esa-sceva/satcom-chunk-collection huggingface dataset:
# Partially versus Purely Data-Driven Approaches in SARS-CoV-2 Prediction
## 3 Material and Methods
### Predictive Analytics  
#### 3.2.1 Linear Regression Model  
Linear regression is a type of statistical analysis that attempts to show the relationship between two variables, dependent and independent variable. The central problem of linear regression is to infer a pattern from a set of training data and how to map new inputs of the same type to corresponding output [2]. Linear regression is widely used in prediction [19], which predicts new labels based on linear fit of the data by reducing the least square error of the predicted data points. Least squared error is measured by finding the distance between the real data points to the generated predictive model and referred to the mean square error, as shown in Figure 5. Linear regression's main aims are to first establish if there is a relation between the two sets of variables (dependent and independent). More specifically, establish if there is a statically significant relationship between them; the level of how significant the relation is can be measured using different performance measurements that will be described later in this section; second, forecast new observation for the aim of answering the following question, \"can we use what we know about the relation to forecast unobserved values?\"  
The linear regression approach may be used to predict COVID-19 through a learning model that correlates those two sets of variables (confirmed, new and death cases from one side) to the dependent variable (time on another side). The learning process can be done by finding the optimal parameters (shown in Equation (1)) for the linear fit by reducing the least squared error.  
Equation (1) shows the relation between independent and dependent variable in the generated linear predictive model:  
\[Y=B_{0}+B_{1}X+\varepsilon \tag{1}\]  
where  
\(Y\): dependent variables: confirmed, new and death cases.  
\(X\): Independent variable: time  
\(B_{0},B_{1},\text{ and }\varepsilon\): Intercept, slope, and standard error respectively.  
\(B_{0}\): is the line intercept and defined as the average value for \(Y\) when x = 0, could be negative value.  
\(B_{1}\): is defined as the value increased by \(Y\) for every unit increased by \(X\), it measures the sensitivity of \(Y\) when \(X\) increased.  
\(\varepsilon\): standered error that should be minimized.  
Figure 5: Linear Regression Model.  
In this paper, we used linear regression to predict the number of COVID-19 new, confirmed, and death cases for a new unseen time (future time). The model confidence level is taken at 95%, so the model is significant at \(p\leq 0.05\). The number of new, confirmed, and death cases are predicted for all three selected countries: US, Italy, and Jordan. The developed models are evaluated using SSE (sum of squared error), MSE (mean squared error), R Squared, and the model's significance is evaluated at \(p\) value \(<0.05\). The results of the linear regression models is shown and discussed in Section 4.1.
# Effects of Irrigation with Desalinated Water on Lettuce Grown under Greenhouse in South Korea
## 2 Materials and Methods
### Experimental Design
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Experiment** & **Planting Date** & **Harvest Date** & **Irrigation** & **Daily** & **Daily** & **Daily Relative** \\  & & & **Amount** & **Temperature** & **Humidity (\%)** \\ \hline \multicolumn{5}{c}{Saline water irrigation (BS: before water treatment using the BWD system a)} \\ First phase & 20 March 2015 & 10 April 2015 & 100.0 & 30.8 & 18.4 \\ Second phase & 30 April 2015 & 21 May 2015 & 117.5 & 32.2 & 22.8 \\ \hline \multicolumn{5}{c}{Desalinated water irrigation (AS: after water treatment using the BWD system)} \\ First phase & 17 June 2015 & 8 July 2015 & 97.0 & 30.3 & 40.1 \\ Second phase & 1 September 2015 & 22 September 2015 & 124.0 & 29.8 & 46.1 \\ \hline \hline \end{tabular}  
* a indicates the small-scale brackish water desalination (BWD) system.  
\end{table} 
Table 1: Planting and harvesting dates, irrigation amounts and daily averages of temperature and relative humidity for each experimental phase. Figure 1: Small-scale brackish water desalination (BWD) system installed in the experimental site and experimental plots planted with lettuce.
## 2 Related Works
### Shallow Domain Adaptation Approaches  
Shallow approaches seek to bridge the gap between the source and target domains by aligning the domain distribution via either (i) instance weighting techniques or (ii) feature transformation techniques.  
Instance-based approaches resolve the domain adaptation problem by applying importance weighting techniques to correct the bias between the source and target domains.  
Figure 1: Taxonomy of domain adaptation approaches.  
Thus, the source domain samples are re-weighted based on the density ratio of the source and target domains, \(w(x)=\frac{Pr(x)}{Ps(x)}\), where \(w(x)\) is the re-weighting factor for the samples in the source domain [19]. Considering a basic scenario, where we need to create a model to identify cancer in a region with an extensive elderly population. Only a few examples from the target domain are supplied, and comparable statistics from other regions with a large youthful population are also provided. Transferring all the data from another region might not be successful because the elderly have a higher risk of cancer in comparison to a younger population. To reduce the difference between source and target samples, the straightforward approach is to assign weights to the instances in the source domain. The dimensionality problem impacts the instance re-weighting method, since it can be challenging to measure alignment in high-dimensional environments. Moreover, all instance-based techniques require some labeled data from the same distribution as the test data to perform effectively. Thus, it is not applicable within an unsupervised domain adaptation setting.  
Feature-based adaptation techniques, on the other hand, aim to transform the original features into a new feature space. Thereon, performing an optimization technique to reduce the gap between domains in the contemporary representation space. This feature transformation can be achieved through different techniques, including feature alignment [20], feature clustering [21], feature selection [22], and feature reconstruction techniques [23]. Techniques must be robust enough to handle the complexity of diverse feature spaces. In addition, there is a risk of over-fitting to the source domain or aligning features too closely, which might not generalize well to the target domain. It is also important to note that feature-based domain adaptation assumes the existence of a domain-invariant mapping from the source domain to the target domain. This assumption may not always hold true in practice, particularly for complex or non-linearly separable data distributions. In such cases, alternative approaches like deep adversarial models, or GANs may be more suitable.
# Axial Load Transfer Mechanism in Fully Grounded Rock Bolting System: A Systematic Review
## 3 Analysis and Results
### Influential Parameters on the Axial Behaviour of FGRBSs  
The performance of FGRBSs is generally governed by many key parameters which can generally be classified into three following sections: (a) the boundary conditions and the mechanical, structural, and geological properties of surrounding rock mass; (b) mechanical  
Figure 7: Bond–slip relationship [65].  
properties of grout, and (c) effects of bolts geometry and surface profile configuration on rock bolt performance. However, [PERSON], [PERSON] [39] suggested that the bolt's profile and the strength characteristics of the bonding agent play the most significant roles among other effective factors [39]. The other influential parameters on the performance of axial transfer mechanism load of FGRBSs, which can be evaluated by conducting experimental tests, are as follows: EL, annulus thickness, hole diameter, installation procedure, cleanness of drilled hole, moisture content of the drilled hole, surface profile of the drilled hole, quality of grout pumping, and grout mixing. This process includes factors like the cleanliness of the drilled hole, its moisture content, the surface characteristics created by drilling, and the quality of both the grout mixing and pumping. It is also worth noting that, for dynamic ground conditions, yielding rock bolts can be particularly effective. These bolts, often created by modifying the geometry and surface profile of FGRBSs, can address the dual challenge of high loading capacity and significant energy absorption [20].
_Article_  
**Uptake of Potentially Toxic Elements by Four Plant Species Suitable for Phytoremediation of Turin**  
**Urban Soils**  
**[PERSON] 1,*, [PERSON] 1(c), [PERSON] 1(c), [PERSON] 1, [PERSON] 2, [PERSON] 2(c), [PERSON] 3 and [PERSON] 1**  
1 Department of Analytical Chemistry, University of Torino, Via [PERSON] 5, 10125 Torino, Italy; [EMAIL_ADDRESS] (M.M.); [PERSON]S] (D.F.); [PERSON]G.B.); [PERSON]ESS] (P.C.)  
2 Department of Life Sciences and Systems Biology, University of Torino, [PERSON] 25, 10125 Torino, Italy; [EMAIL_ADDRESS] (A.F.); [PERSON]M.M.)  
3 Department of Drug Science and Technology, University of Torino, Via [PERSON] 9, 10125 Turin, Italy; [EMAIL_ADDRESS]  
* Correspondence: [EMAIL_ADDRESS]  
Received: 7 May 2020; Accepted: 4 June 2020; Published: 6 June 2020  
**Abstract:** This study investigated the concentrations of 22 elements in two Turin urban soils located in the city center (Campana Street garden (CA)) and in a peripheral area (Nobile Park (NOB)). The former was found contaminated by Pb, Zn, Ba, Cr and Ni and, to a lower degree, by As, Co, Cu and Cd, while the latter showed high concentrations of Co, Cr and Ni. The nature of Cr, Ni and Co in both sites is mainly geogenic, whereas the high content of Pb, Zn, Ba, As, Cu and Cd in the CA soil is probably due to exposure to atmospheric deposition linked to emissions from motor vehicles, domestic and industrial burning of fossil fuels and industrial emissions. We evaluated the uptake of potentially toxic elements (PTEs) by four plant species suitable for phytoremediation (_Brassica juncea, Helianthus annuus, Zea mays_ and _Pteris vittata_) in controlled conditions in CA and NOB soils in order to assess their efficiency in the absorption of PTEs and suitability to restore the CA site. Results highlighted a different uptake ability of the plants according to the considered element; for example, _Brassica juncea_ demonstrated a great capability in cadmium uptake. The effect of a soil improver, derived from the composing of green and organic waste, on absorption efficiency was also studied and it altered uptake preferences of specific elements by the tested plant species, thus suggesting that its use has to be evaluated according to the target.  
**Keywords:** phytoremediation; potentially toxic elements; contaminated urban soil; soil improver
# A Method of Free-Space Point-of-Regard Estimation Based on 3D Eye Model and Stereo Vision
## 3 Methods
### Eye Features Extraction  
Eye feature extraction is a basic component of most of the gaze tracking systems. Due to the installation of the near infrared light source, the dark pupil effect can be observed clearly from the images captured by the video camera, which makes it easier to extract the pupil contour. The device proposed in this paper is equipped with the stereo cameras. After obtaining the position of the pupil contour in the image, the spatial position of the pupil contour can be solved by using epipolar constraint. The extracting process of the eye features has been detailed explained in our previous work [33].  
Due to the installation of the semi-transparent mirror, the eye cameras are able to capture the images of the eye region from the position of the virtual camera, i.e., the front view of the face. Therefore, simple algorithms can be effective for extracting accurate inner eye corner features. In this paper, a multi-scale Harris corner extraction algorithm [34] is used to get the sub-pixel coordinates of the inner eye corner. The result of eye features extraction is shown in Figure 5.  
Figure 4: The distribution of the virtual cameras with coordinate system definition in the gaze tracking system.  
Figure 5: (a,b) show the images captured by a pair of eye cameras after epipolar rectification, and the extracted pupil contour and inner eye corner are marked in these two graphs; and (c) represents the spatial coordinates of detected eye features.
# A Methodology to Evaluate Standards and Platforms within Cyber Threat Intelligence
## 4 Standards Evaluation Results
### Evaluation of the Standards  
After the selection and definition of the standards, an evaluation was made based on academic literature, the study of official documentation and practical demonstrations.  
Taking into account the aforementioned criteria, the evaluation of the standards was made and it is summarized in Table 5. Regarding the results illustrated in Table 5, two considerations must be highlighted. First, as explained before in Section 4.1.1, since CybOX and STIX were usually used together and both standards are maintained by the same organization, CybOX was integrated into the second version of STIX and it is no longer used as an independent language. Thus, as CybOX is now a part of STIX structure it was considered more plausible to evaluate them as a single standard. Second, it was noticed that even though TAXII and RID are autonomous protocols, they are mostly used combined with STIX and IODEF, respectively. It stems from the fact that TAXII and RID are protocols designed specifically to facilitate the transport of STIX and IODEF. Hence, it was chosen to evaluate these protocols as pairs (STIX/TAXII and IODEF/RID) considering the fact that their functions are complementary.
## 4 Results and Discussion
### Sensitivity Analysis
#### 4.2.3 Reservoir Porosity  
Figure 19 shows the variations of hydrate saturation, elastic modulus, and cohesion of the reservoir and wellbore yield area within 0.5 m of the wellbore 20 h after the drilling fluid invasion with other parameters remaining constant (assuming the reservoir porosity changed, but the formation mechanical parameters did not). Figure 20 shows the distributions of hydrate saturation and effective plastic strain around the wellbore 20 h after the drilling fluid invasion, respectively. We can see from the simulation results that the hydrate decomposition ranges at different reservoir porosities differed to some extent; with the increase in porosity of the hydrate reservoir, the hydrate decomposition range near the wellbore gradually reduced, the range of the formation with elastic modulus and cohesion drop also decreased, the range of effective plastic strain around the well also became smaller, and the region of the wellbore with plastic yield also shrunk accordingly. The increase in reservoir porosity makes the plastic yield area decrease. The risk of wellbore instability in the hydrate reservoir with higher porosity will be much greater than that in the reservoir with lower porosity after the complete decomposition of the hydrate.  
Figure 19: The variations of hydrate saturation and elastic modulus, and cohesion of the reservoir and wellbore yield area after the drilling fluid invasion. (**a**) hydrate saturation, (**b**) elastic modulus, (**c**) cohesion of the reservoir, (**d**) cohesion of the wellbore yield area.  
Figure 18: Distributions of effective plastic strain around wellbore at different times.
## 1 Introduction  
### Trust and e-Business  
Trust in a (trans)national invoicing system requires a robust and reliable mechanism to handle faults and ensure system integrity for its participants. Traditionally, trust is inter-mediated by government-regulated third parties, with banks and financial institutions being obvious examples. Increasingly, more decentralised solutions are being sought that circumvent single (or limited numbers of) authorities. These involve the use of blockchain technologies that allow a financial ledger to be distributed and regulated among the participants. A key idea is that the distributed ledger can be universally agreed upon. Two possible approaches to consider regarding distributed systems that share ledgers are crash fault tolerance and Byzantine fault tolerance. Crash fault tolerance assumes that faulty nodes might fail by crashing, in which case they stop participating in the system while the rest of nodes continue to operate. Byzantine fault tolerance, on the other hand, allows for arbitrary fault behaviours, including malicious actions. For this reason, Byzantine fault tolerant systems are more trusted than those which are only crash fault tolerant.  
In a large open and public e-business environment, more trust in the shared financial ledger is desirable, so Byzantine fault tolerant e-business systems are preferred because they provides better and stronger guarantees. This paper addresses the following questions: what is the impact on performance for the increased trust guaranteed by Byzantine fault tolerance? Furthermore, will the additional overhead required allow a Byzantine fault tolerant e-business system to work on a (trans)national scale?
## 5 Conclusions  
During steering maneuvers, real-time monitoring of the vehicle's side slip angle and yaw rate is essential. To maintain lateral stability, an external yaw moment must be applied, which increases energy consumption. Therefore, balancing lateral stability with energy consumption becomes a critical challenge.  
This paper presents a novel adaptive compound controller based on phase plane analysis to effectively balance vehicle stability and energy savings during the steering process. By quantifying the overall stability of the vehicle, the control framework can continuously switch between the pure energy-saving controller, the adaptive stability and energy-saving controller, and the stability controller in real time, with the obtained results summarized as follows:  
* A compound control strategy, which integrates an adaptive-layer controller, is employed to preserve the advantages of hierarchical control and simultaneously improve energy efficiency.
* The proposed SEC strategy dynamically adjusts the adaptive coefficient based on the vehicle's battery state and divides the phase plane diagram into three regions according to the evaluation index, which effectively balances lateral stability and energy savings.
* Simulation results demonstrate that the SEC strategy prioritizes energy savings as the battery's state of charge decreases.
* These findings verify the effectiveness of the proposed adaptive compound controller in achieving a robust balance between lateral stability and energy savings.  
Conceptualization, X.H. and X.C.; Methodology, K.X. and X.C.; Software, K.X.; Validation, K.X.; Formal analysis, K.X. and X.C.; Resources, X.H.; Writing--original draft, K.X.; Writing--review & editing, X.H., X.C. and X.N.; Supervision, X.H. and X.C.; Project administration, X.H. and X.N.; Funding acquisition, X.H., K.X. and X.C. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Natural Science Foundation of China through Grant No. 52005443, the Natural Science Foundation of Zhejiang Province through Grant No. LQ21E050016, the China Scholarship Council through Grant No. 202407280003, and the Key Laboratory of Acoustics and Vibration Applied Measuring Technology, State Administration for Market Regulation through Grant No. AVL202303.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors are grateful to [PERSON] for his valuable discussions during the preparation of the paper.  
The authors declare no conflict of interest.
## 5 Conclusions  
In this research, we proposed a platinum catalytical plate burner with a clover-shaped microchannel design, which can be stacked with a plate reformer for integration within a cylindrical adiabatic container. By investigating three different catalyst placements (50/50, 40/60, and 30/70), we optimized the temperature uniformity of the combustion chamber to achieve a low temperature difference (\(\Delta\)T\({}_{\text{max}}\)) of less than 25 \({}^{\circ}\)C, improved the stability of the long term operation of a methanal steam reforming system with high performance. The catalyst state after the 30 h long-term operation also illustrates the relevant results of transmission electron microscopy (TEM) analysis: optimized combustion chamber (30/70 type) vs. unmodified Combustion chambers (50/50 type) exhibited more uniform sintered catalyst particles throughout the fluid passage, helping to extend catalyst life. Additionally, when integrated with the Methanol Steam Reforming (MSR) system, the CO concentration in the reformer can be effectively reduced by 1.7% with a catalyst degradation rate of 0.16%/min, enabling highly efficient operation.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **This Work** & [15] & [16] \\ \hline Burner \(\Delta\)T\({}_{\text{max}}\) & 25.8 \({}^{\circ}\)C & 20 \({}^{\circ}\)C & 28.7 \({}^{\circ}\)C \\ \hline Burner hydrogen & 99.9\% & 98.21\% & NA \\ conversion rate & & & \\ \hline Reformer methanol & Decrease from 97.1\% & & \\ conversion rate & to 92.3\% (after 30 h) & & 57.79\% (after 20 h) \\ \hline Reformer carbon & & & \\ monoxide selectivity & 7.58\% & NA & 4.02\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of the performance of various burners when integrated with methanal steam reformer.  
Supplementary Materials: The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app142412069/s1](https://www.mdpi.com/article/10.3390/app142412069/s1)]([https://www.mdpi.com/article/10.3390/app142412069/s1](https://www.mdpi.com/article/10.3390/app142412069/s1)), Figure S1: Swiss-roll reformer; Figure S2: Swiss-roll burner; Figure S3: Cloverleaf Counterflow Micro-channel Plate Gas Flow Structures; Figure S4: Burner solvent; Figure S5: Nickel mesh; Figure S6: Burner catalyst preparation process; Figure S7: Integrated autothermal methanol steam reforming system.  
Conceptualization, F.-G.T.; methodology, F.-G.T.; validation, W.-H.H.; investigation, W.-H.H.; resources, F.-G.T.; writing--original draft, W.-H.H. and H.-J.L.; writing--review and editing, F.-G.T.; visualization, X.-J.W.; supervision, F.-G.T.; project administration, F.-G.T.; funding acquisition, F.-G.T. All authors have read and agreed to the published version of the manuscript.  
The research was financially supported by the Ministry of Science and Technology (MOST) of Taiwan (MOST 110-2221-E-007-076-MY3).  
Not applicable.  
The data presented in this study are available upon request.  
The authors declare no conflicts of interest.