esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Theory  
The Sagnac interferometer relies on the phase difference between two counter propagating light beams. Introducing highly birefringent fibers inside a loop provide different light paths, which results in a specific interferometer pattern at the output. The phase difference can be formulated as follows [16]:  
\[\varphi=\frac{2\pi\mathrm{BL}}{\lambda} \tag{1}\]  
where B is the birefringence of the PM-PCF known as the difference between effective refractive indices of the fast and slow axis, respectively, L is the length of the fiber and \(\lambda\) refers to the light wavelength. Due to the determination of the phase difference (\(\varphi\)), the transmission spectrum of the interferometer could be presented according to the following equation [16]:  
\[\mathrm{T}=1-\frac{\cos\varphi}{2} \tag{2}\]Indeed, the transmission spectrum is a period function depending on the phase difference (\(\varphi\)). The wavelength spacing between two adjacent interferometer fringes could be approximated by the following function [16]:  
\[\Delta\lambda=\frac{\lambda^{2}}{\mathrm{BL}} \tag{3}\]  
According to Equation (3), the wavelength spacing of interferometer fringes directly depends on parameters of the fiber, i.e., birefringence and length. Elongation of the fiber leads to a change of phase difference (\(\Delta\varphi\)) between counter propagating light waves, which could be expressed by the following formula [16]:  
\[\Delta\varphi=\frac{2\pi}{\lambda}(\Delta\mathrm{LB}+\mathrm{LAB}) \tag{4}\]  
As a consequence, this change of phase difference causes the interferometer spectrum to red-shift due to an increase in longitudinal strain. The temperature effect is negligible because of the PCF structure. In the proposed setup, the output power could be estimated as an integral over the common spectrum of the Sagnac interferometer (T\({}_{\mathrm{INT}}\)) and filter function of a given DWDM channel (T\({}_{\mathrm{DWDM}}\)) with respect to incident broadband light emission (T\({}_{\mathrm{BLS}}\)):  
\[\mathrm{P}_{\mathrm{out}}\approx\int\mathrm{T}_{\mathrm{BLS}}(\lambda)\mathrm{ T}_{\mathrm{DWDM}}(\lambda)\mathrm{T}_{\mathrm{INT}}(\lambda)\mathrm{d}\lambda \tag{5}\]  
The strain induces change in phase difference, which results in a shift in the interferometer spectrum. Thus, the change of optical power could be approximated as follows:  
\[\Delta\mathrm{P}\approx\int\mathrm{T}_{\mathrm{BLS}}(\lambda)\mathrm{T}_{ \mathrm{DWDM}}(\lambda)\bigg{(}\frac{1-\cos\Delta\varphi}{2}\bigg{)}\mathrm{d}\lambda \tag{6}\]  
Change of phase difference caused by elongation has an influence on the transmitted power. Both the sensitivity and the measurement range are related to the edge slope of the interferometer and the spectral characteristics of DWDM. According to Equation (3), the wavelength spacing of interferometer fringes depends on both incident light wavelength and parameters of the fiber, i.e., birefringence and length. Thus, by the adjustment of the length of the PM-PCF, the measurement range could be modified.
## 3 Materials and Methods
### Instrumentation and Acquisition System
#### 3.2.1 Bus Connector  
This allows the connection between a maximum of six modules, three at each layer. The modules are connected to receptacle 50-way surface mount connectors in which every pin at each connector corresponds to the same pin in all other connectors. Every pin has been assigned an unalterable net to ensure the transmission of the voltages and signals between boards.
## 5 Experiments and Results
### Runtime Test Routine  
Figure 5 shows how the proposed multi-tier streaming analytics model runs its run-time test routine to detect a ransomware version in a realistic environment. In Figure 5, a suspicious version downloads itself onto the targeting computer system when the user browses the web. To do so, the suspicious attack uses many toolkits for this purpose, such as Trojans, spoofing links, and downloading software and apps. Meanwhile, the suspicious version tackles the trap files created by the proposed model during the extraction tier. It activates its static and dynamic traits to infect the trap files. Then, a scan disk is implemented to check-up the actions and infections on the computer system. Whenever infections are observed, they are analyzed statically and characterized dynamically. Accordingly, the ancestor families are attributed, and multi-descent ransomware versions are fused to be ready for further learning by the hybrid machine learner. Consequently, the class label of the fetched version is predicted throughout the learning tier. By tracking and analyzing the observed actions, the proposed model attempts to determine to what ancestor family this version does belong? Thus, it affirms that  
Figure 4: Experimental workflow.  
the suspicious version is either ransomware, or malware, or good-ware. Finally, it either warns the user by a popped up message or; it pops-up a safe acknowledgment to the user's screen.
## 2 Materials and Methods  
In the designed system, the microcontroller performs communication protocol conversion between DVS, SpiNNaker and the servomotor. The data formats are different for the three components, and are referred to as follows:  
* _Events_: visual information captured by DVS and represented by AER protocol (between microcontroller and DVS).
* _Packets_: spikes injected to and received from SpiNNaker (between microcontroller and DVS).
* _Commands_: data used to control the servo (between microcontroller and servo).  
As shown in Figure 1, the microcontroller receives events from DVS, the events are then converted to packets and injected into SpiNNaker. The microcontroller receives packets (spikes) back from the SNN running on SpiNNaker. Finally, it generates servomotor control commands based on the received spikes.  
The neuromorphic processor used is SpiNNaker SpiNN-3 hosted on a development board. It is a multi-chip platform, where each chip has 18 identical processing cores and six bidirectional inter-chip communication links. The SpiNN-3 has 4 SpiNNaker chips and can simulate a SNN with up to 6400 neurons. These chips share a 128 MB SDRAM, which gives over 1 GB/s sustained block transfer rate [9]. The router can route the spikes from a neuron to many connected neurons. SpiNNaker is designed to optimise the simulations of SNNs, and implements some common neuron models such as leaky integrate and fire model.  
The DVS used in our platform is DVS128 from iniLabs, Zurich, which has a resolution of \(128\times 128\). The DVS camera has low latency down to 15 \(\upmu\)s and high dynamic range of up to 120 dB and can work at low power at 20 mW [5; 22]. Figure 2 shows a DVS recording when a ping-pong ball is moving. The outline of the ball will produce spikes, but also some random noise is generated, which can be decreased by increasing the threshold of events.
# Limitations of Using DAQ Cards for Absolute Vibration Measurement in Hydraulic Machines
## 5 Measurement of Absolute Vibrations of Hydraulics Machines Using DAQ Cards, Measurement Setup  
A specific feature of hydraulic machines is a relatively low rotational speed. Consequently, a reliable vibration measurement must ensure proper representation of low-frequency vibration components. The importance of this requirement is often underestimated. However, the real importance of the problem is evidenced by a comparison of the content of [30] limiting the frequency band of the measurement system tested there to 5 Hz (due to unrealistic results below 5 Hz) with the requirements of the standards cited above. Based on the tests carried out, the possible effects of an inattentive approach to the selection of equipment for measuring absolute vibrations in water machines are illustrated below.  
Six different measurement cards were tested. Each device was tested in the same way for all available measurement ranges. Therefore, the number of tested ranges and their span are different for each card. The idea of the test was to quickly and easily verify the cards' suitability for measuring the absolute vibrations of hydraulic machines.  
The tests were carried out using only measuring cards, without the use of exciters and vibration transducers. The method of carrying out the measurements is schematically shown in Figure 2. In order to assess the effect of the properties of the measuring cards on the vibration measurement results, the input of each tested card was shorted. The signal measured in these conditions was processed to correspond to the signal from an accelerometer with a sensitivity of 100 mV/g (such sensors are quite common in vibration measurement devices/systems). The processing of the measured signal includes scaling, high-pass filtering, and integration to determine the vibration velocity and double integration to determine the vibration displacement. The experiment results for each card are presented below. The signal sampling frequency was 2.5 kHz. In each case, the recording lasted 60 s, and then the rms values of the vibration velocity and the peak-to-peak values of the vibration displacements were determined in 1-s intervals, and then they were averaged for the recording time. The results were presented for the following cut-off frequency (fc) values of the applied high-pass filters: 2, 1.5, 1, 0.5, 0.25, and 0.1 Hz.  
The results obtained in this way allow for determining the influence of the DAQ device on the vibration measurement results. This allows for assessing the suitability of the DAQ card for low-frequency vibration measurements using accelerometers.
# Secure Authentication and Credential Establishment in Narrowband IoT and 5G
## 5 Architecture Description and Evaluation
### Testbed  
All authentication-related communications took place between two end-points, namely, the IoT controller and the IoT device. A single IoT controller handled all the authentication requests to the centralized AAA server. Both the IoT controller and the AAA server were co-located in an Intel i5-7400 CPU at 3.00 GHz with 8 GiB of system memory. Moreover, the IoT device was mainly composed of two different elements: an Arduino-compatible SmartEverything FOX board by Arrow and an NB-IoT compatible radio module. The SmartEverything board employed as an IoT device contained an ATMEL SAMD21 Ultra low-power ARM Cortex-M0+ microcontroller. The ATMEL SAMD21 had 256 kB of programmable flash storage and 32 kB of main memory. Additionally, the NB-IoT radio device employed was the Quectel BG96 Multi-mode module, configured to use LTE Cat NB1 only (NB-IoT). Due to the lack of 5G deployments in the nearby area, the employed backhaul network was a 4G system. It was composed of an NB-IoT LTE RAN and a 4G Evolved Packet Core (EPC). Without a lack of genericity, this same scenario could be achieved in a 5G system with LTE RAN or New Radio (NR) indistinctly. During all the experiments, the IoT device was static and located at approximately 575 m from the closest eNodeB.  
The service network employed during the experiments was a public 4G network managed by a mobile operator company. To gain access, the IoT device included a USIM card with a limitless data subscription plan. Additionally, during the experiments, a laptop computer was employed in the field. The laptop was connected through a serial console cable to the IoT device during the duration of all the experiments. The IoT device included a special debug code that exposed a customized command interface that controls several debug functions. Using a script, the laptop triggered the bootstrapping process from scratch by communicating with the IoT device through the command interface. This command was sent to the IoT device at random times of the day. During the bootstrapping process, the laptop logged all the serial console messages of the IoT device, including time-stamps and message sizes at the time of encode and decode. Both PANATIKI and LO-CoAP-EAP were employed in the experiments. Additionally, the IoT controller and AAA server logged all the network packets using _tcpdump_ during the whole process. These logs were later reviewed to match the data logged by the laptop connected to the IoT device. Finally, no notable adverse weather events took place during the duration of the process--the field equipment remained safe and was never compromised.
## 4 Proposed Scheme  
### The Scheme Overview  
This section mainly introduces the model of the proposed scheme. As shown in Figure 1, the BNs are distributed at sea level, the UWSNs are clustered and layered according to the depth of the UW-sensors, the UW-sensor within each time transmits the packets to the cluster head node (CH) inside the cluster, and the CH in each layer accepts the data sent by other UW-sensors and then forwards the packet to the previous CH until it reaches the BN. The non-CH common nodes in the first layer near the BN node can directly transmit data to the BN. The underwater nodes transmit data to avoid the MN detected by the trust model to ensure data security. After calculating the trust value of UW-sensor, the UWSNs will exclude MNs from being pre-selected nodes for data transmission. Before data transmission we need to perform a two-hop availability check on the neighboring nodes to find the void nodes. After removing the void nodes, a path with a smaller total wiring distance is constructed from the remaining neighbor nodes for transmission.
# Towards an Optimized Blockchain-Based Secure Medical Prescription-Management System
## 3 Blockchain-Based Prescription Management DApp Overview
### System Presentation and Architecture
When treating a prescription, the pharmacist has two possibilities: either the prescription is being processed for the first time and has not been registered in the platform or it is already recorded in the platform: * **Prescription processed for the first time**: In the case of a prescription processed for the first time, the prescription does not have a QR code. Therefore, the pharmacist needs to manually register the prescription details within the platform. This involves entering all relevant information regarding the prescription, such as the medication name, dosage, treatment duration, the prescribing doctor's name, and patient information, into the computer system or dedicated electronic platform. Without a QR code, manual registration is necessary to ensure that the prescription is processed correctly and that all required information is available for the patient's future follow-up. Upon inputting the prescription details, the DApp generates a unique QR code specific to that particular prescription. This QR code becomes an integral part of the prescription document, enabling quick access to critical information, simplifying medication management, and promoting patient safety. * **Prescription already registered**: In this case, the pharmacist scans the QR code and gains access to the prescription history, which allows him/her to verify the relevant data of the prescription and complete the purchase procedures with complete safety and transparency. In instances where the patient is not yet registered within the DApp, pharmacists have the authority to create an account on the patient's behalf. As part of the registration process, a personalized QR code is provided to the patient. This unique QR code serves as a secure identifier, linking the patient to his/her healthcare information within the platform. The architecture of the proposed prescription-management system is composed of 3 layers, as described in Figure 1.  
We developed a web application (web layer) that enables seamless interaction with the blockchain platform (blockchain layer). This interface is integrated with an advanced IoT system (sensing layer) that utilizes a camera and a Raspberry board with a QR code reader and scanner application to accurately identify medical prescriptions.
# Third-Generation Sequencing in Clinical Practice: The New Era of Precision Medicine?
## 3 Inherited Disorders  
Less widespread but still valid is the introduction of NS in human genetics, with numerous potential applications in diagnosing inherited disorders.  
Between December 2020 and May 2021, at two hospitals in Stanford, California, 12 cases representative of persons living in the United States with respect to race, ethnic group, and sex were enrolled. Whole-genome NS was performed, and five of them obtained an initial genetic diagnosis in less than ten hours from the blood sample arrival [9]. Between them, it is emblematic the case of a 3-month-old full-term infant who presented in status epileptic, for which a genetic diagnosis of a Poirier-Bienvenu neurodevelopmental syndrome (a _CSNK2B_-related disorder) was made in less than nine hours from enrollment (it takes more than two weeks by standard methods). The ultrarapid result obtained froze further planned diagnostic testing, simplified counseling, and prognostication, and aided in epilepsy management [9].  
In addition to rapidity, the ability of NS to characterize tandem repeats (TR) is the other relevant advantage of ONT approaches in the diagnosis of genetic disorders. TR are implicated in numerous diseases, including [PERSON]'s, frontotemporal dementia, and amyotrophic lateral sclerosis. Sometimes TR can cause disease through their length, sequence, or base modifications; these are all features often difficult, if not impossible, to be assessed with conventional methods. Long-reads NS allows spanning large TR, showing their size, sequence, and the presence of base modifications [10].  
In the complex scenario of inherited disorders, it is mandatory to mention preimplantation genetic testing (PGT), for which both NS rapidity and detection ability are crucial. Standard molecular PGT (such as microarray and short-read sequencing) cannot distinguish embryos carrying balanced rearrangements from those with a normal karyotype, worsening the outcome of assisted reproduction. NS can detect these aberrations identifying exact breakpoints and allowing a haplotype linkage analysis [11]. Furthermore, at Columbia University Medical Center, it was shown the NS ability to perform in 20 min a complete aneuploidy screening and, in a few hours, large copy number variations (CNVs) or mosaic aneuploidy detection [12]. In contrast to existing assays, which take more than 12 h, ONT introduction in PGT could allow same-day testing and embryo transfer, thus avoiding the need for more complex and expensive techniques or embryo freezing [12]. A strategy that is cheaper, more accurate than conventional approaches, and that allows for same-day embryo transfer could be the future of PGT.
# Satellite Measured Ionospheric Magnetic Field Variations over Natural Hazards Sites
## 5 Results  
The observations indicate that after some energetic lithospheric natural and man-made events, magnetic disturbances at LEO altitudes can possibly be traced back to the source region. In the case studies magnetic field variations from satellite measurements are associated with eligible natural sources, among them earthquakes and volcanic eruptions, and also secondly from artificial factors, in particular rocket launches and strong explosions, see Table 1. The manifold causal relationship via lithospheric atmospheric ionospheric coupling (LAIC) is difficult to establish, but atmospheric acoustic waves (AW) and gravity waves (AGW) can serve as almost line of sight channel to bridge the gap from solid earth to ionospheric heights. This conjecture is supported by theory, observations, and numerical investigations. Measurements indicate main wave activity and dissipation at somewhat lower altitudes, e.g., in case of tsunamis [25], but leaking of energy could lead to pronounced structures and boundary layers at LEO altitudes. If a satellite crosses these structures with sufficient orbital speed the AW or AGW induced pattern in magnetic variation can be considered in first approximation as stationary and sketch out the horizontal dimension along the track.
## 4 Results  
### The SEBS Model Sensitivity  
Table 1 provides the sensitivities of \(H\) in regards to the SEBS's inputs. Low sensitivities (\(\left|\,S_{\rm I}(H_{\pm 285^{\circ}})\right|<10\%\)) were found for changes in \(d\), NDVI, LAI, Albedo, \(H_{\rm h}\), and \(R_{\rm s}\). High sensitivities (\(\left|\,S_{\rm I}(H_{\pm})\right|>10\%\)) were found for \(z_{\rm 0m}\), LST, \(T_{\rm a}\), \(P\), and \(u\). In general, the results indicate that the variation of \(H\) largely depends on meteorological parameters at the reference height and \(z_{\rm 0m}\). Exceptions to this finding include both \(H\) calculations outside of the limiting cases and the wet-limit and dry-limit sensible heat flux, and both are determined from net radiation and soil heat flux. Here, it is worth mentioning that in the SD00 model the prescribed forest height (in this case: the Lorey's height) is as sensitive as the \(d\) and \(z_{\rm 0m}\).
# Use of Phase Change Materials for Food Applications--State of the Art in 2022
## 2 Food Applications of PCM
### Food Storage and Transport
#### 2.2.12. Independent Containers for Transport by Truck and Train  
A refrigerated container or reefer container is a container used for transport and capable of refrigeration, for example for transport of fruits, vegetables, or meat [78]. According [78], commonly, the containers have an integrated mechanical refrigeration unit running on electricity, which is directly available at a harbor or on a container ship, while on trucks and trains (or just as backup) electricity can be supplied by diesel-powered generators attached to the container. Sometimes dry ice is used for cooling, allowing cooling even for many days independent of electricity. Common on ships is also cooling by cold air from ship-based cooling units.  
Using electricity supplied by diesel-powered generators on trucks and trains is however not efficient. According news releases by the University of Birmingham [79; 80], University of Birmingham researchers together with CRRC Shijiazhuang (China's largest railway truck maintenance company and rail vehicle air-conditioning equipment manufacturer) developed the world's first-of-a-kind \"refrigerated\" road/rail container with cold storage using PCM. Once charged, the PCM can keep the interior temperature of the container for over 100 h, while a full charge can be achieved in less than 2 h. According to the news release published in 2018, the technology had completed commercial trials carrying real goods for 35,000 km of road and 1000 km of rail transport across different climate zones. Compared to diesel powered refrigeration, cooling with PCM has the advantage of energy saving and environmental benefits, constant temperature, and the passive cooling allows an easy transfer of the containers between trains and trucks which offers better flexibility across the supply chain. In 2019, CRRC Shijiazhuang started to deliver the first order of 49 containers to Yunnan Su Lida Agricultural Products Supply Chain Co., Ltd.  
Some details of the test results are reported in [81]. According to the paper, the tested 40 ft ISO standard container was equipped with 10 plates containing a total of 1260 kg of PCM (commercial Rubitherm RT5). The plates were charged by a separate charging facility. Discharge took almost 95 h. Results showed that the new container had significantly improved performance compared to diesel-powered reefers, with the system COP as high as 1.84, a reduction of the energy consumption by 86%, a reduction of the operational cost by 91%, and a reduction of emissions by 78%. Ref. [82], from CRRC Shijiazhuang, describe and discuss the tests in detail.