esa-sceva/satcom-chunk-collection huggingface dataset:
# A Novel Battery-Supplied AFE EEG Circuit Capable of Muscle Movement Artifact Suppression
###### Abstract  
In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design specifications for medical-grade and research-grade EEG circuits and a comprehensive analysis of various analog front-end architectures for electroencephalograph (EEG) circuit design are presented. Three distinct selected case studies are examined in terms of comparative evaluation with generic EEG circuit design templates. Moreover, a novel one-channel battery-supplied EEG analog front-end circuit designed to address the requirements of usage protocols containing strong compound muscle movements is introduced. Furthermore, a realistic input signal generator circuit is proposed that models the human body and the electromagnetic interference from its surroundings. Experimental simulations are conducted in 50 Hz and 60 Hz electrical grid environments to evaluate the performance of the novel design. The results demonstrate the efficacy of the proposed system, particularly in terms of bandwidth, portability, Common Mode Rejection Ratio, gain, suppression of muscle movement artifacts, electrostatic discharge and leakage current protection. Conclusively, the novel design is cost-effective and suitable for both commercial and research single-channel EEG applications. It can be easily incorporated in Brain-Computer Interfaces and neurofeedback training systems.  
electroencephalography; EEG; muscle artifacts; notch filter; driving right leg; battery-based EEG signal acquisition system; biosignal filtering; low frequency signal; CMRR
## 6 Conclusions, Limitations, and Future Research  
In this paper, I illustrated how scenario analysis can be applied to gain a better understanding regarding the future development of Bitcoin. On the basis of a survey among 51 end users and a subsequent analysis with an expert panel, positive and negative features of Bitcoin, as well as envisioned future opportunities and threats, were collected, bundled, and further developed into three consistent scenarios. The three scenarios showed different features of Bitcoin that shape its impact on an individual, organizational, and national level. These scenarios illustrate the potential future impacts of Bitcoin and can be used as a starting point for future research studies.  
Several limitations exist in this study. First, the collection of positive and negative Bitcoin features, as well as their subsequent bundling, was based on a convenience sample of end users. More insights can be gained by incorporating experts' opinions in future studies. Second, the bundling of the features and the creation of the scenarios revealed a substantial amount of complexity, which was caused by the fact that various stakeholder groups might perceive the exact same feature of Bitcoin differently. This complexity calls for future scenario studies that go into more detail and focus on more specific aspects of Bitcoin's development (e.g., security features, governmental policies, environmental concerns).  
Future research can benefit from this study in several ways. Importantly, several avenues for follow-up studies were already laid out in previous sections of this paper, including research questions and suggested methodologies. Naturally, other researchers should not feel constricted by these suggestions but are explicitly encouraged to find their own niche topics and explore methods other than those suggested in this paper. An extension to general cryptocurrency/blockchain/DLT/token research can be easily achieved. In many regards, other applications that are built on distributed ledgers might turn out to be highly impactful in specific sectors. For example, decentralized finance (DeFi) threatens to disrupt the existing financial systems, and CBDCs, which are currently highly popular among many central banks and can be built upon distributed ledgers, will substantially transform existing monetary systems. Lastly, the suggested research questions are also open to the application of a wide range of existing theories and methodologies, which will hopefully incite a stream of research that is rewarding for academics and fascinating for practitioners.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The author declares no conflict of interest.
## 2 MINLP Formulation
### Set of Constraints  
The set of constraints associated with the problem of the optimal allocation and sizing D-STATCOMs in AC distribution networks are mainly associated with the power balance equations and the binary constraints associated with the installation of these devices. All the restrictions for this problem are listed below.  
\[P_{kh}^{g}-P_{kh}^{d}=\sum_{k\in\mathcal{N}}\sum_{m\in\mathcal{N}}Y_{km}V_{kh }V_{mh}\cos(\delta_{kh}-\delta_{mh}-\theta_{km}),\;\forall\{k\in\mathcal{N} \ \&\ h\in\mathcal{H}\}, \tag{2}\]  
\[Q_{kh}^{g}+Q_{k}^{\text{D-STATCOM}}-Q_{kh}^{d}=\sum_{k\in\mathcal{N}}\sum_{m \in\mathcal{N}}Y_{km}V_{kh}V_{mh}\sin(\delta_{kh}-\delta_{mh}-\theta_{km}),\; \forall\{k\in\mathcal{N}\ \&\ h\in\mathcal{H}\}, \tag{3}\]  
\[V_{\text{min}}\leq V_{kh}\leq V_{\text{max}},\;\forall\{k\in\mathcal{N}\ \&\ h\in\mathcal{H}\}, \tag{4}\]  
\[z_{k}Q_{\text{min}}^{\text{D-STATCOM}}\leq Q_{k}^{\text{D-STATCOM }}\leq z_{k}Q_{\text{max}}^{\text{D-STATCOM}},\;\forall\{k\in\mathcal{N}\}, \tag{5}\]  
\[\sum_{k\in\mathcal{N}}z_{k}\leq N_{\text{available}}^{\text{D-STATCOM }}, \tag{6}\]  
where \(P_{kh}^{g}\) and \(Q_{kh}^{g}\) are the active and reactive power injections of the generator connected at node \(i\) in the period \(h\), and \(P_{kh}^{d}\),and \(Q_{kh}^{d}\) are the active and reactive power consumption in the constant power demand connected at bus \(i\) in the period of time \(h\), \(V_{\text{min}}\) and \(V_{\text{max}}\) are the lower and upper voltage bounds allowed for all nodes of the network at each period time, \(Q_{\text{min}}^{\text{D-STATCOM}}\) and \(Q_{\text{max}}^{\text{D-STATCOM}}\) are the minimum and maximum limits of the distribution system compensators that can be installed along the distribution grid, \(z_{k}\) is the binary variable associated with the allocation (\(z_{k}=1\) or \(z_{k}=0\)) of a D-STATCOM in the network, and \(N_{\text{available}}^{\text{D-STATCOM}}\) is the maximum number of D-STATCOMs that may be installed in the electrical distribution network.
# Hyperspectral Imaging as a Rapid Quality Control Method for Herbal Tea Blends
## Materials and Methods
### SWIR Hyperspectral Imaging Analysis  
A sisuchema short wave infrared (SWIR) camera (Specim, Spectral Imaging Ltd., Oulu, Finland) equipped with ChemaDaq version 3.62.183.19 software (Specim, Spectral Imaging Ltd., Oulu, Finland) was used to acquire images of the raw materials. The imaging spectrograph of this pushbroom imaging system is connected to a 2D array mercury-cadmium-telluride (HgCdTe) detector. Quartz halogen lamps were employed as the light source. Images were captured in the range of 920-2514 nm using a high magnification lens (field of view: 50 mm; spatial resolution: 150 \(\upmu\)m) with a frame rate of 100 Hz at an exposure of 3.0 ms. The resolution of 6-7 nm resulted in images consisting of 256 \(\times\) 320 pixels [13].
# Trends in Quantification of HbA1c Using Electrochemical and Point-of-Care Analyzers
## 9 Concluding Remarks
CdTe & Cadmium telluride  
CE & Certification Europe  
CLIA & Clinical laboratory improvement amendments  
CMOS & Complementary Metal-Oxide-Semiconductor Transistor  
CNF & Carbon nanofibers  
CS & Chitosan  
Cys & Cystamine  
DCIP & Dichlorophenol indophenol  
DMSO & Dimethylsiloxane  
DPV & Differential pulse voltammetry  
DPSP & 3,3\({}^{\prime}\)-Dithio-bis-propionic acid N-hydroxysuccinimide ester  
EDC-NHES & ethyl (dimethylamino propyl) carbodimide-N-hydroxysuccinimide  
EIS & Electrochemical impedance spectroscopy  
ELISA & Enzyme-linked immunosorbent assay  
ESM & Egg-shell membranes  
FAO & Fructosyl amino acid oxidase  
FcBA & Ferrecone bronic acid  
FDA & US Food and Drug Administration  
FDMA & 1,1\({}^{\prime}\)-Di(aminomethyl)ferrocene  
FET & Field-effect transistor  
FPBA & 4-formyl-phenylbononic acid  
FPBA & Formylphenyl boronic acid  
FPBA2 & 3-Formylphenyl boronic acid (2 moiety)  
FPOX & Fructosyl peptide oxidase  
FTO & Fluorine-doped tin oxide  
FV & Fructosyl-valine  
GA & Glutaraldehyde  
GCE & Glassy carbon electrode  
G-COOH & Carboxylic acid-functionalized graphene  
GCPE & Glassy carbon paste electrode  
GG & Glycation gap  
GN & Graphene nanosheets  
GO & Graphene oxide  
GOx & Glucose oxidase  
GPP & Glycosylated pentapeptide  
GS & Graphite sheets  
Hb & Hemoglobin  
HbA1c & Glycated hemoglobin  
HGI & Hemoglobin glycation index  
HPLC & High-Performance liquid chromatography  
IFCC & International Federation of Clinical Chemistry and Laboratory Medicine  
ISFETs & Ion-sensitive field-effect transistors  
ITO & Indium-doped tin oxide  
IVD & In vitro diagnostics  
LoD & Limit of detection  
MEMS & Micro-electro-mechanical system  
MIP & Molecularly imprinted polymer  
MNP & Magnetic bio-nanoparticles  
MPA & 3-Mercaptopropionic acid  
m-PMS & meta-phenazinemethosulphate  
MU & 11-mercapto-1-undecanol  
MUA & 11-Mercaptoundecanoic acid  
MW & Oligo (phenyl ethylynylene) molecular wires  
MWCNTs & Multi-walled carbon nanotubes  
NGSP & National Glycohemoglobin Standardization Program  
OEG & Oligo (ethylene glycol)
## 3 RPL Routing Attacks
### Replay Attack  
The broadcast messages of RPL such as DIO messages can be eavesdropped by any node joining an RPL network. To initiate a replay attack, the eavesdropper node maliciously resends the eavesdropped message to its neighbor RPL nodes. The message is then perceived as a new one having fresh and relevant information. The attack can be applied using any type of RPL control message. If this is performed to duplicate and multicast the DIO messages of a neighbor node, it is then called a neighbor replay attack. Another possibility is that the attacker sends outdated eavesdropped DIO messages containing old routing information to cause the problem of stale routing information. Moreover, the replay attack can be used to initiate a Denial-of-Service (DoS) attack, referred to as a copycat attack. It is based on frequent multicasting of the eavesdropped control messages with a fixed replay interval after modifying the messages' source IP addresses to the one of the attacker. In general, the main objective of replay attacks is the formation of non-optimal topology and the degradation of network performance. It is also possible to have the attack result in DODAG disruption and inconsistency, leading the targeted nodes to be unable to communicate and then detach from the DODAG.
# Design and Construction of a Low-Cost Test Bench for Testing Agricultural Spray Nozzles
###### Abstract  
Droplet size distribution is probably the most important feature of a spray as it affects all aspects of a phytosanitary treatment, i.e., biological, environmental, and safety aspects. This study describes a low-cost laboratory test bench able to analyze agricultural spray nozzles under realistic conditions. The design of the equipment was mainly based on the ISO 5682-1 standard. It has a couple of 3 m long rails, along which the nozzle under test moves while spraying, controlled by a closed-loop position and speed controller. The drops were captured with three Petri dishes containing silicone oil, photographed by means of a digital single-lens reflex (DSLR) camera, and then analyzed with the ImageJ software in order to measure the usual spray parameters: the volumetric diameters, the Sauter mean diameter, and the number mean diameter. Spray trials and tuning of the system parameters were managed by means of a purposely designed user interface running on a Windows 10 PC. Some tests were carried out by using an Albuz ATR80 orange hollow cone nozzle at the working pressures of 0.3, 0.5, 1.0, and 1.5 MPa. The results about spray quality agree with the factory information, and the whole system, even if some aspects still need improvements, has proven reliable.  
nozzle testing apparatus; pesticide; drop pulverization; drop size distribution; image analysis +
Footnote †: journal: Applied Sciences
# Evolution of V2X Communication and Integration of Blockchain for Security Enhancements
## 5 Issues and Challenges in 5G and Edge-Based V2X
### Heterogeneity and Interoperability  
The 5G-based MEC network is highly heterogeneous in design, i.e., operating systems, architectures, radio-based device interfaces, and services. Interoperability issues in edge computing emerge when different edge-cloud service providers interchange data and applications with one another [46]. The issue is not trivial due to the use of different wireless communication modes, different virtualization implementations, or incompatible APIs [47]. There must be a seamless service to retrieve vehicle data from source MEC servers for the target vehicles.
## 3 Proposed Methodology
### Feature Extraction and Selection  
As indicated in the literature [53; 54; 55; 56; 57], it is essential to strengthen evidence provided by the features described on each dataset as this positively influences SL training routines by capturing maximum variability of the inputs and expanding the capacity of inference to the resulting models. If at some point ISCX-Bot-2014 and CIDDS-001 features produce correlation effects, this downgrades the computation of the algorithm. With the incorporation of dimensionality reduction, features that produce wrong variability are discarded, and the remaining inputs are represented in a new subspace of lower dimension based on their variability. In this proposal, \(X_{t}rain\) was preprocessed via Principal Component Analysis (PCA) [45], a dimensionality reduction used to describe features in a new set of noncorrelated variables.  
Principal component \(\mathbf{z}_{1}\) is defined as the linear combination of the original features with maximum variation. Values in this first component are represented in Equation (2):  
\[\mathbf{z}_{1}=O\mathbf{a_{1}}, \tag{2}\]  
where \(n\) is the number of samples, \(O\) is the matrix of observations with zero mean, and \(a_{1}\) is the vector that maximizes variance \(\mathbf{var}(\mathbf{z})\), as formulated in Equation (2).  
\[\frac{1}{n}\mathbf{z}_{1}^{\prime}\mathbf{  
maximizing Equation (4) implies deriving it with respect to the components of \(\mathbf{a_{1}}\) until zero:  
\[\frac{\partial M}{\partial\mathbf{a_{1}}}=2\mathbf{S}\mathbf{a_{1}}-2\omega \mathbf{a_{1}}=0 \tag{5}\]  
Equation (5) results in \(\mathbf{S}\mathbf{a_{1}}=\omega\mathbf{a_{1}}\), where \(\mathbf{a_{1}}\) is an eigenvector of \(\mathbf{S}\), and \(\omega\) the corresponding eigenvalue.  
Ultimately, a new subspace is given by the two main components for both datasets, representing new variables with 89% of captured relevance for ISCX-Bot-2014 and 94% for CIDDS-001.
## 2 Suggested Topology and Its Operation
### Operating States
#### 2.2.1 Non-Inverting State  
During this state, the boost factor (\(\beta\)) or voltage transfer ratio is always positive ensuring that output and input voltages have the same phase. It means the output voltage is positive and negative if the input voltage is positive and negative respectively. This sort of output is ensured just by connecting the load with input with any polarity of the input voltage. The switching arrangement to achieve this target can be viewed in Figure 5a that demonstrates how the controlled switching units are turned on and off to achieve this target. The controlled switching units \(Q_{1}\), \(Q_{3}\), and \(Q_{5}\) are turned on and off with the same type of control signal \(c_{1}\) (\(c_{1}=c_{3}=c_{5}\)), and the switching control of \(Q_{2}\), \(Q_{4}\), and \(Q_{6}\) is ensured through \(c_{2}\) (\(c_{2}=c_{4}=c_{6}\)). Although, in equal phase operation, there is no need to turn on the controlled switching units \(Q_{3}\) and \(Q_{4}\). But their control terminals are connected to switching signals to simplify the control algorithm. Their conduction is blocked by reverse biasing their series-connected diodes as their anode is connected to negative polarity during the positive and negative value of the input respectively. The current closed loops of Figure 5b,c highlight the connection of the load to the source to ensure the voltage in phase operation that is to say.  
\[v_{o}(\omega t)\ =\ v_{in}(\omega t)\ =\ V_{m}\sin(\omega t) \tag{5}\]  
Figure 4: Inductor current elimination through turn-off delay angle.
###### Abstract  
With the increasing scale of low Earth orbit (LEO) satellite networks, leveraging non\(-\)terrestrial networks (NTNs) to complement terrestrial networks (TNs) has become a critical issue. In this paper, we investigate the issue of handover satellite selection between multiple terrestrial terminal groups (TTGs). To support effective handover decision-making, we propose a long short-term memory (LSTM)-network-based traffic prediction mechanism based on historical traffic data. Building on these predictions, we formulate the handover strategy as a Markov Decision Process (MDP) and propose an attention-enhanced rainbow-DQN-based joint traffic prediction and handover design framework (ARTHF) by jointly considering the satellite switching frequency, communication quality, and satellite load. Simulation results demonstrate that our approach significantly outperforms existing methods in terms of the handover efficiency, service quality, and load balancing across satellites.  
LEO satellite network; traffic prediction; LSTM; handover strategy; attention; rainbow DQN Article  
1
# Smart Deployable Scissor Lift Brace to Mitigate Earthquake Risks of Soft-Story Buildings
## 2 Smart Deployable Scissor Lift Brace
### System Initialization  
The structure featuring an open first story is equipped with a scissor lift brace mechanism, positioned at the basement level to accommodate the retracted state of the scissor lift. The mechanism is connected to a threaded bar and a motor, facilitating a rotary action to lift the scissor lift in response to earthquake alerts from the EEW system. A locking mechanism is incorporated into this arrangement to securely fasten the scissor lift to its original structure, ensuring adequate stiffness during an actual seismic event.  
In its initial retracted or undeployed state, the system operates without causing disruption to the occupants, allowing the building to maintain its open space. The system's effectiveness hinges on two essential requirements: a swift deployment speed and a reliable locking system. Achieving a high deployment speed entails the use of a suitable motor and a well-designed mechanical system. Meanwhile, the locking mechanism must be meticulously designed to firmly secure the scissor lift to the original structure, preventing any horizontal movement of the building during an actual seismic event.
## 3 Results
### Statistical Evaluation  
The transport simulations provided velocity fields that enabled the calculation of volume-based properties--\(\kappa\) and \(\tau\)--and surface properties, as discussed in Section 3.1. All of these showed statistical variations and were different in their ranges of values. For the volume-based properties of porous material, many approaches have been developed that describe the relationships between several properties of the material. The Kozeny-Carman relation is only one of them [47]. It is desired to have also a simple approach to calculate the surface properties from volume-based characteristics. As a first step, the statistical correlation between the results can be calculated. [PERSON] and [PERSON] [51] provided not only the fundamentals of various statistical tests, but also criteria for the proper choice of the right test for the desired evaluation. [PERSON]'s correlation test [51] allows for correlation coefficients to be calculated under the conditions mentioned above. Table 3 shows the coefficients \(r(a,b),a,b\in\{s_{\text{tot}}(q),\kappa,\tau\}\), \(r\in[-1,1]\) that were obtained using the R software [50,52].  
The total quantile areas \(s_{\text{tot}}(q)\) for \(q\in\{70\%,50\%,20\%\}\) were chosen as candidates for the correlation test with the volumetric properties: permeability \(\kappa\) and tortuosity \(\tau\). Correlation coefficients can indicate a positive \((r>0)\) or negative \((r<0)\) relationship. Every value other than an extreme one \(\in\{-10,1\}\) can only be used for comparisons. For this reason, the absolute value \(|r(\kappa,\tau)|\) was chosen as an indicator of whether a correlation coefficient indicates a possible physical relation. It was already shown by [PERSON] et al. [4] that \(\kappa\) and \(\tau\) are non-linear with respect to the Kozeny-Carman relation:  
\[\kappa\cdot\tau\sim\varepsilon\left(\frac{V_{p}}{S_{p}}\right)^{2} \tag{7}\]  
with only the geometric properties of the microstructure on the right side: the porosity \(\varepsilon\), total volume \(V_{p}\), and inner surface \(S_{p}\). In Table 3, the correlation between \(\kappa\) and \(\tau\) is \(r(\kappa,\tau)=-0.593\). The absolute value of every correlation coefficient between the surface-related properties \(s_{\text{tot}}\) and \(\kappa\) or \(\tau\) was much lower than this value. This indicates that there was no statistical correlation between surface-based and volume-based properties, although all of them were calculated from the same velocity field. Therefore, it is still necessary to perform transport simulations on the 3D structure to obtain the 2D properties presented in Section 3.1. The same conclusion was found in the analysis of the other interface (GDL/electrode) by [PERSON] et al. [26].
## 2 Materials and Methods
### Equipment  
The chemical compositions of GGBFS before and after alkaline activation were analysed by the Rigaku ZSX Primus II (Applied Rigaku Technologies, Austin, TX, USA). The minerology and quantification were determined by X-ray Diffraction. The synthesized composites were carbon coated and mounted onto a scanning electron microscope for particle morphology determination using a Tescan Vega 3 XMU machine (Tescan Orsay Holding, Brno, Czech Republic). The unconfined compressive strength of the alkali activated GGBFS specimens were analysed using a cyber plus compression machine (Matset S.p.A, Treviolo, Italy). Particle size distribution was conducted using a Microtrac particle size analyser (Microtrac MRB, Osaka, Japan). The potential toxic leachates were determined using an Inductively Coupled Plasma-Optical emission spectrometer (ICP) (Thermo Fisher Scientific, Waltham, MA, USA).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Chemical Composition (\%)** & **GGBFS** \\ \hline Na\({}_{2}\)O & 0.21 \\ MgO & 5.48 \\ Al\({}_{2}\)O\({}_{3}\) & 10.7 \\ SiO\({}_{2}\) & 27.2 \\ P\({}_{2}\)O\({}_{5}\) & 0.01 \\ SO\({}_{3}\) & 2.19 \\ Cl & 0.02 \\ K\({}_{2}\)O & 0.67 \\ CaO & 49.1 \\ TiO\({}_{2}\) & 0.97 \\ Cr\({}_{2}\)O\({}_{3}\) & 0.08 \\ MnO & 1.47 \\ Fe\({}_{2}\)O\({}_{3}\) & 1.22 \\ NiO & 0.01 \\ SrO & 0.29 \\ Y\({}_{2}\)O\({}_{3}\) & 0.02 \\ ZrO\({}_{2}\) & 0.1 \\ BaO & 0.3 \\ Loss of ignition & 0.23 \\ Specific gravity & 2.91 \\ Median particle size (\(\upmu\)m) & 45 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chemical and physical properties of raw GGBFS.  
Figure 2: X-ray Diffraction analysis of GGBFS (Q = quartz, M = magnetite).