esa-sceva/satcom-chunk-collection huggingface dataset:
# Mixed Reality Enhanced User Interactive Path Planning for Omnidirectional Mobile Robot
## 4 Kinematics of the Omnidirectional Mobile Robot  
In this paper, the OMR structure is shown in the Figure 3. It is composed of four Mecanum wheels whose rotational axis is at a 45-degree angle to the robot body, and each pair of diagonal wheels has the same direction [34]. This design allows the mobile robot to move in all directions.  
According to the structure in Figure 3, the velocities of the four wheels of the mobile robot in the x-axis and y-axis can be expressed as follows [35]:  
\[v_{x1}=\frac{v_{1}}{\sqrt{2}}+v_{w1}=v_{rx}+l_{1}\cdot\omega \tag{1}\]  
\[v_{y1}=\frac{v_{1}}{\sqrt{2}}=v_{ry}-l_{2}\cdot\omega \tag{2}\]  
\[v_{x2}=\frac{v_{2}}{\sqrt{2}}+v_{w2}=v_{rx}-l_{1}\cdot\omega \tag{3}\]  
\[v_{y2}=-\frac{v_{2}}{\sqrt{2}}=v_{ry}-l_{2}\cdot\omega \tag{4}\]  
\[v_{x3}=\frac{v_{3}}{\sqrt{2}}+v_{w3}=v_{rx}+l_{1}\cdot\omega \tag{5}\]  
Figure 3: Model of the omnidirectional mobile robot.  
Figure 2: The mixed reality device HoloLens.  
\[v_{y\beta}=-\frac{v_{3}}{\sqrt{2}}=v_{ry}+l_{2}\cdot\omega \tag{6}\]  
\[v_{x4}=\frac{v_{4}}{\sqrt{2}}+v_{wn4}=v_{rx}-l_{1}\cdot\omega \tag{7}\]  
\[v_{y4}=\frac{v_{4}}{\sqrt{2}}=v_{ry}+l_{2}\cdot\omega \tag{8}\]  
where \(v_{xn}\) and \(v_{yn}\) are the velocities of the four wheels on the x-axis and y-axis, respectively; \(v_{n}\) is the velocity at which the wheels turn; and \(v_{wn}\) is the velocity of the wheels relative to the environmental coordinate system (\(n=(1,2,3,4)\), represents the number of wheels). \(v_{rx}\) and \(v_{ry}\) are the overall velocities of the mobile robot; \(\omega\) is the angular velocity of the whole robot.  
By solving Equations (1)-(8), the relationship between the wheels' velocities with the overall velocity and angular velocity of the mobile robot can be obtained. The relevant formula is as follows:  
\[\left[\begin{array}{c}v_{w1}\\ v_{w2}\\ v_{w3}\\ v_{w4}\end{array}\right]=\left[\begin{array}{ccc}1&-1&l_{1}+l_{2}\\ 1&1&-(l_{1}+l_{2})\\ 1&1&l_{1}+l_{2}\\ 1&-1&-(l_{1}+l_{2})\end{array}\right]\left[\begin{array}{c}v_{rx}\\ v_{ry}\\ \omega\end{array}\right] \tag{9}\]  
According to Equation (9), the inverse kinematics equal of the OMR can be expressed as:  
\[\left[\begin{array}{c}v_{x}\\ v_{y}\\ \omega\end{array}\right]=J\cdot\left[\begin{array}{c}v_{w1}\\ v_{w2}\\ v_{w3}\\ v_{w4}\end{array}\right] \tag{10}\]  
The Jacobian Matrix J is:  
\[J=\frac{1}{4}\cdot\left[\begin{array}{ccc}1&1&1&1\\ -1&1&1&-1\\ \frac{1}{(l_{1}+l_{2})}&-\frac{1}{(l_{1}+l_{2})}&\frac{1}{(l_{1}+l_{2})}&- \frac{1}{(l_{1}+l_{2})}\end{array}\right] \tag{11}\]  
The full rank Jacobian Matrix J shows that the mobile robot can move in all directions.
## 3 Heavy Metal Removal Approaches
### Biosorption
Moreover, the biosorption mechanism of Cr (VI) is a complex phenomenon in which the Cr (VI) ion attaches to the biosorbent surface and is subsequently reduced to less toxic Cr (III) [80]. The process of reducing and adsorbing Cr (VI) proceeds in a sequence of three distinct stages, which have been observed and studied extensively. The initial stage involves the binding of chromate ions, which are negatively charged, to positively charged functional groups [81]. This binding process is an essential step in the overall reduction-cum-adsorption process, as it enables the subsequent stages to take place. In the second stage, Cr (VI) is reduced to Cr (III) by functional groups, which donate electrons to facilitate the reduction process [82]. This stage is crucial in the sense that it marks a significant transformation in the chemical composition of the system, as Cr (VI) is converted to Cr (III). The ultimate stage in the process entails the discharge of Cr (III) ions into the solution, while the residual Cr (III) ions are retained by the adsorbent surface, which is adorned with negatively charged functional groups. This phase is a fundamental requisite in guaranteeing the consummation of the adsorption process and the total occupation of the Cr (III) ions on the adsorbent surface [83]. It is noteworthy that this process represents a complex interplay of various chemical and physical phenomena, which require further investigation and elucidation [84]. Table 1, which is effectively and efficiently utilized as a visual representation of data, illustrates, in a comprehensive manner, the inherent capabilities of different biosorbents to uptake heavy metal ions. The microbial biomasses, as previously mentioned, have been identified as remarkably efficient biosorbents when it comes to removing heavy metal ions. Additionally, it is noteworthy that the biosorption phenomenon can be conducted on immobilized biomass. This includes bacterial biomass that exists on a solid surface, fungal biomass located on a supportive medium, or deceased biomass that has been immobilized on another supportive surface [92]. Immobilization serves to not only augment the stiffness, potency, and longevity of the biosorbent but also ultimately to enrich the biosorption capacity. The existence of a diverse array of matrices has made immobilization possible, with matrices such as alginate and polyurethane being extensively employed for this purpose [92,93]. Moreover, it is noteworthy to emphasize that a multitude of microbial and plant biomasses have been employed for immobilization on the aforementioned matrices [91,94]. To illustrate, the biomass of _Chorella homosphaera_ has been successfully immobilized on matrices containing sodium alginate [95].
## 5 Conclusions  
In this paper, an RC (reinforced concrete) isolated continuous girder bridge was selected as the research object. In order to reasonably evaluate the seismic performance of the isolated bridge, considering the randomness of the near-fault ground motion and structural parameters, an incremental dynamic analysis of the bridge structure under different failure states was carried out. With the copula function method, the joint distribution function of components was obtained, and the seismic fragility curve of the bridge system, considering the influence of multiple components and their demand correlation, was established, which was compared with the first-order limit reliability theory model. The main conclusions are as follows.  
Compared with the traditional method, the copula function method has obvious advantages. It can not only overcome the limitation of the assumption that the seismic demands obey the lognormal distribution but can also describe the nonlinear correlation between the seismic demands on the bridge components, especially the tail correlation. This new method eliminates the limitation that only the Pearson correlation coefficient can describe linear correlation and thus simplifies the modeling process of the multivariate joint probability distribution function of the bridge structure. It provides a new model for the seismic vulnerability analysis of complex (multiple) bridge structures.  
The fragility curve of bridge structures obtained with the copula method was located between the two limit values obtained with the first-order method, but there was still a large gap, which indicated that the limit error caused by the traditional fragility analysis method was relatively large. The calculation results showed that the failure probability of the whole bridge structure analyzed with the copula method had a smaller probability interval, and that the evaluation based on the copula method was more reasonable, safer, and more reliable, which also proved the calculation efficiency and superiority of the copula method.  
Furthermore, in this study, the seismic fragility analysis of the isolated continuous girder bridge showed that the failure probability of the isolation bearing was relatively large and was more likely to occur as a limit state failure, while the failure probability of the pier was relatively small. Therefore, in the seismic design of this kind of isolated bridge structure, the seismic capacity of the isolation bearing should be the main consideration. At the same time, this study also showed that the probability of different failure states in the continuous bridge structure was greatly reduced with the seismic isolation scheme, which can greatly improve the seismic performance of the bridge.  
Conceptualization, investigation and writing, Q.L.; supervision, C.Y.; formal analysis, investigation and methodology, C.Y. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Natural Scientific Research Foundation of Fujian, China (Grant No. 2021J01856).  
Not applicable.  
The authors declare no conflict of interest.
## 4 Results and Discussion
### Acoustic Characteristics of Different Configurations
#### 4.2.2 Spectral Characteristics of SPL
Figure 12: Sound pressure level of the monitoring point along the x-direction. panhead, with the noise spectrum corresponding to SPL of 69.75 and 52.09 dB, respectively. When the pantograph diversion strategies are ameliorated, the main-order and second-order frequency disappears. In Figure 14b,c, it can be observed that the aerodynamic noise spectrum of the lower arm rod and the base frame in all three cases exhibits a broad frequency characteristic, and there is no clear primary frequency. Moreover, after the installation of the pantograph fairing, the SPL of the lower arm rod and the base frame with energy less than 300 Hz is mainly raised, while the SPL with energy above 1000 Hz is reduced. Clearly, the noise reduction effect of the fairing of the pantograph on the base frame is more salient, which may be due to the fact that the fairing shields part of the incoming flow in the base frame. However, the sinking platform does not have a strong effect on the noise spectrum characteristics of the lower arm rod and the base frame. Figure 14: Noise spectra of different parts. (**a**) Panhead; (**b**) lower arm rod; (**c**) base frame. Figure 13: The \(1/3\) octave band frequency spectra of aerodynamic noise at the standard observer points of maximum sound pressure level (case 1: 6 th monitoring point; case 2: 6 th monitoring point; case 3: 4 th monitoring point). Next, the characteristics of aerodynamic noise at a wide range of frequencies are analyzed. Figure 15 shows the sound source intensity distribution of different cases at 40, 1600, and 8000 Hz, respectively. As can be seen in Figure 15, when there is no pantograph fairing, the sound source intensity in the pantograph area is more uniformly distributed at high frequencies, and the difference in distribution is larger at low and medium frequencies. Meanwhile, the sound source intensity is significantly greater at a frequency of 1600 Hz. In addition, at a low frequency, the high sound source intensity mainly occurs around the camera for case 1, while it appears on the rear surface of the fairing for case 3. A similar distribution can be observed at a medium frequency, although the base frame contributes significantly greatly. Overall, the installation of the pantograph fairing remarkably changed the distribution of the sound source intensity at low and medium frequencies, but had less effect on the distribution at high frequencies.
###### Abstract  
Spatter formation at melt pool swellings at the keyhole rear wall is a major issue for laser deep penetration welding at speeds beyond 8 m/min. A gas nozzle directed towards the keyhole, that supplies shielding gas locally, is advantageous in reducing spatter formation due to its simple utilization. However, the relationship between local gas flow, laser spot size, and the resulting effects on spatter formation at high welding speeds up to 16 m/min are not yet fully understood. _Methods._ The high-alloy steel AISI 304 (1.4301/X5 CrNi18-10) was welded with laser spot sizes of 300 \(\upmu\)m and 600 \(\upmu\)m while using a specially designed gas nozzle directed to the keyhole. Constant welding depth was ensured by Optical Coherence Tomography (OCT). Spatter formation was evaluated by precision weighing of samples. Subsequent processing of high-speed images was used to evaluate spatter quantity, size, and velocity. The keyhole oscillation was determined by Fast Fourier Transform (FFT) analysis. Tracking the formation of melt pool swellings at the keyhole rear wall provided information on the upward melt flow velocity. _Results._ The local gas flow enabled a significant reduction in the number of spatters and loss of mass for both laser spot sizes and indicated an effect on surface tension by shielding the processing zone from the ambient atmosphere. The laser spot size affected the upward melt flow velocity and spatter velocity.  
laser beam welding; laser spot size; spatter formation; local gas flow; Optical Coherence Tomography; frequency analysis; keyhole geometry Article
# Load Transfer Efficiency Based on Structural Deflection Assessment of the Precast Floating Track
## 2 Precast Floating Panel  
This study focuses on a new type of precast floating panel developed by the Korea Railroad Research Institute (KRRI). Figure 3 shows a 3D-modeling and the cross section of this type of panel. The dimensions of the panel were 4.925 m (length) \(\times\) 2.4 m (width) \(\times\) 0.3 m (thickness). Rail and the slab panel was connected by fastening device (System 300-1, KR type).  
The fabrication process of the precast floating panel is shown in Figure 4. Rebars D19 (longitudinal direction) and D13 (horizontal direction) were installed in a formwork, after completing the formwork, concrete was poured (Figure 4b) and the curing process was carried out (Figure 4c) until the compressive strength of concrete (_f'c_) reached 45 MPa (Figure 4d). This type of track can be installed in a limited amount of time after the existing ballasted track is removed. This design has six anti-vibration devices that are attached to the bottom of one of the precast track panels. The panel is composed of assembly blocks that are connected by concrete crossbeams. The panels are transported to the construction sites for rapid installation and are assembled to a fixed track height by adjusting the base, which is aligned in advance with the upper part of the station slab. The precast floating slab panels are installed sequentially on a flat plane using a hydraulic jack, and a high-precision survey is used to make linear corrections. The anti-vibration isolator uses a wedge-type engineering plastic block to attenuate the vibrations in the vertical direction, through frictional resistance. This provides restorative forces through the coil springs, which are arranged in the lateral and vertical directions to insulate against any vibrations.  
Figure 3: (**a**) Three-dimensional (3D)-modeling of the precast floating panel, and (**b**) cross-section of precast floating panel.
# Bioactive Compounds from Herbal Medicine Targeting Multiple Myeloma
## 3 Flavonoids in Multiple Myeloma
### Apigentin  
Apigenin is a non-mutagenic yellow crystalline solid flavonoid [108]. This is a flavonoid found in oranges, grapefruit, grapefruit, celery, parsley, onions, wheat germ, and chamomile (Figure 1) [109; 110; 111].  
\begin{table}
\begin{tabular}{l l} \hline \hline \multicolumn{1}{c}{**Class of Flavonoids**} & \multicolumn{1}{c}{**Biocative Compounds**} \\ \hline Flavones & Apigenin, Baicalein, Crysoeriol, Luteolin, Scutellarin, Wogonin \\ \hline Flavonols & Fisetin, Myricetin, Quercetin \\ \hline Flavanols & Epigallocatehin-3-gallate \\ \hline Isoflavonones & Daidzin, Genistein \\ \hline \multirow{2}{*}{Chalcones} & Butein, Cardamonin, Isobavachalcone, \\  & Isoliquiritigenin, Xanthohumol \\ \hline \hline \multicolumn{1}{c}{Prenylated flavonoids} & Bavachin, Icaritin, Icariside II \\ \hline \hline \end{tabular}
\end{table}
Table 1: Flavonoids involved in the management of multiple myeloma.  
The anti-cancer activity of apigenin was first reported in 1986 by [PERSON] et al. [112].  
Apigenin can be used in cancer prevention due to its antioxidant, anti-inflammatory, antigenotoxic effects and its ability to neutralize free radicals [113; 114]. Apigenin inhibited prostate, gastrointestinal, bladder, ovarian, colon, and neck cancers, as well as other forms of tumors by inhibiting cancer cell proliferation [115; 116; 117; 118]. Apigenin had a cytotoxic effect on cancer cells [119] and showed proteasome inhibitory activities [120].  
[PERSON] et al. [121] evaluated the cytotoxic activity of apigenin in several human MM cell lines, such as MOLP-8, NCI-H929, RPMI-8226, KMS-11, KMS-12 BM, OPM-2, 1-363, AMO-I, and JJN-3. Apigenin inhibited cell growth of MM cell lines in a dose-dependent manner, while NCIH-929 cells showed increased sensitivity to apigenin compared to other MM cells. Apigenin induced apoptosis, blocked cell cycle in G2/M phase, increased intracellular ROS, and promoted autophagy in NCI-H929 cells. Induction of autophagy by apigenin was demonstrated by upregulation of the expression of Beclin1 and LC3B-II markers.  
[PERSON] et al. [122] reported cytotoxic effects of apigenin on both MM cell lines and primary MM cells, but not on normal blood mononuclear cells (PBMCs). Apigenin inhibited casein kinase 2 (CK2) activity and blocked the cell cycle in G2/M phase in U266 and RPMI 8226 cells. Additionally, it induced apoptosis and downregulated the expression of anti-apoptotic proteins in MM cells, respectively, such as Mcl-1, XIAP, Bcl-xL, Bcl-2, and survivin. Apigenin inhibited the activation of STAT3, ERK, AKT and NF-kB. Apigenin decreased Cdc37 phosphorylation, disassociated Hsp90/Cdc37/kinase complexes and degraded Hsp90/Cdc37 client proteins. Apigenin induced degradation of multiple kinases, including Src, RIP1, Raf-1, AKT and cyclin dependent kinase 4 (CDK4). In CD138+ primary MM cells, apigenin inhibited CK2 activity, and depleted Cdc37 client kinases.
## 4 Results  
A total of 24 patients underwent the bilateral insertion of palatal miniscrews, resulting in 48 screws analyzed. All measurements were performed on postoperative CBCT images and compared with the virtual insertion plan. The analysis revealed measurable discrepancies between the planned and actual positions; the mean angular deviation (MAD) between the planned and actual screw axes was 2.95\({}^{\circ}\)\(\pm\) 1.13\({}^{\circ}\), with a range of 0.9\({}^{\circ}\) to 5.19\({}^{\circ}\) (Figure 8). In terms of linear discrepancies, the mean horizontal deviation at the head level (Hor Head Dmax) was 0.30 mm \(\pm\) 0.16 mm, whereas at the tip level (Hor Tip Dmax), it increased to 0.66 mm \(\pm\) 0.21 mm; similarly, vertical deviations of 0.35 mm \(\pm\) 0.21 mm at the head and 0.67 mm \(\pm\) 0.67 mm at the tip were observed, confirming that deviations increase with the distance from the surgical guide, since the tip is geometrically farther from the fixed reference point. A paired t-test analysis showed that the discrepancies between the head and tip on the horizontal plane were significant on both the right and left sides (\(p\) < 0.05), indicating a systematic translation of the tip relative to the planned trajectory, while no significant differences were found between the right and left sides at the tip or the head, justifying the aggregation of bilateral data. Furthermore, the vertical discrepancy between the head and tip (VHD vs. VTD) was also significant (\(p\) < 0.05), indicating a three-dimensional inclination in the deviation. [PERSON]'s correlation analysis did not reveal statistically significant relationships between angular deviation (MAD) and linear discrepancies, either horizontal or vertical, at the head or tip levels, except for a weak but significant correlation between VHD and MAD (R < 0.05), suggesting that greater angular deviation may be associated with a slight increase in vertical head discrepancy.  
Despite the observed deviations, the data confirm that the use of customized surgical guides produced by 3D printing, combined with standardized protocols and the potential development of more rigid guiding systems to minimize mechanical tolerance, allows for a general improvement in accuracy compared to conventional techniques.  
\begin{table}
\begin{tabular}{l c} \hline \multicolumn{1}{c}{**T-Paired Test**} & \multicolumn{1}{c}{\(p\)**-Value**} \\ \hline hor head dx vs. hor tip dx & \(p\) < 0.05 \\ hor head sx vs. hor tip sx & \(p\) < 0.05 \\ hor head dx vs. hor head sx & NS \\ hor tip dx vs. hor tip sx & NS \\ VHD vs. VTD & \(p\) < 0.05 \\ HTDmax vs. HHDmax & NS \\ \hline
**Spearman test** & **R-value** \\ \hline HTDmax and MAD & NS \\ HHDmax and MAD & NS \\ VTD and MAD & NS \\ VHD and MAD & R < 0.05 \\ \hline \end{tabular}
\end{table}
Table 2: Inferential statistics. \(t\)-test Comparison between linear discrepancies with \(p\) = 0.05 and Spearman’s R = 0.05.
## 4 Future Research and Directions
It could include investigating mineral concentrations at the nano level present in living organisms and the robotic integration of SEM tools with AI and ML for studying the mineral compositions on other planets and stars. Another idea is the integration of SEM with other material characterization tools, such as XRD, and by incorporating robotics, AI, and ML, the process could be automated to a further extent. One major challenge among several in this research direction is the proper use of robotics for sample preparation. The system needs to be designed in a way that it first measures the conductivity and other essential properties of the objective material, then follows the respective algorithms for a particular material type. The pinnacle ofrobotics and instrumentation can play a very important role in this development. This idea of formalization can be especially helpful for visualizing the mineral composition in locations where human intervention is usually not possible. Consider a robotic SEM-based characterization tool, trained with generative ML and AI, containing depths of mineral databases, and programmed in such a way that it is semicontrolled to choose the location of interest for scanning, and then it can operate on auto mode for scanning raw samples and communicating real-time SEM and XRD information from the depths of mines on Earth or on other terrestrial surfaces, such as the moon, Mars, and other planets. In situ and environmental SEM will facilitate understanding changes during reactions. This information would transform the mining industry on Earth but could also revolutionize astronomical and space engineering. The developed portable SEM/ML/AI systems can help save millions of dollars for mining and space agencies. Human researchers would then be able to focus more attention on analyses, research insights, and further development of technology.