esa-sceva/satcom-chunk-collection huggingface dataset:
# IoT System for Detecting the Condition of Rotating Machines Based on Acoustic Signals
## 3 Architecture of the Proposed System  
The system we present in this paper is designed to autonomously perform an estimation of the state of the rotary machine and provide the result in a convenient way to the various stakeholders. The schematic diagram of this system is shown in Figure 7. A microphone, connected to a microprocessor platform for acquisition and processing, captures the acoustic signal produced by a rotary machine. After the recording of the acoustic signal sample is completed, its processing is performed (as explained in the previous section) in order to estimate the condition of the observed machine. The obtained result is delivered to the users.  
Figure 5: Graphical user interface of FASTER configuration software.  
Figure 6: Configuration software with loaded training signals (**left**) and an example of training results (**right**).  
There are several interested parties for information on the current state of the rotary machine. First, it is the staff in charge of maintaining the machines. However, the management of the organization may also be interested in order to better organize and plan further activities and costs of the company. That is why we decided to send the data on the state of the machine to the cloud platform immediately after obtaining the results. In this way, we ensure the immediate availability of information to all stakeholders, regardless of where they are currently located. It is enough for them to have an Internet access and a suitable device (computer, tablet, mobile phone...) to access the cloud platform and stored data.  
For the needs of this prototype, we used a cloud platform developed at the University of Montenegro, which is located on its hosts [31]. In addition to enabling data storage, this platform also enables the visualization of stored data, so that it is easier to follow the trends in the behavior of the observed machine. Usage of this platform is currently completely free. It is just necessary to register with a valid email address.  
However, the data transfer between the estimating device located on the observed machine and the cloud platform is not always completely reliable. Namely, it is possible that the Internet access service provider does not work during some period. In addition, interruption of the mobile operator signal through which we establish a GPRS connection is possible. Finally, there may be a problem with the GPRS modem or the SIM card. For this reason, information about the results of signal processing and estimation of the machine state is displayed on the LCD screen, so that the operator instantly has information about the result. Moreover, the recording is stored on the SD memory card of the device, so it is possible to repeat the process of audio signal processing later and get an estimation of the machine state at the time of recording.
## 1 Introduction
However, machine vision is not suitable for assessing internal quality attributes, whether chemical or physical, and it also is not very effective for defect detection, due to the lack of sufficient spectral information. Hyperspectral imaging has emerged as a powerful inspection tool in the agricultural and food domain since the late 1990s [10,11]. A hyperspectral imaging system produces a two-dimensional (2-D) spatial matrix of vectors, each of which represents a spectrum, typically in the wavelengths ranging from VIS to NIR, thus forming a three-dimensional (3-D) image dataset, known as _hypercube_. The technology integrates or bridges spectroscopy and imaging to acquire both spectral and spatial information from a product simultaneously. It can thus provide a more effective means for detection of chemical compositions as well as external or internal quality attributes in the spatial dimensions. Consequently, research on hyperspectral imaging for food quality and safety inspection has expanded tremendously over the past decade [12, 13, 14, 15]. With large volumes of image data, often covering over 100 or even 1000 wavebands, hyperspectral imaging is limited by the speed of image acquisition, processing and analysis. Numerous studies in recent years have thus been focused on determining a few most effective wavebands by using hyperspectral imaging, so that they can be implemented in a multispectral imaging configuration [16, 17, 18, 19, 20]. Researchers at the U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS) successfully developed online hyperspectral imaging systems that are implemented in multispectral imaging mode for safety inspection of poultry carcass [21, 22, 23]. With the rapid evolution in both hardware and software, hyperspectral imaging is expected to be increasingly used by the food and agricultural industries for quality and safety inspection of food and agricultural products in the coming years. Over the last 15 years, our group has been actively engaged in the development and application of hyperspectral imaging technology for property and quality evaluation of horticultural and food products. In addition to conventional reflectance imaging mode, we have developed several innovative hyperspectral imaging-based techniques or platforms, including _spectral scattering_ for evaluation of firmness and soluble solids content (SSC) [24; 25], _full transmittance_ for internal defect detection [26; 27], _integrated reflectance and transmittance_ for detecting surface and internal quality or defect [28; 29], and _spatially-resolved spectroscopy_ for measuring the optical absorption and scattering properties of fruits, vegetables and other food products [30; 31]. In the following sections, an overview will be first provided of hyperspectral imaging configurations and common sensing modes, followed by a review on each of these hyperspectral imaging-based techniques. The basic principle, instrumentation and data processing methods for each technique are first introduced, followed with applications in food quality assessment.
## 4 Conclusions  
The present study performed a numerical analysis of the HNS propagation characteristics based on CFD simulations under limited scenarios. Using the CFD results, it involves developing a new metamodel for predicting the key parameters, which are newly introduced, together with the Kriging model. The following conclusions are drawn:  
1. From the CFD results, it was found that the streamwise propagation velocity increases linearly with the current velocity because the advection effect is dominant, whereas the transverse propagation velocity decreases. Furthermore, the crack position did not cause a large difference in the streamwise propagation velocity.
2. As the current velocity increases, the averaged HNS mass fraction at sea level decreases because the HNS is actively transported by advection. In the case of the low HNS density, the buoyancy effect becomes stronger and the propagation in the radial direction is increased. Thus, the area occupied by spilled HNS increases, and the averaged HNS mass fraction decreases. For side cracks, the averaged HNS mass fraction decreases because the spilled HNS has lower area.
3. The metamodel was developed using the Kriging model for the key parameters, which were newly defined for the HNS propagation analysis. The hidden point tests for evaluation show that the mean error of the streamwise propagation velocity is 8.48%, the transverse propagation velocity is 5.38%, and the averaged HNS mass fraction is 6.71%, approximately. The current model is the first version developed under the restricted scenario. Thus, it could be updated continuously by adding further CFD results under various scenario.  
Conceptualization, S.H.L. and M.L.; investigation M.K.K., C.H.J., and M.L.; methodology, M.K.K. and C.H.J.; supervision, S.H.L.; writing of the original draft, M.K.K.  
This research was supported by the project titled 'Development of Management Technology for HNS Accident', funded by the Ministry of Seas and Fisheries, Korea.  
The authors declare no conflicts of interest.
## 4 Discussion
### Effects of Oxygen Tension on the Expression of Collagen Type 1 and Runx2 by iPS Cells  
The mRNA expression level of collagen type 1 in EBs on Day 10 was significantly suppressed in the hypoxia group compared with the normoxia group, and was significantly stimulated in the hyperoxia group. The mRNA expression level of Runx2 in EBs on Day 10 showed a similar tendency to the expression of collagen type 1 mRNA on Day 10. These results suggest that EB differentiation under a hypoxia environment was suppressed. The mRNA expression levels of collagen type 1 and Runx2 in OGCs on Day 26 showed a similar result, and the differentiation of OGCs from EBs was more aggravated. In addition, hyperoxia promoted an increase in EBs.  
Hypoxia conditions (2% O\({}_{2}\)) decreased the expression of Runx2 in MG63 cells, which are human osteoblast-like cells [13]. [PERSON] et al. reported that when osteoblast-enriched cultures from fetal rat calvariae were exposed to hyperoxia (90% O\({}_{2}\)) or hypoxia (10% O\({}_{2}\)), the levels of alkaline phosphatase and collagen were decreased in the hypoxia environment and the differentiation of osteoblasts was suppressed [14]. In addition, hypoxia conditions (3% O\({}_{2}\)) have been shown to regulate the osteoblast differentiation of mouse ES cells [29]. It was reported that the hypoxia state reinforces the pluripotency of iPS cells [30; 31; 32]. Furthermore, hypoxia inducible factor (HIF) is expressed when iPS cells are exposed to a hypoxia environment, and contributes to the control of stemness by transcription network under hypoxia conditions [15]. The expression of HIF-1\(\alpha\) plays an important role in regulating the maturation of bone cells and calcification [33]. Hypoxia conditions promote cartilage differentiation from MSCs [34].  
The classification of pluripotent stem cells into naive and primed populations was introduced some time ago [35]. The naive population is equivalent to a preimplantation blast cyst, and the primed population is equivalent to an embryo after implantation [36]. Mouse ES/iPS cells were classified as a naive population. Glycolytic pathway metabolism is important to maintain pluripotency, but naive cells use oxidative phosphorylation [27; 37; 38]. Suppression of the glycolytic pathway and activation of oxidative phosphorylation were caused by a differentiation experiment of ES/iPS cells without determination of differentiation [32; 39]. The shift to a similar metabolic pathway is probably caused by hyperoxia conditions. For this reason, it is thought that hyperoxia conditions alter metabolism and promote differentiation.  
There are clear differences between the characteristics of miPS cells and hiPS cells derived under standard conditions [40]. Since mouse iPS cells were used in this experiment, these results cannot be directly applied to human iPS cells. However, since both mouse and human iPS cells have similar properties, such as enhanced pluripotency under the state of hypoxia state [30; 31; 32], it is possible that the same results as in this experiment can be expected for hiPS cells.
# Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone
## 6 Conclusion and Discussion
More importantly, the time required for high positioning accuracy of our work is much less, which means that our work is more in line with the actual application scenarios of smart phones. Unfortunately, due to the small number of Galileo satellites and GPS satellites with L5 signals observed, we have not been able to effectively use L5/E5 frequency data. Previous studies show that the L5/E5 frequency data quality is significantly better than L1/E1 [11; 12; 13], and the combination of L1/E1 and L5/E5 can effectively eliminate the ionospheric delay error. How to effectively use L5/E5 frequency data will be a focus of our next work. Besides this, differential positioning, especially RTK positioning, can also effectively improve smartphone positioning performance [11; 12]. For this method, the influence on positioning results caused by the phenomenon we found are not clear, which needs further analyses and discussions. We are trying to develop a positioning APP that uses the double clock bias PPP strategy. The preliminary results show that the method has practical effects, and for ordinary single frequency smartphones, their positioning performance can be improved too. A mobile phone positioning app with high precision can effectively improve the user experience of public and may be applied to some professional work with low precision requirements, such as external annotation and cadastral survey. However, it can be foreseen that the GNSS chip in the mobile phone is developing rapidly and the updates of Android operating system will also affect the quality of smartphone raw GNSS observations. Whether the future smartphones have the phenomenon that the differences of pseudorange and carrier phase observations are not fixed needs to be determined according to specific analysis. Conceptualization, C.G. and B.C. ; Methodology, B.C. and P.S. ; Software, B.C. and Y.L. ; Validation, B.C. and Y.L. ; Writing--original draft preparation, B.C. ; Writing--review and editing, B.C. and C.G. This research was supported by the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20171353). The authors declare no conflict of interest.
# Evaluation of Positioning Accuracy of Smartphones under Different Canopy Openness
## 4 Discussion  
### Number of Observation Satellites and Signal Quality of GNSS Devices in a Forest Environment  
The quality of satellite signals received by GNSS devices in a forest environment is affected by many factors, the most important of which are canopy openness and terrain [45; 46]. Due to the influence of canopy openness [46; 47], canopy coverage [47], and tree height [48], the more serious the occlusion, the less the number of visible satellites [49]. It can be seen that the number of satellites in previous studies shows a law of increasing with the expansion of the observation site [50]. However, this is not the case in the forest environment. This may be because the canopy is not completely closed and the satellite signal can penetrate the gap between the canopy to reach the receiver during the movement so that some satellite signals will be recorded by the receiver intermittently during the observation process, resulting in no significant change in the number of visible satellites under different canopy-openness conditions (\(p\) > 0.05). When the number of visible satellites is small, the receiver can also track more satellites. When the canopy openness is large, the  
Figure 13: Comparison of positioning accuracy between dual-frequency smartphone P50 and survey-grade receiver iRTK2 in SPP model (**A**); comparison of positioning accuracy between dual-frequency smartphone P50 and survey-grade receiver iRTK2 in PPP model (**B**).  
number of satellites tracked is not necessarily large [51]. However, from the perspective of actual observation results, some satellites account for less than 20% of the total observation time when the canopy openness is low. These satellite signals have a very limited role in device positioning.  
This study found a significant positive correlation between canopy openness and C/N0 of each device in a forest environment (_p_ < 0.01). With the increase in canopy openness, the satellite C/N0 increased linearly and evenly. When the canopy openness is more than 0.7, the increase in canopy openness significantly promoted the C/N0. This phenomenon is significantly different from the measurement results in the leafy season [44]. In the case of the leaves season, there is a threshold value for the promotion effect of canopy openness on the C/N0 and the C/N0 increases exponentially with the increase in canopy openness. When the openness is below 0.55, increasing the openness can make the C/N0 increase rapidly. In addition, ANOVA of C/N0 and pseudo-range single-point positioning accuracy shows that even in the most unfavorable environment (the canopy openness is between 0.1 and 0.3), the C/N0 is generally higher than 41.16 dBHz. In contrast, the C/N0 of smartphones is generally lower than 31.89 dBHz, even with the high-canopy openness (0.7-0.9).
## 2 Airborne Instruments and Interface with the ATR-42
### Antenna and Cable Losses
#### 2.1.2.1 Sensitivity  
The radiometric sensitivity (or radiometric resolution), referred to as _NEDT_, is the minimum detectable change in the radiometric antenna temperature of the observed scene. This sensitivity is directly related to the rapid fluctuations of the measured radiometric temperature. The radiometric sensitivity, related to the thermal noise _NEDT_ of the radiometer, is given by:  
\[NEDT=\frac{T_{in}+T_{R}}{\sqrt{\tau B}} \tag{2}\]  
where \(T_{in}\) is the temperature at the input of the receiver, \(T_{R}\) is the noise temperature of the receiver, \(\tau\) the integration time and \(B\) the bandwidth of the receiver. In Figure 3, we illustrate the theoretical sensitivity and the CAROLS sensitivity measured in the laboratory, as a function of integration time. It can be seen that for an integration time longer than 300 ms, the sensitivity is better than 0.1 K.
# Audlet Filter Banks: A Versatile Analysis/Synthesis Framework Using Auditory Frequency Scales
## 1 Introduction
Because nonlinear systems may complicate the inversion of the signal processing chain (e.g., [35; 36]), linear approximations of the auditory system are often preferred in audio applications. In particular, gammatone filters approximate well the auditory periphery at low to moderate sound pressure levels [37; 38] and are easy to implement as FIR or IIR filters [32; 39; 40; 41; 42; 43]. Various analysis-synthesis systems based on gammatone FBs have been proposed for the purpose of audio applications (e.g., [35; 39; 40; 44]). However, these systems do not satisfy all requirements of audio applications as, even at high redundancies, they only achieve a reconstruction error described as \"barely audible\". This error becomes clearly audible at low redundancies. In other words, these systems do not achieve perfect reconstruction. To our knowledge, a general recipe for constructing a gammatone FB with perfect reconstruction at redundancies close to and higher than one has not been published yet. In this article, we describe a general recipe for constructing an analysis-synthesis system using a non-uniform oversampled FB with filters distributed on an arbitrary auditory frequency scale, enabling perfect reconstruction at arbitrary redundancies. The resulting framework is named \"_Audlet_\" for _aud_io processing and _aud_itory motivation. The proposed approach follows the theoretical foundation of non-stationary Gabor frames [20; 45] and their application to TF transforms with a variable TF resolution [46; 47; 48]. This report extends the work reported in [20] (Section 5.1) by providing a full theoretical and practical development of the Audlet. The manuscript is organized as follows. The next section briefly recalls the basics of non-uniform FBs, frames, and auditory frequency scales. Section 3 describes the theoretical construction of the Audlet framework. The practical implementation issues are discussed in Section 4 and Section 5 evaluates important properties and capabilities of the framework.
# Negative Poisson's Ratio Lattice Structure with Chiral and Re-Entrant Properties
## 2 Structural Design and Methods
### Experimental Tests  
To investigate the negative Poisson's ratio phenomenon in the window grill structure, we opted for a specific structure with a length ratio (\(\mu\)/\(\beta\)) of 2.367 and a deflection angle (\(\theta\)) of 35 for both sample printing and experimental analysis. The sample had a longitudinal arrangement of 6 unit cells and a lateral arrangement of 3 unit cells, as depicted in Figure 6a. Additionally, the thickness of the chiral cross or re-entrant circle was \(t\) = 3 mm and the angle of inclination was \(\theta\) = 35\({}^{\circ}\). The thickness of the lattice metamaterial measured 10 mm.  
The experiment utilized a CMT410G microcomputer-controlled electronic universal testing machine and an OS6030-81 SUM high-speed camera with a resolution of 5 million pixels. The experimental procedure is depicted in Figure 6b.  
First, the upper and lower fixtures were utilized to securely fasten the two ends of the specimen, as depicted in the section highlighted in Figure 6a. The distance between the upper and lower fixtures were adjusted in accordance with the standard GB/T 1040-79. The proper clamping of the test specimen for the window structure was of the utmost importance. It was imperative to maintain the vertical orienta  
Figure 4: The principle of the SLA printing process (**a**) and the 3D printer (**b**).  
Figure 5: The dog bone samples for the tensile test (**a**) and the stress–strain curve of specimens obtained by tensile test (**b**).  
prevent any occurrence of bending deformation during the testing procedure. Proper maintenance of the distance between the fixture and the end of the specimen was crucial to prevent fracture at the end caused by concentrated local stress.  
Secondly, in this experimental setup, the lower end of the test piece remained fixed, while the upper end was subjected to a tensile force. The tensile speed for the applied load was set at 2 mm/min. The test was terminated at various points when the tensile load reached \(600,700,800,900,1000,1100\), and \(1200\) N.  
Thirdly, the utilization of a high-speed camera enabled the capturing of images at a frequency of 0.2 s during the static tensile experiment. According to the Saint-Venant principle, the stress experienced by an elastomer located far from a load action zone is solely determined by the combined force acting on it.  
To isolate the impact of the load on the NPR, we specifically chose the central region of the specimen as the designated calculation area. The displacement alterations of four distinct points (A, B, C, and D) as depicted in Figure 6a were measured. The NPR could be determined by utilizing formulas 3 to 5.