esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion  
A schematic representation of the SILAR process for the preparation of electrode materials is depicted in Figure 1a. INS nanostructures with stratified, yet interconnected clumps resembling tree reef corals' morphology are shown in Figure 1b, grown on NF. On the other hand, INSC grown on NF substrate with an even more integrated layered clump nanostructure exhibiting cauliflower-like morphology is shown in Figure 1c. This SWCNT can improve the electrode surface properties, charge transport, and performance consistency of the electrode sample. The well-separated layered nanostructure enables better electrochemical reactions and provides a higher active electrode surface area than the as-prepared electrode samples.  
The Substrate Preparation: The substrate is first cleaned and dried to remove any impurities or contaminants from its surface. This is important to ensure that the deposited film adheres well to the substrate.  
Rinsing: After the adsorption step, the substrate is rinsed with a suitable solvent to remove any excess precursor solution that may be on its surface.  
Reaction: The rinsed substrate is then immersed in a second solution (a sulfide dioxide precursor), typically a reducing agent, which reacts with the adsorbed precursor ions to form a thin film of the desired material on the substrate surface. The reducing agent reacts with the precursor ions in a controlled manner to ensure the growth of a uniform and conformal film.  
Drying: Finally, the substrate is dried to remove any remaining solvent or water molecules, leaving behind a thin film of the desired material on its surface.  
XRD (X-ray diffraction) was used to examine the crystalline phase structure of both electrode materials, and the resulting spectra are shown in Figure 1d (Standard ICDD pattern 32-0456), which corresponds to the cubic structure of In\({}_{2}\)S\({}_{3}\), which is found in the XRD spectrum of prepared samples [8]. In spectra, Miller indices are used to index all peaks. All peak positions have confirmed a cubic phase of In\({}_{2}\)S\({}_{3}\) consistent with previously  
Figure 1: (**a**) Schematic illustration of synthesis of sample INS and INSC, FE-SEM images of sample (b) INS, (c) INSC, (d) XRD pattern (missing is the JCPDS file), and (**e**) FTIR spectra of as-prepared electrode materials INS and INSC.  
reported values. The molecular structure and functional group present in In\({}_{2}\)S\({}_{3}\) were analyzed using the FTIR (Fourier-transform infrared spectroscopy) spectra, as shown in Figure 1e. The vibration of the O-H groups in chemisorb water molecules is characterized by a broad peak near 3224 cm\({}^{-1}\), the bending vibration of H\({}_{2}\)O occurs at 1656 cm\({}^{-1}\), and the sulfonic group is characterized by signature peaks between 800 and 1500 cm\({}^{-1}\)[9].
# Generation and Distribution of Quantum Oblivious Keys for Secure Multiparty Computation
## 2 Methods
### Generating the OTs
Passing this test (statistically) ensures that [PERSON] measured his qubits as stated in the protocol as opposed to performing a different (potentially joint) measurement. Such strategy may extract additional information from [PERSON]'s strings, but would fail to pass the specific correlation check in step 6. At step 8, [PERSON] separates his non-tested measurement outcomes in two groups: \(I_{0}\) where he measured in the same basis as the preparation one, and \(I_{1}\), in which he measured in the different basis. He then inputs his bit choice \(c\) by selecting the order in which he sends the two sets to [PERSON]. During step 9, [PERSON] encrypts her first and second input bits with the preparation bits associated with the first and second second sets sent by [PERSON] respectively. This effectively hides [PERSON]'s input bit because she is ignorant about the measurements that were not opened by [PERSON] (by the security of the commitment scheme). Finally, [PERSON] can decrypt only the bit encrypted with the preparation bits associated to \(I_{0}\). In real implementations of the protocol one should consider imperfect sources, noisy channels, and measurement errors. Thus, in step 6 [PERSON] should perform parameter estimation for the statistics of the measurements, and pass whenever the error parameter es below some previously fixed value. Following this, [PERSON] and [PERSON] perform standard post-processing techniques of information reconciliation and privacy amplification before continuing to step 7. These techniques indeed work even in the presence of a dishonest [PERSON]. As long as he has some minimal amount of uncertainty about [PERSON]'s preparation string \(s\), an adequate privacy amplification scheme can be used to maximize [PERSON]'s uncertainty of one of [PERSON]'s input bits. This comes at the cost of increasing the amount of qubits shared per OT [32]. An example of these techniques applied in the context of the noisy storage model (where the commitment based check is replaced by a time delay under noisy memories) can be found in [19].
# Flexible Antennas: A Review
## 2 Materials for Flexible Antennas
### Substrates  
The substrate material used in flexible antenna needs to possess minimal dielectric loss, low relative permittivity, low coefficient of thermal expansion, and high thermal conductivity [50]. Such a constraint is driven by the need for increased efficiency (in different environments) at the cost of larger antenna size. An exception to the above-mentioned fact is the need for large dielectric constant for miniaturized antennas. Three types of substrates have often surfaced in the fabrication of flexible antennas: thin glass, metal foils, and plastics or polymer substrates [51]. Though thin glass is bendable, the intrinsic brittle property restricts its utility. Metal foils can sustain high temperatures and provide inorganic materials to be deposited on it, but the surface roughness and high cost of the materials limit its applications [52]. Plastic or polymer materials are the best candidates for flexible antenna applications which include: (1) the thermoplastic semicrystalline polymers: polyethylene terephthalate (PET) and polyethylene naphthalate (PEN), (2) the thermoplastic noncrystalline polymers: polycarbonate (PC) and polyetherselphone (PES), and (3) high-glass transition temperature, \(T\)g materials: polyimide (PI) [53]. They are popular and attractive in recent years for flexible electronics due to their robustness, flexibility, wettability, and stretchability. Due to high \(T\)g, polyimide is one of the most preferred materials for flexible antennas, which had been used as a substrate in prior studies [54; 55; 56; 57; 58; 59; 60; 61; 62]. [PERSON] et al. [55] reported on the design and performance of an artificial magnetic conductor (AMC)-backed dipole antenna on Kapton Polymiode for RF energy harvesting in the context of next-generation blood irradiation systems. PET and PEN are preferred in many flexible antenna designs due to excellent electrical, mechanical, and moisture resistant properties [63]. For fabricating different types of flexible antennas, PET has been used routinely due to its excellent conformal behavior and mechanical stability [63; 64; 65; 66; 67]. In an earlier report [68], an inkjet-printed slotted disc monopole antenna was designed, printed, and analyzed at 2.45 GHz industrial, scientific and medical (ISM) band on PET for early detection of brain stroke. Next, a new all-organic flexible patch antenna was fabricated with PEDOT: PSS on a selected PET fabric substrate for next-generation wearable antennas [69]. A coplanar square monopole operating at 60 GHz with 68% total efficiency and 1.86 dBi maximum realized gain was presented in [70] over a PEN substrate. PET and PEN substrate have excellent conformality, but low glass transition temperature limits their application for the high-temperature condition. Flexible antennas made for wearable purposes need unique attributes such as limited visibility for the user, robust antenna performance in different conditions, mechanical stability, and withstanding rigor, such as washing and ironing [71]. Different types of substrates used in wearable antennas have
###### Abstract  
Extraction of gas (coalbed methane) produces clean energy and can ensure that coal mines maintain high-efficiency production. The currently available coal seam permeability enhancing technologies and modes have certain application restrictions. Therefore, a novel mode is proposed to promote gas extraction. This mode divides complex coal seams into tectonic regions and nontectonic regions based on geological structures. Then, the characteristics of different regions are matched with the advantages of different hydraulic technologies; thus, pressure relief technologies are proposed for tectonic regions, and fracturing technologies are proposed for nontectonic regions. The permeability of coal seams will be sharply increased without leaving unfratured areas. This mode will promote the effectiveness of gas extraction, shorten the extraction time, and ensure safe and efficient production in coal mines. A field application shows that this mode has a better effect than slotted directional hydraulic fracturing technology (SDHFT). The gas concentration and pure gas flow were increased by 47.1% (up to 24.94%) and 44.6% (up to 6.13 m\({}^{3}\)/min), respectively, compared to SDHFT over 9 months. The extraction time was reduced by 4 months. This mode reduced the number of times that gas concentration exceeded government standards during coal roadway excavation, and the coal roadway excavation speed was increased by 16% (up to 158 m/month).  
gas extraction; permeability enhancement; coal and gas outburst; hydraulic technology; complex coal seam Article
# Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights
## 2 Technical Background of NB-IoT
### The Internet of Things (IoT) and Industrial Internet of Things (IIoT) Technologies
#### 2.2.2 The IoT/IIoT Communication Technologies  
IoT and IIoT are thought to have three or five architectural functionality layers [53; 54]. Meanwhile, in [55], for a Man Like Nervous (MLN) system, other layers are involved. Three-layered IoT/IIoT architecture include perception, network, and application layers. While in five-layered architecture, in addition to the three layers are processing and business layers. However, in any type of architecture proposed or adopted, the network or transport [53] layer is responsible for the communication of devices among themselves and with the network infrastructure (e.g., gateway, server, etc.). IIoT allows the industries to meet their operational targets, among other things. However, most of the peculiar needs of the industries are centered on the capabilities of communication technologies as supported by the network layer. These designs need to include _latency_--time required for data propagation and processing, _topology_--device connection style, _throughput_--the volume of data that the network can support, _scalability_--number of supported devices in the network, the _security of data_ and _energy_--IoT device operational time without power supply [56]. Table 3 lists the common types of communication technologies used by IoT/IIoT and the network-supported features.  
The network or transport layer handles the coverage range of IoT/IIoT. Each type of communication technology has an approximate range it can cover. Therefore, depending on the requirements needed for an application, appropriate technology can be employed. However, for IIoT where timing is critical, latency is an important feature that needs to be put into consideration to achieve reasonable reliability of deployment. To this end, a true picture or understanding of the industrial wireless communication for the application of IoT is necessary.  
Figure 7: A typical structure of Industrial IoT (IIoT) showing basic layers.
## 4 Results and Evaluation  
### Metrics  
The metrics we used to assess the results are F1 score and AUC. There are multiple reasons for choosing these metrics for our model evaluation. The F1 score is the harmonic mean of precision and recall, which means that it assesses both measures [60], given the following formulas:\[precision=\frac{TP}{TP+FP}\]  
\[recall=\frac{TP}{TP+FN}\]  
where \(TP\) is the true positives, \(FP\) is the false positives, and \(FN\) is the false negatives. We have that \(F1\) is calculated by the following:  
\[F1=2\cdot\frac{precision\cdot recall}{precision+recall}\]  
By doing so, the F1 score is an indicator of both quality and robustness.  
On the other hand, \"the AUC of a classifier is equivalent to the probability that the classifier will rank a randomly chosen positive instance higher than a randomly chosen negative instance\" [61]. This can be calculated using the following formula:  
\[AUC=\frac{TN}{TN+FN}+\frac{TP}{TP+FP}\]  
where \(TN\) is the true negatives, \(FN\) is the false negatives, \(TP\) is the true positives, and \(FP\) is the false positives. This is important in this specific problem because of the importance of classifying correctly positive instances of depression.
# Modeling and Resolving Uncertainty in DIKWP Model
## 3 Problem Definition  
HFT serves as a vital component of financial markets and is directly influenced by changes in regulatory environments [25; 26]. However, the ambiguity and uncertainty of regulatory announcements present a challenging issue for HFT firms. To address this, we have selected the implementation of regulatory laws such as the Dodd-Frank Act as a case study. Studying how HFT firms respond to these regulatory challenges not only aids in understanding the adaptability and resilience of HFT firms but also provides insights into the stability of financial markets. In order to prevent systemic financial risks caused by financial storms like the one in 2008-2009, the United States enacted the Dodd-Frank Act in 2010, which mainly aimed to reduce risks in the financial system, improve transparency, and pro tect the financial rights of investors. The scope of this act is very broad, with Titles I to XVI covering topics ranging from strengthening the regulation of large insurance companies and financial derivatives and requiring hedge funds to publicly disclose product information and protect consumer financial rights. Its content exceeds 800 pages, making it the largest act in recent times [27]. However, at the beginning of the enactment of the Dodd-Frank Act, some of these provisions are relatively vague, leaving considerable room for interpretation regarding their implementation and enforcement. For example, the provisions regarding the use of insider information and the prohibition of fraudulent activities in Sections 746 and 747 of the Act are essentially aimed at consumer protection, yet they have been subject to controversy due to their lack of mens rea requirements. This is because instances of unfair transactions may sometimes be a result of subjective malice, while in other cases, they may arise inadvertently [28]. Furthermore, regarding the content of Section 747 (6), wherein it stipulates that the Commission may promulgate such rules and regulations as it deems necessary or appropriate in the public interest and for the protection of consumers to carry out the purposes of Section 747 (5), which prohibits transactions and practices detrimental to the maintenance of a fair and orderly market, such ambiguous provisions may grant law enforcement officials considerable discretionary power during the enforcement process. HFT firms, in particular, often face various moral condemnations [29; 30] for actions perceived as undermining fair trading practices, which may compel them to incur additional compliance costs to ensure adherence to relevant laws and regulations, thus minimizing various forms of scrutiny from law enforcement authorities.  
Based on the relevant definitions and methods of the DIKWP model, we conduct DIKWP transformation analysis on the case study across four dimensions: incompleteness, inconsistency, imprecision, and incorrectness, and construct an impact matrix.
# Designing an Adaptive Underwater Visible Light Communication System +
## 9 Discussion  
This study is based on the adaptive alignment system's performance under LOS and NLOS conditions. It analyzes the BER and power characteristics for manually changing the receiver position and extends to adaptive position change for LOS conditions using a servo motor. In both cases, experiments comprised several trials with varying angular  
Figure 24: Dark room vs. ambient light power chart trial 3.  
Figure 25: Dark room vs. ambient light power chart trial 4.  
displacement to explore the ability of this innovative UVLC approach to maintain reliable communication in the face of synchronization challenges. The result for the manual angular displacement for LOS shows that there is a considerable power dip when the receiver points at an angle away from the alignment position. The result is consistent with prior expectations that LOS communication typically provides the strongest signal, increasing the BER for the position not aligned with the transmitter. For NLOS communication, the adaptive system's performance depends on the receiver's FOV and the transmitter's beam angle. The results highlight that even a slight misalignment can substantially degrade the system's performance.  
After retrieving the results for the BER and power analysis for LOS and NLOS communication, trials on the adaptive alignment system were performed for different angular displacements at the receiving end. However, challenges arose due to synchronization issues and the repetitive reconfiguration of the USRPs when switching between transmitter and receiver modes, which require careful time calibration at both ends for accurate transmission and data fetching, thus adding delays and instability, leading to minor data loss, particularly when the receiver was not positioned accurately in the optimal direction during the time of data reception. The proposed approach produced reasonable results, indicating that the designed model could achieve more reliable performance with further research.  
Furthermore, opting for PPM is an effective approach for preserving signal accuracy without sacrificing energy efficiency. This modulation technique helps to improve the reliability of the UVLC system since it has better noise performance, but choosing the right PPM level is crucial since a high modulation level also increases the BER.
# Finite Element Analysis of a Novel Approach for Knee and Ankle Protection during Landing
## 2 Materials and Methods
### Model Construction  
Before modeling, a computerized tomography (CT) scanner (GE Ltd., Fairfield, CT, USA) was used to scan the right foot of a healthy female (age 24; height 166 cm; body mass 56 kg) with a slice thickness of 0.625 mm. The subject did not have any known musculoskeletal disorder/pain or previous foot surgery.  
The CT images in DICOM format were first imported to Mimics 17.0 (Materialise, Leuven, Belgium), where the six bony segments, namely, the calcaneus, talus, navicular, tibia, fibula, and femur, were reconstructed in three dimensions (3D). The model outputs from Mimics 17.0 were then optimized as solid parts using Geomagic Studio 2014 (Geomagic Inc., Research Triangle Park, NC, USA). In order to improve the reliability of simulation, the six bony segments were further detailed into cancellous and cortical bone with a layer of 2.68 mm [7]. Additionally, we applied the software Hypermesh 12.0 (Altair Engineering Inc., Troy, MI, USA) to establish ligaments in the knee and ankle, and all the bony and ligamentous structures were embedded in a volume of soft tissues. It is worth noting that, in this study, we analyzed the biomechanical responses of the ankle and knee at the moment of peak vGRF when jumping from 0.4 m, 0.8 m, and 1.2 m. In particular, different jumping heights correspond to different knee flexion angles, resulting in different shapes, sizes, and contact areas of the menisci and articular cartilages. Therefore, SolidWorks 2017 (Dassault Systemes SolidWorks Corp., Waltham, MA, USA) was adopted to adjust the knee flexion angle and construct the cartilages and menisci. There was also a heel fat pad, as well as skin tissue, surrounding all structures, whose geometries were determined in Mimics 17.0.  
According to the FE model of human lower extremity, SolidWorks 2017 was further used to design 3D structures of the semi-rigid support at the ankle joint, rigid connecting rod, spring component at the knee joint, and fixed components for three different knee flexion angles. Lastly, on the basis of a mesh convergence study, we applied the Hypermesh 12.0 to mesh all parts in the unbraced FE model with a total of 1,502,888 elements, and the double-joint brace was meshed with 88,073 elements. Among them, except for the tension-only truss elements of ligaments, the parts were of 3D tetrahedral (C3D4) element type. The intact model is shown as Figure 1.
## 5 mPOC Sensory System
### Smartphone-Embedded Sensory Functionalities  
Nowadays, smartphones are equipped with a variety of embedded (on-device) functionalities that serve various purposes. For instance, the microphone is essential for establishing bidirectional voice communication with humanitarian operators. Moreover, microphones can actively capture various physiological sounds, including the user's breathing and respiratory sounds, as well as ambient voices in the background.  
The combination of a loudspeaker and visual signals is utilized to issue appropriate warnings to the user, when necessary, from the humanitarian operators.  
The accelerometer and gyroscope sensors are capable of detecting acceleration/ deceleration along different axes using angular velocities. These sensors enable tracking of tremors, chills, and fatigue, which are characterized by relatively low mobility compared to the user's typical behavior profile. Additionally, sudden falls can also be detected by these sensors.  
Furthermore, smartphones are equipped with a compass, as well as GPS and indoor tracking tools, allowing for the tracking of the user's location, heading, and direction in relation to reference points. This functionality proves helpful in monitoring and keeping track of the user's whereabouts.