esa-sceva/satcom-chunk-collection huggingface dataset:
# Correction of Directional Effects in VEGETATION NDVI Time-Series
## 1 Introduction
The primary goal of this paper is to describe a methodology to perform a Bidirectional Reflectance Distribution Function (BRDF) correction (removal of directional effects inferred by land surface anisotropy) to the NDVI time-series derived from the three VEGFATION sensors. The work is structured as follows: Section 2 briefly describes the datasets used in the methodology's processing and for performance evaluation. Section 3 details the different processing steps implemented in the methodology. The results of performance inherent to the BRDF correction are presented in Section 4 and further discussed in Section 5 while our conclusions are listed in Section 6.
## 3 Results
### Relationships between GPP and Dry-Wet Conditions of the SEDI  
This part of the study aimed to detect whether the GPP was sensitive to the SEDI variability and exceedingly related to its dry-wet climatic condition. Herein, the efficiency of the SEDI in detecting drought influences on carbon production was evaluated. Figure 7 depicts the spatial distribution of correlation values between the four GPP datasets and the SEDI from 1982 to 2016. The results indicated that the regional average correlations between GPP and the SEDI were 0.20, 0.33, 0.41, and 0.50 for the GLASS, GIMMS, VPM, and FluxCom models, respectively. The spatial distribution patterns of the correlations between the SEDI and GPP products were somewhat similar and coherent. Based on the pairwise comparisons, the cross-correlations value between the GLASS-GPP and FluxCom-GPP responses to dry-wet conditions of the SEDI was 0.61, but the response patterns in the other GPP models were less coherent and had a cross-correlations value ranging from 0.35 to 0.59 (e.g., the FluxCom and VPM models' response pattern was the lowest); however, it was still statistically significant. The highest positive correlations were detected in the central and western parts of Turkey, the western and northeastern parts of Iran, and north Iraq, which had anomalous \(r\) values (\(r=0.7\)), especially for the SEDI-VPM and SEDI-FluxCom-GPP associations.  
Figure 6: (**a,b**) The regional temporal trend of the SEDI and the percentage of areas affected by drought categories based on the SEDI series at an annual timescale over the Middle East between 1980 and 2017.
# RAC1B: A Rho GTPase with Versatile Functions in Malignant Transformation and Tumor Progression
## 5 Biological Functions of RAC1B
### Survival/Anti-Apoptosis  
Expression of wild-type Rac1b, but not of wild-type Rac1, in NIH3T3 cells dramatically increased cell survival in the presence of only minimal growth stimuli [41]. Colorectal cells also depend on RAC1B signaling to sustain their survival. Depletion of RAC1B by siRNA reduced cell viability which was due to increased apoptosis [42]. RAC1B overexpression protected thyroid cells (the K1 PTC derived cell line) from undergoing apoptosis [26]. In all three cell types, the prosurvival effect of RAC1B was dependent on activation of canonical NF\(\kappa\)B signaling as evidenced by p65 nuclear localization, an increase in NF\(\kappa\)B reporter activity, a decrease in protein levels of the NF\(\kappa\)B inhibitor \(\mathrm{I}\)kB\(\alpha\), and the ability of the NF\(\kappa\)B super-repressor \(\mathrm{I}\)kB\(\alpha\)(A32A36) to block this cellular response. [PERSON] and coworkers observed that the survival of HEK293T cells stably overexpressing RAC1B was significantly increased in serum-starved media compared to HEK293T cells stably overexpressing RAC1 in which survival was only moderately increased [58]. Also in HEK293T cells (and in SW480 cells) stably overexpressing RAC1B, the anti-apoptotic proteins AKT2 and MCL1 were upregulated and the AKT2/MCL1 pathway activated coincident with inhibition of apoptosis. Conversely, knockout of the _RAC1_ exon 3b or knockdown of endogenous RAC1B in HT29 cells downregulated the AKT2/MCL1 pathway [43]. Finally, inhibition of RAC1B expression in HT29 cells with the nonsteroidal anti-inflammatory drug ibuprofen (see Section 6.6) reduced cell survival in vitro and RAC1B-dependent tumor growth of HT29 xenografts in vivo [27].  
As described above for effects of RAC1B on proliferation, RAC1B can functionally cooperate with B-RAF-V600E in CRC cells to sustain survival and, hence, may form an alternative survival pathway to oncogenic K-RAS [45].
# Active Gait Retraining with Lower Limb Exoskeleton Based on Robust Force Control
## 4 Tracking Control of the Exoskeleton  
Based on the result obtained above, we can rewrite (8a) as  
\[M(x_{e})\ddot{x}_{e}+C(x_{e},\dot{x}_{e})\dot{x}_{e}+g(x_{e})-\Gamma_{2}(t)= \tau_{s}=\tau_{d} \tag{24}\]  
where \(\Gamma_{2}(t)=\tau_{h}-\Phi(x_{e},\dot{x}_{e})\), considering that \(\Gamma_{2}(t)\) is bounded as \(\mid\Gamma_{2}\mid<\Gamma_{2 max}\).  
Let us consider the following control law for (24):  
\[\tau_{d}=M\Big{(}\ddot{x}_{d}-2\gamma\dot{\tilde{x}}-\gamma^{2}\tilde{x}\Big{)} +C\dot{x}+g-\rho_{2}\mid\sqrt{s_{2}}\mid sign(s_{2}) \tag{25}\]  
where we define the position error as \(\tilde{x}=x_{e}-x_{d}\) consider that \(\rho_{2}>\Gamma_{2 max}\).  
The sliding surface in (25) is defined as  
\[s_{2}=\dot{\tilde{x}}+\gamma\tilde{x} \tag{26}\]  
where \(\gamma>0\).  
The closed-loop equation is obtained by replacing the control action (\(\tau_{d}\)) of the control law (25) in Equation (24)  
\[M\ddot{x}_{e}=M\Big{(}\ddot{x}_{d}-2\gamma\dot{\tilde{x}}-\gamma^{2}\tilde{x} \Big{)}+C\dot{x}_{e}+g-\rho_{2}\mid\sqrt{s_{2}}\mid sign(s_{2})-C\dot{x}_{e}- g+\Gamma_{2} \tag{27}\]  
Then, Equation (27) is reduced to  
\[M(\dot{s}_{2}+\gamma s_{2})=\Gamma_{2}-\rho_{2}\mid\sqrt{s_{2}}\mid sign(s_{2}) \tag{28}\]  
Stability Proof  
In order to provide the stability system for (28), the following Lyapunov candidate function is proposed:  
\[V_{2}(t)=\frac{1}{2}s_{2}^{T}Ms_{2} \tag{29}\]  
The derivative with respect to time is  
\[\dot{V}_{2}=s_{2}^{T}Ms_{2}=s_{2}^{T}M\Big{(}M^{-1}\Gamma_{2}-M^{-1}(\rho_{2} \mid\sqrt{s_{2}}\mid sign(s_{2}))-\gamma s_{2}\Big{)} \tag{30}\]  
Then, we obtain  
\[\dot{V}_{2}=-s_{2}^{T}M\gamma s_{2}+s_{2}\Gamma_{2}-\rho_{2}\mid s_{2}^{\frac {3}{2}}\mid\ \ <0\ \ \forall\ s_{2}\in\mathbb{R}^{2}\setminus\ \{0\} \tag{31}\]  
Next, similar to the result of Equation (23), for \(s_{2}=0\), \(\dot{V}_{2}=0\), it follows that \(\dot{\tilde{x}}+\gamma\tilde{x}=0\), then \(\dot{\tilde{x}}\to 0\) and \(\tilde{x}\to 0\), i.e. \(x_{e}\to x_{d}\) asymptotically. In summary, using the first sliding surface (\(s_{1}\)) and the proposed Lyapunov function (\(V_{1}\)), we achieve exponential convergence of \(\tau_{s}\) to \(\tau_{d}\). Similarly, for the error (\(\tilde{x}\)), the sliding surface (\(s_{2}\)) and the Lyapunov function (\(V_{2}\)) ensure that the error converges to zero.
## 3 Results and Discussion  
### Total Metal Concentrations Distribution within the Water Column  
Before analyzing the distribution of trace metals between various fractions, it is useful to analyze their total concentrations in order to obtain a general overview of the trace metal distributions within the water column over different seasons. Vertical profiles of the total trace metal concentrations (unfiltered sample) are shown in Figure 1. Accompanying vertical salinity profiles during the time of each sampling are given in the Supplementary Materials (Figure S1). Additionally, the metal concentrations in unfiltered and filtered samples using all four cut-offs (5, 1.2, 0.1 \(\upmu\)m and 3 kDa) in relation to salinity are given in Figures S2-S6. The highest concentration in all the samples using all filter cut-offs was determined for Al, followed by Fe, Mn, Cu/Zn, Ni, Cd/Co and Pb. Obtained concentrations were within the expected ranges and agreed well with the levels reported in previous studies from this area [8; 27; 29; 40; 41]. Concentrations of Zn, Co, Mn, Fe and Al were higher in the freshwater layer (FWL) than in the seawater layer (SWL), particularly during the winter sampling characterized by high river flow [30], indicating a dominant river source of these metals to the estuary. Conversely, concentrations of Cd, Pb and Ni generally increased from the FWL to the SWL, showing a diluting effect of the Krka River on their concentrations, as already observed for these metals in a previous study covering longitudinal estuarine transect [8]. Concentrations of Cu in the FWL changed between seasons depending on the nautical tourism activity, which is common for this estuary [8; 31]. Similar Cu concentrations were observed in the FWL and SWL in non-touristic periods (February 2019 and April 2021), in contrast to summer samplings when 2-4 times higher Cu concentrations were measured in the samples from the FWL. In all the seasons, Cu showed an increase in the freshwater-seawater interface (FSI), a behavior that has already been observed in this estuary [29; 35]. The accumulation in the FSI was observed also for Zn, Cd and Pb, whereas the concentration of Ni, Co, Fe and Al changed proportionally with the salinity (Figure S2). For Mn, an increase in the FSI was observed in most of the sampling campaigns (except in July 2019), as was observed in a previous study in this estuary [40]. For most of the metals, a similar relationship with salinity was observed in all filter cut-offs (Figures S2-S6). The notable difference in distributions over the salinity gradient between fractions was observed only for Pb, Mn, Fe and Al in the dissolved fraction. Namely, in contrast to higher size fractions (Figures S2-S4), concentrations of Mn,Fe and Al in the dissolved and truly dissolved fractions increased with salinity (Figures S5 and S6). Additionally, all four metals showed a decline from the conservative behavior in the FSI only in these two fractions, indicating a precipitation and colloidal aggregation in the surface layers and their partial dissolution in the SWL.
# Strategies for Post-Translational Control of Protein Expression and Their Applications
## 5 Applications
### Research Tools  
In addition to applying degron technology to therapeutics, researchers have combined it with other technologies to develop new research tools. Here, we include three practical examples of this approach. The first application is the combination of degron and CRISPR/Cas9 to control the expression of endogenous proteins. In general, a fusion protein with a degron tag is exogenously expressed by transient or stable transfection. CRISPR/Cas9 can fuse an endogenous gene with a degron tag sequence. Several groups demonstrated that CRISPR/Cas9 enables the knock-in of DD- or AID-tag-fused essential genes, which are difficult to knockout or knockdown, thus allowing the conditional control of endogenous target protein expression [94; 95]. [PERSON] et al. used CRISPR/Cas9 to introduce SMASH-tagged FOXG1 into human pluripotent stem cells, to generate a cellular model of Forkhead transcription factor 1 (FOXG1) syndrome, a disease associated with abnormal protein expression [96]. Such disease models, generated by conditionally manipulating endogenous protein expression, will facilitate the understanding and therapy of human diseases. The second application is the improvement of off-target editing of CRISPR/Cas9 by fusing a degron to the Cas9 protein and controlling the timing and amount of its expression. Cas9 is expressed constitutively, resulting in off-target editing and subsequent genotoxicity. Because off-target editing is often slower than on-target editing, regulating the expression of Cas9 improves on-target editing while avoiding off-target editing and subsequent genotoxicity. Several research groups have demonstrated that controlling Cas9 expression levels reduces off-target editing [97; 98; 99; 100; 101]. Furthermore, the Cre protein can also be fused with DD to achieve inducible control of gene expression [102]. The third application is the combination of transcriptional regulation techniques to achieve tighter control of protein expression. The tight conditional control of protein expression requires the simultaneous regulation of their synthesis and degradation. [PERSON] et al. and [PERSON] et al., respectively, developed a system for the dual control of protein expression at the transcriptional and post-transcriptional levels [103; 104]. They combined a tetracycline-inducible system for inducible and reversible transcriptional regulation with DD or AID for targeted protein degradation.  
Figure 7: Applications of technologies for post-translational control of protein expression. Schematic diagrams of (**a**) CART cell therapy and (**b**) switchable CAR for CART therapy.
## 3 Results and Discussion
### TGA Analysis of the Adhesive Mixtures  
Figure 2 shows the TGA curves of mass loss and its derivative for the adhesive mixture of pMDI with 30% soy flour. The adhesive mixture was studied immediately after combining its ingredients (uncured), two hours after its preparation (prepolymer) and after its curing (cured). The uncured adhesive mixture presents a 7% mass loss up to 160 \({}^{\circ}\)C, which is attributed to humidity. Several local maxima of the mass loss rate can be observed, which correspond to its unreacted ingredients, such as the degradation of pMDI at 245 \({}^{\circ}\)C, the degradation of MDI monomers at 430 \({}^{\circ}\)C, and, finally, the degradation of the remaining isomers of MDI at 500 \({}^{\circ}\)C [41]. Moreover, and due to the soy flour, two additional local mass loss rate maxima are reported, at \(\sim\)350 \({}^{\circ}\)C, due to starch and protein decomposition [30; 42]. Regarding the cured adhesive mixture, its decomposition presents a mass loss rate maximum at 344 \({}^{\circ}\)C, in accordance with the literature [43]. Finally, the prepolymer presents a mass loss of 0.5% due to humidity up to 160 \({}^{\circ}\)C, which indicates that the moisture content of soy flour is immediately consumed as pMDI starts to cure. This is supported from the major step of degradation that the three analyzed samples present; their corresponding maxima of mass loss rate are located at 250, 322, and 343 \({}^{\circ}\)C for the uncured, the prepolymer, and the cured mixture, respectively.  
Figure 3 shows the TGA results of the various studied adhesive mixtures of pMDI with 15% soy flour, and 15% flour of the agricultural wastes, according to Table 2, while the  
Figure 2: Thermogravimetric curves of the adhesive mixture pMDI/soy flour 70/3: (**a**) mass loss; (**b**) dTG.  
mixture of pMDI with 30% soy flour--as aforementioned--is also presented for comparative reasons. All the specimens were studied after being cured. The adhesive mixtures present a major degradation step, with a local mass loss rate maximum at 330-360 \({}^{\circ}\)C, which is in total agreement with cured pMDI mixtures according to the literature [43]. As shown by the dTG curves (Figure 3b), the glue mixtures with residual olive skin (ROS), olive stone (OS), and olive leaves (OLs)--all extracted--present a better thermal stability of all the other mixtures, while the glue mixtures with wheat flour (WF), extracted (EOP-E) and non-extracted exhausted olive pomace (EOP-NE), residual olive skin non-extracted (ROS-NE), and extracted hemp seeds (HS-E) have a lower thermal stability.
## 5 Conclusions  
The data used in this study are the BDS/GPS observation data collected by IGS/MGEX and the CNCORS, from July to August in 2016. The BDS/GPS joint and BDS single-system orbit determinations are used for orbit determination. The accuracy evaluation is conducted by means of overlapping arcs precision, a comparison with the GBM orbit, and an SLR assessment. The ODOP values of the different distribution strategies are analyzed. In this paper, the influence of the CNCORS on the accuracy of BeiDou orbit determination is comprehensively analyzed, and the differences between the solutions derived from different orbit determination methods are tested and compared. This paper obtained some useful conclusions through the comprehensive analysis of BeiDou orbit determination, and the calculation results and analysis conclusions can provide a reference for BeiDou precise orbit determination in the future. The following conclusions can be drawn from the numerical comparison and analysis:  
(1) The BDS/GPS joint orbit determinations based on observation data from the 124 stations worldwide yield the highest BeiDou orbit determination accuracies in this paper. The radial overlapping arc precision is better than 2.3 cm for all three types of BeiDou satellites. The results of satellite laser ranging (SLR) residuals show that the RMS of the IGSO and MEO satellites is better than 5 cm.  
(2) The addition of the CNCORS greatly improves the accuracy of the BeiDou orbit determination. The analysis of the overlapping arc precision and the SLR assessment results show that the CNCORS most strongly influence the IGSO satellites, less strongly influence the GEO satellites, and have the least influence on MEO satellites.  
(3) By comparing the BDS single-system orbit determination and the BDS/GPS joint orbit determination, we found that the joint orbit determination has the biggest influence on MEO satellites. Among the comparisons of the three orbital directions, the radial direction is improved the most by joint orbit determination, followed by the along-track direction, and the cross-track direction is improved the least.  
(4) The ODOP value of the satellite and the ground tracking stations can be adopted to examine the geometrical configuration. The ODOP value of the different station distribution strategy is generally consistent with the accuracy of the orbit determination, i.e., a smaller ODOP value yields a higher orbit accuracy.  
We would like to acknowledge the efforts of the IGS MGEX campaign in providing the multi-GNSS data. We would like to acknowledge the ILRS for SLR observations. This work is supported by the National Natural Science Foundation of China (No. 41374034) and the National Key Research and Development Program of China (Grant No. 2016 YFB0501802 and No. 2017 YFF0212005).  
[PERSON] and [PERSON] conceptualized the initial idea and experiment design; [PERSON] and [PERSON] wrote the main manuscript text; and the other authors helped with the writing of the text.  
The authors declare no competing financial interests.
## 2 Overview of PSO Schemes and the IPTBK Problem
### MSPSO Algorithms
#### 2.2.2 DMS-PSO  
To increase the diversity of particle swarm searching in multimodal optimisation problems, the DMS-PSO algorithm [22; 23] uses a regrouping strategy in which the entire population is divided into a large number of subswarms. These subswarms are regrouped frequently using various regrouping schedules. Information is exchanged among the particles in the entire swarm. The DMS-PSO uses two phases to enhance the search performance:  
1. Local search phase: A quasi-Newton method (e.g., the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm) is used to speed up the search for the best position in a subswarm. Notably, the space constrained within the range is searched in this phase. The fitness value of a path is calculated by minimising the cost function of traversed paths.
2. Convergence phase: After completing the local search process, the DMS-PSO algorithm periodically regroups the particles of the subswarms into new subswarms. The new subswarms initiate the search process again with the previous particle swarms until the global best position is found.  
Compared with those of the MSPSO methods for IP traceback problems, we regrouped the particles of the subswarms, such as WOSP and DMS-PSO, which have produced pretty good results and are generally considered as the best solutions. Finally, we made the comparisons with those of MSPSO schemes, as shown in Table 2.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Scheme** & **Feature** & **Advantage** & **Limitation** \\ \hline \multirow{4}{*}{WOSP [21]} & When particles get too close, they are expelled by a short range force into new & WOSP is especially fitted for the optimisation on multimodal problems using the SRF where multiple local optima exist. & Sometimes, it may generate loop iterations in the searching process to discover the optimal solution. \\  & & & \\ \cline{1-1}  & DMS-PSO periodically & & \\ \cline{1-1}  & regroups the particles of the subswarms after they have converged into new & DMS-PSO can achieve a good balance between the exploration and exploitation abilities in multimodal problems. & DMS-PSO separates the optimal solution searching process into distinct phases, which could \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \hline \end{tabular}
\end{table}
Table 2: Feature comparisons of three known MSPSO schemes.
# Adaptive Kinetic Scrolling: Kinetic Scrolling for Large Datasets on Mobile Devices
## 5 Results and Discussion
### Results
When the target distance is 200 or 400, the \(p\)-value is approximately 0.4. This means that the difference between the two groups is not statistically significant. In other words, AKS cannot guarantee a reduction in the number of scrolling actions in this case. These results imply that AKS does not contribute to reducing the number of actions when the target distance is not sufficient. As mentioned earlier, there was no significant difference in the number of actions when the target distance was short, and the \(t\)-test confirmed that the difference is not valid. However, the \(t\)-test result also shows that AKS can help the user reach the target information with fewer scrolling actions when the target distance is 600 or 800. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Target Distance**} & \multicolumn{2}{c}{**Standard Deviation**} & \multirow{2}{*}{\(p\)**-Value**} \\ \cline{2-3} \cline{5-4}  & **Standard Scroll** & & **AKS** \\ \hline
200 & \(1.652\) & \(1.825\) & \(0.422\) \\
400 & \(1.914\) & \(2.219\) & \(0.438\) \\
600 & \(4.747\) & \(3.225\) & \(0.021\) \\
800 & \(3.286\) & \(3.540\) & \(<\)0.001 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Standard deviation (\(SD\)) and \(p\)-value of number of scrolling actions. Figure 7: Number of scrolling actions required for scrolling tasks. **RQ. 3 Does AKS affect the occurrence of overshoots? ** Finally, we analyzed whether the application of AKS by users causes higher overshoot or not. This question is to ensure that the increase in the scrolling speed by AKS occurs without side effects when the user performs tasks. We obtained positive results in terms of overshooting by AKS. Overshoots were observed seven times with standard scrolling and ten times with AKS (see Figure 8). For these test sessions, seven and ten overshoots are not significantly different. These results indicate that there is only a marginal difference in the likelihood of an overshoot when AKS is used. The scrolling patterns applied were marginally different for each user, and the effectiveness of the proposed method was dependent on such patterns. A few users scrolled carefully; therefore, in these cases, AKS was triggered fewer times. Vice versa, for the few users with very rapid and bold scrolling, AKS was used more frequently. In conclusion, in most cases, we observed that the proposed AKS method is effective. The effects of AKS have been verified on the basis of experimental results, and a few of the considerations required while applying AKS are discussed in the next section.