esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
Overall, 1409 unique citations were retrieved through electronic database searches. After primary screening, 1121 citations were excluded as they did not meet inclusion criteria, and 288 citations were included in the full-text review and assessment. Of these, 67 records were included in the systematic review. Additionally, 3 studies were included from bibliographic searches. Thus, 70 unique studies were included in the final synthesis. Figure 1 illustrates the selection process according to the PRISMA flow diagram.  
Supplementary Table S2 summarizes the characteristics of the included studies. Most of the included studies were from Asia (n = 21), followed by North America (n = 15), Europe (n = 11), the rest of the world (n = 10), the Middle East (n = 9), and Africa (n = 7). While the majority of the studies were of nurses (n = 45) and nursing students (n = 23), two studies were of both nurses and nursing students (n = 2). Of the 70 included studies, the majority were cross-sectional studies (n = 54), followed by observational studies (n = 15) and RCTs (n = 1). The sample sizes across the included studies ranged from 12 [13] to 1888 [14].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & & **Inclusion Criteria** & **Exclusion Criteria** \\ \hline \multirow{8}{*}{Key outcomes} & \(\bullet\) & Knowledge of oral healthcare & \\  & & among nurses & \\  & \(\bullet\) & Attitude of nurses towards oral & \\  & & healthcare & \\  & & Barriers towards oral healthcare & \\  & & promotion & \\  & & Oral care and practices & \\  & & Trainings and resources to & \\  & & perform oral healthcare & \\ \hline \multirow{4}{*}{Study design} & \(\bullet\) & RCTs & \(\bullet\) & Abstracts \\  & \(\bullet\) & Cluster RCTs & \(\bullet\) & Editorials/commentaries/review \\ \cline{1-1}  & \(\bullet\) & Quasi-experimental studies & \\ \cline{1-1}  & \(\bullet\) & Observational studies & \\ \hline Language & & English & Non-English \\ \hline Search timeframe & Inception to present (February 2023) & Not applicable \\ \hline Any other criteria & No limits on sample size or countries & Not applicable \\ \hline \hline \end{tabular} Abbreviations: RCTs, randomized controlled trials.  
\end{table}
Table 1: _Cont._Given the enormous size of the dataset, this study focused on summarizing the evidence published in the last 10 years (i.e., 2013 to 2023). Overall, five important themes were identified from the retrieved evidence, namely, (i) knowledge of oral healthcare among nursing professionals (n = 28); (ii) attitudes of nursing professionals towards oral healthcare (n = 31); (iii) perceived barriers to oral healthcare promotion (n = 12); (iv) oral care and practices (n = 12); and (v) trainings and resources to promote oral healthcare (n = 19) (Supplementary Table S2).
# Route Optimization for UGVs: A Systematic Analysis of Applications, Algorithms and Challenges
## 4 Discussion
This emergent paradigm necessitates a focused effort on formalizing convergence guarantees for these hybrid approaches as the current lack of rigorous theoretical underpinnings limits their adoption in safety-critical applications. Future research should prioritize the development of verifiable stability criteria and performance bounds for bio-inspired and hybrid control schemes. Future robotic systems are likely to leverage the integration of quantum-optimized algorithms like DENPSO with neuromorphic computing architectures to address critical latency bottlenecks, aligning with the broader trends in accelerating robotic computation [60]. Key challenges remain in scaling bio-inspired neural networks (e.g., BINNs) for effective swarm coordination, which often suffers from scalability issues, as detailed by [61], and in mitigating the vulnerability of fuzzy logic controllers to adversarial attacks, a growing concern documented by researchers in AI safety [62]. Achieving Technology Readiness Level 6 (TRL-6) for next-generation velocity control (NGVC)-Model Predictive Control (MPC) systems by 2030, as projected by [53], necessitates strong cross-industry collaboration and sustained funding from organizations like the NSF and DARPA. This collaborative approach is vital for transforming promising lab-scale proofs-of-concept into robust and fieldable solutions, thereby bridging the gap between theoretical developments and practical deployment [63].
## 2 Materials and Methods  
### Source Materials  
Ground granulated blast furnace slag (GGBFS) was supplied by the Guangxi Guigang Iron and Steel Company. The specific surface area of the slag was determined to be 394 m\({}^{2}\)/kg, and the density was 2.91 g/cm\({}^{3}\) according to [PERSON]'s specific surface area method, after which the slag was ball-milled and sieved. The Bayer red mud used in this study was from Guangxi Province, China. The material was dried at 105 \({}^{\circ}\)C for 24 h and sieved. The specific surface area was determined to be 670 m\({}^{2}\)/kg and its density was 3.11 g/cm\({}^{3}\).  
A water glass was used as an activator, and its modulus (SiO\({}_{2}\)/Na\({}_{2}\)O molar ratio) was 1.8 in this study. It was prepared by mixing a solution of NaOH and commercial sodium silicate (modulus: 3.34) in the pre-calculated ratio. AASRs were prepared using a water glass with a (Na\({}_{2}\)O) concentration of 5 wt.% of cementitious components. Before mixing with the AASR mixture, the alkaline solution was cooled at 20 (\(\pm\)1) \({}^{\circ}\)C for 2 h to avoid the potential effect of the solution's heat on the experimental results.  
The main chemical compositions of the red mud and blast furnace slag was determined by X-ray fluorescence spectroscopy (XRF), which was done a ZSX Primus, and the results are shown in Table 1. The particle size distribution (PSD) of red mud and slag were tested by using a Morphology 4 laser diffraction analyzer, as shown in Figure 1. Those were expressed as volume percentage and cumulative volume percentage. On comparison of the base materials, RM was found to be finer than GGBFS.  
The XRD spectra of both GGBFS and RM are shown in Figure 2. It is clear that GGBFS is primarily composed of a glass phase, while the main phase compositions of RM are Hematite (Fe\({}_{2}\)O\({}_{3}\)), Katoite (Ca\({}_{3}\)Al\({}_{2}\)SiO\({}_{4}\)(OH)\({}_{8}\)), Diaspore (AlO(OH), Calcite (CaCO\({}_{3}\)) and Cancrinite (Al\({}_{6}\)C\({}_{1.44}\)H\({}_{4.88}\)Na\({}_{8}\)O\({}_{30.32}\)Si\({}_{6}\)).  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Binder** & **SiO\({}_{2}\)** & **Al\({}_{2}\)O\({}_{3}\)** & **Fe\({}_{2}\)O\({}_{3}\)** & **MgO** & **CaO** & **Na\({}_{2}\)O** & **K\({}_{2}\)O** & **SO\({}_{3}\)** & **TiO\({}_{2}\)** \\ \hline Slag & 30.79 & 13.56 & 0.96 & 8.18 & 41.59 & 0.40 & 0.46 & 2.12 & 0.94 \\ Red Mud & 13.49 & 20.39 & 30.58 & 0.32 & 15.82 & 9.15 & 0.19 & 0.66 & 7.80 \\ \hline \end{tabular}
\end{table}
Table 1: Chemical compositions of slag and red mud (wt. %).  
Figure 1: Particle size distribution of RM and GGBFS.  
Figure 2: XRD patterns of RM and GGBFS.
# Low Power Wide Area Network, Cognitive Radio and the Internet of Things: Potentials for Integration
## 7 Challenges/Future Directions of CR-LPWAN
### PHY Layer Challenges
#### 7.1.5 Incorporating Adaptive CR Technologies  
LPWAN transceivers can be integrated with adaptive CR technologies. For example, the SX1276 LPWAN transceiver is a product of Semtech's patented LoRa technology [142], which features the LoRa long-range modem and provides high immunity to interference, on top of ensuring minimal current consumption rates. An area where adaptive CR technology can be integrated is in the on-off keying (OOK) modulation module of the SX1276 transceiver. The OOK demodulator in the SX1276 chip works by comparing the RSS output with a threshold value [142]. It uses three different threshold modes, including the \"manual or fixed,\" \"peak,\" and \"average\" threshold methods, all configured using the OokThreshType instruction set [142].  
Towards incorporating CR technologies, it is required that these threshold methods be optimized to ensure that licensed signals are accurately detected. The use of adaptive threshold estimation algorithms (ATAs) is advocated in the OOK demodulator block of the SX1276. There are several ATAs available for use such as the FCME algorithm [143], the recursive onesided hypothesis testing (ROHT) algorithm [124], the first order statistical technique (FOST) [144] also called the m-dB method [145], and several other ATAs [128; 146; 132]. Nevertheless, one research issue to be addressed is the reduction in the computational complexities of these ATAs in order to reduce the power consumption rate of the SX1276 chipset. Summarily, adaptive CR technologies such as ATAs are essential in LPWAN transceivers in order to improve spectrum identification, reduce interference, and ensure effective bandwidth utilization. Some transceiver chipsets such as the ADF7241 based on IEEE 802.15.4 Zero-IF standard [147], the ATA8520 chip by Sigfox [148], the ASIC transceiver by Weightless, and the NANO-S100 by Ingenu [149], use the \"manual or fixed\" threshold method, and as such, they will largely benefit from adaptive CR technologies.
## 5 Conclusions  
In this study, the coupled relationship between the solid-phase temperature field and droplet evaporation was investigated, with a systematic exploration of the effects of substrate thermal conduction characteristics on droplet evaporation behavior. Based on the mathematical model established in the preceding sections, the impacts of substrate thermal conductivity and thickness on the evaporation rate, surface temperature, and evaporation flux of the droplet were analyzed. A dimensionless relative evaporation rate, HCs, was introduced to more accurately characterize the influence of substrate thermal conduction on droplet evaporation. The findings revealed that an increase in substrate thermal conductivity enhances the surface temperature and evaporation flux of the droplet, thereby monotonically increasing the evaporation rate until it approaches the evaporation rate of the evaporative cooling model. Conversely, an increase in substrate thickness extends the heat transfer path, reducing the heat ultimately conducted to the solid-liquid interface and thereby decreasing the evaporation rate of the droplet.  
Furthermore, the concept of equivalent substrates was proposed, wherein distinct combinations of substrate thickness and thermal conductivity yield nearly identical evaporation behaviors. Through dimensionless analysis and numerical simulations, the consistency of evaporation rates and heat transfer at the solid-liquid interface across equivalent substrates was validated, with relative errors below 0.01% for evaporation rates and 2% for interfacial heat fluxes. This confirms the existence of the equivalent substrate phenomenon.  
Finally, the influence of droplet-specific properties, such as contact angle and evaporative cooling coefficient \(Ec\), on equivalent substrates was examined. The results demonstrate the negligible effects of these parameters on the equivalence relationship, underscoring the robustness of the proposed concept. These insights provide a foundational framework for optimizing substrate design in applications requiring precise thermal management, such as microelectronics cooling and advanced manufacturing processes.  
Figure 8: The applicability of equivalent substrates after changing the evaporation cooling coefficient \(Ec\). (**a**) \(Ec=0.01\); (**b**) \(Ec=0.05\); (**c**) \(Ec=0.1\); and (**d**) \(Ec=5\).  
**Author Contributions:** Conceptualization, L.X. and X.X.; investigation, L.X. and X.X.; writing--original draft preparation, L.X.; writing--review and editing, L.X.; supervision, X.X.; project administration, L.X.; funding acquisition, X.X. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was supported by the National Natural Science Foundation of China (52375166).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in the study are included in the article. Further inquiries may be directed to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 2 Materials and Methods
### Database  
The original database consisted of cases of adults with voice disorders assessed at the Voice Care Outpatient Clinic of Edgar Santos University Hospital from January 2014 to December 2019. Each case was assigned a code to maintain anonymity. All information about the patients was available in the form of electronic medical patient records. Laryngeal diagnosis was performed by an Otorhinolaryngologist (ORL) at the Ear, Nose, and Throat Ambulatory Outpatient Clinic of Edgar Santos University Hospital. Voice assessments were performed by a speech-language pathology student under the supervision of a speech-language pathology professor from the Federal University of Bahia Department in the Voice Care Outpatient Clinic of Edgar Santos University Hospital. Standard voice assessment consisted of: (i) a patient interview; (ii) a clinical voice examination, including head and postural description, laryngeal extrinsic musculature palpation, laryngeal position, and speech articulation assessment; (iii) vocal quality analysis by CAPE-V protocol [36]; (iv) maximum phonation time measurement; (v) voice recording of CAPE-V sentences, sustained vowel /a/, and spontaneous speech; and (vi) Voice Handicap Index-10 (VHI) [37] or Voice-Related Quality of Life (V-RQOL) [38] questionnaires. It is important to highlight that these data were collected for clinical purposes, and as such they represent an outpatient sample.
# Ext-LOUDS: A Space Efficient Extended LOUDS Index for Superset Query
## 5 Conclusions and Future Work  
In view of the high space overheads of trie, in this paper, an extended LOUDS structure, Ext-LOUDS, is proposed to efficiently support superset query. Compared to a long bit vector compressed in LOUDS, Ext-LOUDS compresses a trie into 4 shorter vectors. In Ext-LOUDS, a position is its NodeID, so some key operations needed for superset query are super fast. Based on Ext-LOUDS, an efficient superset query algorithm, ELOUDS-Super, is implemented. By extensive experiments on both real and synthetic datasets, we have the following findings: (1) Ext-LOUDS can significantly reduce the space overheads while maintaining a relative good query performance. (2) Ext-LOUDS works well on EFV and datasets with duplicated sets. (3) Ext-LOUDS scales well with varied \(|\)U\(|\) and \(|\)D\(|\). As our future work, we plan to extend Ext-LOUDS to support other set containment query or similarity query. In addition, optimizing  
Figure 8: Space and time overheads for varied \(|\)D\(|\): (**a**) space overheads; (**b**) time overheads.  
Figure 9: Space and time overheads for varied \(|\)U\(|\): (**a**) space overheads; (**b**) time overheads.  
the RANK and SELECT operations in Ext-LOUDS to further improve its query efficiency will also be our future work.  
Conceptualization, L.J. and R.L.; methodology, L.J. and Y.Z.; software, L.J. and Y.Z.; validation, L.J., Y.Z. and Y.C.; writing, L.J. and Y.Z.; resources, L.J., J.D. and J.Y; review, J.D., J.Y. and Y.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China under Grant no. 61562054, China Scholarship Council under Grant no. 201908530036, the National Key Research and Development Program of China under Grant no. 2018 YFB1003904.  
There are no conflicts of interest regarding the publication of this paper.
# A Fingerprint-Based Verification Framework Using Harris and SURF Feature Detection Algorithms
## 3 Proposed Methodology
### Fingerprint Image Preprocessing
#### 3.2.4 Fourier Transform  
Fourier transform (FT) transforms an image from the spatial domain into the frequency domain, which offers better processing of images. The application of the fast Fourier transform (FFT) on a set of pixels of a small area in the image allows reconnection of broken ridges following the same FFT orientation. The image is initially divided into small processing blocks (e.g., of size 32 by 32 pixels). Blocks are generally constructed using overlapped windows to avoid the effect of borders of Fourier transform. For each \(32\times 32\) block, the FFT is applied and the bandpass Butterworth filter is used to remove a Gaussian noise. The Fourier transform of the block is then multiplied by its power spectrum to raise the image quality. Finally, the inverse fast Fourier transform (IFFT) is applied to the resulting image. The Fourier transform is defined as follows,  
\[F(u,v)=\sum_{x=0}^{M-1}\sum_{y=0}^{N-1}f(x,y)e^{-j2\pi\left(\frac{ux}{M}+\frac{ vy}{N}\right)} \tag{3}\]  
for \(u=0,1,2,\ldots,31\) and \(v=0,1,2,\ldots,31\).
# QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing
## 4 Proposed Solution
### SDN Based Smart Gateway  
Software-defined network smart gateway is a gateway that receives vehicles' messages/data and processes it according to rules embedded in it, and forwards it to other vehicles when required, and sends to the cloud or fog for storage and processing. Smart gateways are placed in fog nodes near the roadside to reduce response time.
# Microbes and Parameters Influencing Dark Fermentation for Hydrogen Production
## 4 Bacteria Used for Hydrogen Production During Dark Fermentation  
The rate of H\({}_{2}\) production by bacteria as part of their metabolism depends entirely on the conditions described above, namely pH, temperature, substrate used, HRT, and the type of bioreactor. Several bacterial species are well known for their ability to produce H\({}_{2}\) under dark fermentation conditions, including _Clostidium_ and _Enterobacter_ spp., _Escherichia coli_, and facultative anaerobes such as _Klebsiella pneumoniae_.
# Noise Reduction Using Synthetic Microjet Excitation in Supersonic Rectangular Jets
## 2 Methodology  
The current research investigates a jet noise control approach that focuses on exciting the frequency modes of coherent structures through unsteady fluidic injection directed downstream of the nozzle lip. Such excitation of the jet flow affects the instability modes near the nozzle lip. As those propagate downstream, they evolve into large turbulent structures that appear as the major sources of radiated noise.  
This section presents the numerical setup for 3D high-fidelity simulations of a rectangular jet flow subject to unsteady microjet excitation localized at the longer nozzle lip, as it was found to be the region of greater turbulent kinetic energy amplitude. A time-periodic velocity injection in the downstream direction is considered. This study focuses on a heated, supersonic, fully expanded Mach 1.5 case and compares the baseline scenario without excitation to an excited case at a forcing frequency of \(St_{F}=0.30\) but with a constant excitation velocity amplitude. The geometry and the flow condition match with a previous experiment [2; 3]. A hybrid LES-URANS approach is employed to model the flow, utilizing URANS near wall boundaries and LES in the regions of free shear flow. The analysis involves a comparison of the far-field noise and near-field parameters between the excited and non-excited cases, thus examining the effectiveness of the active noise control methodology, which was previously also explored for a rectangular jet in [33] using a coarse-grid analysis, and in [34] for a circular jet. The proposed computational setup builds on prior work involving numerical simulations of rectangular jet acoustics shielded by an airframe, which was successfully validated against experimental measurements [26].
## 3 Results and Discussions
### Impact of Meteorological Factors on Vegetation GPP
evaluates the sensitivity of forest productivity to precipitation and air temperature in inner Asian forests by using satellite remote sensing, dendrochronology and dynamic global vegetation model (DGVM) simulations, and indicated that in cool arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending the growing season length, with unclear consequences for net carbon uptake [47]. [PERSON] et al. studied the impacts of climate change on forest growth in saline-alkali land of the Yellow River Delta North China by using standard site methods and tree ring sampling, and indicated that precipitation is the main meteorological factor affecting tree growth, while temperature and air pressure are also significantly correlated with tree growth [48]. The Altay Mountains are located in the hinterland of Eurasia, far away from the sea, and have a few water vapor sources. In the situation of global atmospheric circulation, they are located in the westerly zone. The  
Figure 7: Correlation of vegetation GPP with temperature (**a**) and precipitation (**b**) in the Altay Mountains. westerly flow enters this area along the Ertish river valley, raising the condensation cloud to cause rain. Therefore, precipitation is relatively large, and has become one of the wetter regions in the Xinjiang. The variation trends of vegetation coverage in different parts of the mountain were quite different. In general, the areas where the vegetation coverage has decreased are mainly distributed in the west and middle parts of the Altay Mountains, the Piedmont of the mountains, as well as the plain areas in the southwest, central and northeast parts of the mountain.
# Force-Based Self-Organizing MANET/FANET with a UAV Swarm
## 3 Modeling MANETs
### Nodes and Clients  
We model a MANET as a dynamic network topology consisting of three types of entities: clients (mobile terminals), nodes (mobile access points for the terminals) and a root or data sink (a static point of contact to the global infrastructure).  
Nodes in the network are drone-mounted routers that can either serve as the entry point into the MANET (this service is provided to the mobile clients) or as a connection within the MANET, in which case the node simply connects two other nodes. In this case, the node is referred to as the child of its access point node and as the parent for all the nodes to which it provides access.  
Nodes have a limited range within which they can provide connectivity and the quality of the service provided deteriorates quadratically with increasing distance to the node (see Section 3.2). They further have an upper bounded bandwidth, simplified in our model as the number of connections they can serve/the number of connections they can relay. Nodes move under their own power and control, meaning that they can determine their movements themselves. They do so using the local information available to them (see Section 4.1) so their movement is a product of their internal state and their sensed environment. We assume that nodes always know their position.  
Clients are simplified as entities creating a demand for the network. We adopt the Full Buffer Model [48] which means that the number of clients in an individual cell does not change and that all clients always create a demand. Clients also can move, but their movement is determined by an outside function and is therefore not affected by the internal state of the client. Clients are also assumed to know their exact position and to communicate this to their parent node. This assumption is required to enable the drones to determine the quality of service they provide to the clients (as it is based on the distance between the two); in a real-world implementation, this signal strength received by the client could simply be communicated to the drone to achieve the same effect.