esa-sceva/satcom-chunk-collection huggingface dataset:
# Design of a Planar Cable-Driven Parallel Robot for Non-Contact Tasks
## 3 Mechanical Design
### Guidance System  
The cable guidance system is designed to (i) guide each of the four cables on a parallelogram-like routing (Figure 10) to ensure the motion of the \(EE\) in a defined plane; (ii) geometrically define the cable exit points, to apply a standard kinematic model for robot control, (iii) integrate a load sensor for cable tension measurement.  
The cable, which leaves the drum groove from a fixed point in space, in a fixed direction (see Section 3.1), is then guided on a fixed pulley (1) attached to a tension measurement unit, which will be analyzed later on. After that, to obtain a parallelogram shape, the cable passes through four identical swivel pulleys (2,3,4,5) and then, through another fixed pulley (6) (also included in the tension measurement unit) before engaging the other groove on the drum. The proposed cable-loop arrangement realized with one cable avoids possible cable slackness during \(EE\) motion, which may happen if the parallelogram is made of two separate cables driven by the same winch. Two of the swivel pulleys (2,5) are fixed to the base and form the proximal guidance unit, while the other two (3,4) are attached to the platform and form the distal guidance unit. The distance \(a\) between the two pulleys composing each group is equal. This defines the first two sides of the parallelogram, which are invariant, being distances between points of rigid bodies. The other two sides \(b\) are formed by cable sections that are equal and parallel when the cable is taut by design.
# Treatment Selection for Early to Intermediate Hepatocellular Carcinoma
## 5 Application of Molecular Target Agents for the Treatment of Intermediate-Stage HCC  
The application of MTAs for the treatment of intermediate-stage HCC is different among guidelines. Although the efficacy of MTA for intermediate-stage HCC was demonstrated in many Phase 3 studies, including SHARP [23], REFLECT [24], and REACH-2 [25] studies, MTA is not recommended for the treatment of intermediate-stage HCC in BCLC guidelines. In many Asian guidelines, including Japanese, MTA was listed as an optional therapy [4; 5; 7; 11]. This discrepancy comes from the lack of enough  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Authors** & **Pt No.** & **Intervention** & **Results** \\ \hline [PERSON], et al. [16] & n = 59 & TACE + RFA to the nodules & Better PFS, OS than TACE \\  & & with poor lipidod retention & \\ [PERSON], et al. [14] & n = 211 & TACE + RFA to the nodules & Better PFS, OS than TACE \\ [PERSON], et al. [13] & n = 20 & DC beads + RFA & Effective and Safe \\ [PERSON], et al. [17] & n = 167 & RFA to all nodules & Better OS than TACE \\ [PERSON], et al. [18] & n = 92 & TACE + RFA & (especially AFP \(<\) 100 mg/mL) \\ [PERSON], et al. [15] & n = 627 & RFA & Better OS than TACE in Bi/B2 stages \\ [PERSON], et al. [20] & n = 404 & TACE + RFA & Better OS and PFS \\ (B1 stage) & & & \\ \hline TACE, transcatheter arterial embolization; RFA, radiofrequency ablation; DC beads, drug-eluting beads; PFS, progression-free survival; OS, overall survival. & & \\ \end{tabular}
\end{table}
Table 1: Radiofrequency ablation (RFA) for intermediate-stage hepatocellular carcinoma (HCC).  
Figure 3: Barcelona clinic liver cancer (BCLC) stages of RFA-treated patients.  
information comparing the efficacy of MTA and TACE for the treatment of intermediate-stage HCC. In addition, intermediate-stage HCC consists of a wide variety of HCC that is neither early nor advanced-stage HCC, which makes the uniform recommendation of the treatment difficult [25].  
Recently, [PERSON] et al. showed a better survival benefit of lenvatinib than TACE in patients with intermediate-stage HCC beyond the up-to-seven criteria [26]. The report was not a prospective randomized study, but the authors used propensity scores to compensate for biases between two groups and clearly demonstrated the efficacy of lenvatinib for these patients. The PFS values of lenvatinib and TACE-treated patients were 16.0 and 3.0 months, respectively, and OS values were 37.9 and 21.3 months, respectively. These results indicate that MTA could be a treatment of choice in more advanced intermediate-stage HCC.
# Continuous-Thrust Circular Orbit Phasing Optimization of Deep Space CubeSats
## 2 Simplified Thrust Model
Assuming that the thrust vector can be freely steered during the flight, and introducing the dimensionless control variable \(\tau\in[0,\,1]\) which models the thrust magnitude level (the case of \(\tau=0\) indicates a zero thrust, while \(\tau=1\) indicates a full throttle level), according to Equation (12), the propulsive acceleration vector is written as  
\[\mathbf{a}=\frac{\tau\,T_{\text{max}}}{m}\equiv\frac{\tau\,T_{\text{max}_{\oplus} }}{m}\left[\frac{d_{N_{1}}(r/r_{\oplus})^{4}+d_{N_{2}}(r/r_{\oplus})^{3}+d_{N_ {3}}(r/r_{\oplus})^{2}+d_{N_{4}}(r/r_{\oplus})+d_{N_{5}}}{(r/r_{\oplus})^{3}+ d_{D_{1}}(r/r_{\oplus})^{2}+d_{D_{2}}(r/r_{\oplus})+d_{D_{3}}}\right]\mathbf{\hat{a}} \tag{16}\]  
where \(\mathbf{\hat{a}}\) is the thrust unit vector, and \(m\) is the local value of the spacecraft mass. The derivative of \(m\) with respect to the time \(t\) can be written, as usual, using the expression of the thrust magnitude and the specific impulse as  
Figure 4: Comparison between the surrogate thrust model described by Equations (1) and (3) (black lines) and the simplified mathematical model given by Equations (12) and (14) (dash red lines). \[\frac{\mathrm{d}m}{\mathrm{d}t}=-\frac{\tau\,T_{\max_{\infty}}}{g_{0} \,l_{\mathrm{Sp}_{\oplus}}}\left[\frac{d_{N_{1}}(r/r_{\oplus})^{4}+d_{N_{2}}(r/ r_{\oplus})^{3}+d_{N_{3}}(r/r_{\oplus})^{2}+d_{N_{4}}(r/r_{\oplus})+d_{N_{5}}}{e_{N_{1}} (r/r_{\oplus})^{4}+e_{N_{2}}(r/r_{\oplus})^{3}+e_{N_{3}}(r/r_{\oplus})^{2}+e_{ N_{4}}(r/r_{\oplus})+e_{N_{5}}}\right]\times\\ \times\left[\frac{(r/r_{\oplus})^{3}+e_{D_{1}}(r/r_{\oplus})^{2}+ e_{D_{2}}(r/r_{\oplus})+e_{D_{3}}}{(r/r_{\oplus})^{3}+d_{D_{1}}(r/r_{\oplus})^{2}+d_{D _{2}}(r/r_{\oplus})+d_{D_{3}}}\right] \tag{17}\]  
where \(g_{0}=9.80665\,\mathrm{m}/\mathrm{s}^{2}\) is the standard gravity. Bearing in mind Equations (16) and (17), the dimensionless control terms are the throttle parameter \(\tau\) and the thrust unit vector \(\hat{\mathbf{a}}\). The expressions of \(\{\tau,\,\hat{\mathbf{a}}\}\) are obtained by solving the optimization problem described in the next section.
# Exact Relationship between Black Phosphorus Thickness and Behaviors of Field-Effect Transistors
## 4 Discussion
### Effect of the \(l\) on \(R\) and \(\mu\)  
The total resistance of the device decreases with the increase of the material thickness, but it shows a nonlinear change with the thickness. The relationship between resistance and thickness still meets the above semi empirical formula. The carrier mobility increases with the increase of the material thickness. This is mainly because the g\({}_{\rm m}\) (the peak transconductance extracted from the linear scale of transfer behaviors) increases with thickness. Although the relationship between mobility and thickness does not meet the above formula, when BP changes from 6 nm to 20 nm, its value changes much more than when BP changes from 20 nm to 50 nm. This is mainly because when the thickness of the material is less than 21.7 nm, the influence of the thickness of the material on the material band gap is significantly enhanced. Therefore, as the thickness of the BP material decreases, the band gap gradually increases, and the resistance increases significantly.  
After the device is etched by plasma etching technology, the above conclusions are verified, and the modulation effect of gate voltage on current is more obvious in the plasma etched FET device. In addition, experiments have shown that the plasma etching method often introduces different levels of structural damage and impurity elements, causing damage to the lattice structure of the sample materials, which in turn has an impact on the output characteristics of the device.
## 1 Introduction
The real hyperspectral brain tumor image dataset was collected, and the mechanism of non-uniform fringe noise was analyzed for the real hyperspectral pathological image dataset by analyzing the detection mode and instrument characteristics of the spatial dimensional push sweep hyperspectral imaging system. 2. New reference-based and scenario-based correction methods are proposed, respectively. On the one hand, a weighted least squares algorithm with embedded bilateral filtering (BLF-WLS) is proposed, which can preserve the details of pathological images and remove the noise caused by conversion imaging. On the other hand, the instrument fixed-mode noise components in the image data are separated by modeling and computing the black background images that were simultaneously captured. 3. Through the combination of scene-based and reference-based non-uniformity correction denoising methods, clean and clear hyperspectral brain tumor tissue images were obtained. Combining scene-based and reference-based denoising approaches can be taken into consideration for the non-uniformity noise removal of other spatial dimensions push sweep hyperspectral imaging systems due to its effective denoising effect.
## 3 Results
### Google Trends Relative Search Volumes for \"Elderly\" and \"Teledentistry\"
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multicolumn{2}{c}{**Worldwide Relative**} & \multicolumn{3}{c}{**36 Months before**} & \multicolumn{3}{c}{**36 Months after**} \\
**Search Volumes** & \multicolumn{3}{c}{the COVID-19 Outbreak**} & \multicolumn{3}{c}{**the COVID-19 Outbreak**} \\ \hline \hline  & **Mean** & **Median** & **SD 1**  & **SE 2**  & **Mean** & **Median** & **SD 1**  & **SE 2**  \\ \hline Teledentistry & 0.472 & 0.500 & 0.116 & 0.0194 & 0.500 & 0.500 & 0.000 & 0.0000 \\ Elderly & 2.972 & 3.000 & 0.167 & 0.0278 & 3.111 & 3.000 & 0.523 & 0.0871 \\ Oral needs and concerns & & & & & & & \\ Tooth loss & 1.000 & 1.000 & 0.000 & 0.0000 & 0.986 & 1.000 & 0.083 & 0.0139 \\ Periodontitis & 2.944 & 3.000 & 0.232 & 0.0387 & 3.444 & 3.000 & 0.558 & 0.0930 \\ Tooth extraction & 13.306 & 13.000 & 1.618 & 0.2697 & 16.222 & 17.000 & 2.085 & 0.3476 \\ Dentures & 14.361 & 14.000 & 1.246 & 0.2076 & 15.972 & 16.000 & 1.558 & 0.2597 \\ Caries & 7.083 & 7.000 & 0.649 & 0.1082 & 8.222 & 8.000 & 1.198 & 0.1996 \\ Stomatitis & 2.361 & 2.000 & 0.487 & 0.0812 & 2.417 & 2.000 & 0.500 & 0.0833 \\ Teledentistry applications & & & & & & & \\ Consult & 10.806 & 11.000 & 0.668 & 0.1114 & 11.611 & 12.000 & 0.964 & 0.1607 \\ Diagnosis & 40.361 & 40.500 & 3.893 & 0.6488 & 44.444 & 44.000 & 5.882 & 0.9803 \\ Monitoring & 3.694 & 4.000 & 0.467 & 0.0779 & 3.861 & 4.000 & 0.351 & 0.0585 \\ Screening & 3.000 & 3.000 & 0.239 & 0.0398 & 3.611 & 3.500 & 0.688 & 0.1146 \\ Assistance & 63.111 & 62.500 & 5.203 & 0.8672 & 75.000 & 73.500 & 7.018 & 1.1697 \\ Education & 35.111 & 35.000 & 3.328 & 0.5546 & 36.444 & 35.500 & 5.634 & 0.9390 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Worldwide relative search volumes on the Internet for “Teledentistry”, “Elderly”, oral needs and concerns, and teledentistry applications 36 months before and after the COVID-19 outbreak.
# Studies and Rejection of Intercrystal Crosstalk on FPGA in a High-Energy Photon-Counting System
## 3 Studies of Intercrystal Scatter
### Characters
#### 3.2.2 Position  
Figure 8 presents the deposition position distribution of events that make up intercrystal scatter interaction pairs. All incident events are assumed to be detected by crystal \(i\). The crosstalk events are distributed in a concentrated area with a small interval from the incident crystal. Statistics show that 89.93% of crosstalk events are deposited in crystals \(i+1\) or \(i-1\), and this scenario is denoted as \(\Delta\)Det = 1. Meanwhile, the percentages are 8.47%, 1.25%, and 0.35% for the cases in which \(\Delta\)Det equals two, three, and four, respectively. Thus, \(\Delta\)Det \(\leq\) 2 accounts for the majority of cases with a probability of 98.40%, while cases in which \(\Delta\)Det > 2 can be neglected, having only a small share of less than 2%.  
Figure 8: Deposition position relationship between crosstalk events and the corresponding incident events, in which the deposition crystals are denoted as \(i\) for all incident events.  
Figure 7: Energy relationship and distribution of two events (incident and the first crosstalk events) that make up an intercrystal scatter interaction pair. Color bar is used to show the distribution density. The dotted line identifies two events with equal energy.
# Traffic Monitoring System Based on Deep Learning and Seismometer Data
## 4 Results
### Classification Accuracy  
We tested the classification accuracy of the three networks using 20% of the dataset (1116 samples). We compared the results with those of a similarity method for seismic event detections called template matching [41]. We randomly selected 50 waveforms for each vehicle class from the training data to be used as templates. We also recorded 15 min of new data for this experiment. We took into consideration factors that might affect the data, including the time of recording, location of stations, and types of geophones. The networks were not retrained before this exercise, and the templates also were not changed.  
The resulting detection accuracies are listed in Table 3. DNN achieved the best accuracy, with 97.8% correct detections, followed by CNN with 96.6% and RNN with 85.3%. Template matching had much lower classification accuracy and took an order of magnitude longer to process the testing data.
###### Abstract  
This paper presents a high pulse energy, narrow linewidth, mid-infrared (MIR) laser at 6.45 \(\upmu\)m, based on a BaGa\({}_{4}\)Se\({}_{7}\) (BGSe) crystal optical parametric oscillator (OPO) pumped by 1.064 \(\upmu\)m laser. The maximum pulse energy at 6.45 \(\upmu\)m was up to 1.23 mJ, with a pulse width of 24.3 ns and repetition rate of 10 Hz, corresponding to an optical-optical conversion efficiency of 2.1%, from pump light 1.064 \(\upmu\)m to idler light 6.45 \(\upmu\)m. The idler light linewidth was about 6.8 nm. Meanwhile, we accurately calculated the OPO phase-matching condition at BGSe crystal pumped by 1.064 \(\upmu\)m laser, and a numerical simulation system was performed to analyze the input-output characteristics at 6.45 \(\upmu\)m, as well as the effect of crystal length on the conversion efficiency. Good agreement was found between measurement and simulation. To the best of our knowledge, this is the highest pulse energy at 6.45 \(\upmu\)m, with the narrowest linewidth for any all-solid-state MIR ns laser in BGSe-OPO pumped by simple 1.064 \(\upmu\)m oscillator. This simple and compact 6.45 \(\upmu\)m OPO system, with high pulse energy and narrow linewidth, can meet the requirements for tissue cutting and improve tissue ablation accuracy.  
optical parametric oscillator (OPO); BaGa\({}_{4}\)Se\({}_{7}\) crystal; 6.45 \(\upmu\)m mid-infrared (MIR) laser 4.0/.
## 1 Introduction
### Swarm intelligence metaheuristic and literature review  
Metaheuristic algorithms are stochastic approximate algorithms that do not assure generating the best solution, but they will result in a solution near the global optimum. These algorithms have two main phases, specifically diversification (also called exploration) and intensification (also called exploitation). Diversification refers to the global exploration of the search space. The diversification phase is followed by the process of intensification. By conducting exploitation, the algorithm searches around the current best solutions in the population. Due to the stochastic nature of the metaheuristics optimization process, one of the most challenging tasks is to find the proper balance between diversification and intensification.  
Metaheuristic algorithms are generally divided into two groups: evolutionary algorithms and swarm intelligence algorithms. Evolutionary algorithms (EA) are motivated by biological evolution, and they are further split into three sub-classes: evolutionary strategies [22], evolutionary programming (EP) [23], and genetic algorithms (GA) [24]. Swarm intelligence algorithms are population-based algorithms, which mimic the collective intelligence behavior of animal herds, a flock of birds, ant colonies, bacterial growth, and similar decentralized, self-organized systems in nature. The collective intelligence emerges from the cooperation between individuals locally and with their environment. Metaheuristic algorithm hybridization is achieved by the combination of the advantages of two or more metaheuristic algorithms or by incorporating additional operations in the existing metaheuristics, which yields a faster convergence rate, better accuracy, and more adequate balance between the exploration and exploitation process.  
Some of the notable swarm intelligence algorithms are particle swarm optimization (PSO) [25], artificial bee colony (ABC) [26; 27; 28], ant colony optimization (ACO) [29], bacterial foraging optimization (BFO) [30], the firefly algorithm (FA) [31], the whale optimization algorithm (WOA) [32; 33], the bat algorithm (BA) [34], cuckoo search (CS) [35; 36], elephant herding optimization (EHO) [37], Monarch butterfly optimization (MBO) [38], and the tree growth algorithm (TGA) [39]. There are many successful applications of swarm intelligence algorithms on different real-life problems that were performed by many authors such as [40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69].
## 2 Materials and Methods
### Antimicrobial Activity
#### 2.6.1 Disk Diffusion Method  
The antimicrobial assays were performed using the Kirby Bauer disk diffusion method according to the Clinical and Laboratory Standards Institute [27]. Sterile Petri dishes containing solid and sterile Mueller-Hinton Agar (MHA) were used. The samples were dissolved with sterile PBS and 1% Tween 80 and filtered through syringe filters (\(\O\) = 0.22 \(\upmu\)m). The sterile filter disk (\(\O\) = 6 mm) was saturated with 10 \(\upmu\)L of each sample at a concentration of 10 mg mL\({}^{-1}\) and placed on the MHA with the tested bacteria. The bacterial suspension (100 \(\upmu\)L) prepared from an overnight culture was adjusted to an inoculation of 10\({}^{8}\) CFU mL\({}^{-1}\). The plates were incubated at 37 \({}^{\circ}\)C for 18 h. Disks without samples were used as a negative control. Ampicillin (10 \(\upmu\)g/disk), neomycin (30 \(\upmu\)g/disk), oxytetracycline (30 \(\upmu\)g/disk), and erythromycin (15 \(\upmu\)g/disk) were used as positive controls for bacteria. Antimicrobial activity was evaluated by measuring the inhibition zone (mm) for the tested microorganisms and compared to the controls.  
6.2 Determination of the Minimum Inhibitory Concentration (MIC) and the Minimum Bactericidal Concentrations (MBC)  
Serial twofold dilution of each essential oil stock was made with Mueller Hinton Broth with 1% Tween 80, to yield final concentrations ranging from 2.5 to 0.156 mg mL\({}^{-1}\), and placed into tubes. Then, 500 \(\upmu\)L of the bacterial (\(5\times 10^{5}\) CFU mL\({}^{-1}\)) culture was added. The tubes with the MHB or bacterial culture were the negative and positive controls, respectively. The minimum bactericidal (MBC) concentrations were determined after broth macrodilution by subculturing a sample from a tube showing no microbial growth onto the surface of the MHA medium. The plates were incubated at 37 \({}^{\circ}\)C for 18 h. The MBC is defined as the lowest concentration of an antimicrobial agent needed to kill 99.9% of the final inoculum after 18 h of incubation [27].
## 4 Measurement Formation Process
### Maintenance of MLMS Measurement-Formation Path
Of course, in order to further improve the reliability and recover the lost packets timely, we can set nodes around the MLMS paths to buffer the packets they have eavesdropped on; when certain packets are lost, they can be recovered quickly and accurately through multicast inquiry messages to the neighbor nodes. What's more, a consultation method can also be used to further improve the reliability of packet transmission (for example, three-handshake negotiation). The disadvantages of these two methods are the large overhead of transmitting control messages, and we will evaluate it in Section 6.
## 5 Discussion  
To date, many researchers have made many attempts to generate descriptive texts from natural and medical images, but these methods have all used existing diagnostic report data as training labels, aiming to generate the same diagnostic text as the original report. However, the sentences in the original report were too complex, and the logic of the sentences was mostly affected by the subjective factors of clinicians. It is impossible for a computer to understand and reproduce the original report written by a human mind, so the diagnostic text generated by their model was not very effective.  
In terms of spinal medical images, most of the current work is based on the disease detection and classification of spinal medical image datasets, and there has been no related research on the generation of spinal disease diagnosis reports. Therefore, this paper conducted a study on the automatic generation of a scoliosis diagnosis report. Different from the previous description methods, we created a new set of hand-marked sentences according to the visual features of spinal images under the guidance of professional radiologists as the labels for model training, and marked up the original diagnosis report into simple and consistent sentences with the same structure, using these sentences as a training model. Therefore, in the validation of the test sets, the model in this paper could output short but critical feature descriptions of the diagnostic text. In the model, the convolutional attention mechanism CBAM we added was different from the channel attention mechanism in traditional methods or the global attention mechanism. This attention mechanism could focus on channel and spatial features. Therefore, features with better correlation in spinal images could be extracted, and the description sentences generated could pay more attention to the information about spinal curvature. In addition, the attention mechanism was also added in the text decoding stage. The attention mechanism allowed the decoder to focus on the image region, with a high correlation with the words of the current moment, and it could predict the words of the current moment according to the words of the previous moment, instead of directly focusing on the whole image. Finally, the region features related to the current moment were used to generate words. This method was also the reason why the sentences generated by this model had good effects both in accuracy and in the score of evaluation indicators.  
This method is not limited to models and datasets; it can also be applied to other medical image analysis tasks. However, there are limitations to this approach, as the preparation of short statement labels is cumbersome and a certain medical knowledge of scoliosis is required in the process of condensing traditional original diagnosis reports. Therefore, applying the simplified method of sentence labeling to the generation of other medical image diagnosis reports also requires a certain medical knowledge reserve or the guidance of professional doctors.
# Congestion Control and Traffic Differentiation for Heterogeneous 6 TiSCH Networks in IIoT
## 4 Multi-Queue Model and Priority-Based Transmission  
In this section, we introduce a priority-based multi-queue transmission model in order to support heterogeneous traffic in 6 TiSCH networks. Then, we derive a mathematical model to formulate the average waiting time in each queue.