [19], the following attributes are essential for a resilient system: reliability, evolvability and integrity. Reliability and evolvability are related to resilience, as described in the previous definitions. Integrity, according to [PERSON] [19], means that a resilient system does not lose its intention after adaptation or application of changes regarding a failure. This refers mainly to its functional and nonfunctional characteristics. In the publications [6; 7; 25], the following abilities: anticipate, resist, recover and adapt, are directly mentioned as the four basic attributes, or, as in NIST, the four basic goals of resilience. Publications [8] and [9] extend this approach to include the ability to detect a threat. Detection is important for the self-assessment of a system, because if a threat cannot be detected, the system cannot initiate appropriate countermeasuresDiscussion of the Relationships between Key Actions and Attributes  
The attributes are directly related to the key actions. This relationship becomes important when it comes to the concrete design or practical modeling of cyber-resilient systems. In order to design a system to be cyber-resilient or to make an existing system cyber-resilient, it must first be examined how, for example, the ability to resist can be achieved or improved. At this point, attributes must be considered. For example, to make a system resistant, methods can be used that increase robustness. Methods of reliability and security are also helpful here. It is to be considered here that the use of several different methods can lead to dependencies, which must be considered. For example, a method that makes a system more adaptable could at the same time reduce its security. Table 3 shows the mapping of the mentioned attributes to the key actions according to our understanding. The various key actions have interdependencies, which need to be taken into account when building a theoretical model of cyber-resilience. In the following section, such models [6, 8, 9] are briefly presented.
# Drilling Fluid and Cement Slurry Design for Naturally Fractured Reservoirs
## 5 Lost Circulation While Cementing through Naturally Fractured Reservoirs
### Cement Slurries for Primary Cementing through Fractured Formations  
In order to reduce or prevent the loss of a cement slurry in naturally fractured formations or highly permeable rocks, various methods and techniques of cementing as well as different lightweight and ultra-lightweight cement slurries can be used, including cement slurries with microspheres, thixotropic cement slurries, cross-linked cement slurries, foamed cement slurries, gel-cement slurries, and fiber-cement slurries [20; 49; 84; 101; 102; 103].
# An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery
###### Abstract  
Surface water bodies, such as rivers, lakes, and reservoirs, play an irreplaceable role in global ecosystems and climate systems. Sentinel-2 imagery provides new high-resolution satellite remote sensing data. Based on the analysis of the spectral characteristics of the Sentinel-2 satellite, a novel water index called the Sentinel-2 water index (SWI) that is based on the vegetation-sensitive red-edge band (Band 5) and shortwave infrared (Band 11) bands was developed. Four representative water body types, namely, Taihu Lake, Yangtze River, Chaka Salt Lake, and Chain Lake, were selected as study areas to conduct a water body extraction performance comparison with the normalized difference water index (NDWI). We found that (1) the contrast value of the SWI was larger than that of the NDWI in terms of various water body types, including pure water, turbid water, salt water, and floating ice, which suggested that the SWI could achieve better enhancement performance for water bodies. (2) An effective water body extraction method was proposed by integrating the SWI and Otsu algorithm, which could accurately extract various water body types with high overall accuracy. (3) The method effectively extracted large water bodies and wide river channels by suppressing shadow noise in urban areas. Our results suggested that the novel method can achieve efficient water body extraction for rapidly and accurately extracting various water bodies from Sentinel-2 data and the novel method has application potential for larger-scale surface water mapping.  
Sentinel-2; water body extraction; spectral characteristics analysis; water index; Otsu algorithm +
Footnote †: journal: 11 June 2021
# Applying CRISPR Technologies for the Treatment of Human Herpesavirus Infections: A Scoping Review
## 4 Discussion
### Delivery of CRISPR Systems  
Multiple delivery vectors were used in the different studies, including viral vectors such as lentivirususes, AAVs, or gene drive viruses, and non-viral vectors such as plasmid transfection, RNP electroporation or nucleofection, nanoparticles, liposomes, and extracellular vesicles. Each delivery method has its pros and cons. First, the chosen vector should achieve efficient transfection or transduction of the CRISPR system intracellularly. In ex vivo and in vitro settings, non-viral methods such as DNA or RNP electroporation have demonstrated high efficiency and are frequently used, for example, in the optimization of VSTs (e.g., _NR3C1_ knockout strategies [77]) or the generation of CAR T cells [79; 81; 82]. However, these techniques are not readily applicable to in vivo contexts, where tissue barriers complicate delivery to herpesvirus reservoirs like sensory ganglia and B lymphocytes. In such cases, viral vectors are often favored due to their superior transduction efficiency, capacity to traverse tissue barriers, and ability to sustain gene expression over time, as demonstrated in several in vivo studies [49; 50; 59; 83; 84; 85]. Administering delivery vehicles locally (e.g., intrastromally in the eye) or decorating delivery vehicles with targeting ligands could be another strategy to enhance tissue penetration, while also increasing the specificity of CRISPR delivery and reducing off-target effects in healthy host cells. This could be achieved by adding specific binding ligands such as single-chain variable fragments (scFv) or nanobodies to delivery vehicles, a process typically easier in non-viral vectors, even though viral glycoproteins can also be modified with these ligands [86; 87; 88; 89; 90]. For instance, the targeting specificity of extracellular vesicles was significantly enhanced by fusion of a neuro-targeting RVG peptide with a membrane protein of the vesicle [58]. Notably, a vector specifically targeting herpesvirus-infected cells remains to be developed and could largely decrease toxicity toward healthy cells and thus biosafety concerns in general. This is largely due to a lack of biomarkers expressed on infected cells, especially latently infected cells [91]. Third, the packaging capacity of the vector should be large enough to package both the gRNAs and the Cas protein. The limited packaging capacity of the frequently used AAV vector could cause difficulties in delivering multiple gRNAs in a multiplex approach. Fourth, the duration of Cas expression intracellularly should be carefully considered to target enough viral genome copies for efficient antiviral activity while minimizing biosafety concerns. A more transient or HSV-1-specific Cas expression, as achieved with non-viral vectors, HELP particles, or the ALICE system, is more desirable than constitutive Cas expression to limit the chance of off-targets and the induction of host immune responses.
# Experimental Studies of Scale Effect on the Shear Strength of Coarse-Grained Soil
###### Abstract
Thus, it is necessary to conduct quantitative experimental investigations on the influence of the scale effect on the mechanical characteristics of CGS. The main reason why it is difficult to quantitatively express the relationship between the mechanical characteristics of scaled and in situ soil is that there is no accurate and unified mathematical expression of gradation structure. [PERSON] et al. [27] sorted out and summarized the soil grading curve types in engineering projects, and proposed a new gradation equation suitable for CGS, as follows:  
\[P=\frac{1}{(1-e)\Big{(}\frac{d_{\text{max}}}{d}\Big{)}^{n}+b}\times 100\% \tag{1}\]  
where \(P\) denotes the content of soil particles that are smaller than particle size \(d\) (%); \(d\) represent the particle size of soil (mm), \(d_{\text{max}}\) is the maximum particle size of soil (mm); and \(e\) and \(n\) are the parameters of the gradation equation, which determine the shape and inclination of the grading curve, respectively (referred to as the gradation structure). The gradation parameters of coarse-grained soil in high-earth rock dam engineering are concentrated in the region of \(-2<e<1\) and \(0<n<2\), which includes both well-graded and poorly graded cases. The gradation of most coarse grains can be described by adjusting the combination of parameters \(e\) and \(n\). According to the relevant literature [26; 28], regardless of which scaling method is adopted [1], the differences between the scaled and the in situ soil after scaling are mainly the gradation structure and the maximum particle size. As a result, the scale-induced effect can be regarded as the result of the coupling effect of the maximum particle size and gradation structure of the soil sample. Therefore, in this paper, 24 groups of samples of CGS are designed by changing the maximum particle size or gradation structure. A series of large-direct shear tests on samples prepared with the same relative compactness is conducted to explore the relationship of the shear strength of scaled and in situ soil. Furthermore, the impact of gradation structure and maximum particle size upon the CGS is studied by a single variable method, and the relational equation of shear strength direct shear of scaled and in situ soil is established. Consequently, as long as a series of shear strength tests of laboratory scaled samples are carried out following the on-site graduation to acquire the material parameters for the equal soil types, CGS with any graduation can be predicted.