esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Inhibition of Chinesterases (ChEs)  
To evaluate the inhibition of ChEs (AChE and BChE), the spectrophotometric method of [PERSON] with minor modifications [13], was used. AChE (Electric eel AChE, EC 3.1.1.7), BChE (equine serum BChE, 3.1.1.8) acetylthiocholine iodide (ASCh), butyrylthiocholine iodide (BSCH) and 5,5'-dithio-_bis_-(2-nitrobenzoic acid) (DTNB) were purchased from Sigma-Aldrich (Milan, Italy). The assay was performed by a double beam UV-Vis lambda 40 Perkin Elmer spectrophotometer, using optical polystyrene cuvettes (10 10 45 mm, 340-800 nm optical transparency). Each extract was dissolved in methanol/water (70:30 \(v/v\)) in the opportune quantity in order to obtain a final cuvette organic solvent content that does not affect the enzyme activity (<0.1%). Peel and pulp were diluted to a concentration of 100 mg mL\({}^{-1}\), while seeds were diluted to 25 mg mL\({}^{-1}\).  
A total of 3.0 mL of 0.1 M (pH 7.4) phosphate buffer containing DTNB (0.25 mM) and ChE (0.083 U mL\({}^{-1}\)) were placed in a polystyrene cuvette of 1.0 cm path length; 1 \(\upmu\)L of a solution of the tested extract was added. Then, 30 \(\upmu\)L of a 10 mM aqueous solution in phosphate buffer (pH = 7.4) of ASCN or BSCH was added to achieve a final concentration of 100 \(\upmu\)M of substrate. The increasing amount of the yellow 5-nitro-2-tio benzoic anion (Amax 412 nm), produced by the enzymatic hydrolysis of the substrate, was recorded at 25 \({}^{\circ}\)C between 0.5 and 1.5 min. The control without inhibitor, corresponding to 100% of the enzymatic activity, was prepared in the same way. Each experiment was repeated in triplicate. The percent inhibition was calculated using the following equation:  
\[\text{inhibition }(\%)=\frac{A_{c}-A_{i}}{A_{c}}\times 100\]  
where \(A_{i}\) and \(A_{c}\) represent the change in the absorbance in the presence of inhibitor and without inhibitor, respectively.
## 3 Our Proposed Method
### Pre-Processing with Image Fusion  
Image fusion combines multiple images from different sources into a single image containing information from all the input images. Image fusion aims to create a new image with improved features compared to the individual input images. This can include improved resolution, increased contrast, or reduced noise [26; 27]. When two frames from a video sequence are fused, the aspects of motion that contribute to scene interpretation and categorization are brought to the forefront [86].  
The proposed method involves taking a sequence of 32 frames from a video, converting them into grayscale, segmenting them to isolate human appearance, and resizing them to 128 \(\times\) 128. The aim is to create four fused images that are then fed into a previously developed 4-branch 3D CNN model (4S-3 DCNN), with each image being processed by a separate branch. To obtain these four fused images, a fusion process using three levels of image fusion was proposed. Initially, every odd frame is fused with the following frame, resulting in 16 fused frames. The same fusion approach was then performed for the second and third levels, resulting in eight and four pre-processed images by fusion, respectively. Figure 5 provides an example of how this three-level image fusion process generates four fused images from the 32 frames that were grayscale-converted and human-appearance-segmented.  
The formulation for the three-level image fusion is as follows:  
First-level fusion for 32 images:  
\[A_{1}=fuse(F_{1}+F_{2});\ \ A_{2}=fuse(F_{3}+F_{4});\dots\ \ A_{16}=fuse(F_{31}+F_{32})\]  
Second-level fusion for 16 images:  
\[B_{1}=fuse(F_{1}+F_{2});\ \ B_{2}=fuse(F_{3}+F_{4});\dots\ \ B_{8}=fuse(F_{15}+F_{16})\]  
Third-level fusion for 8 images:  
\[C_{1}=fuse(B_{1}+B_{2});\ C_{2}=fuse(B_{3}+B_{4});\ C_{3}=fuse(B_{5}+B_{6});\ C_{4}=fuse(B_{7}+B_{8});\]
# Enhancing Ability Estimation with Time-Sensitive IRT Models in Computerized Adaptive Testing
## 4 Model Performance and Results Analysis
### First Computational Approach Analysis  
The first approach implemented direct parameter estimation without cross-validation, making it computationally efficient but potentially prone to overfitting. While it incorporated basic regularization to constrain parameter values, it lacked hyperparameter tuning and extensive evaluation across different data splits. The results indicated that the 1 PL-IRT model (standard IRT) performed the best, achieving a relatively low AIC (1776.87) and BIC (1961.77) while maintaining a high AUC (0.712). The TP-IRT model exhibited comparable performance, though it had slightly lower AIC/BIC values (1773.15/1960.13), suggesting a minor trade-off between model complexity and fit. In contrast, TWD-IRT and NRT-IRT models demonstrated significantly lower AUC values (0.693 and 0.681, respectively), along with higher AIC/BIC scores, indicating that these transformations introduced instability rather than improving predictive accuracy. The STP-IRT model performed worse than expected, showing elevated AIC/BIC values (2118.26/2305.23) and a low AUC (0.692), which suggests that subtracting a scaled time ratio negatively impacted likelihood estimation. Despite these variations, test information (TIF) remained relatively stable across models, reinforcing that the 1 PL-IRT framework effectively captures student ability with minimal modifications.
# A Study of Precision Current Efficiency Curve Measurement with a Casing-Type Anode
###### Abstract  
Electrochemical machining (ECM) is a non-traditional machining technology that is widely used in the manufacturing of key components in the aviation industry. The current efficiency is defined as the ratio of the observed amount of dissolved metal to the theoretical amount predicted from [PERSON]'s law. In ECM, the current efficiency curve relates the dissolution rate of the anode material and the current density. Accurate measurement of the current efficiency curve is the basis for anode shape prediction and cathode tool design. However, in conventional measurement methods, the phenomenon of edge stray corrosion introduces significant measurement errors. Improving the current efficiency is thus a challenging task for any electrophysical or electrochemical machining process. To improve the measurement accuracy, this paper proposes a current efficiency curve measurement with a casing-type anode. In the proposed measurement method, the anode is designed in two parts: the mandril and the casing. The edge stray corrosion effect is mainly concentrated on the casing, and only the current distribution on the mandril is considered in the calculation of current efficiency. The measurement simulations of the conventional and the proposed methods were carried out. The simulation results show that the casing-type method significantly improves the accuracy of current efficiency measurements, and the current efficiency curve of 304 SS was obtained.  
electrochemical machining (ECM); current efficiency; measure theory; electric field; dissolution rate +
Footnote †: journal: Applied Sciences
## 2 Material and Methods
### Data Sources  
The information utilized in this study includes meteorological, LUCC (land use and land cover changes), terrain elevation, NDVI, soil properties, and socioeconomic data. Terrain elevation data (30 m) were retrieved from the Geospatial Data Cloud [[http://www.gscloud.cn/](http://www.gscloud.cn/)]([http://www.gscloud.cn/](http://www.gscloud.cn/)) (accessed on 20 April 2024) and used to determine the slope length slope factor LS in the RUSLE model for 2000 to 2050. The soil type data were a 1:1 million scale map of Chinese soils, including sand, silt, and clay data of different soil types, which were used to obtain the K-factor for soil erodibility. NDVI (1 km) data in China were used to calculate surface vegetation cover and management factor C. Precipitation data at 1 km resolution were used to calculate rainfall erosivity factor R. Data for factors R, K, and C (2000-2020) were obtained from the Chinese Academy of Sciences Resource and Environment Science  
Figure 1: Location map of the warm temperate forest-farming subregion in the northeast of Loess Plateau, China.  
Data Center [[http://www.resdc.cn](http://www.resdc.cn)]([http://www.resdc.cn](http://www.resdc.cn)) (accessed on 20 April 2024). The rainfall erosivity factor R for the period 2025-2050 was obtained from [PERSON]'s team at the National Qinghai-Tibet Plateau Science Data Center. In this study, the C factor for 2025 to 2050 was used as the average value of the C factor for 2000 to 2020 based on previous experience [30]. Data on land cover types from 2000 to 2020 were obtained from the team of [PERSON] of the School of Remote Sensing at Wuhan University [31] and included cropland land, woodland, grassland, water areas, construction land, unused land, and wetland. The conservation practice factor P for the years 2000 to 2020 was calculated using data with a spatial resolution of 30 m. The distributions of future land use generated from the PLUS model were used to construct P for 2025-2050.
###### Abstract  
In this study, a sliding mode control (SMC) algorithm was proposed based on a novel reaching law to solve the nonlinear disturbance problem of a ground-based laser communication turntable. This algorithm is a chatter-free method, in which the coefficient of sliding mode variable structure function is designed as an adaptive function, so the chattering of the sliding mode approaches zero. For any perturbed system, this algorithm can ensure a finite time for the system state to reach the sliding mode surface from any initial state. Additionally, the system will stabilize in the quasi-sliding mode domain (QSMD) with \(O(T^{3})\) width, where a narrower QSMD width corresponds to stronger robustness toward nonlinear disturbances. Both mathematical calculations and simulations verified the sliding mode and stability of this control algorithm. Experimental results of the velocity closed-loop of pitch axis show that the proposed algorithm effectively improved the anti-nonlinear disturbance ability of the control system compared with the effects of the traditional digital PID and the existing chatter-reduced SMC algorithms, for smooth system operation.  
reaching law; sliding mode control (SMC); ground-based laser communication turntable; chatter-free; quasi-sliding mode domain (QSMD) +
Footnote †: journal: Applied Physics Letters
# Control for Ship Course-Keeping Using Optimized Support Vector Machines
## 5 Conclusions  
In this paper, SVM is applied to the control of a cascaded system with uncertainties with regard to ship course-keeping. The dynamics of the rudder actuator are considered in the plant. To guarantee the real-time performance of the controller, the Lagrangian factors in SVM are determined by on-line tuning algorithms. There are two advantages of the on-line SVM proposed in this paper over conventional on-line SVM. First, no supervised signal is required; second, the capacity of the training samples can be small, which improves the efficiency of the learning machine. Nonlinear functions and an uncertainty (modeling error) in the plant can be effectively identified by the proposed SVM, which helps obtain a controller with simple structure. Another method, L2-gain design, is applied to suppress the disturbance to the plant. The validity of the hybrid controller based on SVM and L2-gain design is confirmed by numerical simulation.  
PSO is used to obtain the parameters in SVM. It should be noted that the optimal parameters are actually obtained in off-line way instead of on-line way, which limits its practical application to real-time control. In the next work, an on-line approach to the selection of SVM parameters will be studied.  
**Acknowledgments:** This work was partially supported by the National Natural Science Foundation of China (No. 51505087), the Special Item supported by the Fujian Provincial Department of Ocean and Fisheries (No. MHGX-16), and the Special Item for University in Fujian Province supported by the Education Department (No. JK15003).  
**Author Contributions:** [PERSON] and [PERSON] analyzed the data; [PERSON] wrote the paper.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 5: Simulation results using SVM controller in combination of inverse dynamic compensation.
## 5 Discussion on Clinical Named Entity Recognition
### Challenges in Clinical NER  
* Nested Entities and Ambiguity: Most clinical terms are often confusing as there is no common ontology. Physicians often use abbreviations or acronyms, which makes it very difficult to standardize clinical text. In the radiation oncology domain, a common challenge is that physicians dictate their clinical assessment based on the style they were trained in and it varies significantly for different types of cancers, which makes it very difficult to develop a standard NER model for processing radiation oncology notes that cater to all of the different types.
* Meaning of Context: The clinical terms used can have different meanings, which vary based on the context. Although this problem mostly applies to non-clinical notes, for clinical NER, this becomes more challenging as the model should understand the complete clinical context along with the entity. A common issue is negative medical findings, where text is written in such a manner that it reports findings in a negative context; however, the NER considers that as a positive.  
Figure 5: Clinical NER models available for text in different languages.  
To address the nested entities and ambiguity, there are efforts to standardize the nomenclature of clinical entities [53; 54]. However, this is still in an initial phase, and to be successful, it needs to be widely adopted.
## 2 Materials and Methods
### Extraction of Remote Sensing Scene Image Elements Based on k-Means Clustering  
The k-means clustering algorithm is a conventional clustering method that uses space efficiently. Clustering methods divide data into several groups. Based on the defined measurement standard, the data in a given group is more similar to other groups of data. The calculation of similarity involves detecting the distance between the data object and the cluster center. The closest distance to the cluster center is divided among the cluster. The procedure is given as follows. First, randomly select k objects that initially represent the average or center of the cluster. Each other object is allocated to the nearest cluster according to its distance from the center of each cluster. Then, calculate the average value of each cluster again to find the center of the cluster, and reorder the clusters accordingly.  
Figure 1: An overview of our proposed method.  
This process is repeated until the criterion function converges. The time complexity of this algorithm is \(O(nkt)\), where \(n\) is the number of all objects, \(k\) is the number of clusters, and \(t\) is the number of iterations.  
In this study, we used a k-means clustering method to segment remotely sensed scene images. We inputted the image as a matrix into the algorithm, specified the parameter k for clustering (that is, segmentation) and finally, achieved the purpose of extracting elements in the scene.  
The proposed method uses the k-means clustering method to segment scene images. A set of RSSIs is input into the algorithm, and subsequently, the separated images are obtained. However, these images still cannot be used to extract the elements in the RSSIs. This is because both the background part and the element part that are divided contain some noise data, which are expressed as dense or washed-out blobs or obstructions in the image. Therefore, to extract the elements through the segmented image, we must first preprocess it.
## 2 Materials and Methods  
### Design, Ethics, and Participants  
A total of 56 participants who attended the physical therapy and health research center between August 2021 and January 2023 and met the inclusion criteria were enrolled in the study. The following inclusion criteria were used to select participants with CAI for the scientific study: (1) individuals who experienced multiple ankle sprains in the past, indicating a chronic instability of the ankle joint; (2) participants who reported persistent symptoms related to ankle instability, such as a feeling of giving way, instability during weight-bearing activities, or chronic pain/discomfort; (3) objective assessments, such as positive anterior drawer test, talar tilt test, or other clinical measures, indicating ligament laxity or mechanical instability of the ankle joint; (4) participants with a documented history of ankle instability symptoms for a minimum duration of, for example, six months or longer; (5) a specific age range for participants, such as adults between 18 and 40 years old; and (6) a score of 25 or less on the Cumberland Ankle Instability Tool [30]. Individuals with a history of lower extremity injury or surgery, neuromuscular or vascular diseases in the lower extremity, limb fractures, pregnancy, or those who were unable to understand or follow commands given by the examiner were excluded. Notably, the study did not involve any specific treatment outcomes but rather aimed to investigate the relationship between ankle JPS and balance in individuals with CAI. Ethical approval was obtained from the King Khalid University-approved scientific ethics committee (REC#24-09-2021). Before taking part in the trial, each subject provided their written consent after receiving appropriate information. The rights, well-being, and privacy of the participants were ensured throughout the research process.  
The outcome assessments in this research were conducted by a physical therapist with extensive experience in musculoskeletal physical therapy following the completion of a Ph.D. To ensure impartiality, a separate evaluator, who had no prior knowledge of the study's protocol, documented the outcomes.
# Study of the Dynamic Adaptive Calculation Method for River Water Environmental Capacity
## 4 Results and Discussions
### Water Environmental Capacity Calculation
#### 4.1.3 Monthly Scale  
The WEC of COD and NH\({}_{3}\)-N at 50%, 75%, and 90% design frequencies for each water function area in the Shaanxi section of the Wei River from January to December has been calculated. In this paper, the Gansu-Shaanxi buffer zone of the Wei River was taken as an example to analyze the monthly changes in WEC. Figures 12 and 13 are the monthly WEC change trend of COD and NH\({}_{3}\)-N in the Gansu-Shaanxi buffer zone of the Wei River.  
Figure 11: The calculation results of NH\({}_{3}\)-N WEC in different water periods based on the standard model.  
Figure 10: The calculation results of COD WEC in different water periods based on the standard model.  
It can be seen from Figures 12 and 13 that the monthly WEC within the year is significantly different. The WEC in September is the largest from January to December, accounting for approximately 16.53% of the annual WEC. This is followed by October and August, which together account for about 25.13% of the annual WEC. The third largest WEC values are observed in July and May, while the WEC in June is slightly smaller. The WEC in February and March is the smallest relatively, accounting for only 1.73% of the annual WEC. The monthly WEC throughout the year is ranked as follows: September \(>\) October \(>\) August \(>\) July \(>\) May \(>\) June \(>\) November \(>\) April \(>\) December \(>\) January \(>\) March \(>\) February.
# Personal Protective Equipment as a Potential Source of
## 4 Discussion
### Identification of Other Plasticizers and Plastic Additives in PPE  
The major plastic additives found in the PPE analyzed in this study were identified to explore any possible health risk. Only the major compounds with large peaks in the chromatogram were selected for tentative identification because most of the main additives are added to plastic products in the percentage range (% _w/w_) [48].  
Notably, cloth masks contained various types of plasticizers and other additives, while disposable procedure masks were free from any major additives other than the detected target phthalates. Most of the identified additives were used as alternative plasticizers to regulated phthalates [49; 50]. In total, three organophosphates were also detected in a reusable cloth face mask. This group of additives is widely used as plasticizers and flame retardants in various products [51; 52; 53; 54]. A recent study reported a number of organophosphate compounds detected in face masks at levels reaching up to 27.7 ug/mask [54]. Organophosphates are emerging pollutants raising increasing concern due to their reported toxic effects, such as endocrine- and reproductive-function disruption [54]. However, the toxicological data on most alternative plasticizers are limited; therefore, it is challenging to draw solid conclusions regarding their safety [55; 56].  
Disposable plastic gloves contained no phthalate plasticizers other than the six target analytes. However, 81% of the analyzed glove samples were found to contain phthalate alternatives such as DOIP, which was found in all the vinyl gloves. DOIP belongs to the class of isophthalate ester plasticizers, which are considered to be among the next generation of phthalate alternatives [57]. Usually, non-phthalate plasticizers are declared by manufacturers to be safer alternatives to phthalates and to have no substance-related toxicity. However, increasing evidence is showing that many non-phthalate plasticizers exhibit various toxic effects on humans and could pose a substantial health concern [57].  
In addition to DOIP, TBC is another non-phthalate plasticizer that was identified in two vinyl glove samples. TBC has been reported to be a safer alternative to phthalates and biocompatible plasticizers [58; 59]. It has numerous applications in the polymer industry, particularly for the synthesis of PVC polymers used for food contact materials [59].  
Fatty acids and hydrocarbons are used in plastic formulations as secondary plasticizers, in addition to performing other roles, such as lubrication [60]. These additives were identified in latex, nitrile, and polyethylene glove samples analyzed in this study. Moreover, fatty acids and their derivatives are receiving increasing attention as natural-based plasticizers because of their low toxicity and low migration [61].