esa-sceva/satcom-chunk-collection huggingface dataset:
# Recent Research Progress in Surface Ligand Exchange of PbS Quantum Dots for Solar Cell Application
## 2 Solid-State Ligand Exchange
### Air-Stable PbS CQDs via Solid-State Ligand Exchange Process  
High device performance and stability are essential requirements to realize efficient solar cells. Even though PbS CQDs had been considered as promising candidates to make breakthroughs in solar cells, the initial ambient stabilities of PbS CQD photovoltaics (PVs) were poor, and their performance had to be measured under N\({}_{2}\)-filled inert conditions. When PbS CQDs were exposed to air, oxidized layers could be formed at the CQD surface, and these layers can cause poor electrical conductivity resulting in decreased device performance. To overcome the poor air stability of PbS CQD PVs, intensive studies to prevent the surface of PbS CQDs from oxidization had been conducted by using specific substances for ligand exchange or control the surface of PbS CQDs. [PERSON] et al. reported 3 nm-sized PbS CQD PVs fabricated via the solid-state ligand exchange process using ethanolithiol (EDT) as a short-chain ligand. The PbS CQD PVs were stable for 63 h, and the performance measurement could also be carried out in ambient conditions. The stability of PbS CQDs are mainly governed by the magnitude of oxidation, and [PERSON] et al. revealed that the oxidation species of PbS CQDs are quite different from their crystal sizes [11]. For larger-sized PbS CQDs within the range of 4 nm to 10 nm diameter, PbSO\({}_{4}\) is mainly observed on the PbS CQD surface after oxidation, whereas, PbSO\({}_{3}\) is the principal oxidation product for oxidized smaller-sized PbS CQDs with diameters less than 3 nm. PbSO\({}_{3}\) and PbSO\({}_{4}\) states in PbS are well-known as trap states located under the conduction band edge with \(-0.1\) eV and \(-0.3\) eV, respectively. The small dots \(-0.1\) eV below the level of the conduction band edge are relatively shallow, which show effects that increase the carrier lifetime [12; 13]. However, the large dots \(-0.3\) eV below the conduction level of the band edge are relatively deep and result in catastrophic recombination of the carriers. The different oxidation species of PbS CQDs depending on their sizes are originated from their different facet geometries [14; 15]. In contrast, the small dot surfaces are almost passivated with the ligand, and spatial hindrance effects prevent PbS CQDs from oxygen (Figure 2). This is the first demonstration of solution-processed CQD PVs showing stability in ambient conditions. Later, the first certified PbS CQD solar cell exhibiting 3% of PCE was also fabricated using EDT-based small-size PbS CQDs and reported [16].
# Can Livestock Farming Benefit from Industry 4.0 Technology? Evidence from Recent Study
## 4 Results
### Pig Fattening
#### 4.3.1 State of Digitalization in the Pig Fattening Sector  
Pig farming has a high degree of automation due to its clear structural, spatial, and temporal process orientation. The individual main process steps from gilt production through piglet production to fattening build directly onto each other. The individual process steps are also subdivided in such a way that, e.g., in piglet production, the individual production steps of the mating center, waiting room, and farrowing house are connected to one another in a fixed weekly rhythm.  
There are many approaches to the production method in pig farming that are also present in industrial production [57].  
Basically, pig farming offers good conditions for the networking of individual subsystems due to its fixed spatial and process structure [58]. Permanently installed systems for feeding and air conditioning may be connected via cable. There is little to be found in the field of animal sensor technology since there are hardly any possibilities due to the lack of sensors [59].  
Because of the costs compared to the revenue opportunities, sensor technology in individual animals almost never goes beyond the research stage. Contactless sensor technology,e.g., image analysis or thermography, is also rarely used outside of research due to the high costs [60, 61].
## 3 Results and Discussion
### Statistical Features
Noteworthy, the similar behavior of samples collected as \"fresh eruption\" and \"pyroclastic wastes\" could be probably due to the fact that pyroclastic wastes have not--or have negligibly--undergone contamination processes. With reference to the MDA, the outcome graph is shown in Figure 4. The graphical interface consists of the results previously obtained from the PCA, with the superimposition of a contour map comprising different colors in relation to the degree of similarity that the analyzed samples highlight. The interpretation of the results is made clearer by the presence of circular, elliptical or square vectors capable of explaining the differences observed in multidimensional space. Obviously, a greater degree of difference observed between the considered samples will correspond to a lower degree of similarity [48]. Figure 4: MDA contour plot as obtained by combining PCA and HCA results. Different colors account for the degree of similarity between the analyzed samples. Figure 3: Results, before (**a**) and after (**b**) the automatic cut. The results of the MDA approach confirm what was suggested by the previous analyses (PCA and HCA). In fact, it is possible to identify three groups, which respectively include:  
1. Samples from the ID 8 and 10 sites, with a degree of similarity equal to 100%, and samples from the ID 6 and 9 sites, with a degree of similarity equal to 78%. These pyroclastic products can be ideally grouped within the same cluster. However, while samples from the ID 6, 8 and 10 sites are pyroclastic wastes, those from the ID 9 site were collected as a fresh eruption sample;
2. All other samples are placed in the quadrants on the left side of the MDA graph. In particular, samples from ID 7 site have a degree of similarity of 56% (green color), and belong to the category of freshly erupted air-fall pyroclastic products;
3. The remaining samples show heterogeneous degrees of similarity, but commonly less than 40% for all of them. This last hypothetical cluster seems to consist of the remaining fresh eruption samples (ID 1, 4 and 5 sites) and the pyroclastic waste samples (ID 2 and 3 sites), which probably have undergone pollution phenomena capable of determining potentially toxic elements concentrations similar to those shown by the fresh eruption pyroclastic samples.
###### Abstract  
The coverage of a surface using multiple viewpoints is a topic of great interest for robotic path planning in inspection applications. Two approaches for coverage path planning are broadly addressed in the literature--geometric methods and optimization methods. While the optimization methods may be the most flexible, they are frequently difficult to implement in practical applications due to their NP hard nature. We present here a geometric algorithm for the coverage path planning of panels used for aerospace applications using a generic camera model that can represent area inspection techniques like thermography and laser shearography. This algorithm relies on drawing a 2D grid on the 3D surface of the panel using geodesic lines on the surface. The coverage of the surface is performed by propagating geodesic lines from a starting point until the patch thus covered diverges too much from a flat surface, and after that, the coverage is continued from another point. The propagation of the geodesic lines is stopped when they begin to converge or diverge, and we define two criteria for the stoppage. We show that the proposed algorithm has good results for 3D virtual models and emphasize its speed, simplicity, and reliability for such applications.  
coverage path planning; geometric algorithms; panel inspection; non-destructive testing 2024 14 906 1
# Analysis of BDS/GPS Signals' Characteristics and Navigation Accuracy for a Geostationary Satellite
###### Abstract
GNSS signal characteristics in GEO, taking into consideration the L1 and L5 frequency bands and the GPS and Galileo constellations, are specifically investigated. Simulation tests and experiments using a high sensitivity commercial off-the-shelf (COTS) receiver were presented to validate the navigation performance [16]. Moreover, several missions have demonstrated the flight performance of GNSS signal processing and onboard orbit determination in GEO orbit. In Europe, Galileo navigation satellite GLOVE-A with a SGR-GEO receiver and an experimental results show that weak side lobe signals have been acquired and tracked by this receiver to increase the number of available satellites in medium-earth-orbit (MEO) and GEO. The position accuracy in this experiment was less than 100 m [17; 18]. The Geostationary Operational Environmental Satellite-R (GOES-R) adopts Viceroy-4 as an onboard GPS receiver to provide orbit determination data for guidance, navigation, and control systems [19]. According to on-orbit performance, the position accuracy is less than 15.2 m and the velocity accuracy is less than 0.52 cm/s [20]. In Europe, a receiver Mosaic GNSS has been adopted in SmallGEO platform used in the Hispast 36W-1 mission. The flight results show that signals with C/N\({}_{0}\) at 27 dB-Hz-28 dB-Hz are received and the RMS of position error is around 120 m [21]. In a GEO mission of TJS-2, the onboard receiver can track 6-8 GPS satellites and the minimum C/N\({}_{0}\) of signals tracked was 24 dB-Hz. The RMS of position error between 30 h orbit determination arcs is 2.14 m using the overlap comparisons assessment [22]. Furthermore, several publications have addressed the feasibility of GNSS-based navigation for lunar missions. Navigation results obtained with a realistic simulator were presented by the past studies to demonstrate the feasibility of lunar orbit spacecraft applications that rely on GNSS receivers [23; 24]. The GEO satellite of No.5 Telecommunication Technology Test Satellite (TJS-5) was launched on 7 January 2020, and a high sensitivity GNSS receiver has been installed to realize tracking GPS and BDS signals and to perform orbit determination autonomously. In this study, we investigate the flight signal characteristics in this GEO missions, considering GPS and BDS in terms of availability, PDOP, C/N\({}_{0}\), the observation quantity and accuracy. Then, we give the performance evaluation of single-epoch least square solutions and real-time orbit determination solutions and discuss the contribution of BDS signals to GEO applications.
## 2 Materials and Methods
### Chemical Composition
#### 2.5.2 GC-SMPE-MS Analysis of Coffee Volatiles  
The chemical profile of aromatic substances in coffee samples was determined by previously developed GC-SPME-MS analytical methods [17; 18]. The GC-MS instrument consisted of an Agilent 7890A oven, 5975C single quad mass spectrometer (Agilent Technologies, Palo Alto, CA, USA), and CombiPal autosampler (CTC Analytics AG, Zwingen, Switzerland). The measured volatile compounds were absorbed onto an SPME fibre coated with a combined DVB/CAR/PDMS phase (Supelco, Bellefonte, PA, USA). The coffee samples (500 mg of freshly ground coffee in a 10 mL headspace vial) were conditioned at 40 \({}^{\circ}\)C for 10 min and were sorbed at the same temperature for 15 min. Volatile compounds were desorbed in the GC inlet at 230 \({}^{\circ}\)C for 10 min in a splitless mode. The individual components were separated on an HP-5 MS column (30 m, 0.25 mm internal diameter, 0.25 \(\upmu\)m, Agilent Technologies). Helium was used as the carrier gas at a flow rate of 1 mL/min. Initially, the temperature program of the oven began at 40 \({}^{\circ}\)C and was increased to 180 \({}^{\circ}\)C at a rate of 5 \({}^{\circ}\)C/min, maintained at this temperature for 1 min, and then increased to 280 \({}^{\circ}\)C at a rate of 30 \({}^{\circ}\)C/min. The temperature of the transfer line was set at 280 \({}^{\circ}\)C, and temperatures of the quadrupole and ion source were maintained at 150 and 230 \({}^{\circ}\)C, respectively. Compounds were measured in scan mode in the range of 45-550 \(m/z\) and a time window of 0-25 min. The volatiles were identified by comparing their MS spectra and retention indices [19] with the data available on the NIST (the National Institute of Standards and Technology) standard reference database [20]. Their identification by other researchers in roasted coffees was also taken into account. All substances with a retention time greater than 25 min were excluded from identification because their peak areas were too small for reliable identification. The constituents were quantified relatively by comparing the ratio of individual peak areas to the total area of all peaks present in the chromatogram (average percentage of relative peak area; % RPA).
## 3 Results and Discussion
### Dilution Effect on algal Growth in ADPE  
As the dark brown color and high NH4\({}^{+}\) concentration of raw ADPE hindered algal growth as described above, 10\(\times\), 15\(\times\), and 20\(\times\) diluted ADPEs were used for microalgae cultivation to determine the dilution effect on algal growth in ADPE. The findings showed that algal growth of NCU-39 was completely inhibited in 10\(\times\) and 15\(\times\) diluted ADPEs at initial NH4\({}^{+}\)-N concentrations of 210 and 140 mg L\({}^{-1}\), respectively; in contrast, algal growth was observed in 20\(\times\) diluted ADPE at initial NH4\({}^{+}\)-N concentration of 105 mg L\({}^{-1}\) (Figure 2 and Table 1). Generally speaking, NH4\({}^{+}\)-N concentration of 110 mg L\({}^{-1}\) was critical for NH4\({}^{+}\) tolerance in green algae, including _Chorella_ spp. [22]. Nevertheless, NCU-39 isolated from NH4\({}^{+}\)-rich waterbody in a ditch surrounding a landfill plant might present a great NH4\({}^{+}\) tolerance above 110 mg L\({}^{-1}\). The complete growth inhibition might be attributed  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Nutrients and Metals (mg L\({}^{-1}\))** & **Raw ADPE** \\ \hline NH4\({}^{+}\)-N & 2098.4 \(\pm\) 4.5 \\ TN & 2305.6 \(\pm\) 6.1 \\ TP & 110.1 \(\pm\) 1.5 \\ COD & 11,256.7 \(\pm\) 20.7 \\ Zn & 64.2 \(\pm\) 0.6 \\ Fe & 65.6 \(\pm\) 0.8 \\ Cr & 0.3 \(\pm\) 0.02 \\ Cu & 0.01 \(\pm\) 0.001 \\ Cd & 0.01 \(\pm\) 0.002 \\ Pb & 0.002 \(\pm\) 0.001 \\ As & 0.05 \(\pm\) 0.002 \\ Hg & 0.02 \(\pm\) 0.001 \\ pH & 8.3 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chemical composition of raw anaerobic digestion piggery effluents (ADPEs). The results are presented as arithmetic means \(\pm\) standard deviations (\(n=3\)).  
to the dark brown color of the diluted ADPEs. To confirm this, we cultured NCU-39 in 10\(\times\) diluted ADPE pretreated by fungal decolorization for the following experiment.
# Action Classification for Partially Occluded Silhouettes by Means of Shape and Action Descriptors
## 3 Proposed Approach for Extraction and Classification of Action Descriptors
### Shape Description  
The shape description algorithm enables obtaining a numerical representation of a shape. It extracts the most distinctive features and reduces two-dimensional image matrix into a vector with numbers, or a single value in case of simple shape descriptors. Such simple descriptors are basic shape measurements or shape factors that capture general characteristics and usually are not used alone [38]. However, when calculated for more shapes and observed over time, they are more valuable. An appropriate selection of the representation helps to limit the influence of outliers, and shape generalization can be used additionally. Here, the Minimum Bounding Rectangle (MBR) is employed.  
An MBR defines a smallest rectangular region that contains all points of a shape [38; 39]. The algorithm creates a blob-like object that covers a foreground silhouette's area and is described by the coordinates of four corner points. The idea of using rectangular blobs is also known from the object detection and tracking approaches. Based on the corner coordinates, several characteristics can be calculated and combined into shape ratios. Basic MBR measurements include its length and width. The length of the rectangle can be calculated in two different ways. Firstly, as a distance between two fixed corners where width is a horizontal measurement and length is vertical (in relation to the coordinate axes). This approach is used to calculate other MBR-based descriptors. However, in the second method, the length is always the longer side of the rectangle, and width is the shorter one, no matter which corner points it concerns. These are referred to as'shorterMBR' and 'longerMBR'. Width and height are further used to estimate perimeter, area, eccentricity, elongation and rectangularity. Eccentricity is a ratio of width to length of the MBR, while elongation is a value of eccentricity subtracted from 1. Rectangularity shows the similarity of an original silhouette to its MBR and is obtained as the ratio of the area of a shape to the area of its MBR. Ultimately, nine different MBR measurements and ratios are considered as shape descriptors for the evaluated approach.  
In the shape description step, each foreground mask is represented using selected shape descriptor. As a result, an image is reduced to a single value. The descriptors of all frames from a given sequence are put into a vector and subjected to the normalization to a range of 0 to 1. Normalized vector can be plotted as a line graph to observe how shape descriptors change over time. The number of shape descriptors of a single sequence equals the number of its video frames; therefore, these vectors are still of different length.
# Three-Dimensional Multifaceted Attention Encoder-Decoder Networks for Pulmonary Nodule Detection
###### Abstract  
Lung cancer is one of the most dangerous cancers in the world, and its early clinical manifestation is malignant nodules in the lungs, so nodule detection in the lungs can provide the basis for the prevention and treatment of lung cancer. In recent years, the development of neural networks has provided a new paradigm for creating computer-aided systems for pulmonary nodule detection. Currently, the mainstream pulmonary nodule detection models are based on convolutional neural networks (CNN); however, as the output of a CNN is based on a fixed-size convolutional kernel, it can lead to a model that cannot establish an effective long-range dependence and can only model local features of CT images. The self-attention block in the traditional transformer structures, although able to establish long-range dependence, are as ineffective as CNN structures in dealing with irregular lesions of nodules. To overcome these problems, this paper combines the self-attention block with the learnable regional attention block to form the multifaceted attention block, which enables the model to establish a more effective long-term dependence based on the characteristics of pulmonary nodules. And the multifaceted attention block is intermingled with the encoder-decoder structure in the CNN to propose the 3D multifaceted attention encoder-decoder network (MAED), which is able to model CT images locally while establishing effective long-term dependencies. In addition, we design a multiscale module to extract the features of pulmonary nodules at different scales and use a focal loss function to reduce the false alarm rate. We evaluated the proposed model on the large-scale public dataset LUNA16, with an average sensitivity of 89.1% across the seven predefined FPs/scan criteria. The experimental results show that the MAED model is able to simultaneously achieve efficient detection of pulmonary nodules and filtering of false positive nodules.  
pulmonary nodule detection; irregular receptive fields; encoder-decoder; computer-aided diagnosis Article
## 2 Thermal Pyrolysis
### Co-Pyrolysis and Catalytic Pyrolysis  
In addition to co-combustion and co-gasification, co-pyrolysis has recently received ample attention. One of the primary benefits of co-pyrolysis is the reduced release of harmful compounds into the environment. This approach, in contrast to single pyrolysis, decomposes two separate starting materials in a single operation. Others have demonstrated that, in some settings, the chosen fractions of polymers such as polypropylene and polystyrene co-pyrolyzed with biomass may have a better effect than the single pyrolysis of plastic/biomass [68; 69]. Furthermore, the action may be enhanced using certain catalysts. Co-pyrolysis allows for the modification of the composition of solid, liquid, and gaseous products and their adaptation as liquid fuels (Figures 4 and 5). The conclusion is that the process's future efficiency is contingent on the development of a co-pyrolysis process that integrates catalytic materials into the reactors. This level of efficiency could be attained by optimising catalyst synthesis procedures from industrial and agricultural waste fractions [70]. Catalytic pyrolysis of polymer waste processing is an alternate method to individual pyrolysis and polymeric co-pyrolysis. One of the main goals of catalytic pyrolysis and co-pyrolysis is to increase the value of the biomass pyrolysis process. One of the most important aspects for many scientists is to produce aromatic hydrocarbons from catalytic pyrolysis, particularly with the use of Zeolite Socony Mobil-5 (ZSM-5), which is regarded as one of the most efficient pyrolysis catalysts [70].  
Figure 4: BTEX yield as a function of material and catalyst ratio (based on [19]).  
Influence of Polymer Type on Technological Aspects of Pyrolysis and Catalytic Pyrolysis Requirements  
The operational parameters of the pyrolysis process are determined by the type of polymer used. Various polymer applications have different requirements, such as reactor type and ideal temperature ranges. For example, PP may be changed at temperatures ranging from 300 to 740 \({}^{\circ}\)C, and the best type of reactor for this application is a semi-batch reactor. In contrast, for PET thermal transformation, the best efficiency can be obtained in a fixed-bed reactor at 500 \({}^{\circ}\)C. The pyrolysis conditions directly affect the output of gas and liquid products [12]. During typical pyrolysis at 690 \({}^{\circ}\)C, around 40% of the entire amount of final product is pyrolytic oil, of which more than half is benzene, toluene, and xylene. At higher temperatures and using a fluidized bed reactor on a technological scale at 730 \({}^{\circ}\)C, the amount of compounds in the total mass of organic products such as toluene, xylene, styrene, and benzene was 31.4%. This demonstrates a link between rising process temperatures and organic matter degradation [71]. At 700 \({}^{\circ}\)C, a high concentration of olefins was detected. The principal products included 20-31 wt.% ethane, 14-18 wt.% propane, 3-6 wt.% butane, and 19-23 wt.% pyrolysis gasoline.