esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The demand for services that provide current sensing data (data) obtained at a specified location is expected to grow in the future. To realize such services with lower sensor installation and operation costs, we consider the use of a pull-type mobile crowdsensing with reverse auction (pull-type ReVauc) that determines the size of the incentive paid to mobile hosts that provide data. In a pull-type ReVauc, more cellular traffic between a server and mobile hosts can increase the service operation cost. In this paper, we propose a new communication method for the pull-type ReVauc that reduces cellular traffic between a server and mobile hosts by using device-to-device communication. Through simulations, we confirmed that the proposed method can reduce cellular traffic compared to the existing method for the pull-type ReVauc while selecting a successful bidder that can provide data at almost the same location for almost the same reward within almost the same amount of time as in the existing method.  
D2D communication; mobile crowdsensing; MCS; reverse auction; incentive +
Footnote †: This paper is an extended version of our paper published in the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, Austin, TX, USA, 23-27 March 2020.
## 3 Results and Discussion  
### Physicochemical Properties of Emulsions  
The stability properties of the emulsions are usually characterized in terms of droplet size, polydispersity index (PDI), and zeta potential (ZP) ([PERSON], 1977). Droplet size is one of the main factors influencing the physicochemical stability of emulsions (Kyoto, Japan). Smaller droplets correspond to the better stability of systems because of the reduction in interfacial energy. PDI describes the broadness of size distribution of droplets, with smaller PDI values indicating a smaller difference between droplet sizes (Kyoto, Japan). ZP is one of the other determinants of emulsion stability. A high positive or negative ZP value (>\(\pm\)30 mV) indicates a stable emulsion, while ZP values approaching zero may trigger degradation processes including coalescence, aggregation, or flocculation (Kyoto, Japan). The obtained results of the DLS examination of extract-doped and non-doped linoleic acid (LA) emulsions are presented in Table 1, Figures 1, S1 and S2.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline  & \multicolumn{3}{c}{**Mean Droplet Size by Intensity Z-Ave Number**} & \multicolumn{3}{c}{**Dominant Droplet Diameter by**} & \multicolumn{3}{c}{**PDI**} & \multicolumn{3}{c}{**ZF**} \\ \multicolumn{3}{c}{**(mm)**} & \multicolumn{3}{c}{**Number**} & \multicolumn{3}{c}{**(mm)**} & \multicolumn{3}{c}{**(mm)**} \\ \cline{3-10}
**Agent/Extract Added** & \multicolumn{3}{c}{**Without Gallic Acid**} & \multicolumn{3}{c}{**Without Gallic Acid**} & \multicolumn{3}{c}{**With Gallic Acid**} & \multicolumn{3}{c}{**Without Gallic Acid**} & \multicolumn{3}{c}{**With Gallic Acid**} & \multicolumn{3}{c}{**Without Gallic Acid**} \\  & \multicolumn{3}{c}{**Add**} & \multicolumn{3}{c}{**With Gallic Acid**} & \multicolumn{3}{c}{**Add**} & \multicolumn{3}{c}{**With Gallic Acid**} & \multicolumn{3}{c}{**With Gallic Acid**} & \multicolumn{3}{c}{**With Gallic Acid**} \\ \hline \multirow{11}{*}{Bird Chemistry} & No addition & \multirow{10}{*}{\(\begin{subarray}{c}\text{{Bird Chemistry}}\\ \text{{Bird Chemistry}}\end{subarray}\)} & 511.0 \(\pm\) 31.3 & 496.5 \(\pm\) 21.4 & 206.6 \(\pm\) 74.7 & 268.4 \(\pm\) 27.4 & 0.414 \(\pm\) 0.072 & 4.06 \(\pm\) 0.028 & \(-\)26.5 \(\pm\) 31.4 & \(-\)22.3 \(\pm\) 1.8 \\  & \multirow{10}{*}{\(\begin{subarray}{c}\text{{Bird Chemistry}}\end{subarray}\)} & 587.5 \(\pm\) 38.2 & 807.8 \(\pm\) 81.5 & 280.9 \(\pm\) 44.1 & 294.8 \(\pm\) 120.1 & 0.379 \(\pm\) 0.048 & \(-\)0.385 \(\pm\) 0.055 & \(-\)28.8 \(\pm\) 1.9 \({}^{\circ}\)\({}^{\circ}\)\({}^{\circ}\)\({}^{\circ}\)\  
Figure 1: Mean size (z-ave), polydispersity index (PDD), and zeta potential (ZP) changes as a function of storage time and gallic acid addition.
## 7 Discussion  
Nowadays, TDM-PON protection schemes are not expanded in an adequate way. Due to a low number of users, capital investments in TDM-PON networks must be minimized and simultaneously a network resiliency must be increased sufficiently. This situation is changed for advanced WDM-PON networks, where the traffic protection and restoration mechanisms must not only be considered, but also realized.  
Depending on a rate of development and projected range of advanced WDM-PON networks, network operators can take into account various traffic protection and restoration scenarios. An important and active part of this aim is a fact if a considered WDM-PON network only accommodates an original TMD-PON network architecture or fully exploits its own potential related to wavelength management features in selected network topologies, eventually with an interconnection with a metropolitan network. For this reason, presented simulation results of the performance analysis for WDM-PON protection schemes can be very useful for their practical applications.  
In the future, TDM-PON and WDM-PON protection schemes can be analyzed based on CAPEX and OPEX costs of particular network components. For this purpose, the PON Network Availability Evaluator will be modified, its graphical interface can be adjusted, and new network elements can be added and its extension with another protection schemes can be realized. Moreover, wavelength multiplexing techniques can be implemented into existing protection schemes. Except for standard values of specific parameters, a targeted utilization of data provided by real network operators together with implemented traffic protection schemes will be very interesting.
## 8 Conclusions and Future Work  
This work presented a novel integration of GISs and mobile agent technologies in e-commerce recommendation systems, demonstrating advancements in personalized shopping experiences. The proposed framework successfully combined real-time location awareness with autonomous mobile agents to create a dynamic and responsive recommendation system. Our case study with Carrefour and Monoprix shows how the Haversine formula-based computations, when paired with the temporal monitoring of consumer behavior, have resulted in suggestions that are contextually appropriate. The experimental findings confirm that the system can analyze complex spatial-temporal data with computing efficiency. The scoring algorithm offers insightful suggestions that improve the shopping experience by skillfully balancing user preferences and geographic proximity.  
The framework exhibits usefulness for both customers and retailers. Retailers may improve product placement and in-store layouts by integrating GISs and visualization technologies, which provide sophisticated data for location-based marketing, inventory management, and consumer interactions. Our results provide additional support for the significance of in-store product placement and its effect on consumer engagement, which have been emphasized in earlier research as a relevant factor. According to recent studies on the benefits of location-aware recommendations, the system offers customers a more tailored and contextually aware buying experience.  
In order to improve suggestion accuracy and context awareness, future research will look at integrating ontology and semantic web technologies. The integration of cutting-edge machine learning approaches to enhance pattern identification and prediction skills will be investigated in more detail. Future developments will also concentrate on improving the system's functionality in various geographic locations and e-commerce platforms, as well as creating increasingly sophisticated visualization tools for business information and consumer engagement.  
**Author Contributions:** Conceptualization, M.S.; methodology, M.S. and S.H.; validation, M.S., M.E. and S.H.; formal analysis, M.S.; writing--original draft preparation, M.S. and S.H.; writing--review and editing, M.E.; supervision, M.E. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Data Availability Statement:** Data are available upon request from the authors.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Contamination with Pharmaceuticals in Aquatic Environment: Focus on Analytical Methodologies
## 3 Determination of Pharmaceuticals in Environmental Samples
### Sample Preparation Techniques
#### 3.1.2 QuEChERS  
An alternative, less explored strategy for determining pharmaceuticals in environmental samples is the use of extraction methods based on QuEChERS (quick, easy, cheap, effective, rugged, and safe) (Table 1). This method is commonly used as a preliminary preparation of solid samples in the multi-residue analysis of polar and non-polar pesticides. The QuEChERS method is based on solid-liquid extraction with an organic solvent, followed by liquid-liquid partitioning using a suitable salt mixture. Dispersive solid-phase extraction (d-SPE) is usually used for the clean-up [42]. Acetonitrile is used as the extraction solvent, and interfering compounds contained in the extract are removed in the clean-up step [65].  
Due to its high versatility, the QuEChERS method has recently been successfully used to extract 19 pharmaceuticals and personal care products in surface and wastewater using acetate buffer and achieved LODs of 0.001-0.167 ng/mL [66]. [PERSON] et al. performed wastewater analysis based on the QuEChERS extraction procedure for more than 100 contaminants, including compounds with various physicochemical properties such as pharmaceuticals, antibiotics, and pesticides [42].
# Design and Performance Analysis of BDS-3 Integrity Concept
## 4 Risk Prevention and Control
### Ground Segment Measures  
Although the risk probability of the ground segment is very low, once it occurs, it easily causes serious consequences and becomes the \"gray rhino\" in system operation and service. For example, the Galileo offline event of 2019 mentioned above was precisely caused by the \"ground technology failure\" according to the EUROPEAN GNSS AGENCY (GAS). More specifically, it is confirmed to be related to the abnormal behavior of a ground atomic clock in the time determination function of the system [30; 31]. Therefore, it is very necessary to strengthen the prevention and control on the ground section.  
The composition of the BDS-3 ground segment and its processing flow can be simplified shown in Figure 4. In order to deal with possible integrity risks, BDS-3 has taken corresponding measures in each processing link:  
* To prevent the MS data anomaly (Event 6 in Figure 1), each MS is equipped with multiple monitoring receivers and atomic clocks to achieve redundancy.
* To prevent the navigation message upload anomaly (Event-9 in Figure 1), one measure is to implement a mutual backup strategy for the uplink station (ULS) antennas to prevent hardware failures; the other is to set up the monitoring function points before uploading and retrieving the navigation messages, respectively (see point a and point \(h\) in Figure 4).
* To prevent the satellite orbit calculation anomaly, the satellite clock calculation anomaly, and the ephemeris fitting anomaly (Events 1-3 in Figure 1), one measure is that the data processing center (DPC) has multiple channels for data calculation and generation, and they are independent of each other; the other is that the master control station (MCS) will check the correctness and validity of the products sent from the DPC.
* To prevent the orbit and time processing equipment anomaly (Event 4 in Figure 1), one measure is that the system is running both the main DPC and the backup DPC online at the same time; the other is that each DPC is equipped with multiple processing equipment to achieve redundancy.
* To prevent the data input anomaly (Event 5 in Figure 1), for all the aspects of data transmission involved in ground segment facilities, the monitoring function points are set up before data transmission and after data reception (see point \(b\) to point \(g\) in Figure 4).  
In addition, BDS-3 also introduces a third-party external monitoring system independent of its own ground segment, such as the international GNSS monitoring and assessment system (iGMAS), commercial receivers, and FPGA verification terminals to conduct continuous and real-time monitoring and evaluation of satellite SIS and messages. When an anomaly is found, these external systems will notify the MCS via a rapid alarm mechanism (for example, a private network).  
Figure 4: Information processing and fault monitoring of BDS-3 ground section. The yellow points a to h represent the fault monitoring function points in the ground segment.
## 2 Geometrical Details and Mathematical Models
### Low-Reynolds Number k-\(\varepsilon\) Model  
The low-Reynolds number \(k\)-\(\varepsilon\) models solve the whole flow field, including the viscous sublayer, instead of the standard \(k\)-\(\varepsilon\) model, which uses the wall functions to solve the flow in the boundary layer. The significant features of the low-Reynolds number \(k\)-\(\varepsilon\) models are that the molecular viscosity is introduced into the diffusion term in the \(k\) and \(\varepsilon\) equations, and the model constants are multiplied by damping functions to make sure the viscous stresses overwhelm turbulent stresses near the wall (in the viscous sublayer). The low-Reynolds number \(k\)-\(\varepsilon\) models are more appropriate for complex turbulence with transition flows [31].  
In this paper, six low-Reynolds number \(k\)-\(\varepsilon\) models proposed by [PERSON] (AB) [32], [PERSON] (LB) [33], [PERSON] and [PERSON] (LS) [34], [PERSON] and [PERSON] (YS) [35], [PERSON], [PERSON] (AKN) [36], and [PERSON], [PERSON] and [PERSON] (CHC) [28] are applied. Six low-Reynolds number \(k\)-\(\varepsilon\) models used in this paper are briefly introduced as follows:  
AB model: this model was proposed to predict the transition process and where the transition starts in the advanced design of modern aerodynamic aircraft. Moreover, it was  
Figure 1: The reduced-scale experimental configuration of [PERSON] et al. [27].  
validated by predicting a boundary layer transition flow with zero pressure gradient under the influence of free-flow turbulence.  
LB model: the special treatment of damping function \(f_{\mu}\) in the model makes the presence of the wall has a direct or indirect effect on \(f_{\mu}\). This model was validated throughout transition processes in fully developed turbulent pipe flow.  
LS model: this model fully re-optimized the damping function \(f_{\mu}\) and \(f_{2}\). Two extra source terms were introduced into the \(k\) and \(\varepsilon\) equations to account for the anisotropy in the region near the wall. This model could accurately predict the flow, heat, and mass transfer near a rotating disc.  
YS model: this model was designed to capture the gradients in the boundary layer. In this model, the Kolmogorov time scale is introduced in the turbulent time scale, avoiding the possible singularities of the \(\varepsilon\) equation at the walls.  
AKN model: this model replaced the friction velocity with the Kolmogorov velocity scale, reproducing the correct turbulent near-wall asymptotic relationship. The AKN model successfully predicts an attached boundary layer flow, separating and re-attaching flow downstream of a backward step.  
CHC model: this model could correctly predict near-wall flow restriction behavior while avoiding singular difficulties near the reattachment point. The performance of the CHC model was evaluated by testing fully developed turbulent flows and a recirculating flow in a pipe extension.  
More details of the six models will be presented in Section 2.3.
# Manufacturing Scheduling Using Colored Petri Nets and Reinforcement Learning
## 4 The Case Study  
### The Order-Picking Process  
A high-volume small parts spread buffer order-picking scheduling system is presented as a case study to illustrate the method. In this class of picker-to-goods order picking systems, item retrieval is decoupled from order assembly by a pick-to-buffer (P2B) technology [62]. In a P2B system items retrieved from pick locations are placed into a pick buffer. Items are deposited automatically into an order container placed on a conveyor when all items of an order have been picked. The physical layout of the order-picking system consists of four pick zones with a common conveyor. Robotic order-picking is considered. Each pick zone is assigned to a gantry robot. A pick zone consists of 30 product toes with each toe having 40 compartments. A compartment can accommodate 20 product units of one Stock Keeping Unit (SKU) type. The order-picking process is a sequential zone picking with batching. The order containers of each batch pass sequentially from one pick zone to the next one and all items to be picked in each zone are picked in one pass. Gantry robots can pick one product item at a time and deposit it in the nearest buffer. Customer orders are organized in five batches of 28 order containers each. Each order container contains a single customer's order and can have multiple line items. One SKU type is collected in every order-picking process. A line item is a single unit of product. The conveyor speed is constant. Randomized storage is assumed. Figure 1 shows the layout of a pick zone (after [63]).  
Figure 1: The layout of a pick zone.
# Study on Shielding Effect of the Pile Group in a Soft-Soil Foundation
###### Abstract  
Pile groups are frequently employed to reinforce soft soil foundations, while the piling process frequently disturbs the adjacent foundation. The shielding effect, which prevents the transmission of disturbances from pile installation, is indispensable for minimizing engineering disturbances and optimizing pile group construction techniques. However, current research focuses predominantly on characterizing the phenomenon of shielding, with a limited exploration of the mechanism. To eliminate the limitation, a numerical investigation of the shielding mechanism of pile groups in a pile-soil system is performed this study. Using the finite difference program FLAC\({}^{3\text{D}}\) and the cavity expansion theory, a three-dimensional numerical model of a pile-soil foundation was created. During the sequential penetration of piles, the response characteristics of the soil surrounding the piles were investigated. Displacement field was first investigated to determine the presence of shielding effects in the pile group and then highlighted the effective role of the existing piles in controlling deformation. Furthermore, through a combined analysis of the stress and strain fields during piling, the mechanism of the shielding effect induced by pile construction is proposed, which is attributed to the direct obstruction effect of piles and the \"soil arching effect\" created by the soil between piles. The former is reflected by the direct barrier of the existing pile to the soil displacement induced via the installation of the new piles. The latter is reflected by the obstruction of soil between two existing piles to the displacement of soil passing through the two existing piles. This research provides a comprehensive understanding of the mechanical behavior of the pile-soil system and has practical implications for controlling disturbances and optimizing construction techniques in piling engineering projects.  
pile group; soft soil foundation; shielding effect; cavity expansion; soil arching effect Article  
Study on Shielding Effect of the Pile Group in a Soft-Soil Foundation  
[PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Study on Shielding Effect of the Pile Group in a Soft-Soil Foundation. _Appl. Sci._**2023**, _13_, 9478. [[https://doi.org/10.3390/app13169478](https://doi.org/10.3390/app13169478)]([https://doi.org/10.3390/app13169478](https://doi.org/10.3390/app13169478))
###### Abstract  
The improved binding ability of graphene-nanoparticle composites to proteins or molecules can be utilized to develop new cell-based assays. In this study, we fabricated reduced graphene oxide-gold nanoparticles (rGO-AuNP) electrodeposited onto a transparent indium tin oxide (ITO) electrode and investigated the feasibility of the electrochemical impedance monitoring of cell growth. The electrodeposition of rGO-AuNP on the ITO was optically and electrochemically characterized in comparison to bare, rGO-, and AuNP-deposited electrodes. The cell growth on the rGO-AuNP/ITO electrode was analyzed via electrochemical impedance measurement together with the microscopic observation of HEK293 cells transfected with a green fluorescent protein expression vector. The results showed that rGO-AuNP was biocompatible and induced an increase in cell adherence to the electrode when compared to the bare, AuNP-, or rGO-deposited ITO electrode. At 54 h cultivation, the average and standard deviation of the saturated normalized impedance magnitude of the rGO-AuNP/ITO electrode was 3.44 \(\pm\) 0.16, while the value of the bare, AuNP-, and rGO-deposited ITO electrode was 2.48 \(\pm\) 0.15, 2.61 \(\pm\) 0.18, and 3.01 \(\pm\) 0.25, respectively. The higher saturated value of the cell impedance indicates that the impedimetric cell-based assay has a broader measurement range. Thus, the rGO-AuNP/ITO electrode can be utilized for label-free and real-time impedimetric cell-based assays with wider dynamic range.  
Keywords:cell-based assay; electrochemical impedance spectroscopy; electrodeposition; gold nanoparticle; graphene oxide +
Footnote †: journal: Applied Physics Letters
# Experimental Approaches in Delineating mTOR Signaling
## 4 Identification and Characterization of mTOR Signaling Pathway Components
### Biochemical Approaches to Identify mTOR Signaling Pathway Components
#### 4.1.6 Proctor Was Identified as an mTOR2 Associating Protein Using Rictor-IPs  
In an effort to identify novel mTOR2-binding proteins, endogenous Rictor IPs or TAP-tagged Rictor pulldowns were performed in either serum-starved or IGF-1-stimulated HEK293 cells [36]. A preimmune IgG antibody IP was included as a negative control. Protein bands present in Rictor-IPs but not IgG-IPs were excised for mass spectrometry analysis, which led to identification of Proctor-1 and Proctor-2. Further endogenous Proctor-1 or Flag-Proctor-1 IPs in HEK293 cells revealed that Proctor-1 associated with mTOR2 but not with mTOR1 complexes. Interestingly, Proctor-1 binding to mTOR or G\(\beta\)L was sensitive to certain detergents such as 1% Triton or 0.3% \(n\)-octylglucoside [36]. siRNA-mediated Proctor-1 knockdown did not affect mTOR2 complex association [36], but Proctor-1 might be necessary for mTOR2 to phosphorylate certain substrates such as SGK1 [37].
## 2 Materials and Methods  
### Data  
Previously, prediction models of agrifood demand were developed using structured data on agri-food production and sales and unstructured data from mass media, including broadcasting programs and social networks, that were collected and saved in the Mongo database [12]. In the present study, covering the years 2018 and 2019 in South Korea, daily retail prices of pork bellies and chicken from a livestock portal service (eKAPEpia) were used as structured data, while broadcast news and blogs mentioning disastrous livestock epidemics such as ASF and AI were used as unstructured data. Regarding ASF, 14 cases were reported in South Korea in 2019 and during the same period, 9586 ASF-related news articles and 16,111 ASF-related SNS posts were reported (Table 1 and Figure 1). For AI in chickens, there were 14 cases in 2018, with reports from 1666 AI-related news articles and 814 AI-related SNS posts. In 2019, no AI cases were reported, yet there were 352 AI-related news articles and 92 AI-related SNS posts (Table 1 and Figure 2).  
Figure 1: Trends in retail pork prices, African Swine Fever (ASF)-related news and SNS frequencies in 2019. The \(x\) axis indicates time and the \(y\) axis indicates retail pork price and frequency.