esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
The ability to reduce the volatile acidity by _T. delbrueckii_ is a feature well documented [2; 42; 43]. Moreover, the use of T. _delbrueckii_ in sequential fermentation led to a reduction in total SO\({}_{2}\) content. Actually, there are no studies that directly correlate low sulfur dioxide production with the use of selected non-_Saccharomyces_ yeasts. However, [PERSON] and co-workers [42] highlighted the ability of _T. delbrueckii_ to reduce SO\({}_{2}\)-binding compounds production. We found that _T. delbrueckii_ in sequential fermentation reduced acetaldehyde content. The sequential fermentation _T. delbrueckii_/_S. cerevisiae_ determined a general increase in some aroma compounds affecting the aroma complexity of the wine, such as phenyl ethyl acetate, ethyl hexanoate and \(\beta\)-phenyl ethanol, even if not at significant levels. Several previous works highlighted the tendency of T. _delbrueckii_ to form higher levels of acetate compounds, \(\beta\)-phenyl ethanol and a general improvement of the quality of wine aroma increasing the perception of varietal and fruity characters [15; 44; 45]. On the other hand, confirming a previous work [15], the aroma profile of resulting wines was affected not only by non-_Saccharomyces_/_S. cerevisiae_ used in sequential fermentation, but also by the vintage. Overall data emphasized the use of selected non-_Saccharomyces_ yeasts, such as _T. delbrueckii_, in sequential fermentation with selected native _S. cerevisiae_ strains for Verdicchio wine production. Indeed, on one side, the use of native _S. cerevisiae_ reinforced the distinctive aromatic characteristics of a particular enological area, usually conferred by native yeast strains. On the other side, non-_Saccharomyces_ yeast produced peculiar fermentation by-products that positively influenced the analytical profile of Verdicchio wine, characterized by a well-structured style. Furthermore, a suitable strategy to obtain wine with reduced sulfites content is the use of improved native _S. cerevisiae_ DiSVA 708 (low sulfite producer) in pure and mixed fermentation with a selected _T. delbrueckii_ strain. [PERSON], [PERSON], [PERSON] and [PERSON] contributed equally to the manuscript. All the authors participated in the design and discussion of the research. [PERSON] carried out the experimental part of the work. [PERSON] and [PERSON] carried out the analysis of the data. All authors have read and agreed to the published version of the manuscript. This research received no external funding  
The authors wish to thank the winery Terre Cortesi Moncaro s.r.c.l. for technical assistance. The authors declare to not have financial and/or personal interests that could influence the study of the present manuscript.
## 3 Results
### Comparative Study with Previous VCSEL-Based Neural Networks  
In [30], the experimental data from a VCSEL based neuron are presented. This implementation detects specific patterns at GHz rates. Moreover, the input images are processed via a time multiplexing technique, which uses the same neuron to process different areas of the image, reducing in this way the number of actual neurons. On the other hand, in this scheme synaptic weights are fixed in advance and no training takes place. In [29] numerical results from a two-layer VCSEL-based spiking network which classifies numerical digits (0-9) are presented. In particular, [29] uses a timing-encoding scheme for data encoding while training is accomplished under a supervised STDP algorithm. Except for the training algorithm, the two networks have some key differences. First of all, Ref [29] deploys Convolutional Layers as a preprocessing step in order to moderate noise impact. In our work, Convolutional Layers are used to extract features from the input images, which offers our network the potential to be used in the classification of more complex images. Second, every pixel of the input image is processed by a different neuron. Since the input images have 400 pixels, a total of 410 neurons (400 neurons for pixel processing and 10 neurons for classification) is required to properly classify the images of the ten digits. In our network, thanks to time multiplexing only 62 are needed in order to classify 4 digits ('5', '6', '7' and '8'). Moreover, for the classification of all ten digits a total number of 87 neurons will be needed: specifically, 10 neurons for the Contrast Detection Layer, 32 at the first convolutional layer, 21 at the second, 14 neurons at the third and 10 neurons at  
Figure 10: Inference time of a single 12 \(\times\) 12 pixel image alongside the number of physical neurons at the PSCNN.  
the output layer. Moreover, [PERSON] [29] deploys a two-layer network while in our case a 'deep' five-layer convolutional neural network is implemented for the first time to our knowledge. Furthermore, the processing time of the images is fixed to 30 ns per image. In our case, the insertion of multiple layers permits the tuning of the processing times ranging from 5 ns (full parallel processing) to 720 ns (minimum number of neurons used). Lastly, in [29] the classification error is linearly dependent on the network's noise. On the other hand, our network has a sigmoid dependance from the noise (Figure 9). This makes our network better for low intensity conditions while [29] is better suited for noisy environments.
# Digital Holographic Positioning Sensor for a Small Deployable Space Telescope
## 5 Conclusions  
In the present paper, we propose a system and technique to measure misalignments of individual optical elements in a deployable telescope for a small satellite. The system does not require any additional passive optical components or detector and allows to align the telescope without an external reference. Since it is based on comparisons of the measured and computed interferograms, we classify it as a digital holographic sensor.  
On an example of the Ritchey-Chretien type telescope, with the primary mirror split into three segments and a movable secondary mirror, we demonstrate that the proposed approach allows one to measure the mirror position with high precision, using simple numerical metrics computed in the Fourier domain. The estimated sensitivity is 0.8 \(\upmu\)m and 0.1 nm for the primary and secondary mirrors, respectively. Using such a system would make it possible to build a deployable telescope fitting in a 1U CubeSat and align it in space with sufficient accuracy, thus providing the gain in collecting power, reaching a factor of 2.49 with respect to a monolithic mirror fitted into a 1U CubeSat.  
The further studies may include revision of the computational algorithms in order to perform the calculation faster and/or increase the number of elements in the image and the achievable accuracy. Another way to improve the proposed concept is to elaborate the proposed metrics in order to increase their sensitivity and decrease the influence of nonlinearities. Moreover, the exact implementation of the laser illumination system and deployment mechanisms should be considered in much more detail. Finally, the sensor performance modeling should take into account the overall errors budget, including thermal effects, noises, possible deformations of the supporting structures, and additional degrees of freedom of the actuators.  
Conceptualization, E.R.M. and A.Z.S.; methodology, E.R.M.; software, D.Y.K.; validation, N.K.P.; formal analysis, N.K.P. and O.G.M.; resources, O.G.M. and A.Z.S.; data curation, D.Y.K. and E.R.M.; writing--original draft preparation, E.R.M.; visualization, D.M.A.; supervision, E.R.M.; project administration, E.R.M.; funding acquisition, E.R.M., O.G.M. and A.Z.S. All authors have read and agreed to the published version of the manuscript.  
Work of E.R.M., D.M.A. and D.Y.K. was funded by the Russian Science Foundation grant number 21-79-00082.  
Not applicable.  
The authors would like to thank their colleagues from KNRTU-KAI, [PERSON] and [PERSON], for describing a similar problem in the field of radio-engineering, which inspired this research. We are also grateful to [PERSON] from Laboratoire d'Astrophysique de Marseille for proofreading of the manuscript.  
The authors declare no conflict of interest.
## 2 Handcrafted Representation-Based Approach
### Other Approaches
#### 2.3.2 Fuzzy Logic-Based Approaches  
Traditional vision-based human action recognition approaches employ the spatial or temporal features followed by a generic classifier for action representation and classification. However, it is difficult to scale up these approaches for handling uncertainty and complexity involved in real world applications. For handling these difficulties, fuzzy-based approaches are considered as a better choice. In [107], a fuzzy-based framework was proposed for human action recognition based on the fuzzy log-polar histograms and temporal self-similarities for action representation followed by SVM for action classification. The evaluation of proposed method on two public datasets confirmed the high accuracy and its suitability for real world applications. Another method based on fuzzy logic was proposed in [108]. This method utilized the silhouette slices and movement speed features as input to the fuzzy system, and employed the fuzzy c-means clustering technique to acquire the membership function for the proposed system. The results confirmed the better accuracy of the proposed fuzzy system as compared to non-fuzzy systems for the same public dataset.  
Most of the human action recognition methods are view dependent and can recognize the action from a fixed view. However, a real-time human action recognition method must be able to recognize the action from any viewpoint. To achieve this objective, many state-of-the-art methods use multi-camera setup in their processing. However, this is not a practical solution because calibration of multiple cameras in real world scenarios is quite difficult. The use of a single camera should be the ultimate solution for view invariant action recognition. Along these lines, a fuzzy logic-based method was proposed in [109] for view invariant action recognition using a single camera. This method extracted human contour from fuzzy qualitative Poisson human model for view estimation followed by clustering algorithms for view classification as shown in Figure 6. The results indicate that the proposed method is quite efficient for view independent action recognition. Some methods based on neuro-fuzzy systems (NFS) have also been proposed for human gesture and action recognition [110; 111]. In addition to this, evolving systems [112; 113] are also very successful in behaviour recognition.  
Figure 6: Example of Fuzzy view estimation framework.
# A Comparative Study of Differential Quadrature Methods for METE Nanobeam Vibrations
## 6 Conclusions  
This research provides a highly accurate numerical analysis (error \(<10^{-10}\)) of the vibrational behavior of METE nanobeams, employing three distinct differential quadrature methods (PDQM, Sinc-DQ, and DSCQM-RSK) implemented via a custom MATLAB program. A parametric study investigated how various factors influence nanobeam vibration, revealing key insights into their behavior:  
* The fundamental frequency increased with increasing axial forces, external magnetic potential, and linear elastic foundation characteristics.
* On the other hand, the fundamental frequency decreased when the temperature and the length-to-thickness ratio, nonlocal factors, and external electric voltage increased.
* Increased displacement and electrical potential amplitudes were associated with higher linear (and nonlinear) elastic foundation parameters.
* BiTiO\({}_{3}\)-COFe\({}_{2}\)O\({}_{4}\) outperformed PTZ-5H-COFe\({}_{2}\)O\({}_{4}\), exhibiting higher fundamental frequency and greater normalized amplitude and electrical potential.  
The numerical methods presented accurately and efficiently analyze the dynamic behavior of METE nanobeams. These results are significant for designing and optimizing smart nanostructures with customized properties for nanoelectronics and biotechnology.  
**Funding:** This research received no external funding.  
**Data Availability Statement:** The data presented in this study are available in the article.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# The Next Generation Platform as A Service: Composition and Deployment of Platforms and Services
###### Abstract  
The emergence of widespread cloudification and virtualisation promises increased flexibility, scalability, and programability for the deployment of services by Vertical Service Providers (VSPs). This cloudification also improves service and network management, reducing the Capital and Operational Expenses (CAPEX, OPEX). A truly cloud-native approach is essential, since 5G will provide a diverse range of services - many requiring stringent performance guarantees while maximising flexibility and agility despite the technological diversity. This paper proposes a workflow based on the principles of build-to-order, Build-Ship-Run, and automation; following the Next Generation Platform as a Service (NGPaaS) vision. Through the concept of Reusable Functional Blocks (RFBs), an enhancement to Virtual Network Functions, this methodology allows a VSP to deploy and manage platforms and services, agnostic to the underlying technologies, protocols, and APIs. To validate the proposed workflow, a use case is also presented herein, which illustrates both the deployment of the underlying platform by the Telco operator and of the services that run on top of it. In this use case, the NGPaaS operator facilitates a VSP to provide Virtual Network Function as a Service (VNFaaS) capabilities for its end customers.  
Keywords:5G; Cloud; Cloud-native; PaaS; NFV; SDN; Telco-grade; CORD +
Footnote †: journal:
## 3 Fortran Program Prediction and Validation  
[PERSON] et al. have verified the predictive ability of the model under isotropic compression conditions, and the predictive ability of the proposed model during a drying-wetting cycle will be verified in this paper. [PERSON] [29] carried out a number of constant mean net stress drying-wetting tests of Wuhan Zoayang expansive soil by using a computer-controlled triaxial stress-path testing system inherited from [PERSON] [30]. The triaxial cell is a Bishop and [PERSON] stress-path cell for testing up to 100 mm diameter cylindrical specimen. The change in suction is achieved by varying pore water pressure. Three sets of drying-wetting test data were selected for model validation. For test A, the constant mean net stress is \(\overline{p}=40\) kPa, and the suction path of the sample is 200 kPa\(\rightarrow\)10 kPa\(\rightarrow\)400 kPa\(\rightarrow\)200 kPa. For test B, the constant mean net stress is \(\overline{p}=70\) kPa, and the suction path of the sample is 200 kPa\(\rightarrow\)10 kPa\(\rightarrow\)350 kPa\(\rightarrow\)50 kPa. For test C, the constant mean net stress is \(\overline{p}=100\) kPa, and the suction path of the sample is 200 kPa\(\rightarrow\)10 kPa\(\rightarrow\)350 kPa\(\rightarrow\)50 kPa. The model parameters of Zaoyang expansive soil and the initial state parameters of the three sets of tests are listed in Tables 1 and 2.  
Figure 2 shows the comparison between the model predictions and the test data. The proposed model can reasonably predict the hydro-mechanical coupling characteristics of unsaturated soils for drying-wetting cycles. The specific volume of the soil gradually increases due to the decrease in the \(p^{*}\) in the soil during the wetting process, which results in elastic expansion deformation. However, the modified suction in the soil decreases, which results in yielding on the SD and causes the LC curve to move inward. The \(S_{\text{r}}\) increase rate increases. The modified suction in the soil changes without yielding on the SI curve during the drying process. The \(S_{\text{r}}\) change is elastic. The effective stress of the soil increases, and yielding occurs on the LC curve. The change rule of the specific volume during drying is more complex and different from that during wetting. The proposed model can reflect not only the influence of the liquid deformation on the soil skeleton deformation but also the influence of the soil deformation on the SWCC.
# Development of a Generic Numerical Transtibial Model for Limb-Prosthesis System Evaluation
## 4 Discussion
### Biomechanical Validation
The widespread use of silicone liners has only been introduced in recent years, resulting in lower pressure peaks. This is due to the features of silicone that help to alleviate contact pressure by flowing from high-pressure to low-pressure areas [8; 28]. Finally, the gait conditions reported in the literature were compared to the P5 load steps at the settling test force corresponding to gait conditions; both heel strike and push-off were evaluated. A note of caution is due here since the reported studies vary regarding the boundary conditions describing the gait cycle. The upper part of Figure 12 shows a wide range of peak contact pressure results, indicating different loading conditions. Theresults from our study for heel strike were 127 kPa and 128 kPa for the PTB and TSB sockets, respectively. A significantly higher maximum contact pressure was observed in the push-off condition of the P5 load step, specifically 192 kPa and 157 kPa for the PTB and TSB sockets, respectively. The numerical results indicate that the push-off instant is more intense and generates higher contact pressures. A limited number of studies from other authors report a wide span of peak pressures, starting at 70 kPa for PT and reaching a maximum of 300 kPa for PA. Similar to the single-leg case, older studies tend to produce a higher peak pressure because no silicone liner was used.
## 2 Literature Review
### Wavelet Threshold Denoising  
Traditional denoising methods, such as low-pass filter, Kalman filter and median filter, aim either at the time domain or the frequency domain. However, single-scale representations of signals are often inadequate when attempting to separate signals from noisy data. By combining the two scales, wavelet threshold denoising presents obvious superiority. According to the wavelet threshold denoising theory proposed by [PERSON], the optimal threshold should diminish the noise but preserve the signal as much as possible [25]. The traditional hard-threshold function exhibits some discontinuities and may be unstable or more sensitive to small changes in the data, while in soft thresholding the wavelet coefficients are reduced by a quantity equal to the threshold value, which will induce the deviation when the filtered wavelet coefficients is reconstructed [26]. Moreover, the threshold is fixed once determined and adaptability is weak during the denoising process. In order to overcome the disadvantages of the original threshold functions proposed by [PERSON], many adaptive denoising approaches have been elaborated by researchers. Improved solutions can be divided into two streams:the first on the improvements of threshold function and the other focus on searching optimal threshold through intelligent algorithms. The threshold function-based methods aim at establishing appropriate function with continuous derivative and selecting thresholds based on gradient descent algorithm. In [10], a new adaptive denoising function with continuous first and second order derivative is presented based on SURE model. In [27], an adaptive logarithmic wavelet threshold denoising function was proposed to select optimal threshold for each decomposition level. Relative to hard and soft functions, the proposed approach increased the signal-to-noise ratio by 44.2% and 27.9%, and decreased processing time by 37.6% and 38.5%, respectively. With the rapid development of artificial intelligent optimization algorithm, intelligent searching-based wavelet denoising approaches have been widely applied in recent years. In [14], a PSO-based image denoising method was proposed for learning the parameters of the adaptive thresholding function required for optimum performance. [PERSON] et al. adopted an adaptive denoising solution for partial discharge signals based on threshold function and genetic algorithm (GA), and the result presents significantly smaller waveform distortion and magnitude errors than the [PERSON]'s soft threshold estimation [15]. In order to eliminate noise components of satellite images, some stochastic global optimization techniques such as Cuckoo Search (CS) algorithm, artificial bee colony (ABC), and PSO as well as their different variants have been exploited for learning the parameters of adaptive thresholding function in [28].
## 3 Feasibility Analysis of IoT Architecture Utilizing LoRa Communications on Mars
### Analysis of the Maximum Message Capacity of Satellites  
This analysis focuses on evaluating the capacity of satellites to receive messages from IoT nodes and, consequently, estimating the number of IoT nodes that could be deployed on the surface of Mars according to the proposed architecture. The communication capacity of each satellite is calculated using LoRa technology, considering the data transmission speed. To conduct this analysis, the theoretical maximum message capacity will be calculated for the satellite's orbital period, determined by [PERSON]'s Third Law [47].  
Also, the transmission rate must be considered based on the different spreading factors (SFs). From the SFs, the transmission data rate from the IoT nodes to the satellites in orbit can be determined and, thus, the number of messages each satellite can receive in its orbital period. The LoRa protocol uses various SFs to determine the type of communication, which determines the spectral efficiency of the transmission and affects the data rate [48].  
The different available SFs have varying transmission rates that impact the message capacity each satellite can manage during each orbital period. By evaluating these rates, it is possible to determine the theoretical number of messages each satellite can receive and the volume of IoT nodes that can be deployed based on the data rates and package duration associated with each SF [49].
## 2 Fine-Timestamp Maker Design
### Architecture and Circuit Design
After clk_0 synchronizes the RO-RST signal, the end of the current conversion (Eoc) signal is also sent out. In this process, the eight-bit ultra-fine counter records the number of oscillation cycles continuously, and its result also indicates the ultra-fine time in units of the period difference between the oscillation signal and clk_0. Taking the case shown in Figure 1b as an example, the acceleration module indicates that the rising edge of the oscillation signal is in the second of the four regions of clk_0. The oscillation frequency is slightly faster than that of clk_0. Therefore, when the rising edge of the oscillation signal becomes aligned with the first region of clk_0 after a few clock periods, the coincidence circuit immediately sends out the RO-RST signal to stop the RO from initiating oscillation and stop the ultra-fine counter from counting. Therefore, the delay jitter accumulations could be controlled as early as possible. The coincidence circuit then sends an Eoc signal to the time assembler, which means the fine timestamp is ready for output, i.e., the second time interpolation is finished. The specific implementation of the coincidence circuit is shown in Figure 5. Where the rising edge of the oscillation signal samples each phase-shifted clock, the successive sampling results of the two cascaded flip-flops are output through an XOR gate (S1-S4). When the rising edge of the oscillation signal moves from one region of clk_0 to another, as shown in Figure 1b, we can detect the alignment between the oscillation rising edge and the region boundary by connecting S1-S4 with a four-input OR gate. Two flip-flops, FF0 and FF1, and one AND gate prevents the error that occurs when the RO-RST directly becomes one for the first sampling. The RO-RST signal is output as the Eoc signal after being synchronized by the system clock clk_0. Figure 4: The overall structure of the Vernier-measuring module.