esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Establishing a Rescreening Method for Mutant Strains
#### 3.2.2 Developing a New Method to Assess NM Potency in Fermentation Broth  
Currently, cylinder plate and HPLC methods are routinely used to determine antibiotic potency [37; 38; 39], but they are unsuitable for high-throughput mutant strain screening. To address this, we established a method to rapidly determine NM potency in the fermentation broth. TB is an azo dye that reacts with NM to induce a color change and obvious absorption peaks [31]. Therefore, TB was used to detect NM potency in the fermentation broth. The blue complex formed by the NM/TB reaction generated a maximum absorption peak at 678 nm using full-wavelength scanning on a microplate reader (Figure 4C).  
Next, we assessed different volumes of TB solution (1.0 \(\times\) 10\({}^{-4}\) mol/L) on absorbance at different NM standard potency levels. When the NM potency standard was between 1.284 and 10.272 U/mL, and the volume of the TB solution (1.0 \(\times\) 10\({}^{-4}\) mol/L) was between 100 and 400 \(\mu\)L, NM potency and absorbance were not linear (Figure 4D). This suggested that the TB volume was inadequate for NM and TB to form a blue complex. Therefore, the volume of TB solution (1.0 \(\times\) 10\({}^{-4}\) mol/L) was increased; at 500 \(\mu\)L, the absorbance  
Figure 4: Optimization of the rescreening method for high-producing NM mutant strains. (**A**) Fermentation correlations between 24-deep well plates and 250 mL shake flasks; (**B**) Fermentation correlations between 48-deep well plates and 250 mL shake flasks; (**C**) A full-wavelength scan of TB and NM reaction solutions; (**D**) The influence of different TB volumes (1.0 \(\times\) 10\({}^{-4}\) mol/L) on the absorbance at different NM standard potencies; (**E**) A NM standard curve; (**F**) Correlations between TB spectrophotometry using a microplate reader and HPLC for NM potency determination.  
displayed a good linear correlation with the NM potency and a good linear equation was obtained (Figure 4D,E).  
\[Y=0.0320\ x-0.0262\ (R^{2}=0.9988), \tag{12}\]  
Furthermore, spike-and-recovery experiments were conducted to verify method accuracy. These showed an average recovery rate of 98.4684% and \(RSD=3.2700\%\) between low level (3 \(\upmu\)g NM standard) and high level (15 \(\upmu\)g NM standard) standards (Table 2). Thus, our method was highly accurate for detecting NM potency in the fermentation broth.  
Finally, we used this new method and HPLC to simultaneously detect NM potencies of 25 mutant strains fermented in 24-deep well plates. These data indicated a high correlation coefficient (\(R^{2}=0.9117\)) between this method and HPLC (Figure 4F), which suggested the new method could replace HPLC. Additionally, the new method was not only rapid (10 min) but simultaneously determined NM potencies in many samples. Therefore, this TB spectrophotometry-based microplate reader method was suitable for the high-throughput screening of mutant strains.
###### Abstract  
This study aims to evaluate the impact of a single session of intraaoral and extraoral photobiomodulation (PBM) on controlling pain and improving a patient's daily activities following surgical extraction of the impacted mandibular third molar, using combined three wavelengths: \"445 nm, 660 nm, and 970 nm\". A pilot study was conducted on 22 patients undergoing extraction of an impacted mandibular third molar. The patients were randomly divided into two groups: (1) The Test Group consisted of patients subjected to immediate postoperative PBM. The extraoral PBM parameters were power = 550 mW and spot area = 5 cm\({}^{2}\), while the intraaoral parameters were power = 200 mW and spot area = 2 cm\({}^{2}\). (2) The Control Group consisted of the patients not subjected to PBM. For all the patients, the pain was evaluated via a Numeric Rating Scale (NRS) on day 0, day 1, day 3, and day 7 after surgical intervention. The patient's daily activities were evaluated on day 7 via a custom-made questionnaire. A statistically significant difference was observed between groups in the pain NRS scores on day 0 (\(p\) = 0.022), day 1 (\(p\) = 0.047), and day 7 (\(p\) = 0.028). No significant difference was found on day 3 (\(p\) = 0.153). A marginal statistical significance was observed with the number of painkillers taken (\(p\) = 0.054). No significant difference was observed with the questionnaire score (\(p\) = 0.206). This pilot study showed a significant reduction in postoperative pain on days 0, 1, and 7 with a single session of intraaoral and extraoral PBM. However, the number of painkillers taken and the scores of the daily activities questionnaire did not show statistical significance despite the observed better results in patients subjected to PBM.  
diode laser; photobiomodulation; pain; surgical extraction; mandibular third molar Article
# Robust Damage Estimation of Typhoon Goni on Coconut Crops with Sentinel-2 Imagery
## 6 Discussion
### Limitations of Our Study  
Assessing subtle damages to the foliage of coconut trees is difficult. Collecting data on the ground via field studies would yield the most accurate reference data, but does not scale to large areas, and is too time-consuming to be applied directly after an event. Furthermore, after typhoons and similar events the affected regions are often hard to access. We resorted to assessing the performance of our model with the help of commercial VHR satellite imagery of several sample regions scattered across the impact zone. We manually analysed those images, and assessed specific changes in 87 diverse locations with these images, these results show that observable changes can be detected with a very high performance (88.9% accuracy); but subtle changes are hard to recognise and presumably were not always detected.  
Another current limitation is that the correlation between reduced canopy coverage and yield is not well understood. Although one can expect reduced foliage to have an impact on overall tree health and ultimately yield, and a correlation between leaves and unripe fruit being torn off, the precise relationship is unknown and requires a more thorough investigation. We note that the relation between plant health and yield has been observed for other crops like wheat [73], parsley [74] and almonds [75].
# A Chest Strap-Based System for Electrocardiogram Monitoring
## 2 Methodology
### Classification Model for Exercise Intensity Assessment
#### 2.3.2 The Calculation of the Positions of Time Domain Feature Waves in ECG Signals  
ECG signals contain numerous and densely distributed time domain feature waves, making it challenging to identify each wave type individually and determine their precise positions. However, since the relative positions of these feature waves remain consistent across cycles, this study employs an R-wave localization approach to identify the time-domain features of ECG signals:  
1. Apply a first-order derivative to the filtered ECG time series signal. The zero-crossing points of the derivative sequence are used to locate all characteristic waves.
2. Use the Pan-Tompkins algorithm to identify the R-wave positions within the signal.
3. Treat each R-wave as a reference point and determine the positions of the other feature waves in each cardiac cycle based on their relative locations to the R-wave.  
The Pan-Tompkins algorithm is an adaptive R-wave detection method that maintains a low false detection rate, even when R-wave amplitudes fluctuate [45]. Its process is illustrated in Figure 6. By applying a dynamic threshold to the moving window integral of the signal and updating this threshold in real time, the algorithm identifies candidate R-peaks that exceed the threshold. It then searches within a specified window in the original signal to locate the highest value among the candidates and confirms it as the true R-peak. The algorithm then proceeds to search for the next R-peak in the following cycle.
## 3 STRP-DBSCAN
### Implementation of STRP-DBSCAN  
The phases of cell graph construction and cell graph merging in STRP-DBSCAN are similar to those in RP-DBSCAN. The pseudo-code implementation of STRP-DBSCAN is shown in Algorithm 2.  
```
Input: Dataset \(D\) containing \(N\) data points, _Eps_, _MintPts_, number of partitions \(k\), approximation parameter _rho_. Output: Data with clustered labels.
1 //Phase I: Data Partitioning.
2 //Partitioning of data using spatial-temporal randomization.
3 {\(P_{1}\),...,\(P_{k}\)} = Spatial_Time_Pseudo_Random_Partitioning(_D_,_Eps_,_rho_,_k_);
4 //Cell dictionary construction.
5 \(M\) = Cell_Dictionary_Building({\(P_{1}\),...,\(P_{k}\)}_Eps_,_rho_);
6 //Inform the constructed cell dictionary to each node in the distributed environment via broadcasting.
7 Cell_Dictionary_Broadcasting(\(M\));
8 //Phase II: Cell map construction (local clustering).
9 //Core cell labelling and subgraph construction.
10 {\(G_{1}\),...,\(G_{k}\)} = Core_Marking_and_Subgraph_Building({\(P_{1}\),...,\(P_{k}\)}_Eps_,_MinPts_);
11 //Phase III: Cell map merging (merged clustering).
12 //Subgraph merging.
13 _newG_ = Progressive_Graph_Merging({\(G_{1}\),...,\(G_{k}\)});
14 //Labelling the points.
15 _newD_ = Point_Labelling({\(P_{1}\),...,\(P_{k}\)}, _newG_);
16 return _newD_;
```  
**Algorithm 2** STRP-DBSCAN  
The computational complexity of STRP-DBSCAN mainly comes from the cell graph construction phase, i.e., the (\(\epsilon\), \(\rho\))-region query in each partition to find candidate cells via the two-level cell dictionary. Therefore, the complexity is \(O\) (\(\log|cell|\)), where \(|cell|\) is the maximum number of cells among all partitions. The complexity of STRP-DBSCAN is the same as that of RP-DBSCAN. However, the \(|cell|\) of STRP-DBSCAN is smaller than that of RP-DBSCAN because STRP-DBSCAN introduces spatial-temporal random partitioning, which achieves a more balanced partitioning of the dataset among computing nodes. Theoretically, STRP-DBSCAN has a lower computational complexity than RP-DBSCAN.
# Evaluation of Different Work Zone Road-Occupation Schemes for Monorail Construction
## 3 Problem Statement and Data Collection  
### Problem Statement  
In typical scenarios, urban road expansion construction often involves the occupation of a particular lane due to the need for maintenance or road widening. During construction, it becomes necessary to temporarily occupy the target lane.  
The rapid increase in the number of motor vehicles in Chinese cities has led to frequent and severe congestion on urban main roads and intersections during morning and evening peak hours. In order to alleviate traffic pressure, more and more places are renovating and expanding urban roads. In addition to widening or designing the alignment of urban roads, cloud rail (suspension rail system) construction has emerged in China in the past two years. The tracks in the suspension rail system can be built on the central median of the road or narrow streets without occupying the road surface separately. It belongs to the medium-volume urban rail transit system with a capacity close to the subway system. During the construction of cloud tracks, it is often necessary to occupy the middle part of urban roads (lanes or central separation strips) for construction equipment stacking or cloud track foundation construction, usually occupying 2-3 lanes during construction. Choosing which lane to occupy in the middle under different traffic conditions has less impact on intersection traffic, which has become an urgent issue for urban reconstruction and expansion projects in China at present. Therefore, this article takes the construction of a monorail at the intersection of a main road in a certain city of Xi'an as a case study. The objective is to investigate the effects of occupying different lanes in the middle during the construction of the monorail on the traffic at the intersection. Additionally, the article offers a calculation method to assist in determining suitable solutions. The intersection is the main road of two urban roads, Zhangba Fourth Road and Jinye Second Road (as shown in Figure 1). The initial lane configuration at this intersection consists of six lanes. There is an auxiliary lane on each side, which is often used as a dedicated lane for buses unless motor vehicles are driving. The speed limit for the north-south main road within the construction operation area is 40 km/h, and the speed limit for the east-west main road is 60 km/h. During the construction period, the innermost lanes of the south entrance and north exit of Zhangba Fourth Road at the intersection were occupied by the construction area. To ensure a balanced number of lanes and smooth traffic, the auxiliary lanes on both sides were used as motor vehicle lanes.
# A Scraper Conveyor Coal Flow Monitoring Method Based on Speckle Structured Light Data
## 5 Application Example and Analysis of Scraper Conveyor Monitoring
### Performance Analysis of Coal Flow Method for Scraper Conveyor  
This paper makes a horizontal comparison between the method in this paper and the existing methods from the aspects of contact type, safety, installation difficulty, monitoring sensitivity, consumption cost, precision, and real-time performance of different methods. From Table 3, it can be clearly seen that the method based on speckle data proposed in this paper has advantages in different performances compared with other existing methods.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Simplification Rate** & **Random** & **Median** & **Median** & **PDS** & **Time/s** \\ \hline
100\% & 98.31\% & 98.31\% & 98.31\% & 98.63\% & 17.6 \\
90\% & 95.30\% & 94.99\% & 95.36\% & 96.85\% & 2.71 \\
80\% & 91.74\% & 91.63\% & 92.05\% & 93.42\% & 1.45 \\
70\% & 88.49\% & 88.35\% & 89.39\% & 91.30\% & 0.81 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of Volume Accuracy of Different Mesh Simplification Algorithms.  
\begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline
**Method** & **Category** & **Safety** & **Difficulty** & **Sensitivity** & **Cost** & **Accuracy** & **Real-Time** \\ \hline Electronic Scale & contact & safe & difficult & not sensitive & cheap & low & real-time \\ Nuclear Scale & contact & unsafe & difficult & not sensitive & cheap & middle & real-time \\ Computer Vision & non contact & safe & not difficult & sensitive & cheap & middle & not satisfied \\ Ultrasound & non contact & safe & not difficult & sensitive & cheap & middle & real-time \\ Lidar & non contact & safe & not difficult & not sensitive & expensive & high & not satisfied \\ Speckle Data & non contact & safe & not difficult & not sensitive & cheap & high & real-time \\ \hline \hline \end{tabular}
\end{table}
Table 3: Performance comparison of different methods.  
Figure 14: Scraper conveyor flow monitoring diagram: (**a**) Time interval (0–200); (**b**) Time interval (200–400); (**c**) Time interval (400–600).
# Fragile Watermarking of 3D Models in a Transformed Domain
## 7 Discussion  
The proposed fragile watermarking algorithm for 3D models performed a watermark bit string embedding by modifying the least significant part of some vertices' attributes (in the present embodiment, coordinates): the watermark was stored in a secret space defined by a secret KLT basis and protected the integrity of the structure of the 3D model, that is the polygon mesh and the vertices of these polygons. Thus, the security of the method lied in the secrecy of the vectors used to derive the KLT kernel.  
The main advantages of the method were:  
* the proposed method was very general because it worked on single vertices and may be extended to protect any number of vertex attributes (like normals, texture properties, etc.), even without modifying the KLT basis size: for example, by applying the cryptographic hash function also on these attributes and XORing the result to the fingerprint \(F\);
* the watermark was embedded into the vertices without tying to a particular representation of the model, i.e., vertices could be changed in order as long as the polygons were updated accordingly;
* modifications to the data were limited to the least significant bits of the mantissa value, so keeping the relative error as small as possible;* affine transformations to the 3D models were allowed (no tampering was shown), as long as they were represented and stored as matrix operations to be applied to vertex coordinates (this is the default Blender behavior). At the same time, the disadvantages of the method were:
* a slight change to the vertices' coordinates was performed;
* if a vertex was duplicated in the 3D model, after watermark embedding, two vertices with different coordinates and/or normal components would be created; thus, small holes or changes in illumination in the vertex area were created; this issue could be solved by recognizing coincident vertices and modifying them in the same manner during watermark embedding; it was possible to perform this action because it was highly probable that both vertices allowed for an equal modification embedding different watermark strings.
# Optimized Parameter Search Approach for Weight Modification Attack Targeting Deep Learning Models
## 4 Experiment
### Experiment Parameters  
The experiment depends on the configuration of the following parameters that allow varying numbers of modified weights, the targeted cluster, and the strategy used:  
* \(k\):= the upper limit of the number of modified weights.
* \(c_{n}\):= the cluster \(n\) to be misclassified, where \(n\in\mathbb{N}\).
* \(m_{f}\):= the method used to incorporate the noise, where \(f\in\{sum,sub\}\). Note that, \(sum\) indicates the summation method and \(sub\) indicate the subtraction method.
* \(\epsilon\):= magnitude of the noise added in each step.
* \(s\):= number of steps used to generate the attack.  
Moreover, these parameters define a configuration \((k,m_{f},c_{n},\epsilon,s)\), where the attack is implemented with \(k\) modified weights, \(m_{f}\) indicates the method used, with the target cluster \(c_{n}\) using \(\epsilon\) magnitude noise and \(s\) number of steps. For each \((k,m_{f},c_{n},\epsilon,s)\) configuration, the accuracy of each cluster defined in the input data is shown in Section 5. Suppose that \(\phi\) is the attacked model and \(l_{c_{p}}\) are the original labels of the elements in a certain cluster \(c_{p}\), then  
\[r_{c_{p}}^{(k,m_{f},c_{n},\epsilon,s)}=\frac{|\{a\in c_{p}|\phi(a)=l_{c_{p}}\} |}{|c_{p}|} \tag{1}\]  
Figure 4: The process to obtain the gradient per cluster.  
Figure 5: The process to select the input neurons with highest impact on the prediction.  
is the result of the \(c_{p}\) for the configuration \((k,m_{f},c_{n},\epsilon,s)\). Defining \(C\) as the cluster with the complete input data, suppose \(C=\{c_{1},c_{2}...,c_{t}\}\) is the set of defined clusters of the input data, \(1\leq n\leq t\) and the configuration \((k,m_{f},c_{n},\epsilon,s)\) is used to generate the attack, then  
\[R(k,m_{f},c_{n},\epsilon,s)=\frac{1+\left(\sum_{i=1}^{t}r_{c_{i}}^{(k,m_{f},c _{n},\epsilon,s)}-r_{c_{n}}^{(k,m_{f},c_{n},\epsilon,s)}\right)}{t+1} \tag{2}\]  
is the main result of the analysis of the \((k,m_{f},c_{n},\epsilon,s)\) configuration. Observe that it is in the interval \([0,1]\). Note that, when the result \(r_{c_{n}}^{(k,m_{f},c_{n},\epsilon,s)}\) decreases, \(R(k,m_{f},c_{n},\epsilon,s)\) increases, and vice-versa if the result \(r_{c_{n}}^{(k,m_{f},c_{n},\epsilon,s)}\) increases. Moreover, if the \(\sum_{i=1}^{t}r_{c_{i}}^{(k,m_{f},c_{n},\epsilon,s)}\) decreases, \(R(k,m_{f},c_{n},\epsilon,s)\) decreases, and vice-versa. Therefore, a high \(R(k,m_{f},c_{n},\epsilon,s)\) value means that the attack is misclassifying mostly the target cluster, and a low \(R(k,m_{f},c_{n},\epsilon,s)\) value means that the attack is misclassifying mostly the rest of the defined clusters. In other words, the objective of the attacker is to achieve as high a value of \(R(k,m_{f},c_{n},\epsilon,s)\) as possible.
## Materials and Methods  
### Study Area  
The study was conducted on typical _Stipa grandis_-dominant temperate steppe (43\({}^{\circ}\)32\({}^{\prime}\)24.06\({}^{\prime\prime}\) N, 116\({}^{\circ}\)33\({}^{\prime}\)41.76\({}^{\prime\prime}\) E, elevation 1250 m) at Xilinhot, Inner Mongolia, northern China (Figure 1). Based on local climate data (1982-2004), the average annual temperature is 0.6 \({}^{\circ}\)C, and the mean daily temperature is \(-\)18.5 \({}^{\circ}\)C in the coldest month (January) and 21.5 \({}^{\circ}\)C in the warmest month (July). Mean annual precipitation is 350 mm, mainly falling in June and August, coinciding with the main growth period. The peak growing month (August) in the steppe area is the second warmest month of the year. The accumulated precipitation in this period was 80.6 mm, and this value contributed more than one fourth of the annual precipitation.  
Figure 1: The location of the study area and the land use of the pastoral farming ecotone in North China. Map was created using ArcMap 10.2 (ESRI, Inc., Redlands, CA, USA. [[http://desktop.arcgis.com/en/arcmap/](http://desktop.arcgis.com/en/arcmap/)]([http://desktop.arcgis.com/en/arcmap/](http://desktop.arcgis.com/en/arcmap/))).  
Soils of the study site are divided into chestnut or chemozem soil, according to the UN Food and Agriculture Organization (FAO) classification. In Xilinhot, which is located at the northern edge of the Chinese pastoral farming ecotone, grazing is the primary land-use pattern [27; 28]. There are also two alternative land uses of the steppe in the region: grazing-exclusion steppe and steppe reclaimed to cropland. The Hunshandake desert, located to the south of Xilinhot, is believed to be an important sand source for sandstorms affecting Beijing. In order to improve environmental conditions in Beijing, the central government of China launched an array of grassland restoration projects to reduce and even forbid/abolish grazing in the Xilinhot region to curb sandstorms [15]. In these areas, grazing-exclusion is the most widely applied practice. To the contrary, as the local environment is considered to be suitable for cropping in some areas of the region, cultivation of the steppe is practiced for crop production with economic considerations.  
Three different land-use patterns which were located adjacent were selected for the study: grazed steppe (G), grazing-excluded steppe (GE), and steppe cultivated to cropland (C). Of these, G is a typical type of steppe that has been grazed by sheep and horses for over 20 years, and GE is steppe in which grazing has been forbidden since 1979, resulting in a a large amount of litter remains on the ground. For C, its original land use and community structure were similar to G until 5 years before the study, when the land was cultivated for wheat cropping. No irrigation was applied to the cropped area. Organic manure was applied before the crop was planted, and 240 kg ha\({}^{-1}\) inorganic fertilizer (N 110 kg ha\({}^{-1}\), P\({}_{2}\)O\({}_{5}\) 70 kg ha\({}^{-1}\), K\({}_{2}\)O 60 kg ha\({}^{-1}\)) was applied in two applications during crop growth.