esa-sceva/satcom-chunk-collection huggingface dataset:
# Additive Manufacturing for Sensors: Piezoresistive Strain Gauge with Temperature Compensation
###### Abstract  
Additive manufacturing technologies allow the fabrication of smart objects, which are made up of a dielectric part and an embedded sensor able to give real-time feedback to the final user. This research presents the characterization of a low-cost 3D-printed strain sensor, fabricated using material extrusion (MeX) technology by using a conductive material composed of a polylactic acid (PLA)-based matrix doped with carbon black and carbon nanotubes (CNT), thus making the plastic conductive. A suitable measurement set-up was developed to perform automatic characterization tests using a high repeatability industrial robot to define either displacement or force profiles. The correlation between the applied stimulus and the variation of the electrical resistance of the 3D-printed sensor was evaluated, and an approach was developed to compensate for the effect of temperature. Results show that temperature and hysteresis affect repeatability; nevertheless, the sensor accurately detects impulse forces ranging from 10 g to 50 g. The sensor showed high linearity and exhibited a sensitivity of 0.077 \(\Omega\) g\({}^{-1}\) and 12.54 \(\Omega\) mm\({}^{-1}\) in the force and displacement range of 114 g and 0.7 mm, respectively, making them promising due to their low cost, ease of fabrication, and possible integration into more complex devices in a single-step fabrication cycle.  
additive manufacturing; fused filament fabrication; 3D printing; conductive materials; carbon nanotubes; sensors characterization; piezoresistive strain sensors; force sensors; robotic arm
# A Smart Parking Solution Architecture Based on LoRaWAN and Kubernetes
## 4 Proposed Solution
### Backend Infrastructure  
This part of the solution is in charge of processing the information collected by the sensors. The backend was mainly built over a cluster of Kubernetes. Kubernetes is an open-source system that allows to automate the deployment of applications based on containers. In this solution, Kubernetes have been used to deploy database server, message queue server, MQTT server and the REST API. The proposed architecture is shown in Figure 4.  
Figure 4: Smart parking solution backend-architecture.  
The main point of entry is the MQTT Server which is based on Mosquito (an open-source MQTT broker). The information forwarded by the Network Server is collected through this server via MQTT protocol. MQTT protocol delivers a lightweight method to handle messaging over a publisher/subscriber model [27]. The information received by Mosquito comes in Javascript Object Notation (JSON) format as shown in Figures 5 and 6. Mosquito server forwards unencrypted payloads to a software component called \"Raw Data Bridge\".  
Figure 5: JSON Payload sent by sensor node and forwarded by Mosquito.  
Figure 6: JSON Payload generated by Mosquito MQTT.  
The Raw Data Bridge takes the payload received from Mosquito and delivers it to an inbound message queue with a specific topic. The Raw Data Bridge acts as a producer that publishes messages to an Exchange. This exchange delivers messages to a queue based on the type of exchange (direct, topic and fanout). Based on that behavior, RabbitMQ Server (an open source message broker that natively supports AMQP protocol and others like MQTT, WebSocket, etc.) delivers messages to other exchanges that will be later consumed by the Parser and Logic components respectively. These components were built in C#. The Parser component, is a software program that transforms payloads received from the sensor to a lighter JSON format that will be later stored in a database repository. On the other hand, payloads processed by the Parser are then published to a new Exchange in the RabbitMQ Server, which will be later consumed in the Logic component. The Logic component is in charge of storing parsed information into a NoSQL repository (MongoDB was used in this implementation). MongoDB stores enriched information generated by the sensors. Finally, all the information stored in the database is exposed through an API REST running over IIS with ASP.NET Core.  
The following versions were used in the proposed architecture RabbitMQ (Version 3.7.7) developed and maintained by VMWare located in Palo Alto, CA, United States, MongoDB (Version 4) developed and maintained by MongoDB Inc, located in New York City, NY, United States and Mosquito (Version 1.4.12) supported and maintained by Eclipse Foundation, located in Ottawa, Canada, for every particular component of the backend infrastructure detailed in Figure 4.
## 3 Results and Discussion
### Effects of Concentration of (CNCs-PEG/NaOH) on Hep G2 Cells  
Figure 16 shows the percentage of cell survival on Hep G2 cells at a seeding density of 20,000 cells/well after incubation with (CNCs-PEG/NaOH)/at different concentrations (12.5 \(\upmu\)g/mL, 25 \(\upmu\)g/mL, 50 \(\upmu\)g/mL and 100 \(\upmu\)g/mL) [67] for 24 h at 37 \({}^{\circ}\)C in a humidified atmosphere consisting of 5% carbon dioxide and 95% air. In addition, if we look at the (CNCs-PEG/NaOH) sample, the survival of Hep G2 cells is decreasing and it is directly proportional to the increase in the concentration of (CNCs-PEG/NaOH) in the range of 12.5 \(\upmu\)g/mL-100 \(\upmu\)g/mL. Moreover, the survival of Hep G2 cells on the sample of (CNCs-PEG/NaOH) at a concentration of 100 \(\upmu\)g/mL showed almost more than 50% cell survival (\(88\pm 3\)) less than the control cells as shown in Figure 16. Additionally, the findings indicated that the (CNCs-PEG/NaOH) displayed good biocompatibility and did not exhibit any cytotoxic effects on Hep G2 cells, indicating its suitability as an MR imaging contrast agent.  
Figure 16: Survival of Hep G2 Cells on the test of (CNCs-PEG/NaOH) at a concentration range of 12.5 \(\upmu\)g/mL–100 \(\upmu\)g/mL.  
Figure 15: (**a**) T\({}_{1}\)-weighted and (**b**) T\({}_{2}\)-weighted MR images of CNCs-PEG/NaOH composite with water background (W) as control.
## 4 Discussion
Salt stress is known to cause oxidative damage by stimulating the production of ROS that, in turn, damages proteins, lipids, DNA, and carbohydrates. To capture and detoxify the ROS, the biosynthesis of antioxidants (phenols and flavonoids) is stimulated. In our study, VOCs produced by _S. indica_ significantly increased TPC, TFC, and antioxidant activity in all salt treatments, suggesting that these extra phenolics, including flavonoids and other antioxidants, help the plants to survive under saline conditions [69]. When treated with _S. indica_, _Bacopa monmiera_ plants showed a higher level of antioxidant activity comparing to the control plants [70]. The fungus _S. indica_ was also found to increase the production of osmoprotectants (proline and glycein) in salt stressed barely plants [15]. The level of phenolic compounds may be directly related to their antioxidant capacity because of their ability to scavene free radicals [37; 71]. Volatiles released by microbes have been shown to be important drivers of plant growth [13; 22; 61]. The mechanisms of this growth promotion are complex. The single application 6-pentyl-2H-pyran-2-one (6-PP), a major VOC of _Trichoderma_, affected root morphogenesis [13]. However, VOCs can also work in a mixture. Methyl benzoate was found to be the dominant molecule produced by _Serendipita_, but its single application did not affect plant growth [22]. Some authors suggest that it is actually CO2 emitted by fungi that is responsible for the increased plant growth; however, this hypothesis was rejected by CO2 capture [22; 71]. The profile of fungal volatiles changes as the fungi grow and mature. It has been suggested that VOCs emitted by microorganisms mimic plant metabolites, providing signals to plants that ultimately generate growth changes [61]. There are not a lot of studies on the effect of _Serendipita_ metabolites. For this reason, strong evidence for a correlation between growth promotion and the production of specific compounds is lacking, suggesting complex molecular interactions are required. Future analytical research on the composition of fungal volatiles at different stages, and molecular research on the specific genes and pathways, may shed light on how fungi can also remotely affect plant growth and their defense mechanisms against stress.
## 5 A Mathematical Model of a Platform Motion
#### Eigenfrequencies of the Drive Shaft  
Other dynamic analyses were aimed at the identification of a basic dynamic characteristic of the drive shaft, namely at finding its angular eigenfrequencies \(\Omega_{i}\), or eigenfrequencies \(f_{i}\). The observed eigenfrequency is compared with the angular excitation frequency \(\omega\) during operation. Their similar values could lead to undesirable excessive vibrations of the mechanism.  
The equation of motion for free oscillation of the drive shaft is:  
\[I_{S}\cdot\ddot{\varphi}+k_{S}\cdot\varphi=0, \tag{57}\]  
where \(I_{S}\) (\(I_{S}\) = 0.462 kg\(\cdot\)m\({}^{2}\)) is the moment of inertia of the shaft and \(k_{S}\) (\(k_{S}\) = 360,430 N\(\cdot\)m\(\cdot\)rad\({}^{-1}\)) is its torsion stiffness. This form of the equation of motion (Equation (57)) and basic characteristics of the shaft are valid when we consider the drive shaft as a flexible body defined by its torsion stiffness. When we rewrite Equation (57) to the form:  
\[\ddot{\varphi}+\frac{k_{S}}{I_{S}}\cdot\varphi=0, \tag{58}\]  
and substitute the known parameters, we obtain the eigenfrequency \(f_{S}\) = 104.565 Hz.  
In reality, the drive shaft is a flexible body represented as a continuum mass, in which eigenmodes can be investigated by means of, e.g., the finite element method (FEM). Then, the equation of motion for free oscillation will be in the form:  
\[\mathbf{I}_{S}\cdot\ddot{\mathbf{\varphi}}+\mathbf{k}_{S}\cdot\mathbf{\varphi}=\mathbf{0}, \tag{59}\]  
where \(\mathbf{I}_{S}\) is the metric of the moments of inertia, \(\mathbf{k}_{S}\) is the stiffness matrix, \(\ddot{\mathbf{\varphi}}\) is the vector of angular accelerations and \(\mathbf{\varphi}\) is the vector of angular deviations. After performing the modal analysis in the FEM software, we found out, that the first six eigenvalues are as follows: \(f_{S1}\) = 89.298 Hz, \(f_{S2}\) = 96.923 Hz, \(f_{S3}\) = 125.863 Hz, \(f_{S4}\) = 160.963 Hz, \(f_{S5}\) = 171.385 Hz and \(f_{S6}\) = 223.951 Hz.  
When we compare results of eigenfrequencies for the flexible body represented just by its torsion stiffness (Equation (58)) and for the flexible body modelled as a continuum (Equation (59)), we can see that results are slightly different. It is caused because the continuum better represents the real body of the analysed drive shaft. The angular excitation frequency of the drive shaft is \(\omega\) = 2.932 rad\(\cdot\)s\({}^{-1}\), or \(f\) = 0.466 Hz. This excitation frequency is much lower than the eigenfrequencies calculated by means of Equation (58) as well as Equation (59). We can conclude that the drive shaft will not reach to the resonance due to the driving in the operation mode.  
Figure 19: Waveform of acceleration of the platform mechanism for time interval of 0.0–0.5 s.
## 6 Simulation Results
Therefore, traffic control in cities does not achieve a general effect. A comparison of the proposed method has been presented in Table 4 in one intersection. The advantages and disadvantages of the proposed model compared with other existing works are summarized as below:  
Advantages:  
* Model predictive control is updated every minute, and this update applies controls based on what will happen in the future to the system. * They can be used for delayed systems and multidimensional systems. * Can be added to that constraint. For example: control the traffic load behind the crossroads for one h a day. * Being bound by model predictive control. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Existing Work** & **Approach** & **Benefit** & **Applied Model** \\ \hline [PERSON] et al. [35] & Single intersection & Minimal waiting time and length of queue & Fuzzy Logic \\ \hline [PERSON] et al. [53] & Single intersection & Optimal traffic and reducing queue length & Model Predictive Control \\ \hline [PERSON] et al. [54] & 3 intersection & Significant reduction in delay or various traffic conditions. & Multi-Agent Deep Reinforcement Learning \\ \hline [PERSON] et al. [55] & 9 intersection & Maximize the throughput and efficiently distribute the signals & Deep Q-Network \\ \hline [PERSON] et al. [56] & 4 intersection & Adaptive multi intersection signal control & Cooperative deep Q-network \\ \hline Proposed & 8 intersection & Optimal traffic and reducing queue length & Model Predictive Control \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of intersections the proposed method with other existing studies. * All controllers are unpredictable, including advanced controllers such as slip model control (a nonlinear controller is resistant). Nonlinear resistors mean that they do their job against system uncertainties. For example, in the math model from the real world, we do not know the name of a parameter. * Unlike all controllers, the \((u)\) predictor signal drops at \((t+1)\) to \((t+np)\). (\(np:Predictivehorizon\)). Disadvantages:
* Model predictive control has several models. Any situation that is based on step response and impact response must be stable. The system must have no integral behavior. Integral behavior means that there should be no necessities in the system model. * In the basic model, the conversion function is noise-sensitive.
# Bond Characteristics of a Deformed Steel Bar Embedded in Donut-Type Voided Slab
###### Abstract  
In reinforced concrete (RC) structures, bond behavior between concrete and deformed steel bar (rebar) has a great effect on the structural behavior of members including voided slabs. According to previous research, bond behavior of a rebar in voided slabs is different from that in general RC slabs by the concrete inner cover formed between rebar and void. However, the bond characteristics of rebar in voided slabs have not been clearly verified yet. This study investigated the bond characteristics of rebar in the donut-type voided slab. Like other voided slabs, the donut-type void-shaper make concrete inner cover formed between rebar and void, and some part of the donut-type voided slab has smaller inner cover thickness than 2.5 \(d_{b}\). Furthermore, inner cover thickness changes along the longitudinal rebar due to the shape of void. These were expected to affect the bond behavior of rebar in the donut-type voided slab. In this study, pull-out tests were performed to find out the effect of bond condition by the region due to voids. To this end, the donut-type voided slab was divided into three regions according to the shape of void, such as 'Insufficient region', 'Transition region', and 'Sufficient region'. Main variables were inner cover thickness, embedded length, and bond location, which is affected by void shape. Bond characteristics of rebar in the donut-type voided slab were evaluated through comparison of bond stress-slip relationship, maximum bond strength, and bond stress distribution of each region. Test results showed that the average bond stress was found to be 25-50% lower than that of the general RC slab in the region of the inner cover thickness of 2.5 \(d_{b}\), which was not satisfied due to void, and the bond stress-slip relationship and the bond stress distribution of the donut-type voided slab was also different from that of the general RC slab according to the type of bond region and inner cover thickness. In addition, the calculation method of bond strength of rebar in donut-type voided slab was proposed, which indicated that the error range between the estimated value and the experimental value was within 5%.  
donut-type voided slab; inner cover thickness; bond stress-slip; bond stress distribution +
Footnote †: journal: Applied  
doi  
* [FOOTNOTE:*]Footnote *: footnotetext: _Applied_
###### Abstract  
Despite many of years of mapping effort, only a small fraction of the world ocean's seafloor has been sampled for depth, greatly limiting our ability to explore and understand critical ocean and seafloor processes. Recognizing this poor state of our knowledge of ocean depths and the critical role such knowledge plays in understanding and maintaining our planet, GEBCO and the Nippon Foundation have joined forces to establish the Nippon Foundation GEBCO Seabed 2030 Project, an international effort with the objective of facilitating the complete mapping of the world ocean by 2030. The Seabed 2030 Project will establish globally distributed regional data assembly and coordination centers (RDACCs) that will identify existing data from their assigned regions that are not currently in publicly available databases and seek to make these data available. They will develop protocols for data collection (including resolution goals) and common software and other tools to assemble and attribute appropriate metadata as they assimilate regional grids using standardized techniques. A Global Data Assembly and Coordination Center (GDACC) will integrate the regional grids into a global grid and distribute to users world-wide. The GDACC will also act as the central focal point for the coordination of common data standards and processing tools as well as the outreach coordinator for Seabed 2030 efforts. The GDACC and RDACCs will collaborate with existing data centers and bathymetric compilation efforts. Finally, the Nippon Foundation GEBCO Seabed 2030 Project will encourage and help coordinate and track new survey efforts and facilitate the development of new and innovative technologies that can increase the efficiency of seafloor mapping and thus make the ambitious goals of Seabed 2030 more likely to be achieved.  
global bathymetry; Seabed 2030; Nippon Foundation/GEBCO; seafloor mapping technologies; seafloor mapping standards and protocols 2018 8, 63; doi:10.3390/geosciences8020063
# Clustered and Distributed Caching Methods for F-RAN-Based mmWave Communications
## 4 System Model
### Beamformer Architecture at the MS  
Different beamforming models exist for the MS terminal in the context of mmWave bands such as the analog beamforming models in [24; 25; 26] comprised of various array geometries. A request \(r\) generated from MS \(m\in\mathbf{M}\) propagates through a wireless link. Each MS is equipped with RF chain \(\psi_{\text{MS}}\) that is connected to a _uniform linear array_ (ULA) for directional transmission with the F-RAN, where it radiates a single beam. The chain is composed of \(A_{\text{MS}}\) antennas that are equally spaced at \(d_{ant}\ =\ \lambda/2\), where \(\lambda\) is the wavelength, \(\lambda\ =\ \zeta/\chi\), where \(\zeta\) is the speed of light and \(\chi\) is the carrier frequency. Note that antennas are parallelly fed by phase shifters to provide continuous beam scanning. Overall, this formulates an analog beamformer that radiates a primary beam vector \(v\Big{(}\Theta_{0}^{\text{MS}}\Big{)}\) that points towards \(\Theta_{0}^{\text{MS}}\) direction. The vector for this direction is part of the vector matrix, \(V_{\text{MS}}\) at the analog stage of the chain, i.e., \(v\ =\ \ v_{ant}\), where \(v_{ant}\) is the analog precoder. It is determined by the far-field array factor for the ULA, written as [27; 28],  
\[\text{AF}_{\text{MS}}\ =\ \frac{1}{A_{\text{MS}}}\sum_{1}^{A_{\text{MS}}}a\exp(j (A_{\text{MS}}-1)(kd_{ant}\cos\Theta_{0}^{\text{MS}}+\beta)) \tag{2}\]  
where the variables \(a\), \(k\), and \(fi\) denote the amplitude of the antenna at the MS, wave number, i.e., \(k\ =\ 2\beta/\ \tilde{\ }\), and the progressive phase shift between the elements at the MS, respectively.
## 1 Introduction  
Selective recognition and sensing of biologically important anions has attracted considerable attention in the field of supramolecular chemistry because of its important roles in medical, biological, chemical, and environmental systems [1; 2; 3; 4; 5; 6; 7; 8; 9; 10]. For example, carboxylate ions are vital components of many human metabolic processes [11]. Phosphorylated species are of considerable interest due to their existence in a variety of biological processes such as energy transduction, signal processing, genetic information storage, and membrane transport [12; 13; 14]. Thus, the importance of the selective detection of carboxylate and phosphorylated biomolecules probably surpasses that of other biologically functional anions. So far, the focus has mainly been on the design of a receptor that has the ability to recognize and bind the biologically important anions. The binding units in receptors are important and often composed of amide [15], urea [16], hydroxyl [17; 18], and pyrrole [19] owing to their capacity to perform as hydrogen donors. However, the literature has reported few cases of acylhydrazone (NHCO) serving as an anion binding site.  
The compounds containing a hydrazine structural unit have a molecular structure that is widely used as a precursor or intermediate of many organic molecules. A hydrazide skeleton is an important synthesisunit and its derivatives also have great potential application because of their wide range of biological and physiological activity, including antiviral, antitumor, resistance to malaria, insecticide, and germicide [20; 21; 22]. Meanwhile, the strong coordination capacity makes it widely used in the analysis of subject areas, and for cyclic or non-cyclic hydrazide derivatives. Therefore, the synthesis and biological properties of hydrazine derivatives attracted the attention of many scholars. The research about the relationship between structure and biological activity could provide useful information in order to explore the sterilization of high effect and low toxicity drugs. However, almost no studies about anion binding ability based on acylhydrazone derivatives are currently being reported.  
Bearing the above considerations in mind, in this paper we report the synthesis of benzoylhydrazine derivatives and their properties containing antibacterial activity and anion binding ability (Scheme 1). The obtained experimental results showed that compound **6** (phenanthroline hydrazide derivative) could effectively recognize and sense AcO\({}^{-}\) in DMSO. To our delight, compound **6** also showed wide antibacterial activity.