esa-sceva/satcom-chunk-collection huggingface dataset:
# Raman Spectroscopy to Monitor the Delivery of a Nano-Formulation of Vismodegib in the Skin
## 3 Results and Discussion  
### Transfersomes Characterization  
The loading of VDG did not alter the Z-average nor the zeta potential of the transfersomes (Table 1). Both formulations presented a unimodal distribution of size and a polydispersity index (PDI) < 0.100. The final molar ratio between VDG and lipids was 1:12.5.  
Since VDG is a lipophilic drug, it inserts into the transfersome phospholipid bilayer. A MC540 probe is useful to assess the phospholipid packing in bilayers by measuring its partition as a monomer between polar and non-polar environments [16], the external aqueous phase, and the transfersome's membrane, respectively. The MC540 locates as a monomer slightly above the domain of the glycerol of the backbone of neutral and charged phospholipids [17]. For this reason, MC540 is sensitive to structural variations in the head group region. The loading of VDG into the transfersomes did alter the PC of MC540 (**_p_ < 0.002), increasing the PC value with respect to the empty transfersomes. A higher PC value corresponds to increased incorporation of the probe into the membrane. Therefore, VDG could favor the loss of packing of the head group of phospholipids.  
On the other hand, Laurdan is useful to determine the phase state of the bilayer, because the GP function (for excitation and emission) acts as a fingerprint to discriminate among different membrane phase state scenarios [18]. The incorporation of the drug did not alter the phase state of the bilayers as expected after the results with MC540 (Figure 1). The curves corresponding to the GP spectra of excitation and emission are typical of a liquid-crystalline phase. Since the transition temperature between the gel and liquid-crystalline phase is around \(-20\,^{\circ}\)C for SPC, and the presence of VDG favored the loss of packing as observed with MC540, transfersomes continued to be in the liquid-crystalline phase after incorporation of the drug.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample** & **Z-Average (nm) \({}^{\text{a}}\)** & **Zeta Potential (mV) \({}^{\text{a}}\)** & **Molar Ratio (VDG:SPC)** & **MC540 CP (A570/A530) \({}^{\text{a}}\)** \\ \hline T & \(111.0\pm 1.8\) & \(-20.3\pm 1.2\) & - & \(0.94\pm 0.01\) \\ \hline T + VDG & \(114.3\pm 1.1\) & \(-18.5\pm 0.8\) & 1:12.5 & \(1.00\pm 0.01\) \\ \hline \hline \end{tabular} \({}^{\text{a}}\) Mean \(\pm\) SD (**_n_ = 3).  
\end{table}
Table 1: Physicochemical parameters of the empty and VDG-loaded transfersomes.  
Figure 1: Laurdan excitation and emission GP spectra of empty transfersomes (T) and VDG-loaded transfersomes (T + VDG) at \(25\,^{\circ}\)C. The curves consist of the averages of three independent measurements.
# Review of Remote Sensing Methods to Map Coffee Production Systems
###### Abstract  
The coffee sector is working towards sector-wide commitments for sustainable production. Yet, knowledge of where coffee is cultivated and its environmental impact remains limited, in part due to the challenges of mapping coffee using satellite remote sensing. We recognize the urgency to capitalize on recent technological advances to improve remote sensing methods and generate more accurate, reliable, and scalable approaches to coffee mapping. In this study, we provide a systematic review of satellite-based approaches to mapping coffee extent, which produced 43 articles in the peer-reviewed and gray literature. We outline key considerations for employing effective approaches, focused on the need to balance data affordability and quality, classification complexity and accuracy, and generalizability and site-specificity. We discuss research opportunities for improved approaches by leveraging the recent expansion of diverse satellite sensors and constellations, optical/Synthetic Aperture Radar data fusion approaches, and advances in cloud computing and deep learning algorithms. We highlight the need for differentiating between production systems and the need for research in important coffee-growing geographies. By reviewing the range of techniques successfully used to map coffee extent, we provide technical recommendations and future directions to enable accurate and scalable coffee maps.  
c 2020, 12, 2041; doi:10.3390/rs12122041
## 4 Numerical Results  
Numerical tests were conducted on a small test network and on two real-scale networks (an urban and a rural network). Each network, by means of the graph theory, was represented as a set of links and nodes. The links represent the phases of the trips (as for instance, the roads) and the nodes represent the transitions between two consecutive links. Among the nodes, it is possible to identify the centroid nodes that represent the origin and destination of each trip.
# Smart Meter Gateways: Options for a BSI-Compliant Integration of Energy Management Systems
### Smart Meter Gateways  
SMGWs act as intermediary between the following three network areas through which they are connected to other devices and stakeholders [7]:  
* _Home Area Network_ (HAN): This network area is for the communication between the SMGW and Controllable Local Systems (CLSs) such as controllable devices or EMSs.
* _Local Metrological Network_ (LMN): This network area is for the communication between the SMGW and and _Smart Meters_.
* _Wide Area Network_ (WAN): This network area is for the communication between the SMGW, the associated EMPs and the _SMGW Administrator_.  
_SMGW Administrators_ are defined as trustworthy entities that are able to manage the encrypted and authenticated transport channels the SMGW uses to communicate with endpoints in the above network areas. Relying on a public key infrastructure (PKI) operated by the _German Federal Office for Information Security_ (\"Bundesamt fur Sicherheit in der Informationstechnik\", BSI) [9], this is realized via _Communication Profiles_ described in Section 3.
# The Effects of High-Performance Cloud System for Network Function Virtualization
## 4 Experiments and Evaluations  
In NFV applications, network performance is a critical concern, and enhanced technologies are proposed to improve packet processing. These technologies bring different effects of performance improvement to a cloud system. This section firstly verifies the functional operations of OpenStack cloud and then evaluates the performance of the clouds with different network enhancement techniques. Lastly, the vIMS application is deployed to validate effective performance. The cloud system applying the OVS networking is a generic case to act as the baseline in the experiment. To further improve the performance, the cloud system enables CPU pinning and hugepages while applying network-accelerating technologies such as OVS-DPDK or SR-IOV.
## 3 Materials and Methods
### Methodology  
This subsection contains an explanation of various phases of the methodology and the approaches used in each phase.  
The sequential workflow of the methodology along with the methods, algorithms, and state of data in each phase is illustrated in Figure 1. The workflow starts from dataset extraction from Twitter into the \"online-education-during-COVID-19 dataset\". The next phase is cleaning the dataset using several preprocessing steps, followed by a lexicon-based approach to annotate the data using corresponding sentiment labels. The labeled dataset is further divided into training and testing sets for machine learning models train and test process, respectively. In this regard, BoW and TF-IDF features are used. A brief description of each of these phases is given in the following sections.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**User** & **Location** & **Tweets Text** \\ \hline educationblog & USA & \#EDUCATION: \#Children read longer \#books of greater difficulty during \#lockdown periods last year, and reported tha\#\textless{}1  [[https://t.co/S9](https://t.co/S9) UbQtKWZL]([https://t.co/S9](https://t.co/S9) UbQtKWZL) (accessed on 1 September 2021) \\ \hline Student & Gujarat, India & We havenot been given online education,so we r in severe depression \\ \hline brenda11831 & USA & 8.4 million fewer jobs than in February 2020, just before \#coronavirus shut down large swaths of the U.S. economy\#\textless{}1  [[https://t.co/DevQfUWDMW](https://t.co/DevQfUWDMW)]([https://t.co/DevQfUWDMW](https://t.co/DevQfUWDMW)) (accessed on 1 September 2021) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Sample tweets from the collected dataset.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**User** & **Text** & \
\begin{tabular}{l} **Polarity** \\ **Score** \\ \end{tabular} &
\begin{tabular}{l} **Sentiment** \\ \end{tabular} \\ \hline NEC\_Education & functional skill key open opportunity wide range career include apprentice & \(-\)0.05 & \(-\)1 \\ \hline Tutor\_eduonix & join free live workshop COVID-19 mental health amp mindful & 0.145 & 1 \\ \hline PrincipalTam & education around learn credible source poor & 0.0 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Sentiment score assigned by TextBlob.
# Onboard Processing in Satellite Communications Using AI Accelerators
This paper identifies the key performance indicators (KPIs) for AI/ML processing onboard SatCom systems, defines a reference architecture, analyzes different use scenarios, and assesses the hardware landscape for current and next-generation commercial AI processors. The main contributions of the paper are as follows:  
* The critical requirements for onboard AI/ML processing include power consumption, latency, and accuracy. * Usage scenarios for onboard AI/ML processing are identified and discussed, including applications in communication satellites. * Three scores for comparing the applicability of onboard AI/ML processing are defined, including the onboard applicability, the AI gain, and the complexity. These scores provide a quantitative measure of the suitability of various scenarios where AI chipsets can be used for onboard AI/ML processing. * The authors present a comprehensive review of commercial AI chipsets and compare their specifications concerning the applicability of onboard AI/ML processing. Overall, this paper thoroughly analyzes the current state of the art in onboard AI/ML processing, and identifies key considerations for its implementation in communication satellites. It also presents a useful framework for comparing and evaluating the suitability of different AI chipsets for onboard AI/ML processing. The remainder of the paper is divided as follows. In Section 2, we present the KPIs and architecture required for AI processing implementation onboard the satellite. Section 3 evaluates the applicability in different use cases, Section 4 evaluates commercial AI chips for implementation, and Section 5 presents the conclusions and challenges.
# Ecosystem Water Use Efficiency in the Three-North Region of China Based on Long-Term Satellite Data
## 4 Discussion  
### Comparisons of WUE over China  
WUE is the ratio of GPP and ET, suggesting that both GPP and ET are potential control factors. For example, GPP is found to be the main control factor in humid regions, as the growth of GPP may be much larger than that of ET [10], suggesting that GPP variation trends are very similar to those of WUE [46], which is consistent with this study. Previous studies globally [47; 48; 49], in China [20; 50; 51], and in parts of China [31; 32] have suggested that the overall average WUE ranges from 1.0 to 2.4 g\(\cdot\)C\(\cdot\)m\({}^{-2}\).mm\({}^{-1}\). Our results are different from most previous studies, as barren lands occupied 41.01% of the total research areas with very low WUE (less than g\(\cdot\)C\(\cdot\)m\({}^{-2}\).mm\({}^{-1}\)), making the WUE values of the whole research region very low. However, the total small increasing trend (0.002 g\(\cdot\)C\(\cdot\)m\({}^{-2}\).mm\({}^{-1}\).y\({}^{-1}\)) was very similar to previous studies [51; 52]. These results suggested that there was large spatial diversity of WUE in different regions. However, the overall WUE is increasing slowly.
## Results
### Convergence  
For each repetition, the number of iterations needed for convergence, \(T\), was saved. Median values of \(T\) for synthetic datasets were: 19 for K-medians, 19 for K-means, and 21 for K-spatialmedians. K-spatialmedians requires slightly more iterations than K-means and K-medians. In practice, the effect of the total running time between \(T=19\) and \(T=21\) is negligible. For real datasets, median values of \(T\) are again similar: 15 for K-medians, 17 for K-means, and 16 for K-spatialmedians. K-means performs slightly worse than the robust K-medians and K-spatialmedians for real datasets. It is known that K-means is sensitive to noise, which could explain these results. Overall, based on the median values of \(T\), there seems to be no practical difference between the convergence of K-medians, K-means, and K-spatialmedians.  
We plotted and analyzed the median of \(T\) as a function of \(K\) for each dataset separately in order to compare the convergence characteristics of K-means, K-medians, and K-spatialmedians. The most relevant plots are shown in Figure 11. Even though the median values of \(T\) are close to each other in general, there are some interesting differences with multiple datasets.  
From Figure 11, we can observe that the robust location estimates, median and spatial median, clearly converge faster than the mean for the S4 dataset, which has highly overlapping clusters. For the USPS dataset, K-medians seems to converge slightly faster than K-means. In the figure, plots for datasets _b2-sub-5_, _b2-sub-10_, _b2-sub-15_, and _b2-sub-20_ show that K-means converges faster than K-medians and K-spatialmedians when \(K\) is smaller than the number of clusters in the dataset. This might be because the mean location estimate is more sensitive to movement towards the center of multiple combined clusters than the robust location estimates since outlying points within a cluster affect it more than the robust location estimates. The plots of datasets G2-2-10 and G2-64-10 demonstrate how the curse-of-dimensionality greatly affects K-medians when compared to K-means and K-spatialmedians. K-medians converge faster than K-means and K-spatialmedians in the 2-dimensional case; however, from the 64-dimensional case onward the reverse is observed.
## 7 Traditional Sound Ray Tracing Model and Slant Distance Correction  
In the USBL positioning system, the slant distance from the underwater target to the ultra-short baseline system is calculated by using the signal transmitting and receiving technique. The three-dimensional position coordinates of the underwater target are obtained by using the trigonometric functions to calculate the slant distance and azimuth angle. This work mainly describes the effect of correcting the slant distance to optimize the positioning of the USBL.  
In underwater acoustic positioning, the traditional method to find the slant distance is to use the propagation time \(T\) and propagation speed \(c\) of acoustic signal to obtain a direct distance \(l\) between the transponder and transmitter. The traditional method considers the sound speed is a constant value and the sound wave is set to propagate at an incident angle \(\theta\) (which is also considered as the initial angle in the method below), then, it can be written that  
\[l=c\cdot T=\frac{H}{\cos\theta} \tag{25}\]  
where \(H\) is the vertical height of the underwater target from the transmitter. The model of the traditional acoustic correction method is shown in Figure 7.  
Figure 6: Combined ray tracing method.  
In actual situations, a sound wave does not propagate along a straight line in the shallow sea area, and its propagation path is always bent towards the direction in which the speed of sound decreases. Therefore, the ray tracing method described above can be used to approximate the actual propagation path of a sound wave using the section of a polyline or an arc. The horizontal distance \(X\) from transceiver head to the underwater target is obtained by summing up the layer by layer  
\[X=\sum_{i=1}^{n}x_{i}=\sum_{i=1}^{n}z_{i}\cdot\tan\theta_{i} \tag{26}\]  
First, it is needed to calculate \(\theta_{i}\)\((i=1,2,\cdots,n)\) using Equation (13), and the total horizontal distance \(X\) using Equation (26). In the USBL, the depth difference \(H\) between the transceiver head and the underwater target can be measured by the depth sensor, and the Pythagorean theorem can be used to obtain a more realistic slant distance between transceiver head and the underwater target \(\hat{l}\), where  
\[\hat{l}=\sqrt{X^{2}+H^{2}} \tag{27}\]
## 1 Introduction
### Notation and Conventions  
The present paper assumes electromagnetic fields oscillating proportional to \(\mathbf{e}^{\mathrm{i}\omega t}\). This time convention implies that the imaginary part of the relative permittivity \(\varepsilon_{r}\) must be negative for a passive dielectric material. The vacuum wavenumber is defined by \(k=\omega\sqrt{\mu_{0}\varepsilon_{0}}\) where \(\mu_{0}\) and \(\varepsilon_{0}\) denotes the permeability and permittivity in vacuum, respectively. The transverse wavenumber is denoted by \(k_{\mathrm{t}}\) and longitudinal wavenumber is defined by \(k_{z}=\sqrt{\omega^{2}\mu_{0}\mu_{r}\varepsilon_{0}\varepsilon_{r}-k_{ \mathrm{t}}^{2}}\). The real and imaginary parts of any complex number \(\xi\) are, respectively, denoted by \(\Re(\xi)\) and \(\Im(\xi)\).
# A Review of Abnormal Crowd Behavior Recognition Technology Based on Computer Vision
## 4 Research Status of Abnormal Crowd Behavior Recognition
### Traditional Methods  
This subsection classifies traditional abnormal behavior recognition methods into the following categories according to the detection principle: abnormal behavior recognition methods based on statistical models, based on motion features, based on dynamic models, and based on clustering discrimination. Most traditional abnormal behavior recognition methods first construct a normal behavior model through visual feature extraction and motion pattern analysis and then perform abnormal behavior recognition by calculating the statistics of features and setting thresholds.
## 2 Materials and Methods
### Modulation and Coding (MODCOD) Concept and ACM Technique Based on DVB-S2X  
The concept of MODCOD is based on the rational application of highly efficient and enhanced modulation for non-linearities, combined with efficient channel error correction codes [26]. Well-recognized techniques for high data rate (HDR) are based on the proper use of the MODCOD concept.  
Especially, the Low-Density Parity Check (LDPC) code followed by the Amplitude-Phase Shift Keying (APSK) modulation will be the next-generation basis for HDR downlink [27] under the DVB-S2X standard [28].  
In short, DVB-S2X is the second-generation extensions standard for Digital Video Broadcasting. This modulation-coding format for high data rate telemetry [29] is based on LDPC codes combined with eight selected modulation formats (QPSK, 8 PSK, SAPSK, 16 APSK, 32 APSK, 64 APSK, 128 APSK, and 256 APSK) and a wide range of code rates (1/4 to 9/10), ranging in spectral efficiency from 0.49 bit/s/Hz to 5.84 bit/s/Hz. As an example, the DVB-S2X 32 APSK constellation is shown in Figure 3.  
Thus, in the satellite context, the onboard computer receives the remote control to change the ACM mode parameters (MODCOD) from the Control and Tracking Centre through a continuous feedback link; the ground station reception system, ERG, performs real-time detection and monitoring of the energy per bit, \(E_{b}\), to interference, \(I_{0}\), plus noise, \(N_{0}\), spectral power densities, \((E_{b}/(I_{0}+N_{0}))\), information that induces the onboard transmitter itself to make the necessary adaptations.  
Figure 3: Bit-mapping constellation for the 32 APSK modulation.  
Figure 2: Representation of underlay paradigm. Source: adapted from [11].  
The ACM technique can benefit cognitive satellite applications when combined with a CR method. Both concepts show how this new strategy can achieve better bandwidth and RF power efficiencies.
# Volatile Freight Rates in Maritime Container Industry in Times of Crises
## 3 Maritime Container Market and the Freight Rates in Times of Crises
### Freight Rates on the Maritime Container Market in Times of Crises
It is expected that the freight rates for ocean shipping, together with air transport, will skyrocket. This actually projects another blow to the already shaken global supply chain [56]. Estimations regarding percentage changes in prices for individual countries' categories are presented in Figure 5. Underdeveloped countries can expect the increase in the prices of imported goods by 8.7%. The biggest increase, both of consumer and import prices, is estimated for small island countries in development. Whereas the estimated increase on the global level is 10.6% on average, small island countries are facing increases as high as 24.2%. Additional obstruction to the reduction in the freight rates in the maritime container industry are demands for the reduction in the greenhouse gases emissions of marine fuels. The initial IMO strategy on reduction of greenhouse gas (GHG) emissions from ships was adopted in April 2018 by the International Maritime Organization--the United Nations' specialized agency for international shipping. The goal has been to reduce total annual GHG emissions by at least 50% by 2050, compared to the year 2008. This is in line with the provisions laid down in the Paris Agreement [57]. However, if the activities are left as they are, with no further efforts to reduce the emissions, it is expected that they increase by between 90% and 130% by 2050 compared to 2008 [58]. To make sure that these predictions do not come true, additional measures to reduce GHG emissions from shipping will have to be adopted. Figure 5: Simulation of the effects of current freight rates on the maritime container market on import and consumer prices. Source: compiled by the author according to [13]. The strategy laid down in 2018 provides a list of short, mid and long-term measures that can be implemented to mitigate climate change. When preparing the document and the measures, the IMO took into account the needs of the developing countries, especially Small Island Developing Countries and Least Developed Countries (LDCs) and conducted an assessment of their short-term measures. This assessment showed that the effects the measures would have on the maritime industry and the costs are relatively small in relation to usual volatility of the freight rates [59].