esa-sceva/satcom-chunk-collection huggingface dataset:
# Monthly Precipitation over Northern Middle Atlas, Eastern Morocco: Homogenization and Trends
## 3 Results
### Regionalization of Stations  
The station maps in Figure 4 show the cluster analysis of the rainfall series, giving an idea of the different regions of precipitation at the level of the northern Middle Atlas. Climatol limits cluster analysis to a maximum of 100 stations by default. This makes it possible to avoid dealing with overly large correlation matrices, and also to avoid very dense graphs that are difficult to read. However, this can be changed by the user to include all series in the analysis (using the nclust argument in the homogeneous function). Additionally, Climatol limits the number of clusters to a maximum of nine [19]. Given the limited number of stations (22), these defaults are acceptable.  
The results obtained display four clusters for the raw data, and two clusters for the homogenized data. The grouping of the homogenized data follows the exposure of the slopes, and the altitude to a lesser extent (Figures 1 and 4). The two blocks of stations were separated by the mountain range of Jbel Bouiblane, where the altitude reaches 3000 m.  
Moreover, the two clusters produced after the homogenization procedure have different monthly and seasonal rainfall regimes. Indeed, the stations in the northwestern part of  
Figure 4: Clusters of stations (**A**) before and (**B**) after homogenization.  
Figure 3: Correlograms of the first differences of the series stations’ raw data (on the **left**) and adjusted data (to the **right**).  
Jbel Bouiblane generally record maximum rainfall in the month of February. Meanwhile, the stations to the south and southeast parts record peak precipitation in April. Moreover, it is very remarkable that the amount of precipitation falling on the first cluster is higher than the other (Figures 5 and 6).  
The figures of the seasonal precipitation regimes also show a spring regime for the southern and southeastern parts, and a winter regime for the northern and northwestern parts (Figure 6).  
Figure 5: Monthly rainfall regime of the two clusters (**B1**, **B2**) after homogenization.  
Figure 6: Seasonal rainfall regime of the two clusters (**B1**, **B2**) after homogenization.  
Method performance and data quality are assessed using the root mean square error (RMSE) values. The RMSE is calculated by comparing the estimated and observed data in each series. High values of this parameter indicate poor quality of the series, or that the station is located in a particular site with a distinct microclimate [19].  
The results obtained show RMSE values oscillating between 0.5 and 38.7 mm, with an average of 8.5 mm for all the series studied. These values generally remain low, and indicate a certain reliability of the data (Figure 7). On the other hand, the geographical location of station S21, which recorded the maximum value of RMSE, is in a depression between the mountains, which gives it a somewhat special microclimate compared to neighboring stations. Furthermore, the values of the SNHT oscillate between 2.5 and 26.6, with an average of 6.28 (Figure 7).
## 3 Methods  
In this work, we investigated the effectiveness of two classification methods (Random Forest and Logit Lasso) with three training strategies, i.e., unbalanced strategy, oversampling of the minority class and subsampling of the majority class. As depicted in Figure 1, we adopted a hold-out approach, randomly selecting \(M=100\) samples for the independent test (i.e., the hold-out test). A repeated k-fold validation (\(N=10\) iterations, \(k=10\) folds) was selected as cross-validation approach on the training set. In detail, each of the three strategies was combined with each of the two classification algorithms resulting in six training schemes. For each scheme, we evaluated both the importance and variability of the features. In addition, the consensus degree on the probability scores of the different strategies was assessed as the correlation between each couple of schemes. Each step is detailed in the following sections. We used a PC with the following hardware configuration: Intel Core i7-8550U CPU @ 1.99 GHz x 4, and 16 GB RAM to run the experiments. All the analyses were performed by using R Statistical Software (v4.1.1., R Core Team 2021) with a run-time of 9.8 min for the execution of the entire framework.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **N. Patients** & **N. Positive/ N. Negative** \\ \hline
**Overall** & 635 & 214/421 \\
**Histologic Type** & & \\ _Ductal_ & 512 & 185/327 \\ _Lobular_ & 67 & 20/47 \\ _Special type_ & 56 & 9/47 \\
**Diameter** & & \\ _Tla_ & 31 & 3/28 \\ _T1b_ & 125 & 18/107 \\ _T1c_ & 281 & 88/193 \\ T2 & 198 & 105/93 \\ ER & & \\ _Positive_ & 571 & 193/378 \\ _Negative_ & 64 & 21/43 \\
**Grading** & & \\ _G1_ & 175 & 35/140 \\ G2 & 287 & 111/176 \\ G3 & 173 & 68/105 \\
**HER2** & & \\ \(0\) & 471 & 161/310 \\ \(1\) & 78 & 23/55 \\ \(2\) & 46 & 21/25 \\
3 & 39 & 9/30 \\
**Multifocality** & & \\ _Positive_ & 143 & 61/82 \\ _Negative_ & 492 & 153/339 \\
**In situ component** & & \\ _Positive_ & 369 & 114/255 \\ _Negative_ & 266 & 100/166 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Characteristics of the samples collected in this study.
# Rethinking LEO Mega-Constellation Routing to Provide Fast Internet Access Services
## 3 Our Proposed Algorithm  
In this section, we present the Internet Fast Access Routing (IFAR) algorithm, which transmits user data to the ground core network as quickly as possible, without the need to calculate the optimal path of the whole network. The IFAR algorithm employs a matching strategy to associate landing satellites, which are responsible for establishing feeder links with Earth stations, with non-landing satellites. This association is performed in a manner that satisfies the link capacity constraints, while minimizing the number of hops required for data forwarding. Then, a linear programming, that can be solved in polynomial time, is used to match the landing satellite (satellite that establishes feeder links with Earth stations) and non-landing satellite, so that each non-landing satellite has corresponding landing satellites as the destination for data forwarding, under the premise of meeting the link  
Figure 1: Schematic diagram of satellite orbit parameters.  
Figure 2: A partial constellation diagram marked by various modeling parameters.  
capacity constraints. Finally, the optimal paths between the source and destination satellite sets are calculated by the forwarding strategy.  
How to select the optimal access satellite for the user according to the satellite-user link quality and satellite available resources, is not considered in our algorithm. We work with the assumption that all the satellite-Earth topological relationships, including satellite-user links and satellite-Earth station (ES) links, are given in all the time intervals.
## 3 MIPs' Applications
### MIPs in Drug Delivery
[PERSON] _et al._ prepared MIPs for Propranolol (a \(\beta\)-adrenergic antagonist) using methacrylic acid (MAA) as a functional monomer to create a transdermal controlled release device and they demonstrated that the permeation of Propranolol was slower for the MIP than from the non-imprinted polymer. Thus, these Propranolol-imprinted systems can be used to prolong the delivery profile [185]. Similar results were obtained with other drugs, such as tetracycline [186] and sulfasalazine [187]. [PERSON] and [PERSON] [186] using tetracycline as template synthesized MIPs with higher binding ability compared with corresponding non-imprinted polymers. The obtained results indicated that the high MIP affinity can be utilized in control release applications, in fact the tetracycline release from MIP was slower than non-imprinted polymer. In another study [188] a molecularly imprinted polymer enables to rebind nicotinamide selectively and release it in a sustained way was prepared. MIPs microspheres have shown also a higher binding properties and sustained release compared to the non-imprinted one. This polymer could represent a promising system in the preparation of nicotinamide controlled formulations for oral administrations. In order to get controlled release of nicotinamide, various MIPs have been synthesized with methacrylic acid and ethylene glycol dimethacrylate by precipitation polymerization. It has been found that the use of different stoichiometric ratio between template, monomer, and cross-linking agent influences binding and release properties of the polymer. Intelligent drug release, refers to the release of a therapeutic agent, may occur as a result of a specific stimuli such as the presence of another molecule. A system with similar characteristics, able to release testosterone at a rate depending on the concentration of hydrocortisone, was described by [PERSON] _et al._ In this study, hydrocortisone as template was used for the preparation of MIP. After the removal of target analyte, the MIP was loaded with testosterone, which is a structurally similar molecule. It was seen that the rate of testosterone release increased when hydrocortisone was present in the solution as a result of template responsive release [189]. Molecularly imprinted polymers can be used also to bind several substances in the gastrointestinal tract, blocking their absorption in the body, as a complement of the pharmacological therapy. In this contest, MIPs as chemical traps to remove undesirable substances from the body, such as glucose, cholesterol [182, 190, 191], bile acid [192] and melittin [193] were developed. Hoshino and coworkersprepared imprinted polymers nanoparticles able to efficiently capture the cytotoxic peptide melittin in the bloodstream, synthesizing protein-size polymer particles with a binding affinity and selectively comparable to those of natural antibodies, by combining MIP nanoparticle synthesis with a functional monomer optimization strategy [193].
# Pixel Circuit Designs for Active Matrix Displays
## 1 Introduction
### TFT Devices
#### 1.3.2 Ltps Tft  
LTPS TFT represents the next-generation TFT technology after a-Si TFT. LTPS TFT is made using a laser crystallisation process and possesses excellent electrical characteristics, with field-effect mobility of up to 50-200 cm\({}^{2}\)/(Vs), higher than that of a-Si TFT and MO TFT [32]. The LTPS TFT has fast switching speeds. It can be fabricated with small size and low parasitic capacitance, which results in high-resolution displays [33; 34]. However, LTPS material is difficult to prepare at low temperatures and large areas [3]. Their fabrication techniques and equipment differ from conventional a-Si TFTs, resulting in higher process costs than a-Si and MO TFTs. As a result, LTPS TFIs are mainly used in small and medium-sized high-resolution displays.
# Nickel-Based Structured Catalysts for Indirect Internal Reforming of Methane
###### Abstract  
A structured catalyst for the dry reforming of methane (DRM) was investigated as a biogas pre-reformer for indirect internal reforming solid oxide fuel cell (IIR-SOFC). For this purpose, a NiCrAl open-cell foam was chosen as support and Ni-based samarium doped ceria (Ni-SmDC) as catalyst. Ni-SmDC powder is a highly performing catalyst showing a remarkable carbon resistance due to the presence of oxygen vacancies that promote coke gasification by CO\({}_{2}\) activation. Ni-SmDC powder was deposited on the metallic support by wash-coating method. The metallic foam, the powder, and the structured catalyst were characterized by several techniques such as: N\({}_{2}\) adsorption-desorption technique, X-ray diffraction (XRD), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), focused ion beam (FIB), temperature programmed reduction (H\({}_{2}\)-TPR), and Raman spectroscopy. Catalytic tests were performed on structured catalysts to evaluate activity, selectivity, and stability at SOFC operating conditions.  
structured catalyst; metallic support; Ni-based catalyst; wash-coating; DRM; catalytic tests; carbon formation; SOFC pre-reformer
###### Abstract  
At the verge of the launch of the first commercial fifth generation (5G) system, trends in wireless and optical networks are proceeding toward increasingly dense deployments, supporting resilient interconnection for applications that carry higher and higher capacity and tighter latency requirements. These developments put increasing pressure on network backhaul and drive the need for a re-examination of traditional backhaul topologies. Challenges of impending networks cannot be tackled by star and ring approaches due to their lack of intrinsic survivability and resilience properties, respectively. In support of this re-examination, we propose a backhaul topology design method that formulates the topology optimization as a graph optimization problem by capturing both the objective and constraints of optimization in graph invariants. Our graph theoretic approach leverages well studied mathematical techniques to provide a more systematic alternative to traditional approaches to backhaul design. Specifically, herein, we optimize over some known graph invariants, such as maximum node degree, topology diameter, average distance, and edge betweenness, as well as over a new invariant called node Wiener impact, to achieve baseline backhaul topologies that match the needs for resilient future wireless and optical networks.  
cloud-radio access networks; survivability; resilience; graph theory; graph invariants; topology optimization; node wiener impact
# Influence of Quality of Mounting Process of RF Transistors on Their Thermal Parameters and Lifetime
###### Abstract  
The paper presents the results of investigations illustrating the influence of imperfections in the soldering process on thermal properties of transistors operating in RF (Radio Frequency) systems. The methods of measurements used to determine the junction and case temperature of the tested transistors and their thermal resistance are described. The results of the performed measurements are presented and discussed, and their statistical analysis is carried out. The correlation between thermal parameters of the tested transistors, parameters of the assembly process and the measurement conditions is investigated. Some calculation results illustrating an influence of device thermal resistance and dissipated power on changing its lifetime are shown and discussed. It is also shown that no correlation between the void sizes and the device thermal resistance and lifetime is observed. Possibilities of improving the assembly process are indicated, which allows extending the expected lifetime of the tested transistors.  
RF networks; assembly process; thermal parameters; measurements; lifetime Article
# Al-Fe-Ni Metallic Glasses via Mechanical Alloying and Its Consolidation
###### Abstract  
In this paper, the influence of mechanical milling on the microstructural evolution and magnetic properties of Al\({}_{82}\)Fe\({}_{14}\)Ni\({}_{4}\) alloys prepared by mechanical alloying is investigated. The elemental powder mixture was processed under argon gas at 250 rpm and 350 rpm using a planetary ball mill. The powder particles experienced severe deformation, fragmentation and mutually cold-welding during the collisions of the balls. The diffraction peaks of the Al, Fe and Ni phases gradually disappeared during the milling process, and a halo peak corresponding to the amorphous phase formed. The amorphization of powders milled at 250 rpm was slower than that of 350 rpm. These alloys achieved a fully amorphous structure after milling for 60 h. The amorphous powder alloy milled at 350 rpm exhibited higher thermal stability compared with that of an alloy milled at 250 rpm. The saturation magnetization and coercive of the milled Al\({}_{82}\)Fe\({}_{14}\)Ni\({}_{4}\) alloy powder were decreased following the formation of a para-magnetic amorphous phase. The highest compressive strength, about 710 MPa, was obtained for the Al\({}_{82}\)Fe\({}_{14}\)Ni\({}_{4}\) alloy sintered at 600 \({}^{\circ}\)C by SPS.  
Al-based amorphous alloy; mechanical alloying; magnetic properties; spark plasma sintering +
Footnote †: journal: Applied Physics Letters  
doi:10.3390/APPL122010561
## 2 Materials and Methods  
### Materials  
All chemicals, reagents and standards used: EtOH (96%), Folin-Ciocalteu reagent, sodium carbonate, hydrochloric acid (37%), formaldehyde, acetonitrile (\(\geq\)99.9%, HPLC grade), MeOH and water (\(\geq\)99%, HPLC grade), standards of individual phenolic compounds (caffeoylmale, chlorogenic, coumaric, ellagic, ferulic, gallic, \(p\)-hydroxybenzoic, protocatechuic, vanillic acid, kaempfer), naringin, quercetin, quercetin-3-glucose, and rutin trihydrate), acetone (p.a.), 2,6-dichlorophenolindophenol, ABTS (2,2\({}^{\prime}\)-azinobis(3-ethylbenzothazoline-6-sulfonic acid)), potassium persulfate, TPTZ (2,4,6-tri pyridyll-s-triazine), iron (III) chloride hexhydrate, and Trolox (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid) were purchased from Sigma-Aldrich, Merck (St. Louis, MO, USA).  
Stinging nettle leaves (_Urtica dioca L._) were obtained from plants grown during the 2022/2023 growing season in Zagreb (Croatia) at the Department of Vegetable Crops, University of Zagreb Faculty of Agriculture, Croatia. The experiment was set up as part of the project \"URTICA-BioFuture--Nutritional and functional value of nettle (_Urtica dioca L._) by application of modern hydroponic cultivation techniques\" (HRZZ IP-2019-04-3325). The plants were grown in a greenhouse in a hydroponic ebb and flow system and harvested before flowering, on 28 March 2023. The leaves were separated from the stems, immediately transported to the Laboratory for Food Packaging, University of Zagreb Faculty of Food Technology and Biotechnology (Zagreb, Croatia), and packaged. Four different packaging films were used: biaxially oriented polypropylene (25 \(\upmu\)m, BOPP; Petruzalek d.o.o., Zabok, Croatia), low-density polyethylene (45 \(\upmu\)m, LDPE; Helana-pak d.o.o. Zagreb, Croatia), polyamide/polyethylene (65 \(\upmu\)m PA/PE; SIMPEX, Salzburg, Austria), and polylactic acid (45 \(\upmu\)m, PLA; NATIVIA(r)NTSS40, Taghleef Industries, Tiszaiyairos, Hungary). The materials were chosen due to their different barrier properties, which can influence the exchange of gases between the inner space and surrounding atmosphere in a packed product. The materials were purchased in rolls, and hand-cut to dimensions of 33 \(\times\) 20 cm. The edges were sealed with a manual sealing machine (AUDION, Virovitica, Croatia).
# Study of the Ionospheric Scintillation Radio Propagation Characteristics with Cosmic Observations
###### Abstract  
The ionosphere has important influences on trans-ionosphere radio propagation. When signals pass through ionospheric irregularities, their amplitude and phase are often attenuated and distorted. In this work, the statistical features of scintillation observed by the Global Navigation Satellite System (GNSS) and low earth orbit (LEO) satellites are investigated with Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) data in solar cycle 24. The amplitude scintillation propagation channel is fitted by the Nakagami-\(\mu\), \(\alpha\)-\(\mu\) and \(\kappa\)-\(\mu\) models. The performance is evaluated in terms of root mean square error (RMSE), kurtosis and information entropy. The results reveal that the \(\alpha\)-\(\mu\) model achieves the best performance in all considered scintillation intensities, while the Nakagami-\(m\) model achieves better performance under severe scintillation in the GNSS-LEO propagation channels.  
ionosphere scintillation; radio occultation; scintillation signal propagation Article  
Study of the Ionospheric Scintillation Radio Propagation Characteristics with Cosmic Observations. _Remote Sens._**2022**, _14_, 578. [[https://doi.org/10.3390/rs14030578](https://doi.org/10.3390/rs14030578)]([https://doi.org/10.3390/rs14030578](https://doi.org/10.3390/rs14030578))
## 3 Numerical Model and Method
### Transient Analysis  
For this numerical study of destabilization of a sand granular stack immersed by homogeneous fluidization, a three-dimensional model coupling the discrete element method (EDEM) to describe the mechanical behavior of the particle assembly and the CFD-ANSYS-FLUENT method to render account of the hydrodynamics of the interstitial fluid, has been developed. The granular samples used consisted of stacks of silicon grains in a rectangular parallelepipedic cell. After sedimentation of particles, stable stacks were obtained under gravity. The two granular samples were prepared, in EDEM, with an initial H\({}_{0}\) stacking height of 115 mm but with starting volume fractions of 0.62 and 0.52 (Figure 3b). The grains, in a uniform particle size distribution, had an average diameter of 1.6 mm. At the base of the cell, an injection speed U was imposed and kept constant during each simulation. The simulations were planned to study the situation where the stresses exerted by a liquid flowing through an immersed granular medium were sufficient, alone, to set in motion certain grains and fluidize a whole part of the stack. The authors have studied the application of the commercial DEM software (EDEM) coupled with the CFD-ANSYS Fluent software on the fluidized bed system, including the validation of this model. However, the results, compared to experimental measurements obtained from the literature, qualitatively capture the physics of fluidization [30]. In addition, it is shown that generally, with a finer grid, all iterative solution methods converge with good accuracy. The computation may require significantly more time [31]. In total, 7875 finer hexahedral cells constituted the computational domain in this work. Moreover, to capture the particles' behavior accurately, a smaller integration time step was also essential. Thus, the time step of \(10^{-4}\) s was chosen in this work, which is certainly supposed to be small enough to produce reasonably accurate results. The validation of this numerical model is also based on the visual observations of dynamic process during the experimental work.
# Simulation of Wind-Battery Microgrid Based on Short-Term Wind Power Forecasting
## 3 Simulation Study and Discussion of Results
### Description of Dataset  
The present work considers that there are three wind turbines and a 1050 Ah storage battery bank that are installed in a residential building. The manufacturer specifications of the wind turbines and battery storage are given in Table 1. The dataset consists of 190 days of meteorological samples that are collected at the location of the wind turbines in hourly intervals, with an intensity of wind speed between 0.6 km/h and 16 km/h during the recording period. The main variables under study include hourly averages of wind speed, wind speed standard deviation, wind direction, power generated, temperature, as well as timestamp of the data. The parameter values \(A=11,200\), \(B=-400\), \(C=7.8\) and \(D=1.46\) were used in Equation (3) as the best fit to the manufacturer's wind turbine power curve, which was divided into eight probability classes using the Fisher-Jenks method.  
Figure 2: Monte Carlo simulation workflow: The simulation is divided into three stages: (1) power output forecast using artificial neural network (ANN); (2) misclassification correction; and, (3) battery storage operations.