esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In this paper, an optically transparent metamaterial broadband absorber with high transparence, low profile, polarization insensitiveness and oblique incidence stability is proposed, as confirmed by both the simulation results and the experimental measurements. The thickness of the absorber is only 0.088\(\lambda\) at the lowest cutoff frequency. The measured bandwidth with an absorptance of more than 85% ranges from 6.0 GHz to 16.7 GHz. The measured average optical transmittance is 85.7%. Less thickness can effectively reduce the weight of the absorber, and higher transparency can significantly improve its optical use in practical applications. In addition, all ITO patterns are located inside the structure, which can significantly increase its service life. The proposed transparent absorber has potential utilizations in practical applications in the observation windows in communication vehicles, electromagnetic shielding rooms and transparent radio-frequency identification systems.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Absorber** & **Absorption Band** & **Relative** & **Thickness** & **Relative** & **Optical** \\  & **above 85\% (GHz)** & **Bandwidth 1** & **(mm)** & **Thickness 2** & **Transmittance** \\ \hline Ref. [39] & 3.6–19.4 & 5.39 & 8.6 & 0.103 & 62–75\% \\ Ref. [40] & 8.6–11 & 1.28 & 3.6 & 0.103 & 80–85\% \\ Ref. [41] & 12–14.3 & 1.19 & 7.75 & 0.310 & 73–82\% \\ Ref. [37] & 5.5–19.7 & 3.58 & 5.5 & 0.101 & 82\% \\ Ref. [38] & 4.6–18 & 3.91 & 6.76 & 0.104 & 75\% \\ This work & 6.0–16.7 & 2.78 & 4.42 & 0.088 & 85.7\% \\ \hline \hline \end{tabular}  
* Relative bandwidth is defined as the ratio of the highest frequency and the lowest frequency in the band when absorption is better than 85%; 2 Relative thickness is defined as the ratio of the thickness and wavelength of the lowest absorption frequency when absorption is better than 85%.  
\end{table}
Table 2: Comparison with other transparent broadband absorbers.  
Figure 11: The measured optical transmittance of the fabricated absorber.  
**Author Contributions**: Conceptualization, H.X.; methodology, H.X. and C.W.; validation, R.Q. and C.W.; investigation, R.Q.; writing--original draft preparation, H.X.; writing--review and editing, C.W. and R.Q.; visualization, R.Q.; supervision, M.L.; project administration, M.L. All authors have read and agreed to the published version of the manuscript.  
**Funding**: This research received no external funding.  
**Conflicts of Interest**: The authors declare no conflict of interest.
## 3 DeepPrevention Overview  
### Data Description  
We extracted the medical data for this study from South Korea's NHIS database for 2002-2013, converting the data to OMOP-CDM format. A total of 29,557 atrophic gastritis patients were identified, of whom 771 had progressed to gastric cancer. For our study purposes, we restricted the sample to patients aged 40 to 75, which resulted in a data set of 18,846 patients with atrophic gastritis, among whom 610 had progressed to gastric cancer. As our main consideration was the effect of lifestyle habits on the development of gastric cancer in patients with atrophic gastritis, we inputted the following 13 features into the prediction model:  
* Demographics: age, sex, test age at which gastric cancer was diagnosed
* Frequency of smoking: ranges included less than half a pack of cigarettes a day, less than one pack, more than one pack but fewer than two, more than two packs
- Smoking duration: ranges included fewer than 5 years, more than 5 years but fewer than 9, more than 10 years but fewer than 19, more than 20 years but fewer than 29 years, more than 30 years
- Current smoking status: yes for smokers and no for non-smokers
* Drinking habits: categorical values included ranges such as two or three times in a month, one or two times in a week, three or four times in a week, and every day
* Regular exercise: binary yes or no
* Income: index into 10 levels by 10% according to the total household income
* Family history of cancer: binary yes or no
* Body mass index: weight in kilograms divided by the square of height in meters
* Number of endoscopic screening tests
* Current status: 0 for before gastric cancer diagnosis and 1 for after gastric cancer diagnosis  
To explore and understand the characteristics of the data set used in this study, two-dimensional visualization was performed using t-Stochastic Neighbor Embedding (t-SNE) [34], as shown in Figure 1. t-SNE reduces high dimensional data to a two-dimensional space, i.e., component 1 and component 2, while preserving the distance between points in the high dimensional space. The red spots in Figure 2 represent gastric cancer patients, and the blue spots represent atrophic gastritis patients. From the visualization of our data set, we found that the complexity of boundaries separating classes was extremely high, and the problem of class imbalance was serious.  
Figure 1: t-SNE visualization.  
In our data set, only 3% of patients with atrophic gastritis developed gastric cancer. It is known that over-sampling methods such as the Synthetic Minority Oversampling Technique (SMOTE) [35] and Adaptive Synthetic Sampling (ADASYN) [36] in extremely class-imbalanced data cause overfitting and an increased training time due to the increased size of the training set [37]. Recently, research on deep learning with class imbalance has attracted much attention [38]. It was noted that very deep neural networks are effective in highly imbalanced class distribution [39]. Therefore, to solve the class imbalance problem, we proposed a deep recurrent neural network with eight hidden layers to capture the features of the minority class at the algorithm level.
## 1 Introduction
[10; 11] proposed measures such as grouting, to strengthen the rock mass, and optimizing the shaft excavation method, to maintain stability of the rock mass. In recent years, many scholars have continued to optimize shaft-surrounding rock support technology using steel structures incorporated into the shaft support system. [PERSON] et al. [12; 13] developed a new support form of steel structure concrete. Their research showed that compared with a single concrete structure, such steel structure concrete has higher compressive strength and better support for vertical shafts. [PERSON] et al. [14; 15], based on engineering reality combined with indoor tests and field survey methods, proposed a U-shaped steel arch and cast concrete shaft support technology. [PERSON] et al. [16; 17; 18] adopted a numerical calculation method to analyze the large deformation mechanism of a soft rock roadway in vertical and inclined shafts and correspondingly proposed the use of bolt-shotcrete support technology, which has been successfully applied in practical engineering. Previous studies have proposed useful solutions to technical problems involving the deformation control of deep shaft-surrounding rock. However, most did not consider the strain-softening mechanical behavior of deep shaft-surrounding rock, and no specific post-peak rock mass strain-softening mechanical model has been established to reveal the post-peak rock mass mechanical response. The post-peak strain-softening characteristics of rock mass are the basis for more accurate analysis of shaft stability and the design of safe and reliable supporting structures. Therefore, it is of great significance to study the post-peak strain-softening characteristics of rock mass. This paper analyzes the supporting structure interaction mechanism in terms of the stability of deep shaft-surrounding rock and softening characteristics of deep rock mass. A combination of related theories is used to establish an equivalent joint strain-softeningmodel and to characterize the post-peak strain-softening characteristics of rock mass. The relevant surrounding rock support technology is adapted to the post-peak strain-softening characteristics of deep rock mass, and composite support technology is proposed for the deep well surrounding rock, which involves high-strength anchor cables, well circles, and shotcrete. The developed support technology is applied to the Heilongjiang Niaoshan coal mine project. The results show that the surrounding rock deformation is controlled within a safe range, confirming the field application results. The concepts and support technology results presented here provide a useful reference for future mine engineering support design.
# Principles and Characteristics of Different EDM Processes in Machining Tool and Die Steels
## EDM Process Details
### Performance Measures/Parameters  
Performance parameters are the factors that measure performance of the EDM process. There are numerous parameters, but the main performance measure parameters are MRR, TWR, and surface quality. The MRR is the erosion rate of workpiece surface; it also defines the measure of the machining speed. A large number of studies were performed with a focus on ways and techniques that result in an improvement in MRR [87; 88; 89; 90; 91]. On the other hand, TWR is a performance measure for the erosion rate of the tool electrode. This parameter has a direct influence on the geometry and accuracy of the machined cavity due to a continued change in the electrode profile during the machining process. Apart from the accuracy and geometry of the part being machined, it also affects the life of the tool. A focus on reducing TWR is extremely important because wear of the electrode affects the electrode profile and leads to lower accuracy [85; 92; 93]. The surface integrity is another important response which is representative of machined surface quality or conditions. The surface quality is a composite characteristic with components such as SR, extent of the heat-affected zone (HAZ), recast layer thickness, and micro-crack density. Many research studies were introduced to explore utilization of the EDM process in surface treatment, and they reported the surface effectiveness caused by the process [94].
## 5 Results and Discussion
### Soda Line Glass
  
As expected from Figure 12a,b, deviations were larger than most values previously calculated. For the 4.7-mm glass plate, Lamb-wave attenuation data agreed with the theoretical prediction better than the test results on the 2-mm sheet. Again, a third order polynomial and a linear fitting equation were used. Averaged results are as follows: \begin{tabular}{c c c c} \hline \hline Wave Mode & Deviation (dB/m) & Percent Deviation (\%) & Data Count \\ \hline Symmetric case 47 mm: & 2.17 & 41.1 & 22 * \\ \hline Asymmetric case 47 mm: & 1.64 & 29.5 & 81 \\ \hline \hline \end{tabular}   
* Data below 600 kHz only. Figure 12: **(a)** Three sets of \(\alpha\)–S\({}_{\rm o}\) values for soda lime glass sheet of 2.0-mm thickness. All with Olympus V103 as Tx and KRN-BB-PC as Rx. Blue dots: Single-cycle sinewave at 600 kHz, Blue squares: Single-cycle sinewave at 750 kHz, Blue triangles: Single-cycle sinewave at 750 kHz, one-surface detection. Calculated \(\alpha\)–S\({}_{\rm o}\) (solid blue curve), \(\alpha\)L and \(\alpha\)T (blue and red dashed lines) are also plotted. Blue dotted curve was also for \(\alpha\)–S\({}_{\rm o}\), but calculated using reduced \(\alpha\)L and \(\alpha\)T (see text). Vertical bar shows 2 \(\times\) dev. **(b)** Two sets of \(\alpha\)–A\({}_{\rm o}\) values for soda lime glass sheet of 2.0-mm thickness plotted in red symbols. Both sets used single-cycle sinewave at 600 kHz with Olympus V103 Tx at 60\({}^{\circ}\) incident angle and KRN-BB-PC Rx. Calculated \(\alpha\)–A\({}_{\rm o}\) (solid red curve), \(\alpha\)L and \(\alpha\)T (blue and red dashed lines) are also plotted. \(\alpha\)–A\({}_{\rm o}\) (red dotted) used reduced \(\alpha\)L and \(\alpha\)T (see text). Vertical bar shows 2 \(\times\) dev. In the 4.7-mm glass plate, deviation values were comparable to those of 6.4-mm Al plate, but percent deviation values were twice or more. Agreement between theory and experiment was poor in the case of the 2-mm glass sheet and was moderate for the 4.7-mm glass plate.
###### Abstract  
Background: The aim of this study was to identify variations in the origins of the anterior branches of the external carotid artery (ECA) and to propose an update of the current classification. Methods: The study included 100 carotids arteries from fifty human donors. Classification of anterior branches of external carotid artery was performed according to [PERSON] et al. (2009). Results: The configuration origins of anterior branches were found as follows: Type I, 82%; Type II, 1%; Type III, 16%. No Type IV was observed. The study identified seven subgroups of anterior branch variations in the external carotid artery. The most frequently observed variations were Subtype Ia in 40% (n = 20) of cases on the right side and Subtype Ib in 38% (n = 19) on the left side. In addition, a rare and previously unclassified configuration was observed in a 72-year-old male donor, where the carotid artery was pentafurucated on the left side. Conclusions: In conclusion, the presence of anatomical variants not previously included in the anterior external carotid artery branching classifications supports the consideration of a revision to the present classification system.  
common carotid artery; carotid bifurcation; superior thyroid artery; lingual artery; facial artery; external carotid artery; anatomical variation; classification updating 2023  
the carotid bifurcation (50.2%); (b) from the common carotid artery (26.6%); (c) from the external carotid artery (23.2%) [9]. Several authors have already described variabilities in the anatomy of the ECA anterior branches (STA, LA, and FA) [1; 2; 3; 4; 6; 8; 10; 11; 12; 13; 14]. [PERSON] et al. (2011) and [PERSON] et al. (2005) have reported variations in the forms of the LFT, thyrolingual trunk (TLT), and thyrolinguofacial trunk (TLFT) [6; 7]. Additionally, several studies have reported different origins for these branches, such as those arising from other carotid arteries or originating from the carotid arterial tree in combination with other arterial trunks [15; 16; 17; 18]. Due to the heterogeneous nature and wide variability of the ECA and its branches, they are clinically significant in radiology and surgery procedures in the neck region [2; 3; 4; 7; 8; 19].  
The purpose of the anatomic dissections performed in this study was to examine various configurations of the origin of anterior branches of the ECA and to suggest a revision to the classification system to include anatomical variations. The findings of this study, along with a review of the literature, were used to develop this updated classification model.
## 4 SIP Protocol Analysis
### SIP Interfaces  
The first step for building our dataset is to identify the source that generates this data. Therefore, we monitored the IMS interfaces to collect all messages that are related to SIP protocol inside the IMS domain. Figure 4 shows the IMS architecture, and the monitored SIP interfaces are highlighted in red. The Interfaces are mentioned below:  
* **Mw Interface**: The interface between S-CSCF/I-CSCF (Interrogating Call Session Control Function) and P-CSCF;
* **Gm Interface**: The interface between Subscriber (Handset) and P-CSCF;
* **Mg Interface**: The interface between Mobile Switching Center (MSC) (circuit switching domain) and I-CSCF;
* **ISC Interface**: The interface between S-CSCF and the Application server;
* **Mj Interface**: The interface between the Breakout Gateway Control Function (BGCF) and Media Gateway Controller Function (MGCF);
* **Mi Interface**: The interface between BGCF and S-CSCF.
## 1 Introduction
The proposed mobility support scheme is network-based and provides multi-hop communication between the GW and the MN via Static Nodes (SNs) (Note that in this paper, by Static Nodes we mean the static sensor nodes of the network (PAN); we named so in order to avoid any ambiguity between the MN (which is also a sensor node) and the static sensor nodes of the network.). Thus our schemes allow the MNs to communicate with the GW through short range IEEE 802.15.4 communication links that help the MNs to conserve power and extend the lifetime of the overall networks including MNs. Also the proposed scheme takes into consideration the sleep state of the SN. The paper further presents a distributed version of the LoW Mob, named as the Distributed LoW Mob (DLoW Mob) scheme. The aim of DLoW Mob is two folds; firstly it tries to reduce the number of Location Update (LU) messages to the GW by introducing the concept of Mobility Support Points (MSPs) which could extend the overall lifetime of the network. MSP acts as a master node for a set of SNs and handles all the mobility related functionality. Secondly, it supports route optimization between source and destination MNs in a PAN, so that the data packets are not routed via GW. Moreover, we have also discussed the security considerations for our proposed mobility schemes. The main objective of proposed security mechanism in this paper is to provide a security solution to our proposed mobility schemes. The performance evaluation compares the end-to-end delay and packet success ratio between source and destination MN in a PAN at different speed of MN in LoW Mob, DLoW Mob, and DLoW Mob with Route Optimization scheme. The handoff signaling costs for the LoW Mob and DLoW Mob schemes are determined through analytical modeling. The remainder of the paper is organized as follows. Section 2 describes the related work followed by the 6 LoWPAN mobility requirements in Section 3. Section 4 defines the system model and assumptions. Section 5 and 6 describe LoW Mob and DLoW Mob respectively in detail. Security considerations for our proposed schemes are discussed in Section 7. Performance evaluation follows next in Section 8, and finally Section 9 concludes the paper.
# A Simple Estimation Method of Weibull Modulus and Verification with Strength Data
## 4 Material Strength Data
### Summary  
It is shown in this section that Equation (14) provides the best correlation between the observed Weibull modulus and estimated values from the average and standard deviation (or the coefficient of variation) of experimentally determined strength datasets; that is, m = 1.1 \(<\)\(\sigma\)\(>\)/S = 1.1/CV (modified Robinson relation). This conclusion is based on a comparison of these values from more than 260 datasets. Estimated m values matched to normally calculated m\({}_{\text{obs}}\) values on average within 1%, and each pair of m values was within \(\pm\) 20% except for 11 cases.
# Applications of Plasma Produced with Electrical Discharges in Gases for Agriculture and Biomedicine
###### Abstract  
The use of thermal and non-thermal atmospheric pressure plasma to solve problems related to agriculture and biomedicine is the focus of this paper. Plasma in thermal equilibrium is used where heat is required. In agriculture, it is used to treat soil and land contaminated by the products of biomass, plastics, post-hospital and pharmaceutical waste combustion, and also by ecological phenomena that have recently been observed, such as droughts, floods and storms, leading to environmental pollution. In biomedical applications, thermal plasma is used in so-called indirect living tissue treatment. The sources of thermal plasma are arcs, plasma torches and microwave plasma reactors. In turn, atmospheric pressure cold (non-thermal) plasma is applied in agriculture and biomedicine where heat adversely affects technological processes. The thermodynamic imbalance of cold plasma makes it suitable for organic syntheses due its low power requirements and the possibility of conducting chemical reactions in gas at relatively low and close to ambient temperatures. It is also suitable in the treatment of living tissues and sterilisation of medical instruments made of materials that are non-resistant to high temperatures. Non-thermal and non-equilibrium discharges at atmospheric pressure that include dielectric barrier discharges (DBDs) and atmospheric pressure plasma jets (APPIs), as well as gliding arc (GAD), can be the source of cold plasma. This paper presents an overview of agriculture and soil protection problems and biomedical and health protection problems that can be solved with the aid of plasma produced with electrical discharges. In particular, agricultural processes related to water, sewage purification to ozone and with advanced oxidation processes, as well as those related to contaminated soil treatment and pest control, are presented. Among the biomedical applications of cold plasma, its antibacterial activity, wound healing, cancer treatment and dental problems are briefly discussed.  
old plasma technologies; biomedicine; ozone generation; soil purification; pest control; antimicrobial effects; wound healing; tumour treatment; dentistry applications
## 1 Introduction  
Savannah River Site (SRS) located in Aiken, South Carolina, functioned as a nuclear materials production facility for the U.S. Department of Energy (DOE), where metal-clad uranium (U) targets were used in the production of plutonium [1]. From 1954 to 1982, SRS wastewater originating from the metal plating and fabrication processes was released directly into Tims Branch, a second-order stream. Because of these activities, large quantities of both U (depleted as well as naturally-occurring) and Nickel (Ni) were released and deposited into stream sediments and an abandoned farm pond- the Steeds Pond, that served as a natural settling basin along Tims Branch [1; 2]. Although contaminant distribution is heterogeneous in the Steeds Pond sediments, U and Ni concentrations are found upwards of 1000 mg/kg [2]. To gauge in-situ remediation (natural attenuation) and recommend appropriate strategies for the decontamination of SRS contaminated ecosystems, it is necessary to obtain a deeper understanding of the mechanisms exhibited by the native soil microbiota that have evolved to resist metals and radionuclides. In fact, microorganisms exposed to the contaminant stresses not only have the unparalleled ability to survive in radionuclide contaminated environments, but also potentially reduce the toxicity of both U [3; 4; 5] and Ni [6], respectively. Microbially-mediated mechanisms for the reduction of U toxicity include bioreduction, biosorption, biomineralization, and bioaccumulation [4]. For Ni, most commonly known resistance mechanisms are mediated by efflux pumps such as cnr CBA (cobalt-nickel resistance) from _Cupriavidus metallidurans_ CH34, NccCBA (Nickel-cobalt-cadmium) and NreB (nickel resistance) from _Achromobacter xylosoxidans_ 31A, and CznABC (Cadmium-zinc-nickel) from _Helicobacter pylori_[6]. However, the genomic mechanisms underpinning U and Ni conversions into the less mobile and less toxic forms continue to remain unclear. Soil samples for this study were collected from site 101 located within the Tims Branch system. At this site, U concentrations are typically present between 700 and 800 ppm [5], which are considered high U concentrations invoking the criteria of [PERSON] et al. [7]. Therefore, this site represents an opportunity to study genome-enabled mechanisms recruited by the SRS-native microorganisms, facilitating their survival in co-contaminated environments. In fact, the stress posed by environmental contaminants facilitates the recruitment of genes by horizontal gene transfer mechanisms that enable the microbial cells to not only resist, but also bioremediate, the contaminants, mostly by the synthesis of proteins for cellular survival [8]. Some examples of such genomic-mechanisms include efflux systems, the presence of metal resistant genes, detoxification genes, and biosorption/bioaccumulation of the contaminant at or within the bacterial cell membrane [9]. Furthermore, a growing body of research is demonstrating that metal contaminants in the environment have the propensity to co-select for antibiotic resistance within the naturally-occurring microbiota [10].