esa-sceva/satcom-chunk-collection huggingface dataset:
# Age Prediction from Korean Speech Data Using Neural Networks with Diverse Voice Features
## 4 Results and Analyses
### Evaluation Metrics  
Multiple evaluation metrics were used to assess the performance of the age prediction model. These metrics are described by Equations (4)-(7). When the model correctly predicts positive data, it is referred to as a true positive (TP). When the model incorrectly predicts data as positive that are actually negative, this is called a false positive (FP). A false negative (FN) occurs when the model predicts a negative for data that are actually positive, whereas a true negative (TN) occurs when the model correctly predicts data that are actually negative.  
\[Accuracy=\frac{TP+TN}{TP+TN+FP+FN} \tag{4}\]  
\[Precision=\frac{TP}{TP+FP} \tag{5}\]  
\[Recall=\frac{TP}{TP+FN} \tag{6}\]  
\[F1-score=\frac{2\times TP}{2\times TP+2\times FN} \tag{7}\]  
The accuracy, calculated using Equation (4), represents the proportion of correctly predicted samples out of the total samples. The precision, calculated using Equation (5), is the proportion of samples predicted to be positive that are actually positive. The recall, calculated using Equation (6), represents the proportion of actual positives that are correctly  
Figure 9: Process overview.  
predicted. Finally, the F1-score, calculated using Equation (7), is the harmonic mean of the precision and recall.
# Senti-Sequence: Learning to Represent Texts for Sentiment Polarity Classification
## 6 Discussion  
The three datasets employed differ in the number of average words per document and the number of documents. Books and IMDB datasets contain much larger documents in comparison to the Twitter dataset, as depicted in Table 2. All methods under evaluation decrease their performance on the Books dataset. This could be explained by the less amount of training data available plus the larger extension of the documents which also shows a greater variation in the polarity of the contained words. Nevertheless, it seems interesting that Senti-Sequence did not follow this pattern. In fact, the dataset having shorter documents presented more challenges to the correct classification of the method. However, the proposal attained the best F1 score. This suggests that Senti-Sequence is more sensitive to very short texts and also that it does not need very large collections.  
It is noteworthy that in the case where the documents were larger, as in IMDB and Books, Senti-Sequence outperforms the other models. An identical behavior is observed when analyzing the performance over the Twitter dataset which contains shorter documents. This suggests that the proposed method has a high and stable performance under short and long temporal dependencies in texts for sentiment classification. This may be due to the fact that the resulting vector formed by 0, 1, and \(-\)1 better simplifies the contribution of each word's polarity to capture the overall polarity in texts, contrasting with more complex word representations originally proposed for content classification. Additionally, the nonlinear mapping of the polarity of each word to a continuous value by using all of its surrounding scores eases the final discrimination task of the network. This claim is supported by the fact that no improvement is achieved when a recurrent architecture is added to a feed-forward network, but when we use a bidirectional recurrent model instead, that maps each binary polarity considering all the surrounding polarities within the document, a noticeable increase in performance is consistently observed.  
In summary, Senti-Sequence performs well over short and long text collections, without needing large amounts of text data. The experimental results suggest that the nonlinear mapping strategy enabled by a bidirectional recurrent model over word polarities is able to capture the overall sentiment of a text document expressed as a binary value. An important part of this mechanism relies on the accurate polarity prediction made by a Support Vector Machine model trained over rich word embedding collections such as ConceptNet.
# Biohydrogen from Microalgae: Production and Applications
## 2 Hydrogen Metabolism in Green Microalgae: Biophotolysis
### Photosynthetic Electrons and Hydrogenase  
The pivotal process of microalgal metabolism consists of oxygenic photosynthesis and complex redox reactions that take place at the level of the thylakoid membranes in chloroplasts through two successive phases. During the first light-depending reactions, ATP and reduced NADH, and NADPH, are generated to be involved in the next dark reactions where the atmospheric CO2 is fixed by a RuBiSco (ribulose-1,5- bisphosphate carboxylase/oxygenase) enzyme to ultimately generate energy rich-carbohydrate stores. Specifically, during the light phase, an electron transport chain is generated along with photosystems II (PSII) via the plastoquinone (PQ) pool, cytochrome b6f complex (Cyt b6f), and photosystems I (PSI) due to the light energy received as photosystems are associated with light-harvesting complexes I and II (LHC I and LHCII), consisting of numerous photoreceptive pigments. These electrons through PSI leave the electron transport chain and reach the final acceptor ferredoxin (Fd) [8; 9].  
In anoxic conditions, Fd is able to address electrons to the hydrogenase enzyme. This kind of enzyme catalyzes a reversible reaction in which hydrogen can also be split into electrons and protons:  
\[2\text{H}^{+}+\text{e}^{-}\leftrightarrow\text{H}_{2} \tag{1}\]  
Figure 1: Hydrogen production processes in microalgae.  
Hydrogenases from the green algae _Chlamydomonas reinhardtii_ are the most well-characterized among microalgae. This model organism expresses two different Fe-hydrogenases genes: _HydA1_, the isoform mainly involved under anoxic conditions, and _HydA2_[10; 11]. Hydrogenase activity is part of the various responses that microalgal organisms carry out in response to anoxic or stress conditions, and is highly regulated on several levels. After the ribosomal translation in the cytoplasm, the protein is driven to chloroplasts through a transit peptide at the N-terminal end [12]. Assembling of the protein and the catalytic center, H cluster, are required to obtain the functional 47-48 kDa enzyme. _HydEF_ and _HydG_ genes encode for maturation proteins, crucial for its activation [13]. H cluster is composed of [4 Fe4S] unit cysteine-linked to a di-iron unit able to receive electrons via Fd, but easily reversibly inactivated by oxygen [14; 15]. Evidence of hydrogen metabolism is reported also in less investigated species, such as _Scenedesmus obliquus_[16; 17], _Chlorella fusca_[18], _Chlamydomonas moewusii_, _Lobochlamys culleus_[19], _Chlorococcum littorale_[20], _Tetraselmis subordinis_[21].
# PPDC: A Privacy-Preserving Distinct Counting Scheme for Mobile Sensing
## 5 Related Work  
Recently, both the applications about mobile sensing and the problem of distinct counting have been discussed from a variety of aspects [7; 15; 16; 17; 18]. However, their scenarios usually include either privacy protection of users or distinct counting without considering them at the same time, which leads to lacking a secure and resource-saving system.
# Vibration Compensation of the Frequency-Scanning-Interferometry-Based Absolute Ranging System
## 2 Theory Background
### Method for Vibration Influence Reduction
Next, the beat signal of the measuring optical path is resampled in equal phases to remove the influence of nonlinear tuning. After the resampling process, the signal given by Equation (15) is obtained by processing \(M\) points respectively taken from the vicinity of the midpoint position of the beat signals of two adjacent periods. Subsequently, the chirp-z transform (CZT) of the signal given by Equation (15) is performed to locate the spectral peak position \(P\) of the second term accurately. Finally, using the peak frequency, the distance value, which is almost immune to vibration, is calculated by:  
\[R_{r}=\frac{\tau_{0}c}{2}=\frac{\tau_{r}(P-1)c}{2M}. \tag{16}\]
# Surface Subsidence Monitoring in Kunming City with Time-Series InSAR and GNSS
## 2 Methods
### Data Processing Flow  
In this paper, Kunming city is taken as the research object, InSAR and GNSS technologies are combined to obtain the information of surface deformation in the study area, and the temporal and spatial distribution trend of surface deformation is analyzed. The research content is mainly divided into the following four points: First, based on the GACOS-assisted SBAS-InSAR technology, the land vertical deformation field characteristics of the 2018-2020 time series in Kunming city area are obtained, and the spatio-temporal distribution is analyzed. Secondly, the vertical deformation of typical areas are analyzed. Thirdly, CORS observation data from 2019 to 2020 is utilized for networking solution and adjustment with neighboring IGS stations. Obtain the precise three-dimensional coordinates of the single-day CORS station under the framework of International Terrestrial Reference Frame 2014 (ITRF2014) and the Eurasian reference frame, transfer the velocity under the ITRF frame to the background of the Eurasian plate. The vertical velocity field of CORS station with no net rotation is obtained, and the vertical motion characteristics of CORS station is analyzed. Fourthly, compare and analyze the vertical deformation rate of CORS station and InSAR under the Eurasian reference frame. The data processing flow is shown in Figure 1.
# Machine Learning-Driven Dynamic Traffic Steering in 6G: A Novel Path Selection Scheme
## 2 Related Works
In addition, this study shifts the focus from RAT to the heterogeneity of the transport networks, composed of the terrestrial network (TN) and the non-terrestrial network (NTN); satellite and DOCSIS cable are the transport technology candidates envisioned for the 6G infrastructure. The study into NTN cooperation with the TN network progresses towards the definition of workable architecture between both. The prominent candidate of NTN technology is satellite technology, and multiple integration types are discussed in [11]. The 3 GPP in Release 17 (R17) specified the enhanced functions for the foundational technologies that include coverage and capacity. Specifically, the integrated satellite-terrestrial network (ISTN) proposed in [11] provides a novel ISTN architecture for different scenarios. Ref. [11] also highlights the challenge of coordinating unified technical standards to enable ISTN because of the uncertain time of 6G commercialization and the reconciliation efforts within the satellite industry. Ref. [12] performs a survey and highlights the challenges involved in the ISTN categorically from the network architecture, technical performance, and optimization together with the findings of key technology enablers to successfully have ISTN for 6G.
# Pas: Privacy-Preserving Authentication Scheme Based on SDN for VANETs
## 7 Discussion  
In terms of the high identity management cost and low authentication and communication efficiency, PAS adopts BLS signature mechanism and SDN to propose a privacy-preserving authentication scheme, which includes registration protocol, V2I authentication protocol, V2V authentication protocol, and vehicle revocation protocol. Compared with the traditional authentication schemes, PAS has the following advantages:  
* PAS alleviates the high computational cost and communication cost caused by certificate generation, transmission and verification, which improves authentication efficiency.
* Since the traditional schemes focus on the authentication of vehicle identity and ignore the establishment of a secure tunnel for reliable data transmission, PAS requires the ve  
Figure 10: Packet loss ratio of each scheme.  
Figure 9: Average authentication delay of each scheme.  
hicle to store the key negotiation parameters in a signed message. Once authenticated, the vehicle assumes that the message can be sent and received safely and reliably.
* By integrating SDN, it is more convenient to dynamically update the public keys of vehicles, which improves the flexibility of vehicle management. However, in order to support the large-scale deployment of VANETs, there are several problems that must be addressed.
* Multi-hop packet routing and forwarding mechanism--As the vital part of data transmission in VANETs, multi-hop packet routing and forwarding mechanism supports vehicles to interact with other vehicles across a wider range. However, due to the high-speed of vehicles and the rapid change in network topology, it is difficult to find an appropriate intermediate node for data transmission between the source node and the destination node, resulting in unstable communication between vehicles with a long distance between them. As a result, establishing a new multi-hop packet routing and forwarding mechanism to improve the stability of data transmission and ensure the reliability of data is very important for the rapid promotion of VANETs.
* Pseudonym change mechanism--In order to protect the location privacy, the vehicles need to periodically change their identity to prevent the tracking from adversaries. However, the traditional pseudonym change schemes are severely limited by the environment in which the vehicles are located, and cannot change the pseudonym in areas with low vehicle density safely. Therefore, proposing an efficient pseudonym change scheme is crucial to protect the location privacy of vehicles.
* Data-sharing mechanics--The data-sharing mechanism supports the vehicles to obtain the required data in time and improves the driving experience. However, it is easy for the adversaries to forge the shared data and confuse the surrounding vehicles in VANETs. The traditional data-sharing mechanisms usually face the problems of complex access control mechanism and low efficiency of data sharing. Therefore, designing a secure and efficient data-sharing mechanism is very important to support the rapid development of VANETs.
# De Novo Transcriptome Identifies Olfactory Genes in _Diachassimomorpha Ionigicaudata_ (Ashmead)
###### Abstract  
_Diachassimomorpha Ionigicaudata_ (Ashmead, _D. longicaudata_) (Hymenoptera: Braconidae) is a solitary species of parasitoid wasp and widely used in integrated pest management (IPM) programs as a biological control agent in order to suppress tephritid fruit flies of economic importance. Although many studies have investigated the behaviors in the detection of their hosts, little is known of the molecular information of their chemosensory system. We assembled the first transcriptome of _D. longicaudata_ using transcriptome sequencing and identified 162,621 unigenes for the Ashmead insects in response to fruit flies fed with different fruits (guava, mango, and carambola). We annotated these transcripts on both the gene and protein levels by aligning them to databases (e.g., NR, NT, KEGG, GO, PFAM, UniProt/SwissProt) and prediction software (e.g., SignalP, RNAMMER, TMHMM Sever). CPC2 and MIREAP were used to predict the potential noncoding RNAs and microRNAs, respectively. Based on these annotations, we found 43, 69, 60, 689, 26 and 14 transcripts encoding odorant-binding protein (OBP), chemosensory proteins (CSPs), gustatory receptor (GR), odorant receptor (OR), odorant ionotropic receptor (IR), and sensory neuron membrane protein (SNMP), respectively. Sequence analysis identified the conserved six Cys in OBP sequences and phylogenetic analysis further supported the identification of OBPs and CSPs. Furthermore, 9 OBPs, 13 CSPs, 3 GRs, 4 IRs, 25 ORs, and 4 SNMPs were differentially expressed in the insects in response to fruit flies with different scents. These results support that the olfactory genes of the parasitoid wasps were specifically expressed in response to their hosts with different scents. Our findings improve our understanding of the behaviors of insects in the detection of their hosts on the molecular level. More importantly, it provides a valuable resource for _D. longicaudata_ research and will benefit the IPM programs and other researchers in this filed.  
_Diachassimomorpha Ionigicaudata_; Ashmead; parasitoid wasps; transcriptome; olfactory protein; odorant-binding protein; chemosensory protein +
Footnote †: journal: Journal of the American Journal of Research
# Effect of Radial Height of Helical Static Blade on the Cavitation Performance of Inducer
## 4 Results Analysis
### Analysis of Simulation Results
#### 4.2.3 Critical Cavitation Number  
Figure 10 shows the change in the critical cavitation number under different radial heights. It can be seen that when the radial height \(k\) is from 0.05 to 0.125, the corresponding critical cavitation number is below the case of the separate inducer, which means the inducer can operate under the more serious cavitation condition with the help of a helical static  
Figure 8: Velocity and streamline distribution under different radial height.  
blade. As the radial height continues to increase, the critical cavitation number gradually rises, and the cavitation performance continuously declines. Therefore, in a certain range of radial height, the helical static blade helps to improve the cavitation performance of the inducer.
# Toward Scalable Video Analytics Using Compressed-Domain Features at the Edge
###### Abstract  
Intelligent video analytics systems have come to play an essential role in many fields, including public safety, transportation safety, and many other industrial areas, such as automated tools for data extraction, and analyzing huge datasets, such as multiple live video streams transmitted from a large number of cameras. A key characteristic of such systems is that it is critical to perform real-time analytics so as to provide timely actionable alerts on various tasks, activities, and conditions. Due to the computation-intensive and bandwidth-intensive nature of these operations, however, video analytics servers may not fulfill the requirements when serving a large number of cameras simultaneously. To handle these challenges, we present an edge computing-based system that minimizes the transfer of video data from the surveillance camera feeds on a cloud video analytics server. Based on a novel approach of utilizing the information from the encoded bitstream, the edge can achieve low processing complexity of object tracking in surveillance videos and filter non-motion frames from the list of data that will be forwarded to the cloud server. To demonstrate the effectiveness of our approach, we implemented a video surveillance prototype consisting of edge devices with low computational capacity and a GPU-enabled server. The evaluation results show that our method can efficiently catch the characteristics of the frame and is compatible with the edge-to-cloud platform in terms of accuracy and delay sensitivity. The average processing time of this method is approximately 39 ms/frame with high definition resolution video, which outperforms most of the state-of-the-art methods. In addition to the scenario implementation of the proposed system, the method helps the cloud server reduce 49% of the load of the GPU, 49% that of the CPU, and 55% of the network traffic while maintaining the accuracy of video analytics event detection.  
video coding; compressed-domain analysis; motion vectors; object tracking; edge computing; cloud computing +
Footnote †: journal: Applied  
19 August 2020; 10, 6391; doi:10.3390/app10186391
# Application of Polymers as a Tool in Crystallization--A Review
## 4 Summary and Conclusions
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type of Process** & **Polymer Used as Tool** & **Crystallized Substance** & **Reference** \\ \hline Microporous poly(vinylidene fluoride) membranes & hen egg white lysozyme & [22] \\ \hline Poly(acrylic acid), poly(sodium 4-styrenesulfonate), & & \\ poly(allylamine hydrochloride), & & \\ poly(ethyleneimine), polyamide pellets & & \\ \hline Polyethylene, polypropylene, polyvinyl chloride, & & \\ poly(vinyl alcohol), polystyrene, poly(4-aminostyre) & Benzocaine, 1,1\({}^{\prime}\)-bi-2-naphth & [24] \\ \hline Siloxane templates & Diphenylurea & [25] \\ \hline Polyethylene, polyvinyl chloride, polycarbonate, & & \\ PET, nylon 66, ethylene vinyl alcohol, cellulose & CaCO\({}_{3}\) & [26] \\ acetate, poly(methyl methacrylate) & & \\ \hline Nanocomposites & PET & [27] \\ \hline
2-((4-vinylphenyl)amino)-benzoic acid/divinylbenzene copolymer, hydroxyethyl methacrylate/divinylbenzene copolymer, & & \\ methacrylate/divinylbenzene copolymer, & & \\ hydroxyethyl methacrylate/divinylbenzene copolymer & & \\ copolymer & & \\ \hline Nylon 66, polyester, polypropylene & paracetamol & [60] \\ \hline
2-hydroxyethyl cellulose & paracetamol & [61] \\ \hline Functionalized Merrifield Resin & paracetamol & [62] \\ \hline Cross-linked terpolymers in which one component & & \\ is the cross-linker & & \\  & & \\  & & \\  & & \\ \hline poly(vinyl alcohol) & Aspirin, indomethacin & [64] \\ \hline Poly(acrylic acid) films crosslinked with & & \\  & divinylbenzene & Aspirin & [66] \\ \hline Poly(4-acrylomorpholine) and poly(2-carboxyethyl & Aspirin & [67] \\ acrylate), each cross-linked with divinylbenzene & & \\ \hline poly(styrene-co-chloromethylstyrene) & Pyrazinamide, & [78] \\ \hline Ethyl cellulose & Agomelatine Form I & [86] \\ \hline cellulose nanocrystal/poly(2-hydroxyethyl & & \\ methacrylate), cellulose & & \\ nanocrystal/poly(2-hydroxyethyl & CaCO\({}_{3}\) & [96] \\ methacrylate-co-acrylic acid) & & \\ \hline Poly(methyl methacrylate) & Pervoskite & [103] \\ \hline Polyacrylamide & CdS & [105] \\ \hline Highly carboxylated polystyrene latex & Calcium silicate hydrate & [107] \\ \hline Poly(lactic acid) & ZnO & [114] \\ \hline Acrylamide, poly(ethylene glycol)dimethacrylate & Lysozyme, concanavalin A & [116] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Crystallization on polymeric surfaces/nucleation induction: Polymers and crystallized substances.