esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The current research studied the effects of laser surface hardening treatment on the phase transformation and wear properties of gray cast irons heat treated by austempering or quench-tempering, respectively. Three austempering temperatures of 232 \({}^{\circ}\)C, 288 \({}^{\circ}\)C, and 343 \({}^{\circ}\)C with a constant holding duration of 120 min and three tempering temperatures of 316 \({}^{\circ}\)C, 399 \({}^{\circ}\)C, and 482 \({}^{\circ}\)C with a constant holding duration of 60 min were utilized to prepare austempered and quench-tempered gray cast iron specimens with equivalent macro-hardness values. A ball-on-flat reciprocating wear test configuration was used to investigate the wear resistance of austempered and quench-tempered gray cast iron specimens before and after applying laser surface-hardening treatment. The phase transformation, hardness, mass loss, and worn surfaces were evaluated. There were four zones in the matrix of the laser-hardened austempered gray cast iron. Zone 1 contained ledeburite without the presence of graphite flakes. Zone 2 contained martensite and had a high hardness, which was greater than 67 HRC. Zone 4 was the substrate containing the acicular ferrite and carbon-saturated austenite with a hardness of 41-27 HRC. In Zone 3, the substrate was tempered by the low thermal radiation. For the laser-hardened quench-tempered gray cast iron specimens, three zones were observed beneath the laser-hardened surface. Zone 1 also contained ledeburite, and Zone 2 was full martensite. Zone 3 was the substrate containing the tempered martensite. The tempered martensite became coarse with increasing tempering temperature due to the decomposition of the as-quenched martensite and precipitation of cementite particles. In the wear tests, the gray cast iron specimens without heat treatment had the highest wear loss. The wear performance was improved by applying quench-tempering heat treatment and further enhanced by applying austempering heat treatment. Austempered gray cast iron specimens had lower mass loss than the quench-tempered gray cast iron specimens, which was attributed to the high fracture toughness of acicular ferrite and stable austenite. After utilizing the laser surface hardening treatment, both austempered and quench-tempered gray cast iron specimens had decreased wear loss due to the high surface protection provided by the ledeburitic and martensitic structures with high hardness. In the worn surfaces, it was found that cracks were the dominant wear mechanism. The results of this work have significant value in the future applications of gray cast iron engineering components and provide valuable references for future studies on laser-hardened gray cast iron.**  
**Keywords: gray cast iron; austempering; quench-tempering; laser surface hardening; wear loss**
# Secure Inter-Frame Space Communications for Wireless LANs
###### Abstract  
The internet of things (IoTs) offers a wide range of consumer benefits, from personal portable devices to internet-connected infrastructure. The wireless local area network (WLAN) is one of the potential candidates for IoTs technology to connect billions of smart devices. Long-range WLAN is widely deployed in dense networks as an alternative to cellular networks or satellite internet access because of its low cost, high performance, and existing ecosystem. However, due to the nature of unregulated communications in industrial, scientific, and medical (ISM) bands, WLANs experience interferences from other radios such as radars and frequency hopping devices. Once interference is detected at a WLAN device, the channel is avoided and other channels become crowded. Thus, it degrades network throughput and channel utilization. In this paper, a secure inter-frame space communication system design is proposed for WLANs to share the ISM bands with other radio systems that generate periodic radio signals. The proposed secure inter-frame communication scheme achieves the goal by designing accurate radar detection and secure inter-frame space communication. The simulation results demonstrate that the proposed scheme significantly increases the receiver sensitivity and user datagram protocol throughput.  
secure communications; WLAN; interference; radar +
Footnote †: journal:
## 5 Discussion
### Equivalence Rule Analysis  
To look into this further, we perform an analysis of the improvement of the ETM metric as equivalence rules are added (Figure 7). When only the preprocessing equivalence rules are used, there is already a large decrease in the false negative rate from ESM to ETM in both models on BIRD and the C3 model on Spider due to the fixes in functionality (Section 3.3), while the Super model on Spider had a much smaller decrease because it was imitating Spider's style, which ESM was built for. Without these preprocessing rules, the basic AST matching has much higher false negative rates (shown in Appendix A).  
The overall trend shows that, as expected, each rule we cumulatively add decreases the false negative rate of ETM. However, the equivalence rules did not have an equal impact on the improvement from ESM to ETM. Some models benefited more from certain rules, and others didn't have a reliance on any one rule in particular. Some rules were particularly impactful, while others were almost never utilized. Rule 14 (which entailed unnecessary use of JOIN) was the most important addition in Spider for models that directly used the training set (DAIL, Super, FLM-based) because even the training sets were not consistent in whether the JOIN keywords they used were necessary. Thus, the models that relied on it had similar levels of variation. The models that were more reliant on generating without access to examples from the training set, however, had much more reliance on specific rules, indicating a certain preference for styles of SQL queries. For example, the models based solely on GPT (C3 and DIN) had Rule 6 as the most useful, indicating that GPT has a bias toward generating COUNT (c1) instead of COUNT (*). As more rules are added, the discrepancy in false negatives between the best and worst models decreases, showing that each equivalence rule added reduces bias in ETM.
## 3 Results  
### Single Sensor FVI Quality (Using Resampling)  
Single-sensor (GF2 PAN+GF2 MS) FVI quality was tested according to the strategy in Table 4. The original GF2 has a 1 m PAN and a 4 m MS image, so we resampled the 4 m MS image into 6 m, 8 m, 10 m and 12 m MS images so that our SRR became 1:6, 1:8, 1:10 and 1:12 respectively. We fused the 1 m PAN image with 6 m, 8 m, 10 m and 12 m MS images, and calculated FVIs. To evaluate the quality of FVIs, we need RVI in same resolution (i.e., 1 m), but we have an original 4 m MS image. To get 1 m RVI, we again resampled the original 4 m MS image into a 1 m MS image and calculated the RVI, then we compared and evaluated the quality of FVI with respect to RVI using quality indices. All the FVI quality results are expressed in % so that its precise numeric value can be listed. The result for GS fusion has CC (98.85 to 99.05%), RMSE (10.06 to 13.50%) for SRR 1:6, CC (98.93 to 99.08%), RMSE (12.00 to 13.54%) for SRR 1:8, CC (97.39 to 98.73%), RMSE (10.81 to 14.66%) for SRR 1:10 and CC (98.17 to 98.59%), RMSE (12.77 to 15.78%) for SRR 1:12. Similarly, the detailed result of GS, Ehlers, PC, MIHS and the HPF fusion result for different VIs are listed in Table 5. In GF2-GF2 fusion, for most of the VIs like EVI, NDVI, OSAVI and SAVI; GS fusion has a lower effect on FVI quality (high CC and low RMSE values). However, in SRR, 1:6 and 1:8, for ARVI and GNDVI, MIHS fusion is good. However, for GNDVI and ARVI, GS fusion has a better position after MIHS (Table 5). It also shows the range of CC and RMSE values in different SRR and different fusion algorithms (Table 5).
# Location Selection Methods for Urban Terminal Co-Distribution Centers with Air-Land Collaboration
## 4 Algorithm Design
### Co-Distribution Center Site Selection Method Based on GWO
#### 4.2.5 No-Fly-Zone Handling  
The no-fly zone can be regarded as a set of vertices surrounded by a closed graph of multiple line segments. To determine whether the delivery path of the UAV crosses the no-fly zone, we can calculate the number of directions of the line segments and check whether the straight line connecting the co-distribution center and the customer demand point intersects with the boundary line segments of the no-fly zone.  
As shown in Figure 3, for co-distribution center \(l_{k}(x_{l_{k}},y_{l_{k}})\) and customer demand point \(J_{l}\big{(}x_{l_{l}},y_{l_{l}})\), when determining whether their connecting lines pass through any polygon of the no-fly zone, \(\overset{\rightarrow}{R}=[r_{0}(x_{r_{0}},y_{r_{0}}),r_{1}(x_{r_{1}},y_{r_{1}} ),\cdots,r_{n}(x_{r_{n}},y_{r_{n}})],n\geq 2\), can be transformed into the problem of determining whether the connecting lines intersect with the sides of the polygon. This can be carried out using the number of directions.  
For any line segment in the no-fly zone, calculate the following four directions:  
\[\begin{cases}o_{1}=(\overrightarrow{l_{k}-r_{q}})\times(\overrightarrow{r_{q +1}-r_{q}})\\ o_{2}=(\overrightarrow{l_{l}-r_{q}})\times(\overrightarrow{r_{q+1}-r_{q}})\\ o_{3}=(\overrightarrow{r_{q}-l_{l}})\times(\overrightarrow{l_{k}-l_{l}})\\ o_{4}=(\overrightarrow{r_{q+1}-l_{l}})\times(\overrightarrow{l_{k}-l_{l}}) \end{cases} \tag{28}\]  
The product of the number of directions has the following cases:  
\[\begin{cases}o_{1}\times o_{2}<0\ and\ o_{3}\times o_{4}<0,&\text{intersecting}\\ o_{1}\times o_{2}>0\ and\ o_{3}\times o_{4}>0,&\text{not intersecting}\\ o_{1}\times o_{2}=0\ and\ o_{3}\times o_{4}=0,&\text{patallel or intersecting endpoints}\end{cases} \tag{29}\]  
In Equation (29), if the product of the number of directions is 0, then the two segments share the same line, or the endpoint of one line segment is on the line where the other line segment is located. At this point, we can determine whether the bounding boxes of line segments \(\overrightarrow{r_{q}r_{q+1}}\) and \(\overrightarrow{l_{k}l_{l}}\) overlap on the x- and y-axes using Equations (30) and (31). If these equations are simultaneously satisfied, then the two line segments are partially overlapping, i.e., they intersect.  
\[\max(\min(r_{q}(x),r_{q+1}(x)),\min(l_{k}(x),J_{l}(x)))\leq\min(\max(r_{q}(x), r_{q+1}(x)),\max(l_{k}(x),J_{l}(x))) \tag{30}\]  
Figure 3: No-fly-zone-crossing judgment method based on direction number.  
\[\max(\min(r_{q}(y),r_{q+1}(y)),\min(I_{k}(y),J_{l}(y)))\leq\min(\max(r_{q}(y),r_{q+ 1}(y)),\max(I_{k}(y),J_{l}(y))) \tag{31}\]
# Non-Invasive Hydration Monitoring with a Graphene Dual Sweat Sensor
## 2 Materials and Methods  
An SPE with two working electrodes was functionalized with either a sodium or potassium ion selective membrane using a drop-cast technique. The reference electrode also includes a junction layer to increase its stability. The performance of the reference electrode with the junction layer was compared against that of an external reference electrode probe. Several tests were performed to ascertain the performance of the dual-sensing biosensor. A run-to-run repeatability test was conducted on a sensor to identify the shift between tests on one sensor, and a reproducibility test was performed with five sensors to understand the differences in the reading of the same concentration between different sensors. For the selectivity test, magnesium chloride, ammonium chloride, and calcium chloride were used to indicate how other electrolytes can potentially affect the sensor's performance. Finally, the sensor was tested for real-world application, analyzing sweat samples collected from an individual. The samples were also analyzed with a commercial analyzer and ICP-OES for cross-validation.  
The electrochemical detection method employed to detect the concentrations of sodium and potassium ions in standard solutions and sweat samples comprised open-circuit potentiometry (OCP). The sensor was either immersed in the test solution, or 30 \(\mu\)L of the solution or sweat samples were dispensed on it. The OCP value was recorded for 30 s. To ensure consistent liquid deposition, the Scienion SciFlexarray S12 device was used for all dispensing activities, which included the drop-casting of ion selective membranes.  
Sodium chloride (NaCl), potassium chloride (KCI), ammonium chloride (NH4 Cl), calcium chloride (CaCl2), magnesium chloride (MgCl2), sodium ionophore, valinomycin, dioctyl sebacate (DOS), sodium tetrakis[3,5 bis (trifluoromethylomethyl) phenyl] borate (NaTFPB), polyvinyl chloride (PVC), sodium tetraphenylborate (NaTPB), tetrahydrofuran, Nafion, polyvinyl butyl (PVB), potassium ferricyanide (K3 Fe(CN)6), and hydrochloric acid (HCI) were purchased from Sigma-Aldrich (St. Louis, MO, USA).
# Analysis of Coastal Zone Data of Northern Yantai Collected by Remote Sensing from 1990 to 2018
## 3 Results
### Characteristics of Coastline Changes
#### 3.1.3 Characteristics of the Fractal Dimension of Coastline Variation  
The shape of the coastline is winding and complex. Therefore, the calculation of the fractal dimension of the coastline is helpful to understand the change of the length and shape of the coastline and can provide an important basis for promoting the protection of the coastline and its manageable development and utilization. Based on the coastline information extracted by visual interpretation from 1990 to 2018, the fractal dimension changes of the coastline in the study area were calculated by ArcMap software and the least squares method. In this study, 10 grid lengths (30, 60, 90, 120, 150, 180, 210, 240, 270, and 300 m) were used to cover the coastline to be analyzed, and the fractal dimension of the coastline was calculated. Finally, the changes in the fractal dimension of the coastline in the study area in the past 30 years were obtained (Figure 8).  
Figure 6: Variation of coastline length in different regions from 1990 to 2018.  
The fractal dimension of the study area calculated in this study is close to that of the coastline of Shandong Province studied by [PERSON] [27], and the trend of change is consistent. Generally speaking, the fractal dimension of the coastline in the study area shows an increasing trend with time. However, it can be clearly seen in Figure 7 that before 2015, the coastline fractal dimension increased by 0.0382, but in 2015-2018, the coastline fractal dimension increased by 0.0043. Thus, as people have gradually realized that the destruction of human activities on the oceans has begun to have a serious impact on human survival, the protection of marine resources and careful use of marine resources has become a greater priority [10].  
Figure 7: Coastline change rate in different regions from 1990 to 2018. (**a**) Change of coastline in Laizhou from 1990 to 2018, (**b**) Change of coastline in Zhaoyuan from 1990 to 2018, (**c**) Change of coastline in Longkou from 1990 to 2018, (**d**) Change of coastline in Penglai from 1990 to 2018, (**e**) Change of coastline in Fushan from 1990 to 2018, (**f**) Change of coastline in Zhifu from 1990 to 2018, (**g**) Change of coastline in Laishan from 1990 to 2018, (**h**) Change of coastline in Muping from 1990 to 2018.
## 3 Results and Discussion  
### Effects of Fermentation on the Color and Taste Qualities of MT and FMT  
In order to evaluate the color and taste properties of MT and FMT in a more objective mode, we used the E-tongue and colorimeter for testing. FMT had the typical characteristics of FBT. The surface of FMT was covered with golden spores of _E. cristatum_ (Figure 1A). The color and brightness of the tea infusion could impact consumer choices. The color of the tea deepened with the progress of fermentation, with yellow-green gradually changing to reddish-brown (Figure 1B). As shown in Figure 1C, the L* value of FMT infusion decreased slightly, which represented the brightness of tea infusion decreased after fermentation, and the a* values of FMT infusion were significantly higher than MT infusion, which meant that FMT infusion was redder and MT infusion was greener. The results were consistent with previous reports [16]. The results of the b* value showed that MT infusion was yellower. Theabrownins are the main tea pigments that affect the color of tea infusion. The darker the color of tea infusion, the higher the content of theabrownins [22]. The change in infusion color intuitively indicated the different contents of theabrownins thereof. The fermentation of MT with _E. cristatum_ might increase the contents of theabrownins.  
The taste properties of tea infusions are shown in Figure 1D. Compared to MT, the signal values of umami and saltiness sensors of FMT were obviously increased, whereas the sourness, astringency, and bitterness signals values of FMT were decreased. Moreover, the aftertaste-bitterness and aftertaste-astringency signals were also reduced after fermentation. Previous studies indicated that the taste properties of tea could reflect its chemical profile [22]. Catechins and alkaloids have been reported as the main contributors to the bitter taste and astringency [28], and theabrownins are negatively correlated with bitter taste. During the fermentation process, catechins in MT were oxidized and polymerized into theabrownins. The contents of theabrownins were increased after fermentation; therefore, the bitterness and astringency decreased [29]. Research also showed that theabrownins exhibited a strong umami taste [30]. Moreover, the salty taste of tea was attributed to free  
Figure 1: Sensory quality of MT and FMT. (**A**) The appearances of MT and FMT. (**B**) Tea infusion of MT and FMT. (**C**) Color parameter of tea infusion. (**D**) E-tongue analysis of taste characteristics.  
amino acids and tea polysaccharides [22; 29]. It is worth noting that FMT had a special fungus fragrance. The changes in the taste properties were caused by the fermentation of _E. cristatum_.
## 2 Related Works
While it holds promising benefits, it is important to note that the coordination between TPC and TRC can be a complex process. The HPR-DCC's potential limitations thus lie in this inherent complexity of achieving the optimal balance between power and throughput efficiency. Several factors affect the quality of channel communication, such as vehicle speed, vehicle density, and signal transmission distance. Relying solely on CBR as the foundation for the control algorithm proves inadequate for ensuring equitable communication among all users. This study introduces the incorporation of additional parameters alongside CBR to holistically assess state transitions, guaranteeing a more equitable allocation of resources for vehicles experiencing identical states.
# Profile Design of the Grooved Die and Rolling Force Prediction in the Cold Pilger Rolling Process
## 3 Die Groove Shape Design in the Cold Pilger Rolling Process  
### Design Procedures  
The steps for designing the pilger die groove shape are outlined below.  
**1.** The roll and mandrel groove shapes, which are the essence of pilger die shape design, shall always have a parabolic shape, as shown in Figure 12.  
**2.** Determine the dimensions of the initial material and the final product. The outer diameter of the initial tube, the outer diameter of the pilger rolled product, _R.A._, and principal deformation zone were set at 30 mm, 15.88 mm, 70%, and \(L/2\), respectively. The roll size and working zone intervals(\(L\)) are determined by considering the roller specifications and site conditions.  
**3.** Design the roll shape by applying an exponential function, \(y=e^{ax+b}+c\). Here, exponents \(a\), \(b\), and \(c\) adjust the parabolic radius of the working zone. Thus, the index can be changed according to the design parameters specified in Step 3.  
**4.** Design the mandrel in the same way as the roll shape design.  
**5.** Predict the rolling force in the working zone in the pilger rolling process by applying the rolling force prediction method proposed by Equation (9).  
**6.** Finally, employ the Q factor to evaluate the expected mechanical properties of the final product.
## 4 Lignin Biodegradation and Ligninolytic Enzymes  
L Lignin is degraded by microorganisms under aerobic conditions, although the degradation rate of lignin is much lower than it is for cellulose and hemicellulose. The intact biomass is attacked first by Basidiomycetes fungi [17; 18; 19; 33]. These fungi initiate degradation processes enzymatically to decompose lignin, cellulose, and hemicellulose. The biodegradation of lignin is a heavily oxidative process by indirectly random mechanisms involving several enzymes in the oxidoreductase family [22; 25; 33]. Enzymatic biodegradation is associated with oxidizing agents such as superoxide anion (O\({}_{2}\)-), hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)), hydroxyl radicals (-OH), and singlet oxygen (\({}^{1}\)O\({}_{2}\)) [19; 33]. These reactive compounds break the bonds between the subunit of monolignols and depolymerize lignin gradually within ligninolytic enzyme reactions.  
The main four enzymes in fungus species reported as key biocatalysts for breaking C-C or C-O bonds in heterogeneous and complex structures of lignin are lacase and lacase-like multicopper oxidase, lignin peroxidase (LiP), manganese peroxidase (MnP), and versatile peroxidase (VP). These proteins are secreted from fungi species including mushrooms, penetrate into undecayed wood tissue, and initiate lignin degradation using phenolic compounds as mediators by radical mechanisms [19; 33]. Since the lignin degradation activities in white- and brown-rot fungi, such as basidiomycetes, last several decays, many ligninolytic enzymes have been identified and characterized [17; 18; 19]. In addition to fungi, some bacterial lignin degradation activities have been reported in _Arthobacter_, _Flavobacterium_, _Microoccus_, _Pseudomonas_, _Brucella_, _Orthobactrum_, _Sphingobium_, and _Sphingomonas_ and other related species belonging to _Actinobacteria_, \(\alpha\)- and \(\gamma\)-_Proteobacteria_[34; 35; 36]. Nevertheless, fungal enzymes are most commonly used in lignin degradation. Moreover, the ligninolytic enzymes from mushroom species belonging to phylum Basidiomycare attractive sources for the application of lignin valorization based on chemoenzymatic approaches [17; 19; 37].
# Geolocation and Tracking by TDOA Measurements Based on Space-Air-Ground Integrated Network
## 1 Introduction
Due to the spherical constraint conditions of source position and velocity, previous algorithms are not suitable for jointly estimating the source position and velocity [29; 30] with TDOA measurements only. Therefore, we propose an iterative maximum likelihood estimator for both position and velocity in the scenario of geolocation based on SAGI networks. The remainder of this paper is organized as follows. In Section 2, we develop the CRLB for the source localization in different coordinate systems and analyze the effects of different system errors which contain clock synchronization error, position bias of the observers, elevation bias of the target and non-horizontal velocity of the target. Section 3 presents the maximum likelihood estimator of the source position and velocity. Numerical investigations for three different geolocation scenarios are reported in Section 4. Conclusions are presented in Section 5.