esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results: Medical History-Taking Challenges
### Observation 1: More than 90% of Physicians Suffer from High Workload  
To answer **RQ1**, respondents were asked to rate their cognitive workload experience using a Likert scale with the following options: (1) very low; (2) low; (3) moderate; (4) high; and (5) very high. It was observed that **92.31%** of physicians marked (3), (4), and (5). Sixty-six (66.35%) selected (4) and (5), which means they felt high workload every time or almost every time, while 25.96% selected (3), which means they experienced high workload occasionally. The average workload rating derived from this scale was around 3.79 out of 5, indicating a moderate workload on average. This finding is significant for understanding an indication of the actual stress and pressure that physicians face in their professional roles.  
Figure 1 illustrates the relationship between workload and ultimate working hours. It shows that physicians working more than 13 h a day experience extreme workload, with 82% of them feeling \"very high\" workload. For those working 10-13 h, 54% feel \"high\" workload, and 23% experience \"very high\" workload.  
Inquiring about physicians' work hours revealed a common trend: most work beyond their official duties, often engaging in other clinics or institutions. Around 54.81% work primarily in medical college hospitals, while 19.30% also practice in private clinics. On average, they work about 8.89 hours officially and 9.53 hours in total, with notable variations  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Characteristics** & **Frequency** & **Percentage** \\ \hline _Years of experience:_ & & \\
2–4 years & 14 & 13.46 \\
5–10 years & 14 & 13.46 \\
11–15 years & 16 & 15.38 \\
16–20 years & 13 & 12.50 \\
20 years+ & 47 & 45.19 \\ \hline _Working organizations:_ & & \\ Medical college hospital & 58 & 55.77 \\ Private hospital & 25 & 24.04 \\ Private clinic & 21 & 20.19 \\ NGO & 19 & 18.27 \\ Upazila health complex & 12 & 12.50 \\ District hospital & 7 & 11.54 \\ Online doctor consultancy & 5 & 6.73 \\ Other & 13 & 4.81 \\ \hline _Working locations:_ & & \\ Urban area & 71 & 68.27 \\ Sub-urban area & 31 & 29.81 \\ Rural area & 25 & 24.04 \\ \hline \hline \end{tabular}
\end{table}
Table 1: _Cont._  
Figure 1: The relationship between workload and total working hours. Physicians assessed their workload using five categories ranging from “very low” to “very high”. When physicians work longer hours than usual, it leads to a “high” or “very high” workload.  
reflected in the standard deviations of 3.11 and 3.02, respectively. This extended workload may strain their services, potentially impacting their performance and patient care quality.
# MAC Layer Protocols for Internet of Things: A Survey
## 2 Short Range MAC Layer Protocols
### Weightless
Unlike W and N, the Weightless-P standard does not require a Temperature Compensated Crystal Oscillator (TCXO), which makes the system cheaper and less vulnerable to loss of synchronism due to the ambient temperature variation. This characteristic is only possible because it uses Gaussian Minimum Shift Keying (GMSK) modulation and an offset-QPSK modulation. Weightless-P technology capacity was measured in a comparative way with the capacity of several multiple access technologies. The transmission power is set up serving a defined population of devices. The maximum flow for each multiple access mechanism allows 1404 bps for UNB, 93 bps for spread spectrum, and 4923 for NB (Narrow Band) [68].
# Implant Model Generation Method for Mandibular Defect Based on Improved 3D Unet
###### Abstract  
The accurate reconstruction of a defective part of the mandible is a time-consuming task in maxillofacial surgery. In order to design accurate 3D implants quickly, a method for generating a mandibular defect implant model based on deep learning was proposed. First, an algorithm for generating a defective mandible 3D model randomly from a complete mandible 3D model was proposed due to the insufficiency of 3D models. Then a mandible 3D model dataset that consists of defective mandible 3D models and a complete mandible 3D model was constructed. An improved 3D Unet network that combines residual structure and dilated convolution was designed to generate a repaired mandibular model automatically. Finally, a mandibular defect implant model was generated using the reconstruction-subtraction strategy and was validated on the constructed dataset. Compared with the other three networks (3D Unet, 3D RUnet, and 3D DUnet), the proposed method obtained the best results. The Dice, IoU, PPV, and Recall for mandible repair reached 0.9873, 0.9750, 0.9850, and 0.9897, respectively, while those for implants reached 0.8018, 0.6731, 0.7782, and 0.8330. Statistical analysis was carried out on the experimental results. Compared with other methods, the P value of the method proposed in this paper was less than 0.05 for most indicators, which is a significant improvement.  
implant design; mandible; synthetic data generation; 3D shape completion; 3D Unet Article
## 1 Introduction
Although there are abundant studies on rock breakage using TBM cutters and microwave-induced rock fracturing, research that combines the two is poorly researched, justifying the study of the influences of microwave irradiation on the rock-breaking efficiency of TBM cutters. The researchers selected a high-strength rock, Chifeng basalt, to conduct microwave irradiation tests and rock-breaking tests using a reduced-scale TBM cutter. Influences of microwave irradiation on the rock-breaking efficiency of the TBM cutter were evaluated by analyzing changes in the wear loss of the reduced-scale TBM cutter, rock removal, stress characteristics, energy consumption during rock breakage, and specific energy.
## 2 Materials and Methods
### Optimizing HE Classification Model
The segmentation masks, along with the baseline and follow-up CTs, were used as input for a classification CNN to predict HE. The classifier outputs probability scores for each subject. Then, from the threshold array, sensitivity array, specificity array, and f1 score array, one can choose the optimal threshold; for example, a threshold based on the maximum F1 score [33]. After that, we can create the confusion matrix elements at a given threshold. Using ROC analysis of the final prediction probabilities [34], we established the 100%, 95%, and 90% sensitivity and specificity thresholds in the internal test cohort and evaluated them in the external validation cohort.
# What is 5G? Emerging 5G Mobile Services and Network Requirements
## 4 5G Mobile Services
### Intelligent 5G Services
#### Crowded Area Services  
Crowded areas such as stadiums or concerts can be a source of massive amounts of traffic as shown in Figure 7. In these scenarios, many users are present, and they each get a different experience of service for similar and different content. Furthermore, many users upload and download UHD videos through social networks, and this eventually increases congestion. To provide wireless services efficiently in crowded areas, ultra dense networks cannot be avoided. In this scenario, placing video data at the network edge of base stations along with mobile edge computing reduces the load of the 5G core network. User location identification helps to provide location-based services in large shopping malls. The current 4G networks provide crowded area services by using many base stations and the available backbone bandwidth. Hence, 5G can provide these services effectively without any interruption by adopting the small-cell concept and mobile edge computing. However, all these services come at a certain cost; therefore, there is a trade-off between quality of service and cost. UHD and 3D multimedia contents are replacing the current low-volume contents, and the 5G network entails supporting a higher transmission rate. The ever-increasing multimedia traffic cannot be processed at the central server. Consequently, technologies such as local caching servers are essential to provide data from local servers in the 5G network.  
As technical challenges for intelligent 5G services including user-centric computing and crowded area services, energy-efficient user association and power allocation, energy harvesting base stations and fronthaul technologies are considered [19; 20]. To support intelligent 5G services, especially crowded area services, dense small cell networks cannot be avoided. In some cases, the small cell base station (BS) can be a moving BS, i.e., mobile BS, and then, energy efficiency can be a more significant issue. To achieve high energy efficiency, optimization of user association and power allocation, as well as an energy harvesting feature are needed. The optimal partitioning and design of fronthaul can be an issue in terms of bandwidth and latency of fronthaul.  
Figure 6: User-centric computing services.
## 3 Results and Discussion
### Thermogravimetric Differential Thermogravimetry Analysis  
Figure 7 shows the thermogravimetric differential thermogravimetry (TG-DTG) analysis curves of the EGC0 and EGC7-12 groups on day 28. At 40-800 \({}^{\circ}\)C, the sample exhibited significant mass loss, mainly caused by the loss of chemically and physically bound water and the decomposition of AFt, C-S-H gel, Ca(OH)\({}_{2}\), CaCO\({}_{3}\), and other products.  
Figure 6: XRD pattern of multicomponent solid waste cementitious material: (a) 3 d; (b) 28 d.  
As shown in Figure 7, three weight loss peaks mainly occurred in the whole test stage. The peak at 50-200 \({}^{\circ}\)C corresponds to the evaporation of physically bound water and the decomposition of AFt and C-S-H/C-(A)S-H gel [33], and the peak near 350 \({}^{\circ}\)C to 500 \({}^{\circ}\)C is related to Ca(OH)\({}_{2}\) decomposition [34]. The peak near 600-700 \({}^{\circ}\)C is related to CaCO\({}_{3}\) decomposition [35]. The weight loss of the sample at 50-200 \({}^{\circ}\)C is positively correlated with the increase in the EMR content, indicating that the increase in the EMR content and the decrease in the CS content were beneficial for the generation of hydration products, particularly AFt. In addition, all the groups featured Ca(OH)\({}_{2}\) decomposition peaks with different weight loss values at 350-500 \({}^{\circ}\)C. The EGC7 group, with the highest CS content, displayed the highest Ca(OH)\({}_{2}\) weight loss peak, attributable to the presence of excessive CS and consistent with the XRD results.  
Table 4 presents the mass loss rates of the samples in each group. The EGC7 group exhibited a slightly lower mass loss rate than the EGC0 group. This is attributable to the single-doping of CS, which not only reduced the GBFS content, thereby diminishing the number of active components, but also resulted in a deficiency of SO\({}_{4}\)\({}^{2-}\), leading to a reduction in AFt generation. The EGC8-12 group demonstrated a higher mass loss rate than the EGC0 group, with the EGC12 group doped with EMR exhibiting the highest mass loss rate. This observation is attributable to the generation of more AFt in the EGC12 group, while the lack of CS incorporation correspondingly resulted in fewer dissolved GBFS groups and lower C-S-H gel generation. Therefore, the co-incorporation of CS and EMR more effectively stimulated the activity of GBFS, which also proves that the mechanical properties of the EGC11 group were better than those of the EGC12 group.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Samples**} & \multicolumn{3}{c}{**Mass Loss Ratio (\%)**} \\ \cline{2-3}  & **50–200 \({}^{\circ}\)C** & **350–500 \({}^{\circ}\)C** \\ \hline EGC0 & 7.89 & 3.05 \\ EGC7 & 7.73 & 5.26 \\ EGC8 & 8.37 & 5.21 \\ EGC9 & 8.42 & 4.83 \\ EGC10 & 8.47 & 3.84 \\ EGC11 & 8.78 & 3.40 \\ EGC12 & 9.27 & 2.94 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Mass loss rate of samples at 50–500 \({}^{\circ}\)C.  
Figure 7: TG-DTG curve of multicomponent solid waste cementitious material.
## 3 Results  
### Ultrasound Measurements  
In general, none of the ultrasound measurements yielded a significant difference between modalities, as they all had similar effects. None of the modalities had a positive or negative significant effect on the cross-sectional area, echo intensity, pennation angle, fascicle length, or muscle thickness. The only significant result was that the male participants, overall, had larger muscles than the female participants, thus larger pennation angles and fascicle length (Table 1).  
For the cross-sectional area, there was no interaction effect (F = 0.97, \(p\) = 0.34, \(\uppi^{2}\) = 0.08), and there was no modality effect (F = 0.59, \(p\) = 0.45, \(\uppi^{2}\) = 0.16) or time difference (pre vs. post) (F = 1.84, \(p\) = 0.68, \(\uppi^{2}\) = 0.09), but there was an effect for sex (cP = 0.009, \(\uppi^{2}\) = 0.51), with a corrected \(p\) value of 0.009, with males having a higher cross-sectional area than females. The reliability results for the cross-sectional area are as follows: F = 0.95, \(p\) = 0.35, ICC3.1 = 0.99, SEM = 0.40 cm\({}^{2}\), MD = 1.1 cm\({}^{2}\). For echo intensity, there was no interaction effect (F = 01.21, \(p\) = 0.33, \(\uppi^{2}\) = 0.12), and there was no modality effect (F = 1.77, \(p\) = 0.33, \(\uppi^{2}\) = 0.12), time (pre vs. post) (F = 1.61, \(p\) = 0.20, \(\uppi^{2}\) = 0.16), or sex difference (\(p\) = 0.47, \(\uppi^{2}\) = 0.03). The reliability results for echo intensity are as follows: F = 0.19, \(p\) = 0.61, ICC3.1 = 0.98, SEM = 1.52 a.u., MD = 4.23 a.u. For the pennation angle, there was no interaction effect (F = 1.42, \(p\) = 0.24, \(\uppi^{2}\) = 0.05), and there was no modality effect (F = 1.71, \(p\) = 0.19, \(\uppi^{2}\) = 0.09) or time difference (pre vs. post) (F = 0.62, \(p\) = 0.65, \(\uppi^{2}\) = 0.02), but there was an effect for sex (cP = 0.008, \(\uppi^{2}\) = 0.22), with males having a larger pennation angle than females. The reliability results for the pennation angle are as follows: F = 0.01, \(p\) = 0.98, ICC3.1 = 0.97, SEM = 0.57\({}^{\circ}\), MD = 1.58\({}^{\circ}\). For the fascicle length, there was no interaction effect (F = 1.81, \(p\) = 0.19, \(\uppi^{2}\) = 0.03), and there was no effect for modality (F = 2.98, \(p\) = 0.09, \(\uppi^{2}\) = 0.11), time (pre vs. post) (F = 0.12, \(p\) = 0.46, \(\uppi^{2}\) = 0.01), or sex (cP = 0.09, \(\uppi^{2}\) = 0.31), with males having a longer fascicle length than females. The reliability results for fascicle length are as follows: F = 4.01, \(p\) = 0.09, ICC3.1 = 0.88, SEM = 0.35 cm, MD = 0.95 cm. For muscle thickness, there was no interaction effect (F = 1.71, \(p\) = 0.19, \(\uppi^{2}\) = 0.07), and there was no effect for modality (F = 1.41, \(p\) = 0.24, \(\uppi^{2}\) = 0.13), time (pre vs. post) (F = 1.00, \(p\) = 0.23, \(\uppi^{2}\) = 0.02), or sex (cP = 0.25, \(\uppi^{2}\) = 0.20). The reliability results for muscle thickness are as follows: F = 0.11, \(p\) = 0.75, ICC3.1 = 0.98, SEM = 0.04 cm, MD = 0.12 cm.
## 2 Related Work
### Security Standard  
A thorough examination of numerous articles on comparable systems reveals a noticeable absence of discussions or evaluations of ACN security according to standardization. While the literature offers a diverse range of approaches, the importance of standardization cannot be overlooked during system analysis. The ISO 26262 was one of the first standardization protocols within the automotive context. The document contains guidelines regarding the functional security of a vehicle intended for component malfunctions, which can cause damage to things or people [16]. Despite the fact that this protocol provides a relevant framework for assessing the reliability of components within an automotive system, the main focus does not take into account multiple external factors, which can lead to failure [17]. A more recent protocol is defined in ISO PAS 21448 [18], which is currently used for evaluating the safety of intended functionality (SOTIF), and this is usually combined with the previously described ISO 26262. A particularly relevant combination of these two protocols can be found within the context of automated [19, 20] and autonomous [21, 22] driving. This combination can give a complete overview and assess the complete security of both components and functionalities related to such components. As reported in Table 1, there are slight differences between ISO PAS 21448 and ISO 26262,which can be considered as complementary to each other. Even though such synergistic protocols can assess the security of the entire system, these protocols do not consider the external environment.  
As is widely known, the environment plays a relevant role in attack modeling, and the entire cyber-physical system must be considered for a reliable threat assessment. The ISO/SAE 21434 was released with the goal of establishing standards for designing a secure system within the automotive context able to standardize the minimal security and privacy criteria [6]. A recent study [23] applied the ISO/SAE 21434 to a generic E/E architecture. This work attempted to mitigate the gap in the literature by creating a comparative image of the E/E architectures on a generalized level, highlighting the importance of ECUs in all possible automotive systems.  
According to the analysis conducted in [23], the authors of the current paper want to assess security in a more detailed system, highlighting the potential of this protocol even for smaller systems. Given the sensitive nature of the data and the potential impact on individuals' safety and privacy, ensuring the cybersecurity of ACN systems is paramount. ACN systems collect and send data such as the location of the crash, driver information, and potentially health details. These data must be protected from unauthorized access, interception, or disclosure to maintain individuals' privacy.
## 5 Simulation Studies and Laboratory Testing--The Method
Initially, using SOL 103 Response Dynamics, the vibration modes of the beam were examined. Based on the obtained data, the considered vibration modes were limited to 1, 2, 4, and 6 modes, accounting for over 87% of the vibrating mass along the excitation axis. SOL 112 Modal Frequency Response was employed, simulating the range from 5 to 13 Hz with a 0.1 Hz step. Vibrations were imposed along the Y-axis of the simulation, while the remaining degrees of freedom were constrained using nodes defined in locations corresponding to the beam's attachment with the vice. Subsequently, the relative strain values along the Z-axis for eight nodes located on the edges of the surface corresponding to the active area of the piezoelectric transducer were recorded. The arithmetic mean for each node was calculated and Equation (14) was applied. The simulation view with the imposed excitation and  
Figure 3: The measurement setup with a movable base. constraints is depicted in Figure 4. All dimensions are presented in Figure 2. The position of the transducer relative to the beam mounting is 25 mm.
# Design of a 3-Bit Circularly Polarized Reconfigurable Reflectarray
## 4 Conclusions  
In this study, 3-bit circularly polarized reconfigurable reflectarray was designed and analyzed. The phase compensation method used in this study is the rotating unit structure loaded with the phase delay line. The circularly polarized reconfigurable reflectarray consists of 64 cells in an \(8\times 8\) configuration, with eight PIN diodes loaded into each cell. To independently control each cell, a corresponding DC control circuit was designed and tested with the array. One sample of the proposed circularly polarized reconfigurable reflectarray was fabricated and tested. The simulation results agree well with the measurement results. In the bandwidth range of 3.43-3.71 GHz, the circularly polarized reconfigurable reflectarray achieved a gain of 16 dB, an aperture efficiency of 27%, an axial ratio of \(\leq\)3 dB, an  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**References** & [39] & [40] & [25] & [41] & **This Work** \\ \hline Reconfigurable & & & & & \\ technology & & & & & \\ \hline Number of & & & & & \\ phase shifts & continuous & 1-bit & 1-bit & / & 3-bit \\ \hline Polarization & linear & Circular & circular & circular & circular \\ \hline Number of & & & & & \\ diodes & & & & & \\ \hline Loss of unit & & & & & \\ \hline Angular & & & & & \\ stability & & & & & \\ \hline Aperture & & & & & \\ efficiency & & & & & \\ \hline Scanning & & & & & \\ range & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: The comparison of the proposed reconfigurable reflectarray with other works.  
Figure 16: Radiation pattern of double beam: (**a**) xoz plane and (**b**) yoz plane.  
operating bandwidth of 8%, and a beam scanning range of \(\pm 60^{\circ}\). The circularly polarized reconfigurable reflectarray can also achieve a good dual-beam radiation performance after testing. The 3-bit circularly polarized reconfigurable reflectarray proposed in this paper has the advantages of low loss, high aperture efficiency, a wide beam scanning range, and excellent stability in wide-angle oblique incidence, which can be used for low-cost phased array, satellite communications, and deep space exploration.  
Conceptualization, Z.C., X.L. and X.Y. ([PERSON]); methodology, Z.C. and X.Y. ([PERSON]); validation, Z.C. and C.H.; investigation, X.Y. ([PERSON]) and Y.Z.; writing--original draft preparation, Z.C.; writing--review and editing, Z.C. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the Key Research and Development Program of Zhejiang Province, under Grant No. 2022C01093; the National Natural Science Foundation of China, under Grant No. 62271122; and in part by the Scientific Research Foundation for Yangtze Delta Region Institute of University of Electronic Science and Technology of China, Huzhou, under Grant Nos. U03220080, P0121003, and U05220004.  
The data that support the findings of this study are available within this article.  
The authors declare no conflicts of interest.
## 4 Proposed Protocol
### Training and Submission  
During the training phase shown in Figure 5, the trainers perform training on the initial models on their devices. When the time limit of the training process is reached, the trainers claim their accuracies and aggregate their model updates for the current epoch. The process ends after each trainer submits the IPFS hash of their update and the model integrity hash to the smart contract for verification purposes. Further details are listed as follows.  
1. The trainer performs model training on \(M_{0}\) to generate \(\beta\) and \(\delta\) (an accuracy claim based on the result). Honest trainers make truthful claims, whereas malicious actors may fabricate the accuracy of results. The trainer then creates \(H_{\beta}\), which is the hash of \(\beta\) used to verify the integrity of the payload's content by the voter.
2. The trainer sends \(\beta\) to IPFS.
3. IPFS stores \(\beta\).
4. IPFS generates a unique cryptographic hash for the trainer's model update (\(\beta_{ipfs}\)) and returns it to the trainer.
5. The trainer sends \(H_{\beta}\) and \(\beta_{ipfs}\) to the \(SC\).
6. The \(SC\) stores \(H_{\beta}\) and \(\beta_{ipfs}\).
7. The \(SC\) relays a successful transaction event to the trainer.