esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
Recently, molecular docking studies have gained attention in drug design in terms of analyzing interactions, estimating binding affinities, increasing efficacy and reducing cost [25]. For this reason, the use of similar technological computer programs is very important. After investigating the inhibition effects of TYR, AChE, and BuChE enzymes of C1 and C2 molecules, the interaction between the significantly effective C2 molecule and the AChE enzyme was investigated by in silico molecular docking studies. The C2 molecule is luteolin-7-O-glucoside, which is in the structure of a flavone glycoside. The interactions between the ligand and the enzyme, the bonds formed and the bond lengths are shown in Table 3 and the molecular interaction between C2 and AChE enzyme is shown in Scheme 1. The benzopyran ring's 4-oxo performed a hydrogen bonding with residue of PHE288. Other hydrogen bonds were observed between the residues of SER286, ARG289, and the 5-OH group of the benzopyran ring. Groups belonging to the glycoside structure of C2 (3, 4, 5-OH) performed much hydrogen bonding with related residues of the enzyme (respectively: SER286, ASP285, and ASP285). The other two hydrogen bonds were observed between the 3,4 hydroxy groups of phenyl and residue of ASP72. \(\pi\)-\(\pi\) charge transfer interaction occurred between the benzene ring at position 2 of the ligand and the benzene ring of TYR334. qqqqHydrophobic interactions (shown in green residues), positive load interaction between ARG289 residue and ligand, negative charge interaction between ASP285 and ASP72 residues and ligand, and polar interactions were observed between SER286 and SER81 residues and ligand (Scheme 1). The ligand was superimposed (glide score: \(-8.31\)) into the active part of the enzyme. In the docking study, no interaction was observed between any of the catalytic triad residues (HIS440, SER200) and the molecule. Many cholinesterase inhibitors, such as donepezil, amhenonium, avd physostigmine, contain the N atom. In previous studies, it was stated that compounds containing the amine group showed strong cholinesterase inhibition [39; 40; 41; 42]. A modified new molecule with the C2 skeleton containing an amine group may have stronger cholinesterase inhibition. It may be useful to carry out additional studies on this subject.
# Numerical Simulation of Co-Barrier Efficiency of Air Curtains in Mine Refuge Chambers
## 5 Conclusions  
This study analyzes the CO barrier effectiveness of the air curtain in the mine refuge chamber with varying installation positions, jet velocity, angle, and structural parameters. The specific findings that can be drawn from numerical analysis are as follows:  
1. Increasing the jet velocity of the air curtain does not always increase the barrier effect of the air curtain; increasing the jet angle of the air curtain, the barrier effect of the air curtain first increases and then decreases;
2. A 6 mm hole diameter air curtain with a 15 mm hole spacing was installed on the top side of the refuge door, with a jet velocity of 22 m/s and a jet angle of 10\({}^{\circ}\), giving the best CO barrier;
3. The correlation equation of predicted air curtain hole diameter and hole distance with air curtain efficiency is proposed to provide guidance for the structural design of air curtains in other applications.  
All the authors made contributions to the concept and design of the article. methodology, Z.Z. and Z.S.; software, Z.S.; formal analysis Z.Z.; data curation, J.L.; writing--original draft preparation, Z.S.; writing--review and editing, Z.S.; visualization, R.M.; supervision, H.M.; Project administration, X.T.; funding acquisition, Z.Z. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Condition**} & **Installation** & **Airflow** & **Hole** & **Hole** & **Airflow** & **Efficiency** \\  & **Location** & **Velocity** & **Diameter** & **Spacing** & **Angle** & **at 5 min** \\  & & **(m/s)** & **(mm)** & **(mm)** & **(mm)** & **(m/s)** \\ \hline  
\hline \hline \end{tabular}
\end{table}
Table 1: _Cont._  
**Funding:** The author would like to thank the financial support the National Natural Science Foundation of China (No. 52168013).  
**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.  
**Data Availability Statement:** Data available in a publicly accessible repository.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 3 Method
### Search Space
#### 3.1.1 Search Space for Backbone  
The macro architecture of backbone is shown in Figure 1, and we propose to search operation types and connections for each cell. The backbone consists of \(3N\) normal cells and three reduced cells. Unlike DARTS where normal/reduced cells share the same architecture, we independently search each of the cells, i.e., all cells can have different architectures. The importance of candidate operations and connections are represented by the architecture parameters \(\mathbf{\alpha}\), which is trained by SGD algorithm during the search stage. After searching, we derive the final architecture according to the magnitude of \(\mathbf{\alpha}\). Specifically, for each intermediate node, we preserve two connections sourced from different predecessors, and select the best operation on the two connections.
# Evaluation of Yogurt Quality during Storage by Fluorescence Spectroscopy
## 4 Conclusions  
The present work demonstrates that fluorescence spectroscopy can be used rapidly and non-invasively for the evaluation of yogurt quality during deteriorating. The characteristic fluorescence spectra of yogurt consist of a broadband spectrum in the wavelength region of 500 to 600 nm with a peak at 525 nm attributed mainly by the riboflavin and Maillard products of raw milk and several narrow emission peaks in the region of 600 to 750 nm caused by the porphyrin and chlorin compounds existing naturally in yogurt. Based on a total of 100 fluorescence spectra from five brands of yogurt, LDA discrimination model was carried out to classify the yogurt brands, which showed a preferable classification result. To realize the prediction of yogurt quality, two ARC formulas \(K_{622/633}\) and \(K_{661/672}\) were utilized to extract the spectral information related to yogurt deterioration, particularly in the 600 to 750 nm region. The decreasing tendency of \(K_{622/633}\) and the increasing tendency of \(K_{661/672}\) indicate the photodegradation of porphyrin and chlorin compounds. Moreover, the fluorescence peak ratio \(K_{622/633}\) shows a good linear relationship with the measured pH value and viscosity of yogurt, which further verifies the physico-chemical change related to the quality of yogurt. Based on these two fluorescence peaks ratios \(K_{622/633}\) and \(K_{661/672}\), MLR models were established to verify the dependence of fluorescence signal with pH value and viscosity. A more than 85% correlation coefficient is obtained for each class of yogurt, which further demonstrates the potential and effectiveness for the evaluation of yogurt quality by using fluorescence spectroscopy.  
[PERSON] and [PERSON] performed the fluorescence spectral measurements. [PERSON] and [PERSON] performed the measurements of pH value and viscosity. [PERSON] and [PERSON] were involved in the data processing and data analysis. [PERSON] and [PERSON] were involved in writing and revising the paper.  
This work was financially supported by the China Postdoctoral Science Foundation (No. 2017M612399), the Science and Technology Project of Henan Province (No. 182102110427), the Science and Technology Innovation Project of Henan Agricultural University (No. KJCX2018A09), the National Natural Science Foundation of China (No. 31671581), the Natural Science Foundation of Henan Province (No. 162300410143), and the Science and Technology Project of Henan Province (No. 182102110250).  
The authors declare no conflict of interest.
## 2 System Model of FTN Signal Processing  
### FTN Signal Processing  
FTN signaling is a technique for transmitting information at a rate higher than the allowed Nyquist limit in order to improve the transmission efficiency by applying the FTN method, which increases the interference rate. However, FTN signaling has a limitation in maximizing the transmission efficiency due to performance degradation arising from ISI. The transmission signal with ISI can be given by Equation (1):  
\[\rm{s(t)}=\sqrt{E_{s}}\sum\
olimits_{n}a_{n}h(t-n\tau T),\ \tau<1, \tag{1}\]  
where \(\rm{a}_{n}\) is the encoded bit stream; \(E_{s}\) is the average symbol energy; \(\rm{h(t)}\) is a unit-energy baseband pulse, which, for this paper, we will assume is orthogonal to shifts by \(\rm{T}\); and \(\tau\) is the interference time. The interference ratio, \(\tau^{\prime}\), is given by:  
\[\tau^{\prime}(\%)=100\times(1-\tau). \tag{2}\]Figure 1a shows that no ISI is generated, as the transmission is run at the Nyquist rate, when \(\tau=1\). However, in Figure 1b, \(\tau=0.7\), the adjacent symbols affect each other due to FTN, and, as a result at each decision point of data, the parts labeled with a red circle are added to the raw data and affect them. Thus, we know that there is a change in the waveform due to the interference. While the signal's waveform becomes distorted due to ISI, if this issue is overcome, it can be seen that the transmission rate improves by 30% at the same time.
## 4 Analysis of Positioning Accuracy  
Referring to [30], evaluating the computation process and the significance of approximate accuracy is an important step in deriving either exact or approximate solutions for the localization problem. This section presents an estimation-theoretic analysis of the proposed measurement mechanisms to assess the achievable localization accuracy with Cramer-Rao lower bound (CRLB) for joint TOA/AOA estimation.  
The measurements at the reference sensor can be modeled as  
\[\hat{\tau} = \tau+\delta_{\tau} \tag{7}\] \[\hat{\phi} = \phi+\delta_{\phi} \tag{8}\]  
where \(\tau\) is the true propagation time and \(\phi\) is the true angle information. Note that \(\delta_{\tau}\) and \(\delta_{\phi}\) are uncorrelated Gaussian noises with the distributions \(\delta_{\tau}\sim\mathcal{N}(0,\sigma_{\tau}^{2})\) and \(\delta_{\phi}\sim\mathcal{N}(0,\sigma_{\phi}^{2})\). Assuming that the direct path exists between the sensor and the target, the estimated target position is given by  
\[\hat{x} = x_{s}+v\hat{\tau}\cos(\hat{\phi})=x_{s}+\hat{r}\cos(\hat{\phi}) \tag{9}\] \[\hat{y} = y_{s}+v\hat{\tau}\sin(\hat{\phi})=y_{s}+\hat{r}\sin(\hat{\phi}) \tag{10}\]  
where \(\hat{r}\) is the distance measurement (_i.e._, \(\hat{r}=v\hat{\tau}=r+v\delta_{\tau}\)), \((x_{s},y_{s})\) is the true position of the sensor and \(v\) is the speed of signal. Assuming \(\delta_{\tau}\) and \(\delta_{\phi}\) are sufficiently small, the variance of the position estimation \(\hat{p}\) is approximated by  
\[\sigma_{p}^{2}\approx v^{2}\sigma_{\tau}^{2}+d^{2}\sigma_{\phi}^{2}=\sigma_{r} ^{2}+d^{2}\sigma_{\phi}^{2} \tag{11}\]  
Given the above assumptions [31], the CRLB with a single sensor is derived as follows. The probability density function of \(\mathbf{g}=[\hat{r},\hat{\phi}]\) is  
\[f(\mathbf{g};x,y)=\frac{1}{\sqrt{2\pi\sigma_{r}^{2}}}\cdot\exp\left[-\frac{1}{ 2\sigma_{r}^{2}}\left(\hat{r}-d\right)^{2}\right]\]\[\cdot\frac{1}{\sqrt{2\pi\sigma_{\phi}^{2}}}\cdot\exp\left[-\frac{1}{2\sigma_{\phi}^ {2}}\left(\hat{\phi}-\arctan\left(\frac{y-y_{s}}{x-x_{s}}\right)\right)^{2}\right] \tag{12}\]  
Thus, the [PERSON] information matrix yields  
\[I(\mathbf{x}^{(t)})=\left[\begin{array}{cc}\frac{\cos^{2}(\phi)}{\sigma_{ \tau}^{2}}+\frac{\sin^{2}(\phi)}{d^{2}\sigma_{\phi}^{2}}&\frac{\sin(2\phi)}{2} \left[\frac{1}{\sigma_{\tau}^{2}}-\frac{1}{d^{2}\sigma_{\phi}^{2}}\right]\\ \frac{\sin(2\phi)}{2}\left[\frac{1}{\sigma_{\tau}^{2}}-\frac{1}{d^{2}\sigma_{ \phi}^{2}}\right]&\frac{\sin^{2}(\phi)}{\sigma_{\tau}^{2}}+\frac{\cos^{2}( \phi)}{d^{2}\sigma_{\phi}^{2}}\end{array}\right] \tag{13}\]  
and the CRLB can then be written as  
\[Var(\mathbf{x}^{(t)})\geq I^{-1}(\mathbf{x}^{(t)})=\left[\begin{array}{cc}I _{1,1}^{{}^{\prime}}&I_{1,2}^{{}^{\prime}}\\ I_{2,1}^{{}^{\prime}}&I_{2,2}^{{}^{\prime}}\end{array}\right] \tag{14}\]  
Thus,  
\[Var(\tilde{x})\geq I_{1,1}^{{}^{\prime}},\ \ Var(\tilde{y})\geq I_{2,2}^{{}^{ \prime}} \tag{15}\]  
Accordingly, the best possible fused estimation for target localization may be determined by applying Equation (15) and the CI method.
# Scheduling Optimization of Mobile Emergency Vehicles Considering Dual Uncertainties
## 1 Introduction
Throughout most of the existing research, mobile emergency vehicle scheduling models have been widely discussed. In particular, there are numerous models and processing algorithms that have been developed with minimum cost, shortest duration, and widest service scope. Nonetheless, most of them are not willing to consider the uncertainty of different factors because of the complexity it brings. Moreover, the introduction of mobile emergency mode systems and infrastructure work is still in the preliminary exploration stage. There is a lack of optimal mobile vehicle scheduling schemes considering the effectiveness of emergency services, emergency response time, and emergency cost. For the government and auxiliary agencies of emergency services, it is important to explore more effective scheduling strategies for mobile emergency units to maximize life and property savings. Optimized mobile emergency scheduling with double uncertainties can shorten rescue time, expand rescue scope, and increase rescue quantity. It can also enrich the framework of mobile emergency systems and provide a solution for reasonable scheduling of emergency resources. Aiming to minimize mobile emergency costs and time with double uncertainties, this paper presents a scheduling optimization model of mobile emergency vehicles based on the mobile emergency features of vehicle flexibility, autonomy, intelligence, etc. The path uncertainty and demand uncertainty were measured by path integrity and demand disturbance variation, respectively. After transforming the multi-objective problem into a single-objective problem, the model was solved by an integer-coding hybrid genetic algorithm. Finally, the emergency data of the \"5.12\" Wenchuan earthquake were taken as an example to verify the validity and applicability of the scheduling optimization model.
# Radio Resource Dimensioning for Low Delay Access in Licensed OFDMA IoT Networks +
## Appendix E Proof of Proposition 7  
### Laplace Transform of the Interference with MRC  
To show that the Laplace transform remains the same, we let \(\mathbf{h}_{x}=[h_{x,1}\ldots h_{x,n_{r}}]\) denote the complex Gaussian vector containing the (signal) fading coefficients and \(\mathbf{h}_{y}=[h_{y,1}\ldots h_{y,n_{r}}]\) the fading vector between the interferer and the collector. When using a MRC decoder, the \(n_{r}\) observations of \(x\) are projected into the orthonormal vector \(\mathbf{u}_{x}=\mathbf{h}_{x}/\|\mathbf{h}_{x}\|\). The equivalent interferer channel is then the scalar product between \(\mathbf{u}_{x}\) and \(\mathbf{h}_{y}\). Let \(\mathbf{u}_{y}=\mathbf{h}_{y}/\|\mathbf{h}_{y}\|\), the equivalent fading seen by each interferer \(A_{f,i}=|\langle\mathbf{u}_{x},\mathbf{h}_{y}\rangle|^{2}\) is exponentially distributed. This is a consequence that the cosinus square of an angle between a Gaussian vector and a given direction \(\cos^{2}(\mathbf{u}_{x},\mathbf{h}_{y})\) is beta distributed with parameters \(1\) and \((n_{r}-1)\) as shown in [27]. This leads to a distribution of \(\beta(1,n_{r}-1)\) multiplied by a chi-squared with \(2n_{r}\) degrees of freedom which is exponentially distributed. In other words,  
\[A_{f,i}=|\langle\mathbf{u}_{x},\mathbf{h}_{y}\rangle|^{2}=\|\mathbf{h}_{y}\|^ {2}\cos(\mathbf{u}_{x},\mathbf{u}_{y})\sim\chi_{2n_{r}}^{2}\times\beta(1,n_{r} -1)=\text{exprnd}(1). \tag{10}\]
# Comparative Analysis of Local Differential Privacy Schemes in Healthcare Datasets
## 2 Preliminaries
### Local Differential Privacy  
Local Differential Privacy (LDP) [20] offers a stringent privacy guarantee, wherein users place their trust solely in themselves and not in any central authority.  
**Definition 1** (Local Differential Privacy).: _An algorithm \(\zeta\) satisfies \(\epsilon\)-local differential privacy for any user if for any two data records \(u\) and \(w\) and for any output \(\hat{u}\) within the range of outputs of algorithm \(\zeta(\hat{u}\subset Range(\xi))\), Equation (2) holds:_  
\[Pr[\zeta(u)\in\hat{u}]\leq\epsilon^{\epsilon}Pr[\zeta(w)\in\hat{u}]. \tag{2}\]In Equation (2), \(\epsilon\) is the privacy budget, a smaller \(\epsilon\) implies stronger privacy protection, while a larger value indicates the opposite.
# Offloading of Atomic Tasks in Satellite Networks:
## 3 Task Offloading Model
### Local Calculation Model  
Satellites generally have a certain degree of computing power. We define the time consumption of low-medium orbit satellites as follows,  
\[T_{s,q}^{lm}=\frac{n_{q}}{a_{s}^{lm}}. \tag{2}\]  
As shown in Equation (2), \(T_{s,q}^{lm}\) denotes the time required for the atomic mission to calculate locally on the satellite \(s\), \(n_{q}\) denotes the number of computing resources required for atomic tasks, \(a_{s}^{lm}\) denotes the computing power of the low-medium orbit satellite's CPU. Similarly, the time consumption of high-orbit satellites can be defined as the following formula,  
\[T_{s,q}^{h}=\frac{s_{q}}{r_{u,v}}+\frac{n_{k}}{a_{s}^{h}} \tag{3}\]  
where \(T_{s,q}^{h}\) denotes the time required to calculate task \(q\) on the high-orbit satellite \(s\), \(n_{q}\) denotes the number of computing resources required for task \(q\), \(a_{s}^{h}\) denotes the computing power of high-orbit satellites, \(s_{q}\) denotes the data volume of task \(q\).
# Game theory-based Routing for Wireless Sensor Networks: A Comparative Survey
## 3 Game Theory-Based Routing Protocols in WSNs
### Routing Protocols Based on Noncooperative Games
#### 3.2.6 Game Theory-based Energy-efficient Routing Algorithm (GERA)
Technical weaknesses:
* It is basically an extension of the LEACH protocol [68], with an improvised method of CH selection using game theory. The authors did not elaborate on the intra-cluster communication between the CMs and CH. Further, an effort should have been made to explain the LEACH protocol for a better understanding of GERA;
* The protocol cannot adapt to any kind of topology change and node failure. Applications:
* GERA can be applied to typical static WSNs that are not subjected to any kind of topology change. Possible future improvements:
* Explanation of intra-cluster time slotting can be added;
* Routing metrics like end-to-end delay and latency can be introduced for performance comparison.
# Studies on the Electrochemical Behavior of Sulfite on Incoloy 800 in a Neutral Environment
## 2 Materials and Methods  
A 250 mL three-electrode undivided cell connected to the equipment SP 150 Bio-Logic potentiostat/galvanostat (BioLogic, Seyssinet-Pariset, 38170 France) was used during all measurements. The working electrode was a disk of Incoloy 800 with an active surface of 1 cm\({}^{2}\). The elemental composition of Incoloy 800 is given in Table 1. Two graphite bars were used as counter electrodes and Ag/AgCl as the reference electrode (all potentials \(E\) are given versus the reference electrode Ag/AgCl, \(E_{Ag/AgCl}\) = 0.197 V). Sodium sulfate Na\({}_{2}\)SO\({}_{4}\) (Merck p.a. 99%, Merck KgaA Darmstadt, Germany) and sodium sulfite Na\({}_{2}\)SO\({}_{3}\) (Merck p.a. 98%, Merck KgaA Darmstadt, Germany) were used to prepare the electrolyte solution. Deionized water was used.  
Electrochemical experiments were performed in 1 mol L\({}^{-1}\) Na\({}_{2}\)SO\({}_{4}\) solution with pH 7 in the absence and presence of different sulfite concentrations (10\({}^{-3}\), 10\({}^{-2}\), 10\({}^{-1}\), 5 \(\times\) 10\({}^{-1}\), and 1 mol L\({}^{-1}\)) without any pretreatment of the electrode. Cyclic voltammograms were recorded at different scan rates (5-500 mV s\({}^{-1}\)) and linear bias at low scan rate (1 mV s\({}^{-1}\)) to ensure quasi-stationary conditions.
# Digitalizing Industrialized Construction Projects: Status Quo and Future Development
## 4 Qualitative Analysis
### Production Phase
#### 4.2.3 Quality Inspection  
Quality inspection entails the application of digital technologies such as 3D laser scanning and BIM to evaluate the geometric dimensions, surface quality, and other quality parameters of precast elements during the production process. This ensures the timely correction of quality issues to meet design specifications.  
The increased utilization of precast concrete elements (PCEs) in industrialized construction necessitates meticulous inspections to ensure compliance with specified tolerances, but manual inspection often leads to the delayed detection of geometric errors, due to a lack of systematic data storage and transmission mechanisms. To address this, [PERSON] et al. [55] presented an end-to-end framework for PCE dimensional and surface quality assessment, incorporating inspection checklists, procedures, scanner selection, and data storage methods. [PERSON] et al. [56] proposed a dimensional quality assessment system leveraging 3D laser scanning and BIM, catering to the growing demand for dimensional quality control. Similarly, [PERSON] et al. [57] introduced a laser scanning-based dimensional quality assurance technique that can achieve a measurement accuracy of 3 mm. Additionally, [PERSON] et al. [58] proposed the use of a Terrestrial Laser Scanner to concurrently scan multiple PCEs, convert 3D point cloud data to 2D images, and adopt the Rotated Binary Neural Network algorithm to achieve automatic segmentation from the as-designed BIM model. This approach streamlines the extraction of diverse PCE types from extensive laser scanning data, thereby enhancing inspection efficiency.  
The current state of research on the production phase of industrialized construction encompasses several key areas. First, digital manufacturing employs tools such as 3D printing and CNC to enhance the customization, sustainability, and productivity of precast elements, despite ongoing concerns about the accuracy of some techniques. Second, process optimization strategies enhance flexibility in response to varying demands, resulting in improvements in efficiency and quality. Third, quality inspection methods that integrate laser scanning and BIM support dimensional compliance checking, though further advancements in practicability are necessary.