esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Prediction of Storage Period and Tomato Quality During Storage by Regression Analysis
Moreover, the skewness, GLN, mean, RP and a* values of the tomato peel have been shown to be effective indicators of the brick values of the tomato flesh (mean R\({}^{2}\) > 0.969 and test R\({}^{2}\) > 0.900) (Figure 9d), whereas the skewness, kurtosis, L* and b*, have  
Figure 7: Scatter diagram, principal component, and truth tables of the discrimination among tomato samples at days 3, 7, 10, 14, 17, and 24, employing the physicochemical parameters of tomato flesh. been demonstrated to be significant indicators of firmness values (mean R\({}^{2}\) > 0.963 and test R\({}^{2}\) > 0.854) (Figure 9e). Finally, the kurtosis, standard deviation, mean, correlation, and RP values of the tomato peel have been shown to be effective indicators of the moisture content of the tomato flesh (mean R\({}^{2}\) > 0.965 and test R\({}^{2}\) > 0.928) (Figure 9f). The results collected illustrate the effectiveness of ML applied to image texture data in revealing associations with fruit and vegetable quality attributes. These quality parameters include physicochemical attributes, antioxidant and antiradical activities, and phytochemicalal content, among others. The findings suggest that these algorithms can serve as a tool for the prediction and assessment of vegetable and fruit quality and shelf life. However, a limitation of the present study is its focus on a single tomato cultivar from one geographic region. Future studies should explore different varieties and production systems to ensure broader applicability of the proposed approach. Figure 8: Prediction of tomato storage days from textural features of tomato peel. Figure 9: _Cont._
## 4 Analysis and Results
### Communities Identified in the IOTA and IoTeX Networks  
We obtain the existing communities in these networks using _Community API_[66], a Python module that implements the Louvain algorithm [68]. We identify a number of communities, as Table 7 shows. The presence of a community of nodes in a visibility graph is inherent to its creation. Community participant nodes tend to cluster together with a small value of the average shortest path along the timeline [54].  
Figure 7 provides both volatility information as subplots in Figure 1 plus community information along IOTA and IoTeX timelines.
## 2 Related Works
In [24], GPS spoofing attacks confined by a sequential probability ratio detector were explored. Nevertheless, there was no investigation into guiding the UAV to an arbitrary hostile location. In our cyber-physical safety framework, we elaborate on GPS jamming and spoofing attacks on the civilian UAM attitude control system in such a way that the UAM service provider can predict the risk of jamming and spoofing attacks as wellas find the root causes of such attacks. A detailed system model and problem description are given in the following section.
## 4 Methodology
### Greedy: A Greedy Algorithm for Communication Reduction  
The second approach is a simple algorithm that aims to reduce communication. In this algorithm, whose pseudocode is listed in Algorithm 3, the layers are assigned to the same device in order until it has no memory to fit some layer. Next, if there is any space left in the device and the layer type is convolution, pooling, or input, then a two-dimensional number of vertices (width and height) that fit the rest of the memory of this device are assigned to it or, if the layer is fully connected, then a number of vertices that fit the rest of the memory of this device are assigned to it. After that or if there is any space left in the device, the next layer or the rest of the current layer is assigned to the next device and the process goes on until all the vertices are assigned to a device. It is worth noting that Algorithm 3 assumes that there is a sufficient amount of memory provided by the setups for the neural network model. Furthermore, this algorithm can partition graphs using fewer devices than the total number of devices provided. This algorithm contains two loops that depend on the number of layers (L) and the number of devices (D) of the setup, which render the algorithm complexity equals to O(L+D). However, it is worth noticing that both L and D are usually much smaller than the number of neurons of the neural network.  
Figure 5 shows the visual partitioning using the greedy algorithm for each experiment. It is worth noting that this algorithm works both for the free-input-layer and the locked-input-layer experiments because the input layer could be entirely assigned to the same device for all setups. Furthermore, as the partitioning scheme is similar for LeNet 2:1 and LeNet 1:1 in the experiments with 2, 4, and 11 devices, only the partitionings for LeNet 2:1 are shown in Figure 5a-c for the sake of simplicity. For the experiments with 56 and 63 devices, the greedy algorithm results in the same partitioning because the same device model is employed in these experiments. However, as LeNet 2:1 employs 44 devices and LeNet 1:1 employs 38 devices, both results are shown in Figure 5d,e, respectively.  
Figure 4: LeNet 2:1 per-layer partitioning provided by the user.  
```
1:functiongreedyAlgorithm(\(lenet\), \(setup\))
2:for\(layer\gets 1\) to \(lenet.numberOfLayers\)do
3:for\(device\gets setup.first\) to \(setup.last\)do
4:if\(lenet[layer].memory\
eq 0\)then
5:if\(lenet[layer].memory\leq device.memory\)then
6:assign\(layer\) to \(device\);
7:elseif\(lenet[layer].type=conv\) or \(pooling\) or \(input\)then
8:assign a 2D number of vertices that fit \(device\);
9:elseif\(lenet[layer].type=fully\)\(connected\)then
10:assign the number of vertices that fits \(device\);
11:endif
12:\(device.memory\leftarrow device.memory-assigned\);
13:\(lenet[layer].memory\gets lenet[layer].memory-assigned\);
14:else
15:break;
16:endif
17:endfor
18:endfor
19:endfunction
```  
**Algorithm 3** Greedy algorithm for communication reduction.
## 2 Fair Scheduling Algorithms in IEEE 802.16e Mobile WiMAX Networks
### Deficit Round Robin (DRR)  
DRR [4] is one of the simple throughput fair allocations used in wired networks. DRR avoids packet fragmentation overheads by scheduling only a full packet. Basically, the packet is not scheduled, and the deficit (amount that would have been allocated) is stored in case a packet will result in exceeding the fair share.  
Table 1 shows an example of DRR. In this example, there are four MSs, and each MS has only one flow. Each flow is mapped to a single queue. Suppose all packets are 125 bytes in size. Again, assuming the Mobile WiMAX frame capacity is 300 bytes. Then, to achieve a fair allocation, the fair share is set to 1/4 th of 300 or 75 bytes; this is called the quantum size.  
In this example, the packets are scheduled sequentially from each queue. Four frames are illustrated as an example. There are 2 rounds in the first and third frame. There are no rounds in the second and fourth frame. Note that notation _N/M_ is used where \(N\) is the size of allowed transmission, and \(M\) is the cumulative deficit counter value at the end of that round.  
Basically in each round, the deficit counter is increased by the quantum size, 75. The packets from queues with the deficit counters greater than the head packet size are scheduled. Again, in this particular example, only two packets in each frame are transmitted, and result in 50 unused bytes. The packets being transmitted in each frame are shown in Table 1. Notice that \(N\) is always 125 bytes.
## 4 Discussion
### Identification of Branching Reactions  
As a positive finding, QPAML classifies reactions reported in the literature as candidates for disruption, as well as subsequent reactions in the same pathway, just as in a real disruption would occur, regardless of whether the fluxes are not equal. The resulting reactions classified for disruption span the entire metabolic pathway, as indicated by the connectivity of reactions in Figure 7. Consequently, silencing branching reactions may deactivate multiple reactions. For instance, silencing the chorismate mutase reaction inactivates the enzymatic reactions of the L-tyrosine and L-phenylalanine biosynthesis pathways.  
All reactions with experimental evidence were at distances of 1 or 2 from the 76 pFBA optima enzymatic reactions.  
Reactions adjacent to pFBA optima are more suitable for silencing. Reactions at a distance of 2 reported in the literature were considered either due to the presence of a bifunctional enzyme encoded by _pheA_[76] or the incomplete silencing of adjacent reactions due to the lack of acknowledgment of the _eutD_ encoded isoenzyme [97; 98; 99; 100]. Apart from the reactions reported in the literature to enhance the production of tryptophan, the algorithm identified reactions that have been silenced to increase the production of precursor metabolites (Table 3).  
The enumeration of metabolic pathways has been a challenging problem that has been addressed from different points of view [58; 107; 108]. A more accurate method for measuring reaction distance is necessary to avoid classifying reactions in the last part of salvage pathways as branching reactions. For instance, reactions involved in the \(\beta\)-oxidation pathway that are tightly regulated [109] may not be suitable for disruption.
## 4 Results and Analysis
### EV Penetration in Rural Network
#### 4.2.2 Case 6: 40% EV Penetration in Rural Network  
In addition, in this scenario, the outcomes of which are presented in Figure 14, the results are acceptable, showing that the MV/LV transformer is able to sustain the 40% EV penetration with the maximum peak of 102.2%. The impact of the EV does not require any interventions but the coupling of photovoltaic and battery system can be useful in the future, to face even higher penetration of vehicles. Neither the voltage profile is affected significantly since the variation with respect to the base case is less than 1%.
# Mitigating Distractor Challenges in Video Object Segmentation through Shape and Motion Cues
## 3 Methods  
This section introduces the main components of our method, including the baseline network in Section 3.1, the object shape extraction module (OSEM) in Section 3.2, and the object motion prediction module (OMPM) in Section 3.3. The object shape extraction module can enhance the network's segmentation performance in the object overlap area, and the object motion prediction module can improve the network's robustness to distractor objects. Figure 1 shows the intuitive effects of these two modules. In the first row, using only the segmentation results from OSEM demonstrates high accuracy in edge-region segmentation but comes with the issue of incorrectly segmenting distractor objects. On the other hand, in the second row, relying solely on OMPM for segmentation noticeably reduces the problem of distractor objects but leads to a decrease in accuracy in edge-region segmentation. In the third row, by simultaneously applying OMPM and OSEM, we clearly observe the synergistic effects of both, substantially alleviating the issue of distractor objects and successfully enhancing the accuracy of edge-region segmentation.
## 2 System Overview  
### System Structure  
The configuration of the FPTLIR is shown in Figure 1, which consists of two main components: the flight mechanism and the travelling mechanism [39]. The flight mechanism is designed according to a hexacopter UAV, which includes the undercarriage, folding arm, control chamber, motor, and rotor blade. In addition, the travelling mechanism consists mainly of rolling components and pressing components. The rolling component comprises an active travelling wheel and two auxiliary guide wheels, while the pressing component includes a main pressing wheel and two auxiliary pressing wheels. Moreover, two lithium-polymer batteries are located under the control chamber to adjust the FPTLIR's center of gravity for improved flight stability.
# Time-Domain Near-Infrared Spectroscopy and Imaging: A Review
## 3 Instruments for TD-NIRS
### Time-Correlated Single Photon Counting (TCSPC) Technique
#### 3.2.3 Multi-Channel TD-NIRS Systems Based on TCSPC for DOT  
Multi-channel TD-NIRS systems have been developed for the purpose of TD-DOT. In 1999, a Japanese group developed a 64-channel TD-NIRS system and studied the image reconstruction algorithm as well as the performance of the system [45]. Figure 9 shows the photograph and block diagram of the system which had 64 independent detector units, while light sources of three pulsed laser diodes with three wavelengths operated in turn using an optical switch for selecting a wavelength and a mechanical switch for selecting a source position. Results using this system are reviewed in a later section [46; 47; 48].  
A 32-channel TD-NIRS system named MONSTIR (Figure 10) was developed by a group from the University of London for reconstructing TD-DOT images of brain functions in premature infants at bedside [49]. The DOT images obtained using these systems are reviewed later in Section 5.3.4.  
Figure 9: Photo and block diagram of the 64-channel TD-NIRS system developed by the group in Japan. Modified from Reference [45].  
[PERSON] et al. [50] developed a 16-channel TD-NIRS system based on the TCSPC technique to reconstruct TD-DOT images from measured TR reflectances at an adult human forehead. Results of TD-DOT using this system are reviewed later in Section 5.3.4.
###### Abstract  
Beamwidth-reconfigurable antennas are useful for the intersatellite link of low earth orbit formation flying and constellation, as they prevent unauthorized satellites from eavesdropping. In this article, a circularly polarized slot array antenna based on a half-mode substrate-integrated waveguide (HMSIW) for the K-band beamwidth reconfiguration is proposed using a new radio frequency (RF) switch structure and a pair of modified \(-45^{\circ}\) and \(+45^{\circ}\) linearly polarized HMSIW slot arrays for the dual operation of a single-pole double-throw (SPDT)/a power divider (PD) and easy integration with other components, respectively. The RF switch structure consists of a T-junction PD, \(\lambda/4\) lines, and beam lead PIN diodes with current control resistors and without a DC block circuit for low DC power consumption and size reduction. The \(-45^{\circ}\)/\(+45^{\circ}\) linearly polarized HMSIW slot arrays providing linear and circular polarizations (LP and CP, respectively) are operated for CP. The use of a short-circuited termination instead of dissipative termination results in easier integration with other components because the 16 radiating slots consume most of the input power. The dimension of the beamwidth-reconfigurable antenna including the bottom metal layer is 157.2 \(\times\) 23.3 \(\times\) 0.254 mm\({}^{3}\) (12.5 AlO\({}_{0}\)\(\times\) 1.86 AlO\({}_{0}\)\(\times\) 0.0202 AlO\({}_{0}\)). The RF switch for the SPDT shows the insertion losses of 1.8-2.3 and 16.7-24.2 dB and an isolation of 20.9-33.4 dB for both outputs within the 10-dB bandwidth. The RF switch for the PD has an insertion loss of 3.9-4.8 dB. The one- and two-antenna operation modes of the CP antenna provide the gains of 9.44 and 6.99 dBic, the axial ratios of 2.24 and 3.47 dB, and the horizontal beamwidths of 35.8\({}^{\circ}\) and 78.2\({}^{\circ}\), respectively.  
Beamwidth-reconfigurable antenna; half-mode substrate-integrated waveguide (HMSIW); single-pole double-throw (SPDT); power divider (PD) +
Footnote †: journal: Electronics
# VR Simulation and Implementation of Robotics: A Tool for Streamlining and Optimization
## 4 Case Study
### Simulation Model  
The model of the Z production line was meticulously crafted within the simulation software Visual Components Premium 4.8, leveraging both company data and insights gleaned from a thorough analysis of the current operational landscape. The depicted model in Figure 6 encapsulates the intricate production journey of rotor pockets within the designated workspace, incorporating all pertinent elements and stakeholders involved in this process. Notably, the simplicity of the model is deliberate, eschewing superfluous details such as spatial infrastructure and ancillary equipment. This strategic omission serves a dual purpose: facilitating the ease of integration with VR simulation models, should the need arise for enhanced realism or expanded functionality, while concurrently optimizing file size to ensure smooth technical performance. The judicious decision to forego the  
Figure 5: Workplace layout scheme.  
inclusion of peripheral elements, such as doors, lights, and flooring, is underpinned by their tangential relevance to the core simulation objectives, thus streamlining data processing and evaluation without compromising the efficacy of the proposed solution.  
The production process model encompasses various simulated components essential to the workflow, including belt conveyors, human operators, CNC milling machine, cooling devices, and handling units for storing and transporting finished products. To streamline the simulation and circumvent complexities associated with integrating ingot inputs arriving from another workplace, the authors opted to simplify by generating inputs directly at the \(Z\) line production. These inputs, represented by yellow cubes, are set to arrive at 250-s intervals, facilitated by the device called \"Feeder\", depicted as a beige box, which ensures the regular entry of input material onto the belt conveyor. Belt conveyor no.1 transports these inputs to a human operator, controlled within the simulation using the human source controller (HSC) and idle location (IL) devices. Idle locations are represented as rectangles with a black circle, and on the contrary, HCS is represented as a black circle with a blue outline and a human logo. The HSC initiates the operation of the human operator along a predefined route, while the IL determines their starting position and return point upon route completion. The production equipment itself, namely the CNC milling machine, is not simulated in detail, as its precise operation is overseen by rained programmers. Only the duration of the milling process is specified, not the intricacies of its performance, reflecting our deference to the expertise of company personnel responsible for its optimization. Following milling, products are transferred to a second belt conveyor for cooling, where they are then loaded into pallets by a second human operator, who returns to their initial position after completing the task. Similar devices and programming principles are employed for both human operators to ensure consistency and ease of simulation.
## 3 Results
0.05 of this spectral parameter; the probability of  
Figure 4: Statistical analysis of the following spectral parameters: (**A**) Amide I/PO\({}_{4}\), (**B**) C/P, (**C**) MM, (**D**) FWHM\({}_{603}\), and (**E**) IRSF. Data are presented as mean \(\pm\) SD; different letters indicate statistically significant differences among groups (one-way ANOVA and [PERSON]’s multiple comparison test; \(p<0.05\)). BA3 displayed an increasing trend, with a maximum of 0.5 at the highest amide I/PO\({}_{4}\) value, while the lowest ones were strongly associated (probability = 1) with the ENV category, hence, to the animal bones. With regards to the C/P ratio, the probability associated with BA1 and BA2 reached the maximum level (0.3) at a value of ca. 0.10 of this spectral parameter, while the probability of BA3 displayed an increasing trend, with a maximum of 0.6 at the highest C/P value; as with the previous case, the C/P lowest values were strongly associated (probability = 0.8) with animal bones. By considering the MM index, the probability associated with BA1, BA3, and ENV showed an almost similar decreasing trend, while the regression line associated with the probability of the BA2 category increased, with a maximum level of almost 0.7 related to the highest MM index values. With regards to the FWHM\({}_{603}\) value, the probability associated with BA1 showed the highest level of ca. 0.3 with an FWHM\({}_{603}\) value of 20 and decreased with higher values; the probability associated with BA2 and BA3 showed a superimposable increasing trend, which reached 0.4 with high values of the analyzed spectral feature. Finally, the logistic regression performed by using the IRSF index showed an almost superimposable decreasing trend of probability for BA1, BA2, and BA3 categories, which reached the null probability at >3.25 IRSF values; the highest IRSF values were strongly associated (probability = 1) with animal bones. Then, the statistical significance of the association between the burial area and the spectral parameters of all samples was determined using the ENV category as the reference (Table 3). No significant effect of the burial area was detected for amide I/PO4 and MM parameters (significance > 0.05). With regards to the C/P ratio and FWHM\({}_{603}\), a significant effect was highlighted only for BA2 and BA3 (significance < 0.05), while for the IRSF index, a significant effect was found only for BA1 and BA3 categories (significance < 0.05). Overall, these data confirmed that the chemical and structural features of carbonated hydroxyapatite were different among the samples according to the burial area [5]. Figure 5: Correlation between C/P and MM indexes calculated for the archaeological human and modern ruminant bones from the Fewet oasis in the Sahara of SW Libya. The central black line represents the regression line of the fitted model; grey lines represent the 95% confidence interval.
## 3 Results and Discussion
### Invertase Activity in Fresh and Dried Samples  
The invertase activity in fresh and dried mango of the varieties Sindri, S.B. Chaunsa, and Tommy Atkins was also analyzed, and the results are displayed in Figure 2. Invertase activity was the highest in fresh samples of Tommy Atkins (0.95-1.37 units min\({}^{-1}\) g\({}^{-1}\)), followed by SB Chaunsa (0.93-1.21 units min\({}^{-1}\) g\({}^{-1}\)), and Sindri (0.45-0.77 units min\({}^{-1}\) g\({}^{-1}\)). During drying however, as for amylase, both the drying temperature and the air velocity showed a significant influence on the invertase activity retention in dried samples. In all three varieties, the maximum average invertase activity (3.12-9.99 units min\({}^{-1}\) g\({}^{-1}\)) was retained in samples dried at 80 \({}^{\circ}\)C and 1.4 m s\({}^{-1}\) air velocity compared to those dried at lower temperatures and 1.0 m s\({}^{-1}\) air velocity. As invertase is also a thermotolerance enzyme, this finding corroborates that the preservation of heat-resistant enzymes in dried mango is directly related to the drying time. Drying at 80 \({}^{\circ}\)C and air velocity of 1.4 m s\({}^{-1}\) exhibited a higher moisture loss and shorter drying time compared to low drying temperatures at an air velocity of 1.0 m s\({}^{-1}\)[2; 13]. Consequently, a reduction in drying time could effectively lead to the preservation of invertase in dried samples. On the other hand, many studies have also reported that prolonged heat exposure to invertase above the optimal temperature of 37 \({}^{\circ}\)C causes its destruction or degradation, due to thermal denaturation of enzyme protein [37; 38]. Thus, mango slabs dried at a low temperature required a longer drying time to remove moisture up to its target level, and eventually the invertase activity decreased.  
Figure 2: Invertase activity in fresh and dried mango varieties Sindri, SB Chaunsa, and Tommy Atkins; D = dried samples at temperatures 40 \({}^{\circ}\)C to 80 \({}^{\circ}\)C. a–g, different letters in the box plot indicate significant differences under the limit of \(p<0.05\), (\(n=20\times 3\)).