esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
The incorporation of carbon nanotubes (SWCNT, MWCNT, graphene) into a polymer matrix considerably enhances the intrinsic properties of the polymer. These CNT-based nanocomposites exhibit excellent thermal, mechanical and physical properties which make them very promising for use in a wide range of fields from energy storage to optoelectronics to biomedical devices (electro-mechanical sensors, anti-corrosion coatings, etc.). Both non-covalent and covalent approaches can be employed. Although the non-covalent methods appear easier to perform, grafting in the presence of nanoparticles combined with ultrasonic polymerization can provide stronger CNT-polymer interactions and achieve a uniform and stable dispersion (breakdown of the nanoparticle agglomerates), the strong attachment of functional materials to the CNT surfaces, and a fine dispersion of CNT nanoparticles within the polymeric matrices. Nevertheless, the pathway to covalently functionalizing the nanocarbons requires the use of an acid mixture which affects the structural properties of the carbon materials within the nanocomposites, and hence their performance. The possibility of incorporating a high filler loading which could improve the interfacial interactions through covalent bonding between the carbon and the matrix would improve the physical properties of the nanocomposites. Inverse emulsion polymerization appears to be a possible alternative for the fabrication of covalent linkage-based nanocomposites because there is no need for prior acidic treatment of the CNTs. The non-covalent approach can also be considered when the aim is to avoid a structural perturbation of carbons, since achieving a good dispersion of carbon in the matrix is based on physical interactions (Van der Waals, \(\pi\)-\(\pi\) stacking and hydrogen bonds) that do not alter the intrinsic properties of carbon. However, this approach suffers from low structural stability.  
Obtaining carbon-based nanocomposites with enhanced structural stability along with a decrease in sp\({}^{2}\) hybridized perturbation of carbon materials is a major challenge. The scale-up for fabrication of such composites can also be a hurdle, in particular for graphene-based nanocomposites because of the high cost of neat graphene. One solution would be to use reduced graphene oxide which is less oxygen-rich.  
Hybrid nanocomposites possessing high properties can also be fabricated with other kinds of nanoparticles, and silica in particular due to its high surface area and its ability to form strong interactions with organic components such as the grafting of polystyrene chains onto a silica surface [4; 49] or anti-fog molecules onto a methacrylic silica surface [50].  
This research was partially supported by the Kinnert Academic College internal research fund.  
The authors declare no conflict of interest.
# Towards Mitigating Jellyfish Attacks Based on Honesty Metrics in V2X Autonomous Networks
## 2 Jellyfish Attack Overview
### Jellyfish Reordering Attacks  
As the term implies, the attacker node ignores the first in, first out (FIFO) queue's basic function of data forwarding and instead selects packets at random before transmitting them to its next hop node [21], as demonstrated in Figure 1. Because some of the reordered packets' acknowledgments (ACKs) were not received in a timely manner, the sender had to retransmit them. When a packet is received, the receiver automatically generates an ACK for the packet. In the case of out-of-order packets, the sender will receive redundant ACK messages. If the number of duplicate ACK messages reaches a certain threshold level, the TCP will launch its flow control mechanism, which decreases the overall throughput and causes the network to become more congested [22].
## 3 Results and Discussion
The \(I_{\text{NBE}}\)/\(I_{\text{YL}}\) for the InGaN grown at 760 \({}^{\circ}\)C is 1.41, while it is enhanced with a ratio of 1.83 for the InGaN/GaN grown at 780 \({}^{\circ}\)C. This discloses an improved crystalline quality at elevated \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample** & \(C_{GaN}\) **(Å)** & \(C_{InGaN}\) **(Å)** & **In\%** & **Relaxation (\%)** \\ \hline InGaN/GaN on sapphire (760 \({}^{\circ}\)C) & 5.186 & 5.280 & 11 & 3.9 \\ \hline InGaN/GaN on HEMT (760 \({}^{\circ}\)C) & 5.179 & 5.272 & 16 & 30 \\ \hline InGaN/GaN on HEMT (780 \({}^{\circ}\)C) & 5.180 & 5.269 & 14 & 73 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The out-of-plane lattice constant \(c\) of GaN, InGaN, and relaxation degree in InGaN layer of the three samples. Figure 3: XRD reciprocal space mapping of (104)-plane for InGaN/GaN heterostructures at the temperature of 760 \({}^{\circ}\)C both on the (**a**) AlGaN/GaN-on-Si HEMT and (**b**) GaN/sapphire template. temperatures. The \(p\)-type conductivity in the InGaN/GaN heterojunctions are further confirmed by the Hall effect and Seebeck measurements. From the above results, the growth and structure properties of InGaN/GaN heterostructures grown on the AlGaN/GaN-on-Si HEMT and GaN/sapphire templates are quite different. The poor-quality GaN in the HEMT structure results in a much wider FWHM value for the following InGaN epitaxial layer than that grown on GaN/sapphire template even deposited at the same conditions. Although the InGaN is nearly coherently grown on GaN/sapphire, it starts to be relaxed when grown on the AlGaN/GaN-on-Si HEMT at the same growth conditions. The In incorporation is also enhanced due to the relaxation of the epitaxial film. The quality and interface of the InGaN/GaN heterojunction can be improved by slightly increasing the growth temperature. However, the relaxation degree is increased, which becomes a problem for the InGaN/GaN heterostructure grown on the AlGaN/GaN-on-Si HEMT. Further optimization in the growth condition to control the strain is still needed.
# Immersive Two-Channel Recordings Based on Personalized BRIRs and Their Applications in Industry
## 5 Methods for Creating 2-Channel Immersive Audio
The DBAP technology, even though based on amplitude panning, is applied to a series of speakers, and works best if using irregular loudspeaker layouts [45]. Ambisonics is another multichannel scheme that strives to recreate a theoretically accurate sound field at a certain listening position. Multiple ambisonic decoders have been proposed in the past [46; 47], but the main principle of capturing sound from multiple channels in all spatial directions still stands. The process of ambisonics can be divided into two main phases: encoding and decoding. During encoding, sound is captured using an array of microphones arranged in a specific pattern or one special ambisonic microphone, which records the sound pressure and particle velocity. These data are then encoded into spherical harmonics, which represent the sound field. During decoding, the encoded spherical harmonics are decoded to reproduce the sound field over a set of loudspeakers or headphones. In a two-channel setup, this involves binaural rendering. The rendering uses panning, but different from VBAP object panning, ambisonic panning employs a continuous virtual panning function by assuming a continuous distribution of loudspeakers [46]. Converting multichannel audio to binaural presentation is usually achieved with the help of HRTFs [48], and this is where BRIRs have a chance to take their place. Since they carry both the room impulse responses as well as HRIRs, the sound panning is enhanced while still maintaining the original loudspeaker location and room acoustics, giving the audio the most natural effect. Obtaining a set of BRIRs is relatively easy. The set of measured signals from binaural microphones (e.g., the ones shown in Figure 3) placed in the subject's ear canals, for each of the loudspeakers, is processed into binaural impulse responses. By generating a chosen impulse from every loudspeaker, any number of stereo responses can be obtained. These responses can then be processed, filtered, and convolved with a chosen immersive audio recording and combined into a two-channel recording in any audio program. Personalized BRIRs achieved in this way preserve all the immersive properties of the specific loudspeaker setup in the given room. Even though they require the presence of a human, their usage, as mentioned earlier, is definitely worth it in most scenarios where recreating specific listening experiences is the most important goal.
# Machine Learning in Smart Buildings: A Review of Methods, Challenges, and Future Trends
## 4 ML Techniques in Energy Prediction
### Supervised ML Solutions
#### 4.1.2 Decision Tree  
The decision tree method is an important predictive ML modeling approach that constructs a model of decisions based on the actual values of features in the data. Decision trees can be utilized for both classification and regression problems. In tree structures, leaves represent class labels, and branches represent conjunctions of attributes that lead to those labels [50]. The decision trees where the target variable takes continuous values are called regression trees. Decision trees are often among the most favored of ML algorithms because of their speed and accuracy. The most common algorithms for decision trees are [51] classification and regression tree, ID3, C4.5 and C5.0, Chi-squared, M5, and conditional decision trees. The study in [52] introduced a machine learning technique utilizing decision trees to identify the most prevalent human behaviors and their temporal relationships, hence facilitating the rapid modeling of human behavior in intelligent environments. Reference [53] presented a prototype distributed data mining system for the healthcare sector, utilizing the C4.5 classification algorithm, capable of delivering patient monitoring and health services. The decision tree algorithm is a non-parametric model that is straightforward to read and elucidate. The primary drawback of this method is its susceptibility to overfitting.
## 3 Results and Discussion
### Antioxidant Capacity of the Hydrophilic and lipophilic Fractions Determined Against DPPH*Radicals
\begin{table}
\begin{tabular}{l c c c} \hline
**Sample** & **Hydrophilic Fraction** & **Lipophilic Fraction** & **Total Antioxidant Capacity** \\ \hline LLL seeds & 2.25 \(\pm\) 0.02 \({}^{\text{a}}\) (80.4\%) & 0.54 \(\pm\) 0.03 \({}^{\text{a}}\) (19.6\%) & 2.80 \(\pm\) 0.03 \({}^{\text{a}}\) \\ LAM seeds & 2.32 \(\pm\) 0.02 \({}^{\text{b}}\) (84.4\%) & 0.44 \(\pm\) 0.03 \({}^{\text{a}}\) (15.6\%) & 2.75 \(\pm\) 0.03 \({}^{\text{a}}\) \\ LLL sprouts & 2.88 \(\pm\) 0.01 \({}^{\text{c}}\) (87.0\%) & 0.43 \(\pm\) 0.02 \({}^{\text{a}}\) (13.0\%) & 3.31 \(\pm\) 0.02 \({}^{\text{b}}\) \\ LAM sprouts & 2.59 \(\pm\) 0.02 \({}^{\text{d}}\) (84.9\%) & 0.45 \(\pm\) 0.02 \({}^{\text{a}}\) (14.8\%) & 3.05 \(\pm\) 0.01 \({}^{\text{c}}\) \\ fermented LLL & 2.25 \(\pm\) 0.01 \({}^{\text{a}}\) (73.1\%) & 0.84 \(\pm\) 0.03 \({}^{\text{b}}\) (26.9\%) & 3.08 \(\pm\) 0.02 \({}^{\text{c}}\) \\ fermented LAM & 2.29 \(\pm\) 0.01 \({}^{\text{e}}\) (80.6\%) & 0.55 \(\pm\) 0.02 \({}^{\text{a}}\) (19.4\%) & 2.84 \(\pm\) 0.01 \({}^{\text{a,f}}\) \\ fermented LLL sprouts & 2.54 \(\pm\) 0.01 \({}^{\text{f}}\) (86.1\%) & 0.41 \(\pm\) 0.03 \({}^{\text{a}}\) (13.9\%) & 2.95 \(\pm\) 0.01 \({}^{\text{d,f}}\) \\ fermented LAM sprouts & 2.11 \(\pm\) 0.02 \({}^{\text{g}}\) (83.4\%) & 0.42 \(\pm\) 0.02 \({}^{\text{a}}\) (16.6\%) & 2.53 \(\pm\) 0.01 \({}^{\text{e}}\) \\ \hline \end{tabular} Abbreviations are the same as under Table 1. Data are expressed as means \(\pm\) standard deviations (n = 3). Means in each column followed by different letters \(\approx\)\(\pm\) indicate statistically different mean values (\(p<0.05\)). The percentage contribution of the antioxidant capacity of the hydrophilic and lipophilic fractions to the total antioxidant capacity (TAC) of the sample is shown in the brackets.  
\end{table} 
Table 4: Antioxidant capacity of the hydrophilic and lipophilic fractions determined by the DPPH assay (μmol TE/g DM). the same methods (r = 0.77). The total antioxidant capacity of the samples provided by the CV technique was threefold to fourfold higher than that provided by the DPPH assay and up to 13 times higher than that provided by PCL. This relationship was previously observed in thermally treated buckwheat products and buckwheat sprouts evaluated for their antioxidant capacity using both CV and DPPH assays [20; 28; 29] as well as in different types of breads [30].
# Experimental Assessment of the Spatial and Temporal Distribution of Non-Contact Tonometer Airflows
## 4 Discussion
### Clinical Implications  
When the CorvisST was first launched, it only described the dynamic corneal response to the air-puff [2]. However, over recent years there has been an increasing exploration and discussion about the use of the CorvisST to assess corneal biomechanics in-vivo [33; 34]. The Biomechanical Index (CBI) is based on corneal thickness and dynamic corneal response and showing high sensitivity and specificity to distinguish between healthy and ectatic eyes [12]. A further development of the CBI was the Tomographic Biomechanical Index (TBI), which analyses the combination of data from the dynamic response, CBI and tomographic data. The TBI has been shown to detect ectatic diseases even in milder forms [35]. The latest development was the introduction of the biomechanically corrected IOP (bIOP) and the Stress-Strain Index (SSI). The bIOP has been shown to be less effected by corneal thickness and age than the original CorvisST IOP [36]. The SSI claims to determine the biomechanical properties of the human cornea in-vivo. For this, the piston chamber pressure, as provided by the CorvisST, the corneal thickness, bIOP and the dynamic corneal response are used [3]. The CBI, TBI and the SSI evaluate the corneal response caused by the explanation of the airflow pressure from the CorvisST. However, the parameters do not consider the actual airflow pressure nor the affected corneal area by this pressure. As shown in this study, the piston chamber pressure, and the airflow pressure at an 11 mm distance differ significantly. Therefore, for future modelling studies it is of significant importance to include the airflow pressure as present on the cornea.  
The ORA determines the corneal biomechanical parameters from the piston chamber pressure at the point of the first and second explanation [25]. The corneal hysteresis (CH) is defined as the differences between the piston chamber pressure at explanation 1 and the piston chamber pressure at explanation 2. The corneal hysteresis as provided by the ORA was used to characterise the viscous damping of the corneal tissue. The corneal resistance factor (CRF) was developed empirically and claims to represent the overall resistance of the cornea against deformation [4]. Based on the results of this study, it can be assumed that the pressure applied to the cornea differs significantly from the piston chamber pressure in magnitude and shape. Studies on healthy eyes showed a high variation in those parameters [37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52]. The difference between the piston chamber pressure and the airflow pressure at an 11 mm distance can be one of the major factors contributing to such a diversity.
# Flexible UHF RFID Tag for Blood Tubes Monitoring
## 4 Fabrication and Experimental Characterization of the Proposed Tag Antenna
### Differential Radar Cross Section  
The differential radar cross section (\(\Delta\)RCS) is also an important parameter, which measures the strength of the modulated backscattered signal reradiated by the tag. It is expressed as the ratio of backscattered power of the modulated signal reflected from the tag to the incoming power received by the tag from the reader. It can be obtained from the following relationships [39]:  
\[\Delta\text{RCS}=\frac{P_{tag}(4\pi)^{3}d^{4}}{P_{r}\,G_{r}^{2}\,\lambda_{0}^ {2}}\,, \tag{4}\]  
where _Ptag_ is the power of the modulated signal received by the reader from the tag, \(d\) = 0.45 m is the distance between the tag and the reader antenna. Also, _Pr_, _Gr_ and \(\lambda\)0 were defined in (3). The measured differential radar cross section obtained for the proposed tag attached to a full and empty tube in the frequency range from 0.8 GHz and 0.9 GHz is shown in Figure 13. The peak value is \(\Delta\)RCS = -43 dBsqm at the resonant frequency of 867 MHz when the tag is attached to the tube filled with blood. Again, there is a big difference when the tag is attached to an empty tube, as the value of \(\Delta\)RCS considerably decreases to about -53.8 dBsqm at the same frequency. Note that the very small values of the differential cross section are an indication that it will be difficult to detect the tag when the tube is empty, especially in real conditions with non-negligible values of RCS noise floor level. However, the strong backscattered signal at the resonant frequency 867 MHz when the tube is full of blood leads to a maximum reading range and allows the reader to detect the backscattered signal more easily. As indicated, this may be useful in blood traceability applications, where the important information to be collected comes from tubes that are full of blood.  
Figure 12: Measured tag power sensitivity obtained for the proposed tag attached to full and empty blood tubes.
# Temporal-Guided Label Assignment for Video Object Detection
## 3 Methodology
### Temporal-Guided Label Assignment Framework  
As shown in Figure 2, the blue box above is the process of forwarding propagation. The image is sent to the backbone to obtain feature maps. Then, the feature maps are sent to the RPN to obtain the classification and coarse regression results. 'Inference' indicates the subsequent forward propagation process, which includes ROI Align and the detection head, to obtain the final detection results. The orange box below is the module for calculating the RPN loss. The label assignment adopts the automatic label assignment strategy in AutoAssign [18]. The traditional form of IOU label assignment is not used, and all locations can be positive and negative samples. We use weight maps to represent the likelihood that a sample is positive or negative.
## 3 Results  
Two hundred and nine items were initially found. One hundred sixty-four papers were excluded after title and abstract evaluation, according to exclusion criteria. Subsequently, full text assessment of the remaining 45 papers, led to the exclusion of other 35 studies because did not fulfill inclusion criteria. Finally, 10 articles published between 1983 and 2018 were selected in the current scoping review. In particular, we included three papers evaluating the efficacy and seven papers evaluating the effectiveness of physical therapy modalities in CRPS-I. Among selected studies, we found two papers regarding electromagnetic field therapy (one randomized double-blind, placebo-controlled and one randomized controlled double-blind pilot study); eight papers regarding patients receiving electrotherapy (one randomized, double-blinded, placebo-controlled prospective study; three case reports; three case series; one case-control study); two papers regarding laser therapy (one case control study; one case series). Among these papers, two studies (one case series and one case-control study) investigated the role of multiple interventions (i.e., transcutaneous electrical nerve stimulation (TENS) and laser therapy) in CRPS.  
No preclinical studies were found  
magneto-therapy on 30 patients with CRPS-I. Two groups of 15 participants each were formed. Experimental group received rehabilitation program associated to BEMER therapy for 10 consecutive days while control group received the same rehabilitation program together with a sham BEMER treatment. Outcome measures were pain (measured by VAS), upper limb function (measured by hand grip strength and disabilities of the arm, shoulder, and hand scores) and lower limb function (measured by Maryland Foot Score). After a 1-month follow-up, patients treated with BEMER combined with rehabilitation program had statistically significant pain relief (50% vs. 9%; \(p\) = 0.002) and functional improvement both for upper (46.7% vs. 31.8%; \(p\) = 0.241) and lower limbs (38.5% vs. 14.6%; \(p\) = 0.009) compared to control group.
###### Abstract  
To establish complementary information for the diagnosis and evaluation of ocular surface diseases, we developed a multi-modal, non-invasive optical imaging platform by combining ultra-high resolution optical coherence tomography (UHR-OCT) with a microvascular imaging system based on slit-lamp biomicroscopy. Our customized UHR-OCT module achieves an axial resolution of \(\approx\)2.9 \(\upmu\)m in corneal tissue with a broadband light source and an A-line acquisition rate of 24 kHz with a line array CCD camera. The microvascular imaging module has a lateral resolution of 3.5 \(\upmu\)m under maximum magnification of \(\approx\)187.5\(\times\) with an imaging rate of 60 frames/s, which is sufficient to image the conjunctival vessel network and record the movement trajectory of clusters of red blood cells. By combining the imaging optical paths of different modules, our customized multi-modal anterior eye imaging platform is capable of performing real-time cross-sectional UHR-OCT imaging of the anterior eye, conjunctival vessel network imaging, high-resolution conjunctival blood flow videography, fluorescein staining and traditional slit-lamp imaging on a single device. With self-developed software, a conjunctival vessel network image and blood flow videography were further analyzed to acquire quantitative morphological and hemodynamics parameters, including vessel fractal dimensions, blood flow velocity and vessel diameters. The ability of our multi-modal anterior eye imager to provide both structural and functional information for ophthalmic clinical applications was demonstrated on a healthy human subject and a keratitis patient.  
multi-modal imaging; UHR-OCT; microvascular imaging; ophthalmic imaging +
Footnote †: journal: Applied Soft 2020, 10, 2545; doi:10.3390/app10072545