esa-sceva/satcom-chunk-collection huggingface dataset:
# Theoretical Study on Geometries of Electrodes in Laboratory Electrical Resistivity Measurement
## 2 Theoretical Background  
### Electric Potential from a Point Electrode  
Electrical resistivity is defined by [PERSON]'s law and [PERSON]'s flux theorem. [PERSON]'s law as an empirical equation gives \(R=V/I\), where \(V\) and \(I\) are the potential differences across a resistor and the current passing through it, respectively. Meanwhile, [PERSON]'s flux theorem defines the flow and distribution of an electric charge induced by an electrical field. To formulate the electrical potential of a single electrode, [PERSON]'s law can be alternatively rewritten in terms of the electrical field strength \(E\) (volts/m) and current density \(J\) (amps/m\({}^{2}\)) when the electric field is conservative (i.e., curl \(\
abla\times\mathrm{E}=0\))  
\[J=\sigma E=\sigma(-\
abla V) \tag{1}\]  
where \(\sigma\) is the electrical conductivity of the material (1/\(\Omega\cdot\)m), \(V\) is the electric potential (volts), and \(\
abla\) is the del operator. By taking the del operator on both sides of Equation (1), it can be expressed as  
\[\
abla\cdot J=-\left(\underbrace{\
abla\sigma\cdot\
abla V}_{=0}+\sigma\
abla ^{2}V\right)=-\sigma\
abla^{2}V=0 \tag{2}\]  
The electrical conductivity in the homogeneous medium keeps constant, and thus the divergence of electrical conductivity becomes zero. The Laplace equation that describes the electrical potential distribution under steady-state conditions can be rewritten with the spherical coordinate system,  
\[\
abla^{2}V=\frac{1}{s^{2}}\frac{\partial}{\partial s}\left(s^{2}\frac{ \partial V}{\partial s}\right)=\frac{\partial^{2}V}{\partial s^{2}}+\left( \frac{2}{s}\right)\frac{\partial V}{\partial s}=0 \tag{3}\]  
where \(s\) is the distance from electrode center. By solving the second order Euler differential equation, it can be expressed as  
\[V=\frac{C_{1}}{s}+C_{2} \tag{4}\]  
Two constants, \(C_{1}\) and \(C_{2}\), can be obtained by imposing the boundary condition (\(V=0\) as \(s\)\(\rightarrow\)\(\infty\)) and using the relation between the current and current density,  
\[I=A\cdot J=A\cdot\left(\sigma\cdot-\frac{dV}{ds}\right)=A\sigma\frac{C_{1}}{s ^{2}}\ \ \ \ \therefore C_{1}=\frac{\rho I}{A}s^{2} \tag{5}\]  
where \(A\) is the equipotential surface area and \(\rho\), as electrical resistivity, has an inverse relation with its conductivity (=1/\(\sigma\)). Thus, the electric potential gradient (\(dV/ds\)) induced by a shaped electrode in the homogeneous half space helps to formulate general electrical potential [16],  
\[V=\int\frac{\rho I}{A}ds \tag{6}\]  
where \(A\) is the equipotential surface area as a function of \(s\), which is the distance from the electrode center line.
## 4 Security Analysis
### Repetitive Attacks Against a Node before Migration  
As mentioned in the previous section, to improve the successful attacking probability, single-step attacks can be launched repeatedly until a successful attack or an effective migration occurs. Similar to [7], we assume an attacker without memory. In this case, the repetitive attacks are independent of each other. Following [18; 60; 66], we describe the number of attacks on a node as a Poisson distribution. The average number of arrivals per interval is denoted as \(\varphi\). According to the previous section, a single-step attack follows a Binomial distribution with \(p_{A}\) successful probability. Then, in a migration period, the number of successful attacks follows a Compound Poisson distribution [28].  
Let \(Y(t)\) be a discrete random variable for the number of attacks before time \(t\). \(Y(0)\) indicates that attacks of this node start at time 0. According to Poisson distribution, the probability of a node being attacked \(i\) times can be obtained as  
\[P\{Y(t)-Y(0)=i\}=e^{-\varphi t}\cdot\frac{(\varphi t)^{i}}{i!}. \tag{1}\]  
Let \(F(t)\) be a discrete random variable for successful attacks before time \(t\). Considering the Binomial distribution, the probability of the node being compromised \(k\) times is  
\[P\{F(t)-F(0)=k\}=\sum_{i=k}^{\infty}\frac{(\varphi t)^{i}}{i!} \cdot e^{-\varphi t}\cdot\binom{i}{k}\cdot p_{A}^{k}\cdot(1-p_{A})^{i-k} \tag{2}\] \[= e^{-\varphi}\cdot\frac{(p_{A}\cdot\varphi)^{k}}{k!}\cdot\sum_{j =0}^{\infty}\frac{[\varphi(1-p_{A})]^{j}}{j!}=e^{-\varphi}\cdot\frac{(p_{A} \cdot\varphi)^{k}}{k!}\cdot e^{\varphi(1-p_{A})}\] \[= \frac{(p_{A}\cdot\varphi\cdot t)^{k}}{k!}\cdot e^{-p_{A}\cdot \varphi\cdot t}.\]  
Thus, the number of successful attacks on a node also follows a Poisson distribution with \(\varphi^{\prime}=\varphi\cdot p_{A}\). If attack rate for the system is represented as \(r\), \(\varphi=r\) and \(\varphi^{\prime}=rp_{A}\).  
Then we have the probability of no successful single-step attack in the first period is  
\[P\{F(T)-F(0)=0\}=e^{-Trp_{A}}. \tag{3}\]  
Computationally, it is possible to successfully attack a single node repeatedly within one migration period. But in reality, the attacker only needs to succeed in attacking this node once. The probability of compromising one node over each migration period is  
\[\mu=1-e^{-Trp_{A}}. \tag{4}\]
## 3 A Taxonomy of Measuring Methods, Techniques, and Sensors in Physiological-Based DMSs
### Photoplethysmography (PPG)  
Photoplethysmography is an optical measurement method used to record changes of blood volume in blood vessels. The PPG sensor integrates a light source (LED) and a photodetector (PD) to record the intensity of light that has passed through or been reflected from biological tissue. The intensity of the light changes depending on changes in blood volume at the location where the measurement is being made. Blood flow is pulsatile, and the resulting pulse wave can be detected in various parts of the circulatory system. Usually, in driver monitoring systems the PPG signal is used for monitoring HR and HRV, but it is known that the amplitude of the pulse wave is modulated by respiration. So, the respiration signal can also be extracted from the PPG for monitoring of the RR parameter. This technique is called PPG-derived respiration.  
Blood pressure measurement is another notable application field of the PPG method. The relationship between BP, pulse transit time (PTT), and wave arrival time (PAT) is well known [45; 46]. PTT is the time interval between the peaks of two PPG signals for one cardiac cycle, measured at two different locations on the body. PAT is the time interval between the R peak of the ECG signal and the subsequent peak of the PPG signal for the corresponding cardiac cycle. By using appropriate algorithms, the values of these parameters can be converted into BP values, but to implement this approach, two PPG sensors are required that simultaneously measure the PPG signals at a certain distance from each other. In 2021, [PERSON] et al. [47] proposed a PTT-based approach for continuous and cuffless BP measurement using single-site four-wavelength PPG signals (blue (470 nm),green (570 nm), yellow (591 nm), and red (635 nm)). The penetration depth depends on the wavelength of the light; therefore, the approach using multi-wavelength PPG signals can provide information about blood pulsations from different blood vessels located at different depths in the body. The time difference observed between PPG signals of different wavelengths obtained from the same body location can be considered as localized pulse transit time. Pulse wave analysis (PWA) is another recently used approach for cuffless blood pressure measurement using PPG signals [48]. This technique is based on extracting various features from the PPG signal and training machine learning models to estimate blood pressure values.  
In DMSs, the acquisition of PPG signals can be performed by using contact or non-contact techniques. In contact techniques, the PPG signal can be obtained from wearable or non-wearable devices.
## 2 Generalities and Classification of Cannabis Metabolites
### Specialized Metabolites of Cannabis  
To date, several NC specialized metabolites have been identified in _Cannabis_, located in various parts of the plants, including roots, leaves, stems, seeds, and pollen [29,39]. Identified quaternary amines include choline, trigonelline, L-isoleucine betaine, neurite, and muscarine, although the presence of muscarine in the roots remains uncertain [29]. These amines are derived from amino acids, similarly to piperidine, pyrrolidine, and hordenine, a phenylethylamine that is also found in _Cannabis_ (Figures 1 and 2).  
The spermidine-type alkaloids reported in _Cannabis_ include cannabisistovine and anhydrocannabisativine (Figures 1 and 2) [13,21,30,40]. In total, ten alkaloids have been identified in _Cannabis_, primarily found in the roots, but also detected in other parts of the plant [29]. Additionally, fifteen phenolic amides and lignanamides have been identified in _Cannabis_ (Figures 1 and 2). Among these are the hydroxycinnamic acid amides (HCAAs) N-trans-coumaroyl-tyramine in roots, and N-trans-feruloyltyramine and N-trans-caffeoyltyramine in flowers, seeds, and roots. Other metabolites include cannabis A to G, as well as cannabis M, N and O, 3,3'-demethylheliotropamide, and grossamide, with cannabis B and G present in the roots [12,14,29,30,41]. Cannabisins, 3,3'-demethylheliotropamide and grossamide are HCAA dimers, as shown in Figure 2.  
While flavonoids and stilbenes lack a nitrogen atom in their structures, they are derived from the phenylpropanol pathway and exhibit biological activities of medical interest. These metabolites are primarily found in the leaves and flowers of _Cannabis_. Notable flavonoids include cannflavin A, B, and C, whilst at least thirty distinct stilbenes have been identified [30,42].  
_Cannabis_ uses a variety of metabolic pathways to produce these specialized metabolites (Figures 1 and 2). In the following sections, we will explore these pathways, examining the biosynthetic routes that enable the production of both alkaloids and phenolic compounds.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Type** & **Precursor** & **Chemical** & **Example** & **Structure** \\ \hline Piperidine & Aspartate/ & Heterocyclic & Piperidine & \\ Pyrrolidine & Argin/ & Heterocyclic & Pyrrolidine & \\  &
# Power Factor Correction Application Based on Independent Double-Boost Interleaved Converter (IDBIC)
## 5 Conclusions  
The paper proposes a new type of converter for active Power Factor Correction applications, combining some key functions in one solution. The three voltage levels at the output together with the high gain capability could be favorable assets for future integration in bipolar symmetric/asymmetric DC microgrids. Likewise, the input interleaved operation and low voltage stress on the power semiconductors can be beneficial for efficiency improvements and high-power/high-voltage applications.  
The proposed converter has been analyzed through theoretical, simulated and practical approaches to highlight the overall impact of the solution. From the simulation results, the operation of the new converter meets the analytical description presented, where the mathematical model of the converter was developed to help tuning the control loop. According to the experimental part, near the converter rated power, the obtained results in terms of THD and power factor are improving. Another phenomenon that can be observed is that the converter has better performance, in terms of power quality, at higher voltage gains. In terms of efficiency, on the other hand, it has been observed that at low supply voltage, the efficiency is lower. Therefore, the performance is decreasing with the increasing of the converter's gain. In this matter, for future optimization iterations, this tradeoff must be considered, but with the remark that these are common facts in boost PFC applications.  
Regarding the converter overall performance attained, the results are promising, considering that this is the first prototype developed, which is not optimized in terms of switching and passive elements criteria. In view of this, future developments are mandatory for power and control optimizations, and more close analyses are needed on the implementation of the converter topology in market applications.  
Conceptualization, N.C.S. and P.D.T.; methodology, S.I.S.; software, L.N.P.; validation, N.C.S. and V.M.S.; formal analysis, V.M.S. and G.I.F.; investigation, S.I.S.; resources, N.C.S.; data curation, L.N.P.; writing--original draft preparation, N.C.S. and S.I.S.; writing--review and editing, P.D.T.; visualization, G.I.F.; supervision, N.C.S.; project administration, P.D.T. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the EUROPEAN REGIONAL DEVELOPMENT FUND through the COMPETITIVENESS OPERATIONAL PROGRAM 2014-2020 Romania, grant number 16/01.09.2016, project title \"High power density and high efficiency micro-inverters for renewable energy sources-MICROINV\".  
Not applicable.  
The authors declare no conflict of interest.
## 1 Introduction
road maintenance analysis and decision-making method, and used this method to balance maintenance costs, road conditions, and energy consumption; [PERSON] et al. [1] proposed a project two-layer network-level pavement maintenance decision-making optimization model consisting of a multiyear fund allocation model and a project selection model with the goal of maintenance efficiency; [PERSON] [9] established a multi-objective decision model for pavement maintenance with the minimum maintenance cost and maximum maintenance benefit as the maintenance goal under the financial constraints; [PERSON] [10] constructed a two-layer optimization model for network-level road surface decision making, with the maximum sum of vehicle travel cost savings and traffic revenue increase, and the minimum generalized cost of vehicle travel as the upper and lower objectives, respectively; [PERSON] [2] established a multi-objective network-level pavement maintenance decision optimization model under both deterministic and uncertain conditions, with the goal of achieving the average pavement performance and the percentage of road length that meets a certain pavement performance index threshold. In summary, existing research mostly establishes decision optimization models from the perspective of operating units, with objective functions mostly targeting maintenance costs, road network performance, investment benefit ratio, etc., and less considering optimization of user costs and the environmental impact of maintenance. There is a lack of comprehensive consideration of maintenance costs, road network performance, user costs, and the environmental impact of maintenance. In summary, based on the review of the existing literature, this article first analyzes and quantifies the user costs that affect the effectiveness of road maintenance. Secondly, through the concept of sustainable development of roads, the optimization of road maintenance decision making is divided into two steps: the first step is to determine the minimum maintenance budget funds, and the second step is to determine the optimal plan. The specific optimization method adopts the 0-1 mathematical programming method, establishes a network-level pavement maintenance decision optimization model based on a quantitative model, and identifies the most reasonable maintenance optimization plan among the four aspects of maintenance funds, maintenance performance improvement value, user benefit improvement, and environmental impact reduction. Finally, a road network in a province is selected for the case study. This study can help decision makers consider the diversity of practical problems from the perspectives of managers, users, and the environment, and make road maintenance decisions from a more reasonable perspective as China is about to enter a new era of \"focusing on maintenance\".
# How Biological and Environmental Factors Affect the Quality of Lavender Essential Oils
###### Abstract  
Background/ObjectivesThe plants of the _Lavandula_ genus are widely investigated because of their significance for pharmaceuticals and food. The composition of lavender essential oil is determined by genotype and can be induced by environmental, ontogenetic factors, and morphogenetic features. Linalool and linalyl acetate are the most abundant compounds, performing essential ecological functions and participating in lavender's therapeutic properties. This review reports on the biosynthesis of lavender oil compounds and summarises the environmental, developmental, and molecular factors contributing to essential oil composition in lavender flowers. **Results** Floral developmental stage and ontogeny are fundamental for optimal harvest time. The harvesting period for high-quality lavender essential oil is affected by environmental and developmental factors that influence the gene expression of monoterene biosynthesis. **Conclusions** These findings indicate the appropriate features for high-quality lavender essential oil and contribute to information that may allow for the manipulation of monoterenes biosynthesis in lavender breeding efforts.  
lavender; flower; essential oil; monoterenes biosynthesis; gene expression +
Footnote †: journal: Physiologia
# High-Performance Garbage Collection Scheme with Low Data Transfer Overhead for NoC-Based SSDC
## 2 Background
### Conventional SSD Organization  
Traditional SSD architectures typically comprise a CPU, DRAM, and multiple NAND flash memory units, referred to as channels. As shown in Figure 1, the CPU manages read and write requests from the host and temporarily stores data in DRAM. Given that the read and write speeds of NAND flash memory are significantly slower than those of the CPU and DRAM, parallelism is employed through multiple NAND flash channels.  
Historically, these components have been interconnected using a system bus, which serves as the communication highway. However, this bus-based approach comes with several inherent limitations. Buses are constrained in terms of bandwidth, which can lead to bottlenecks when multiple components attempt to communicate simultaneously. As the number of NAND flash channels increases, the bus must handle more requests, which exacerbates latency issues and limits scalability. This results in inefficient data transfer, particularly during critical operations such as GC, where data must be moved frequently and rapidly.  
Additionally, the bus architecture creates contention among different components, leading to delays that can severely impact overall SSD performance. The rigid addressing and communication methods of bus systems hinder the flexibility required for modern SSD workloads that demand high throughput and low latency. Thus, while conventional bus-based SSD controllers were suitable for early SSD designs, they struggle to meet the performance demands of contemporary applications.  
In contrast, the adoption of interconnect-based architectures, such as network-on-chip, offers significant advantages in handling the increasing complexity and performance requirements of SSDs. NoC systems facilitate better parallelism and scalability, allowing for non-blocking communication among components, which mitigates the limitations associated with traditional bus systems.
## 5 Results: The Geometry Assurance Process Today
### The Concept Phase  
For most companies in the study, the geometry assurance process starts with some kind of evaluation of concepts suggested by the design department. The suggested concepts are based on customer demands and other requirements and, to a large extent, also on experiences from previously produced models and projects.  
The geometry engineers check if the suggested concept(s) can be built with reasonable geometrical quality (see 1, Figure 6). At this first stage, the evaluation is usually based on discussions, previous experiences, and sometimes, also on simple styling surfaces. The positions of the split-lines between parts affect both the visual sensitivity to variation and the level of geometrical variation in, for example, a weld between two parts [32].  
The choice of locating scheme (2, Figure 6) is critical for the geometry assurance process. The locating scheme, used to fixate parts during assembly, must lock all degrees of freedom of a part and should be as robust as possible to variation. At this stage in the process, there usually exists a (not-so-detailed) CAD model of the part. This is exported from the CAD system in a neutral triangular format (often WRL or JT) and used in a variation simulation software to evaluate robustness. At the companies in this study, RD&T [7] is the most commonly used software. The suggested locating schemes are documented in reports and 2D drawings generated from the CAT tool. At one of the companies in the study, the produced results were linked to the 3D digital model.  
The next main step is to define the tolerances on the parts (3, Figure 6). The goal is to find tolerances such that the final requirements on the product can be fulfilled but, at the same time, keep costs down. Again, triangular representations of the CAD model are used as the input, together with  
Figure 6: The input and output to the current digital thread for different geometry assurance activities.  
old inspection data (from similar concepts), if available. The analysis is done using variation simulation software to predict the final variation on the product (or subassembly) level or by simplified analyses in Excel or similar. The predicted variation is compared with the requirement on the product level, and the process is iterated until satisfactory results are obtained. Of course, experiences from previous projects are also important input. The output is the part tolerances described in a variation simulation model and/or on 2D drawings.