esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
The findings of the experiments allow the drawing of the following conclusions:  
* Under standard CVCC test conditions, an increase in the proportion of n-hexane in the blend with canola oil resulted in slight changes in the values of ID, CD and MPR parameters.
* The values of the derived cetane number for the blends analyzed were similar to those for pure canola oil and significantly lower in relation to the derived cetane number for typical diesel fuel.
* Engine test results showed a significant effect of n-hexane addition on lowering the auto-ignition delay angle.  
These test results complement studies referring to the combustion of alternative fuels for diesel engines. The results presented in the article confirm that in order to evaluate the suitability of fuels and their self-ignition properties, it is necessary to conduct tests on a modern diesel engine with split injection. This is due, among other things, to the variable conditions in the engine combustion chamber and the different fuel injection timing with split pilot injection and main injection, which has a significant impact on the combustion process.  
Conceptualization, A.J., R.L. and H.K.; methodology, A.J., R.L., P.S. and H.K.; formal analysis, A.J., R.L., P.S. and H.K.; investigation, A.J., R.L., P.S. and H.K.; resources, A.J., R.L., H.K. and P.S.; data curation, A.J. and H.K.; writing--original draft preparation, A.J., R.L., H.K. and P.S.; writing--review and editing, A.J., R.L., H.K. and P.S.; visualization, A.J. and H.K.; supervision, A.J., R.L. and H.K. All authors have read and agreed to the published version of the manuscript.  
The research leading to these results has received funding from the commissioned task entitled \"VIA CARPATIA Universities of Technology Network named after the President of the Republic of Poland [PERSON]\" contract no. MEiN/2022/DPI/2578, action entitled \"In the neighborhood--inter-university research internships and study visits\".  
Not applicable.  
Data Availability Statement: Data supporting this study are included within the article.  
The authors declare no conflict of interest.  
Figure 15: Values of maximum combustion pressure, \(p_{\text{max}}\), for diesel engine operated with crankshaft speed 3000 rpm.
## 2 Materials and Methods
### Monitoring of Selected Parameters
#### 2.2.1 Monitoring of Pressure, Flow and Temperature  
Author [10] deals with the design of laboratory test equipment for testing hydraulic circuit elements and hydraulic fluids in his scientific monograph. The measuring technology, which is part of the hydraulic circuit, consists of a Hydac ETS 4144-A000 temperature sensor, a Hydac EVS 3110-1 flow sensor, and a Hydac HDA 3744-A-400-000 pressure sensor, which are connected to the HMG 3010 recording unit. Thanks to this, it is possible to simultaneously measure and record all three quantities. The recording unit allows the measurement of the flow in the range of 6-60 dm\({}^{3}\) min\({}^{-1}\), 15-300 dm\({}^{3}\) min\({}^{-1}\), and 40-600 dm\({}^{3}\) min\({}^{-1}\), the pressure in the range of 40 MPa, and the temperature to 100 \({}^{\circ}\)C (Figure 2).
## 4 Experimental Results and Analysis
### Parameter Analysis
#### 4.4.4 The Dimension of the Subspace d after Dimensionality Reduction  
In order to evaluate the impact of subspace dimension d on the dimensionality reduction performance, based on the a priori knowledge, the variation range of subspace dimension d is set at [5; 10; 15; \(\ldots\), 45]. Figure 9 shows the dimensionality reduction results obtained after selecting different subspace dimensions d on the two datasets. In Figure 9, it can be seen that among all of the algorithms, the classification accuracy of each type of algorithm increases continuously and then stabilizes as the dimension of subspace d increases. Among the algorithms, the overall classification accuracy of the algorithms in this paper is optimal. In a certain range, as the dimension of subspace d keeps increasing, the effective spatial-spectral feature information in the subspace keeps increasing, meaning that the classification accuracy of the algorithm gradually increases. However, because enough rich and discriminative features have been captured when the subspace dimension d increases to a fixed value and continues to increase, the classification accuracy of the algorithm does not continue to increase.
## 2 Related Work
### Diagnosis Method Analysis  
In previous research, motor fault diagnosis has relied on monitoring stator current or voltage harmonics to identify the frequency components indicative of various faults. Time-domain, frequency-domain, and time-frequency-domain analyses have been commonly used for this purpose. A test motor for stator ITSCF is constructed, where a control system is implemented using DSP, and ITSCF monitoring is conducted based on the analysis of second-order harmonics in the \(q\)-axis current [12]. Reference [13] evaluates the current and voltage characteristics of PMSM's ITSCF and applies Linear Discriminant Analysis (LDA) to improve diagnostic accuracy, distinguishing between different fault types such as static eccentricity and ITSCF, as well as estimating their severity. Additionally, zero-sequence voltage component (ZSVC) detection is another common method for fault diagnosis [14]. However, it requires a connection at the neutral point of the stator winding and is susceptible to disturbances from motor drives or other types of faults [15], increasing the difficulty of motor fault diagnosis.  
In addition to the aforementioned methods, error diagnosis can also be performed using linear filtering techniques, such as the Kalman filter, which develops an appropriate model by identifying parameters specifically designed to indicate stator faults [16]. Alternatively, the Vold-Kalman filtering order tracking algorithm [17] can be used to track specific harmonics over a wide range of machine speeds and under different load conditions. In addition, some studies employ wavelet transform analysis, such as using complex wavelet analysis to examine radial [18], axial, and tangential vibrations for diagnostic purposes. For instance, ref. [19] utilizes the dual tree complex wavelet transform (DTCWT) for feature extraction, making it meaningful to model Probabilistic Neural Networks (PNNs) with wavelet methods. These approaches are often based on specific filters to isolate frequency bands that match the fault characteristic frequencies.
## 2 Materials and Methods
### CNCs Characterization
#### 2.3.6 Transmission Electron Microscopy (TEM) Analysis  
The MCC and CNCs samples' morphology, size distribution, and average particle diameter were analyzed using transmission electron microscopy (Phillips CM12, thermo scientific, Netherlands) at an accelerating voltage of 120 V. Whereby a small amount of sample (<1 mg) was dissolved in ethanol. Then the solution was sonicated for 15 min. After that, the solution was dropped onto the TEM grid and was allowed to dry at room temperature before characterization. The size of the nanoparticle was measured by the utilization of ImageJ software v1.8.0 based on extraction from TEM micrographs.
## 3 Results and Discussions
### Polyphenols
#### 3.1.3 Ultrasound Effect on Almond Skins Microstructure  
Almond skin microstructure after ultrasonication was investigated using SEM (Figures 4 and 5). As revealed in Figure 4, SEM observations provided information about the destruction of skin layers. Figure 4D showed that ultrasound effects are progressive. Thus, two main ones were detected: fragmentation and cell erosion. These effects are as follows: (1) fragmentation of all almond skin layers, (2) cell erosion: elimination of parenchyma cells, cuticle & upper aleurome cell walls, (3) cell erosion: elimination of parenchyma cells and cuticle + partial elimination of upper aleurome cell walls, (4) Cell erosion and elimination of parenchyma cells; almond skin layers are described in [PERSON] et al. 2010 paper [12]. Further SEM images are illustrated in Figure 5 showing primary (\(<\) 0.5 \(\upmu\)m) and secondary effects (\(>\) 1 \(\upmu\)m), also called sonoporation, in addition to erosion of cell walls after 20 min of sonication. In fact, the primary effects constitute zones of nucleation, acting by themselves as nucleation sites,  
Figure 3: TPC (expressed as eq mg Naringenin/g almonds) kinetics with and without ultrasound.  
Data are the means \(\pm\) SD, n = 3. Ultrasound (yellow) versus silent (orange).  
Figure 2: (**A**) Pareto graphic for TPC; (**B**) Pareto graphic SST.  
As a result, the alterations caused by ultrasound on the almond skin cells explain the presence of cellular content (polyphenols) that have been extracted. Increasing treatment time effects positively TPC extraction yields. Theses latter were investigated and analyzed using Ultra-High-Performance Liquid Chromatography (UPLC).
# The Challenges of Advanced CMOS Process from 2D to 3D
## 4 Dopant Implantation in CMOS
### Challenge of Ion Implantation in 3D Structure Devices  
In 2012, 3D tri-gate transistors came into mass production by Intel on its 22 nm micro-processor. Such a design brings a lower junction leakage and better short channel effect control compared to traditional planar structure. However, in the meantime, the transformation from planar to 3D put forward higher requirements for the fabrication process such as implantation, the conformal doping of source/drain areas and lower fin damage by implantation [112].
# TRAP: A Three-Way Handshake Server for TCP Connection Establishment
## 2 Background
### Netfilter  
Netfilter is a Linux kernel networking filter framework, usually compiled as a Loadable Kernel Module (LKM), offering various hooks in the network layer of the packet manipulation. Kernel  
Figure 3: TCP header format (reference source: RFC-793) [6].  
Figure 2: Illustration of SYN flood attacks.  
modules are pieces of code that can be loaded and unloaded into the kernel upon demand [13]. It also provides various functions, like altering the packet's source or destination Media Access Control (MAC) address and filtering based on certain criteria like TCP port and redirecting it to a new IP address.  
Netfilter provides a set of tables, which indicates the traversal of packets throughout the kernel space and the user space. Inside these tables are sets of pre-defined chains, which ultimately contain sets of rules. By using the user-space program iptables, a user is freely to modify these rules to control the behavior of how network packets are processed by a Linux kernel [14].  
Netfilter provides following hook points for a packet as depicted in Figure 4:  
1. Having passed simple sanity checks (i.e., not truncated, IP checksum, etc.), a network packet is passed to the NF_INET_PRE_ROUTING [1] hook.
2. Next, it enters the routing decision to determine if the packet is for the local machine. If it is true, then it is passed to the NF_INET_LOCAL_IN [2] hook, before going to the user-space program.
3. If the packet is for another interface or device, it is passed to the NF_INET_FORWARD [3] hook.
4. The packet then passes a final hook, the NF_INET_POST_ROUTING [4] hook, before being put on the wire again.
5. For any outgoing packet from the user-space program, NF_INET_LOCAL_OUT [5] hook is called first, before going to the routing decision.  
A kernel module can register to listen at any of these hooks. When a packet arrives at the specified hook, the kernel module gets the raw packet buffer, and is free to manipulate the packet's content or header.  
The return value can be one of the five value:  
1. NF_ACCEPT: continue the packet traversal as normal.
2. NF_DROP: drop the packet and free the buffer.
3. NF_STOLEN: stop the traversal but not freeing the memory, the kernel module will take control afterwards.
4. NF_QUEUE: queue the packet.
5. NF_REPEAT: call this hook again.
## 6 Patient Transfer Logistics
### MQTT Protocol  
The message queuing telemetry transport (MQTT) is a client server publish/subscribe messaging transport protocol. It is lightweight, open, simple and easily implementable. MQTT is ideal for use in IoT applications that require a small code footprint and/or network bandwidth as a premium. The protocol runs over network protocols that provide ordered, lossless, bi-directional connections, e.g., TCP/IP. In the MQTT protocol there is a broker and a receiver. The broker has 'topics' through which a recipient of data generated by a sender is determined. To receive the data, a receiver subscribes to a particular topic. A receiver receives the data published by any sender with that particular topic [92]. In the proposed system, the topic will be the route number/name, such that the published location data from buses will contain this information. The location data will comprise the current latitude and longitude of a bus and will be published at a frequency of 5 s. To ensure the scalability of the system, the MQTT brokers can be clustered as in Figure 8. Each of the brokers maintains the same topic list. In case of one broker crushing, another broker automatically handles the requests, balancing within themselves. The advantage of clustering is the assured system availability. For each route number, the location data is received via MQTT and stored in the database. The broker can be directly modified to write to the database upon reception of data or an MQTT client can be created to perform this function.
# Characterizing Growing Season Length of Subtropical Coniferous Forests with a Phenological Model
## 4 Discussion
### Management Implications  
Prescribed fire is a widespread practice in the southeastern region of the United States, especially on lands where restoration is a primary management goal [35]. Fire resulted in moderate delays of the SOS, which were stronger in the site that had higher water availability; however, fire did not impact other subsequent phenology parameters. Our results also suggested a slightly amplified association between SOS and weather variables, such as radiation and air temperature, during years of prescribed fire. However, these impacts may be mitigated by projected changes in climate, which include global warming trends associated with earlier onset of SOS [32]. Perhaps a larger concern for land managers is the interaction of prescribed fire with drought conditions, which may advance the EOS and also become more common under a future climate [35]. However, a longer time series is needed to quantify these interactions and rigorously address this question, as well as study other management techniques, such as thinning, given underlying natural variability in climatic conditions and the expectation that this variance will increase with climate change.
# Detection and Attribution of Greening and Land Degradation of Dryland Areas in China and America
## 3 Results
### Dryland Areas in China
#### 3.1.2 Dominant Factor Distribution  
To investigate the dominant factors and synergistic effects of driving factors, we applied the ternary map of CO\({}_{2}\)(red), LU (green) and CC (blue). It can be seen in the Figure 5 that northeast China is mainly dominated by CO\({}_{2}\) fertilization effects. For the northwest, more regions are mainly controlled by CC. Many studies suggest that the northwest of China is undergoing a trend of wetter and warmer from the 1980s. [PERSON] et al. (2002) found that the climate of arid regions in Northwest China are undergoing the shift from warm-dry to warm-wet. This research has aroused widespread concern ([PERSON] et al., 2002). Additionally, this change of climate is improving the environment of the northwest of China. Climate change has occurred longer than the 30 yr climatology and has influenced the ecological vegetation visibly ([PERSON] et al., 2002). Meanwhile, most color of the northwest is purple, which means CO\({}_{2}\) also has non-negligible effects. LU (green) shows a main effect in the middle of Inner Mongolia.  
Figure 4: (**a**) Observed change of vegetation growth in Chinese dryland area. Yellow means decrease in NDVI\({}_{m}\) and green means increase. Dotted areas suggest the change is significant (\(\kappa_{FDR}\) = 0.10). Areas that have large uncertainties are masked in white. (**b**) The change of NDVI attributed to CO\({}_{2}\). (**c**) The change of NDVI attributed to LU. (**d**) The change of NDVI attributed to CC. (**e**) The change of NDVI attributed to CV.
## 2 Materials and Methods
### 3D Printing of the Phantom  
The STL files were sliced into layers using IdeaMaker (Raise3D, Irvine, CA, USA) for fused deposition modelling (FDM) printing and ChituBox (Shenzhen Chitu Systems Co., Ltd., Shenzhen, China) for digital light curing resin (DLP) printing. Parameters such as printing material, infill density, and support structures were configured in the software (Table 1). FDM printing was performed using a Raise3D N2 Plus 3D printer (Raise3D, Irvine, CA, USA) with the materials listed in Table 1. DLP printing was performed on an Anycubic Photon S 3D DLP printer (Shenzhen Anycubic Technology Co., Ltd., Shenzhen, China). The accuracy of these printers in fabricating patient-specific phantoms has been reported previously [29]. The printers are calibrated annually to maintain printing resolution and accuracy, with the FDM printer achieving an XY resolution of 12.5 microns and the DLP printer achieving an XY resolution of 47 microns. The prepared sliced files were transferred to the respective printers for 3D printing. Support structures added during the slicing process were manually removed post-printing.  
Figure 1: 3D Volume-rendered model created by segmenting the patient’s CT images using 3D Slicer Front view (**A**) and side view (**B**) of the model with skin, subcutaneous fat, muscle, and thoracic bones removed. (**C**) Lungs removed to display the lung vessels and lung nodules. (**D**) Front view of the outer skin layer.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{**Nozzle**} & \multicolumn{2}{c}{**Bed**} & \multirow{2}{*}{**Printing Time**} & \multirow{2}{*}{**Weight**} & \multirow{2}{*}{**Printing Cost**} \\ \cline{2-2} \cline{5-6}  & **Temperature** & & & & **(h)** & **(g)** & **Printing Cost** \\ \hline Lung Blood Vessels & - & - & 20 & - & 183.6 \\ \hline Bone & 215 & 60 & 220 & 1680 & 57.1 \\ \hline Lung Nodules & 215 & 60 & 3.5 & 22 & 0.6 \\ \hline Pulmonary Venous System & 215 & 60 & 3 & 26 & 0.7 \\ \hline Skin & 235 & 90 & 98 & 552 & 15 \\ \hline Oesophagus & 215 & 60 & 2.5 & 32 & 0.9 \\ \hline Stomach & 215 & 60 & 12 & 280 & 7.6 \\ \hline Trachea & 215 & 60 & 1.5 & 22 & 0.6 \\ \hline Heart & 235 & 90 & 22 & 440 & 12 \\ \hline Left Deep Back Muscle & 235 & 90 & 23 & 263 & 7.2 \\ \hline Right Deep Back Muscle & 235 & 90 & 21.5 & 243 & 6.6 \\ \hline Lung & 215 & 60 & 95 & 1105 & 30.1 \\ \hline Thyroid & 215 & 60 & 1 & 15 & 0.4 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Printing parameters and cost of phantom.
## 4 Results and Discussion
### Clustering Results Analysis
#### 4.3.1 Comparative Analysis of Intercity Trip Chains from a Temporal Perspective  
Table 5 shows the most frequently clustering centers of intercity trip chains between Beijing and Tianjin in May 2019 and May 2021. In the Beijing to Tianjin direction, the age distribution of travelers changed from 25-29 years old in 2019 to 19-24 years in 2021. Due to the COVID-19 pandemic in 2021, companies had strict control over personnel travel, resulting in an increased proportion of travel by students who were relatively less controlled. The departure time shifted from 8 AM-9 AM to 7 AM-8 AM. Young people who aimed to travel may have had the tendency to depart relatively early. The waiting time at the departure hub increased from 20-25 min to 30-35 min [66]. In 2021, COVID-19 epidemic prevention and control measures were still ongoing. Railway stations may have had increased security checks and health code verification processes, resulting in passengers needing to arrive early and waiting times being extended. In the Tianjin to Beijing direction, the age distribution of travelers shifted from 25-29 years in 2019 to 30-34 years in 2021. Perhaps due to the pandemic, it had become more difficult for young people to find jobs, and the main force of travel had shifted to middle-aged people. The departure times changed from 10 AM-11 AM to 12 PM-1 PM. The group aged 30 to 34 may have generally enjoyed flexible working hours, avoiding rush hour and choosing to depart at noon to avoid traffic pressure. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Time** & **Direction** & **Optimal Value of K** & **Maximum Silhouette Coefficient** \\ \hline \multirow{4}{*}{May 2019} & Beijing–Tianjin & 5 & 0.204 \\  & Tianjin–Beijing & 5 & 0.201 \\  & Beijing–Shijiazhuang & 4 & 0.197 \\  & Shijiazhuang–Beijing & 4 & 0.218 \\  & Tianjin–Shijiazhuang & 4 & 0.234 \\  & Shijiazhuang–Tianjin & 3 & 0.233 \\ \hline \multirow{4}{*}{May 2021} & Beijing–Tianjin & 4 & 0.192 \\  & Tianjin–Beijing & 5 & 0.216 \\  & Beijing–Shijiazhuang & 6 & 0.188 \\  & Shijiazhuang-Beijing & 4 & 0.213 \\  & Tianjin–Shijiazhuang & 3 & 0.251 \\  & Shijiazhuang–Tianjin & 4 & 0.251 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The optimal number of clusters for intercity trip chains.
## 3 Results and Discussion
### Underlying Mechanism--Correlation to the Flow Resistance
Therefore, the effect of SGS on the area ratio correlates well with its effect on the trans-stenosis flow resistance, suggesting that the area ratio is a key parameter, to determine the effect of SGS on the flow resistance. Specifically, when the glottal area is significantly smaller than the SGS area (SGS severity below 75%), the SGS generates nearly no additional flow resistance, and the vocal fold dynamics are little affected. By increasing  
Figure 13: (**a**) The cycle-averaged trans-glottis, trans-stenosis, and total flow resistance versus SGS severity. (**b**) The ratio of the cycle-averaged glottal area to the SGS area versus SGS severity. the SGS severity beyond 75%, the area ratio starts to increase rapidly, and the trans-stenosis flow resistance increases accordingly. It is noticed that, when the SGS severity is 96%, the area ratio reaches 0.62, meaning that the SGS area is only less than two times the cycle-averaged glottal area, but the trans-stenosis resistance is only 0.14 of the trans-glottis resistance. When the SGS severity reaches 99%, the area ratio becomes 2.14, meaning that the SGS area is only half of the cycle-averaged glottal area, but the trans-stenosis resistance is about the same as the trans-glottis resistance. The reason is that very high trans-glottis flow resistance is generated during the early glottal opening and late glottal closing when the glottal area is very small. Finally, we compare the flow resistances in the cases with different SGS locations. As shown in Figure 14, the SGS location has negligible effects on flow resistance. The 2.1 and 3.13 cm cases have nearly the same flow resistance, with reductions of 0.8% of the total flow resistance and 1.2% of the trans-glottis resistance for the 90% area reduction case and 0.4% of the total flow resistance and 0.9% of the trans-glottis resistance for the 96% area reduction case. This also nicely corresponds to the observation that the SGS location has nearly no effect on voice production within that stenosis-glottis distance interval.