esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
With the widespread application of facial image-based age estimation technologies in fields such as marketing, medical aesthetics, and intelligent surveillance, their importance has become increasingly evident. However, in real-world scenarios, the facial images obtained are often incomplete due to occlusions caused by masks or sunglasses, which obscure the eyes, mouth, or nose to varying degrees. Such occlusions lead to the loss of critical facial feature information, thereby reducing the accuracy of age estimation. Although prior research has explored de-occlusion methods for occluded facial images, there remains a lack of studies focusing on the implicit facial feature information present in fixed occlusion patterns. To address this issue, this study proposes a novel method for reconstructing occluded facial features to enhance age estimation accuracy under occlusion conditions. This study introduces a facial feature reconstruction network based on knowledge distillation and feature reconstruction. The primary objective is to leverage complete facial information from a teacher model to guide a student network in fully extracting effective information from the unoccluded regions of occluded images. Additionally, the proposed method reconstructs feature maps of the occluded regions through a meticulous, layer-wise feature reconstruction process. The reconstructed network can then act as a feature encoder to provide more informative features for the age estimation regression module. Experimental results demonstrate that the proposed approach achieves superior performance in age estimation with randomly occluded images on the MORPH-2, AFAD, CACD, and IMDB-WIKI datasets, with mean absolute errors (MAE) of 4.27, 4.83, 5.15, and 5.71, respectively. These results outperform existing occluded facial age estimation methods based on attention mechanisms and generative facial image reconstruction.  
k +
Footnote †: journal: Applied Sciences
# Flying Ad Hoc Networks: A New Domain for Network Communications
## 1 Introduction
Numerous proposals have been introduced by researchers to address these challenging themes. We describe, classify, and qualitatively compare those proposals, suggesting a clear taxonomy for each topic. Then, we contribute to the advance of the state of the art by measuring the impact of an unmanned aerial vehicle on the on-board \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Characteristics** & **MANET** & **VANET** & **FANET** \\ \hline Node Mobility & Lower (2-D) & Low (2-D) & RW-UAV: High (3-D) \\  & & & FW-UAV: Medium (3-D) \\ \hline Node Speed & Lower (6 km/h) & Medium-High & RW-UAV: Medium (50 km/h) \\  & & (20–100 km/h) & FW-UAV: High (100 km/h) \\ \hline Mobility Model & Random & Manhattan models & RW-UAV: RPP [17] \\  & & & FW-UAV: PPRZM [18]/ST [19] \\ \hline Topology Change & Low & Medium & High \\ \hline Energy Constraints & Medium & Low & RW-UAV: High (15–30 min) \\  & & & FW-UAV: Medium (to 5 h) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of MANET, VANET, and FANET. Figure 1: An example of communication links in a FANET using the 5 GHz band for U2U communication and the 2.4 GHz band for U2G coverage. WiFi radiation pattern. To do so, we conduct a set of experiments in a controlled environment, a radio-frequency (RF) anechoic chamber, to obtain the RP of a WiFi communication module embedded in a UAV. From the results, we quantify the effect (if any) of the UAV engines (revolutions per minute (RPM) and vibrations produced in the chassis and antennas), the UAV propellers, and the UAV chassis on the RP. In light of these outcomes, we show the conditions that should be met to assume that an UAV has an isotropic RP, or (at least) a constant RP. Therefore, we provide a basis to simplify radiation studies and to obtain more accurate experimental results in future related works. The rest of the paper is organized as follows. In Section 2 the revision of the state of the art is presented and discussed. The case study is detailed in Section 3. The paper ends with a conclusion in Section 4.
## 4 The Data-Collection, Processing, and Display Software
### Equipment Configuration  
CDAP's configuration files are pre-set to contain operating parameters, serial numbers, and other information to define the appropriate operating conditions for all instruments and to initialize their operating state. The software can also be set to support single-head (one radiometer) or dual-head operation (two radiometers to capture both upwelling and downwelling radiation simultaneously). Parameters modeling the characteristics of reflective reference panels are included to correctly provide a full-brightness baseline during calibration.  
Figure 5: Hercules Instrument Box (HIB) and components.
# Control Strategy of In-Port U-Turn for Ships Based on Arctangent Function Nonlinear Feedback
## Appendix A Calculation of Hydrodynamic Derivatives  
The dimensionless calculation formulas for hydrodynamic derivatives are given in Equation (A1):  
\[X^{\prime}=\frac{X}{\frac{1}{2}\rho L\
u V^{2}}\quad Y^{\prime}=\frac{Y}{ \frac{1}{2}\rho L\
u V^{2}}\quad N^{\prime}=\frac{N}{\frac{1}{2}\rho L^{2} \
u V^{2}}\] (A1)  
The dimensionless calculation formulas for hydrodynamic derivatives are given in Equations (A2)-(A5):  
\[\begin{array}{l}Y^{\prime}_{\rm p}=-\left(\frac{\pi}{2}\lambda+1.4C_{b} \frac{B}{L}\right)\left(1+0.67\tau^{\prime}\right)\\ Y^{\prime}_{r}=\frac{\pi}{4}\lambda(1+0.8\tau^{\prime})\\ N^{\prime}_{\rm p}=-\lambda\left(1-0.27\frac{\tau}{L_{\rm p}}\right)\\ N^{\prime}_{r}=-\left(0.54\lambda-\lambda^{2}\right)\left(1+0.3\tau^{\prime}\right) \end{array}\] (A2)  
\[\begin{array}{l}X^{\prime}_{v\rm p}=0.4\frac{B}{L}-0.006\frac{L}{d_{m}}\\ X^{\prime}_{vr}=my(1.11C_{b}-0.07)-m_{y}\\ X^{\prime}_{rr}=0.0003\frac{L}{d_{m}}\end{array}\] (A3)  
\[\begin{array}{l}Y^{\prime}_{[\rm ss,|v]}=0.048265-6.293(1-C_{b})\frac{d_{m} }{B}\\ Y^{\prime}_{|r|r}=0.0045-0.445(1-C_{b})\frac{d_{m}}{B}\\ Y^{\prime}_{|vs,|r}=-0.3791+1.28(1-C_{b})\frac{d_{m}}{B}\end{array}\] (A4)  
\[\begin{array}{l}N^{\prime}_{[\rm ss,|v]}=\left(0.96(1-C_{b})\frac{d_{m}}{B}- 0.066\right)\left(1+\left(58(1-C_{b})\frac{d_{m}}{B}-5\right)\frac{\tau}{d_{m }}\right)\\ N^{\prime}_{|r|r}=\left(0.5C_{b}\frac{B}{L}-0.09\right)\left(1-\left(30C_{b} \frac{B}{L}-2.6\right)\frac{\tau}{d_{m}}\right)\\ N^{\prime}_{vrr}=\left(0.5C_{b}\frac{B}{L}-0.05\right)\left(1+\left(48\left(C _{b}\frac{B}{L}\right)^{2}-16\left(C_{b}\frac{B}{L}\right)+1.3\right)\frac{10 \tau}{d_{m}}\right)\\ N^{\prime}_{vvr}=\left(\left(-57.5\left(C_{b}\frac{B}{L}\right)^{2}+18.4\left( C_{b}\frac{B}{L}\right)+1.3\right)-1.6\right)\left(1+\left(3\left(C_{b}\frac{B}{L} \right)-1\right)\frac{\tau}{d_{m}}\right)\end{array}\] (A5)  
where \(\tau^{\prime}\) is dimensionless draft difference, \(d_{m}\) is mean draft, \(B\) is ship breadth, \(L\) is ship length, \(C_{b}\) is block coefficient, and \(\lambda=2d_{m}/L\), \(l_{v}=\lambda\Big{/}\left(\frac{\pi}{2}\lambda+1.4C_{b}\frac{B}{L}\right)\).
# Development of a New Test-Rig for Wheel-Rail Contact Experiments under Large Slip Conditions
## 4 Experimental Research
### Validation Experiments  
To verify the decoupling theory of the test-rig, a sudden change in creep force between wheel and rail is required. By spraying water on the dry track for a short time, the loss of adhesion is obtained during the operation of the test-rig, and the response of creepage is observed.  
In Figure 11(a), the target vehicle velocity is constant at 20 km/h while the target creepage is constant at 0.05. The applied axle load is 14 t. After running for a period of time, a small amount of water is suddenly sprayed on the dry rail surface, and the adhesion coefficient decreases. As the water is removed by the rotating wheel, the adhesion coefficient returns to the initial state. At the time of sprinkling water, the creepage fluctuates slightly with an error of no more than 0.002, indicating that the sudden change in adhesion has little impact on creepage on the test-rig.  
In Figure 11(b), the target vehicle velocity is constant at 20 km/h, and the target creepage is sinusoidal, varying from 0.25 to 0.3 with a period of 12 s, which is the same as the parameters in Figure 10(b). The applied axle load is 14 t and the sprinkler system is suspended temporarily. It can be seen that the error between measured creepage and target creepage is not greater than 0.005, which means that the precise slip is available on the test-rig under large slip conditions.  
Figure 11: The actual value of the creepage in simulation. (**a**) Target creepage varies from 0 to 0.3 and creepage fluctuation occurs at the beginning; (**b**) target creepage varies from 0.25 to 0.3, creepage fluctuation occurs continuously without PID control.
# Failure Prediction of the Rotating Machinery Based on CEEMDAN-ApEn Feature and AR-UKF Model
## 3 Experiment and Results
### Initial and Final Failure Prediction  
During the entire life cycle, the bearing will degrade continuously over time, and gradually changes from the healthy state to the failure state over a long period of time. Therefore, the threshold of the initial failure should be set to achieve the prediction starting time, and the threshold of the finial failure should also be set to end the prediction process.  
As shown in Figure 7, the threshold of the initial failure is set as 0.8963 by using the Chebyshev inequality described in Section 2.3, and the degradation process starts from the 538 th point, which is also named as PST. It is obvious that the degradation curve has a significantly sudden-changing at the 701 st data point; thus, it is used as the final failure point, and the corresponding CEEMDAN-ApEn value (1.3251) is set as the threshold of the final failure.
## 4 Discussion
### Developing and Detailing a Protocol for Isolation and Characterization of Gingipains
#### 4.1.3 Characterization of Gingipains
Equipment  
Refrigerated centrifuge (Beckman Coulter, Brea, CA, USA), PowerPacTM Basic Power Supply (Bio-Rad, Vienna, Austria), Mini-PROTEAN(r) Tetra Cell (Bio-Rad, Vienna, Austria), Water bath (Memmert, Schwalbach, Germany), Orbital shaker (Biosan, Warren, MI, USA) Benchtop micro refrigerated centrifuge (Kubota, Tokyo, Japan), Microplate reader (Tecan, Switzerland, Europe). 5. Conclusions  
Gingipains are one of the virulence factors that are crucial for the pathogenesis of _P. gingivalis_ to cause infection in humans. Therefore, the isolation and characterization of gingipains are important to enable researchers to explore and understand the possible invasion mechanisms to cause the development and progression of periodontitis and certain systemic diseases. In the current study, the relatively simple and cost-saving approaches to isolate and characterize the gingipains by using the passive-diffusion mediated elution method and gelatin-zymography were demonstrated. Native-PAGE is an alternative and quick method to isolate the gingipains. Gelatin zymogram is also one of the powerful approaches to characterize and identify the catalytic domains of the gingipains by using selective inhibitors This protocol is suitable and can be extended to isolate and characterize proteins and proteinase samples with a greater difference in their isoelectric point which allows them to separate more efficiently and make ease of purification and characterization of proteins. Conceptualization, N.K.F., S.F., M.R. and P.L. ; methodology, E.S.W., R.K., M.A.S., N.K.F., S.F., M.R. and P.L. ; investigation, E.S.W., M.A.S., R.K., N.K.F., S.F., M.R. and P.L. ; resources, E.S.W., M.A.S., R.K., N.K.F., S.F., M.R. and P.L. ; data curation, E.S.W., M.A.S., R.K., N.K.F., S.F., M.R. and P.L. ; writing--original draft preparation, E.S.W., M.A.S., R.K., N.K.F., S.F., M.R. and P.L. ; writing--review and editing, E.S.W., M.A.S., N.K.F., S.F., M.R. and P.L. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the Ministry of Higher Education (MOHE) Malaysia, MyGRANTS, grant number FRGS/1/2018/SKK14/AIMST/01/1. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The data presented in this study are available on request from the corresponding author. **Acknowledgments:** The authors would like to thank the Ministry of Higher Education (Ref: FRGS/1/2018/SKK14/AIMST/01/1) and AIMST University for financial support and assistance to successfully complete this study. **Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Description of the Facilities
### Anechoic Chamber with Flow AC-2 TsAGI  
The free-jet anechoic facility AC-2 TsAGI (Figure 1) is designed for acoustic measurements in free-field conditions of subsonic and supersonic jets, airframe noise, propeller noise, etc. The interior chamber dimensions, including sound treatment (wedge tip to wedge tip), are 9.6 m \(\times\) 5.3 m \(\times\) 4.2 m. All interior surfaces of the chamber are acoustically treated using polyurethane wedges with a cut-off frequency of 160 Hz. For the airframe noise tests, a round nozzle with a diameter of 0.4 m was used, with the maximum flow speed being 80 m s\({}^{-1}\).  
The landing gear model was installed on a horizontal metal plate with sawtooth trailing edge serrations (Figure 2a) to reduce trailing edge noise. The nozzle and the support system were covered with sound-absorbing material to decrease sound reflections from them.  
The microphones were installed at the sideline from the landing gear model at a distance of 1.265 m along the line parallel to the flow axis at azimuthal angles \(\theta\) = 50\({}^{\circ}\), 70\({}^{\circ}\), 90\({}^{\circ}\), and 110\({}^{\circ}\) (Figure 2b) and polar angles \(\varphi\) = 20\({}^{\circ}\) and 40\({}^{\circ}\) (Figure 2c). One microphone was located in the overhead position at (\(\theta\), \(\varphi\)) = (90\({}^{\circ}\), 90\({}^{\circ}\)).  
For the landing gear noise measurements, 9 multi-field microphones 1/4\({}^{\prime\prime}\) Bruel & Kjaer 4961 (frequency range 5 Hz -20 kHz, dynamic range 20-130 dB, sensitivity 60 mV Pa\({}^{-1}\)) were used. Before the tests, the microphones were calibrated with a pistonphone Bruel & Kjaer 4228.  
A photo of the microphones in AC-2 TsAGI is provided in Figure 2d. The microphones were installed on horizontal holders, which had a length of 30 cm to reduce the effect of noise reflection from the vertical part of the frame on the measured noise. An open door that can be seen in Figure 2a,d was closed during the tests to enhance the acoustic characteristics of the anechoic facility AC-2 TsAGI.  
The flow velocity \(V\) in both small-scale and full-scale tests ranged from 34 m s\({}^{-1}\) to 75 m s\({}^{-1}\).  
Figure 1: A photo of anechoic facility AC-2 TsAGI.
###### Abstract  
In this study, xanthine oxidase immobilized silica coated Fe\({}_{3}\)O\({}_{4}\) nanoparticles (Fe\({}_{3}\)O\({}_{4}\)@SiO\({}_{2}\)-XO) were successfully prepared and characterized by transmission electron microscope, X-ray powder diffraction, Fourier transform infrared spectroscopy and vibrating sample magnetometer. The average diameter of the Fe\({}_{3}\)O\({}_{4}\) nanoparticles was about 300 nm to 350 nm with a shell thickness of 60 nm. The maximum saturation magnetization of the Fe\({}_{3}\)O\({}_{4}\)@SiO\({}_{2}\)-XO nanoparticles was 44.9 emu/g, which ensured the separation from the medium within one minute by using an ordinary magnet. A xanthine oxidase (XO) inhibitor screening method using Fe\({}_{3}\)O\({}_{4}\)@SiO\({}_{2}\)-XO nanoparticles was established and utilized in the extract of _Clerodendranthus spicatus_. Under the optimized conditions, two compounds were screened out and identified as gardenin B and eupatorin. The half maximal inhibitory concentration (IC\({}_{50}\)) values of these two compounds were 1.488 \(\mu\)g/mL and 11.197 \(\mu\)g/mL, respectively. The interactions between these two compounds and XO were investigated by the fluorescence spectroscopic method. The results suggested that the quenching effects of gardenin B and eupatorin were due to a static quenching mechanism. Furthermore, gardenin B showed stronger binding capacity than that of eupatorin. In conclusion, this screening method exhibited efficiency and reusability in screening, identification and analysis of enzyme inhibitors from complex mixtures.  
Clerodendranthus spicatus; inhibitors; magnetic nanoparticles; silica; xanthine oxidase +
Footnote †: journal: Applied Physics Letters
# Research on Path Planning Based on the Integrated Artificial Potential Field-Ant Colony Algorithm
## 2 Environment Modeling  
In this study, the grid method is chosen to establish the model of AGV. Assuming there are static obstacles in the environment, in order to prevent AGV from colliding with obstacles, if there are obstacles in the actual position corresponding to a grid in the grid environment, no matter whether the grid is completely covered by obstacles, the grid is coded as \"1\" and shown in the simulation diagram with black grid. If a grid faces no obstacles, then it is coded as \"0\" and displayed in the simulation with a white grid. At this time, the AGV is treated as a particle, and the side length of the unit grid is set to 1. This is shown in Figure 1.  
Figure 1 illustrates the correlation that exists between Cartesian coordinates and grid identifiers. Grid numbers start as an increasing sequence, from the left side to the right side, from top to bottom, starting with the numbers 1, 2, and so on. The Cartesian system is set, with the due east direction representing the positive \(x\)-axis, and the due north direction representing the positive \(y\)-axis. The upper boundaries for the horizontal and the vertical coordinates are represented as _MM_. The grid number is assigned a unique identifier along with positional coordinates, thus creating a correlation between the grid number and the rectangular coordinates:  
\[\left\{\begin{array}{l}x_{i}=a_{0}(\text{mod}(i,\textit{MM})-0.5)\\ y_{i}=a_{0}(\textit{MM}+0.5-ceil(i/\textit{MM}))\end{array}\right. \tag{1}\]  
In Formula (1), \(i\) indicates the serial number code corresponding to the grid; _MM_ indicates the number of rows or columns of a square grid map; (\(x_{i}\),\(y_{i}\)) is the horizontal and vertical values corresponding to the \(i\) th cell in the grid. \(a_{0}\) represents the side length of a unit of the grid; mod(\(i\),_MM_) indicates the remainder of \(i\)/_MM_. _ceil(\(i\)/_MM_) indicates that \(i\)/_MM_ is rounded up.  
In the process of AGV movement, there are eight movement directions, but the direction of the previous step needs to be removed, and the actual alternative direction is 7.
# Aiding ICD-10 Encoding of Clinical Health Records Using Improved Text Cosine Similarity and PLM-ICD
## 7 Conclusions  
The classification of EHRs from text into diagnostic codes has been challenging to the NLP community. The proposed methodology relies on a method based on Cosine similarity between the clinical record and the ICD-10 code description, using a strategy of using the conceived multiple runs algorithm along with the concept of the bucket category.  
Comparing the F1-score obtained with PLM-ICD for the test set used, it is inferior to the best obtained in the state-of-the-art (46.9% to 58.5%). Since no training or architectural changes were made to PLM-ICD in the current project, the only reasonable explanation for the different results is the difference in the test set used, because [PERSON] et al. used a bigger test set consisting of 24,461 records [13], in comparison to the 4077 used in this work because of limited computational resources.  
The results show that the use of PLM-ICD-C, consisting of the improved Cosine method and PLM-ICD, improved the results, increasing the F1-score by 0.5%, but most important, by increasing the precision from 46.3% to 50%, which means a significant improvement on the code suggestions given to the medical doctors performing encoding functions.  
The use of ICS is not advantageous for values of \(S_{P}\) above \(T_{1}\) or below \(T_{2}\), where it is more reliable to use only the PLM-ICD. For values of \(S_{P}\) between \(T_{2}\) and \(T_{1}\) values, then PLM-ICD-C, with the use of ICS, is a better choice.  
In future work, the improved Cosine method can be applied to other datasets that overcome the limitations that MIMIC-IV may have. The dictionary of synonyms, where only four pairs were used, just as a proof of concept, shall also be expanded. A more complete NER model can also be used, to detect other biomedical terms, and not only diseases.  
Conceptualization, M.M. ([PERSON]); Methodology, V.D. and M.M. ([PERSON]); Software, H.S.; Validation, V.D.; Investigation, H.S.; Resources, M.M. ([PERSON]); Data curation, H.S. and V.D.; Writing--original draft, H.S.; Writing--review & editing, M.M. ([PERSON]); Supervision, M.M. ([PERSON]) and M.M. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
This work was produced with the support of INCD funded by FCT and FEDER under the project 01/SAICT/2016 n\({}^{\circ}\)022153. This work received financial support from the Polytechnic Institute of Coimbra within the scope of Regulamento de Apoio a Publicacao Cientifica dos Estudantes do Instituto Politecnico de Coimbra (Despacho n.\" 5545/2020).  
No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
The authors declare no conflicts of interest.
# A Comprehensive Evaluation Algorithm of Multi-Point Relay Based on Link-State Awareness for UANETs
###### Abstract  
The Multi-Point Relay (MPR) is one of the core technologies for Optimizing Link State Routing (OLSR) protocols, offering significant advantages in reducing network overhead, enhancing throughput, maintaining network scalability, and adaptability. However, due to the restriction that only MPR nodes can forward control messages in the network, the current evaluation criteria for selecting MPR nodes are relatively limited, making it challenging to flexibly choose MPR nodes based on current link states in dynamic networks. Therefore, the selection of MPR nodes is crucial in dynamic networks. To address issues such as unstable links, poor transmission accuracy, and lack of real-time performance caused by mobility in dynamic networks, we propose a comprehensive evaluation algorithm of MPR based on link-state awareness. This algorithm defines five state evaluation parameters from the perspectives of node mobility and load. Subsequently, we use the entropy weight method to determine weight coefficients and employing the method of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for comprehensive evaluation to select MPR nodes. Finally, the Comprehensive Evaluation based on Link-state awareness of OLSR (CEL-OLSR) protocol is proposed, and simulated experiments are conducted using NS-3. The results indicate that, compared to PM-OLSR, ML-OLSR, LD-OLSR, and OLSR, CEL-OLSR significantly improves network performance in terms of packet delivery rate, average end-to-end delay, network throughput, and control overhead.  
UANETs; MPR; OLSR; mobility; link status; NS-3; TOPSIS +
Footnote †: journal:
# Reducing System Load of Effective Video Using a Network Model
## 2 Related Work
### RTSP (Real Time Streaming Protocol)  
RTSP is a network protocol designed for communication systems to control streaming media servers. Figure 9 shows a media server and client architecture using RTSP. Such a network protocol is used for a system that streams media in real time to a client with video or audio functions and is used to remotely control a media server. Commands are similar to VCR operation methods, such as PLAY and PAUSE, and access the server based on time information. It can operate on a variety of transport layer protocols, including TCP and UDP, and forwards packets after establishing an RTP/RTCP channel using a trusted connected TCP for sending control messages.  
Figure 8: Convolutional Neural Networks with three layers.  
Figure 9: A multimedia architecture with RTSP.