esa-sceva/satcom-chunk-collection huggingface dataset:
# On-Machine Precision Form Truing and In-Situ Measurement of Resin-Bonded Spherical Diamond Wheel
## 1 Introduction
The profile graph showed that the achieved form-truing error can be less than 2 \(\upmu\)m under the optimal process parameters. More research on precision form truing of spherical diamond wheel is of great significance to further improve the grinding surface form accuracy and reduce the machining allowance in the subsequent polishing process. The in-situ measurements of the dimension and form accuracies of the grinding wheels are the critical process of on-machine form truing. The common measurement methods of grinding wheel profile include contact measurement, image acquisition method, graphite copy method, and so on [21,22]. The detection probe in contact measurement is highly liable to be damaged since sharp diamond abrasive particles are randomly distributed on the grinding wheel surface, which could substantially affect the detection result [23]. The image acquisition and graphite copy methods are not suitable for profile measurement of grinding wheels with large-size and complex surface. Chromatic confocal displacement sensor and laser displacement sensor are commonly used in non-contact measurement systems. Chromatic confocal displacement sensor is based on wavelength displacement modulation technique, and possesses a sub-micron meter accuracy over a millimeter order range [24]. Chromatic confocal profilometer has been widely used in science investigation and industry fields for its high precision and great measurement range [25]. [PERSON] et al. [26] integrated a chromatic confocal measurement probe with an ultra-precision turning machine, and on-machine measurement with nanometer-level accuracy was achieved. Laser scan micrometer is based on the triangulation measurement principle, which is characterized by good stability, large measurement range, and high efficiency [27]. It has become widely available in measurements of dimension, surface profile, and even 3D shape [28, 29, 30]. However, the measurement accuracy is affected by the geometrical and optical conditions [31]. For non-contact measurement of grinding wheel profile accuracy, the sensor needs to meet the requirements of precision, range, and working distance at the same time. In this paper, the coarse-grained diamond roller is applied to perform precision form truing of the resin-bonded spherical diamond wheel. The non-contact in-situ measurement method of the form-truing error and the alignment error are proposed and verified by using a laser scan micrometer.
## 4 Data Analysis
### Development of Structural Models
#### 4.3.3 Exploratory Power of Structural Model  
Overall, the findings show that the measuring model has high convergent validity and discriminant validity, in addition to the reliability of the individual items. The model also indicates the overall impact made by any dependent variable involved in the analysis on the dependent variable. The observed variation should be explained with high significance by the model's dependent variable, and therefore it strengthens the significance of each of the barriers involved in analysis. The PLS approach yielded an R\({}^{2}\) that was equivalent to that obtained using conventional regression [6; 82]. The sum of all possible permutations was represented in R\({}^{2}\). The explanation for this is found in the independent variables of the dependent variable. An increase in R-Square value is always responsible for increasing the predictive power of a structural model developed in analysis. Figure 8 presents all path coefficient values for each barrier involved in each construct. When accounting for corrections, the R\({}^{2}\) values for the IOT obstacles were 0.893. The study's findings suggested that the scope of the IoT implementation was considerable, and that these models might shed light on the challenges faced by the Malaysian construction industry when attempting to apply the IoT. They came to the conclusion that the IoT constructs might be responsible for 90% of the IoT barrier mitigation. The modification of R\({}^{2}\) may be used to determine whether the absence of an independent construct in a model significantly alters the DV when testing hypotheses about the model's fit. This measure is known statistically as the \(f^{2}\), or effect size, and is computed by following Equation (2).  
\[f^{2}=(\text{R}^{2}\;\text{included}-\text{R}^{2}\;\text{excluded})/(1-\text{ R}^{2}\;\text{excluded}) \tag{2}\]  
The following criteria for assessing effect size are suggested: \(f^{2}\) = 0.010 (Small), \(f^{2}\) = 0.140 (Moderate), and \(f^{2}\) = 0.340 (High). The effect size is increasing as the value  
Figure 8: Path analysis of structural model.  
of f increases. The observed effect size is at a moderate level, which provides a major modification to the research model and provides effective insights regarding the implementation barriers of the IoT.
# Remote Sensing-Based Multilayer Perceptron Model for Grassland Above-Ground Biomass Estimation
## 4 Research Methods  
The following flowchart provides a comprehensive overview of the research methodology employed in this study (Figure 2). It systematically outlines the steps from data acquisition to the final result analysis, facilitating a clear understanding of the overall research process.  
To achieve accurate inversion of above-ground biomass in Xiwuzhumuqin Banner grasslands, this study was carried out through three main stages: feature variable extraction,  
Figure 2: Technology roadmap.  
model construction and optimization, and accuracy evaluation. The specific methods are described as follows.
## 2 Materials and Methods  
### Study Area and Data Collection  
The experiment was carried out within two different commercial olive groves (cultivar 'Coratina'), both in southeastern Italy (province of Bari--Apulia region), and both consist of mature, fully productive trees. Field A, covering 1.60 ha, was located in Bitonto (41\({}^{\circ}\) 7\({}^{\prime}\) N, 16\({}^{\circ}\) 39\({}^{\prime}\) E; 124 m a.s.l.) and trained under irrigated conditions (Table 1). Field B was 3.80 ha, situated in Palombaio (41\({}^{\circ}\) 2\({}^{\prime}\) N, 16\({}^{\circ}\) 35\({}^{\prime}\) E; 221 m a.s.l.), where it was trained under rainfed conditions (Figure 1). Except for irrigation, the other farming practices were the same for both fields, including pruning and soil management. The pH of the irrigation water was 6.65, while the EC was 1.01 dS/m. The study area is characterized by a Mediterranean climate with hot summers and mild winters; based on the Koppen and Geiger classification, the climate is categorized as CFa. The hottest months are July and August, with maximum temperatures usually above 29 \({}^{\circ}\)C; precipitations are mostly concentrated in autumn and winter, with a yearly average rainfall of 645 mm [35]. Specific weather conditions of the two fields for the investigated season were provided by the Apulia region [36]. The soil is classified as clay loam (USDA classification); the soil pH was 7.18 and 6.97, while the soil EC was 0.21 dS/m and 0.19 dS/m for field A and field B, respectively. The most common pests in the study area were the Olive Fruit Fly (_Bactrocera oleae_, R.), the Olive Moth (_Prays oleae_, B.), and the Verticillium wilt (_Verticillium dahliae_, K.).  
In this study, one time per month, from June to September 2024 (June 27 th, July 17 th, August 29 th, and September 28 th) and in synchronism with Sentinel-2A overpass, \(\text{Fv}^{\prime}/\text{Fm}^{\prime}\) was measured using an OS30p Pulse Modulated Chlorophyll Fluorometer (Optic Sciences, Inc., Hudson, NH, USA) with a leaf-clip holder for plant leaves in light adaptation conditions [37]. The measurements were conducted on 18 random trees per field (\(n=36\) per date). For each sampled tree, we measured three replicate measurements and used their average for analysis (Figure 1). Field sampling was carried out between 11.00 and 13.00 (hr solar). Significant differences of \(\text{Fv}^{\prime}/\text{Fm}^{\prime}\) between both fields were determined through the Wilcoxon test (\(\alpha=0.05\)).
# Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases
## 2 Related Work  
### Lightweight Cryptographic Protocols and IoT  
A substantial body of research has addressed security and privacy challenges in the IoT, with a particular focus on the feasibility of lightweight cryptographic primitives. [PERSON] et al. (2012) recommend Elliptic Curve Cryptography (ECC) and symmetric ciphers as suitable solutions for resource-constrained IoT networks. In line with this, our work employs ECC for key exchange and symmetric cryptography for data encryption between MQTT entities. However, the study does not integrate or analyze the role of application-layer protocols such as MQTT or CoAP. [PERSON] et al. (2013) compare classic algorithms (e.g., RSA, AES, and Triple DES), but their focus remains on cryptographic performance, without reference to communication protocols. In contrast, our study couples lightweight cryptographic mechanisms with a specific application-layer communication protocol.  
Other works, such as [PERSON] et al. (2014), examine the practicality of public-key cryptography in Wireless Sensor Networks (WSNs), while [PERSON] et al. (2015) evaluate Attribute-Based Encryption (ABE) for IoT access control. Furthermore, our earlier works ([PERSON] et al., 2016; [PERSON] et al., 2017) explore certificateless Identity-Based Cryptography (IBC) in embedded deployment. Nevertheless, all these contributions overlook the integration of cryptographic schemes within secure IoT messaging protocols. Addressing this gap, our work evaluates TLS-secured MQTT, experimentally characterizing the cost of integrating standard TLS 1.3 into real IoT platforms, such as Raspberry Pi \(4B\) boards.
## Data and Methods
### Data Preprocessing
#### 2.2.2 Landsat Images and Preprocessing  
We processed all available surface reflectance products of Landsat (Table 1) accessible from the Google Earth Engine (GEE) which is an open and powerful platform for using Landsat image processing ([[https://developers.google.com/earth-engine/datasets/catalog](https://developers.google.com/earth-engine/datasets/catalog)]([https://developers.google.com/earth-engine/datasets/catalog](https://developers.google.com/earth-engine/datasets/catalog))) such as atmospheric correction. The international mainstream satellite remote sensing data, including Landsat, Sentine and MODIS, was stored on the Google Earth Engine Cloud Platform. The Google Earth Engine can store, manage, and process massive amounts of remote sensing data, providing a technical means for global or regional land use classification. Some built-up lands, high biomass corn fields, and barren lands which have a complex structure and rough land surface that may bring about high PALSAR backscattering coefficients similar to the forests will produce the commission error. Therefore, we generated an annual maximum NDVI (INDVImax, hereinafter) map to exclude the potential disturbance from buildings which also have backscattering coefficients [26; 39]. Poor quality of observations which were caused by the shadows and clouds were removed based on CFmask [40; 41] and metadata because the CFmask algorithm can provide cloud, cloud shadow, and snow mask for Landsat TM/ETM+ images. Pixels that are cloudless and not in ETM + scan line zoning were selected as good quality observations.  
\[\mathrm{NDVI}\ =\ (\mathrm{NIR-RED})/(\mathrm{NIR+RED}), \tag{4}\]  
\[\mathrm{NDVImax}\ =\ \mathrm{Max}(\mathrm{NDVI1},\mathrm{NDVI2},\mathrm{NDVI3}, \ldots\mathrm{NDVIn}), \tag{5}\]  
where NIR and RED are the land surface reflectance values of red (RED, 630-690 nm) and near-infrared (NIR, 760-900 nm) spectral bands of Landsat TM/ETM+/OLI image, respectively.
# Static Compressive Properties of Polypropylene Fiber Foam Concrete with Concave Hexagonal Unit Cell
## 1 Introduction
The negative Poisson's ratio structure and the influence of material property parameters on the energy absorption effect of composite structure have been considered comprehensively, and the negative Poisson's ratio structure has been combined with the design of composite energy-absorbing materials. For example, [PERSON] et al. [21] modeled a sandwich panel consisting of two metal panels and a three-dimensional isotropic foam core with a negative Poisson's ratio, and the one with the smallest Poisson's ratio had the highest blast resistance, as shown through finite element simulations. [PERSON] et al. [22] used sandwich composite specimens prepared from 3D printed dot matrix cores and glass/epoxy composite sheets. They performed low-velocity impact tests, and found that the location of the impact point affected the impact mechanical response and energy absorption capacity of the sandwich panels. [PERSON] et al. [23] proposed a combined mold of laminated carbon fiber-reinforced plastic negative Poisson's ratio unit structure specimens, which were made by the high-temperature hot pressing process, and experimentally verified the potential engineering application of the CFRP + NPRS series in lightweight vibration damping and energy absorption. [PERSON] et al. [24] put forward that a negative Poisson's ratio filled structure can be obtained by filling the negative Poisson's ratio structure with foam concrete with different densities, and the test showed that an appropriate amount of foam concrete filling significantly improved the energy absorption capacity of the negative Poisson's ratio structure. [PERSON] et al. [25] introduced the negative Poisson's ratio structure into concrete for the purpose of improving the energy storage modulus and the blast absorption capacity of concrete. This paper studies the influence of polypropylene fiber content on the peak stress, failure mode, deformation capacity, and energy absorption capacity of foam concrete with concave hexagonal unit cells. The concave hexagonal unit cells were obtained by pouring foam concrete into self-made molds. Static compression tests were carried out on concave hexagonal unit cells and cube specimens. Herein, the Poisson's ratio, failure mode, and energy absorption capacity of different concave hexagonal unit cells are compared, and the energy absorption principle of concave hexagonal unit cells in fiber foam concrete is discussed.
###### Abstract  
The cathode flow field design of a proton exchange membrane (PEM) fuel cell is essential to fuel cell performance, which directly affects the uniformity of reactant distribution and the ability to remove water. In this paper, the single serpentine flow field design on the cathode side is optimized to reach a high performance by controlling the rib groove rate (the ratio of the number of grooved ribs to the number of total ribs). The rib groove starts from the inlet side and then evenly distributes over the ribs. Four rib groove rates are selected in this study, namely, 0, 1/3, 2/3, and 1. A three-dimensional PEM fuel cell model is used to analyze the output performance of the fuel cell. The results indicate that the rib groove design has a significant effect on the distribution of oxygen at the cathode side, the density of the membrane current, the concentration of water vapor under the rib, and the fuel cell output performance. The output performance of the fuel cell improves with the increased rib groove rate. However, when the rib groove rate is greater than 2/3, its impact on the overall performance of the fuel cell begins to slow down. The PEM fuel cells exhibit the best output performance when the rib groove rate is 1.  
**Keywords:** proton exchange membrane fuel cell; cathode flow field design; rib groove; COMSOL Multiphysics; current and power density curves
## 4 Experimental Results
### The ROV Is Facing Away from the Current  
In this scenario, the ROV moved along the vector direction \([-15,\,-15,\,-60]\) while the ocean current flowed orthogonally to its trajectory. To establish a \(0^{\circ}\) angle between the current and the ROV's path, the current vector was defined as \([1,\,-1,\,0]\), which lay entirely within the horizontal _xy_-plane. This configuration corresponded to an azimuth  
Figure 10: When the ROV moves side-on to the ocean current.  
Figure 9: When the ROV moves facing the ocean current.  
angle \(\beta_{c}=-3\pi/4\) and an elevation angle \(\alpha_{c}\approx 2.34\) rad, representing a purely horizontal flow with no vertical component.  
The ROV started from the initial position [0, 0, \(-\)40] and navigated toward the target position [\(-\)15, \(-\)15, \(-\)60], with the target yaw set to 0\({}^{\circ}\). This setup facilitated the investigation of how lateral ocean currents and resulting wake flow influenced the vehicle's maneuvering and trajectory correction. The simulation results for this perpendicular interaction are presented in Figure 11.  
In this sample, the ROV started at [0, 0, \(-\)40] and finally reached [\(-\)14.9869, \(-\)14.7836, \(-\)60.148]. The resulting Euclidean distance between the two points was approximately 0.6924 m. The absolute deviations in each direction were 0.3805 m along the \(x\)-axis, 0.5783 m along the \(y\)-axis, and 0.0334 m along the \(z\)-axis.  
Table 1 compares three scenarios of the ROV approach relative to the ocean current. The ROV exhibited the highest efficiency when aligned with the current, achieving the target with minimal deviation. In contrast, lateral approaches resulted in moderate sideways drift, while moving against the current demanded substantial corrective actions and caused trajectory delays. These findings highlight the critical role of orientation in path planning within dynamic underwater environments.  
Such insights are valuable for developing adaptive control strategies for ROVs operating under varying flow conditions, ensuring robust performance despite changing current directions [26; 27].  
\begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Scenario** & **Start Point** & **Final Position** & **Distance (m)** & **Error (\%)** \\ \hline facing directly toward the current & & [\(-\)14.8114, \(-\)14.5905, \(-\)60.039] & 0.4525 & 15\% \\ \hline side-on to the current & [0, 0, \(-\)40] & [\(-\)14.6195, \(-\)14.4217, \(-\)60.0334] & 0.8
## 3 Results and Discussion  
### Strain-Time Curve  
The creep strain-time graphs for both current and braced wooden cross-arm configurations at each point of main members are presented in Figure 9. Based on the curves, it can be seen that creep pattern are divided into three phases which are instantaneous deformation,  
Figure 8: Schematic diagram of Burger model.  
primary and secondary creeps. As expected in the early experiment, the highest creep strain is located at y3, which at the centre of cross-arm's main member beams. This was probably due to the each of main members of the structure experienced compression from both ends when the force is exerted at free end of the cross-arm. As mentioned by [PERSON] (2017) [40], a simple interconnected members of a structure without bracing systems would induce inelastic behaviour, which tends to experience buckling at the centre of the structure arm. This established that the operational cross-arm would experience buckling action due to external forces from the dead weigh at the end of the structure.  
In the meantime, the findings also depicts the creep strain patterns have two distinct stages: elastic and viscoelastic stages. However, the transition period from the elastic period to the viscoelastic phase was extended for the current design cross-arm (red arrow's location shown in Figure 9). This established that the braced wooden cross-arm provide the structure become more stable in viscoelastic stage.  
Based on Figure 9b,d, the curves in both left and right main members of braced design cross-arm exhibit a similar pattern. The similar creep strain pattern for both left and right wooden cross-arm is probably due to the addition of bracing system provide better structural integrity. Subsequently, a symmetrical shape and deformation pattern would permit during the cross-arm service to grasp the power cables and insulators, which would reduce any potential sudden failure of the structure after years of service.  
Figure 9: Creep strain-time curves for current wooden timber cross-arm for (**a**) left and (**c**) right; braced wooden timber cross-arm for left (**b**) and right (**d**) main member.  
Besides that, the installation of the brace arms reduces the creep strain along the operation time. This can be observed where the instantaneous deformation of the braced design cross-arm are noticeably less than current design cross-arm at any points along the individual member. For instance, at the middle of cross-arm (y3), the finding displays that the creep strain value for the current wooden cross-arm was higher than the braced wooden cross-arm. At this point of view, the inclusion of bracing system in the structure would significantly provide higher creep resistant performance by reduced the creep strain approximately 31%. This outcomes is tally with a research conducted by [PERSON] et al. [41]. They mentioned that the improvement of mechanical response of a structure is significant enhanced as the addition of bracing members could resist lateral forces which subsequently avoid from buckling.
###### Abstract
Most previous studies indicate variations in the WUE response to drought on an annual scale [23] and have shown a significant discrepancy in different regions and ecosystems. Based on climate divisions, there is a negative correlation between the WUE and drought in arid regions, while in humid regions, WUE has both positive and negative correlations with drought [7]. According to geographic divisions, drought has an enhancement effect on WUE in Southwest China [23]. The WUE is negatively correlated with drought in Northeast China and Central Inner Mongolia, while it is positively correlated with drought in Central China [6]. Based on different ecosystems, droughts have lagged effects on the WUEs of shrubs and sparse vegetation, presenting marked differences compared with forest ecosystems [24]. Current research on the WUE is quite successful at both time and spatial scales. However, to date, few studies in the world have focused on the correlation between CWUE and drought during drought events in the HHHP. Based on meteorological station data, remote sensing data, and other data, this study used the Cubist algorithm to establish the monthly integrated surface drought index (mISDI) dataset in the HHHP and used the run theory to identify drought events. The correlation analysis between drought events and the CWUE (CWUE = GPP/ET) based on mISDI in the HHHP from 2001 to 2020 will help farmers to establish climate-induced disaster risk awareness, develop advanced vegetation strategies based on empirical knowledge and reduce the damage caused by abrupt environmental changes. The results of this study may assure food production and reduce the impact of drought disasters by analyzing the temporal and spatial trends of droughts and their impact on the CWUE.