esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Analysis of Flavor Nucleotides and Equivalent Ulamami Concentration (EUC)  
Nucleotides could enhance the overall taste of the food through synergistic effects with amino acids [11]. Herein, an assessment was carried out to investigate the effect of the drying method on nucleotides and their relevant compounds, including ATP, ADP, AMP, IMP, HXR, GMP, and HX (Figure 4A, Table S1). IMP, AMP, and HXR were the major compounds in all dry groups, in compliance with the results of past research [15]. The total nucleotide content in oysters was significantly enhanced since drying treatment compared with fresh oysters, with the highest total nucleotide content in the VFD group (400.80 \(\pm\) 15.79 mg/100 g), followed by the HAD group (330.71 \(\pm\) 6.57 mg/100 g), and the lowest total nucleotide content in VD was only 206.86 \(\pm\) 8.27 mg/100 g. Among these nucleotides, GMP, IMP, and AMP are essential sources of oyster umami and taste. The importance of GMP for the umami of seafood has been widely demonstrated [10; 26; 27]. However, the drying process significantly reduces the concentration of GMP in oysters, especially in the high-temperature drying group (HAD and VD). The loss of GMP may be related to its sensitivity to heat [23; 28; 29]. [PERSON] et al. only detected GMP in _Coregonus peld_ meat cooked at low temperatures [18]. The hot-drying process of shitake mushrooms also led to a sudden reduction in GMP [28; 29]. AMP can provide a salty and sweet taste and suppress bitterness in oysters, and IMP alone presents taste and plays a complementary role with monotonous glutamate to enhance oyster umami [8; 15; 29]. The trend of the sum of IMP and AMP in this study was consistent with that of total nucleotides. Subsequently, the nucleotide percentage in different groups was analyzed, and the relative content of IMP and AMP in the dried group increased significantly compared with that of the CK, with the highest relative content in the HAD group (77%), which benefited the quality of dried oysters in the HAD group.  
The umami intensity in fresh and dried oysters was evaluated using the EUC theory (Figure 4B), an essential attribute of oysters. EUC refers to the synergistic umami-enhancing effect of flavor-presenting nucleotides (IMP GMP and AMP) when coexisting with glutamic acid and aspartic acid in a specific ratio to increase the umami intensity. Compared with fresh oysters, the EUC was importance significantly enhanced in the HAD and VFD groups,  
Figure 4: Analysis of nucleotides (**A**) and EUC (**B**) in dried oysters under different drying conditions. CK: blanched oysters; VFD: vacuum freeze drying; VD: vacuum drying; NSD: natural sun-drying; HAD: hot air drying; Different letters indicate significant differences between groups (\(p<0.05\)).  
whereas the results were opposite in the NSD and VD groups, with the highest EUC value in the HAD (51.86 g MSG/100 g), which was 1.42-5.41 times higher compare within other groups. This finding demonstrated that HAD had a significant advantage in obtaining high EUC values, in agreement with the survey consequences of [PERSON] et al. [17].
###### Abstract  
The most common acoustical treatment of public rooms, such as schools, offices, and healthcare premises, is a suspended absorbent ceiling. The non-uniform distribution of the absorbent material, as well as the influence of sound-scattering objects such as furniture or other interior equipment, has to be taken into account when calculating room acoustic parameters. This requires additional information than what is already inherent in the statistical absorption coefficients and equivalent absorption areas provided by the reverberation chamber method ISO 354. Furthermore, the classical diffuse field assumption cannot be expected to be valid in these types of rooms. The non-isotropic sound field has to be considered. In this paper, a statistical energy analysis (SEA) model is derived. The sound field is subdivided into a grazing and non-grazing part where the grazing part refers to waves propagating almost parallel to the suspended ceiling. For estimation of all the inherent parameters in the model, the surface impedance of the suspended ceiling has to be known. A method for estimating the scattering and absorbing effects of furniture and objects is suggested in this paper. The room acoustical parameters reverberation time \(T_{20}\), speech clarity \(C_{50}\), and sound strength \(G\) were calculated with the model and compared with calculations according to the classical diffuse field model. Comparison with measurements were performed for a classroom configuration. With regard to all cases, the new model agrees better with measurements than the classical one.  
room acoustics; calculation models; absorption; scattering; airflow resistivity +
Footnote †: journal: Physics Letters A  
Article An Energy Model for the Calculation of Room Acoustic Parameters in Rectangular Rooms with Absorbent Ceilings  
1 Saint-Gobain Ecophon AB, Yttervagen 1, 265 75 Hyllinge, Sweden  
2 Engineering Acoustics, Lund University, [PERSON] 1, 221 00 Lund, Sweden; 2 [EMAIL_ADDRESS]
## 6 Simulation Results and Discussion
### Optimization Results
#### 6.1.2 PV/Wind/Battery System  
The PV/wind/battery system is the other alternative to electrify the specified site. According to the simulation analysis this system was optimized to the LCOE of USD 0.323/kWh and NPC of USD 219,736. The PV/wind/battery system is free of pollutant gas emissions, and economically feasible compared with the stand-alone diesel system. However, the PV/wind/battery system demands a relatively high initial investment cost (USD 129,986) due to its high component cost compared with the other configurations considered in this study.
## 1 Introduction  
Oral diseases are the most prevalent chronic childhood diseases, presenting as a major public health issue affecting children of all ages in developing and developed countries. Early detection and control of these diseases are very crucial for a child's oral health and general wellbeing. Since oral diseases are preventable in nature, early and accurate identification of risk factors can be very useful for developing cost-effective measures to prevent oral diseases.  
For identifying risk factors for oral diseases, such as dental caries, caries risk prediction models have been developed, which can lead potentially to the development of preventive measures that, in return, can improve patient care [1]. Caries risk assessment tool (CAT), caries management by risk assessment (CAMBRA) and the Cariogram are the most commonly used caries risk assessment models [2]. The Cariogram is regarded as a good caries risk prediction model; however, its sensitivity is reportedly in the range of 41-75% and its specificity is in the range of 65.8-88% [3].  
Dental plaque is considered a precursor of most oral diseases, which include dental caries and gingivitis [4]. Hence, the prevention of accumulation of plaque on the oral hard and soft tissues is very critical in maintaining oral health among children [5; 6]. The traditional method for the detection of dental plaque using an explorer (with or without a disclosing agent) is inconvenient to be used with children [7; 8]. Several advanced methods, such as laser-induced autofluorescence spectroscopy and digital imaging analysis, had been reported in the literature, but their major drawbacks include equipment cost and the difficulty in technique standardization [9; 10; 11].  
The newer developments in the field of science and technology have gained tremendous attention with the development of artificial intelligence (AI), a new breakthrough in technology that quickly became popular in the scientific world. AI technology has been widely put to use in the field of medical sciences and has demonstrated excellent performance in a variety of tasks related to patient care that include disease diagnoses and identification of patient's risk for developing a disease among many more [12]. AI has also demonstrated excellent performance in diagnosing and predicting the prognosis of COVID-19 and has contributed to its drug discoveries [13]. AI models have also gained attention with their use as ancillary tools, increasing the precision and accuracy of diagnoses. In dentistry, it is used in orthodontics, orthognathic surgeries and oral cancer for planning treatments and predicting their outcomes [14; 15; 16]. Hence, the aim of this systematic review is to assess the performance of AI models designed for application in pediatric dentistry.
# A Review on the Thermal Hazards of the Lithium-Ion Battery and the Corresponding Countermeasures
## 5 Management and Countermeasures
### Warning  
There are two aspects from the perspective of early warning in order to solve the safety problem associated with LIB. The first is for a single battery; real-time monitoring of voltage, current, resistance and other data should take place prior to the occurrence of thermal hazard, allowing for an alarm to be raised when an abnormality appears. The second is to carry out management monitoring for a battery pack, that is, to analyze and alarm the abnormalities occurring during the operation of the entire battery pack. The early warning includes monitoring the changes in voltage, current, resistance and other electrical performance parameters, the temperature change and the escaping gases. An early warning and monitoring system is disclosed by [PERSON] et al. [269] for battery packs. During normal cycling of a battery, surface temperature, voltage, current and impedance may be monitored to determine if abnormalities exist in the battery. [PERSON] invented a method for detecting LIB failure within a battery pack based on variations in the measured electrical isolation resistance of the battery pack [270]. Besides, escaping gas from LIB is becoming a growing concern since the volatile organics emitted are flammable and their unpredictable release represents a safety risk. [PERSON] et al. [271] illustrated the results that the sensor could detect escaping gas prior to thermal events. With enough prior warning from the sensor, there is a desire to determine whether it provides suitable control at the fringes of battery performance. [PERSON] et al. [272] applied an autonomous wireless sensor system for early fire and gas leak detection of LIBs. The system consisted of two modules: a gas sensor module and a power management module. At the same time, there have been more studies on the thermal runaway and fire releasing gases of LIBs; therefore, the number of gas detection methods that can be used for thermal runaway and fire warning has also increased [273; 274; 275]. The problem of thermal runaway and fire in LIBs is now more serious, therefore some advanced means are needed to predict the occurrence of disasters. Accurate warning of thermal runaway and fire shall be achieved through more quantitative data analysis.
# Smart Handoff Technique for Internet of Vehicles Communication using Dynamic Edge-Backup Node
## 2 Literature Review
In [23] the authors improved the handoff process of network-based DMM by using the HO-initiate procedure and IEEE 802.21 media independent handoff services. Their proposed technique begins the problem of compulsory registration delay by using the HO-initiate process and lessens the delay of determining the next access network and candidate mobile anchor access routers (MAARs). The authors of [11] provide a brief overview of communication and information exchange between vehicles and provide the latest scheme for handoff algorithm which relies on the vehicular communications specifically focused on the vehicle to infrastructure (V2I). In highlighting the impact of the new emerged concept of mobile edge computing in the field of VANET, see the authors of [24; 25]. In this paper, vehicular edge computing (VEC) was investigated as an important application of mobile-edge computing in vehicular networks.
# Reconstruction of Missing Data in Weather Radar Image Sequences Using Deep Neuron Networks
## 3 Data and Experimental Design  
### Dataset  
The radar dataset was constructed based on the radar reflectivity data of 11 S-band Doppler weather radar (Beijing Metstar Radar Co., Ltd., China) stations covering the Guangdong province from 2010 to 2019. The products of Constant Altitude Plan Position Indicator (CAPPI) [49] images with a resolution of 0.1 km were generated and used in the study. The dates of the radar data were chosen according to the rule that short-term heavy precipitation (greater than 20 mm/h) occurred at more than 3 automatic weather stations over Guangdong province. The size of the radar echo images was 256 \(\times\) 256, and the limits of the values of radar reflectivity factors were 0 to 80 dBZ. To facilitate the study, the length of the sample sequences was extracted and fixed at 10. The training set and validation set were split by samples in 2010-2018 with sizes of 18,000 and 2000, respectively. The test set of size 2000 was retrieved from samples in 2019 to ensure independence.
## 5 Conclusions  
This paper takes a natural gas foundation treatment project in Wuhu as an engineering example and designs on-site vibration control tests. A corresponding numerical model is established using ABAQUS finite element analysis software for mutual verification. The isolation effect of the isolation trench and the influence of the depth and position of the trench on its isolation effect are analyzed, and the following conclusions are drawn:  
1. The similarity between the field test results and the simulation results confirmed the effectiveness of using the Mohr-Coulomb criterion to establish a multi-layer homogeneous medium model in ABAQUS and simulating the excitation of DC on actual soil by setting the impact velocity and contact type of the mass block. Moreover, the application of this model in the study of the isolation trench performance is also reliable.  
Figure 16: Attenuation trend of PGA and PGV with the measuring distance at different isolation trench positions.  
2. The field test results indicate that the isolation trench has a significant isolation effect on the soil behind it. As the distance between the soil and the isolation trench increases, the isolation effect becomes weaker. However, the isolation trench has an amplifying effect on the vibration of the soil in front of the trench, so this part of the soil is more likely to be damaged in DC. Therefore, some reinforcement measures need to be adopted, such as supporting structures.
3. In the simulation results, when the depth of the isolation trench increases from 1 m to 3 m, the isolation effect of the trench increases significantly, and the deeper the trench, the better the isolation effect. When the depth of the isolation trench increases from 3 m to 4 m, the isolation effect does not change significantly.
4. The closer the isolation trench is to the vibration reduction object, the more obvious the isolation effect. In actual engineering, to achieve the best isolation effect of the isolation trench, the distance between the compaction points and the isolation trench should be increased as much as possible on the premise of ensuring that the isolation trench will not affect the stability of the object itself, and the distance between the object that needs to be vibration reduced and the isolation trench should be reduced.  
Conceptualization, T.P.; Funding acquisition, Y.Z.; Investigation, X.L., T.P., G.L., L.S. and X.X.; Methodology, X.L., T.P. and X.X.; Project administration, G.L. and L.S.; Supervision, Y.Z.; Writing--original draft, X.L. and D.C.; Writing--review and editing, T.P. All authors have read and agreed to the published version of the manuscript.  
The authors would like to express their sincere gratitude for the financial support provided by the 173 Key Basic Research Project of the National Natural Science Foundation of China.  
Not applicable.  
The data used to support the findings of this study are included within the article.  
The authors declare no conflict of interest.
# A Study on Sensitive Bands of EEG Data under Different Mental Workloads
## 4 Significance Analysis of Mental Workload and Feature Based on SVM Classifier
### Comparative Analysis of Classification Results  
The full band and \(\beta\) band features of all the participants are sent to the SVM for classification of mental load respectively. The classification accuracy of the two methods on the test set is shown in Table 5, where Acc(\(f\)) indicates the accuracy of classification using full band features, and Acc(\(\beta\)) indicates the accuracy of classification using the \(\beta\) band feature.  
From the classification results, the effect of using the \(\beta\) band data for classification alone is better than the classification using the four bands data. It can be explained that the \(\beta\) band feature contains most of the useful information about the data. The rest of the band information interferes with the data. In the case of testing mental load, the \(\beta\) band data can be separately analyzed, which not only can reduce the dimension of the data, but can also improve the performance of the model, and save resources such as memory.
# A Novel Wideband Splitter for a Four-Element Antenna Array
## 3 Proposed Antenna Array Splitter
Power losses in the  
Figure 1: Proposed circuit of the wideband splitter for a four-element antenna array. transmission lines can be caused by conductor heating, dielectric heating, and radiation losses. Thus, if low losses are required, it is necessary to use transmission lines with minimal power losses.
# Hybrid Approach for Indoor Localization Using Received Signal Strength of Dual-Band Wi-Fi
###### Abstract  
In this paper, we propose a hybrid localization algorithm to boost the accuracy of range-based localization by improving the ranging accuracy under indoor non-line-of-sight (NLOS) conditions. We replaced the ranging part of the rule-based localization method with a deep regression model that uses data-driven learning with dual-band received signal strength (RSS). The ranging error caused by the NLOS conditions was effectively reduced by using the deep regression method. As a consequence, the positioning error could be reduced under NLOS conditions. The performance of the proposed method was verified through a ray-tracing-based simulation for indoor spaces. The proposed scheme showed a reduction in the positioning error of at least 22.3% in terms of the median root mean square error compared to the existing methods. In addition, we verified that the proposed method was robust to changes in the indoor structure.  
Keywords:dual-band; indoor localization; range-based localization; received signal strength; trilateration; Wi-Fi +
Footnote †: journal: Sensors
## 1 Introduction  
It is generally accepted that the terahertz (THz) range is the frequency range of 0.1-10 THz. In recent years, THz technology has attracted growing attention with the progress of THz sources and instrumentation [1, 2]. THz technology has been widely used in many fields, including but not limited to filtration [3], molecule identification [4], imaging [5, 6] and environmental monitoring systems [7] because it has many fascinating electromagnetic characteristics, such as being harmless to the human body and having artificial magnetism and high chemical sensitivity [8, 9, 10, 11]. However, the electromagnetic responses of general natural materials to THz waves are always very weak and cannot meet the requirements for real-world applications. Currently, people put much effort into incremental THz-wave efficiency by using metamaterials [12, 13, 14] to enhance the coupling effect between the THz wave and the metamaterial.  
Metamaterials are special materials with artificial micro/nanostructures. By adjusting their geometric dimensions, they have many unique electromagnetic responses, including asymmetric transmission, negative refraction index, perfect absorption, and superlens [15, 16, 17, 18, 19], and they can work in visible, infrared (IR), THz and microwave spectra ranges [20, 21, 22, 23]. Such a unique electromagnetic response can be used in THz optics applications. To date, there has been a significant amount of literature reporting on tunable metamaterials [24, 25] by using a split-ring resonator (SRR) [26, 27], complementary SRR (CSRR) [28], electric SRR (eSRR) [29], F-shaped SRR [30], V-shaped SRR [31], I-shaped SRR [32], U-shaped SRR [33], C-shaped SRR [34], and three-dimensional SRR [35], etc. However, the tuning ranges of these proposed THz metamaterials are not large enough for the THz filter application. Therefore, the requirement of realizing a tunable THz filter with a large tuning range has become a hot topic of scientific research.  
In this study, we propose a tunable THz metamaterial using an eSRR to exhibit polarization-sensitive characteristics. An eSRR is composed of double symmetrical semicircles and two central metal bars on silicon on an insulator (SOI) substrate. By changing the relevant geometrical dimensions of the semicircles and two central metal bars, the resonances of the eSRR device are always stable in transverse electric (TE) mode, and the resonances of TM polarized mode can be tuned with a tuning range of 0.50 THz by moving the bottom metal bar. Moreover, the resonances can be switched between dual-band and triple-band resonances by changing the lengths of two metal bars.
## Appendix A Triage-NLU Implementation  
The Triage-NLU prototype is implemented in Python 3.11.9 using the Hugging Face Transformers library for multilingual semantic parsing and Flower for federated learning simulation. The architecture consists of two main components: a multilingual semantic parser based on mT5 and a secondary classification head for medical intervention prediction. To implement the proposed TriagE-NLU, the following steps were followed:  
1. _Preprocessing and Data Handling_ involve several steps. First, multilingual inputs from the TriageX dataset are loaded and tokenized. Patient metadata is then normalized and merged with the corresponding input text to provide contextual grounding. Finally, the target EUREKA frames are converted into linearized string formats suitable for sequence generation tasks.
2. _Semantic Parsing (mT5)_ is performed by fine-tuning the google/mT5-Base model in a sequence-to-sequence setup. The input follows the format: \"<lang>: <dialogue> [SEP] <age> [SEP] <conditions>\", and the output corresponds to a serialized EUREKA frame represented as a JSON-like string. To ensure structural validity, constrained decoding rules are applied during generation to enforce correct EUREKA slot formatting.
3. _Intervention Classification Head_ is implemented by attaching an MLP classifier either on top of the encoder output or the parsed EUREKA frame. This classifier is trained using a multitask learning approach, either jointly with the semantic parser or in a sequential setup, depending on the configuration.
4. _Federated Learning Simulation_ uses Flower to simulate clients.
5. _The Evaluation_ process includes computing frame-level and slot-level F1 scores for the EUREKA semantic parsing task, as well as measuring accuracy and Macro F1 for intervention classification. Additionally, performance is analyzed separately for each language to assess cross-lingual generalization.