esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Control Strategy Description
### Control Strategy for the Motor
#### 3.1.1 SMC Strategy  
In terms of control theory, SMC is a nonlinear control method with strong immunity and robustness for parameter perturbation and external disturbance, and does not rely on an accurate control system model [31]. The control input is changed for a certain purpose that can force the system trajectory to move on a predetermined sliding surface. As shown in Figure 4, the system trajectory will gradually converge to the sliding surface \(S(x)=0\). Therefore, the SMC strategy is suitable for application in the motor control during the clutch slipping process, as it can avoid the phenomenon of torque interruption and unfavorable drivability.  
Here, the motor torque is selected as the control variable. The motor speed is regarded as the system state variable, and its ideal trajectory \(x_{d}\) can be defined as:  
\[x_{d}=\omega_{\textit{ind}}\dot{\textit{i}}_{\textit{g}}\dot{\textit{i}}_{0} \tag{11}\]  
where \(\omega_{\textit{ind}}\) is the expected wheel speed, and its value is dependent on the vehicle velocity. From Equation (8), the sliding surface with the Lagrange function can be designed as:  
\[S=k(x-x_{d})-L(x,t)=k(x\textit{-}x_{d})-M_{0}\exp(-\alpha t) \tag{12}\]  
where \(k\) denotes the constant with a positive value. When the system is in sliding mode, the equation \(\dot{s}=0\) will be satisfied. The control law \(u_{1}\) can be derived as follows:  
\[u_{1}=J_{m}\ddot{x}_{d}-\frac{J_{m}}{k}M_{0}\alpha\exp(-\alpha t)+b_{m}x-T_{c} -d+\frac{1}{i_{0}i_{g}}\big{[}J_{\textit{in}}\dot{\omega}_{\textit{in}}+b_{ \textit{in}}\omega_{\textit{in}}+T_{L}\big{]}-\chi\text{sgn}(s) \tag{13}\]  
where \(d\) is the disturbance, and it contains the modeling error and parameter perturbation; \(\chi\) is a positive constant. When the state trajectory reaches the sliding mode surface, the system will traverse between both sides of the sliding surface and approach the equilibrium point. During this process, the control variable will generate high-frequency oscillation [32]. In this study, sgn(s) is replaced by the continuous function \(\theta(s)\) to restrain the chattering phenomenon.  
\[\theta(s)=\frac{s}{|s|+\sigma} \tag{14}\]  
where \(\sigma\) is the positive constant with a smaller value.
# Evaluation of Light Pollution in Global Protected Areas from 1992 to 2018
## 5 Discussion  
### The Influence of Policies on Light Pollution  
The dominant decreasing trend of NTL in PAs in Japan and the USA is closely related to protection policies and organizations. The first governmental guideline about light pollution was published in March 1998 in Japan [57]. The Ministry of Environment in Japan has published light pollution control guidelines to help local authorities take efficient control measures and enforce special environmental regulations. For instance, the Okayama prefecture enacted the first regulation in Japan to deal with light pollution to protect space-based radio astronomy observations in 1989. Moreover, in the USA, some organizations have been founded to mitigate the negative impacts of light pollution [60], such as the New England Light Pollution Advisory Group (NELPAG), the International Dark-Sky Association (IDA), and the Dark Skies Advisory Group (DSAG) [61]. With years of hard work, the status of light pollution in Japan and the USA has been mitigated considerably, which is helpful to realize the sustainable development of ecology and environment in/around urban domains.
## 3 Methodology and Mathematical Formulations
### Airflow Physics and Turbulence Modeling
#### 3.3.5 Environment of Wind Direction Methodology  
To meet the requirements for assessing the environmental impact of airflow inside the main ordination hall, we analyzed wind direction data obtained from the Thai Meteorological Department, specifically focusing on wind rose data from Ayutthaya province (Figure 7). The analysis revealed that throughout the year, the wind predominantly flowed from specific directions, which allowed us to identify representative cases. Based on this information, we selected the top-five wind directions for our investigation: south (S = 180\({}^{\circ}\)), south-southeast (SSE = 157.5\({}^{\circ}\)), east (E = 90\({}^{\circ}\)), northeast (NE = 45\({}^{\circ}\)), and north (N = 0\({}^{\circ}\)). These directions represented the primary wind patterns affecting the region and ensured a comprehensive understanding of the airflow dynamics in the Temple. To simplify the simulation and focus on the primary objectives, we assumed a constant wind velocity for all cases, based on measured values from our experimental setup. This approach ensured uniform boundary conditions and facilitated the comparison of flow behavior under similar conditions. Additionally, the atmospheric boundary layer was neglected in the simulation, as the Temple's geometry and airflow within the enclosed hall were the primary factors influencing internal ventilation and including the atmospheric boundary layer would have added complexity without substantially impacting the localized airflow patterns within the Temple that were the focus of this study. These assumptions and selections provided a streamlined yet reliable framework for investigating the environmental impact of flow behavior inside the ordination hall, while maintaining alignment with real-world wind conditions in Ayutthaya province.  
Figure 7: Wind rose diagram for Ayutthaya province based on annual wind direction data from Thai Meteorological Department, 2024.
# Progress in Improving Photovoltaics Longevity
## 4 Results
### PV Degradation Mechanisms
#### 4.1.3 Specific Degradation (Mechanical/Other)  
* **Cell cracking**. Due to the fragile nature of the semiconductors and their small thickness, cell cracking is a frequently reported concern for PV modules. Cracking can occur during the manufacturing process and is mainly due to mechanical stresses induced by handling, lamination, transportation [108], and implementation. It can also be caused by mechanical loads in operating conditions, weather conditions, such as snow and wind, or thermomechanical stresses and temperature cycles, which are related to climate alterations and environmental factors [68]. Cracks obstruct the electrical conductivity in the cell, leading to decreased short circuit current and shunt resistance (Rsh) and increased Rs. [PERSON] et al. divided cell cracks into three main categories, type A, B, and C, according to their severity [69], while [PERSON] et al., in their review, studied the cracks observed in c-Si solar cells [70]. The size, orientation, number, and position of cracks on a PV module can vary, and therefore, their impact on module performance is evaluated as severe or less severe. If cell cracking occurs in the field, other degradation modes, such as PID and delamination, may arise or accelerate. An additional consequence of cell cracking is a non-uniform current distribution across the PV module. Near the cracks, a localized heat accumulation is developed, leading to the formation of hot spots. The forthcoming temperature increase could even cause encapsulant delamination. The detection of these cracks can be conducted either by visual inspection, if the crack has sufficient dimensions, or by applying testing techniques such as electroluminescence (EL) imaging [109], I-V characteristic curves, hot-spot endurance tests [110, 111], or UVF [112] in the case of micro-cracks, which are invisible to the naked eye. * **Interconnect open-circuit failure**. The internal electrical circuit of a PV module consists of solar cell metallization and interconnect wiring. The circuit can face a variety of failures due to construction or processing errors. Weakening of wiring and metallization does not directly affect the module unless the resistance of these components increases significantly. In this case, the degradation of the module, as well as safety issues, are imminent [71, 72]. As soon as the module is set to operation, the internal circuit, along with its joints, are under the influence of thermo-mechanical stresses, which are attributed to an increment in Rs and cause power losses. The extent
## 2 Temporomandibular Joint (TMJ) and Temporomandibular Disorders (TMD)
### The Existence of TMD
#### 2.2.1 Imaging Methods  
Postero-anterior cephalogram is a radiograph of the head taken with the X-ray beam perpendicular to the patient's coronal plane, with the X-ray source behind the head and the film cassette in front of the patient's face [31].  
Panoramic tomogram of the jaw, or panoramic radiography, also called panoramic X-ray, is a two-dimensional scanning dental X-ray that captures the entire mouth in a single image, including the teeth, upper and lower jaws, surrounding structures and tissues. It shows a two-dimensional view of a half-circle from ear to ear [31].  
Lateral cephalogram is an X-ray taken of the side of the face with very accurate positioning, so that various measurements can be made to determine the relationship of the top and bottom jaw (maxilla and mandible), and therefore assess the nature of a patient's bite [32].  
The above X-ray methods have been used to compare between players, and gender- and age-matched controls. Significant morphological differences have been found between violin players and controls [31; 32]. Different parameters have been suggested for characterization and comparison. For instance, in the lateral cephalogram method, six cephalometric parameters are used for comparison [45]:  
1. Maxilla angular position with reference to the base of the skull;
2. Mandible angle position with reference to the base of the skull;
3. Facial type. For this parameter, the facial axis, facial angle, mandibular plane, lower facial height and mandibular arch are used to determine one of three face types--dolichofacial, having a disproportionately long face; mesofacial, having an average shaped face, neither too long nor too wide; brachyfacial, having a disproportionately short face;
4. Sagittal skeletal relation [46] or facial convexity as determined by the anteroposterior relationship of the mandible to the maxilla;
5. Upper incisor inclination in relation to the maxilla upper mandibular incisor inclination;
6. Lower incisor inclination in relation to the mandible.  
Using these parameters, upper string players are found to have a measurable increase in the facial height compared to the matched controls, especially in the right side of the lower face, and an increase in proclination of the upper and lower incisors [31]. This can be considered to result from prolonged playing of the violin, involving increased face muscle activity. Thus, compared to controls, the categories of violin and viola players are shown to have a higher prevalence of brachyfacial type individuals, manifested by smaller facial heights and greater lengths of mandibular corpus [31]. This finding has been further confirmed not only for strings, but also for wind instrument players [32].
## 7 Conclusions  
To maximize the performance of the NOMA system, we propose a resource allocation framework of MDRL-UL that combines deep reinforcement learning and unsupervised learning. The framework treats the resource allocation as a constrained optimization problem and divides it into two sub-problems of channel allocation and power allocation. To resolve the sub-problem of channel allocation, a multi-agent deep reinforcement learning approach is introduced, where each agent corresponds to a subchannel in a cell and can  
Figure 15: (**a**) Impact of the random search strategy on the energy efficiency. (**b**) Impact of the random search strategy on the sum rate.  
allocate the subchannel to two users based on the global channel gain information. When all the channels are allocated, a channel allocation scheme is obtained. With the channel allocation scheme, an unsupervised learning approach using an attention-based neural network is proposed to obtain a power allocation scheme. Simulation results show that the proposed framework of MDRL-UL outperforms other algorithms in terms of energy efficiency and sum rate, and the testing process is more stable than other algorithms, even if the environment is time-varying. In addition, the random search strategy can significantly improve the testing performance of the NOMA system.  
Conceptualization, M.S. and Y.Z.; data curation, M.S., Y.Z., X.H., and J.Z.; formal analysis, M.S., Y.Z., X.H., and J.Z.; investigation, M.S., Y.Z., X.H., and J.Z.; resources, M.S. and Y.Z.; software, M.S. and Y.Z.; supervision, M.S., X.H., and J.Z.; validation, M.S., Y.Z., X.H., and J.Z.; visualization, M.S. and Y.Z.; writing--original draft, M.S. and Y.Z.; writing--review and editing, M.S., Y.Z., X.H., and J.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Provincial Natural Science Foundation of China (No. LH2019F038), the Basic Research Fund for the Provincial Universities in Heilongjiang Province (No. 145409323) and the Postgraduate Innovative Research Project of Qqihar University (No. QUZLTS_CX2024049).  
Not applicable.  
The authors declare no conflict of interest.
# Unmanned Aerial Vehicle Routing Problems: A Literature Review
## 4 Approaches and Domains in UAV Routing in Existing Literature
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Author** & **Approach** & _Objective_ & _Experimental Data_ \\ \hline
[95] Oberlin, Rathinam, and Darbha, & Heterogeneous, Multiple & \
\begin{tabular}{l} 6 UAVs with a minimum turning radius \\ vary uniformly from 100 to 200 meters and \\ the heterogeneous fleet of UAVs \\ \end{tabular} &
\begin{tabular}{l} 6 UAVs with a minimum turning radius \\ vary uniformly from 100 to 200 meters and \\ uniformly generated targets [4, 40] in a \\ square of area \(5\times 5\) km\({}^{2}\) \\ \end{tabular} \\
[78] [PERSON], [PERSON], [PERSON], and [PERSON], 2013 & TSP & \
\begin{tabular}{l} Minimize the total traveling time for the \\ homogeneous fleet of UAVs \\ \end{tabular} &
\begin{tabular}{l} 6 UAV having cruise speed 100 km/h and \\ maximum distance 200 km \\ One aerial vehicle with a cruise speed of \\ 100 m/s covering an operational area of size \\ 20 km \(\times\) 20 km \\ \end{tabular} \\
[97] [PERSON] et al., 2016 & Asymmetric TSP & \
\begin{tabular}{l} Minimize the total traveling time for \\ homogeneous fleet of UAVs \\ \end{tabular} &
\begin{tabular}{l} 2 UAVs in a zone of size \(30\times 30\) units \\ where targets are located randomly and 50 \\ instances for each problem size with 10-40 targets \\ \end{tabular} \\
[98] [PERSON], [PERSON], and [PERSON], 2016 & \begin{tabular}{l} Time-Dependent TSP in \\ Controlled Airspace \\ (TDTSPPCA) \\ Dynamic Traveling \\ Repairperson Problem \\ (DTRP) \\ \end{tabular} & \
\begin{tabular}{l} Minimize the total traveling time and \\ the holding time over mission \\ waypoints for homogeneous fleet of \\ UAVs \\ \end{tabular} &
\begin{tabular}{l} 5 scenarios 10-40 mission waypoints, \\ randomly selected among the navigation \\ points located within a circle having center \\ in Milano Linate and ray of 80 NM \\ Simulated with a Single UAV with \\ randomly generated targets \\ \end{tabular} \\
[72] [PERSON], [PERSON], and [PERSON], 2013 & Multi-vehicle TSP & Maximize the expected target coverage & 21-day simulation of the [PERSON]’s (1997) \\  & & [100] notional Nari dataset \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Overview of traveling salesman problem (TSP) approaches used in UAV routing.
###### Abstract  
In this paper the influence of in situ local heat treatment performed by additional stitches on the weldability of high-strength low-alloy (HSLA) S355J2C+N steel was tested. The investigated steel is characterized by high susceptibility to cold cracking. It is necessary to find a method to improve the quality of welded joints. The local heat treatment was applied as an effect of bead-on plate welding made on the face of a Tekken test joint. The specimens were made by the use of covered electrodes in the water environment. For testing weldability, Tekken test specimens were made. Then, the different number of the pad welds with different overlapping were laid on the face of the tested welds. Non-destructive (NDT) visual and penetrant tests were undertaken. During the NDT, imperfections like shape mistakes and spatters were found. Then, metallographic macro- and microscopic testing were performed. The macroscopic observations proved that water environment can generate imperfections like cracking and pores. However, for specimens with additional stitches the number of imperfections decreased. Microscopic tests proved that the proposed technique affected the structure of the heat-affected zone (HAZ). The specimens without the application of additional stitches are characterized by brittle bainitic and martensitic structure. Specimens, in which the additional stitches were applied, contain tempered martensite, fine ferrite and fine pearlite in their HAZ. It was also observed that the number of cracks decreased for in situ local heat-treatment specimens. The final step was Vickers HV10 hardness measurement. These measurements confirmed previous results. The heat from additional stitches affected the steel by significantly decreasing the hardness by 80-100 HV10. The results of experiments showed that the heat from pad welds provided microstructural changes in heat-affected zones and a decrease in the susceptibility to cold cracking, which results in improvement in the weldability of HSLA steel in wet welding conditions.  
**Keywords:** underwater wet welding; high-strength low-alloy steel; cold cracking; bead-on plate welding; metallographic testing +
Footnote †: journal: Applied Physics Letters
# Contribution of Gray and White Matter Abnormalities to Cognitive Impairment in Multiple Sclerosis
## 1 Introduction  
Multiple sclerosis (MS) is a demyelination disease affecting the central nervous system (CNS), typically characterized by motor and sensory dysfunction, and optic neuritis. Previous studies reported that 40%-70% of MS patients also exhibit cognitive impairments (CI), primarily in learning, memory, information processing speed, and executive functions [1].  
CI can occur in the early stages of the disease course, even among newly diagnosed patients, and typically has severe detrimental impacts on patients' lives [2; 3]. Previous studies hypothesized that CI is associated with the extent of white matter (WM) lesion load in MS patients [4], based on the volume of T2 (transverse relaxation time) lesions visible on conventional MR imaging. However, several studies reported a weak relationship between WM damage and cognitive changes [5; 6; 7]. Later, several studies using diffusion tensor imaging (DTI) reported that widespread subtle pathological changes in WM microstructures (normal appearing WM; NAWM) exhibited a significant correlation with CI, whereas T2-hyperintense lesions of MS did not [8]. In addition, researchers proposed that fractional anisotropy (FA) in the uncinate fasciculus was associated with processing speed and spatial memory [9], and [PERSON] et al. found that WM integrity was related to cognition in CI-MS patients [10].  
Extensive gray matter (GM) loss has been widely reported in patients with MS, including cortical and deep GM. Asymmetric left-sided loss of GM in the left fronto-temporal cortex and precuneus, as well as bilateral anterior cingulate gyrus and caudate nuclei atrophy, were reported in relapsing-remitting MS (RRMS) [11]. Moreover, an association between decreased GM volume and cognitive impairment was also reported. Several studies of MS patients have revealed a relationship between CI and deep GM atrophy in a range of areas, including the thalamus, hippocampus, caudate nucleus, globus pallidus, and basal ganglia, based on voxel-based morphometric (VBM) analysis, which allows quantification of GM volumes in vivo [12; 13; 14]. However, [PERSON] et al. reported that only WM integrity was significantly different between CI and cognitive preservation (CP) patients, while no difference in regional GM volume was found [10]. However, both RRMS and secondary progressive MS (SPMS) patients were enrolled in [PERSON]'s study [10]. Previous research indicated that cognition in SPMS patients was more frequently and severely impaired than among RRMS patients [15]. Thus, the inclusion of different disease subtypes of MS may have affected the results.  
The neural mechanisms underlying CI in MS remain controversial. The discrepancy between previous results may be related to the different types of MS included in study samples. Thus, the current study aimed to further explore the neural basis of cognitive impairment by distinguishing CI and CP groups of RRMS patients according to cognitive ability, and examining them with a combination of DTI and VBM techniques.
## 2 Materials and Methods
### Architecture  
The architecture of our working pattern, as depicted in Figure 7 is basically a group of four modules linearly connected. The fact that it is cloud based not only allows us to communicate with the cellular network operation support system (OSS), but also, one can use each module individually for another reasons besides frequency planning.  
Each module represents a processing service, while between each module will be a storage service, to save any inputs/outputs. We implemented four different processes:  
* **Cell coverage estimation module**: Responsible for estimating a cell power around its location.
* **Cell grid intersections module**: Responsible for understanding which cell coverage intersects.
* **World map creation module**: Responsible for creating a world map, which is a data structure containing a set of pixels identified by their hashes--in this case, Geohashes. Each pixel will have an undefined number of pairs of cell/power.
* **Planning module**: Responsible for applying a linear optimization and its defined rules to the data generated by the previous modules.  
The four steps of the pattern are detailed in the next sections.