esa-sceva/satcom-chunk-collection huggingface dataset:
# Design and Application of a New Visible Light-Curing 3D Printing Platform
## 4 Discussion  
A visible light-curing 3D printing machine has been developed, comprising a control device, conveying apparatus, leveling mechanism, and a light source module. The control system is an integration of the Mks-Robin control board, the Marlin 2.0 control system, and the Simplify3D software, orchestrating the operations of the leveling and light source devices as well as the conveying mechanism. The conveying apparatus, built around the BJ 1030-4 peristaltic pump and its feed pipeline, ensures the precise transportation of energetic slurry. The leveling mechanism employs a transducer and an ultrasonic oscillator to ensure the uniform distribution of the energetic slurry within the tube shell. Lastly, the light source module, featuring a cooling fan and a 50 W visible light-curing lamp, facilitates the curing of the energetic slurry contained within the shell. This design introduces a groundbreaking 3D printing charging method that boasts zero pollution, no radiation, and heightened safety.  
Through orthogonal experimentation and range analysis, with the curing depth as the evaluation index, the best formulations for the visible light-curing slurry were EA/PUA (prepolymer), 37.21% PETA/HDDA/BA (active diluent monomer), 0.47% CQ (visible light initiator), 0.93% DMT (active agent), and an additional 0.93% of other additives. Using standard deviation as the evaluation index, the optimal formulation of the energetic power column was 20% visible light-curing slurry, 57.72% AP, 15.28% Al, and 7% RDX. The experimental results show that the section of the energetic powder column was smooth, the packing was evenly distributed, and it had good compatibility. The average combustion rate of the energetic propellant column was 1.165 mm\(\cdot\)s\({}^{-1}\); the maximum light intensity during the combustion of the charge column was 2.053 cd. This novel light-curing 3D printing platform provides a new way for charging the energetic charge column.  
Conceptualization, Y.F. and S.B.; methodology, S.B.; software, Y.F.; validation, Y.F., B.Z. and LL.; formal analysis, Y.Y.; investigation, Y.F.; resources, Y.F.; data curation, B.Z.; writing--original draft preparation, Y.F.; writing--review and editing, Y.F.; visualization, S.B.; supervision, S.B.; project administration, S.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
This novel light-curing 3D  
**Institutional Review Board Statement**: Not applicable.  
**Informed Consent Statement**: Not applicable.  
**Data Availability Statement**: Not applicable.  
Figure 15: Relationship between burning light intensity and time of energetic powder column.
# Application of Molecularly Imprinted Polymers in the Analysis of Waters and Wastewaters
## 5 Application of MIPs for the Detection of Different Classes of Contaminants
### Heavy Metals
#### 5.1.2 Lead  
As a heavy metal element, lead is one of the most toxic to both animals and humans. It has severe toxicological effects on living organisms, and it can be transferred from soil to plants, and then to animals and humans through the food chain, resulting in severe contamination. Due to its non-biodegradability, lead accumulates through its association with inorganic and organic matter, such as by means of adsorption processes, formation of complexes, or chemical reactions [48]. Lead is a component in many industrial products, such as paints, cables, pipelines, and pesticides, and the main anthropogenic input is through the fossil fuel of combustion engines [43; 45].  
A solid phase extraction method based on lead ion-imprinted polymers (Pb-IIPs) using 8-hydroxyquinoline grafted gelatin and chitosan as a monomer and genipin as a cross linker. Three-dimensional IIPs were prepared with a high adsorption capacity, i.e., 235.7 mg g\({}^{-1}\)  
Figure 3: Preparation of reduced graphene oxide-ion-imprinted polymer modified glassy carbon electrode [46]. (Reproduced under permission from Elsevier, doi:10.1016/j.msec.2016.03.005).  
and a detection limit of 0.2 ng mL\({}^{-1}\). The adsorption/desorption interactions were tracked using spectrophotometric detection at 560 nm within a linear range of 1-100 ng mL\({}^{-1}\)[49].
# A Secure Opportunistic Network with Efficient Routing for Enhanced Efficiency and Sustainability
## 4 Routing Protocols Integrated with Cybersecurity and Blockchain Technologies  
In this section, we explore various routing protocols that are seamlessly integrated with cybersecurity and blockchain technologies, introducing enhanced capabilities to optimize communication within OppNets. Each protocol harnesses unique features to address specific challenges and improve the efficiency of message delivery.  
1. _Blockchain-Assisted Epidemic Routing:_ This approach uses a decentralized ledger to optimize message replication strategies. Smart contracts play a crucial role in governing the dissemination process, effectively reducing redundancy and improving delivery rates [23].
2. _Proof-of-Delivery (PoD) Routing:_ Leveraging the transparency of blockchain, PoD routing ensures reliable message delivery. Through smart contracts, successful message reception is validated, triggering incentives for relaying nodes and thereby enhancing overall message delivery efficiency [24].
3. _Consensus-Based Routing with Blockchain:_ Consensus-based routing algorithms incorporate blockchain consensus mechanisms, such as Proof of Work and Proof of Stake, to validate routing decisions. The immutable nature of blockchain records enhances trust in 251 consensus outcomes, ensuring both secure and efficient message forwarding [25].
4. _Blockchain-Powered Predictive Routing:_ Predictive routing algorithms leverage historical encounter data stored on the blockchain to predict future node interactions. The execution of smart contracts facilitates the implementation of predictive algorithms, ultimately enhancing the accuracy of encounter-based routing strategies [26].
## 4 A Survey on Cognitive Radio Implementation Research
### Some TV Band White Space Devices for Cognitive Radio  
For years, cognitive radio research has focused on TV band (VHF and UHF spectrum) because this band provides superior propagation and building penetration compared to other unlicensed spectrum in other bands like the 2.4 and 5 GHz bands. After two years white space devices (WSD) testing, the Federal Communications Commission (FCC) in the United States issued a report and order which permits cognitive use of the TV white space spectrum. These new regulatory rules open up an opportunity to develop new wireless networks to utilize this spectrum [112]. The following section will give a brief introduction of the most recent WSD devices from commercial companies such as Motorola, Inc., Adaptrum, Inc. and Philips, Inc. In addition, engineers at the University of Kansas (KU) have built and tested a simulated WSD transmitter and successfully demonstrated how WSD transmissions can be structured to avoid causing harmful interference to licensed broadcasts on adjacent channels.
## 3 Challenges for Routing Protocols in FANETs
### High Dynamic Topology  
Low link quality is an issue with FANETs due to the extremely high dynamic network topology caused by high mobility. As a result, link disconnections and network partitions frequently increase route discovery and maintenance and reduce routing performance [78]. Peer-to-peer connections are established to sustain coordination and collaboration between UAVs [79]. A multi-UAV Network is an ideal option for homogeneous and small-scale missions. Multi-cluster networks are required when particular UAVs must perform several missions.
## 1 Introduction
The use of C-RAN is essential in order to increase the capacity, i.e., the number of active IoT devices in a smart city scenario, and improve the coverage and throughput of other outdoor and indoor scenarios, namely, a stadium with a pitch and an indoor factory. The following is a summary of the article's main contributions:  
* We provide a system-level assessment of C-RANs including multiple RISs spread around BSs in three different scenarios at three different frequency bands, namely, 3.6 GHz, 28 GHz and 100 GHz;
* A system-level evaluation for multi-stream MIMO-OFDM links is performed for numerologies 0 and 3 from 5G NR in three 3D scenarios with different parameters, numbers of transmitting/receiving antennas, bandwidths, frequency carriers, numbers of RIS elements, degrees of transmitting power, etc. ;
* System-level evaluation demonstrates that C-RAN deployments in all simulated scenarios, including an urban smart city, a stadium with a pitch, and an indoor factory, can achieve significant performance improvements over typical cellular networks without RISs, in terms of both EE and SE. The article is organized as follows: Section 2 presents the model for the C-RAN system with RIS. Section 3 presents the system-level configuration and scenarios that are considered in the evaluation and also presents and discusses system-level simulation results. The conclusions are outlined in Section 4.
# Rician Beamforming: Despeckle Method via Coarray Projection Stochastic Analysis
## 2 Physical and Mathematical Background
### SAFT Stochastic Behaviour
* High particle count regions with diverse reflectivity values, in geometrical groups that yield to energy concentration near the analysis point, i.e., concavities. Unfortunately, \(X\) and \(Y\) behaviour cannot be considered as monomodal: \(\alpha_{f}\) and \(\beta_{f}\) get recurrent values due to the structure being analysed. In this case, the speckle noise is much higher in the image due to the rise in \(\left.s(\chi)\right|_{\mathbf{p}_{\mathbf{z}}}\) of low frequency waves. These aberrations cause artefacts due to the effects of secondary lobes and main lobe low directivity on the resulting image. * High particle count regions with high reflectivity values and high spatial density. In this case \(\alpha_{f}\) and \(\beta_{f}\) tend to 0; that is, there is high coherence between wavelets involved in summation (5). \(X\) and \(Y\) resemble non-zero mean Gaussian variables, and \(E\) follows a Rician distribution [31].
## 3 Results  
### Impact of Different Biochars on Bacterial Growth  
It is known that biochars could induce the changes in bacterial community structure, but how biochars influence the cell growth of individual strain was still unclear [1]. Therefore, 12 rhizosphere-associated bacterial strains from 4 phyla were selected to examine the impact of biochar on the cell growth, these strains could subsequently enhance soil fertility through phosphate/potassium solubilization, acidification, and production of cellulase, xylanase, \(\beta\)-glucanase, phytase, and chitin. Three biochar samples, including rice husk biochar, corncob biochar, and bamboo biochar, were applied in this work, and the physico-chemical properties of these biochars were listed in Table 1. All the properties varied greatly among the three biochar samples, indicating different influences that these biochars might exert on bacteria. It is worth mentioning that the average pore size of bamboo biochar was too large to be detected by BET analyzer. As shown in Figure 1, the maximal growth promotion and inhibition were observed on _B. mucilaginous_ and _K. viridis_, respectively, no matter which biochar sample was applied. However, different growth variation was detected in the bacteria culture added with biochars derived from different feedstocks. Compared with the other two biochar samples, corncob biochar showed a positive impact on all tested bacteria except _K. viridis_, and strains with the growth promotion degree more than 20% included _Ochroachrum_ sp., _B. pumilus_, _B. licheniformis_, _B. mucilaginous_, and _B. megaterium_. Bamboo biochar had a similar behavior as corncob biochar, except its negative effect on _B. cereus_. When rice husk biochar was added, the growth of _B. pumilus_ (ACCC04306), _B. licheniformis_, _B. cereus_, and _K. viridis_ was suppressed, respectively. Meanwhile, different strains from the same species, such as _B. pumilus_ ACCC04063 vs. ACCC011736 and _B. megaterium_ AS1217 vs. ACCC01667, exhibited discrepant responses towards the same biochar. Considering the positive impact on most of tested bacteria, the biochar derived from corncob was used in the following studies.
# Development of Prediction Method for Dimensional Stability of 3D-Printed Objects
## 2 Experiments
### Regression Models  
In this study, three types of regression models were employed to predict 3D object dimensions. A multiple linear regression model was employed for the analysis, while Gaussian process regression (GPR) and support vector machines (SVM) algorithms were implemented using MATLAB version R2021a. Additionally, an ANN model was constructed using Python for the purposes of comparison and evaluation.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Material** & **PLA** \\ \hline Nozzle temperature (\({}^{\circ}\)C) & 210 \\ Bed temperature (\({}^{\circ}\)C) & 60 \\ Nozzle moving speed (mm/s) & 60 \\ Infill density (\%) & 100 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Printing conditions.  
Figure 2: Measured profile of the object.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Model** & **Dataset 200 (RAM Optical Instrumentation \\ Incorporated, Rochester, NY, USA)** \\ \hline Measuring range (mm) & 200 \(\times\) 150 \(\times\) 150 \\ Optical magnification & \(\times\)35–\(\times\)280 \\ Resolution (\(\upmu\)m) & 0.5 \\ Max. measured load (kg) & 23 \\ Accuracy (\(\upmu\)m) & 2.5 in XY axis \\ \hline \hline \end{tabular}
\end{table}
Table 5: Specifications of RAM optical measurement inspection system.  
The input parameters were inclination angle, layer thickness, support space, and raster angle, and the output parameters were the MDSEs for dimensional accuracies of the objects. A total of 81 datapoints were used for the prediction of 3D objects. These 81 datapoints were randomly divided into training, validation, and test datasets at a ratio of 70%, 15%, and 15%, respectively.  
ANN model was employed with three hidden layers and 32 nodes. A rectified linear unit (ReLU) activation function was used. The mean absolute errors (MAEs) loss function and adaptive moment estimation (ADAM) optimizer, including a learning rate of 0.001, \(\beta\)1 = 0.9, \(\beta\)2 = 0.999, and \(\varepsilon\) = 10\({}^{-8}\), were applied in model training and optimization. The models were trained for 200 epochs with minibatches of 10 to avoid the overfitting issue. The flow chart for ANN model is shown in Figure 3.
# PLC-Controlled Intelligent Conveyor System with AI-Enhanced Vision for Efficient Waste Sorting
## 5 Discussion
### Contribution and Research Implications  
The incorporation of the YOLOv8 deep learning model with a PLC into the sorting system marks a notable enhancement in automated waste sorting technology. The results confirm the high precision of the system, achieving classification accuracies of 88% for metal cans and up to 91% for plastic bottles. This shows a crucial improvement in the efficiency of recycling operations. In addition, the system has been proven capable of maintaining this high level of accuracy even in the presence of continuous chaotic waste streams and improperly arranged objects, showcasing its suitability for large-scale industrial waste management applications.  
The implementation of the system has provided valuable insight into the practical challenges of automated waste sorting. One significant challenge is handling objects overlaps, which can lead to inaccuracies in classification. Although the system demonstrates proficiency in sorting and classifying objects within disordered waste streams, advancing the development of algorithms that can accurately differentiate and categorize overlapping objects is identified as a critical focus for subsequent iterations, which is essential to address complex classification challenges. Such refinements are crucial to improve the robustness and efficiency of the sorting system. Future enhancements will focus on increasing the resilience and reliability of the system in managing diverse operational conditions, ensuring consistent performance in a wider range of waste management scenarios.
# Are Clinical Balance Measures Linked to Cycling Performance?
## 2 Materials and Methods
### Experimental Setup and Procedure  
A field-based test of cycling performance was conducted on a closed circular cycling track approximately 800 m in length (Figure 1). On each testing day, the track was inspected for loose debris and the public was informed of testing to ensure participant safety. Upon arrival, participants' height in centimetres with a stadiometer (Seca 213, Los Angeles, CA, USA) and weight in kilograms with electronic scales (Tanita BC-587, Tokyo, Japan) were measured.  
An array of inertial measurement units (IMUs) (Noraxon MyoMOTION, Noraxon, Phoenix, AZ, USA) were used to capture the roll angle of the pelvis in the coronal plane as a measure of overall lean angle. The IMUs were attached to the skin overlying the spinous processes of T10 and S1 using manufacturer-supplied double-sided adhesive tape reinforced with rigid medical-grade strapping tape. IMUs are validated for field-based kinematic assessment in cycling [18; 19]. IMU data were recorded using the manufacturer's data logger. The participant's own bicycles were fitted with a 10 Hz global positioning system (GPS) (Optimeye S5, Catapult Sports, Melbourne, Australia) secured vertically to the lateral aspect of the bicycle seat post with rigid tape. The GPS captured speed, location via longitude and latitude, and elapsed time. Participants were asked to warm up and familiarize themselves with the track by cycling five laps of the course in an anti-clockwisedirection at a self-selected pace. Two traffic cones were used to mark the start of the cycling track. From a standing start, participants were instructed to cycle to their maximum speed for five continuous laps in an anti-clockwise direction. Participants were verbally informed of their lap count upon the completion of each lap. On the completion of their five laps, the GPSs and IMUs were removed, and the data were downloaded to manufacturer-supplied software (Catapult Sprint version 5.1.7, Catapult Sports, Australia; Noraxon myoResearch 3.18, Noraxon, Phoenix, AZ, USA) for further analysis.  
Prior to balance testing, participants were verbally rescreened for recent injury. Next, they removed their shoes, and leg length (in cm) was measured as the distance between the anterior superior iliac spine and the medial malleolus [20]. Before commencing each balance test, participants were provided standardised instructions (Appendix A). During testing, participants received instructions to enable them to remain focused on remaining balanced.
# Rock Breaking Performance of TBM Disc Cutter Assisted by High-Pressure Water Jet
## 5 Conclusions  
A new tunneling method was presented in this paper that is a TBM coupled with a high-pressure water jet. A numerical simulation based on the FEM and SPH method was carried out to study the effect of parameters on rock breaking performance, which was proved to be reliable by the rock breaking experiment. The results can provide theoretical guidance and data support for designing the most efficient system of a TBM with a water jet for digging a full-face hard rock tunnel. The details of the conclusions are shown as follows.  
1. Results of the theoretical analysis and numerical simulation showed that the high-pressure water jet can increase the TBM digging efficiency and decrease the disc cutter wear rate.
2. With the growth of the jet velocity, the force and wear of the disc cutter will reduce, and the rock breaking efficiency will increase. The optimum jet velocity is 224.5 m/s in this simulation.
3. With the kinetic energy of the disc cutter and the rock crushing volume as the evaluation criteria, 1.5 mm is the optimum value for the water jet in the simulations.
4. The water jet located at the center section of the disc cutter plays a major role in reducing the force and wear of the disc cutter, while the one located beside the center section of the disc cutter plays a major role in increasing the rock breaking efficiency.  
Conceptualization, F.W. and C.G.; methodology, F.W.; software, F.W.; validation, F.W., D.Z. and C.G.; formal analysis, X.Z.; investigation, N.X.; resources, F.W.; data curation, D.Z.; writing--original draft preparation, F.W.; writing--review and editing, C.G.; visualization, X.Z.; supervision, C.G.; project administration, C.G.; funding acquisition, F.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Fundamental Research Funds for the Central Universities, grant number 2019 QNA07.  
The authors declare no conflict of interest.
## 3 The Selection Parameters of the MPPT Algorithms  
The evaluation parameters are selected to compare MPPT algorithms since these factors determine the performance, efficiency, and cost-effectiveness of the algorithm. Each of these parameters covers a different aspect of how the MPPT functions and how it integrates into the overall design of a PV system. The selected parameters are intended to comprehensively evaluate both traditional and advanced algorithms [39]. The most widely used parameters for evaluating MPPT algorithms are as follows: sensed parameters, circuitry, tracking speed, implementation complexity, true MPPT, accuracy, and cost.
## 4 Conclusions  
In conclusion, we present a design of reconfiguring SRR meta-atoms, which exhibits the capability to tune the electromagnetic responses of the incident THz wave by moving SRR meta-atom positions. There are two tuning resonances with a tuning range of 50 GHz in TE mode when SRR-2 and SRR-4 meta-atoms move along positive \(x\)-axis direction. On the other hand, there is one single-resonance tuned from 0.67 THz to 0.72 THz in TM mode by moving SRR-1 and SRR-2 meta-atoms along positive \(y\)-axis direction. This shows that the resonances can be tuned in a range of several tens of GHz in the situation where the SRR array is still axially symmetric even if the whole configurated pattern is changed. By moving the SRR-2 and SRR-4 meta-atoms along the positive \(y\)-axis direction, there is an EIT resonance in TE mode. Furthermore, the resonances can be transformed from dual-band to multi-band in TE mode by moving the SRR-2 meta-atom along positive \(x\)-axis direction. When the position of SRR-2 and SRR-3 meta-atoms are moved along \(x\)- or \(y\)-axis direction, the switching function is transformed from triple-band to single-band in TM mode. This shows that the asymmetric SRR array can change their EIT resonance from single-band, to dual-band and triple-band. This work provides a detailed investigation of the electromagnetic response of a planar SRR array and paves the way for future studies on tunable metamaterials. It can be potentially used in many applications such as wearable electronic devices, tunable filters, active sensors, modulators and so on.  
Conceptualization, Y.L. and Y.-S.L.; methodology, Y.L. and Y.-S.L.; software, Y.L.; validation, Y.L. and Y.-S.L.; formal analysis, Y.L. and Y.-S.L.; investigation, Y.L. and Y.-S.L.; resources, Y.L. and Y.-S.L.; data curation, Y.L. and Y.-S.L.; writing--original draft preparation, Y.L. and Y.-S.L.; writing--review and editing, Y.L. and Y.-S.L.; supervision, Y.-S.L.; project administration, Y.-S.L.; funding acquisition, Y.-S.L. All authors have read and agreed to the published version of the manuscript. This research was funded by the financial support from the National Key Research and Development Program of China (2019 YFA0705000). The authors declare no conflicts of interest.