esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Other DprE1 Inhibitors under Active Clinical Development  
Following the discovery of DprE1 as a target of BTZ043, numerous molecules acting on this enzyme emerged, particularly from the whole-cell based phenotypic screening campaigns (for a recent review see [32]). As a result, DprE1 was given an unflattering attribute--a promiscuous target [33]. Nevertheless, DprE1 remains to be one of the best understood and the most vulnerable novel targets. One of the reasons for its high sensitivity against a number of different pharmacophores could be its periplasmic localization, which makes it easily accessible for the drugs [34]. Consequently, in addition to macozinone, there are currently three other DprE1 inhibitors progressing down the clinical studies pipeline. BTZ043, sponsored by the University of Munich; the Hans Knoll Institute, Jena; and the German Center for Infection Research, successfully completed a single dose escalation Phase 1 study (NCT03590600) [35] and is currently recruiting for a combined Phase 1 and 2 study, which will evaluate safety, tolerability, pharmacokinetics and early bactericidal activity of the multiple ascending doses (NCT04044001) [36]. A non-covalent DprE1 inhibitor, TBA-7371 [37] developed by TB Alliance, Bill and Melinda Gates Medical Research Institute and Foundation for Neglected Disease Research, completed a Phase 1 study (NCT03199339) [38]--a partially blind, placebo-controlled study of (i) a combined single ascending dose with a food effect cohort, (ii) multiple ascending dose group, and (iii) a cohort to investigate interactions between TBA-7371 with midazolam and bupropion. Currently, recruitment of adult patients with rifampicin-sensitive pulmonary tuberculosis is taking place for the participation in a Phase 2 study (NCT04176250) [39] to assess safety, early bactericidal activity, and pharmacokinetics of escalating doses of TBA-7371. A combined Phase 1 and 2 study of OPC-167832 by [PERSON] is in progress (NCT03678688) [40], aimed at evaluation of the safety, tolerability, pharmacokinetics, and efficacy of multiple oral doses of the drug in patients with uncomplicated drug-sensitive pulmonary tuberculosis with a positive smear. In a parallel group, low dose or high dose OPC-167832 will be combined with delamanid and compared to delamanid only, or standard treatment with isoniazid, rifampicin, pyrazinamide, and ethambutol.
## 1 Introduction
Their study confirmed the characteristics of airflow movement inside tunnels and natural ventilation shafts caused by train entry and exit. Further, [PERSON] [5] investigated the effect of train-induced wind on ventilation in subway tunnels and station environments, focusing on minimizing airflow disturbances during train entry and exit at platforms. They estimated the train-induced airflow through field measurements and employed computational fluid dynamics (CFD) analysis to verify train-induced airflow variations. Their study examined the effects of train-induced wind on station and tunnel ventilation using numerical analysis and scaled models. [PERSON] et al. [6] conducted an experimental study on the effects of particle shape and size on ballast degradation. They conducted experiments using both single particles and uniform aggregates, considering both size and shape factors. Their findings revealed the effect of particle shape and size on railway ballast degradation. [PERSON] et al. [7] investigated the effects of vibration and thermal fatigue cracking on railway vehicle brake discs, and [PERSON] et al. [8] reviewed studies focused on rail corrosion, including corrosion types, protection methods, and detection technologies. These studies primarily conducted statistical analyses of CWR fracture occurrences over specific periods to identify correlations between factors and propose mitigation strategies. Further, prior research related to CFD focused on estimating natural ventilation volumes in urban rail tunnels and quantifying airflow changes attributed to train entry and exit at platforms. However, research on the effects of temperature variations on CWR fractures is lacking. This study analyzes the causes of CWR fractures in urban railway systems, identifies factors that affect the thermal expansion behavior of CWR, and determines the extent of the impact of a fracture for analyzing the primary causes of CWR fractures. In addition, the effects of winter-season temperature variations around ventilation shafts on CWR are also analyzed.
## 4 Discussion
### The Interplay of IEQ, Energy Use, and Environmental Impacts  
Educational institutions hold the responsibility to provide spaces that nurture intellectual and personal growth. By prioritizing IEQ, schools and universities create environments where their students and staff can thrive mentally and physically. However, balancing energy efficiency with IEQ presents a considerable challenge, as these objectives can occasionally be at odds. Therefore, it is mandatory to adopt a comprehensive technique that simultaneously considers energy performance, environmental impacts, and IEQ. This strategy ensures that initiatives aiming to enhance energy efficiency do not undermine IEQ or other important aspects of a building's performance. Prior to analyzing the interactions between factors, we assessed the data normality using Shapiro-Wilk tests. The statistical results for indoor temperature (0.89772, \(p\) = 0.14823), CO\({}_{2}\) (0.90298, \(p\) = 0.17331), lighting level (0.92209, \(p\) = 0.30366), sound level (0.95615, \(p\) = 0.72779), energy use (0.86406, \(p\) = 0.05498), and GWP (0.87597, \(p\) = 0.07784) showed no significant deviation from normality (\(p\) > 0.05). This validates the assumption of normality for subsequent analyses. To provide a comprehensive overview of the relationship between the IEQ, energy consumption, and environmental impacts, an overlap graph illustrating these parameters was created and is shown in Figure 13. For clarity, the sound and illumination levels were excluded from the graph despite them being discussed in the preceding section. As indicated in Figure 13, winter is characterized by significant environmental impacts due to the elevated energy consumption, correlated with high CO\({}_{2}\) concentrations, although the ambient temperatures fall into Category 1 of thermal comfort. During the summer months, the dynamics shift: we observe elevated temperatures, accompanied by lower CO\({}_{2}\) levels, reduced energy use, and diminished environmental impacts. To understand the interdependencies between the factors studied, we performed a Pearson's correlation analysis. The resulting correlation coefficients and \(p\)-values are presented in Table 3.  
Figure 12: Reductions for LCA indicators compared to the baseline scenario (S0). The analysis revealed several key correlational patterns among the variables studied. Notably, a strong negative correlation was observed between indoor temperature and both energy use (\(-0.8371\), \(p<0.0006\)) and GWP (\(-0.8401\), \(p<0.0006\)). This implies that as indoor temperatures rise, there is a significant tendency for energy consumption and the associated GWP to decrease. This could be attributed to reduced heating demands in warmer indoor environments. Similarly, a strong negative correlation was found between indoor tempera
# Handover Scheme in LEO Satellite Networks Based on QoE for Streaming Media Services
## 4 Performance Evaluation  
In this section, we will use the simulation system built in this paper to perform simulations and evaluate the performance of the proposed QoE access and handover method for subscriber streaming services through simulations.
# Multilayer Bolometric Structures for Efficient Wideband Communication Signal Reception
## 1 Introduction
The experimental findings showcase the possibility of a reasonable balance between bandwidth and efficiency. Moreover, our investigations illuminate a pathway to further enhancing detector efficiency by transitioning from a \"resonator-as-substrate\" layer sequence to an \"anti-reflection coating\" configuration.
## 4 Enabling Technologies for FSO Communication
### Adaptive Transmission
#### 4.4.1 Overview
This method requires a base code with a minimum rate suitable for the worst-case channel condition. Puncturing schemes are typically defined and tested at each desired rate to ensure optimal performance. Conversely, Raptor codes adjust their rate by extending the codeword length, with the Tx generating coded bits continuously until the Rx decodes the transmitted word without error. Raptor codes have been previously proposed for the network layer of both wired and RF communication systems [215]. Demonstrations of Raptor and punctured codes in the PHY layer of an FSO link, under various turbulence conditions, have shown high tolerance to deep fades caused by AT [214]. However, the achievable information rates (lower bounds on channel capacity) indicate that these approaches are still several decibels below channel capacity, suggesting potential for further improvement [216].
## 3 Applications in Food Safety
### Preparative Solutions
Following this methodology, molecularly-imprinted monolithic capillary columns (MIMCC) were used to selectively extract FQs from phosphate buffer diluted milk samples [32]. A novel porous, chemically stable and long-lifetime MIMCC for on-line extraction of antimicrobials was _in situ_ fabricated with sulfaquinoxaline as the template and used for trace analysis of five antimicrobials in food samples [54]. Over the past few years, there has been growing interest in the use of monolithic materials as SBSE coatings [64]. In this approach, the commercial stir bars are coated with monolithic material and applied as sorptive extraction media. Recently, an SBSE method based on monolithic material as the coating was successfully applied to extract penicillin in milk and honey samples [42]. Samples were diluted with water and were then directly used for sorptive extraction, with no additional step to eliminate fats and proteins in milk samples and/or sugar in honey samples prior to extraction.
# Personalized Augmented Reality Based Tourism System: Big Data and User Demographic Contexts
## 6 Evaluation
### Prediction Evaluation  
With the implementation of the data analysis methods, which include the DT and SVM methods, 90% of the data are considered as training data, and 10% of the data are considered as testing data. In order to check the results, three statistical indicators were used, which include correctly classifying the instances, the root mean square error calculated by using Equation (13), and the mean absolute error calculated by using Equation (14).  
\[\mathrm{x}RMSE =\sqrt{\frac{1}{n}\sum[y_{i}-x_{i}]^{2}} \tag{13}\] \[MAE =\frac{\sum_{i=1}^{n}\lvert x_{i}-y_{i}\rvert}{n} \tag{14}\]  
In Table 4, the DT method shows better performance among all three identified factors. Another way to evaluate it is to use the space under the recall-precision curve. The larger the space under the PR chart, the higher the values of the precision and the recall. A high amount of accuracy indicates a false positive, and a high amount of recall indicates a false negative. Therefore, the graph above the other diagram shows better performance than the other method. Figure 13 shows the recall-precision diagram for both the SVM and the DT methods. According to the diagram, the DT is higher than the SVM diagram in all parts.  
Another indicator that is used in this study to evaluate the performance of the two DT and SVM methods, is the classification error matrix, which is shown in Table 5. In Table 5, the DT also showed better performance with this indicator. It performed better than the SVM in the three types of park and restaurant locations, but it performed worse than the SVM only with the cafe floor. The overall accuracy indicator can be used in order to review Table 3 in a more detailed manner. The overall accuracy is calculated by the sum of the original diameter numbers of the error matrix divided by the sum of the total numbers  
\begin{table}
\begin{tabular}{c c c c} \hline  & **Root Mean Square** & **Percentage of Correctly** & **Mean Absolute** \\  & **Error** & **Classified Instances** & **Error** \\ \hline SVM & 0.361 & 73.75 & 0.285 \\ J84 & 0.287 & 77.5 & 0.164 \\ \hline \end{tabular}
\end{table}
Table 4: Results of the DT and SVM.  
Figure 13: Recall–precision chart.  
of the matrix. which is calculated using Equation (15). The overall accuracy calculated for the DT is 77% and 73% for the SVM method.  
\[\textit{Overall accuracy}=\frac{1}{n}\sum p_{ii} \tag{15}\]  
According to the drawbacks of the overall accuracy method, the kappa indicator was used to ensure the accuracy. The kappa indicator was calculated using Equation (16), which gives 0.667 for the DT and 0.611 for the SVM.  
\[kappa=\frac{p_{o}-p_{c}}{1-p_{c}}*100 \tag{16}\]  
where \(p_{o}\) is the correct classified observational pixels, and \(p_{c}\) is the expected agreement about the pixels.
## 3 Results
### Research Question 1  
Does media (VR and desktop screening) have an effect on the spatial understanding of DNA molecules between students with low, medium, and high spatial ability?  
To examine this research question, individuals' spatial recognition in two different groups were measured. Although, desktop screening group had (\(n\) = 29) participants, both the test of normality and [PERSON]'s test were not significant. This indicates that the assumptions of normality and homogeneity for an ANOVA test were not violated.  
Figure 8: Revised Purdue spatial visualization test.  
An ANOVA was conducted to evaluate the effects of independent variables, spatial ability (low, medium, and high) and media (VR and desktop screening), on student spatial recognition of DNA structure (dependent variable). As shown in Table 2, the results for the ANOVA indicated a significant for both spatial ability main effect and the spatial ability-by-media effect. The partial eta squared (\(\eta\) 2) showed a medium effect size. Figure 9 shows the frequency of each level of media within three spatial ability categories affected by the spatial recognition score.  
As shown in Table 3, the analysis showed a significant difference, \(p<0.05\), in spatial recognition among spatial ability groups using VR and desktop screening. Pairwise comparison showed that there was a significant difference, \(p<0.05\), only between low and high spatial ability groups.  
The result also showed that media had no significant effect on spatial recognition, but it is important to note that the mean value (M = 5.90) of VR group with low spatial ability was higher than the mean value (M = 4.75) of desktop screening group with low spatial ability (Table 3).
# Comprehensive Review of Storage Optimization Techniques in Blockchain Systems
## 5 Summary and Future Directions
### Summary
#### 5.1.3 Computational Efficiency  
In blockchain storage optimization, balancing storage efficiency with computational costs is a fundamental challenge in designing high-performance storage systems. Techniques such as data compression, deduplication, and erasure coding are pivotal in minimizing redundant data storage and optimizing overall system architecture. Data compression utilizes efficient algorithms to reduce the bit-size representation of data, which is particularly effective in environments with high transaction volumes or data redundancy, thus significantly lowering storage overhead. Deduplication further enhances efficiency by identifying and eliminating duplicate data blocks, ensuring that data are not redundantly stored across multiple nodes, leading to reduced storage requirements. Erasure coding, by fragmenting data into smaller parts and generating redundant fragments, not only optimizes storage efficiency but also increases data recovery capabilities, making it highly suitable for systems with high data durability demands. When these techniques are applied in tandem, they can substantially reduce storage redundancy, improving the overall efficiency of blockchain systems, particularly in handling large-scale data storage.  
However, the adoption of these storage optimization techniques introduces significant computational overhead. Data compression and decompression processes require considerable computational resources, especially when reading or restoring data, as the decompression phase may introduce latency. Deduplication relies on computationally intensive hash calculations and data matching, which consume processing power and may degrade data storage and retrieval speeds, particularly in high-frequency transaction environments. Erasure coding involves complex encoding and decoding operations, which can be computationally expensive, particularly when recovering data in the event of node failure or data loss. In large-scale blockchain networks, where the number of nodes and the volume of data increase, these computational demands can become bottlenecks, slowing down storage operations and affecting system throughput and response time.  
Consequently, the design of blockchain storage optimization systems must strike a careful balance between storage efficiency and computational cost. While techniques such as compression, deduplication, and erasure coding offer significant storage benefits, their computational complexities need to be carefully evaluated to avoid performance degradation. Over-reliance on one particular optimization method, especially those with high computational demands like erasure coding or deduplication, may result in processing bottlenecks that negatively impact system performance. Therefore, selecting the appropriate optimization techniques based on the specific use case and requirements is essential to achieving an optimal balance between storage efficiency and computational cost, ensuring that the blockchain storage architecture remains both scalable and efficient.
# Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
## 2 Preliminaries
### Computation of 3D Moments
To achieve this, we can substitute Equation (14) into (10), which yields the following formula:_  
\[\mathbf{MC}_{:,k}=\sum_{z}\mathbf{R}_{e(k,z)}\otimes\left[\mathbf{R}_{e(n,x)} \:\mathbf{F}\,\mathbf{R}_{e(n,y)}^{T}\right]. \tag{16}\]  
From the formula (16), we can observe that the moments of the function \(g\) can be calculated using the original function \(f\) and the orthogonal polynomials that contain the kernels within them. These orthogonal polynomials are denoted as \(\mathbf{R}_{e(n,x)}\), \(\mathbf{R}_{e(m,y)}\), and \(\mathbf{R}_{e(k,z)}\) for the x, y, and z dimensions, respectively. Here, \(\mathbf{R}_{e}\) is the embedded version of the orthogonal polynomials and is obtained by multiplying \(\mathbf{R}\) (the standard orthogonal polynomial matrix) with the Toeplitz matrix \(H\) of the corresponding kernel (\(h_{x}\), \(h_{y}\), or \(h_{z}\)). It is important to note that the Toeplitz matrix \(H\) represents the convolution kernel. **Remark 1**. : _The current formula for computing moments is faster than the formula that first applies the convolution operation and then computes the moments. This is because in the current formula, the kernels are embedded within the polynomials themselves. This embedding operation is performed at the beginning, after checking the database and extracting relevant information. Once the embedding is complete, the moments can be computed without the need to apply the kernel for each object (function)._  
_In other words, the current method saves computational time because the convolution operation is performed only once, and the resulting orthogonal polynomials containing the embedded kernels are then used to calculate moments for multiple objects without the need for repeated convolution._  
Note that the matrix \(\mathbf{H}\) in the previous equation represents a Toeplitz matrix that is truncated to a size of \(N\times N\) for the operator \(\mathbf{h}\). Suppose \(\mathbf{h}=[\mathbf{h}_{0},h_{1},\cdots,\mathbf{h}_{m}]\), then the Toeplitz matrix can be constructed as follows:  
\[\mathbf{H}= \begin{bmatrix}h_{0}&0&0&\cdots&0&0\\ h_{1}&h_{0}&0&0&\cdots&0\\ \vdots&h_{1}&h_{0}&0&\cdots&0\\ h_{m}&\vdots&h_{1}&\ddots&\ddots&\vdots\\ 0&h_{m}&\vdots&\ddots&h_{0}&0\\ 0&0&h_{m}&\cdots&h_{1}&h_{0}\end{bmatrix} . \tag{17}\]  
After presenting the mathematical model for moment computation, it can be applied for object recognition to demonstrate its advantages and importance. This process includes the following steps: generating the orthogonal polynomials, followed by constructing the Toeplitz matrix version of the kernel, and finally, embedding the kernel into the orthogonal polynomials. This approach has several advantages, such as efficient and fast moment computation, without the need to repeatedly apply the kernel for each object, which makes it ideal for object recognition systems.
# Effect of Kinesio Taping on Hand Sensorimotor Control and Brain Activity
###### Abstract  
Kinesio taping has been used to improve sensorimotor control performance. In this study, we explored the effect of Kinesio taping with different tensions on hand force control, joint proprioception, reaction time and brain activity. This was an observational study with a single-group, repeated-measures design. Twenty-four healthy participants (12 women) randomly assigned to three wrist/finger flexor taping conditions: (1) taping with 20% additional tension (taping20), (2) taping with neutral tension (tapingN), and (3) without taping (control). Grip force and wrist joint proprioceptive senses, reaction time, and force control performance were recorded in each of the taping conditions. An EEG of the bilateral sensorimotor cortex and an EMG of the right finger flexors were recorded to investigate changes in brain activity and functional connectivity between the brain and muscles (coherence). Our results indicated that taping significantly improved the joint position sense for participants with an error >3\({}^{\circ}\) (control vs. tapingN vs. taping20: 4.1\({}^{\circ}\)\(\pm\) 1.04\({}^{\circ}\) vs. 2.6\({}^{\circ}\)\(\pm\) 0.97\({}^{\circ}\) vs. 2.1\({}^{\circ}\)\(\pm\) 0.91\({}^{\circ}\); \(p\) = 0.001). In addition, Kinesio taping-induced improvements in force control were moderately correlated with decreases in the EEG beta band power. In conclusion, Kinesio taping could improve the joint proprioceptive sense, and taping-induced improvement in force control is likely due to neural desynchronization in motor cortex.  
Kinesio taping; proprioception; neuromuscular control; EEG; EMG +
Footnote †: journal: Applied Sciences