esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiments
### Comparative Experiment
Notably, even when compared with models with much larger parameter scales (e.g., BERT-ALL with 109 M parameters and RoBERTa with 125 M parameters), SecEmoNet still maintains the best performance. This fully demonstrates the high efficiency of SecEmoNet's design--it breaks the conventional perception that \"more parameters mean better performance\" and achieves superior task performance through a lightweight architecture. \begin{table}
\begin{tabular}{c c} \hline \hline
**CLIP-Line** & **BERT-Line** \\ \hline SecEmoNet & t = 4.576 (\(p\) = 0.004) & t = 3.576 (\(p\) = 0.012) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Experimental results of paired \(t\)-test. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Emotion** & **Hate** & **Sentiment** & **Offensive** & **Irony** & **Stance** & **Avg** \\ \hline SVM & 64.7 & 36.7 & 62.9 & 52.3 & 61.7 & 67.3 & 57.6 \\ LSTM & 66.0 & 52.6 & 58.3 & 71.7 & 62.8 & 59.4 & 61.8 \\ FastText & 65.2 & 50.6 & 62.9 & 73.4 & 63.1 & 65.4 & 63.4 \\ RoBERTa & 72.0 & 49.9 & 69.1 & 77.1 & 65.4 & 66.7 & 66.7 \\ BERT-Line & 39.27 & 57.64 & 55.99 & 72.09 & 47.75 & 57.17 & 55.0 \\ BERT-ALL & 79.94 & 57.71 & 60.97 & 84.42 & 68.71 & 57.25 & 68.2 \\ CLIP-Line & 72.34 & 53.57 & 62.02 & 79.77 & 73.34 & 69.66 & 67.3 \\ SecEmoNet & 74.52 & 57.44 & 65.65 & 82.91 & 74.11 & 69.98 & 70.8 \\ \(\Delta\) & +2.18 & +3.87 & +3.63 & +3.14 & +0.77 & +0.28 & +3.5 \\ SE & \(\pm 0.13\) & \(\pm 0.52\) & \(\pm 0.34\) & \(\pm 0.06\) & \(\pm 0.23\) & \(\pm 0.02\) & \(\pm 0.22\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The specific distribution of data in the experimental datasets; \(\Delta\) represents the improvement of SecEmoNet compared with CLIP-Line. “SE” represents Standard Error.
# Effect to the Surface Composition in Ultrasonic Vibration-Assisted Grinding of BK7 Optical Glass
###### Abstract  
Because of the changes in cutting conditions and ultrasonic vibration status, the proportion of multiple material removal modes are of uncertainty and complexity in ultrasonic vibration-assisted grinding of optical glass. Knowledge of the effect of machined surface composition is the basis for better understanding the influence mechanisms of surface roughness, and also is the key to control the surface composition and surface quality. In the present work, 32 sets of experiments of ultrasonic vibration-assisted grinding of BK7 optical glass were carried out, the machined surface morphologies were observed, and the influence law of machining parameters on the proportion of different material removal was investigated. Based on the above research, the effect of surface composition was briefly summarized. The results indicated that the increasing of spindle rotation speed, the decreasing of feed rate and grinding depth can improve the proportion of ductile removal. The introduction of ultrasonic vibration can highly restrain the powdering removal, and increase the proportion of ductile removal. Grinding depth has a dominant positive effect on the surface roughness, whereas the spindle rotation speed and ultrasonic amplitude both have negative effect, which was caused by the reduction of brittle fracture removal.  
surface composition; optical glass; ultrasonic vibration; grinding; influence law Article
## 5 Conclusions  
In order to improve the linearity of mixers in the millimeter-wave band more efficiently, a new linearization method for the active mixer is proposed, and a down-conversion mixer with ultra-high IP1 dB/OP1 dB and wide IF bandwidth for the 5G NR band was designed. It was fabricated in a 130 nm SiGe BiCMOS process offered by STMicroelectronics. The use of the \"reverse lift\" improves the linearity of the proposed mixer greatly. The non-linearity of the transistors performs the linearization without adding any complicated structures, which is helpful for the low-cost design of 5G high-speed communication transceivers. As compared to other silicon-based publications in Table 5, the mixer demonstrates a measured IP1 dB of +7.2\(\sim\)+10.1 dBm, an average OP1 dB of +5.4 dBm, \(FOM\) of 24.73, and \(FOM_{IF}\) of 33.76 with 8 GHz IF bandwidth, showing the best linearity performance among the published mixers. Furthermore, this method is based on the analysis of the fundamental amplifier; so, it is not just for mixer design, it also has excellent potential to be used in any amplifier-based circuit design with high linearity.  
Conceptualization, S.Y.; methodology, S.Y.; validation, S.Y. and K.H.; formal analysis, S.Y.; investigation, S.Y.; resources, S.Y.; data curation, S.Y. and K.H.; writing--original draft preparation, S.Y.; writing--review and editing, S.Y.; visualization, S.Y.; supervision, H.F. and K.M.; project administration, K.M. and M.L.; funding acquisition, K.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Guangdong Provincial Key Research and Development Program, grant number 2019B10156003.  
Not applicable.  
The authors declare no conflict of interest.
# Performance Evaluation of Direct-Link Backhaul for UAV-Aided Emergency Networks
###### Abstract  
Today's wireless networks provide us reliable connectivity. However, if a disaster occurs, the whole network could be out of service and people cannot communicate. Using a fast deployable temporally network by mounting small cell base stations on unmanned aerial vehicles (UAVs) could solve the problem. Yet, this raises several challenges. We propose a capacity-deployment tool to design the backhaul network for UAV-aided networks and to evaluate the performance of the backhaul network in a realistic scenario in the city center of Ghent, Belgium. This tool assigns simultaneously resources to the ground users--access network--and to the backhaul network, taking into consideration backhaul capacity and power restrictions. We compare three types of backhaul scenarios using a 3.5 GHz link, 3.5 GHz with carrier aggregation (CA) and the 60 GHz band, considering three different types of drones. The results showed that an optimal UAV flight height (80 m) could satisfy both access and backhaul networks; however, full coverage was difficult to achieve. Finally, we discuss the influence of the flight height and the number of requesting users concerning the network performance and propose an optimal configuration and new mechanisms to improve the network capacity, based on realistic restrictions.  
U 25 June 2019; 26 July 2019; 30 July 2019
# Towards Secure Searchable Electronic Health Records Using Consortium Blockchain
## 2 Background and Related Works
### Relate Works  
#### 2.2.1 Blockchain-Based Healthcare Applications  
In recent years, blockchain has received a lot of attention in areas such as data storing, data sharing, and data confidentiality. Many studies have used this technology to address problems in existing EHRs. Existing deployments of IT infrastructure in a medical facility usually involve private structures that impose limitations on scalability and information sharing [26] where it is important to choose a suitable type of blockchain (private or public) for medical data sharing. [PERSON] et al. in [3, 27] presented a review of security and privacy-preserving EHRs which explain different blockchain architectures based on sharing EHRs. They review a comparison of current EHRs schemas-based blockchains with security metrics and functionality.  
Recently, blockchain is becoming a major technology that will change the way we share information with increasing confidence in distributed environments without the need for authorization. [PERSON] et al. [28] present a blockchain technology survey that evaluates the unique characteristics of blockchain and discover the research gaps, classify and review the various ways that IoT and blockchain can be integrated, and also review existing networks and frameworks for blockchain-IoT and assessment results with a comparison of various blockchains in IoT devices. There are many EHRs schemes based on blockchain provided. For example this study [29] designed MedRec, an Ethereum-based medical data-sharing platform that allows for the decentralized safe integration of medical data across medical organizations. Nonetheless, to preserve blockchain stability, its consensus technique PoW requires a high computing load. A design that is similar to this is proposed in [30]. [PERSON] et al. [31] proposed the MDSM medical blockchain system, which uses an upgraded DPoS consensus method to reduce node computation burden and improve data sharing security and efficiency. For COVID-19 pandemic management, smart contracts and  
Figure 2: Overview of proxy re-encryption scheme.  
blockchain were also used [32; 33]. The idea of these studies is tracking the tests through automated medical passports and certificates of immunity.
## 3 Materials & Methods
### Graph Modeling
The initial building of the heterogeneous graph was carried out by generating three subgraphs: user-user graph, topic-topic graph, user-topic graph. In the user-user graph, \(G_{u}\) was assigned as the new empty graph, where node \(U\) represented the user and edge \(E_{uu}\) represented similar users (line 4-5). User nodes were created and added to the user graph and the node attributes were set as gender and age (line 6-10). The edges between users mean this user is similar, which is based on threshold value; for example, if user A is similar to user B according to the similarity matrix and measures calculated in the previous section, and based on threshold value, then a link between these two nodes is added and weight is assigned to it. The weight between the nodes denotes the similarity value (line 12-18). Figure 6: The Proposed Schema of Heterogeneous Graph. Figure 7: Link Types in Heterogeneous Graph. ```
1:Input:\(G_{u},G_{z}\)
2:Output:\(G_{uz}\)
3:Begin
4:\(\bigbackslash\bigbackslash\) Assign \(G_{z}\) as heterogeneous graph between subgraphs
5:\(G_{u}\) and \(G_{z}\)
6:\(G_{z}\gets Graph(U,Z,E_{uz})\)
7:\(\bigbackslash\) Add user topic edges
8:for\(v\) user \(\in\) usersdo
9:\(Z_{user}\gets Interesting topics\) for user
10:for each topic in \(Z_{user}\)do
11: Create edge \(E\big{(}U_{user},\ Z_{topic}\big{)}\) between \(U_{user}\), and \(Z_{topic}\)
12: Add edge \(E\big{(}U_{user},\ Z_{topic}\big{)}\) to graph \(G_{uz}\)
13:endfor
14:endfor
15:return\(G_{uz}\)
16:End
```  
**Algorithm 3**_Cont._  
The generation heterogenous graph phase is described in Algorithm 4, which is a heterogenous graph with two types of nodes: user \(U\) and topic \(Z\); \(G_{uz}\) is assigned as the heterogeneous graph between subgraphs \(G_{u}\) and \(G_{z}\). The link \(E_{uz}\) between user and topic represents interest; for example, user A is interested in topic C.  
Finally, the data analysis process is aided and clutter in the graph network is reduced by generating an interactive graph. An interactive graph enables the visualisation of all three subgraphs: users graph, topics graph, and users to topics graph. It also allows an overview of all users interested in a specific topic. Moreover, it shows the relationships between specific users. ```
1:Input:\(G_{u},G_{z}\)
2:Output:\(G_{uz}\)
3:Begin
4:\(\bigbackslash\) Assign \(G_{z}\) as heterogeneous graph between subgraphs
5:\(G_{u}\) and \(G_{z}\)
6:\(G_{z}\gets Graph(U,Z,E_{uz})\)
7:\(\bigbackslash\) Add user topic edges
8:for\(v\) user \(\in\) usersdo
9:\(Z_{user}\gets Interesting topics\) for user
10:for each topic in \(Z_{user}\)do
11: Create edge \(E\big{(}U_{user},\ Z_{topic}\big{)}\) between \(U_{user}\), and \(Z_{topic}\)
12: Add edge \(E\big{(}U_{user},\ Z_{topic}\big{)}\) to graph \(G_{uz}\)
13:endfor
14:endfor
15:return\(G_{uz}\)
16:End
```  
**Algorithm 4** Generate Heterogeneous Graphs with two types of nodes
## 4 Measurements and Methods
### Comparison between Measurements and Calculations  
The measurements and calculations were compared for the octave band frequencies 125 Hz to 4000 Hz. Calculations of \(C_{50}\) and \(G\) were performed with the formulas presented  
Figure 8: The practical absorption coefficients for the ceiling absorbers and wall panels used in the experiments. (Red) Ecophhon Industry Modus 50 mm, (blue) Ecophhon Gedina A 15 mm, (green) Wall Panel A 40 mm.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \(G_{\text{argg}}\) (dB) & \(C_{50,\text{argg}}\) (dB) & \(T_{20,\text{argg}}\) (s) \\ \hline
125 Hz & \(\pm\)0.61 & \(\pm\)0.56 & \(\pm\)0.077 \\
250 Hz & \(\pm\)0.30 & \(\pm\)0.29 & \(\pm\)0.018 \\
500 Hz & \(\pm\)0.40 & \(\pm\)0.29 & \(\pm\)0.010 \\
1000 Hz & \(\pm\)0.25 & \(\pm\)0.27 & \(\pm\)0.006 \\
2000 Hz & \(\pm\)0.37 & \(\pm\)0.38 & \(\pm\)0.010 \\
4000 Hz & \(\pm\)0.36 & \(\pm\)0.36 & \(\pm\)0.008 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Uncertainty interval related to repeatability, corresponding to a 95% confidence interval, for the measurement procedure used in the experiments.  
in Section 3, according to Equations (19) and (20). \(T_{20}\) was calculated by the logarithmic version of Equation (8) using the \(-5\) to \(-25\) dB dynamical range according to ISO 3382-2.  
For comparison, calculations according to the Sabine formula were included. The reverberation time \(T\) was calculated as  
\[T=\frac{0.161V}{A_{ceiling}+A_{furniture}+A_{surface}+4 mV} \tag{42}\]  
where \(A_{ceiling}=\alpha_{p}S_{ceiling}\) and \(\alpha_{\text{p}}\) is the practical absorption coefficient given in Figure 8. \(A_{furniture}=V_{furniture}^{2/3}\) according to the EN 12354-6. For a sparsely furnished room, \(V_{furniture}\) is approximately 1-2% of the room volume [29]. \(A_{surface}\) and the air absorption were calculated in the same way as in Equation (33).  
The absorption coefficients for the floor and walls were estimated from the reverberation time measurements in the empty room, i.e., without an absorbent ceiling. Those values were used both in the diffuse and non-diffuse calculations for calculating \(A_{surface}\).  
Assuming a linear decay under diffuse field conditions and a reverberation time, given by Equation (42), \(C_{50}\) and \(G\) are calculated as  
\[C_{50}=10\log\Bigl{(}10^{(6/T)0.05}-1\Bigr{)} \tag{43}\]  
And  
\[G=10\log\Bigl{(}\frac{4}{A}\Bigr{)}+31 \tag{44}\]  
where \(A=0.16\frac{V}{T}\) is the equivalent absorption area in m\({}^{2}\) cabin and \(V\) is the room volume.
## 6 Results and Discussion  
In this section, the case study that corresponds to Jeddah Seaport located in the kingdom of Saudi Arabia is introduced. This case study has been chosen because the border guard of Jeddah Seaport has stressed that the current deployed video surveillance camera system is not fully efficient due to two main reasons. First of all, the placement of cameras in its current state does not meet their expectations because there are some areas of the seaport that are overloaded by many cameras, while other places are not well covered. Secondly, the current total coverage of Jeddah Seaport is around 50%, while the border guard aims to achieve a coverage close to 100% with an optimal number of cameras.  
In the following, the adopted methodology for acquiring data that are necessary to implement the HybVOR approach is presented. Then, the results obtained by deploying surveillance camera network based on our proposed approach are highlighted. Afterward, the results of the HybVOR implementation are discussed.
# Role of Protein Glycoslation in Host-Pathogen Interaction
## 3 Glycosylated Proteins of Hosts Act as Barriers to Defense Pathogens
### Chemical Barrier  
In animals, the glycoproteins facilitate the growth of probiotics in the gut thus provides a chemical barrier against pathogens [93]. The \(O\)-glycans of glycoproteins like MUC2 can serve as attachment sites for probiotic colonization [13; 94] by providing favorable nutrition substances [95]. Consequently, intestinal surface harbors a complex ecosystem consisting of a myriad of intestinal microorganisms that affect the physiology, immune function, and fitness of the host [96]. Among those probiotics including _Bifidobacterium_ and _Lactobacillus_ are considered as the key players to exert health-promoting effects [94].  
Glycoproteine can also eliminate gut pathogens comparable to antibiotics [16]. _Helicobacter pylori_ is a severe pathogen that infects the stomachs of nearly half of human population. It widely presents in stomachs but rarely in deeper portions of the gastric mucosa that coated by the mucus [97; 98]. [PERSON] et al. [16] discovered that the special \(O\)-linked carbohydrate terminal, \(\alpha\)(1,4)-GlcNAcAc, and the mucins (comprising of Muc6) with \(\alpha\)(1,4)-GlcNAc expressed in the gastric mucosa have activity against _H. pylori_ by inhibiting the biosynthesis of the cell wall.  
In plants, glycosylation can stabilize plant extracellular proteinases and regulate their activities against pathogen invasion. Usually, the active sites of plant extracellular proteinases are protected by \(N\)-carbohydrate residues during glycosylation to avoid the proteolytic process introduced by other proteases [5]. For example, the aspartic proteinases (StAPs) are extracellular proteinase from potato which have in vitro antifungal activity towards _Phytophthora infestans_ and _Fusarium solani_[19; 77; 99]. In apoplast StAPs accumulated significant more in the _P. infestans_ resistant cultivar than in susceptible cultivar [19], accumulated slower when unglycoslated than glycosylated, and the fungicidal activity of deglycosylated StAPs was lower than native StAPs [5].
# Two Decades of Groundwater Variability in Peru Using Satellite Gravimetry Data
## 4 Discussion
### Trends and Drivers of Groundwater Depletion  
GWS depletion peaked during 2007-2010 and 2015-2023, with rates of \(-\)90 mm/year in \(\mathrm{I}\mathrm{a}\mathrm{a}\mathrm{a}\mathrm{a}\mathrm{a}  
use, recharge, aquifer type). GRACE monthly percentiles enable high-sensitivity detection of these changes, serving as a valuable tool for early warning and water resource planning.
# Infrared Image Deblurring via High-Order Total Variation and Lp-Pseudonorm Shrinkage
## 6 Discussion and Conclusions  
Deblurring infrared images plays a significant role in an infrared imaging system. To improve the performance of deblurring images, the proposed HTV-Lp model combines first-order and high-order gradients of images with Lp-pseudonorm shrinkage. The ADMM algorithm is used to split the proposed model into several decoupled sub-problems. In the process of solving these problems, the convolution and FFT theorem are applied to image deblurring to avoid large computational complexity. The comparison of HTV-Lp with existing ATV, ITV, ATpV, FTV4 Lp, and Hybrid TV models shows that HTV-Lp obtained the average highest PSNR and SSIM and lowest GMSD values of all methods and successfully mitigated staircase artifacts.  
A limitation of this study is that non-local patch similarity is not fully considered in the proposed model. Additionally, there is room for further improvement with regard to the speed of the HTV-Lp algorithm within the framework of the accelerated ADMM. Thus, in our future work, we will focus on improving the performance and efficiency of the proposed method.  
Conceptualization, J.Y. and Y.C.; Data curation, J.Y.; Formal analysis, J.Y.; Funding acquisition, Y.C.; Investigation, J.Y.; Methodology, J.Y.; Project administration, J.Y.; Resources, J.Y.; Software, J.Y.; Supervision, Y.C. and Z.C.; Validation, J.Y.; Visualization, J.Y.; Writing original draft, J.Y.; Writing--review and editing, Y.C. and Z.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Educational and Research Project for Young and Middle-aged Teachers of Education Department of Fujian Provincial (JAT190378); Fujian Province Major Teaching Reform Project (FBJG20180015); The Foundation of President of Minnan Normal University (KJ19019), and the Teaching Reform Project of Minnan Normal University (JG201918).  
Thanks to [PERSON] of the University of Electronic Science and Technology of China for sharing the FTV4 Lp code.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
# Benefits of Probiotics--Biodetoxification
## 2. Probiotics--Biodetoxification of Food
### The Role of Probiotics in Food Biodetoxification
#### 2.2.8. Bisphenol A  
Polycarbonate plastics epoxy resins are commonly used as utility products and packaging materials. They contain an added hardening component--harmful bisphenol A (BPA)--which can migrate to the food matrix. Prolonged contact time, increased temperatures, and food composition can accelerate the migration of xenobiotics from packaging materials. Fatty and acidic foods promote migration of BPA [68]. The presence of this xenobiotic is related to toxic effects, including increased risk of cancer, and endocrine and fertility disorders [69]. The EU Commission Regulation (EU) 2024/3190 of 19 December 2024 on the use of bisphenol A and other bisphenols and bisphenol derivatives prohibits the use of BPA in polycarbonate drinking cups and bottles for infants and young children [70]. There are many reports confirming the usefulness of probiotics in BPA biodetoxidications. [PERSON] et al. investigated six probiotic strains (_L. reuteri, L. helveticus, L. brevis, L. delbrueckii, L. casei_, and _Bacillus subtilis_), confirming the potential of probiotics in the biodegradation of BPA. The highest degradation rate of BPA in this in vitro study was reached (69.83%) with _Lactobacillus reuteri_[71].
# Detection of Movement and Lead-Popping Artifacts in Polysomnography EEG Data
## 2 Methods
### Algorithm
#### 2.1.2 Step-by-Step Description
Accordingly, each channel has its own two pools; \"good\" segments constitute one pool, and \"bad\" segments constitute the other. Scanning each channel for outliers. Segments declared \"bad\" are immediately designated as outliers. To detect outlier segments among the pool of \"good\" segments for each channel, we adapted a global threshold approach. We derived the global threshold based on the distribution of average correlation among the \"good\" segments. Specifically, we considered one-fourth of the 75 th percentile value of the correlations in the \"good\" segment pool as the threshold. Using this cutoff, we rescanned the \"good\" segment pool from each channel for outliers. A \"good\" segment was considered an outlier when its average correlation was below the cutoff. As a result, each segment in a channel was labeled as \"1\" (outlier) or \"0\" (not outlier). Artifact regions and outlier channel(s). If the distance between two outliers (a and b) is less than 5 min (300 segments, 10 epochs), all segments between a and b are marked as outliers, creating an artifact region. If the total length of artifact regions in a channel exceeds 5% of the channel's length after preprocessing, the channel is excluded in the next round of average correlation calculation; nevertheless, the channel is not considered an outlier channel at this stage.