esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### Objectives  
The millions of interactions that occur daily between organizations and users in these platforms generate millions of terabytes of information. The application of machine learning algorithms and multiple linear regressions allows us to extract the underlying knowledge in these immense information banks. Nevertheless, the ultimate goal of these techniques is the identification of trends, patterns, or models that facilitate decision-making and allow the organization to manage these technologies [29; 30] efficiently.  
Although some works have previously applied machine learning algorithms and multiple linear regressions to examine the activity occurred on social media, the dynamic and changing nature of these spaces requires constant updates of this knowledge [2]. An in-depth analysis of the trends and patterns of use is, without a doubt, the basis on which professionals in this field develop efficient management of these technologies in their organizations.  
This research, based on the application of machine learning algorithms and multiple linear regressions, aims to provide information that serves to update this knowledge about the media. Consequently, the main objective of this work is to identify the variables that allow organizations to manage their social network services efficiently.  
The object of study is the official Twitter accounts of university organizations in Spain. The social network service Twitter is taken as the object of research for the ease of access to the data. Likewise, the decision to opt for university organizations is due to the purely communicative purpose of these organizations, leaving aside the transactional objective of business organizations. Finally, the selection of Spanish institutions is justified both by the huge social media activity shown by universities in this country and by the variety of publication topics traditionally addressed by their accounts [31].  
In this setting, the research analyzes how certain characteristics of the content, on the one hand, and the message of the content, on the other hand, increase the recognition of publications through retweets and favorites.  
The characteristics of the content considered are publication volumes, publication components, and publication moments, whereas the effect of the message of the content focuses on the publication topics. This research will, therefore, answer the following two research questions:  
Research Question I (RQI): What are the publication volumes, publication components, and publication moments that increase content recognition in the form of retweets and favorites?  
Research Question II (RQII): What are the publication topics that increase content recognition in the form of retweets and favorites?
# Notch Fatigue Life Research Based on Critical Distance Theory
## 6 Conclusions  
1. The stress prediction value based on the point method at the cross-sectional cutout of steel box girders is 7-13% higher than that of the line method, and the fatigue life prediction value of the point method is basically more than 50% lower than that of the line method; the point method prediction value is more conservative than that of the line method.
2. The fatigue prediction model of steel box girder transverse bulkhead arc cutouts proposed in this paper has high accuracy, which is more precise compared with other methods currently used in engineering applications, and verifies the effectiveness and feasibility of the critical distance method. The fatigue life prediction results of the line method and the section model fatigue test results are basically about 10% error, the source of error is inferred to be related to the size effect, and the error will be further reduced if the volume method is used.
3. Whether using the point method or the line method, the calculated characteristic stress decreases with the increase in notch radius; the fatigue life increases with the increase in notch radius. When designing the curved notch of steel box girder cross-sections, the appropriate increase in notch radius is beneficial to the improvement of the fatigue life of the structure.
4. In this paper, the fatigue test specimens are all smooth curved notch specimens, and for the members containing initial defects, the calculation model for assessing fatigue life using critical distance theory needs further study.  
Conceptualization, H.N. and Y.Y.; Methodology, J.C. and Y.Y.; Software, H.N.; Validation, J.C.; Formal analysis, J.C.; Investigation, L.H. and Y.Y.; Resources, Z.C.; Writing--original draft, J.C.; Writing--review & editing, H.N. and Z.C.; Visualization, L.H.; Supervision, L.H.; Project administration, J.C. and Z.C.; Funding acquisition, Z.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Changsha City Natural Science Foundation Project, grant number kq220207 and Hunan Provincial Natural Science Foundation Project, grant number 2023 JJ40505.  
The authors declare no conflict of interest.
# Optimal Design of Small-Aperture Optical Terminals for Free-Space Links
## 4 Conclusions  
In this paper, we have outlined the process for designing a low-complexity optical terminal for fixed or dynamic terrestrial FSO links of lengths on the order of kilometres. The design balances geometric and fibre coupling losses by constraining the terminal's aperture size to achieve maximal power throughput over the link and minimal scintillation. The terminal features TT compensation through a fast-steering mirror with a constrained range and bandwidth, which keeps the power throughput and scintillation optimised in the presence of atmospheric turbulence and tracking errors. Optimised terminal parameters--aperture diameter, effective focal length, total power throughput, and TT bandwidth and range--are presented in Tables 1 and 2 for a variety of link lengths and turbulence strengths. For dynamic links, it is necessary to know the residual TT due to imperfect target tracking, at which point the analyses presented are immediately applicable.  
[PERSON] wrote the manuscript with input from all authors and conducted all the contained analyses; B.D.-M. provided detailed guidance on the overall structure of the manuscript; [PERSON] assisted with numerical simulations; [PERSON] and S.S. provided general supervision. All authors have read and agreed to the published version of the manuscript.  
This work has been supported by the SmartSat CRC, whose activities are funded by the Australian Government's CRC Program. [PERSON] is supported by an Australian Government Research Training Program Scholarship and a top-up scholarship funded by the Government of Western Australia.  
Not applicable.  
The datasets generated during this study are available from the corresponding author on request.  
The authors thank [PERSON] and [PERSON] for manuscript feedback.  
The authors declare that this study received funding from SmartSat CRC. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} SMF & Single-mode fibre \\ FWHM & Full width at half maximum \\ FSO & Free-space optical \\ RMS & Root mean square \\ TT & Tip-tilt \\ PSD & Power spectral density \\ \end{tabular}
# Energy-Aware Online Non-Clairvoyant Scheduling Using Speed Scaling with Arbitrary Power Function
## 3 Definitions and Notations
### Scheduling Basics  
An online non-clairvoyant uni-processor job scheduling HSIF is proposed, where jobs arrive over time and there is no information about the sizes of jobs. The importance/weight/priority (generated by the system) \(imp(j)\) of any job \(j\) is known at job's arrival and size is known only at the completion of a job. Jobs are sequential in nature and preemption is permitted with no penalty. The speed of a processor \(s\) is a rate at which the work is completed. At any time \(t\), a job \(j\) is active if arrival time \(ar(j)\leq t\) and the remaining work \(rem(j,t)>0\). At time \(t\), the scaled importance of a job \(j\) is \(pr(j,\ t)\). Executed time \(ext(j,\ t)\) of a job \(j\) is current time \(t\) minus arrival time \(ar(j)\), i.e., \(ext(j,\ t)=(t-ar(j))\).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Function Type Used**} & \multirow{2}{*}{**Algorithms**} & \multicolumn{3}{c}{**Competitiveness**} & \multicolumn{1}{c}{**Clairvoyant/**} \\ \cline{3-6}  & & **General \(\alpha\)** & \(\alpha\) = 2 & \(\alpha\) = 3 & **Non-Clairvoyant** \\ \hline \multirow{2}{*}{**Traditional Power**} & SelMig [27] & \(\alpha^{2}\) & 4 & 9 & Non-clairvoyant \\  & NC [11] & \(\left(2+\frac{1}{\alpha-1}\right)\) & 3 & 2.5 & Non-clairvoyant \\  & ALG [12] & \(\left(\frac{2n}{\ln\alpha}\right)\) & 2 & 2.52 & Clairvoyant \\  & & \(\left(for\ large\ value\ of\ \alpha\right)\) & & & \\ \hline \multirow{2}{*}{**Arbitrary Power**} & WLAPS [26] & \(16\left(1+\frac{1}{\epsilon}\right)^{2}\) & \multirow{2}{*}{\(>\)16} & \multirow{2}{*}{\(>\)16} & \multirow{2}{*}{Non-clairvoyant} \\  & & _where \(\epsilon>1\)_ & & & \\ \multirow{2}{*}{**Function**} & OCA [10] & 2 & 2 & 2 & Clairvoyant \\ & HSIF [this paper] & 2 & 2 & 2 & Non-clairvoyant \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of previous results. SelMig: Selfish Migrate; NC: Non-Clairvoyant; ALG: algorithm proposed by [PERSON] et al.; WLAPS: Weighted Latest Arrival Processor Sharing; OCA: online clairvoyant algorithm; HSIF: Highest Scaled Importance First.  
The scaled importance based flow of a job is integral over times between the job's release time and its completion time of its scaled importance at that time. The ascending inverse density (a) of a job \(j\) is executed time divided by its importance, i.e., \(a(j)=\left(\frac{ext(j,t)}{imp(j)}\right)\). The ascending inverse density is recalculated discretely either on arrival of a new job or on completion of any job. The response time of a job is the time interval between the starting time of execution and arrival time of a job. The turnaround time is the time duration between completion time and arrival time of a job. The weight, importance and significance of a job are used as the synonyms of the priority of jobs.
## 3 Results and Discussion
### The Influence of Sulfur and Development Time  
#### 3.4.1 Fluorescence Microscopy Test  
The SBS-modified asphalt with and without sulfur was tested by fluorescence microscopy after high-temperature development [34; 35; 36]. The test results are shown in Figure 9.  
For SBS-modified asphalt with sulfur addition, there is a clear filamentous SBS polymer network from the start to the 6 h development time. After 6 h of development, the filamentous structure becomes unclear and it might be indicative of the degradation of the SBS polymer network.  
SBS-modified asphalt without sulfur addition shows a filamentous SBS polymer structure which grows more obvious with extended development time. The width of the filamentous SBS also increases, suggesting the structure is strengthened during the development.  
Related studies [37; 38; 39] have reported that the sulfur-crosslinked SBS network might be more vulnerable to thermal storage. The C-S bond introduced by sulfurization is sensitive to heat and might break during the development stage of the modified asphalt production. On the other hand, SBS-modified asphalt without sulfur does not contain heat-sensitive C-S bonds, so the development only facilitates its swelling and thus a stronger polymer network is observed with extended development time.
# eHealth Integrity Model Based on Permissioned Blockchain +
## 2 Blockchain Based eHealth Integrity Model
### Requirements  
In the presented model, it was assumed that the eHealth system has a distributed architecture. In such an architecture, one or more central (usually government-owned) clouds and many interconnected healthcare sites (e.g., hospitals) exist. In the BEIM, it is assumed that all healthcare sites use software certified by a government authority that allows access to central health services. The BEIM allows implementing the following security services that can together provide transactional transparency in the eHealth system using a permissioned blockchain. These are services allowing the verification of:  
1. EHR integrity;
2. access permissions to records in each EHR; andaudit logs related to each EHR.  
In all three cases, it should be possible to detect if all records are present, unmodified, and that the order in which they were added is preserved (backdating detection). Additionally, it should be possible to prove that a document was not added.  
A fundamental blockchain property is the inability to delete or modify data that already exist in a blockchain. This contradicts a legal requirement for almost every eHealth system to have the option to remove patient records. Usually, in case of an erroneous entry, a new entry is added. However, there are legal cases that require a removal option. Two types of transaction ('add' and'remove') are used to implement that option. Therefore, there is no need to remove transactions from the blockchain.  
Taking into account the sensitive nature of medical records, transactions in a blockchain should not contain any unencrypted data about patient health. Transactions can only contain metadata about medical documents (records), access rights, or log entries.
## 4 Performance Results and Discussion
### Evaluation of Setup 5: Redundant Transmission via 5G Mid-Band and 5G mmW Systems  
The results of Setup 5, using one mid-band and one mmW system, are shown in Figure 15. The end-to-end latency of the individual UEs, one and two, are given in Figure 15a,b as a distribution over time. UE1 with a mean latency of 6.24 ms and UE2 with 2.35 ms. The combined transmission after elimination on Switch 2 is shown in Figure 15c, with an average latency of 2.35 ms. With the shorter transmission time of the mmW system compared to the mid-band system, the impact of FRER is very limited. Similar to Setup 4, it can be seen that different spikes in the mmW plot have been equalized by the mid-band system. Further, compared to Setup 4, no latency spike could be detected in all three plots. Due to the very high degree of redundancy, there was no shared resource that could create a latency spike accruing in both communication paths.
## 3 Experimental Results
### 2 \(\times\) 2 Array Performance  
The 2 \(\times\) 2 array shown in Figure 8 is the basic unit cell of the Ka-band transmitter. In the 2 \(\times\) 2 array, the antenna elements are configured by using a sequentially rotated manner, where two adjacent radiators are separated by 5.3 mm. This configuration leads to an improvement of both polarization purity and radiation pattern symmetry [30], and its size allows for the subsequent assembly of the MMIC component on the bottom side of the PCB.  
The complete Ka-band antenna will be built with many of these unit cells, so to maintain the distance of 5.3 mm between antenna elements, the 2 \(\times\) 2 array must not be larger than 10.6 mm \(\times\) 10.6 mm. Because of this, the H-slots (L4) and the input ports in the bottom layer are orthogonally placed in order to achieve the integration of the whole feeding network, from chipset to patch, in a minimum space.
## 5 Discussion and Conclusions
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **(1)** & **(2)** & **(3)** & **(4)** & **(5)** \\ \hline
**Models** & **Model 1** & **Model 2** & **Model 3** & **Model 4** & **Model 5** \\ \hline ma2x & 24.6666 **\({}^{*}\)** & \(-0.1102\) & \(-3.6657\) & \(-4.5840\) & \(-4.4747\)\({}^{**}\) \\  & (5.5449) & (1.6010) & (2.5841) & (1.9957) & (1.3032) \\ ma3x & 0.0295 \({}^{*}\) & \(-0.0005\) & \(-0.0043\) & \(-0.0042\) & \(-0.0061\)\({}^{**}\) \\  & (0.0097) & (0.0021) & (0.0028) & (0.0022) & (0.0010) \\ ma4x & 14.2537 \({}^{*}\) & \(-0.2065\) & \(-0.9629\) & \(-0.9985\)\({}^{*}\) & \(-2.0066\)\({}^{**}\) \\  & (4.6376) & (0.8448) & (0.5260) & (0.4090) & (0.2180) \\ ma5x & 0.8242 \({}^{*}\) & \(-0.0166\) & \(-0.1214\) & \(-0.1074\) & \(-0.1789\)\({}^{***}\) \\  & (0.2932) & (0.0646) & (0.0751) & (0.0612) & (0.0300) \\ ma6x & 0.0419 \({}^{*}\) & \(-0.0006\) & \(-0.0027\) & \(-0.0026\) & \(-0.0059\)\({}^{***}\) \\  & (0.0147) & (0.0026) & (0.0016) & (0.0012) & (0.0007) \\ \hline \hline \end{tabular}  
* Notes: Robust standard errors in parentheses, \({}^{***}\)\(p<0.01\), \({}^{**}\)\(p<0.05\), \({}^{*}\)\(p<0.1\). The control variables are the same as in Tables 4 and 5, which are not reported here due to limited space.  
\end{table} 
Table 6: Additional robustness test. countries, the heterogeneity of socio-economic effects on regional development from HSR also needs further analysis. [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] wrote the paper and [PERSON] proofread the article for language editing. All authors have read and agreed to the published version of the manuscript. This research was funded by the Project of Postgraduate Research & Practice Innovation Program of Jiangsu Province, grant number (No. KYLX16-0276). The authors declare no conflict of interest.
# Breast Geometry Characterization of Young American Females Using 3D Image Analysis
## 3 Result and Discussion
### Breast Shape Analysis  
As Table 5 illustrates, five shape components were extracted from 26 measurements by principal component analysis. Varimax rotation was used, and the rotation converged in seven iterations. The first component consisted of most of the measurements, which were related to breast dimensions, including total volume, arc, and linear lengths. The second and third components were represented by widthwise and height-wise ratios, respectively. The fourth component was explained by breast angles. From multiple perspectives, the inner breast measurements were found to belong to unusual components. Unlike other widths/heights and angles, the inner width and angle settled in the second component. The ratio between breast width and height solely formed the fifth component. Factor analysis allowed factor scores to be calculated for each component, and these scores assisted in distributing the 156 breasts into four shape clusters. A total of 156 cases were split into 48, 30, 37, and 41 cases to form each cluster. One-way ANOVA supported the classification, where all measurements had meaningful F-values at \(p\) = 0.000 significance level. [PERSON]'s post-hoc analysis was followed to see the unique geometrical characteristics of each cluster. The post-hoc results are summarized in Table 6. Clusters 2 and 4 had obvious geometrical features being significantly small and large, respectively. Most arc, width, height, and depth measurements, as well as areas and volumes, recorded largest with cluster 4 and smallest with cluster 2. Cluster 4 had an average breast volume of 726 cm\({}^{3}\) with a breast base area of 220 cm\({}^{2}\) and a breast depth of 71 mm. In contrast, the average breast volume of cluster 2 was less than half of cluster 4, 324.552 cm\({}^{3}\), with a breast base area of 150 cm
## 4 Adaptive Fault-Tolerant Communication Scheme
### Fault-Tolerant Priority Queue
It represents the time period in which the sensor \(S_{i}\) wants to maintain the activation of the fault-tolerant priority \(p\). The function acquiescence\({}_{ip}(t)\) indicates whether the sensor \(S_{i}\) will acquiesce in its fault-tolerant priority \(p\):  
\[\text{acquiescence}_{ip}(t)= \begin{cases}1,\text{ If }p\text{ has been active for }\lambda_{ip}(t)\text{ at time}t\\ 0,\text{ Otherwise}\end{cases}  \tag{1}\]  
If a fault-tolerant priority \(p\) of the sensor \(S_{i}\) has been activated for more than \(\lambda_{ip}(t)\) at time \(t\), then acquiescence\({}_{ip}(t)\)=1. Otherwise, acquiescence\({}_{ip}(t)\) = 0. This function means that the sensor \(S_{i}\) will acquiesce in the fault-tolerant priority \(p\) until \(S_{i}\) has used the priority \(p\) for the time period of \(\lambda_{ip}(t)\). The current fault-tolerant priority tuner of the sensor \(S_{i}\) is re-calculated as follows:  
\[m_{ip}(0)=0 \tag{2}\]  
\[m_{ip}(t)=[m_{ip}(t-1)+\delta_{ip}(t)]\times\text{acquiescence}_{ip_{current }}(t) \tag{3}\]  
As shown in Figure 4, the current fault-tolerant priority of the sensor \(S_{i}\) is initially \(p_{current}\), and \(m_{ip}\) is set to 0. If \(p_{current}\) is acquiescent at time \(t\), then \(m_{ip}(t)\) = 0 (see e.g., State 0, State 3 and State 5 in Figure 4). Otherwise, \(m_{ip}\) will continue to change based on the adjustment factor \(\delta_{ip}(t)\) over time unless the priority tuners of some fault-tolerant priorities exceed activation threshold \(\theta\), when the control node will activate a new fault-tolerant priority for the sensor \(S_{i}\) (e.g., \(p_{2}\) is activated at State 2 in Figure 4) and all priority tuners of the sensor \(S_{i}\) will be set to 0 (see e.g., State 3 and State 5 in Figure 4). When multiple priorities' tuners exceed activation threshold \(\theta\) at the same time, the highest priority will be activated (e.g., \(p_{3}\) is activated at State 4 in Figure 4). Figure 4: Switching of fault-tolerant priority.
## 3 Results and Discussion
### Characterization
#### 3.1.4 FTIR Study
Adsorption of Cr(VI) onto PANI was determined by the increase in intensity of the peak at 1005.2 cm\({}^{-1}\) while in composites the same was observed at 1039.6 cm\({}^{-1}\) as reported elsewhere [57; 58]. Similar results were obtained after adsorption of Ni(II) on all adsorbent materials, however; shifting of % transmittance was less as compared to Cr(VI), indicating stronger interactions between Cr(VI) and adsorbent materials as compared to Ni(II) [59]. FTIR results correlated to the results obtained from EDX and UV-visible spectroscopy.
## 2 Internal Force Calculation of Lining
### Pressureless Water Conveyance
#### 3.1.1 Influence of Water Conveyance Pressure on the Maximum Internal Force of Lining  
In order to reveal the influence of water conveyance pressure on the maximum internal force of the lining, four working conditions are selected with tunnel inner radii of 2, 3, 4 and 5 m. The maximum internal force under the water conveyance pressure of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9 MPa were calculated, respectively. The positive and negative value of internal force only indicates the direction of the force. The bending moment and shear force are the maxima of absolute value and the axial force is the inverse of the minimum value (i.e., the maximum axial tension). The curve of the maximum internal force with water conveyance pressure under four lining sizes is shown in Figure 7.  
It can be seen from Figure 7 that the maximum internal force of the lining will increase with the increase of water conveyance pressure and inner radius. The larger the inner radius of the lining, the more significant the influence of water conveyance pressure on the maximum internal force. Under the same water conveyance pressure, the influence of changing the inner radius on the bending moment is greater than that on axial force and shear force. This shows that, when the hydraulic tunnel has high requirements for water-passing capacity, the internal force borne by the lining is large, so it is necessary to strengthen the design of structural strength.