esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
This study used modified manganese sand as an adsorbent to explore its adsorption effect on iron and manganese ions from groundwater. The effects of pH, manganese sand dosage, and the initial concentration of Fe/Mn on the removal rate of iron and manganese ions were studied through single-factor experiments. Based on the above three factors, a quadratic polynomial model between the adsorption rate and the above factors was established to determine the optimal adsorption conditions. The response surface analysis showed that pH had the most significant effect on the adsorption process. The optimum conditions for the adsorption of iron and manganese ions by modified manganese sand were pH = 7.20, the dosage of manganese sand = 3.54 g/L, and the initial concentration ratio of Fe/Mn = 3.80. The analysis of variance showed that the RSM model could accurately reflect the adsorption process of manganese sand. In addition, we confirmed that the relative error between model predictions and experimental values was close to 1%, proving that the response surface model was reliable. The kinetic data of the manganese sand were described well with the pseudo-second-order model. The isothermal adsorption of iron and manganese ions by modified manganese sand was fitted well using the Langmuir equation.  
modified manganese sand; iron and manganese ions; response surface methodology
## 4 Discussion
### Study Limitations  
It is important to note that ultrasound examinations used in this study were performed in a clinical setting; a common intention was to screen patients who were either newly diagnosed or had not been assessed by a rheumatologist in a while but also to correlate unspecific abdominal symptoms or altered laboratory parameters. The exact reason for the examinations being performed was not always evident from the medical records. While abdominal ultrasound examinations are done regularly during examinations in patients with SARD, we did not perform them at every visit. Therefore, when comparing our findings to previously published studies, there may have been a different approach as to whether and how patients were selected for abdominal ultrasound examinations.  
Ultrasound was performed by either of two experienced physicians. As we analysed retrospective data that were collected in a clinical setting, examination results were not validated by a second sonographer. Changes of findings between visits might partially be attributable to variability between examiners, although abdominal ultrasound has been shown to be reliable and reproducible [36]. Patients with secondary Sjogren's syndrome had different underlying diseases, mostly rheumatoid arthritis (82.1%). It should be noted that in secondary Sjogren's syndrome, we do not know if abdominal ultrasound findings are influenced by the secondary SS, the underlying disease or both. Furthermore, we did we not analyse the relation between ultrasound findings and established disease activity scores, but rather assumed that changes in anti-inflammatory medication reflected the current disease activity. This parameter was chosen for being available for each patient visit and across all SARD entities. We had to rely on the hospital discharge letter while studyingthe impact of examinations on therapeutic decision making. We cannot exclude that these results have been discussed more extensively elsewhere, for instance verbally between examining and treating physicians. Lastly, our cohort was hospitalized in a referral centre. The spectrum of findings might be different in an outpatient setting.
## 4 Discussion
### Multiple Biological Pathways Involved in Regulating the Formation of Terpene Aroma Compounds in WDT  
A KEGG enrichment analysis of WFLs' DEGs revealed prominent pathways including \"plant hormone signal transduction\", \"sesquiterpenoid and triterpenoid biosynthesis\", \"MAPK signaling pathway-plant\" and \"indole alkaloid biosynthesis\". It has been reported that in low-temperature conditions, tea plants absorb nerolidol from their surroundings. This nerolidol is then transformed into bound nerolidol glucoside via the action of UGT enzymes [20]. The presence of nerolidol in tea leaves triggers the activation of mitogen-activated protein kinases (MAPKs) and the production of plant hormones [22]. This is significant because hormone signaling mediates the response of _CsTPS_ to external stresses [37]. [PERSON] et al. [38] further established that these plant hormones amplify the biosynthesis of terpenoid compounds. Therefore, we hypothesize that under low-temperature conditions, tea plants may absorb terpenoids from the surrounding environment. These terpenoids could activate MAPKs and induce the production of plant hormones, which are beneficial for the biosynthesis of terpenoids. Furthermore, during the winter's low temperatures, terpenoids are likely converted into their corresponding glycosides through the action of UGT enzymes. These synthesized terpenoid glycosides have a high potential to transform into volatile terpenoid aroma compounds during the processing of dry tea.  
Tea leaves are subjected to various external stresses during processing. It has been reported that under the dual influence of low temperatures and mechanical damage, tea leaves can respond by synthesizing more indole and nerolidol [39; 40]. The content of indoleand nerolidol in SDT increased by 3001.08 ng/g and 2182.23 ng/g, respectively, while the content of indole and nerolidol in WDT increased by 5444.03 ng/g and 4267.67 ng/g, respectively (Table S3). Interestingly, after processing, defensive compounds such as allo-ocimee, \(\beta\)-cyclodextrin and (\(E\))-\(\alpha\)-bisabolene were only detected in WDT (Table S3) [41; 42; 43]. It is speculated that external stresses during processing stimulated other metabolic processes involved in aroma synthesis, thereby enhancing the aroma of WDT.
## 9 Real-World Applications, Case Studies, and Tools
### Customer Feedback and Support Ticket Triage  
Enterprise adoption of AI annotation agents has accelerated dramatically in customer experience management, where organizations deploy agents to process and categorize massive volumes of unstructured feedback data. E-commerce platforms utilize annotation agents to systematically tag thousands of customer reviews with thematic labels and sentiment indicators, transforming raw textual data into structured insights overnight. Case studies from 2023 demonstrate that support departments implementing LLM annotation agents for ticket triage achieved 90% agreement with manual classification while saving dozens of staff hours weekly. Platforms like UBIAI have commercialized these capabilities, offering integrated systems that automatically label support documents using either zero-shot LLM predictions or domain-specific fine-tuned models [24; 130]. These annotation agents excel at imposing meaningful structure on unstructured business data at unprecedented scale, enabling downstream analytics and workflow automation that would be prohibitively expensive through traditional annotation approaches.
# GIS-Analysis for Active Tectonics Assessment of Wadi Al-Arish, Egypt
## 3 Data and Methods
### Stream Length-Gradient Index (SL)  
Topography development results from an interaction between erosion processes such as rivers and streams over lithology with different rock strengths and soils [6; 52]. The interaction eventually provides a dynamic equilibrium [6]. The stream length-gradient index (SL) was first recognized by [52] while studying the role of the strength of rocks and soils in rivers of the Appalachian Mountain zone in a region of the southeastern part of the United States [6]. This index is calculated as:  
\[\text{SL}=\left(\Delta\text{h}/\Delta\right)\text{l}\]  
where \(\left(\Delta\text{h}/\Delta\right)\) describes the local slopes of the streams being studied and l is the stream length from the dividing point against midpoint center of the stream reach. The SL index is a very effective parameter to assess relative tectonic signals. Usually, this index gives values increasing along channels running over active spots and provides low values when these run parallel to structural elements initiated by major tectonics such as strike-slip faults [53].
## 5 Related Work  
### Spectrum-Based Fault Localization  
Spectrum-based fault localization (SBFL) techniques are widely studied [16; 17; 18; 19; 20; 21], which has been extended in various ways by considering inputs other than statement coverage [1], control flow analysis [2], and data flow analysis [3].  
For example, [PERSON] et al. [1] used the statement coverage information, which applied color to visually map the participation of each program statement in the outcome of the execution of the program with a test suite. This technique recorded the statement coverage status of the test case execution and whether the test case is executed successfully. For each statement in the code, the execution status of the failed test case and the pass test case can help the user locate potentially faulty statements. [PERSON] et al. [14] investigate this diagnostic accuracy as a function of several parameters (such as the quality and quantity of the program spectra collected during the execution of the system). They used the similarity coefficients Ochiai in the field of molecular biology to define the probability of failure of statements in a program. [PERSON] et al. [4] obtained the coverage information of each executable statement and the execution result (pass or fail) with respect to each test case by using a crosstalk-based statistical method.  
In addition, [PERSON] et al. [22] compared the correct runs and failed runs. They assumed the existence of a faulty run and a larger number of correct runs and adopted a technique that compares the spectra corresponding to correct run and faulty run. Then, they produced a report of suspicious parts of the program. [PERSON] et al. [5] presented a technique that obtained a ranking of statements in terms of their likelihood of being faulty by leveraging the result of combinatorial testing. [PERSON] et al. [23] proposed a technique, namely HSFL (spectrum-based fault localization), to leverage the information of version histories in fault localization.
# Experimental Study on Freezing Front Model of Alpine Tunnel under Wind Field
###### Abstract  
In order to study the freezing front characteristics of alpine tunnels under the condition of wind flow field and relying on the Osaka Mountain tunnel in Qinghai Province, the physical model test of an alpine tunnel was built. By using the Surfer software combined with the laboratory test data, the radial and longitudinal temperature variation trends of the tunnel were obtained, and the overall temperature vector graph of the tunnel was simulated; the radial and longitudinal evolutionary laws of a freezing front in an alpine tunnel under airflow conditions were systematically analyzed, and the radial and longitudinal governing equations of a freezing front in the tunnel model under airflow conditions were proposed. The results show that: With the decrease of the test air temperature, the thermonuclear area in the surrounding rock gradually shrinks, the frozen area of surrounding rock at the bottom of the arch gradually increases, and the frozen area of surrounding rock at the top of the arch gradually expands to the interior of the mountain. The influence degree of ventilation on the longitudinal and radial temperature distribution of the tunnel is obvious, and the greater the wind speed, the greater the influence degree. In particular, the fluctuation range of the longitudinal temperature distribution of the tunnel is more extensive under the influence of ventilation. The freezing front distance in the inverted arch area is the largest, and the expansion distance of the freezing front in the wall foot area is obviously higher than that in the vault; the variation of the longitudinal freezing front at different positions of the tunnel shows parabolic attenuation and with an increase in tunnel depth, the trend of freezing front gradually eases and becomes stable and disappears; the three radial regions of the freezing front and the longitudinal quadratic parabola governing equations can predict the specific distribution characteristics of the freezing front at different depths of the tunnel.  
alpine tunnel; wind flow field; freezing front; model test Article
# Interval-Based LDA Algorithm for Electrocardiograms for Individual Verification
## 2 Materials and Methods
### Preprocessing  
We used the ECG data from the MIT-BIH public database to test the proposed algorithm. The MIT-BIH database (MITDB) [34] is the standard ECG database universally used for ECG analyses that contains 48 records of heartbeats collected from 47 subjects; each record was sampled at 360 Hz  
Figure 1: Basic ECG signal cycle.  
Figure 2: Simplified block diagram of the proposed interval-based LDA algorithm.  
and is approximately 30 min long. The subjects were 25 men with ages ranging from 32 to 89 years and 22 women with ages ranging from 23 to 89 years. The data were obtained with a two-channel ambulatory Holter monitor at the Bath Israel Deaconess Medical Center from 1975 to 1979. In most database records, the upper signal is a modified limb lead II(MLII) obtained by placing the electrode on the chest, and the lower signal is usually a V1(occasionally V2 or V5 or V4). Normal QRS complexes are usually prominent in the upper signal, thus, we only used the single lead data (the upper signal, MLII) in the experiment.  
To minimize the negative effect of random noises, we applied the scheme proposed by Sornmo [35] in our study, in which noisy ECG signals are passed through the bandpass filters (BPF) spanning from 0.5 to 200 Hz to reject the DC components and high-frequency noise. Subsequently, we implemented a notch filter and a short-time Fourier transform (STFT) to eliminate the power line interference and its harmonics. Figure 3 shows the preprocessing procedures.
## 2 Methods  
In this section, we provide a detailed description of the proposed dual-driven learning-based MIMO symbol detection method. We begin by presenting a brief overview of the UAV AG communication scenario in urban areas. Subsequently, we introduce the mathematical formulation of the communication system. Building upon this mathematical expression, we outline the MIMO symbol detection problem. Finally, we provide a comprehensive explanation of the proposed dual-driven learning-based MIMO symbol detection method.  
UAV AG Communication Scenario: We start by providing an overview of the UAV AG communication scenario, specifically focusing on an urban area. This setting involves UAVs acting as communication nodes, transmitting and receiving signals from ground base stations. UAVs' high maneuverability enables them to establish wireless links with ground stations (GSs), facilitating efficient communication in urban environments.  
Expression of the Communication System: We present a mathematical formulation that characterizes this UAV AG communication system, which includes wireless channel modeling.  
MIMO Symbol Detection Problem: Based on the mathematical formulation, we identify the MIMO symbol detection problem.  
Proposed Dual-Driven Learning-Based MIMO Symbol Detection Method: Here, we provide a comprehensive description of the proposed dual-driven learning-based MIMO symbol detection technique. This approach combines both model-driven and data-driven networks to enhance the detection accuracy. We delve into the architecture and working principles of the dual-driven network, highlighting the integration of the model-driven OAMP-Net and the data-driven symbol correction network. We elaborate on how the algorithm updates the parameters of both modules simultaneously in each iteration, ensuring effective collaboration between the model-driven and data-driven components.  
By following this structure, we aim to provide a detailed understanding of the proposed dual-driven learning-based MIMO symbol detection method, contextualizing them within the UAV AG communication scenario.
# A Two-Stage Gradient Ascent-Based Superpixel Framework for Adaptive Segmentation
## 2 Conventional Gradient Ascent Method  
### SLIC Superpixel Method  
The principle of SLIC superpixel is very concise to understand, the overall process contains four major steps: initialization, assignment, updating and post-processing. The algorithm can be described as follows:  
* The expected superpixel number \(k\) is assigned manually to determine the grid interval \(S=\sqrt{N/k}\), where \(N\) is the pixel number of the Lab image to be partitioned;
* \(k\) initial cluster centers are initialized on the uniform grid in the image plane and represented as a feature vector \(C_{k}=[l_{k},a_{k},b_{k},x_{k},y_{k}]\), where \(C_{k}\) is composed of \(C_{k}^{c}=[l_{k},a_{k},b_{k}]\) in color space and \(C_{k}^{s}=[x_{k},y_{k}]\) in 2-dimensional space position;
* Each pixel \(i\) is assigned a label in accordance with the nearest cluster center \(C_{k}\) based on a distance measure \(D(i,C_{k})\) as \[D(i,C_{k})=\sqrt{\|C_{i}^{c}-C_{k}^{c}\|^{2}+\rho\|C_{i}^{s}-C_{k}^{s}\|^{2}},\] (1) where \(\rho=100/S^{2}\) is a default factor in [15] to normalize color and spatial proximity, and \(\|\cdot\|\) represents the Euclidean distance;
* A local k-means method is adopted to adjust the center and the labels of pixels in every \(2S\times 2S\) region. This procedure goes until all pixels get new labels and all centers update to \(C_{k}^{\prime}\) as \[C_{k}^{\prime}=\sum_{i\in\Omega_{k}}\bigl{[}C_{i}^{c},C_{i}^{c}\bigr{]}/n_{k},\] (2) where \(\Omega_{k}\) means the cluster centered at \(C_{k}\), and \(n_{k}\) is the number of pixels in \(\Omega_{k}\). This step is iterated until it reaches a predefined global termination;
* The isolated fragments are merged to a final superpixel \(\Omega_{k}^{m}=\{\Omega_{k}\), \(\Omega_{k1}\), \(\cdots\), \(\Omega_{kn}\)] by region growing method, where \(\Omega_{k1}\) indicates a small region unconnected to its cluster but eventually relabeled the same as \(\Omega_{k}\), so that the connectivity among superpixels can be enforced.
# Evolution of Permeability and Sensitivity Analysis of Gas-Bearing Coal under Cyclic Dynamic Loading
## 4 Results and Discussion
### The Influence of the Static Load Stage on the Permeability  
The variation in permeability with the static load stage of the cyclic dynamic load is illustrated in Figure 5. It is evident that there is a positive correlation between the permeability of the coal body and the static load stage. When the static load stages are 0.3 \(\sigma_{c}\), 0.45 \(\sigma_{c}\), 0.6 \(\sigma_{c}\), and 0.75 \(\sigma_{c}\), the permeability of the coal samples is observed to be 0.0137 \(\upmu\)m\({}^{2}\), 0.0144 \(\upmu\)m\({}^{2}\), 0.0152 \(\upmu\)m\({}^{2}\), and 0.0198 \(\upmu\)m\({}^{2}\), with corresponding growth rates of 2%, 7.1%, 13.1%, and 47.2%, respectively. During the elastic stage of coal, the impact of cyclic dynamic loading on permeability is not significant. This is because, during this phase, the internal damage to the coal body is minimal, and the resulting plastic deformations and newly formed cracks are also relatively few. However, before and during the yield stage of the coal mass, its permeability significantly increases, with a maximum increase of up to 47.2% compared to the permeability without dynamic loading. The reason is that, during this stage, the application of cyclic dynamic loads significantly exacerbates the internal damage to the coal body, leading to the expansion of primary fractures and the formation of numerous secondary fractures. It is evident that, when coal seams are subjected to higher stress conditions, they are more prone to damage and abnormal gas outbursts when disturbed by external dynamic loads.
# Simulation of the Infiltration of Fractured Rock in the Unsaturated Zone
## 2 Mathematical Model
### Extended Interface Condition  
As already mentioned in the introduction, in the extended DFEFVM, both pressure and saturation can be discontinuous at matrix-matrix and matrix-fracture interfaces. Therefore, two additional conditions are required to close the system of equations. The first condition concerns volume conservation. It imposes a constraint on the pressure equation at multiplicated nodes. The second condition is the extended pressure condition, which dictates the capillary value at the interface, [PERSON] et al. [61].  
\[\begin{cases}p_{v}^{m}(S_{w}^{m})=p_{c}^{f}(S_{w}^{f})&\text{if }S_{w}^{f}\leq S_{w}^{*}\\ p_{c}^{m}=p_{e}^{m}&\text{otherwise}\end{cases} \tag{8}\]  
where, \(S_{w}^{*}\), stands for the threshold saturation at which capillary pressure in the fracture reaches the entry pressure of the matrix, Figure 2. If the wetting-phase saturation in the fracture is below this threshold value, the capillary pressure in the fracture is higher than the entry pressure of the matrix, and the first condition of (8) is enforced so that capillary pressure is continuous across the interface. When the fracture saturation is higher than the threshold value and capillary pressure in the fracture is smaller than the entry pressure of the matrix, the non-wetting phase cannot leave the fracture. However, this capillary barrier does not stop the flow in the opposite direction. In this situation, capillary pressure is discontinuous across the interface. If matrix and fracture share the same entry pressure, capillary pressure is always continuous across the interface.  
For permeable coarse-grained sandstones and sub-mm fracture apertures, the capillary equilibrium condition may be satisfied. However, for larger fractures, with linear relative permeability curves and capillary pressure conditions imposed by local fracture aperture, this does not apply. In particular, when the maximum capillary pressure in the fracture \(p_{max}^{f}<p_{d}^{m}\), the capillary entry pressure, capillary equilibrium between the fracture and the rock matrix is not possible.  
Figure 1: Triangular finite elements discretising two material patches M\({}_{1}\) and M\({}_{2}\), and node–matched line elements representing three fractures F\({}_{1}\), F\({}_{2}\) and F\({}_{3}\). Manifolds are constructed at multiplicated nodes. This also applies to lower-dimensional fracture manifolds.