esa-sceva/satcom-chunk-collection huggingface dataset:
# Design and Test of Seeding-Picking Mechanism of Fully Automatic Transplanting Machine
## 2 Materials and Methods
### Design of Seedling Delivery Device  
The seedling-feeding device mainly consists of 4 parts, as shown in Figure 1 (3), which are the bracket, the seedbed, the electromagnetic seedling lifting mechanism, and the longitudinal shifting mechanism; among them, the seedbed is supported by the bracket and fixed on the frame, and the seedbed is A roller runner is installed, and the plug tray is placed between the two runner bars. Two stepper motors are installed on the left and right sides of the seedbed, with each motor equipped with a rubber roller. The rollers are connected to the motors via couplings. The distance between the two rollers on the same side is adjustable, and the drive mechanism is located on the same side. The two stepper motors rotate in opposite directions, which causes the rollers to rotate in opposing directions. This action squeezes the thin fluency bar with the smooth strip, allowing the thin fluency bar to move along the inclined direction of the seedbed under the influence of the extrusion force, as shown in Figure 2b. When the plug tray is tilted on the seedbed, it passes through the seedling lifting area before arriving at the predetermined seedling-picking point. Six electromagnetic seedling lifting devices are installed below the seedling lifting area, as illustrated in Figure 1 (7). The selected electromagnetic ejector rod is a push-pull long-stroke electromagnet produced by Jiexiang Electric (Suzhou, China). This device controls the current to the electromagnetic seedling lifting apparatus, enabling the electromagnetic seedling lifting rod to move up and down according to a preset displacement amount. This movement facilitates the adjustment of the plug seedling substrate and helps overcome the adhesion between the substrate and the inner wall of the plug grid. As a result, the knot strength can reach a loose state, thereby enhancing the efficiency and success rate of subsequent seedling clamping. After collecting the seedlings from the entire plug tray, the roller device gathers the hole trays on the runner, completing a seedling feeding cycle.
## 3 Results and Discussions  
### Analysis of Numerical Simulation  
#### 3.1.1 Flow Field Characteristics  
The calculation of pressure, momentum, turbulent kinetic energy, and turbulent dissipation rate utilizes a second-order upwind scheme to ensure high accuracy of the computational results. The under-relaxation factor adopts the default value in CFD. Steady-state calculation has been performed, and the following analysis was conducted after achieving convergence of the results:  
From Figure 7, the air velocity near the surface of the photovoltaic (PV) module increased with the increase in vertical height, with a maximum value ranging from 3.33-3.89 m/s. and the pressure near the surface of the photovoltaic (PV) module changed by an opposite trend, ranging from 3.33-5.56 pa. The main reasons for the above phenomena were as follows:  
1. The gas micro-mass flowing into the calculation domain would first reach the surface of the near-ground photovoltaic (PV) module and collide with it, then lose part of the kinetic energy to rapidly reduce the flow rate and cause retention;
2. With the extension of time, more and more gas micro-clusters would be retained on the surface of the near-ground side photovoltaic (PV) module, increasing the pressure of this region;
3. When the retention amount of gas micro-clusters reaches the threshold, the mainstream would be squeezed out and then be far away from the surface of the near-ground side photovoltaic (PV) module, and finally approximately tangentially across the surface of the far-ground side photovoltaic (PV) module;
4. When air micro-clusters pass through the far-ground side surface of the photovoltaic (PV) module, the collision probability is greatly reduced, which makes the airflow velocity larger and the air pressure lower.  
Figure 6: Experimental procedure flowchart.  
3.1.2. Influence of the Spherical Coefficient on the Distribution Characteristics of Aerosol Particles  
The study focused on the relationship between surface particle settlement, accumulation, and the sphericity coefficient under three particle size conditions. We examined the distribution characteristics of aerosol particles on photovoltaic component surfaces, specifically using a particle diameter of \(d=20\)\(\upmu\)m. Figure 8 demonstrates the possibility of establishing concentration distribution cloud maps of particles on the surface of photovoltaic components, utilizing simulation results. Figure 9 illustrates the particle distribution under experimental conditions, primarily indicating particle accumulation below the deposition surface, aligning with the conclusions derived from numerical simulation.
# Behavior and Damage Characterization of Impulsively Loaded Cross-Laminated Timber Panels
## 2 Materials and Methods  
The following research uses an impulsive, one-way, out-of-plane, three-point bending test program of CLT panel specimens with low span-to-depth ratios to study shear modes of failure and characterize damage in impulsively loaded CLTs. Center-point bend tests are recommended for determining apparent bending stiffness, shear strength, and RS strength of CLTs using the ANSI/APA PRG 320-19 [17]. Furthermore, CLT panels subjected to out-of-plane bending experience shear deformations, i.e., shear warping, than flexural elements composed of other materials, e.g., steel. The effect of shear deformations is more pronounced at low values of span-to-depth ratio, \(L/h\leq 14\)[18], \(L/h\leq 15\)[19], or \(L/h\leq 18\)[20]. At particularly low values of the span-to-depth ratio, the effect of the shear deformations dominates the response of a CLT panel loaded out of plane, controlling 50-60% of the overall deflection. Furthermore, at low values of \(L/h\), interlaminar stresses in the cross laminations increase significantly, leading to a higher likelihood of RS failures. [PERSON] et al. [18] show that the experimental methods they employed to determine rolling shear modulus in the cross layers of CLT overestimated the modulus when values for \(L/h\geq 8\). This indicates that a value of \(L/h\) equal to approximately eight or less appears to be an appropriate range to consider for experimental testing where RS modulus and strength are of interest. The ANSI/APA PRG 320-19 recommends the use of a center-point flexural test, a special case of three-point flexural tests, with a CLT specimen having a span-to-depth ratio of \(5\leq L/h\leq 6\). Short-span center-point flexural tests have been used by several researchers to induce RS failures and determine RS strength in quasi-statically loaded CLT [18; 21; 22; 23; 24; 25].
## 3 Methodology
### Fuzzy Delphi  
Different fuzzy Delphi techniques have been presented in the multiple-criteria decision-making (MCDM) literature. However, this study was developed based on a classic form of the method [15]. The proposed technique in this study was a combination of gray numbers, fuzzy set theory, and a Delphi technique, as follows.  
Step 1 (expert panel): Experts were asked to provide an interval value (gray number) as a representation of the relative importance of the intended criteria. Here, \(\left[q_{k}^{(i)}.r_{k}^{(i)}\right]^{(p)}\) denotes the \(i\)th respondent in the \(k\)th iteration for the \(p\)th alternative.  
Step 2 (fuzzification): The interval values were turned into a fuzzy membership  
\[Y^{(p)}(x_{s})=\frac{y_{s}^{(p)}}{y_{s}^{(p)}}. \tag{4}\]  
Step 4 (defuzzification): The center of gravity (COG) was the proposed methodology used to defuzzify the proposed fuzzy number. Finally, the average value for each criterion was measured:  
\[\overline{COG^{(p)}}=\frac{\int Y^{(p)}(x_{s})\times x_{s}\times d(x_{s})}{ \int Y^{(p)}(x_{s})\times d(x_{s})}. \tag{5}\]  
Step 5 (consensus evaluation): If the linear absolute distance of the calculated average value (\(\overline{COG^{(p)}}\)) with all of the respondents' defuzzified values (the COG) was less than 0.7, the answer converged and the process for this criteria was stopped.
## 5 Simulation Set-Up of the Proposed HF-Based Security Architecture
In addition, in this step, the channel is created as shown in Figure 9. Once the channel is created, each peer can join the channel to establish communication within the HF network. * In this step, we access the peer _cli_ using the prompt command _docker exec -it_. Through the peer _cli_, we initiate the connection of the peer to the channel, as shown in Figure 10.
* This step involves the installation of the chaincode. At this point, we pack the chaincode into a Docker container, install it on the peers, and instantiate it on the channel. Then the initial state of the ledger is created and stored in the _CouchDB_. Figure 11 depicts the initiation of the installation of the chaincode in the channel, while Figure 12 depicts the final step of the process which is the successful approval of the chaincode to the channel and the commitment of the chaincode by both peers. * Finally, as the chaincode is installed in the peers, the user can interact with the state of the ledger and initiate transactions through the peer _cli_ by querying the chaincode. Figure 5: Creating CAs (step 1). Figure 6: Enrolling the CA admin (step 2). Figure 8: Creating the genesis block (step 4). Figure 10: Joining _peer0.org1_ into the channel (step 6). Figure 3:0 Channel creation (step 5). Figure 3:1 Enrolling the org1 admin (step 2). In Figure 13 we present the containers deployed for the purpose of the HF network simulation:  
It is worth mentioning that the aforementioned HF architecture can be secure and effective against eavesdropping, spoofing, and masquerading attacks due to the deployed Certificate Authority that provides TLS and MSP certificates to the nodes (i.e., peers, orderers) connected to the network. These certificates are necessary in order for a node to be able to securely communicate, transmit, or receive information in the network. Therefore, a non-certified, by the deployed CA, node is unable to participate in the network.
## 4 Challenges and Considerations
### Post Processing
The above-mentioned needs increased lead time and costs; however, these may be minimised with further development of novel technologies and hybrid AM systems, and improvements in design software that can account for expected variations post production.
## 5 Experimental Verification  
To verify the validity and reliability of the PMSG presented in the previous section, a system for performance evaluation was constructed, as shown in Figure 9. The performance evaluation method of generator includes a method employing a dynamo or back-to-back system. However, because the generator designed in this study has a large capacity and high rotational speed, it is difficult to establish a performance evaluation using dynamo. Therefore, by constructing a back-to-back system, two rotor types of PMSG experiments were performed. Figure 10 shows the results of the FEM analysis when the Inconel 718 rotor is loaded and the comparison result of the line-to-line voltage and phase current characteristics measured during the experiment.  
In the case of the Inconel 718 rotor, it has a nonmagnetic characteristic even after heat treatment for coupling the rotor. In addition, since there is no magnetic flux leakage to the shaft, the error rate of the line voltage is about 1.96% and the error rate of the phase current is about 1.89%, so it was possible to obtain a result satisfying very similar electromagnetic characteristics and requirements.  
Figure 8: Modal analysis of Inconel 718 shaft rotor.  
Figure 7: Critical speed analysis of Inconel 718 shaft rotor.
# Programmable Deterministic Zero-Copy DMA Mechanism for FPGA Accelerator
## 3 Programmable Deterministic Multi-Queue Accelerator Model
### Model Design  
We divided the model structurally into three modules: Serverless-friendly Programmable Multi-queue Scheduling, Deterministic DMA for Serverless, and UserSpace Zero-copy Driver. Combined with the characteristics of a multicore serverless node, a programmable rule-based flow classifier is used to forward the input flow precisely to hardware queues bound to different cores to enhance the concurrency. A hardware clock component is added to interact with the transmission scheduler to control the transport engine of each hardware queue for deterministic delivery. In addition, the zero-copy driver in the userspace, which eliminates hardware interrupts and data copy overhead, can further enhance the packet sending and receiving efficiency.  
The three modules provide their features in the accelerator and interact through a hardware descriptor ring that the accelerator and the host jointly manage. This ring is located in the memory pool allocated by the driver, and both the DMA controller and the accelerator can operate. Each descriptor stores information such as the physical address of the packet, the timestamp, the descriptor completion flag, etc. The starting physical address of the descriptor ring is stored in the accelerator's base register, the number of descriptors is stored in the size register, and the registers tail and head represent the production and consumption of descriptors. The descriptor between the tail and head is available (avail). The accelerator and host interact through reading and writing registers. The state of the descriptor ring's usage follows the production-consumption mode and its state change over time, as shown in Figure 2. The accelerator delivers or collects the packet to/from the host through the DMA controller in cooperation with the PCI bus. The driver implements deterministic DMA functionality by writing a descriptor with a custom timestamp field into the hardware descriptor ring, combined with the precise timing of the PTP hardware clock.
# Performance Analysis of Latency-Aware Data Management in Industrial IoT Networks +
## 2 Literature Review
Our DML concepts and algorithm can work on top of this approach (and of any clustering approach), for example by allocating the role of proxies to cluster heads. In fact, clustering and our solution address two different problems. In [25], the authors considered industrial networks with a fixed number of already deployed edge devices that acted as proxies and focused on the maximization of the network lifetime. They considered as lifetime the time point until the first node in the network died. As a result, in this paper, they assumed a different model, different optimization problem and different performance targets. Finally, a relevant application domain for distributed data management was also the workshop networks in smart factories [26; 27], in which a large amounts of data was transmitted, bringing big challenges to data transfer capability and energy usage efficiency. Motivating examples: We also present two indicative application areas where the DML and the relevant algorithm can provide additional value. In [28], the authors presented a typical situation in an oil refinery where miles of piping were equipped with hundreds and thousands of temperature, pressure, level and corrosion sensors, which were deployed in a large geographical area. Those sensor motes not only performed industrial condition monitoring tasks, but they also used the industrially-oriented communication technology TSCH. In [29], the authors presented two large-scale deployments of hundreds of nodes; one in a semiconductor fabrication plant and another on-board an oil tanker in the North Sea. They used Mica2 and Intel Mote nodes, very similar to our sensor motes of choice. In both those applications, due to the exact fact that the sensor motes were not able to communicate directly with the controller (transmission range restrictions), the system designers naturally considered a multi-hop propagation model. The targeted decentralization of the data distribution process in those large-scale condition monitoring and predictive maintenance application areas could lead to economic benefits for the industrial operator and maintenance of some important metrics in the network at good levels, while ensuring that the end-to-end latency is acceptable, without introducing overwhelming costs in the system for the purchase of expensive equipment.
## 5 Discussion
### What Should Be the Next Research Topics to Advance Treatments for Human Hair Graying?
Only a few studies have evaluated the anti-hair-graying efficacy of plant extracts, mixtures, or bioactive compounds through clinical trials [146; 151; 152], and most studies were conducted using human cells or mice. There are limitations to predicting their therapeutic efficacy for human hair graying based on mouse model studies because of the higher complexity of controlling hair pigmentation in humans. There may be other similar studies not covered in this review. For example, glycosylated polyphenols derived from _Larix europea_ wood extract and _Camellia sinensis_ leaf extract reduced oxidative stress and protected MSCs in human hair follicles ex vivo, and in a clinical study carried out for 4 months on 44 Caucasian male volunteers with 30% to 95% gray hair, a lotion containing the active ingredient reduced the proportion of gray hairs to the total hairs and the number of gray hairs per unit scalp area relative to day 0 values to a greater extent compared to the placebo control [178]. More expanded clinical trials are needed to evaluate the efficacy of various plant-derived natural products on human hair graying. Early diagnosis and patient-tailored treatment are essential. As the possible causative factors for hair graying are known, specifying the exact cause through questionnaires and biochemical analysis is important for specific patients. In reported cases, hair graying occurring due to iron or essential fatty acid deficiency was treated by supplying each nutrient [117; 122]. Mirtazapine-induced hair graying could be treated by discontinuing this medication [128]. Analysis of the patient's oxidative stress status and stress hormone levels will also provide an important guide to patient-tailored treatment. Since plant-derived natural products have both pros and cons as medicines, they must be used for appropriate purposes in appropriate amounts to find a balance between efficacy and side effects [37; 39; 40]. For example, PM extract may be used to alleviate both hair loss and graying [133; 134; 179], but caution should be taken because its high doses can cause liver toxicity [180; 181]. Molecular targets for treating hair graying are being specified, and information on the efficacy and mechanism of action of individual phytochemicals is expanding. We hope that by using such information, an effective treatment that will help maintain the health and beauty of hair will be developed in the near future.
## 5 Discussion of Slurry Diffusion Behavior in Rough Fractures and Analysis of Field Applications  
From the results of the previous rough fracture grouting diffusion experiments, it can be observed that grouting pressure, fracture aperture, and fracture roughness have varying degrees of impact on the pressure distribution along the slurry diffusion path. Grouting pressure serves as the primary driving force enabling slurry flow within the fractures. A higher grouting pressure implies increased slurry flowability and an extended range of slurry pressure distribution. The size of the fracture aperture alters the flow space for the slurry. A larger aperture reduces the difficulty of slurry filling in the fractures, allowing slurry pressure to be more fully released and leading to decreased pressure. Greater fracture roughness, on the other hand, increases the resistance to slurry flow, resulting in a faster pressure decay rate. Therefore, for different fracture parameters in the grouting environment, the appropriate grouting techniques should be selected accordingly:  
Figure 14: Comparison curve of pressure differences between different measurement points.  
When the fracture aperture is relatively small, the roughness of the fracture will have a more pronounced effect on slurry flow. Slurry is less likely to flow within the fractures. Using a higher grouting pressure at this point can lead to local vortex phenomena due to excessive flow velocity, causing increased resistance losses along the path, which may not be conducive to slurry diffusion. Therefore, in the case of small fracture apertures, using a lower grouting pressure for construction will yield better grouting results.
2. When the fracture roughness is relatively high, as indicated by the earlier analysis, lower grouting pressure should be used for construction. Conversely, using a higher grouting pressure will better meet the actual grouting requirements.
3. When the fracture roughness is relatively high, as indicated by the earlier analysis, a lower grouting pressure should be used for construction. Conversely, using a higher grouting pressure will better meet the actual grouting requirements.  
To better assess the applicability of the research findings, field applications were carried out at the Waytian Coal Mine in Guizhou. Prior to this, measurements and analysis were conducted to determine the distribution of fractures in the tunnel surrounding rock. Combining theoretical analysis and experimental results, the grouting process was optimized. A comparative analysis of tunnel deformation before and after implementing the optimized grouting process was performed. The tunnel surrounding rock deformation is shown in Figure 15a,b. From the figure, it can be observed that the use of the optimized grouting process effectively controlled the deformation of the tunnel surrounding rock, reducing it to 3 mm/day, ensuring safe and efficient coal mining operations.