esa-sceva/satcom-chunk-collection huggingface dataset:
# Sustainable Optimization of the Injection Molding Process Using Particle Swarm Optimization (PSO)
## 4 Result  
### Experimental Setup  
This study focused on optimizing the plastic injection molding process to produce ink barrel caps using a new mold and polypropylene 3040C as the raw material. The polypropylene 3040C (PP3040C) material had a density of 0.905 g/cm\({}^{3}\) and a melt flow rate (MFR) of 25 g/10 min (230 \({}^{\circ}\)C, 2.16 kg), ensuring optimal flow characteristics for thin-walled parts. Key process parameters were identified through consultations with field technicians, such as pressure-holding switch position, melt endpoint, injection endpoint, holding pressure, nozzle temperature, and melt temperature. The target specifications were defined as a product weight of 66-70 g and a 3-5 mm thickness based on customer requirements. A Taguchi method was first employed to optimize the architecture of the BPNN, followed by further parameter optimization using PSO.  
The six process parameters--pressure-holding switch position, melt endpoint, injection endpoint, holding pressure, nozzle temperature, and melt temperature--were selected based on their well-documented influence on part quality in injection molding literature [3; 6; 12] and direct consultations with field technicians. The following parameters collectively control three critical phases of the molding process:  
1. Material flow dynamics (melt endpoint, injection endpoint);
2. Pressure and packing control (pressure-holding switch position, holding pressure);
3. Thermal stability (nozzle temperature, melt temperature).  
Preliminary screening experiments using Plackett-Burman design confirmed these factors accounted for >85% of observed variability in part weight and thickness (\(p<0.01\)). The pressure-holding switch position was particularly prioritized due to its dual role in preventing over-packing (reducing material waste) and minimizing residual stresses (improving part durability). Melt temperature selection (234.8 \({}^{\circ}\)C for PP3040) was further validated against the material's thermal degradation threshold (270 \({}^{\circ}\)C) to ensure energy efficiency without compromising polymer integrity. This targeted parameter set provides a balanced representation of mechanical, thermal, and flow-related variables while remaining practically adjustable on most SME-grade molding machines.
## 5 Results and Discussion: Cogging Torque
### SE: Evaluation on 24-Slot, 22-Pole PMSM and MPMSM  
In Figure 7, the cogging torque outcomes of the FE evaluation of a 24-slot, 22-pole PMSM and a 24-slot, 22-pole MPMSM are presented for SE. Similar to DE results, SE results were extracted considering the rotor structure completes one full turn to correctly obtain the harmonic content of the cogging torque signal. However, only the main period (when eccentricity is present) is presented in order to provide a clearer visualization. In Figure 7a,c, the cogging torque waveform is shown for a 24-slot, 22-pole MPMSM and PMSM, respectively. In turn, Figure 7b,d present the harmonic spectrum of the cogging torque waveform for both machines, modular and conventional, when SE is present.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \(Q_{s}\)/\(2p\)ECC & \(\Delta\left(Q_{s},2p\right)\) & \(\mathbf{0.25\ mm}\) & \multicolumn{2}{c}{\(\mathbf{0.50\ mm}\)} & \multicolumn{2}{c}{\(\mathbf{0.75\ mm}\)} & \multicolumn{2}{c}{\(\mathbf{1.00\ mm}\)} \\ \hline  & & Mod [\%] & Mon [\%] & Mod [\%] & Mon [\%] & Mod [\%] & Mon [\%] & Mod [\%] & Mon [\%] \\
18S 12P & 6 & 0.19 & 0.22 & 0.53 & 0.65 & 1.15 & 1.30 & 2.07 & 2.18 \\
18S 20P & 2 & 27.23 & 26.21 & 102.72 & 105.80 & 238.69 & 236.47 & 422.04 & 424.21 \\
24S 20P & 4 & 0.29 & 0.69 & 1.33 & 3.05 & 4.42 & 7.62 & 11.00 & 17.45 \\
24S 22P & 2 & 12.58 & 16.57 & 72.73 & 89.18 & 180.61 & 215.49 & 374.00 & 435.19 \\
24S 28P & 4 & 0.41 & 0.11 & 1.62 & 2.12 & 4.64 & 8.61 & 10.33 & 26.39 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Relative cogging torque increase of different PMSM and MPMSM slot/pole combinations in the presence of DE.  
Figure 7: FE evaluation of cogging torque in the presence of SE for 24-slot, 22-pole PMSM and MPMSM: (**a**) cogging torque waveform for the modular machine, (**b**) cogging torque spectrum for the modular machine, (**c**) cogging torque waveform for the monolithic machine, (**d**) cogging torque spectrum for the monolithic machine.  
When SE is present, the main period of the cogging torque changes from 1.36 to 16.36 mechanical degrees, which corresponds to the pole pitch. From (2), it may be noted that the cogging torque main period is defined by the periodicities of the stator and rotor structures when no eccentricity is present, but eccentricity breaks the stator/rotor periodicity. For the case of SE, the minimum airgap is stationary, and the relative position between the magnet symmetry axis and teeth symmetry axis depends exclusively on the movement of the poles, which is periodical and repeats each \(360/2p\) mechanical degrees. Therefore, the main cogging torque period should change to the additional harmonic components generated, given by:  
\[T_{T\text{ }\text{ }\text{AHC SE}}=\frac{360}{2p}, \tag{8}\]  
From Figure 7, it can be noted that significant cogging torque components with HO = 22 and its multiples are generated with SE, which results in a peak-to-peak value increase of up to 400%. Nevertheless, this does not hold true for all evaluated slot/pole combinations.
## 4 Numerical Simulation and Discussion
### Discussion  
#### 4.4.1 Factor Analysis  
Comparative studies are also implemented in parallel which considers the hydro-mechanical (HM) interaction process and neglects the influence of thermal field variation. The deformation processes at VD4 and VD7 are displayed in Figure 20.  
A comparison between THM and HM results represents the influence of the thermal field. According to the results, thermal field variation shall be responsible for more than 60 percent of the total deformation; it is the main factor that causes the deformation after the initial impoundment.  
Figure 19: Comparison between simulation data and observed data.  
While long term deformation is mainly caused by the temperature changes, the deformation in the first two years is mainly affected by seepage variation.
# Secure Cognitive Radio Vehicular Ad Hoc Networks Using Blockchain Technology in Smart Cities
## 1 Introduction
The authenticity is proven by an RSU, which serves as a database to deploy a smart contract and provides secure key pairs to all vehicles that successfully register with the RSU. In addition, after registering, PU takes some amount from the vehicles that use its free spectrum. Moreover, secondary users also perceive the channel provided by PU before initiating their communication, as channel statistics vary with space and time. A belief propagation algorithm with an energy detection scheme is utilized to exchange local sensing results and finalize the channel's state at the present location. This ensures that the channel is used safely and securely. Moreover, to make our blockchain network a fair and secure mechanism for conveying any message, we introduce rewards to all nodes who participate in conveying any message that is beneficial for other vehicles on the road. In this way, we ensure that all nodes participating in this network are authentic and gain benefits by becoming part of this network and performing their duties honestly. These are the major contributions of this article:  
1. The consideration of two major concerns in vehicular networks: spectrum scarcity and security. Integrating blockchain technology in cognitive vehicular communication through a new method of spectrum sharing for primary and secondary users is one of the major contributions of this article. 2. Another contribution is the provision of a fair and secure reward scheme for cognitive vehicular communication that aims to convey information quickly and honestly. 3. This article considers spectrum sensing and routing simultaneously using blockchain technology, with the main contribution being the calculation of a path between source and destination that only uses authentic vehicles to forward messages when channels are idle. The remaining parts of this article are arranged in the following manner: Section 2 provides a literature review; Section 3 describes the proposed scheme; Section 4 shows the performance evaluation; and Section 5 draws conclusions.
# Detection and Prevention of DDoS Attacks on the IoT
## 2 Scenarios of DDoS Attack
### System Resource Consumption DDoS Attacks
#### 2.2.2 Local Area Network Denial (LAND) Attack  
The main difference with SYN flood is that the fake IP is changed to the same as the attacked host IP. As a result, the host continuously sends SYN + ACK packets back to itself, forming an infinite loop and consuming the resources of the attacked host.
## 4 Discussion
It was found that the size and thickness of the precipitates as well as the inter-particle distance were not the same for all HAGBs and this was also proved for LAGBs. However, in neighboring areas where for instance an HAGB met with an LAGB the size of the precipitates was coarser in the HAGB. The morphology of the precipitates was globular in most cases for the LAGBs, while for the HAGBs the size was globular, elliptical and in some cases they were semi-continuous as a layer on the interfaces. In the SGBs, any precipitation was difficulty discerned, and the interfaces on the whole leaned on such particles. The precipitation behavior was comparable between the surface and mid-thickness locations, and by high-magnification imaging, one could not easily distinguish if one of the two areas was observed. Optical microscopy can prove as a very useful tool for signifying low ductility performance in automotive profiles for crash systems and bumpers. In case the thermomechanical process leads to inferior formability, this can be clearly demonstrated by the formation of PFZs which are recognizable at even a 500\(\times\) magnification by optical microscopy. They appear as white, thin zones on the grain boundaries. The more continuous they are, the more probable it is that intergranular cracking will appear in mechanical tests in the respective profiles. It is obvious that the delineation of the grain boundaries with PFZs revealed some of the HAGBs which were those with higher precipitation propensity and formed thicker PFZs. From the point of fractographic examination, a low-ductility sample exhibited ductile, intergranular cracking, resulting from the combination of a low-strength intergranular zone depleted in alloying elements surrounding the higher-strength grains interiors, including \(\beta\)\" and \(\beta\)\"precipitates of nanometer size, which were not easily discernible with an SEM. In the case of the harder 6 xxx alloys which contained higher Si and Mg contents as well as other strengthening elements such as Mn and Cr, a grain boundary decision across the thickness was not observed and can be only noticed on subsurface layers in case secondary recrystallization occur [13]. After the initiation of the initial crack when it reached the recovered region of the profile in the mid-thickness location of the profile, it propagated at a transgranular mode of low or high ductility with dimples formation, depending on the metallurgical condition (aging). Additionally, since no other low-energy paths existed, the constituent \(\alpha\)-AlFeSi particles played this role and cracking could be detected between two adjacent particles. In the current investigation, similar behaviors were observed in the WQ and SC three-point bent specimens which had elongation values higher than 12%.
###### Abstract
During oxidative stress, Nrf2 dissociates from Keep1 to be translocated into the nucleus; in turn, nuclear Nrf2 upregulates ARE-associated gene expression, i.e., heme oxygenase-1 (HO-1), NAD(P)H quinine oxidoreductase (NQO1), glutamate-cysteine ligase (GCL), GSH, GSH peroxidase (Gpx), etc., to maintain the cellular redox homeostasis [15]. As polyphenols from dietary sources are widely known for tackling oxidative stress, modulation of Keep1-Nrf2-ARE signaling by some of these compounds is expected to bring benefits in the prevention of oxidative-stress-mediated cancers. Certain phytochemicals including dietary constituents that can decrease tumorigenesis both in vitro and in vivo experimental models. It has been well-established that the intake of these phytochemicals can either prevent cancer or slow down its growth and progression [16]. They play these roles either by decreasing metabolic activation of carcinogen, increasing the detoxification of carcinogens, or preventing them from binding with their cellular targets. Figure 1 demonstrates how certain groups of dietary nutraceuticals have been recognized or are thought to modulate specific pathways causing breast cancer development. This evidence, as well as additional information on naturally occurring food constituents and vitamins, has established the idea that diet modification can play vital role to prevent cancer [17]. Terpenoids, present largely in plants, animals, fungi and microbial species, are known for exhibiting potential effectivity against cancers [18]. For example, betulinic acid, a triterpene compound extracted from birch tree, has shown cytotoxic activity in multiple cancer cells [19; 20]. The cancer suppressing properties of terpenoids include inhibition of cell adhesion, migration and proliferation, specifically observed for a novel diterpene, tanshinone [21]. Limonene, a monoterpene, can be deposited in the fatty tissues due to its lipophilic nature in order to produce a long-term chemopre effective by mediating cell cycle arrest and eventually apoptosis [22]. Recently, multiple terpenoid compoundshave been found to be effective in activating the Keap1-Nrf2-ARE pathway, where the downstream target genes of Nrf2 were enhanced in a process that involved phosphoinositide 3-kinases (PI3K), protein kinase C (PKC), etc., [23]. In this review, we summarize the information of dietary terpenoids demonstrating a cancer chemopretive role by direct or indirect modulation of the Keap1-Nrf2-ARE signaling system. The chemopretive mechanisms of the associated up- and downstream signaling molecules of Keap1-Nrf2-ARE signaling are also discussed.
# A Charging and Discharging Data Privacy Protection Scheme for V2G Networks Based on Cloud-Fog-End
## 4 Correctness and Security Analysis
### Security Analysis
#### 4.2.7 Resistance to Distributed Denial of Service (DDoS) Attacks  
The communication architecture of this scheme is based on cloud-fog collaboration, where introducing fog devices between the cloud and user layers enables distributed computation and storage of fog computing, mitigating issues such as vulnerable transmission distance and susceptibility to DDoS attacks in traditional cloud computing.
# Ad Creative Discontinuation Prediction with Multi-Modal Multi-Task Neural Survival Networks
## 4 Methodology
### Overview of the Proposed Framework  
Figure 3 shows the outline of our framework. For predicting the timing of ad creative discontinuation, we adopt and integrate the hazard function, which is based on the discrete-time survival prediction strategy [28]. From the input ad creative \(\mathbf{x}\) observed in time \(t\), our framework outputs hazard probability \(\mathbf{h}\) for \(L\) pre-defined time intervals \(t\) such that \((0,t_{1}]\), \(\mathcal{T}=(t_{1},t_{2}]\), \(\cdots\), \((t_{L-1},t_{L}]\) through hazard function \(f(\cdot|\cdot)\) with sigmoid function \(\sigma\):  
\[\mathbf{h}=\sigma(f(t|\mathbf{x}))\in\mathbb{R}^{L}. \tag{1}\]  
The details of how the function is learned are in described in Section 4.2.  
The input to our framework is ad creative \(\mathbf{x}\) observed in time \(t\); the framework uses the four types of features that constitute an ad creative: text features \(\mathbf{x}_{1}\) (e.g., title, description), categorical features \(\mathbf{x}_{2}\) (e.g., gender of the serving target, genre of the ad creative), image  
Figure 3: Outline of our framework that exploits a hazard function, which draws on the idea of survival prediction, to predict the discontinuation of ad creatives. The input includes the four types of features: text, categorical, image, and numerical features. The output is the hazard probability, which includes whether the target ad creative has been discontinued in each time interval.  
features \(\mathbf{x}_{3}\) (e.g., the image attached to the ad creative), and numerical features \(\mathbf{x}_{4}(t)\) (e.g., the number of impressions, clicks, conversions, and the CPA for the ad creative), which include statistical features and time-series features. \(\mathbf{x}_{1}\) to \(\mathbf{x}_{3}\) are invariant with time interval \(t;\mathbf{x}_{4}\) varies with \(t\) due to the serving performance.  
For the input features, each type of feature is encoded according to the type, such as text embeddings \(\mathbf{e}_{1}\), categorical embeddings \(\mathbf{e}_{2}\), image embeddings \(\mathbf{e}_{3}\), and numerical embeddings \(\mathbf{e}_{4}(t)\). For all features, we performed conventional encoding and aggregation as well as encoding based on DNN techniques. Due to the space limitation, the details of these input features and encoding processes are presented in Appendix A. Additionally, we briefly mention the properties of the features obtained by these encoding processes in the section.  
For predicting the hazard probability, the encoded features are finally integrated using a multi-layer perceptron (MLP) to estimate the serving days of an ad creative in the pre-defined time intervals:  
\[\mathbf{h}=\sigma(f(t|\mathbf{x}))=\sigma(\text{MLP}([\mathbf{e}_{1},\mathbf{e}_{2},\mathbf{e}_{3},\mathbf{e}_{4}(t)]))\in\mathbb{R}^{L}. \tag{2}\]
# Instability Characteristics of and Control Techniques for Mudstone-Clay Composite Roof Roadways
## 3 Microscopic Experimental Study on Mudstone-Clay
### Analysis of Mudstone-Clay Experimental Results  
#### 3.2.1 XRD Experimental Analysis  
X-ray diffraction analysis of the layered mudstone-clay roof composition, which exhibits significant deformation during rainy seasons, revealed the following mineral  
Figure 2: Main experimental equipment diagram.  
contents and the crystal structures [35] (Figure 3): Red mudstone comprises 29% muscovite, 42.9% quartz, 11.8% anorthite, and 16.3% calcite. Clay samples contain 49.9% quartz, 30.2% muscovite, 11.4% kaolinite, and 8.4% anorthite. Yellow mudstone contains 52% quartz, 46.2% muscovite, and 1.8% hard gypsum. Among these minerals, muscovite, quartz, anorthite, and calcite demonstrate weak hydrophilicity with stable structures and minimal water reactivity. While anhydrite exhibits strong hydrophilicity, its low relative content minimally impacts roadway deformation. Kaolinite, a clay mineral containing hydroxyl groups, displays strong water absorption when dry and high plasticity upon water contact, though it resists swelling.
# Removal of Metal Ions in Spin-on Hardmask Using Functionalized Porous Silica Adsorbents
## 2 Experimental
### Adsorption Isotherm Modeling  
To plot the adsorption isotherms, solutions were prepared individually for each metal ion [18]. Single-metal ion solutions with initial concentrations of 0.02, 0.05, 0.1, 0.2, 0.4, 0.6, 0.7, 0.8, 0.9, and 1.0 M for each metal ion in methanol were prepared. For each concentration, 30 mL of the solution was placed in a 50 mL vial. MCM-41-NH\({}_{2}\) adsorbent was then dispersed in each solution at a ratio of 2 mg mL\({}^{-1}\) (adsorbent/solution). The mixtures were stirred at room temperature for 24 h, and the initial and equilibrium concentrations of metal ions were measured using ICP-OES.
# Two Design Options for Compact Linear Accelerators for High Flux Neutron Source
## 3 Physical Design of DTL Accelerator
### Drift Tube Designs  
A series of computations has been carried out using the SUPERFISH code [44] to design drift tubes in the 162.5 MHz and 325 MHz DTLs. The cell length is equal to \(\beta\lambda\), where \(\lambda\) is the RF wavelength, and they are 1.845 m for 162.5 MHz and 0.922 m for 325 MHz, respectively. Their corresponding normalized speeds (\(\beta_{\text{in}}\)) at DTL entrances are 0.0732 and 0.0800.  
The tank (\(D\)) and drift tube (\(d\)) diameters in a DTL have to satisfy the requirement of \(\lambda/4\) post-coupler criteria, which is defined as following [45]:  
\[1.03\geq\frac{[(D-d)/2]}{(\lambda/4)}\geq 0.90 \tag{4}\]  
where \(\lambda\) presents the RF wavelength. Both diameters also are constrained to make the cavity resonate at the desired frequency. For these purposes, the tank (\(D\)) and drift tube (\(d\)) diameters of a conventionally post-coupled DTL operating at 162.5 MHz are determined as (\(D\) = 102 cm, \(d\) = 15 cm). Similarly, in the 325 MHz DTL, they are chosen as (\(D\) = 56 cm, \(d\) = 9 cm). The frequency in each cell is slightly adjusted by changing some of the other geometrical parameters like the drift tube face angle (\(\alpha\)) and gap-to-cell-length ratio (g/\(\beta\lambda\)) (see Figure 7).  
Figure 7: Gap-to-cell-length ratio (**a**) and face angle (**b**) variations as a function of cell number required to achieve the designed resonant frequencies (162.5 MHz design in blue and 325 MHz design in yellow).
## 5 Results and Analysis
### Test Performance
#### 5.1.3 Efficiency  
Given that enhancing the efficacy of the GEP algorithm through the utilization of feature selection was a primary objective of this study, it is imperative to conduct an analysis of the computational time. Figure 5a-c shows the computational time of 30 independent runs on the training set across generations in the MS, MFT, MWT scenario, respectively. The simulation results show that the computational budget of the FS-IGEP algorithm was significantly less than that of the IGEP and GEP algorithms in all mentioned scenarios. This is consistent with our expectation that the rules designed with a limited terminal set with chosen features were relatively short and simple, which reduced the time for fitness evaluation and improved the efficiency of the algorithm. Moreover, it was observed that the IGEP algorithm had higher computational complexity and more computational time than the GEP algorithm in the three scenarios. These observations offered valuable insights regarding the function of VNS. While the VNS algorithm could help GEP to find more competitive rules through the variable neighborhood search, it did not help GEP to reduce the computational budget. This further confirmed the role of feature selection in generating compact and understandable dispatching rules in a feasible computational time.
## 4 Methodology
### Analysis Strategies  
In this section, various approaches for reconstructing TDRS orbits in different scenarios are outlined in Table 1. The methodology involves a comprehensive examination of multiple factors that may affect the orbit's accuracy, including a priori conditions and arc length. As a result of estimating the initial states of the TDRS satellite in these diverse scenarios, a comprehensive assessment of the orbit's error is obtained. This aids in the investigation of the effects of various variables on the study's findings (see Section 5).