esa-sceva/satcom-chunk-collection huggingface dataset:
# Metabolic Periparturient Diseases in Small Ruminants: An Update
## 3 Hypocalcemia
### Epidemiology  
Hypocalcemia occurs at specific periods, such as peripartum, due to the demand for calcium by fetuses or milk production, during which serum and interstitial replacement is insufficient [102]. Normal serum calcium (Ca) levels range from around 2.2 to 2.9 mmol/L (8.9-11.7 mg/dL in cattle), 2.8-3.2 mmol/L for sheep and 2.2-3.05 mmol/L for goats) [54; 60]. Its diffusing ionizable fraction (Ca\({}^{++}\)) represents about half of the total calcium in serum. Serum levels of Ca\({}^{++}\) are affected by the acid-base balance to diffuse into different tissues, where it is essential to promote muscle contraction, among numerous other functions. In does, similar to cows and in contrast to ewes, hypocalcemia appears mainly after parturition (up to 8 weeks). The fetolacental mass is larger and the udder is smaller in pregnant ewes than in cows, mainly in multiple pregnancies [103]. Hypocalcemia is more likely to occur in does with high production levels or multiple fetuses, in which calcium concentration in milk is approximately 32.5 mmol/L (130 mg/dL) [60; 104]. However, similar to ewes,hypocalcemia can also appear in does during the _ante-partum_ from approximately 80 days of gestation, with greater demand for calcium due to fetal skeleton mineralization (1-3 weeks) and later to colostrum [105] during the first week [106].  
The clinical incidence of hypocalcemia is generally less than 5%. However, severe outbreaks may involve up to 30% of the flock [107; 106]. Mortality can reach 90% of untreated animals [106]. Older animals (4-6 years) are considered more susceptible due to their lower capacity to regulate intestinal absorption and bone mobilization of calcium [108; 109]. [PERSON] et al. [110] reported a total prevalence of 24.2% of subclinical hypocalcemia in Saanen and Beetal dairy goats. In this last study, hypocalcemia was observed in 6.8% and 39.4% of does carrying singletons and multiple fetuses, respectively. Other relevant risk factors associated with the most susceptible periods precipitate the occurrence of the disease, as reported in Table 5.
# An Accurate GNSS Spoofing Detection Method Based on Multiscale Eye Diagrams
## 3 Spoofing Detection Method
### MSC-MMP Performance Analysis
The Canny algorithm achieved a F score of 0.898, whereas the Log and Zero Crossing algorithms both had a score of 0.852. Due to their lower recall rates, these algorithms were less effective overall compared to the MSC-MMP algorithm. Overall, the MSC-MMP algorithm performed best across the three key performance metrics and was therefore chosen for edge detection in eye diagrams.
## 2 Numerical Analysis of the Erosion Model
### Validation of the Numerical Model Validity
#### 2.4.2 Comparison of Numerical Simulation Erosion Models  
The Zhang [17] erosion model as well as [PERSON]'s wall bounce coefficients were used for simulation calculations. The maximum erosion rate cloud obtained with numerical simulation based on the experimental working condition parameters in Table 4 is shown in Figure 3.  
As can be seen from Figure 3, the maximum erosion rate of the elbow is 1.45 \(\times\) 10\({}^{-8}\) kg/(m\({}^{2}\cdot\)s). The maximum erosion location is at the outlet end of the 90\({}^{\circ}\) elbow and the straight pipe connection. From Figure 4, it can be seen that the maximum erosion thickness is 21.9 \(\times\) 10\({}^{-11}\) m/s, and the erosion wear rate obtained from the simulation model verification in this paper is 0.254 nm/s.  
The value of the error between the simulation results and the experimental data in this paper is 9.59%, which is smaller than the error between the numerical simulation and the experiment in the literature. This proves that the numerical model in this paper is closer to  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Experimental Data** & **Simulation Data from the Literature** & **Experimental Data** & **Simulation Data** \\ \hline Numerical (nm/s) & 0.219 & 0.254 & 0.219 & 0.240 \\ Inaccuracy & & 15.98\% & & 9.59\% \\ \hline \hline \end{tabular}
\end{table}
Table 4: Experimental data and numerical simulation data.  
Figure 4: Experimental diagram of erosion and wear.  
Figure 3: Plot of the erosion rate of 90\({}^{\circ}\) bends.  
the experimental results. The existence of the error may be because the liquid phase flow in the experimental process is more complex, and the mutual collision between the particles and the impact of the angle of the particles are different. However, the overall error is less than 10%, which is credible.
# Reliable Integrity Preservation Analysis of Video Contents with Support of Blockchain Systems
## 3 Proposed Scheme
### Analyzing Integrity of Original Video Files
The rest of the software modules, such as those extracting the signature from the input file and displaying the ongoing analysis results, are constructed as a stand-alone tool working on a local computer, called the front-end server. The proposed mechanism calculates the hash value of the whole source code in the front-end server and compares it with the hash value stored in the blockchain system. In this structure, whenever the source code in the front-end server is updated, its hash value is stored with its time stamp separately in the blockchain system. Then, it can be checked to see which update version the source codes in the front-end server belong to. Figure 4: Detailed structure of integrity analysis mechanism. Figure 3: Procedure to check the source code reliability of the proposed scheme.
###### Abstract  
Collisions between pieces of equipment as well as between equipment and workers frequently occur inside underground tunnels, owing to limited visibility coupled with a confined work environment. To address this problem, a Bluetooth-beacon-based proximity warning system (PWS) capable of preventing collisions inside underground tunnels has been proposed. The proposed PWS receives signals from Bluetooth beacons attached to bodies of mine workers and/or their equipment via smartphones installed in vehicles, thereby providing drivers with primary (caution) and secondary (warning) alerts in stages, based on the intensity of received signals. After identifying suitable received signal strength indicator (RSSI) threshold values corresponding to the caution and warning zones, a field test was performed inside an underground tunnel based on results obtained from a preliminary experiment. Using collective results obtained during 50 experimental repetitions, the accuracies of the first and second alert occurrences in the caution and warning zones were determined to be 93% and 95%, respectively. The proposed Bluetooth-beacon-based PWS was demonstrated to be effective for preventing collisions inside underground tunnels. In addition, the proposed system is relatively inexpensive, and its functions can easily be extended via the use of smartphone applications.  
underground tunnels; Bluetooth beacon; smartphone; safety management; App Inventor 1
# An Intelligent Event-Sentiment-Based Daily Foreign Exchange Rate Forecasting System
## 4 Results and Discussion
### Descriptive Statistic  
Table 3 shows the descriptive statistics of all the datasets. The mean value of the exchange rate was 7.769, 98.257, and 1.536 for Hong Kong, Pakistan, and the UK, respectively. Similarly, their standard deviation was 0.0261, 14.740, and 0.170. Since the Jarque Bera (JB) test statistic is significant, the distribution of all the variables is non-normal.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variables/Countries** & **Hong Kong** & **Pakistan** & **UK** \\ \hline Exchange rate, crude oil prices, gold price index. & From 26 April 2008 to 31 May 2018 2123 observations & From 29 March 2008 2132 observations & From 2 January 2008 to 31 January 2019 28 November 2018 2633 observations \\ \hline \hline \end{tabular}
\end{table}
Table 1: Data description.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Country** & **Local Events** & **Number of Tweets** & **Global Event** & **Number of Tweets** \\ \hline Hong Kong & Hong Kong Protest (2014) & 1,188,372 & US Election 2012 & 1,740,258 \\ Pakistan & Lahore Blast 2016 & 1,149,253 & US Election 2012 & 1,740,258 \\ UK & Brexit & 1,826,290 & US Election 2012 & 1,740,258 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Dataset details along with local and global events for each country.  
We tested the problem of stationarity by using the ADF unit root test. The augmented Dickey-Fuller test uses the following hypothesis.  
**Hypothesis 1.**_Unit root exists._  
**Hypothesis 2.**_No unit root exists._  
Table 4 shows the results of the ADF unit root test. We found all the data series to be stationary at first difference except gold price index, which was stationary at level.
## 3 Materials and Methods  
### Position Algorithm Calculation  
This article proposes a received signal strength indication (RSSI)-weighted fusion algorithm (WF). Based on the data that can be obtained in the experiment, the algorithm selects the trilateral positioning method and the least-squares positioning method, together with the dead reckoning positioning method and the two stations ranging plane positioning method from the classic ranging positioning methods; the centroid positioning method is selected from the classic non-ranging positioning methods. Then, the weights based on error distance are assigned to the positioning results of trilateral positioning, least-squares positioning, and centroid positioning to constitute a fusion positioning algorithm.  
The algorithm is suitable for vehicle wireless positioning in a vehicle-road collaborative environment. The antennas arranged on the roadside base station and the vehicle are used to send and receive signals to obtain positioning data. The algorithm is less interfered with by signal transmission and can compensate for GPS positioning and trilateral positioning due to the positioning failure caused by unstable vehicle environment and location conditions. The algorithm is a phased experimental result of this research, and the purpose of the experiment is to verify the positioning accuracy of the algorithm. Therefore, the experiment assumes that the GPS coordinates are real coordinates to verify the accuracy of the algorithm. If it is applied in the actual urban traffic state recognition, it is necessary to conduct a more detailed study on the weight calculation in the algorithm.  
The calculation process of the fusion location algorithm is as follows.
## 4 New TIRA System Design
### System Monitoring  
Monitoring system health and status permanently is important to maintain high availability. It further gives crucial information in case of repair and maintenance. This includes system health parameters such as device temperature, voltages and currents, application parameters like encoder values of the rotating axes, set and error values of the antenna controller and meteorological measurements like air temperature/humidity and liquid water content to estimate the signal propagation parameters like the zenith tropospheric delay.  
Every module reports environmental and system parameters via a network to a time series database (InfluxDB, open-source, MIT license, [[https://www.influxdata.com/accessed](https://www.influxdata.com/accessed)]([https://www.influxdata.com/accessed](https://www.influxdata.com/accessed)) on 29 October 2024). This solution enables us to analyze a high-rate time series of measurements with high performance and presents the result on a configurable dashboard system (Grafana, open-source, AGPLv3 license, [[https://grafana.com/](https://grafana.com/)]([https://grafana.com/](https://grafana.com/)), accessed on 29 October 2024)  in real time. Collecting a high-rate time series requires high storage capacity and slows down the querying and processing of such kinds of data. Time series databases are designed to overcome this drawback by rule-based aggregation of the high-rate data using statistical downsampling methods and fast compression algorithms to reduce data size and query time.  
Alongside MBSE, we also aim to develop a comprehensive digital twin of our radar system. The basic concepts are shown in Figure 17 by the example of the antenna's positional control system. The digital twin can be based on physical models with parameters estimated from monitoring data or even black-box models. New positional controller designs, for example, can be tested and optimized on the digital twin, before they are implemented on the real system. Having a complete system model, new methods of space observation can be developed with the digital twin before applying them on the real system.  
Figure 16: Overview of the ARCADIA method for MBSE.  
To not be tied to a specific modeling tool, the open Functional Mock-up Interface (FMI) standard is used to integrate simulation models into the system as illustrated in Figure 18. Such models can be exported from both open-source and commercial modeling tools.
# DataMatrix Code Recognition Method Based on Coarse Positioning of Images
## 4 Binarization Method Based on Grayscale Change Trend
### Gray Change Trend  
By constructing a mask image [41] and performing an AND operation with each pixel of the DM code image, the target image can be obtained and used to acquire the target grid. The length and width of the target grid are reduced by two pixels in turn for iterative division. The unit pixel gray value of each divided grid is calculated to obtain the gray change trend from the periphery to the center, as shown in Figure 10, where the numbers 1-12 on the first subgraph of Figure 10 represent the row and column indices for locating  
Figure 9: Adaptive sampling grid division diagram: (**a**) adaptive sampling grid division diagram of Figure 4a; (**b**) adaptive sampling grid division diagram of Figure 6a.  
specific sub-regions, which are used to analyze grayscale variation trends. The pseudocode of this module is shown in Algorithm 1, and its computational complexity is shown in Table 1, where \(L\) is the initial size of the grid, \(x\) is the number of grids, \(p\) is the total number of pixels in the image, and \(t\) is the number of gray values per grid.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Algorithm 1.** Iterative division of the grid \\ \hline \hline
**Input:** A list of grids _GPL_ that each contains the four corner coordinates of a grid after partitioning, a binarized black-and-white image _BI_. \\
**Output:** A list of the grayscale distribution trends _GVLA_ for each grid in the grid list. \\
1: Initialize _GVLA_ as an empty list \\
2: For each _grid_points_ in _GPL_: \\
3: Initialize an empty _list_ \\
4: Get _grid_length_ and _grid_width_ from _grid_points_ \\
5: While _grid_length_ > 2 and _grid_width_ > 2: \\
6: Create an empty _mask_ of the same size as _BI_ \\
7: Fill _grid_points_ region in the _mask_ with value 255 \\
8: Compute _gray_value_ = mean of pixels in _BI_ inside the _mask_ \\
9: Append _gray_value_ to _list_ \\
10: If _grid_length_ > 2 and _grid_width_ > 2: \\
11: Decrease _grid_length_ and _grid_width_ by 2 \\
12: Else If _grid_length_\(\leq 2<\)_grid_width_: \\
13: Decrease _grid_width_ by 2 \\
14: Else: \\
15: Decrease _grid_length_ by 2 \\
16: Update _grid_points_ by shifting corners inward \\
17: End While \\
18: Append _list_ to _GVLA_ \\
19: End For \\
20: Return _GVLA_ \\ \hline \hline \end{tabular}
\end{table}
Table 1: The computational complexity of Algorithm 1.  
Figure 10: Grayscale change trend of partial grid.
## 5 Communication Protocol  
The first fundamental step for two devices to communicate securely using wireless communication with this protocol is to have synchronized initial conditions for the chaotic equations. If possible, the best approach to execute this is to synchronize it through a physical connection, as it is the most secure communication method. An alternative is to have these variables already be defined during the manufacturing process. Also, this synchronization applies to the case of the Table LookUp of the encryption unit. The device then starts with a communication request. This request identifies the sender and asks to receive the seed to start the encrypted communication. There is no threat in this step, as even if through spoofing, a third party receiving the seed from the asked device would not be able to establish a secure communication due to the lack of the initial conditions of the chaotic system. Afterwards, the second device generates a seed with its internal algorithm and sends it to the other end. When both devices have the shared seed, they can both use their implemented chaotic system to generate the same pseudo-random key. Therefore, a secure communication can be established. This process will protect the IMDs as it will ensure an encrypted communication, at the same time, the threat of achieving the encryption key by an external third-party is diminished. The devices have individual systems to generate this key, while the process itself has a low cost in the memory and computation process. This prevents the devices from sharing the key wirelessly and insecurely, and also can be programmed to change the encryption key at any needed time. The exchanged messages will include in their segments a Hash [34] segment (Figure 8) that can be simply generated using, for instance, a cyclic redundancy check algorithm [35].  
Figure 7: Scheme of the blockCipher Operation in both (**a**) Encryption and (**b**) Decryption Mode.  
This Hash ensures the integrity of the exchanged message, thus guaranteeing that the message is not modified and the encryption key used is the same one on both ends. The seed is designed to expire. Therefore, there will be a periodic update of the seed. This expiration period will depend mainly on the system, to be a trade-off between performance and security. When the seed expires, the device should request again from the system a seed to be able to maintain the communication. This constant change is resource-friendly regarding the IMD capacities. Also, it ensures that an external party cannot uncover it for two main reasons. First, only one input is being communicated publicly. Second, avoiding the use of the same encryption key will prevent an attacker from analyzing the wireless communication statistically and concluding the possibilities of the key to exploit them. This is where the use of a low dimensional chaotic system is beneficial.
## 6 Application of Algorithm to Various Scenarios for Fault Identification: Case Studies
### Effect of Fault Location
#### 6.1.1 Fault on Bus 652  
All the types of faults were simulated on node 652. This node was considered because the line between this node and node 650 (where currents are recorded) consists of hybrid combination of the UG cable and OH lines. The results for phase-A to ground fault are detailed in Figure 9. WD-index corresponding to the phase-A has a high magnitude at the moment of fault incidence, as depicted in Figure 9b, whereas the magnitude of this index corresponding to the phases-B & C is low. Figure 9c illustrates that ALN-index has a high magnitude corresponding to all the phases due to fault incidence. Figure 9d illustrates that the fault index corresponding to faulty phase (phase-A) is high compared to the threshold, whereas this FI corresponding to healthy phases (phases-B & C) has a low magnitude compared to the threshold. Hence, the algorithm effectively detects the AG fault and also identifies the nature of the phases. It is also established that the algorithm is effective in the identification of faults on a hybrid combination of lines consisting of the UG cable and OH line sections.  
Figure 9: Identification of a phase-A to ground fault and incident on node 652 of the test system (**a**) Current waveform (**b**) WD-index (**c**) ALN-index (**d**) Fault index.
# Rare Earth Elements Uptake by Synthetic Polymeric and Cellulose-Based Materials: A Review
## 8 Cellulosic Materials for RE Capture
### Loaded Cellulose Materials  
In a different study, graphene oxide/polyethylene glycol/carboxylated bacterial cellulose ion-imprinted polymer (IIP) composites showed up to 49 mg/g Dy (III) captured at pH 4.0 [95]. Phosphorylated NCC/carbon nanotube composites capture up to 45 mg/g of La (III) ions at pH 4.0 [96]. Carboxylated NCC/carbon nanotube composites capture up to 34 mg/g Dy (III) at pH 4.0 [97]. It seems that both graphene oxide and carbon nanotubes only work as a support for functionalized NCC and do not influence the REE capture capacity. Additionally, considering that both phosphoric and carboxylic moieties were evaluated at pH 4.0, those materials have similar performance for REE capture to carboxylated cellulose-based materials. It is highly advisable to include more REEs in future studies, as previously stated.  
Another alternative is the use of cellulose supported on silica particles, which show similar capture capacities for REEs to those reported for carboxylated cellulose. The results revealed a removal capacity up to 29 mg/g of REEs [98]. As previously discussed in REE uptake by polymeric materials, silica works as a suitable support due to its desirable properties and does not contribute to REE uptake itself.  
In addition, a different approach is observed when cellulose is supported in Al-layered double hydroxide (Al-LDH); the resulting composite shows a capture capacity for REEs up to 102 mg/g at neutral pH and seems selective toward heavy REEs [99]. However, the main drawback of these types of composites is their stability under acidic conditions found in mining wastewaters and AMD, which could cause dissolution of Al-LDH, making them unsuitable for the intended application.
# Wireless Accelerometer Architecture for Bridge SHM: From Sensor Design to System Deployment
## 1 Introduction  
Infrastructural networks can be metaphorically compared to the veins and arteries of a nation, facilitating the flow of people and goods essential for cultural and economic prosperity. Among these networks, bridges play a critical role in maintaining system resilience. However, bridges are particularly vulnerable to a wide range of degradation processes, influenced by their construction materials, structural design, and exposure to environmental factors. Consequently, efficient management and maintenance of these structures have always been a top priority, with the United States leading these efforts since the 1970s [1, 2, 3].  
In recent years, bridge management has become an increasingly pressing issue, underscored by a series of high-profile collapses around the world. Scientific research highlights aging and damage from natural disasters as the primary threats to bridge integrity, with 70% of structural failures resulting from a combination of these factors. Alarmingly, data from the World Meteorological Organization reveals a five-fold increase in natural disasters over the recent 50 years, driven by climate change and intensifying weather extremes [4; 5].  
In recent years, research into bridge monitoring activities has intensified, driven by the need to assess structural health and guide maintenance efforts, thereby preventing failures with potentially catastrophic consequences [6; 7]. The standard method for conducting such monitoring involves equipping bridges with systems of wired vibration sensors, such as accelerometers or velocimeters [8]. These sensors are strategically placed to measure the structure's natural frequencies, reconstruct mode shapes, and determine damping factor. Tracking the variation of these parameters over time serves as a fundamental approach to structural health monitoring (SHM) of civil infrastructure, with continuous monitoring over the lifespan of the structure being the ultimate goal [9; 10].  
While continuous monitoring systems are well established in other engineering domains [11], such as railway vehicles and wind turbines, implementing such systems for bridges and viaducts presents unique challenges. Both traditional wired and emerging wireless monitoring systems have their respective advantages and limitations: