esa-sceva/satcom-chunk-collection huggingface dataset:
# General Total Least Squares Theory for Geodetic Coordinate Transformations
###### Abstract  
Datum transformations are a fundamental issue in geodesy, Global Positioning System (GPS) science and technology, geographical information science (GIS), and other research fields. In this study, we establish a general total least squares (TLS) theory which allows the errors-in-variables model with different constraints to formulate all transformation models, including affine, orthogonal, similarity, and rigid transformations. Through the adaptation of the transformation models to the constrained TLS problem, the nonlinear constrained normal equation is analytically derived, and the transformation parameters can be iteratively estimated by fixed-point formulas. We also provide the statistical characteristics of the parameter estimator and the unit of precision of the control points. Two examples are given, as well as an analysis of the results on how the estimated quantities vary when the number of constraints becomes larger.  
Keywords:total least squares; Gauss-Newton algorithm; errors-in-variables; affine/orthogonal/similarity/rigid transformations; constraints; general algorithm +
Footnote †: journal: Applied Physics Letters
## 2 Materials and Methods
### Cell Viability Assay  
MTT assay was utilized to evaluate cell viability. Briefly, cells were seeded for 24 h in a 96-well plate (NunclNunclonTM, NuncGmbH & Co., Wiesbaden, Germany) with a density of 1.2 \(\times\) 10\({}^{4}\) cells/well. Then were treated with _V. macrophylla_ EO at concentration of 1.25; 2.5; 5 and 10 \(\mu\)g/mL for 24, 48 and 72 h. After the incubation period, 0.5 mg/mL of MTT (Sigma, Deisenhofen, Germany) was added to each well for 2 h at 37 \({}^{\circ}\)C and the cells were dissolved with 200 \(\mu\)L/well of dimethylsulfoxide (Merck, Darmstadt, Germany). The absorbance of formazan was read at 570 nm on a scanning microtiter spectrophotometer plate reader. The results were calculated as the percentage of viability in relation to the untreated cells standardized to 100%. They are the mean \(\pm\) SD of three separate experiments done in triplicate.  
Figure 1: Vepris macrophylla tree.
## Materials and Methods
### Flux Data  
The study site has an eddy-covariance system for measuring the flux of CO\({}_{2}\) between the ecosystem and the atmosphere (see [13; 14]). An additional system was deployed to measure BVOCs. Isoprene was measured in 2011 by the eddy-covariance system based on the FIS [45]. Isoprene, monoterpenes and methanol were measured by PTR-MS (Ionicon, Innsbruck, Austria) [46] in 2012 using virtual disjunct eddy covariance. The eddy-covariance flux and meteorological parameters were measured on a 32-m walkup scaffold tower, approximately 10 m above the canopy. Complete details of the eddy-covariance technique and BVOCs measurements are provided by [PERSON] et al. [13] for the 2011 campaign and by [PERSON] et al. [14] for the 2012 campaign. Measurements were recorded from May to September 2011 and from May to October 2012.  
CO\({}_{2}\)-flux data were gap-filled and partitioned using marginal distribution sampling described by [47]. The CO\({}_{2}\) fluxes (net ecosystem exchange, NEE) were partitioned into two components: gross primary production (GPP) and ecosystem respiration (Reco). This method is a nighttime-based approach where Reco is estimated by nighttime data using a respiration model, and GPP is then calculated as the difference between Reco and NEE. We considered only days with average photosynthetically active radiation (PAR) between 10:00 and 12:00 (CST) higher than 600 \(\upmu\)mol m\({}^{-2}\) s\({}^{-1}\) and calculated the average values for GPP and isoprene emissions between 10:00 and 12:00 (CST) to coincide with the overpass of MODIS Terra to obtain daily flux data. LUE was calculated as:  
\[\text{LUE}=\text{GPP}/\text{Fapar}\times\text{PAR}\]  
The fraction of absorbed PAR (fAPAR) was derived by [48]:  
\[\text{fAPAR}=1-\text{PARbc}/\text{PARin}\times\text{e}^{1.35}\]  
where PARbc is PAR below the canopy and PARin is incident PAR. e\({}^{1.35}\) represents the mean effect of the absorptivities in the spectral bands of PAR and global solar radiation.  
Additional meteorological variables were measured continuously at the site. Incident PAR above the canopy, air temperature and volumetric soil-water content (SWC) at 10 cm were also measured. See [13; 14] for details.
# A Testbed to Evaluate the FIWARE-Based IoT Platform in the Domain of Precision Agriculture
## 3 Fiware
### FIWARE NGSI Context Management
#### 3.2.1 Context Information Model  
All information handled by applications is modelled through the definition of a Context Information Model composed of contextual elements which we will refer to as _entities_. Entities may refer to physical objects (i.e., sensors or actuators), to hardware and software (i.e., an IoT programme) and to high level abstractions that model _things_ and group both physical objects and _resources_.  
Entities are represented by the generic data structures shown in Figure 1. Entities are uniquely identified by an Entity Id/ Entity Type pair. Entities have _attributes_, characterised by a triplet (<name_attribute, type, value>). And each attribute can have optional _semantic data_ (metadata) also characterised by triplets <name_metadata, type, value>. The values of the attributes become the system's contextual information. A fundamental concept is that entities are not linked to a specific representation formalism. For example, they can be represented as an XML document (SensorML, ContextML, etc.) or as entries in a NoSQL database (MongoDB). An important advantage of this conceptual model is its compatibility with IoT formats (SensorML) while also allowing additional extensions.
## 4 Drug Delivery Systems--Applications in Infectious Diseases
### Stimuli-Responsive DDS for Triggered Antibiotic Release
#### 4.3.2 Pathogen-Sensitive DDS  
An application of an infection-responsive antibacterial agent is the coating of medical implants with vancomycin conjugated to an _S. aureus_-sensitive peptide sequence. In the absence of _S. aureus_, the antibiotic is not released, whereas in the presence of _S. aureus_ in the area surrounding the implant, this sensor peptide will be recognized and then cleaved by a staphylococcal enzyme, leading to the release of the antibiotic only in the presence of the pathogen [24].  
Daptomycin-loaded polydopamine-coated gold nanocages conjugated to antibodies against _S. aureus_ lipoproteins have been shown to be effective in in vivo MRSA biofilm models. A similar type of gentamicin-loaded nanocages were effective against _P. aeruginosa_ biofilms when conjugated to an antibody against a _P. aeruginosa_ outer membrane protein. However, the same nanocage formulation was not efficient when loaded with ceftroline or vancomycin and conjugated to anti-Spa antibodies against _S. aureus_[25].
## 1 Introduction
Some previous experiments on snowdrifts using wind tunnels have used bran, or other particles, as a substitute for natural snow, but these cannot completely replicate the distribution of natural snow. Tests have been carried out in advanced climate wind tunnels [26], where the influencing factors that may affect the results, such as the wind speed, temperature, and snowfall rate, are fully controllable. However, they are very expensive and not readily available for most researchers. Snowdrift loads around buildings or on the roofs, which have a great impact on functionality and security of buildings, require particular attention. However, for the existing research methods, numerical simulation still needs to be improved with data from field observations and wind tunnel tests. Field observations are rarely available when considering security and technical issues, even though they should provide the most reliable data. Wind tunnel tests are the main source of data, but the expense of experiments in climate wind tunnels is so high that few experiments are reported, and it has restricted further studies. What is more, the wind speed and direction of field observations vary dramatically, so some conclusions may be confused when the natural environment is problematic. Hence, this paper proposes a new approach to investigate the snowdrift loads with a facility in which the wind speed and direction are controllable and a snowing environment, just like natural snowfall, is available. The purpose of this facility is to provide a new approach to study snow distribution under the action of wind. In comparison with traditional wind tunnel tests, there will be a 90% or more decrease in the construction cost because the facility need not be equipped with a refrigerating system. Besides that, the operating expense of the facility is much lower than climate wind tunnels. Transportation of snow particles can be classified into three processes, i.e., creep, saltation, and suspension. Saltation, which is widely accepted as contributing most to the total transfer volume, is a process in which snow particles move with repeated leaping up, or jumping, on the snow surface. The height of saltation is usually below 0.1 m. Generally, the length of saltation \(L\)[27] is suggested to be  
\[L\cong 10\;\text{h}. \tag{1}\]  
Yet, to ensure that the saltation process could be accurately reproduced on the roofs or around the building, it is suggested that the characteristic length of the prototype model is larger than the length of saltation \(L\). In this study, the design parameters of the facility, experiment method, and the adopted similarity criteria are introduced and discussed. Finally, a prototype model with external dimensions of \(1.0\times 1.0\times 1.0\) m\({}^{3}\) was selected, taking both economy and theory into consideration, to study the surrounding snow distribution and evaluate the repeatability and reliability of the new approach.
###### Abstract  
Utilizing idle space for agricultural planting can generate production profits while greening the urban environment. How can the space available for agricultural planting in cities be inventoried and quantified, and what is the production potential? With the help of GIS, spatial analysis was carried out, and more objective conclusions were drawn through calculation. This paper takes the roof space in Shibei District of Qingdao as an example to study: First, we analyzed the influencing factors and inventory standards of roof agricultural planting; second, we selected inventory standards for idle roof space inventory and conducted statistical analysis of the data obtained from the inventory. Furthermore, combining the annual yield of vegetables per unit area and the annual consumption standards of vegetables by citizens, we calculated the yield and supply and demand; next, we summarized the research results, analyzed their reliability and the advantages and disadvantages of this inventory, and derived formulas for calculating the agricultural production potential of rooftops and urban spaces. Finally, we concluded that the idle roof area in cities and the potential for agricultural production are significant. The research results indicate that the roof area of urban buildings in the Shibei District of Qingdao is 383.3 hectares, with an annual vegetable production potential of 25,800 tons, which can supply the urban population of 184,300. Based on the above research, it is proposed that rooftop agriculture should be given priority in the future development of urban agriculture, and it is recommended that other urban spaces should be inventoried to promote the development of urban agriculture.  
rooftop agriculture; space inventory; analysis of agricultural production potential; urban agriculture +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Effect of Carbon Felt Modification
#### 3.2.2 Electrochemical Performances of Tannery Wastewater Oxidizing Bioanodes  
Chronoamperometry Analysis  
The ability to generate a current of oxidation on unmodified electrodes and electrodes modified by clay minerals was evaluated directly in real tanner wastewater completed with acetate (20 mM). The experiments were conducted in parallel and were inoculated at the same time with the same acclimated activated sludge (5% _v/v_). All the working electrodes were maintained at \(-\)0.2 V vs. SCE. The current density on LTA zeolite and bentonite-modified electrodes increased rapidly after the inoculation, reaching 1.5 A/m\({}^{2}\) and 0.5 A/m\({}^{2}\), respectively, after only 2 days (Figure 3). Then, the current decreased because of acetate depletion. Successive additions of 20 mM acetate restarted the current generation. After the third addition of acetate, the electroactive biofilm colonizing the modified anodes reached maximum current densities of 24.5 A/m\({}^{2}\) and 27.9 A/m\({}^{2}\) for zeolite and bentonite, respectively. In contrast, for unmodified carbon felt, the initial lag time before any current increase was detected was very long. The oxidation current began to increase after 5 days. The highest current density, of 16.9 A/m\({}^{2}\), was also reached after the third addition of acetate. In sum, coating the carbon felt with clay minerals changed its bioelectrochemical behavior. The start-up time of the current generation using a hydrophilic surface (LTA zeolite and bentonite) was shorter than that required by a hydrophobic surface (unmodified carbon felt). Several groups have reported that microorganisms adhere differently to materials with different hydrophobicity, and it is easier for bacteria to adhere to  
Figure 2: ESEM images of unmodified and modified carbon felt. (**A**) Commercial carbon felt, (**B**) Linde Type A (LTA) zeolite-modified carbon felt, (**C**) Bentonite-modified carbon felt.  
hydrophilic materials than hydrophobic ones, therefore, hydrophilic materials should be applied as anodes in MFC systems to shorten the start-up time [16; 17].
## 8 Conclusions  
Aiming at the problem of reliability prediction of rolling bearings, this study proposed CYCBD algorithm improved by Ivy optimization algorithm to efficiently remove signal noise from vibration signals. The reliability modeling method based on logistic regression is constructed, the integrated learning model combining AdaBoost and MKRVM is further used to accurately predict the bearing reliability, and the effectiveness and accuracy of the method are verified. The innovations of this paper are as follows:  
1. Improved Denoising Method: A CYCBD method enhanced by the Ivy algorithm is proposed for efficiently denoising bearing vibration signals. By optimizing the cyclic frequency and filter length of the CYCBD method using the Ivy algorithm, noise components in the signal are effectively removed, significantly improving the denoising performance.
2. Feature Dimensionality Reduction and Visualization: To address the issue of high-dimensional bearing feature sets, a novel dimensionality reduction method, PaCMAP, is employed. This method reduces the dimensionality of multidimensional feature sets and achieves visualization of the feature space, providing a more intuitive analysis of feature distributions.
3. Reliability Prediction Model: To meet the reliability prediction requirements of rolling bearings, an AdaBoost-MKRVM-based prediction model is developed. This model integrates ensemble learning with the Relevance Vector Machine to improve prediction accuracy, offering an effective solution for rolling bearing reliability evaluation.  
Compared with the results of the citation [23] with similar logic, the prediction error RMSE is 0.8982, and the MAE of the AdaBoost-MKRVM prediction model proposed in this paper is 0.052, which further improves the prediction accuracy.
## 4 Application
### Additive Manufacturing (AM)  
Concept designs were ranked according to their weight and strength properties in the last step of the generation and evaluation cycle. According to this ranking, the design concept with the best performance was additively manufactured. In this process, the CAD model was converted to STL format and made ready for printing. The concept design was produced by adjusting the printer settings, such as layer height, infill density, and print speed, according to the desired precision and print quality.  
The final iteration's concept design with the best mechanical properties was produced using two different additive manufacturing methods: SLA (stereolithography) and FDM (fused deposition modeling). Table 4 compares the production process of this part (model generated by GAN) using SLA and FDM techniques. While polylactic acid (PLA) offers an environmental advantage due to its biodegradability, the use of liquid resin in SLA provides superior surface quality. Moreover, SLA's finer layer thickness makes it more suitable for this application, which demands high detail and surface quality. In terms of production speed, SLA completes the process in 175 min, whereas FDM takes 317 min. However, FDM emerges as a more cost-effective option with a cost of USD 0.61 compared to SLA's USD 1.17.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Methods** & **Parts** \\ \hline \hline \multirow{2}{*}{SLA} & Material & : Resin \\  & Quantity of Material & : 18 mL \\  & Layer Thickness & : 0.05 mm \\  & Production Time & : 175 min. \\  & Cost & : USD 1.17 \\ \hline \multirow{2}{*}{FDM} & Material & : PLA \\  & Quantity of Material & : 22 mL \\  & Layer Thickness & : 0.12 mm \\  & Production Time & : 317 min. \\  & Cost & : USD 0.61 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Production comparison of SLA and FDM methods.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Generated Models** & **Properties** & \\ \hline \hline \multirow{2}{*}{SLA} & Part & : P\_98 \\  & Material & : AISi10 Mg \\  & Volume (cm\({}^{3}\)) & : 103.23 \\  & [PERSON] (MPa) & : 71.2 \\  & Safety factor & : 3.79 \\  & Part & : P\_137 \\  & Material & : AISi10 Mg \\  & Volume (cm\({}^{3}\)) & : 98.28 \\  & [PERSON] (MPa) & : 61.8 \\  & Safety factor & : 4.37 \\  & Part & : P\_358 \\  & Material & : AISi10 Mg \\  & Volume (cm\({}^{3}\)) & : 95.36 \\  & [PERSON] (MPa) & : 69.8 \\  & Safety factor & : 3.86 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Examples of joints produced by the 3 DGAN model at the end of the fourth iteration and their physical properties.
## 5 Our Proposed Novel Resource Allocation Scheme
### Optimizing User Pairing and Subcarrier Mapping \(\mathbf{x}\):  
Given \(\underline{\mathbf{r}}\) and \(\Phi(\underline{\mathbf{r}})\), the objective function becomes:  
\[F(\mathbf{x},\underline{\mathbf{r}},\mathbf{\Phi}(\underline{\mathbf{r}}))=\sum_{i=1}^{N}\sum _{j=1}^{N}\sum_{k=1}^{K}x_{i,j,k}R_{i,j,k}(x_{i,j,k}) \tag{28}\]  
This is a standard three dimensional assignment problem and is NP hard in most cases [31]. In order to deal with it practically, we have developed a sub-optimal method which also has pretty good performance. This principle of this method is to reduce this three-dimensional assignment problem to a two-dimensional assignment problem.  
Similarly to Equation (27), the whole sum rate achieved by adding all subcarriers is composed of two terms: the first one is the sum rate when only \(\mathbf{y}_{A}\) is used for decoding, the second one is additional information obtained from BS B, which is limited by two factors. One is the additional information \(\mathbf{y}_{B}\) can offer conditioned by \(\mathbf{y}_{A}\), the other one is how many resources the backhaul link could afford. These two factors are described by the bound of multiple access and cut set bound in information theory [12]. Based on these observations above, it is reasonable to let \(\mathbf{y}_{A}\) be fulfilled with data as much as possible, so that the information required from BS B is less. This idea can also maximize the worst case, where the backhaul resource is close to zero.  
Therefore, for each timeslot, we can first map scheduled \(K\) users in base station A onto the \(K\) subcarriers such that achievable sum rate of these users is maximized, which is also consistent with the no-cooperation scenario. The procedure can be easily achieved by selecting the best user for each subcarrier. Here, we use a mapping function \(\alpha(i):\left\{1,2,...,K\right\}\rightarrow\left\{1,2,...,K\right\}\) to denote this assignment. After that, the objective function is reduced to:  
\[F(\boldsymbol{x},\boldsymbol{\varGamma}\boldsymbol{\Phi}(\underline{r}))=\sum \limits_{i=1}^{N}\sum\limits_{k=1}^{K}x_{i,j,\alpha(i)}R_{i,j,\alpha(i)}(x_{i, j,\alpha(i)}) \tag{29}\]  
This \(\alpha(i)\) procedure is a suboptimal procedure but it reduces the dimensions of the problem expressed in Equation (28) from three to two. We can observe this pre-mapping brings about a tiny performance loss compared to the optimal solution.  
Then we pair users in base station A with users in base station B by using the function \(\beta(i):\left\{1,2,...,K\right\}\rightarrow\left\{1,2,...,K\right\},\) which is a perfect matching problem [15]. By relaxing the binary variables to continuous variables in [01] and solving this linear programming problem, we get the exactly optimal binary solution.
## 3 Results
### Carbon Deposits Formed in CME/Air and CH\({}_{4}\)/Air Flames
#### 3.1.2 CH\({}_{4}\)/Air Flame  
In Flame II, a CH\({}_{4}\)/air co-flow flame, the substrate was inserted into the flame volume at an HAB of 50 mm and 60 mm for a residence time of 1 min. The shortened residence time of the substrate in this flame ensured that deposited carbonaceous material was not oxidized during the deposition process and avoided excess thermal stress on the substrate holder.  
The introduction of the disc at 50 mm HAB resulted in deposition of the carbonaceous material, forming two distinct regions on the surface of the substrate. The deposits resemble the shape of a flat washer with an inner and outer diameter. The center area (circular region) has a light contrast resembling the metallic color of the substrate and is encompassed by an outer deposition region of black soot that forms a \"ring-like\" fixture (Figure 3B (Zone-1, Zone-2)). As illustrated in Figure 3B, the sooty \"ring-like\" fixture (Zone-1) and the disc center (Zone-2) correspond to different radial areas within the flame. Deposition of Zone-1 material occurred within the luminous envelope at the flame's outer  
Figure 3: Representative SEM images of early soot deposits to fully developed hydrophobic films deposited on the surface of the SS substrate introduced at various HAB for a (**A**) CME/air and (**B**) CH\({}_{4}\)/air flames. (**A**) Deposits formed in Flame I at HAB of 10 mm (a1,a2), 12 mm (b1,b2), 15 mm (c1,c2), and 20 mm (d1,d2) for a substrate residence time of 5 min. (**B**) Deposits formed in Flame II at HAB of 50 mm (Zone-1 (e1–e3) and Zone-2 (f1–f3)) and 60 mm (g1–g3) for a substrate residence time of 1 min.  
region while the deposits of Zone-2 originated from the pyrolysis zone in the center of the flame. Zone-2 deposits, similar to the CME/air flame at an HAB of 10 mm, were formed within the pyrolysis zone of the flame where there is little to no soot formation [36], therefore the relatively \"clean\" center surface shown in light and SEM imaging is to be expected (Figure 3B(Zone-2,f2,f3)). The Zone-1 \"ring-like\" deposits formed in the luminous zone of the flame produced a hydrophobic C-layer (Figure 3B(e1)). Unlike the hydrophobic layers formed in the CME/air flame, the morphology of Zone-1 deposits is neither interconnected nor weblike. Instead, clusters of non-spherical soot form irregular structures (Figure 3B(e2,e3)) similar in appearance to the quasisquare-shaped islands identified by [PERSON] et al. [19; 22].  
At a substrate insertion of 60 mm HAB, a superhydrophobic C-layer was formed (Figure 3B(g1-g3)). Unlike the deposits of the \"ring-like\" pattern formed at 50 mm HAB, the ones formed at 60 mm HAB displayed \"spiderweb-like\" structures similar to those formed in the middle region of the CME/air flame. This is a notable phenomenon that demonstrates the importance of flame structure for C-layer development: it is possible to create similar C-layers with nearly identical hydrophobic performance from two different fuels by utilizing the structure of the flame and the soot evolution process.