esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
Therefore, the EMLWDF algorithm can satisfy the users with GBR by providing the required RBs and at the same time satisfy more users with NGBR compared to other algorithms by allocating RBs efficiently. The fairness index of the MLWDF algorithm is close to the EMLWDF algorithm due to the channel and QoS awareness. However, the PF algorithm allocates RBs to the user without considering the distance of the user from eNB and the probability of packet loss. Furthermore, PF is the only channel aware but QoS-unaware algorithm in this comparison that does not consider the QoS requirement of the user. Thus, PF cannot fully satisfy the user with strict delay threshold, which leads to high packet loss and low throughput. Therefore, considering all of these facts, PF has the lowest fairness in this comparison. The figure also shows that the fairness index decreases as the number of users increases due to the limitation of the available RBs in the cell. Figure 8: Average user throughput for HTTP. Figure 9: Fairness index for different algorithms. Spectral efficiency is calculated by the ratio of the total bits of all users successfully transferred and the total bandwidth of the channel for a specific time. Thus, the unit of spectral efficiency is bit/s/Hz. The spectral efficiency comparison in Figure 10 demonstrates that EMLWDF utilizes the spectrum more efficiently than PF and MLWDF. Ensuring the adequate distribution of the RBs by EMLWDF avoids the waste of spectrum resources and thus increases the efficiency. On the contrary, PF only considers current and previous data rates, whereas MLWDF uses delay, which leads to lower spectral efficiency. Overall, 33.31% and 3.53% improvement have been achieved by the proposed EMLWDF compared to MLWDF and PF algorithms, respectively. This paper implements 900 MHz as the operating frequency. Figure 11 shows a cell-edge throughput comparison by implementing the EMLWDF algorithm in 900 MHz, 1800 MHz and 2100 MHz frequency bands with the same bandwidth for VoIP data. The 900 MHz band achieves 5.23% and 4.0% higher cell-edge throughput than 1800 MHz and 2100 MHz bands, respectively. Important to note here is that both 1800 MHz and 2100 MHz frequency bands still perform better than the PF and MLWDF algorithms that are implemented in this paper. Figure 12 shows the effect of the user speed on the cell-edge user throughput for EMLWDF algorithm. It is clear that the static users have throughput than other users. The users with 5 kmph speed have 4.85% less cell-edge throughput and the users with 40 kmph speed have 42.36% less than the static users due to the higher packet loss, longer delay, and low SINR. Figure 11: Comparison of different frequencies with EMLWDF for VoIP. Figure 10: Spectral efficiency of different algorithms.
# SNA: Sensitivity-Aware Neural Architecture Adaptation for Uniform Quantization
## 4 Experimental Results
### Results

Table 3: Results obtained with ResNet-50-SANA and EfficientNet-B2-SANA using different initialization schemes on ImageNet. The target of the W3A8 configuration with a 1.155 multiplier for the SANA models is the W4A8 configuration with a 1 multiplier for original models. EfficientNet-B2-SANA showed sensitivity issues, and using W3A8 did not lead to significant improvements, while ResNet-50-SANA gained a substantial improvement over the original W4A8 methods. of 78.46%. We then applied various quantization strategies to reduce the model size to 24.4 MB. The results are shown in Table 4. It is worth noting that, for the same size, our approach achieved better accuracy than the mixed-precision model. Additionally, our method is fully automated, and it is much easier to deploy than a mixed-precision model, further emphasizing its superiority. When comparing the expanded ResNet-50 model with the original ResNet-50 model, after 4 bit quantization, the expanded model (Expanded-ResNet50) achieved the same size (24.4 MB) as the original model after 8 bit quantization. The accuracy of the expanded model after 4 bit quantization (77.772) was higher than that of the original model after 8 bit quantization (77.318). It should be noted that, if we further release the degree of freedom to allow choosing the multiplier r in a layerwise manner, then the final model can become even more quantization-friendly, resulting in a superior 77.984 final accuracy. Conversely, trying to achieve a larger compression ratio by shrinking the original baseline model will lead to inferior results. As in Table 4, the 8 bit quantized result (74.860) of the Shrunk-ResNet50 was much worse than the naive 4 bit quantization result (76.210) of the original ResNet-50 model, with the same model size of 12.2 MB. In contrast, applying SANA with a multiplier of 1.155 and a 3 bit quantization can achieve 76.630 accuracy, which is significantly better than the other methods, with the same 12.2 MB model size.
# Study on Filling Capacity of Optical Glass in a Novel Rapid Hot Embossing Process
## 5 Conclusions  
A novel rapid hot embossing approach is proposed for microstructuring of optical glass in this study. The detailed information about the precision loading module and the rapid heating module is introduced. The filling capacity of N-BK7 glass is quantified by the maximum height of the embossed microlens. Effects of process parameters on the filling capacity of glass in the novel rapid hot embossing process are evaluated. Some conclusions are drawn as follows:  
1. The tailor-made novel rapid hot embossing device allows a maximum temperature of 800 \({}^{\circ}\)C and a heating rate of 300 \({}^{\circ}\)C/min, with decent temperature control accuracy and uniform temperature distribution. Besides, it is demonstrated to have a satisfactory reproducibility in imprinting microlenses on the N-BK7 glass.
2. The glass microlens can be fabricated by just applying a small embossing force of 20 N at the appropriate temperature.
3. The filling capacity of glass is improved by increasing embossing force, embossing temperature and soaking time, but decreasing annealing rate.  
Figure 10: (**a**) Profiles, (**b**) maximum heights, and (**c**) curvature radii of microlenses under various annealing rate.  
Figure 9: (**a**) Profiles, (**b**) maximum heights, and (**c**) curvature radii of microlenses under various soaking time.  
(4) The filling capacity of N-BK7 glass is more sensitive to embossing force and embossing temperature, compared to soaking time and annealing rate.  
Conceptualization, F.G., G.Y. and J.L.; methodology, J.L., X.W. and G.Y.; software, J.L. and G.Y.; validation, J.L., X.W. and G.Y.; formal analysis, J.L., X.W. and G.Y.; investigation, J.L. and G.Y.; resources, F.G. and G.Y.; data curation, J.L. and X.W.; writing--original draft preparation, J.L. and G.Y.; writing--review and editing, J.L., F.G. and G.Y.; visualization, J.L. and G.Y.; supervision, F.G. and G.Y.; project administration, G.Y.; funding acquisition, G.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Shenzhen Science and Technology Innovation Commission (SGDX20190919094403772) and Shenzhen University (000002111214).  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors would like to appreciate the colleagues and advisor for their help to improve the paper.  
The authors declare no conflict of interest.
# Biosynthetic Pathways of Hormones in Plants
## 4 Salicylic Acid
However, the PAL pathway has been known for much longer in relation to its role in the ICS pathway [48; 51]. PAL is an upstream enzyme that leads to the production and accumulation of many other potentially defense-related compounds that are synthesized during the phenylpropanol pathway [52]. The conversion of phenylalanine into _trans_-cinnamic acid is catalyzed by PAL, which has been identified in numerous plant species. The activity of this enzyme is tightly regulated by various biotic and abiotic stress factors [53]. Depending on the order of the hydroxylation of the aromatic ring in _trans_-cinnamate, SA can also be synthesized from _o_-coumaric acid or benzoic acid through chain-shortening reactions. The specific pathway that leads to SA formation is determined based on whether hydroxylation occurs before or after the chain-shortening reactions [50]. In certain plants, such as sunflower (_Helianthus annuus_), potato (_Solanum tuberosum_), and pea (_Pisum sativum_), SA is derived from benzoic acid. This result is achieved via the chain-shortening of cinnnate through a \(\beta\)-oxidation process, leading to the synthesis of benzoic acid, which is subsequently converted into SA [54]. On the other hand, _Primula acaulis_ and _Gaultheria procumbens_ can synthesize SA from _o_-coumarate [55].
## 1 Introduction  
Several methods are available to describe and characterize the physics of musical instruments and their sound radiation. [PERSON] (1756-1827) first discovered that rigid and thin structures (e.g., plates), most of them symmetric and very clear, could depict special and particular mode shapes when they were bowed by a vibrating violin bow [1]. [PERSON] is therefore considered one of the pioneers (together with [PERSON]) of modern experimental modal analysis. Starting from [PERSON]'s studies, modal analysis became quite important for studies on musical instruments. [PERSON], in his important works about stringed musical instruments' acoustics, described experimental modal analysis as one of the most important physical analyses of violins [2, 3]. [PERSON], during her long activity as a scientist and violinmaker, considered modal analysis the most important and useful method for determining acoustic and sound quality in violin tops and backs [4, 5]. However, no information about modal patterns and their importance (and rank) in the definition of sound characteristics was provided, although [PERSON] stated that modes 2 and 5 were fundamental for the sound characterization of violin plates. These results were confirmed by several other authors, such as [PERSON] [6, 7]. Experimental modal analysis is based on the measurements of a frequency response function (FRF), which is obtained by exciting the sound board with a shaker or an impact hammer and capturing the vibration by means of accelerometers. Nevertheless, several authors such as [PERSON] [8], [PERSON] [9] and [PERSON] [10] have not discovered a robust correlation between FRFand modal analysis. Moreover, they have questioned whether there was a rank among all the modes, and what the relationship is between modal analysis (i.e., mode shapes) and sound radiation. When [PERSON] stated that modes 2 and 5 in violins were fundamental, she did not provide any scientific reason for not considering modes 1, 3 and 4; therefore, further research was required. Conversely, a different acoustic parameter that has recently been introduced called intensity of acoustic radiation (IAR) is well linked to the mechanical vibration of the sound source [11]. The IAR enables the sound characterization of musical instruments, including wind instruments [12].  
Even though several measurements could be utilized for characterizing musical instruments, they do not enable the ranking of the different modal shapes or link modal shapes with sound radiation (i.e., sound production of musical instruments).  
In this paper, the intensity of acoustic radiation (IAR) is experimentally evaluated for three Persian stringed musical instruments, namely the thar, si-thar and santoor. The IAR enables the determination of the most important frequencies responsible for sound propagation of the musical instruments. Furthermore, based on the results of the IAR, the modal patterns obtained from these frequencies are calculated. The Persian musical instruments were made in an original workshop in Tehran, Iran, then purchased and carried straight to Europe.
## 6 Results and Discussion
### Scenario 1: Area Coverage with RoI.1/2/3  
These simulations had been performed with precise parameters which provides better performance: \(\mathrm{d}_{0}=\mathrm{R}_{\mathrm{S}}\) the initial distance, \(\mathrm{\
u}=0.5\) the distance to add between nodes after every iteration, \(\mathrm{\mu}=0.05\) the transition distance for sensor nodes on the boundary, \(\mathrm{R}_{\mathrm{S}}=7\) the sensing range and the communication range \(\mathrm{R}_{\mathrm{T}}=14\).  
Initial deployment is illustrated in Figure 12. The Initial number of sensors needed to monitor the area is calculated based on the initial distance \(\mathrm{d}_{0}\), \(\mathrm{N}_{0}=54\). The model decides to add one sensor between RoI.2-RoI.3, and another one between RoI.1-RoI.2, so full connectivity can be achieved. After many iterations, the algorithm decides whether to save the proposed design or not based on the  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Sensors** & \(\mathbf{x_{N}}\) & \(\mathbf{x_{N-1}}\) & \(\mathbf{x_{3}}\) & \(\mathbf{x_{2}}\) & \(\mathbf{x_{1}}\) \\ \hline \(\mathrm{x_{1}}\) & \(\mathrm{d}_{1,N}\) & \(\mathrm{d}_{1,N-1}\) & \(\mathrm{d}_{1,3}\) & \(\mathrm{d}_{1,2}\) & \\ \(\mathrm{x_{2}}\) & \(\mathrm{d}_{2,N}\) & \(\mathrm{d}_{2,N-1}\) & \(\mathrm{d}_{2,3}\) & & \\ \(\mathrm{x_{N-1}}\) & \(\mathrm{d}_{N-1,N}\) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Euclidean distance between sensor nodes in one direction.  
Figure 11: Topology ensuring maximum interest, full coverage, and connectivity.  
value of the objective function. At the end, the best topology was found at iteration 6673, shown below in Figure 13.  
Figure 14a illustrates the network before ensuring connectivity. Sensor nodes within the same RoI are connected, and there is a bi-directional link in green between them as they are within each other's communication range, while nodes from a different RoI are isolated as shown by yellow links.  
Figure 14: Illustration of WSN connection graph: (**a**) Before solving connectivity; (**b**) after solving connectivity.  
Figure 12: Initial sensor deployment \"Scenario 1\".  
Figure 13: Optimal sensor deployment “Scenario 1”.  
Figure 14b is an illustration of the network after ensuring the connection between all sensor nodes and defining the sink node. Full connectivity is achieved, as demonstrated by all the green links passing through all sensor nodes. Figure 15 illustrates that the required degree of the joint interest is satisfied using only 26 nodes instead of 54 nodes used in the first deployment, and it shows that the best deployment was found at iteration It = 6673, where the topology provides a joint interest of 97.09% coverage ratio, with a minimum number of sensor nodes. During the first 400 iterations, the maximum joint interest was approximately satisfied and Rips values were increasing while the numbers of nodes were decreasing, meaning that the area was over-covered. The processing time of the application was around 60 s but only if the first and the optimal deployment topology are displayed, otherwise it exceeds 10 min.
# High-Resolution Digital-to-Time Converter Implemented in an FPGA Chip
## 2 Principle of the Proposed DTC
### DTC Based on a Programmable Delay Line  
This paper uses a Vernier delay line based on PDLs to realize the DTC. Figure 4 shows the block diagram of the DTC. Two PDL delay lines are built. Each delay line has 240 PDLs, and each PDL has 32 delay taps. A control module controls 40 PDLs, and 12 control modules are used in the two delay lines. CLKA is the reference clock of PDL A0-PDL A239, and CLKB is the reference clock of PDL B0-PDL B239. The frequency of CLKA is 202 MHz and that of CLKB is 200 MHz. Therefore, the resolution of the DTC based on the Vernier delay line realized by PDL is 1 ps, and the dynamic range is 7680 ps.  
In order to increase the dynamic range, a modified structure for the DTC is proposed, shown in Figure 5. In the modified design, PDL A0-PDL A236 and PDL B0-PDL B236 act as the first stage delay line (coarse delay line). PDL A237-PDL A239 and PDL B237-PDL B239 act as the second stage delay line (fine delay line). In the first stage delay line, the number of delay t  
Figure 4: A simplified block diagram of the proposed DTC.  
Figure 3: Schematic diagram of a programmable delay line. (**a**) Schematic diagram of a PDL (programmable delay line); (**b**) Schematic diagram of PDL delay lines.  
The number of working delay taps of PDL B is set according to Equation (6). As for the second stage, the number of delay taps of PDL A and PDL B are the same, which is represented by CNT\({}_{B}\). For a certain time interval \(T_{x}\), CNT\({}_{A}\), and CNT\({}_{B}\) can be calculated from the equations below. In the modified design, the frequency of CLKA and CLKB are still 202 MHz and 200 MHz. The effective range of the DTC is enlarged to 590 ns.  
\[\text{INT}_{x}=\text{CNT}_{B}-\text{CNT}_{A}=\left\lfloor\frac{T_{x}}{\tau_{B }}\right\rfloor \tag{6}\]  
\[\left\{\begin{array}{l}\text{CNT}_{B}\times\tau_{B}-\text{CNT}_{A}\times \tau_{A}=T_{x}\\ \text{CNT}_{B}-\text{CNT}_{A}=\left\lfloor\frac{T_{x}}{\tau_{B}}\right\rfloor \end{array}\right. \tag{7}\]  
\[\left\{\begin{array}{l}\text{CNT}_{A}=\frac{T_{x}-\tau_{B}\times\left\lfloor \frac{T_{x}}{\tau_{B}}\right\rfloor}{\tau_{B}-\tau_{A}}\\ \text{CNT}_{B}=\frac{T_{x}-\tau_{A}\left\lfloor\frac{T_{x}}{\tau_{B}}\right \rfloor}{\tau_{B}-\tau_{A}}\end{array}\right.. \tag{8}\]  
DTCs available with a large dynamic range are most realized by coarse and fine methods. The coarse method is commonly realized by counting the periods of a clock signal [3; 9; 10], which is very simple in implementation. However, the counting circuit may introduce additional errors into the circuit and decrease the conversion accuracy, especially the error caused by the trigger of the counter. This paper uses a coarse and fine delay line to increase the dynamic range. The coarse delay line and the fine delay line are the same, except that, in the coarse delay line, the number of working delay taps of PDL A0-PDL A236 is set to 0. By doing this, we increase the dynamic range without decreasing the conversion accuracy.
## 4 RFF Extraction and Identification Methods
### Random Forest and Sequential Detection-Based RFF Identification Method
The flow of the radio frequency fingerprint identification method using the thought of sequential detection is as follows:  
1. First, the RFF features of devices and their statistical parameter sets are extracted to form the final feature vectors \(\mathbf{X}\), which are entered into the fingerprint database. 2. Then, in the process of the signal collection and identification, the same length of signal is cut out from each frame newly collected, and its features are calculated in the same way to obtain the feature vector \(\mathbf{Y}\). 3. Next, the feature vector \(\mathbf{Y}\) is compared with the feature vectors \(\mathbf{X}\) in the fingerprint database to calculate the similarity \(\mathbf{S}\). The similarity can be measured by correlation coefficient, Euclidean distance, Mahalanobis distance, etc. 4. The feature vector of newly acquired signal frame whose similarity exceeds the threshold will be stored in the buffer area, indicating that this frame of received signal is subordinate to the devices in the database, and the buffered data will be used for the judgment of subsequent new frames. On the other hand, if the similarity does not reach the threshold, it means that this frame is exceptional data, which may originate from a non-registered device, and additional buffer area needs to be opened up to store it. 5. The newly received frame data from the same device for the second time will not only be compared with the previously entered fingerprint database, but also with the data in the buffer area. With the increase of data in the buffer area, the judgment accuracy will correspondingly be improved. Furthermore, when the buffer area data reaches a certain amount, the stable feature vectors can be updated to the fingerprint database, so as to dynamically adjust the fingerprint feature vectors of the devices in the database. Through the sequential detection method, the system can continuously track relevant RFF features, and observe and learn their long-term change rule. During the process of identification, the feature of the current signal is compared with the real-time updatedfingerprint database and the buffer area data at the same time for better recognition. In the meantime, continuous observation can avoid misjudgment caused by accidental instantaneous fluctuation of RFFs. When there is anomalous difference in the occasional one frame of signal caused by external factors, whose similarity to the feature vectors in the database is lower than the threshold, it will be stored in the new buffer area separately. Afterwards, when the subsequent feature values return to the normal range, they will still be judged to the original device, which will not affect the final judgment result. Therefore, the radio frequency fingerprint identification method incorporating sequential detection can further improve the recognition rate of RFFs in the changeable mobility environment.
## 1 Introduction
Bistable phenomena and lock-up phenomena occur when the rotor passes a critical speed [12]; (2) using a metal rubber damper to reduce vibration, but this has almost no damping effect at noncritical speeds [13]; (3) using friction dampers to create frictional energy between metals, but their disadvantages are weak supporting capacity and poor temperature stability, and the material cannot be restored to its original state after yielding [14]. These methods described above also have great limitations. In practical industrial situations, due to space constraints and limitations of working conditions, passive control is still required as the main vibration control method. However, passive control has problems such as nonlinearity, installation space, and small vibration reduction range. Therefore, in view of these problems, this paper designs a novel integral squeeze film bearing damper that has a damping effect on a wide frequency range. Moreover, it is segmented, which eliminates the problem of oil film nonlinearity. And it has a simple structure which greatly saves installation space. The novel integral squeeze film bearing damper (ISFBD) is less common in the vibration control of an unbalanced single-side cantilevered rotor system. In this study, vibration control research of this novel ISFBD shows that it provides good theoretical support and a feasible vibration control scheme for the systems in industry. In this paper, the vibration damping characteristics of the novel integral squeeze film bearing damper are analyzed. The influence of installation position and quantity of the novel ISFBDs on the stability, energy distribution, and vibration control of the unbalanced single-side cantilevered rotor system were numerically calculated. At the same time, a vibration control platform was built to verify the vibration control effect. The results show that different installation positions and quantities have different effects on stability, energy distribution, and vibration control of the system. When two novel ISFBDs are installed at the same time, the vibration control effect is best.