esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Data Set  
### In-Situ Data  
The data collected by the drifting buoys used cover the periods from 3 June to 20 August 2012 and from 28 July to 26 August 2013. The longitude range of buoys movement was from 120\({}^{\circ}\)E to 127\({}^{\circ}\)E, and the latitude range was from 29\({}^{\circ}\)N to 39\({}^{\circ}\)N. The trajectories of the drifting buoys illustrated in Figure 1 show they are mainly concentrated in the East China Sea, the west part of the southern Yellow Sea and the west coast off the Korean Peninsula. The position data measurement interval was approximately half an hour, and in approximately 77 days of the battery life cycle, 6505 profiles were obtained.  
Figure 1: The study area and its bathymetry. From light blue to dark blue, the water depth ranges from 10 to 200 m. The color lines show the tracks of three drifting buoys. Red dots represent the buoy locations of selected cases, which are distributed in the northern Yellow Sea, southern Yellow Sea, and East China Sea from north to south.  
The drifting buoy moves with the current on the sea surface or at a certain depth, which is one of the convenient and effective tools for ocean observation. It is affected by wind and currents. The principle of measuring current is to use the Lagrange method to describe the movement of sea water. The accuracy of measurement is mainly related to the ratio of the area of drifting buoy above and below the sea surface. Figure 2 is a diagram showing a working drifting buoy. The drifting buoy was similar to [PERSON]'s drogue drifter [35]. The area of the buoy on the sea surface is 0.031 m\({}^{2}\), and the area of the buoy under the sea surface is (0.031 + 0.7) m\({}^{2}\). The ratio of the upper and lower areas was as low as 0.04. The center point of the sail below the sea surface was 3 m underwater. The structure of the drifting buoy shows that the movements of the drifting buoy are mainly controlled by SSC.
# Recommendation Algorithm for Multi-Task Learning with Directed Graph Convolutional Networks
###### Abstract
The main work contributions are as follows:  
1. In order to solve the problem that the recurrent neural network (RNN) only models the single transfer relationship of two adjacent items in the recommendation field and ignores other item information in the session, the MTL-DGCNR model adopts a directed graph convolutional network. 2. In order to effectively enhance the changing ability of features and obtain a simpler feature distribution than GCN, the MTL-DGCNR model adopts the learning embedding of the directed graph, and fully considers the embedding of the first-order proximity nodes and the embedding of the second-order proximity node. 3. In order to effectively solve the cold start problem in recommendation and the one-to-many, many-to-one, or many-to-many relationship between users and commodities, the MTL-DGCNR model adopts a multi-task learning method, and uses knowledge graph embedding as auxiliary tasks, and cooperates the DGCNR model to complete the recommendation task. 4. Experiments verify that the goal effect achieved by integrating two learning tasks in one MTL paradigm is better than the effect of two tasks achieving their respective tasks separately. Utilizing user micro-behavior embedding helps to better capture user preferences at a fine-grained level. Compared with other deep learning models, MTL-DGCNR has a higher interpretability and accuracy in the field of e-commerce recommendation. A more effective commodity recommendation is realized to meet the personalized needs of users.
## 2 Materials and Methods  
### Study Area  
The MLRYR region (23\({}^{\circ}\)33\({}^{\prime}\)\(\sim\)35\({}^{\circ}\)08\({}^{\prime}\)N, 108\({}^{\circ}\)21\({}^{\prime}\)\(\sim\)123\({}^{\circ}\)10\({}^{\prime}\)E), including Hubei, Hunan, Anhui, Jiangxi, Jiangsu, Zhejiang, and Fujian provinces, has a subtropical monsoon climate with a warm temperature and abundant precipitation, and is a crucial grain, oil, and cotton production base in China [24] (Figure 1b,c). The land-use types in this region are croplands, forests, grasslands, urban/built-up lands, water bodies, permanent wetlands, and barren (Figure 1a). The watershed area is 80 \(\times\) 10\({}^{4}\) km\({}^{2}\), and the landform types are mainly plains, hills, and mountains [25]. The elevation ranges from \(-\)142-3090 m (Figure 1c). The main crops are winter wheat and rice (single-cropped and double-cropped rice). In addition, the MLRYR has the most abundant water resources in China, with the highest density of river networks and the most concentrated distribution of freshwater lakes, including Poyang lake, Dongting lake, Taihu lake, Chao lake, etc. The annual mean temperature and precipitation are 17.9-29.9 \({}^{\circ}\)C and 793.8-2390.1 mm, respectively (Figure 1d,e). Moreover, the MLRYR is densely populated, especially in Jiangsu and Zhejiang; however, when crops are mature (August-October each year), the East Asian Summer Monsoon retreats southward. The monsoon rain band anomaly leads to drought and flood disasters in this region. Combined with the increasing demand for water resources, drought has become one of the critical disasters in this region [26].  
From late July to mid-November in 2019, the average precipitation among Hubei, Hunan, Jiangxi, Jiangsu, Anhui, Zhejiang, and Fujian provinces was 246.2 mm, 40% less than that in the same period of the previous year (417.8 mm) and the lowest since 1961. The average air temperature was 1.4 \({}^{\circ}\)C higher than that of the same period last year, the highest in history. Prolonged periods of low rainfall and high temperature have resulted in a continuous drought in summer and autumn in this region, especially from September to early October and early November. [PERSON] et al. [27] also revealed that the warm central equatorial Pacific Sea surface temperature and anthropogenic warming were possibly responsible for this drought event. This drought greatly impacted agricultural production in the seven provinces mentioned above, with some crops in the arid areas being affected and water levels in rivers, lakes, and reservoirs decreasing significantly [26; 28].
## 3 Numerical Algorithms and Computational Methodologies
### Core-Fluid Simulations
#### 3.4.2 Discretisation Schemes for Core Region  
Since the model problem is transient in nature, time discretisation is crucial and must be implemented in a way that enhances numerical stability and convergence. The time derivatives are, therefore, approximated via an implicit Euler scheme. A linear scheme with Gaussian integration is applied on space derivative terms, i.e., the gradient terms. A Gaussian first order upwind scheme is used for the discretisation of the convective terms. The Laplacian terms are discretised via bounded, second-order Gaussian linear corrected schemes.  
The systems of linear equations generated by the above space-time discretisations are solved via efficient and robust linear algebraic techniques. Specifically, a Bi-Conjugate Gradient Stabilised (BiCGStab) solver is used for the discretised velocity, temperature, and polymer-stress constitutive equations. For the discretised velocity and polymer-stress constitutive equations, the BiCGStab solver is applied in conjunction with the Incomplete LU with zero fill-in (ILUO) pre-conditioners. For the discretised temperature equation, the BiCGStab solver is used in conjunction with the Diagonal Incomplete LU (DILU) pre-conditioners. The pressure equation is solved with a Conjugate Gradient (CG) method using a Cholesky pre-conditioner.
# Recent Trends and Progress in Corrosion Inhibitors and Electrochemical Evaluation
## 3 Types of Corrosion Inhibitors
### Composite-Based Corrosion Inhibitors
#### 3.4.5 Micro-Arc Oxidation Coatings  
Micro-arc oxidation (MAO), also known as plasma electrolytic oxidation (PEO), is a surface treatment process that is used to enhance the corrosion resistance and wear resistance of metals, particularly lightweight metals, like aluminum and magnesium. It involves the formation of a ceramic oxide layer on the metal's surface through controlled electrochemical reactions that occur during a spark discharge process. It is a new, environmentally friendly coating process that can create ceramic coatings on metals, including aluminum, magnesium, titanium, and their alloys [91]. On the surface of the metal, a thick and dense oxide layer develops during the micro-arc oxidation process. The metal is well shielded from corrosive substances including moisture, salts, acids, and alkalis by this oxide layer, which serves as a physical barrier between the metal and its surroundings [92]. A homogeneous and regulated coating thickness is made possible by micro-arc oxidation throughout the entire metal surface. Any locations with insufficient coverage could become susceptible to corrosion and, hence, uniformity is essential for providing constant corrosion protection [93]. Micro- and nano-sized holes are frequently present in the oxide layer formed through micro-arc oxidation. Corrosion inhibitors or sealants can be efficiently trapped and retained in these pores, increasing the material's resistance to corrosion. Additionally, the intricate porous structure might slow down corrosive substances' passage through the covering, which will lessen corrosion [94]. The corrosion and wear resistance of the micro-arc oxidation coating on a novel glass microsphere-reinforced magnesium alloy composite was studied by [PERSON] and colleagues. Figure 9 illustrates the MAO coating process [95]. To protect the AZ91D magnesium alloy against corrosion, waterborne polyurethane (PU) coating's ability to adhere to and resist corrosion on an aluminum alloy surface was studied by [PERSON] et al. [96]. This study showed that MAO treatment and silane coupling agent modification of the MAO layer considerably improved the adhesion and corrosion resistance of MAO-PU composite coatings on 7050 aluminum alloy.  
MAO coatings have a number of benefits, but there are some drawbacks that must be taken into account. The MAO process can make it difficult to achieve uniform coating thickness over intricate geometries. Varying coating thickness might result in inconsistent performance and aesthetically undesirable outcomes [97]. In comparison to the main material, MAO coatings may be relatively fragile. Reduced impact resistance and susceptibility to cracking or chipping under mechanical stress can both be caused by this brittleness [98].
# Performance Characteristics of an Orthopter-Type Vertical Axis Wind Turbine in Shear Flows
## 2 Experimental Approach  
### Wind Turbine Model  
In this paper, we employed a right-handed Cartesian coordinate system \((x_{1},x_{2},x_{3})=(x,y,z)\), in which the \(z\)-direction was aligned in the vertical direction. The wind turbine used in this study was an O-VAWT with three flat-plate blades as shown in Figure 2. The blade had a height of \(h=4.00\times 10^{-1}\) m, chord length of \(c=4.00\times 10^{-1}\) m and thickness of \(4.0\times 10^{-3}\) m. Each of the blades not only revolved around the main shaft but also rotated around its own blade axis, which was rotationally supported by a pair of connecting arms. The distance between the main shaft and one of the blade axes was \(R=2.55\times 10^{-1}\) m. In addition, each of the blade axes was connected with the main shaft by a chain via sprockets. Since the ratio of the number of teeth on the sprocket of the main shaft to that of the blade axis was 1:2, each of the blades rotated around the own blade axis a half time while the rotor revolved around the main shaft one time. When seen from the top, the rotor revolved around the main shaft counterclockwise and each of the blades rotated around the own blade axis clockwise as shown in Figure 2c. Therefore, by using the angular velocity of the rotor revolution (\(\omega\)), the angular  
Figure 1: Illustration of the approaching wind flow to the wind turbine near upwind corners of a building. (**a**) Bird view; (**b**) enlarged top view.  
velocity of the blade rotation is expressed as \(-\omega/2\). Furthermore, as shown in Figure 2c, according to the azimuthal angle of a blade (\(\varphi\)), we call the range of \(90^{\circ}<\varphi<270^{\circ}\) the \"upwind region\" of the rotor, \(0^{\circ}<\varphi<90^{\circ}\) and \(270^{\circ}<\varphi<360^{\circ}\) the \"downwind region\" of the rotor, \(180^{\circ}<\varphi<360^{\circ}\) the \"advancing side of the rotor\" and \(0^{\circ}<\varphi<180^{\circ}\) the \"retreating side\" of the rotor. The O-VAWT is designed so that the drag force on a blade is large on the advancing side of the rotor while being small on the retreating side of the rotor.  
Figure 2d shows a projected swept area of the rotor (\(A\)), which is defined as:  
\[A=(2R+0.5\;c)\;h. \tag{1}\]  
We define the diameter of the rotor as:  
\[D=2R. \tag{2}\]  
Figure 2: Orthopter-type vertical-axis wind turbine (O-VAWT). (**a**) A photograph of O-VAWT with three flat blades, main shaft, arm, the chains and sprockets; (**b**) an isometric view of O-VAWT with three flat blades; (**c**) motion of rotor and blades viewed from the top; (**d**) a projected swept area of the rotor viewed from the upwind side.  
The O-VAWT had a rotor's diameter of \(D=5.1\times 10^{-1}\) m and a projected rotor's swept area of \(A=2.84\times 10^{-1}\) m\({}^{2}\) can be considered as a micro wind turbine. A small scale wind turbine that has a diameter up to 1.25 m and the swept area up to 1.2 m\({}^{2}\) is categorized as a micro wind turbine [4].
## 3 Face Recognition Data and Methods
### Face Recognition Approach--FaceNet  
For face recognition, we employed the set of features supplied by the FaceNet algorithm [9]. FaceNet is a deep convolutional network designed by Google, trained to solve face verification, recognition and clustering problems with efficiency at scale. It is highly accurate and robust to occlusion, blur, illumination, and steering. It directly maps face images to a compact Euclidean space, where distances directly correspond to a measure of face similarity. Once this space has been produced, tasks such as face recognition can be easily implemented using standard techniques. It achieved accuracy of 99.63% on the Labeled Faces in the Wild (LFW) data set, and 95.12% on the YouTube Faces Database.  
To create the FaceNet features, we applied the python Keras implementation (Available at: [[https://github.com/nyoki-mtl/keras-facenet](https://github.com/nyoki-mtl/keras-facenet)]([https://github.com/nyoki-mtl/keras-facenet](https://github.com/nyoki-mtl/keras-facenet)), (accessed 30 October 2022)). We employed the pretrained Keras model (trained using the Microsoft-Celeb-1M data set, which as of 6 June 2019 is no longer available). For this, the images needed to be resized to 160 \(\times\) 160 pixels and globally rescaled (compute the mean and SD across all intensities from each color channel and, for each channel, subtract the mean intensity and divide by the SD intensity). The algorithm produced 128 numerical features per subject.
## 4 Experiments and Results
### Ablation Study
#### 4.5.2 Effectiveness of the GFA Module  
We have also incorporated a global feature attention (GFA) module into our proposed method to enhance the performance of the results. As presented in Table 3, combined with the GFA module, the mIoU has increased by 1.28%. This demonstrates the effectiveness  
Figure 8: Comparison of ablation results on the NEU-seg dataset. The yellow boxed areas indicate the consistency between our method’s segmentation results and the ground truth. (**a**) Original images, (**b**) ground truth, (**c**) UNet, (**d**) UNet+RRD, (**e**) UNet+GFA, (**f**) UNet+RRD+GFA, and (**g**) AFFNet (ours).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Method** & **mIoU (\%)** & **Gain** \\ \hline UNet & 77.40 & - \\ UNet+RRD & 79.93 & +2.53 \\ UNet+GFA & 78.68 & +1.28 \\ UNet+RRD+GFA & 80.54 & +3.14 \\ Ours (+OHEM) & **80.94** & +3.54 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The effects of different modules, including RRD, GFA, and OHEM strategy on network performance.  
of GFA in enhancing the ability of the network to extract meaningful features for defect detection, resulting in improved accuracy and efficiency of industrial defect detection.
# Spatial Data Reconstruction via ADMM and Spatial Spline Regression +
## 7 Conclusions  
In this paper, we study the problem of inferring the fine-grained spatial distribution of certain density data in a region based on the aggregate observations recorded for each of its subregions, which is extremely challenging and seldom visited before, and analyze the challenges of it. We propose the Constrained Spatial Smoothing (CSS) approach that exploits both the intrinsic smooth property of underlying factors and the additional features from external social or domestic statics. We further propose a training algorithm which combines the Spatial Spline Regression (SSR) technique and ADMM technique to learn our model parameters efficiently.  
To evaluate our algorithm and compare it with various other approaches, we run extensive evaluations based on the Milan Call Detail Records dataset provided by Telecom Italia Mobile. The simulation results on the dataset show that our algorithm significantly outperforms other baseline approaches by a great percentage. (Note that cross validation and statistical testing are techniques that are usually applied in experiments. However, both techniques require sampling effectively from the sparse spatial data while keeping the intrinsic spatial structure, which is difficult in our problem.) This shows that jointly modeling the underlying spatial continuity and the local features that characterize the heterogeneity of different locations can effectively improve the performance of spatial recovery.  
Although we use the data on cell phone activities to illustrate our methodology, our algorithm is not limited to solving the problem of inferring the distribution of cell phone activities, but is also applicable to a variety of problems where estimating an implicit or explicit smooth surface is required, such as inferring the spatial distribution of population densities based on the aggregate population observed at sparsely scattered polling stations, reconstructing a fine-grained geographical distribution of users for an Internet media provider or retailer only from aggregated user counts observed at certain datacenters or points of presence (PoPs), and so on.  
Conceptualization, B.L., B.M., L.K. and D.N.; Data curation, B.L. and B.M.; Formal analysis, B.L., B.M., L.K. and D.N.; Investigation, B.L., B.M., L.K. and D.N.; Methodology, B.L., B.M., L.K. and D.N.; Project administration, B.L., B.M., L.K. and D.N.; Software, B.L. and B.M.; Supervision, B.L., B.M., L.K. and D.N.; Validation, B.L., B.M., L.K. and D.N.; Visualization, B.L., B.M. and L.K.; Writing--original draft, B.L., B.M., L.K. and D.N.; Writing--review and editing, B.L., B.M. and D.N.  
This research received no external funding.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} CSS & Constrained Spatial Smoothing \\ SSR & Spatial Spline Regression \\ SMS & Short Message Service \\ ADMM & Alternating Direction Method of Multipliers \\ QP & Quadratic Programming \\ CDR & Call Detail Records \\ PoPs & Presence of Points \\ CDF & Cumulative Distribution Function \\ \end{tabular}
## 1 Introduction  
Substituted 1,4-dihydroxyproyridines (1,4-DHPs) are analogs of nicotine adenine dinucleotide dehydrogenase (NADH) coenzymes and are an important class of drugs [1]. In recent years, attention has been paid to the synthesis of 1, 4-dihydropyidines due to their significant biological activities [2]. They are well known as calcium channel modulators and have emerged as an important class of drugs for the treatment of cardiovascular diseases [3]. In particular, dihydropyridine drugs, such as nifedipine, nicardipine, amlodipine are effective cardiovascular agents for the treatment of hypertension [4]. Due to their ability to block the l-type calcium channel, DHPs, such as felodipines have been characterized as potentiators of several mutant cystic fibrosis transmembrane conductance regulator (CFTR) channels [5]. In addition, dihydropyridine unit has been used as a hydride source for reductive amination [6].  
**Examples of 1,4-Dihydropyridine drugs.**  
Heterocyclic ring system, such as acridinedine is generally considered to be among the most prevalent ring systems in medicinal chemistry [7]. They are known to be potent frameshift mutagens in virus and bacteria [8]. Acridinedines have also been reported as antimalarial agents [9].  
Organic compounds bearing trifluoromethyl group have attracted considerable attention due to their role in organic, medicinal, and heterocyclic synthesis. In particular, the incorporation of fluorine atom has been used by medicinal chemists to tailor the physical and metabolic profiles of drug candidates [10]. For instance, addition of fluorine in the place of hydrogen has been known to enhance binding interactions, improve metabolic stability, increase CNS penetration, and eliminates ancillary ion channel activity by attenuating amine basicity [11]. The electronic effect of fluorine via induction is enormous and this change could have a major effect on the binding potential of the small molecules.  
Polycyclic compounds, particularly heterocycles are important in medicinal chemistry because their rigid structures permit selective interaction with proteins and other receptors. The literature has few reports of dihydropyridines containing the highly electronegative and lipophilic trifluoromethyl group. Thus, the synthesis of trifluoromethylated heterocyclic compounds has drawn much attention in recent years. In continuation of our efforts towards the synthesis of fluorinated heterocycles of biological importance, we turned our attention to the synthesis of fluorinated hexahydroquinoline derivatives in trifluoroethanol (Scheme 1), as potential calcium channel modulators. We chose 2,2,2-trifluoroethanol because the solvent appears to have low nucleophilicity, strong hydrogen bond donating ability and high polarity [12]. It is also cheap and relatively nontoxic.  
**Scheme 1.** Synthesis of fluorinated hexahydroquinoline from 5-trifluoromethyli-1,3-cyclohexanedione, aldehydes, \(\beta\)- ketoesters and ammonium acetate.