esa-sceva/satcom-chunk-collection huggingface dataset:
We showed that cyclo(Pro-Hyp), a major component of food-derived cyclic peptides, was more effective at enhancing the growth rate of mouse skin fibroblasts than Pro-Hyp [13]. Based on these in vivo and in vitro studies, linear or cyclic Hyp-containing di- and tripeptides are expected to accumulate in the bloodstream after the ingestion of CP and subsequently regulate the functions of target cells in the skin and joint tissues. Food-derived peptides are absorbed through peptide transporters such as Pept1, an exclusive di- and tripeptide transporter expressed in the intestinal brush-border membrane [15,16]. However, in previous studies, micromolar levels of Hyp-containing peptides that consist of more than four amino acid residues have not been detected in human blood after the ingestion of CP [6,7]. The higher absorption of Hyp-containing di- or tripeptides by the ingestion of CP could promote joint, skin, and muscle health. Food-derived di- or tripeptides detected in human blood are produced via the degradation of protein and long-chain peptides by gastrointestinal and food-derived enzymes during digestion and fermentation, respectively. The co-ingestion of food or beverage matrices with CP might affect peptide digestion in the gastrointestinal tract, thereby altering the production of small peptides and consequently influencing the absorption of the peptides into the blood. Previous studies have examined the absorption of food-derived collagen peptides in human blood after the ingestion of CP that had been dissolved in water. [PERSON] et al. have demonstrated that the co-ingestion of fermented milk and CP could increase the plasma concentration of collagen-specific amino acids, especially proline (Pro) [17]. They suggested that milk-derived peptides in fermented milk products might affect the absorption of collagen-derived amino acids in the small intestine. Therefore, it is expected that the co-ingestion of CP and yogurt might enhance the absorption of short chain peptides and amino acids in the blood. It has been reported that lactic acid bacteria in cheese have proteolytic activities that are accomplished by their cell envelope proteases and intracellular peptidases [18]. A previous study showed that the ingestion of smaller CP cleaved by ginger proteases enhanced the absorption of Hyp-containing peptides in mouse blood after oral administration [19]. These studies suggest that food-derived enzymes can produce small peptides and enhance the absorption of food-derived peptides in human blood after ingestion. Therefore, the fermentation of CP with yogurt might increase the production of short chain Hyp-containing peptides and its ingestion could possibly enhance absorption of Hyp-containing di- and tripeptides in human blood. In this study, we examined the level of Hyp-containing di- and tripeptides in CP which had been prepared with or without yogurt fermentation. We also evaluated the concentration of Hyp-containing di- and tripeptides in human blood after the co-ingestion of CP with or without yogurt fermentation.
## 2 Materials and Methods  
### Imaging Dataset  
A total of 264 eyes from 155 patients diagnosed with Stargardt disease were identified from the ProgStar study that had both SD-OCT scans performed on the initial visit and FAF imaging performed at a six-month follow-up. Of these two hundred and sixty-four eyes, two hundred and thirty-seven were identified that had FAF imaging performed at a twelve-month follow-up. All of the FAF images were manually segmented by certified graders to create ground-truth masks marking the atrophied regions of the retina. Images were randomly assigned to training and testing sets in an approximate 3:1 ratio. Of the six-month follow-up FAF images, two hundred of the images were used for training, and sixty-four were used for testing. Of the twelve-month follow-up FAF images, one hundred and eighty of the images were used for training, and fifty-seven of the images were used for testing. The SD-OCT volume dimensions are 496 (depth) \(\times\) 1024 (A-scans) \(\times\) 49 (B-scans) pixels or 496 (depth) \(\times\) 512 (A-scans) \(\times\) 49 (B-scans) pixels. The 496 \(\times\) 512 images were resized to a standard width of 1024. After segmentation, 49 \(\times\) 1024 feature maps were produced from each SD-OCT volume. These feature maps were resized to 512 \(\times\) 512 for registration to FAF images and later resized to 128 \(\times\) 128 prior to being input to the neural network due to memory constraints. SD-OCT scans and FAF images of right (OD) eyes were reflected horizontally to maintain consistency throughout training and testing.  
All images were de-identified according to the Health and Insurance Portability and Accountability Act Safe Harbor. All subjects gave their informed consent for inclusion before they participated in this study. This study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of each of the participating institutions. This study has been registered at [[https://www.clinicaltrials.gov](https://www.clinicaltrials.gov)]([https://www.clinicaltrials.gov](https://www.clinicaltrials.gov)) (NCT01977846, accessed on 12 June 2023).
# A New Approach to Preform Design in Metal Forging Processes Based on the Convolution Neural Network
## 3 Numerical Experiments
### Two Axisymmetric Forging Cases  
The CNN sub-models were utilized to derive preform shapes for the two axisymmetric test parts, as shown in Figure 8 where the height features are listed in Table 2. The dimensions of the two shapes were randomly designed to yield completely different geometrical features.  
The finite element forging simulation results for the preform candidates were acquired from the 2D FEM model, summarized in Appendix B, by considering the 2D cross-sections of the preform candidates as derived by 3D modeling shapes.  
Based on the FEM results, for the test shape, as shown in Figure 8a, the preform derived by the CNN#3 sub-model resulted in a maximum forging load reduction of 15.9% (Figure 9). For the shape shown in Figure 8b, the CNN#4 sub-model derived a preform resulting in a 16.5% forging load reduction (Figure 10).  
\begin{table}
\begin{tabular}{|c|c c c c c c|} \hline CNN sub-model \# & CNN\#1 & CNN\#2 & CNN\#3 & CNN\#4 & CNN\#5 & CNN\#6 \\ \hline \multirow{3}{*}{
\begin{tabular}{c} Height-based grouping conditions \\ \end{tabular} } & \multirow{3  
Figure 8: **(a)** First and (b) second axisymmetric test forging shapes adopted for the validation of the CNN sub-models.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Forging Shape** & **Height** & **CNN\#1** & **CNN\#2** & **CNN\#3** & **CNN\#4** & **CNN\#5** & **CNN\#6** \\ \hline \multirow{2}{*}{Figure 8a} & Hmax & 0.48D & 0.51D & 0.51D & 0.50D & 0.50D & 0.48D \\  & Hmin & 0.30D & 0.29D & 0.32D & 0.30D & 0.30D & 0.29D \\ \multirow{2}{*}{Figure 8b} & Hmax & 0.40D & 0.39D & 0.40D & 0.40D & 0.39D & 0.41D \\  & Hmin & 0.27D & 0.29D & 0.31D & 0.28D & 0.33D & 0.30D \\ \hline \hline \end{tabular}
\end{table}
Table 2: Height features of the derived preform shapes for the axisymmetric forging shapes.  
Figure 9: **(a)** Preform geometries and **(b)** forging force–punch patch curves computed for each of the CNN sub-models (including the cylindrical billet) for the forgings of Figure 8a.
# The Design and Implementation of a Novel Open Source Massive Deployment System
## 2 Related Works
### Differential Update Method  
Regarding the previously mentioned system deployment software adopting differential update technology, \"rsync\" is the major open source software that provides fast incremental file transfer and a synchronization mechanism [18]. However, more procedures than just copying files are required in system deployment. Such procedures include the creation of partition tables and file system(s) and interactions with the boot loader. However, because \"rsync\" lacks all of the functions that are required to deploy an entire system onto a disk, some other tools have been developed to cross the gap based on the differential update method. Mondo Rescue [19] is open source software that can deploy Linux and FreeBSD systems. Mondo Rescue has been used by thousands of users and companies. Another open source software, called ReaR [20], can also deploy the Linux system and has been expanded as Disaster Recovery Linux Manager (DRLM), which can support massive deployment [21]. Storix System Backup Administrator (SBAdmin) [22] is a commercial proprietary software with good graphical user interface (GUI), Web, and command-line interfaces. Therefore, system administrators can choose the interface that they prefer when conducting system deployment. Because SBAdmin can deploy the Linux system only, the application of SBAdmin is constrained.
## 3 High-Dimensional Medical Imaging Analysis Based on Deep Learning
### Semi-Supervised Deep Learning Strategies for MRI  
Traditional classifiers need labelled data for the training process. Labelling individual images, however, is often difficult, expensive and time consuming, as it requires the efforts of experienced annotators. Semi-supervised learning (SSL) is a special form of classifier, which reduces the overhead for annotation and labelling by using both labelled and unlabelled samples.  
Ideally, only labelled samples should be used to ensure good classifier performance, but in many imaging modalities there is a shortage of these. For example, when classifying lesion patches vs. normal tissue patches, annotated features can be used to create a set of labelled patches. MRI without annotations can still be used to create a large set of unlabelled patches. There are two aspects in SSL methodologies that can lead to better classifier outcomes: the first is predicting labels for future data (inductive SSL); the second is predicting labels for the already available unlabelled samples (transductive SSL) [89].  
Figure 7: Flowchart of Semi-Supervised tumour Segmentation (SSTS). This was developed in line with [88].  
SSL is naturally practiced by medical personnel in medical imaging, during segmentation as well as for diagnosis. For example in image segmentation, an expert might label only a part of the image, leaving many samples unlabelled. In computer-aided diagnosis, there might be ambiguity regarding the label of a subject, so instead of adding these subjects to the training set or removing them completely, they can still be used to improve the classifier performance [90]. [PERSON] et al. [91] presented an extension of [PERSON]'s Rational Model of Categorization and this forms the basis for SSL. Using an unconstrained free-sorting categorisation experiment, it was illustrated that labels were only useful to participants when the category structure is ambiguous.  
Typically semi-supervised approaches work by making additional assumptions about the available data [89; 92]. These include the smoothness assumption, i.e., samples close together in feature space are likely to be from the same class, the cluster assumption, i.e., samples in a cluster are likely to be from the same class, and the low density assumption, i.e., class boundaries are likely to be in low density areas of the feature space. For an in-depth review of SSL (not limited to MRI), one should refer to [90].
## Materials and Methods
### Field Verification Test Section  
#### 2.3.1. Manned Helicopter and Carrying Equipment  
The helicopter used in field test was Bell206L4 (Figure 4), equipped with a Simplex model 7900 (Simplex Manufacturing Company Inc., Auburn, AL, USA) spray system for precision variable-rate spraying control. Simultaneously. A total of 51 CP nozzles were installed in the aircraft, of which 6 nozzles (spacing of 17 cm) were installed below the belly in a vertical downward direction, and 45 nozzles (spacing of 15 cm) were installed on the boom in a horizontal backward direction. An airborne BeiDou real time kinematic (RTK) differential system developed by SCAU with the function of RTK differential positioning was also equipped, which can record flight parameters in real-time and draw actual operation trajectory as references of the spraying effect. The specification of the helicopter and carrying equipment are listed in Table 2.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Main Parameter** & **Norms and Numerical Value** \\ \hline Airframe length (m) & 10.56 \\ Airframe height (m) & 3.04 \\ Main rotor/Tail rotor diameter (m) & 11.28/1.65 \\ Maximum load (L) & 600 \\ Maximum velocity (km/h) & 241 \\ Empty weight (kg) & 1 057 \\ Max. takeoff weight (kg) & 2 064 \\ Boom length (m) & 8.60 \\ Nozzle quantity & 51 \\ Spray width (m) & 25-40 \\ Pesticle tank size (m \(\times\) m \(\times\) m) & \(2.40\times 1.20\times 0.45\) \\ Working performance (hm2/h) & 305-500 \\ Spray system & Simplex \\ BeiDou plane accuracy (mm) & (\(10+5\times\) D \(\times\) D \(\times\) D \({}^{-7}\)) [a] \\ BeiDou elevation accuracy (mm) & (\(20+1\times\) D \(\times\) D \({}^{-6}\)) [a] \\ \hline \hline \end{tabular}  
* [a] D represents actual distance measured by BeiDou differential system, km.  
\end{table}
Table 2: Technical parameters of Bell206L4 helicopter and main performance indexes of equipped equipment.  
Figure 4: Bell206L4 helicopter for spraying operation.
# Provably Secure ECC-Based Anonymous Authentication and Key Agreement for IoT
## 2 Preliminaries
### Elliptic Curve Encryption Mathematical Problems  
Let \(q>3\) be a big prime number, \(E(a,b)\) denote a non-singular elliptic curve over a finite field \(F_{q}\), and \(P\) be a generator point. The group operation is the usual multiplication of points on the elliptic curve, and \(G\) is a subgroup of order \(p\), where \(p>q\)[39]. Hence, the following applies.  
Definition 1: Elliptic curve discrete logarithm (ECDL) problem: For the given points \(X\) and \(aX\), where \(X\in G\) and \(a\in Z_{q}^{*}\), it is computationally intractable to find \(a\).  
Definition 2: Elliptic curve Diffie-Hellman (ECDH) problem: For the given points \(aX,bX\in G\), where \(X\in G\) and \(a,b\in Z_{q}^{*}\), finding point \(abX\) is computationally intractable.
## 4 Experimentation and Results
### Retailer Characteristics
#### 4.1.2 Product Categories  
The study's shops mainly sell various consumer goods, such as snacks, drinks, chocolates, and clothing. These categories were selected because of their broad customer appeal and high sales volume, facilitating product turnover. Among these areas, each store has a large assortment of popular chocolates, candies, juices, soft drinks, trendy clothing, and accessories. The stores are perfect places to test real-time object identification algorithms designed to improve inventory management, product placement, and the overall shopping experience because of the wide range of items that cater to various consumer tastes and shopping demands.
## 5 Conclusions
Hence, the properties of the low-cost SHM system may provide a competent, cheap methodology for the SHM of civil structures. The on-field arrangement of the low-cost SHM system demonstrated a relevant capability for monitoring the structural response through a permanent wireless Internet connection and remote communication to distances of up to 20 m between the measuring node and base station. This research combined the implementation of low-cost, easy-to-use electronic devices; the practicality of laboratory and on-field experimental setups; and the computing of standard dynamical identification techniques in order to efficiently characterize the structural dynamic properties of civil infrastructure using an extensive, flexible SHM system. Future research directions may extend the presented standard dynamical identification technique by adding vibration-based damage detection methods, finite element model updating, and digital twins algorithms that examine the structural health in ambient conditions or in response to natural hazards in real-time. Conceptualization, D.C.-R., A.R.O. and A.G.; methodology, D.C.-R., A.R.O. and A.G.; formal analysis, D.C.-R. and A.R.O. ; software, D.C.-R. and C.C. ; writing--original draft preparation, D.C.-R., A.R.O. and A.G.; writing--review and editing, D.C.-R. and A.R.O. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The data presented in this study might be available on reasonable request from the corresponding author. The authors would like to thank Universidad del Norte for providing the National Instrument data acquisition system and PCB Piezotronics accelerometers for the instrumentation of large-scale civil structures. The authors declare no conflict of interest.
## 3 Pose Estimation Based on Visual-IMU Fusion
### Pose Estimation and Optimization Based on Visual-IMU Fusion  
Both the visual odometry and the IMU odometry can obtain the pose transformation matrix. However, the feature point pairs are easily lost when the visual odometry moves rapidly; the IMU data can easily be diverged. Therefore, we adopt a tightly coupled approach to construct a least squares problem of minimizing the visual reprojection error Equation (2) and the IMU pre-integration error Equation (4), and we obtain the pose estimation using nonlinear optimization:  
\[\chi=\underset{\chi}{\text{argmin}}\left\{\sum_{k\in F}\sum_{p\in P}\left\|r_ {C_{p}}\right\|^{2}+\sum_{k\in F}\left\|\big{(}r_{l_{k}}\big{)}\right\|^{2}\right\} \tag{5}\]  
\[\chi=\{p_{k}^{w},v_{k}^{w},q_{k}^{w},p_{k}^{w},p_{k}^{a}\} \tag{6}\]  
where \(F\) represents all image frames; \(P\) represents the feature points extracted from all image frames; \(p_{k}^{w}\), \(v_{k}^{w}\), and \(q_{k}^{w}\) represent the position, velocity, and attitude, respectively, of the \(k\)th key frame under the world coordinate system (W); and \(b_{k}^{w}\) and \(b_{k}^{a}\) represent the bias of the gyroscope and the acceleration at the \(k\)th key frame, respectively. Finally, we adopt the Gauss-Newton method to solve Equation (5) in order to obtain poses \(p_{k}^{w}\) and \(q_{k}^{w}\) at the \(k\)th key frame. According to the pose information of the previous frames, the global pose transformation matrix \(T_{C}^{W}\) of the current time can be obtained.  
Therefore, this paper obtains the global real-time positioning information of the forest point cloud reconstruction system at the current time.
# Queue Spillover Management in a Connected Vehicle Environment
## 3 Intersection Signal Control Modeling  
In this study, the following three assumptions are proposed:  
* The vehicle controller can provide spatial position and speed information to the intersection signal controller;
* Signal controllers of adjacent intersections can interact with each other;
* Keeping the same safety distance between the vehicles in line.  
Figure 1: The schematic diagram of intersections between intersection and signal controller under Vehicle to Infrastructure (V2I).  
Figure 2: Queue overflow control scheme at intersection.
## 3 Results and Discussion
### Microstructure of Geopolymers
#### 3.2.3 FT-IR Spectroscopy Analysis  
Figure 6 shows the FT-IR spectra of materials prepared with an 8 M NaOH activator and different amounts of calcium hydroxide. The spectral results focused on the range from 400-1600 cm\({}^{-1}\), where some important broad bands characterizing T-O bonds (T: Si, Al) are located [2]. The band in the range of 800-1200 cm\({}^{-1}\) corresponds to the asymmetric and symmetric stretching vibration of Si-O bonds. The characteristic broad band located in the range of 900-1200 cm\({}^{-1}\), which is associated with the asymmetric stretching vibration  
Figure 5: Scanning electron micrographs of geopolymer materials prepared using 8 M NaOH activator and Ca(OH)\({}_{2}\) content of 0 g (**a**), 15 g (**b**), 30 g (**c**), 45 g (**d**), 60 g (**e**), 75 g (**f**) at 28 days of curing time.  
of the Si-O-T, is the key focus of geopolymer specimens [2]. It can be seen that the peak position of the wavenumber shifted from 972 cm\({}^{-1}\) to 985 cm\({}^{-1}\) as the calcium hydroxide content was increased from 0 to 30 g. Then, a higher amount of calcium hydroxide than 30 g would make the peak position shift to a lower wavenumber. [PERSON] et al. [25] also found a shift in the Si-O-T asymmetric stretching vibration when the amount of Ca(OH)\({}_{2}\) was increased in the fly ash-based geopolymers. Particularly, the peak shifted first to a lower wavenumber and then shifted to a higher wavenumber as the amount of Ca(OH)\({}_{2}\) was increased. The authors believed that the polymerization of Si-O-Al should take place when Ca(OH)\({}_{2}\) is less than a critical value of content, while the C-S-H gel is generated when higher than this critical value of Ca(OH)\({}_{2}\) amount is added. In this study, the shifting of the asymmetric stretching vibration to a higher wavenumber should indicate that C-S-H gel coexists with N-A-S-H gel in the geopolymer materials prepared with up to 30 g of Ca(OH)\({}_{2}\). The shifting to a lower wavenumber (from 985 cm\({}^{-1}\) to 968 cm\({}^{-1}\)), as higher than 30 g of Ca(OH)\({}_{2}\) was added, might correspond to the coexistence of C-A-S-H gel formed by ion exchange with N-A-S-H gel [37]. Moreover, the band shoulder at 952 cm\({}^{-1}\), which is assigned for C-A-S-H gel, was more clearly observed for materials prepared with 60 g and 75 g of Ca(OH)\({}_{2}\). Hence, C-A-S-H gel could coexist with N-A-S-H and C-S-H gels in materials prepared using higher than 30 g of calcium hydroxide.
## 2 Architecture of the Tethered Hexacopter System
### UWB Positioning System
For the reliable estimation of the tag's coordinates, a minimum of four usable distance measurements was required. During the final stage, the accuracy of the position calculation was evaluated. The evaluation process took into careful consideration various factors, including the number of accurate measurements, the quality and reliability of those measurements, and the distance between the anchor and the tag. These critical aspects were thoroughly assessed to ensure the validity and effectiveness of the evaluation. The adaptive UWB-based positioning system provided the estimation of the UAV's relative position, along with an assessment of its accuracy, to the algorithm performing the integration of the data provided from different measurement systems in order to output the final UAV position with respect to the position of the landing pad. This approach ensured that UWB measurements were excluded during the integration stage if the UWB system was unable to estimate the UAV's position. By considering the reliability of the UWB system's estimations, the integration stage selectively incorporated measurements from other reliable positioning systems. This exclusion helped maintain the accuracy and integrity of the integrated position estimation by avoiding the inclusion of potentially unreliable or erroneous data. As a result, the integration algorithm  
Figure 9: Dataflow of the adaptive UWB positioning algorithm [7]. could generate more robust and trustworthy estimates of the UAV's position by leveraging the most reliable and accurate sensor information available.
## 3 Localization Algorithms in WSNs
### Range Free Localization Algorithm  
Range free localization technique, which is totally dependent on the contents of the received packet and is a much cheaper solution than many range based localization techniques [64] in WSNs. Range free schemes are simple, inexpensive and energy efficient where localization is performed using geometric interpretation, constraint minimization and resident area formation [65].