esa-sceva/satcom-chunk-collection huggingface dataset:
# Bindings and RESTlets: A Novel Set of CoAP-Based Application Enablers to Build IoT Applications
## 4 Flexible Direct Binding
In line with this, we modified the CoAP protocol by introducing four additional options, namely BIND_URI_HOST, BIND_URI_PORT, BIND_URI_PATH and BIND_PAYLOAD. BIND_URI_HOST and BIND_URI_PORT (optional in case default port is used) are defined to indicate the IP address and port number of the device that needs to be notified when events arrive. BIND_URI_PATH is the resource representation on the device through which it is triggered. When the request is stored on the sensor, the presence of these options is used to differentiate between a binding relationship and a traditional observation relationship. The optional BIND_PAYLOAD option may be used in a request if we wish a specific value to be sent during notification. In its absence, the new resource representation will be sent to the actuator. The method used for the notification will be PUT. Figure 5 shows the flow chart that describes how a binding relationship is established while Figure 6 shows the notification process. As shown in Figure 5, when a new request from the initiator that contains the observe option arrives at the sensor, it checks for the presence of one of the newly defined options to identify whether the request is a binding request or not. If so, the information contained in the newly defined options will be used as details to define the observer. If not, the source IP address, source port number and source URI_PATH will be taken as IP address, port number and URI path of the observer. For binding requests, we may optionally store the address of the initiator too. Once this is done, the initiator will not be involved in any event notification communications. Figure 4: Sensor-Actuator Interaction. (**a**) Indirect; (**b**) Direct Binding. Figure 5: Flow Chart Showing Binding Relationship Establishment. Figure 6: Flow Chart Showing Notification of Events. Referring to Figure 6, event notification of both binding and observation relationship is conducted in a similar way. The notification process starts when the state of an observed resource changes, which causes a packet to be sent to all observers. The notification process is almost the same for both binding and observation relationships except two steps. The first difference is the method. In case of a normal observation, a response packet is created while in case of a binding a PUT message is prepared. The payload to be used for binding relationships can be modified by the BIND_PAYLOAD option, which is the second difference. Apart from these two differences the notification process is the same. Management of the binding relationships can be facilitated by introducing binding directories. Binding directories are similar to resource directories but list existing binding relationships. Through the binding directory, we may find out which binding relationships exist and perform reconfiguration by sending other binding requests, if necessary.
## 6 Toxicity and Health Risk Assessments
In conclusion, BaP dominates in terms of its chronic carcinogenic risks and should be prioritized in environmental and health regulations, whereas Nap's toxicity management warrants greater focus on acute exposure contexts. The human health risk assessment results for Nap and BaP across multiple regions (Table 4) show that the non-carcinogenic risk of Nap is generally within a safe range. With the HQ at all observation sites being below the safety threshold of 1, its non-carcinogenic risk is negligible. In terms of carcinogenic risk, significant spatial differences are observed across different geographical environments. Low carcinogenic risk levels (\(\text{ECR}<10^{-6}\)) are found in open areas, such as during winter in Harbin in China, the Pearl River Delta urban agglomeration, the North Atlantic, and the Indian Ocean. Medium carcinogenic risks (\(10^{-6}<\text{ECR}<10^{-5}\)) are observed in semi-enclosed areas, including rural north China,  
Figure 6: The toxicity mechanisms of IVOCs. indoor environments in Germany, and the industrial area of Assiut, Egypt. Notably, the observation site in the high-density urban area of Haidian District, Beijing, China, has an ECR value exceeding \(10^{-5}\), reaching a high-risk level. Data analysis reveals a triple-gradient characteristic in regard to Nap pollution risk. The risk in terrestrial systems is significantly higher than that in marine environments, with the average risk level in indoor microenvironments being more than double that of outdoor environments. Urban built-up areas also have risk values one order of magnitude higher than rural areas. This spatial differentiation pattern is likely closely related to the intensity of anthropogenic emissions and the characteristics of pollution sources, especially the regional distribution differences of traffic sources, industrial emissions, and residential sources. Similar conclusions have been drawn from PAH risk assessments in southern California, India, and several countries in South America [18; 19; 104]. It is recommended to focus on the coordinated control of indoor and outdoor urban environments and to establish a Nap risk early warning system based on source apportionment. The carcinogenic risk value of BaP at the Svirsk site in Russia exceeds the high-risk threshold (\(10^{-5}\)), while its non-carcinogenic risk is more than 10 times the safety threshold, indicating a complex health risk posed by BaP in this area. Similarly, significant risk accumulation is also observed in the Haidian District of Beijing, China, and the Assiut area in Egypt. In contrast, the ECR of BaP during winter in Harbin, Lianhu District of Xi'an, Jinan, Tokyo, Japan, and Gdynia, Poland, is all below \(10^{-6}\), with a HQ below 1, meeting acceptable risk standards. Geographic analysis indicates that high-risk sites are mostly concentrated in urban industrial clusters (such as Svirsk in Russia and the Haidian District in Beijing, China), confirming the decisive role of industrial emissions and traffic sources
## 3 Data analysis and BP Neural Network Model Building
### Transfer Function Determination  
There are three transfer functions commonly used in the BP neural network model and these functions are applied in the hidden and output layer. The default transfer functions in \"newff\" function include a hyperbolic tangent function(\"tansig\") in hidden layer as shown in Equation (5) and a pure linear function(\"purelin\") in the output layer in Equation (6).  
\[\tan sig(n)=\frac{2}{(1+e^{-2n})^{-1}} \tag{5}\]  
\[\mathrm{purelin}(n)=n \tag{6}\]The final prediction formula can be obtained by training the model to determine the appropriate parameters. Among these parameters, the number of hidden layer nodes should be tested by user. The other corresponding parameters could be determined automatically.
# Development of Compact and Robust Physical System for Strontium Optical Lattice Clock
## 3 Operation and Results
The power of each beam of the 689-nm Red MOT lasers was adjusted to 0.8 mW, and the stirring laser's power was diminished to 50 \(\mu\)W. After 60 ms, we achieved a Red MOT with a temperature of approximately 4.5 \(\mu\)K and a population of about \(2.8\times 10^{5}\). Subsequently, all optical and magnetic fields, excluding the 813-nm lattice beam (maintained in an active state), were turned off to load the atoms into a one-dimensional optical lattice. The lattice beam operated at a power of 500 mW, a waist radius of 53 \(\mu\)m, and a trap depth of approximately 92 Er (Er = 3.44 kHz, representing the recoil energy). Eventually, around \(1.4\times 10^{4.87}\)Sr atoms were transferred from the Red MOT to the lattice. The images captured by the CCD for the Blue MOT, Red MOT, and atoms in the optical lattice are, respectively, presented in Figure 6b. By analyzing the decay of atoms trapped in a lattice, we estimated their lifetime to be approximately 3.6 s, as illustrated in Figure 6c. The lattice lifetime of transportable optical clocks typically ranges from several hundred milliseconds to a few seconds [30; 31; 34; 36], and our lattice lifetime is comparable to that of other transportable optical clocks. However, there is a notable difference when compared to laboratory clocks, where the lattice lifetime of optical clocks often extends to several seconds to tens of seconds [37]. We attribute this discrepancy primarily to the lack of active power stabilization on the lattice laser, which leads to significant power noise and consequently impacts the lattice lifetime. Nonetheless, given that our lattice lifetime is already sufficiently long, we have not pursued further investigation into the impact of power noise on the lattice lifetime. Figure 6: (**a**) The timing sequence in the Sr optical clock; (**b**) images recorded in situ for Blue MOT, Red MOT, and atoms in lattice; (**c**) the lattice lifetime measurement.
# Numerical Simulation of Fluid-Structure Coupling for a Multi-Blade Vertical-Axis Wind Turbine
## 3 Condition Setting
### Coupled Meshing
#### 3.2.1 Fluid Meshing  
When the flow field is analyzed, the solid wind turbine grid is first suppressed, and a hybrid meshing approach is used to partition the entire domain. In regions near the solid surfaces, an expansion layer is inserted to further capture the effect of the fluid near the wall. Figure 3 shows the division diagram of the fluid grid. Unstructured grids are employed and locally refined in the regions close to the blade rotation area. In contrast, structured grids and a combination of structured and unstructured grids are used in the regions far from the blade rotation area, utilizing a multigrid meshing approach to reduce computational load.
## 3 Results and Discussion  
### Exploration of Pb Recovery/Removal Using Resins  
There are many commercial resins available from different manufacturing companies. These resins have different chemical and physical properties. To explore the suitable resin for Pb(II) uptake, twenty-three resins were tested, which have different functional groups. The exploration process was conducted at resin amounts ranging from 0.1 g to 0.5 g at 20 mL constant volume metal solution, 180 min adsorption time, 150 adsorption speed, 1000 mg/L solution concentration, pH 3.5, and 20 \(\pm\) 1 \({}^{\circ}\)C room temperature.  
Figure 1 illustrates fourteen resins that have a Pb(II)-removal percentage above or close to 90%. These resins mainly contain sulfonic, phosphonic/sulfonic, amino/phosphonic, iminodisatic, bis-picolylamine, or sulfonic/trimethylamine group(s), while the other nine resins with functional group(s) of iso-thiouronium, carboxylic, N-methylglucosamine, diethylhexylphosphate (D2 EHPA), thiourea, aminomethylphosphonic, or trimethyl ammonium have relatively low adsorption performance for lead ions (Figure 2). Among the twenty-three resins tested, Dowex G-26 resin with sulfonic group and Purolite MTS 9570 resin with phosphonic/sulfonic groups were selected. These two resins have been tested by the same author, and they had high efficiency for removal of cadmium and copper as well [32].
# Real-Time Prediction of Operating Parameter of TBM during Tunneling
## 5 Conclusions  
We simulated WF based on ARIMAX in consideration of both geological parameters and previous TBM operating parameters. Two actual projects with different construction conditions were selected to test the performance of the method. For comparative analysis,  
Figure 5: Prediction results of current thrust in project B-2.  
Figure 6: Prediction error for the stacked values of current thrust in projects A-1 and B-2 according to real-time prediction distance.  
Figure 7: Difference in error (mean absolute percentage error (MAPE)) of ordinary least squares (OLS) with reference to ARIMAX in projects A-1 and B-2.  
the proposed method was compared with non-time series OLS. Additionally, the prediction of current thrust was examined depending on the real-time prediction distance to validate the practical applicability. The simulation results showed that the ARIMAX outperforms the OLS predictor in both projects. As for the analysis according to the real-time prediction distance, the results showed that time series-based ARIMAX provides meaningful results where the real-time prediction distance is under 8 rings (11 m) or less. Such a time interval gives enough time for TBM operators to make decisions. The WF based on ARIMAX can provide reasonable TBM operating conditions with time-varying data. Of course, there remain several challenges such as outlier processing for in situ data and consideration of the operator's driving skills. Nevertheless, this study is expected to be used as an important reference for the development of predicting various operating parameters in the future.  
Conceptualization, H.-L.L., K.-I.S. and C.Q.; Methodology, H.-L.L. and C.Q.; Writing--original draft, H.-L.L., K.-I.S., C.Q., J.-S.K. and K.-S.K.; Writing--review & editing, H.-L.L., K.-I.S., C.Q., J.-S.K. and K.-S.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (no. NRF-2020R1F1A1075881). This research was also supported by the Nuclear Research and Development Program of the National Research Foundation of Korea (NRF-2021M2C9A1018633) funded by the Minister of Science and ICT.  
The authors declare no conflict of interest.
# Distributed MIMO Measurements for Integrated Communication and Sensing in an Industrial Environment
## 7 Conclusions
The following abbreviations are used in this manuscript:  
1 PPS one pulse per second  
AGC automatic gain control  
CP cyclic prefix  
D-MIMO distributed MIMO  
DAC digital-to-analog converter  
FPGA field-programmable gate array  
ICAS integrated communication and sensing  
IMU inertial measurement unit  
IoT internet of things  
JCAS joint communication and sensing  
lidar light detection and ranging  
LS large intelligent surface  
LO local oscillator  
LoS line of sight  
LSF large-scale fading  
M2M machine-type communication  
mmWave millimeter wave  
MIMO multiple-input multiple-output  
MPC multipath component  
MRC maximum ratio combining  
MRT maximum ratio transmission  
NLoS non-line of sight  
OFDM orthogonal frequency-division multiplexing  
OTA over the air  
PDF probability density function  
PL path loss  
Rb Rubidium  
RF radio frequency  
RMS root mean square  
SLAM simultaneous localization and mapping  
SNR signal-to-noise ratio  
SSF small-scale fading  
TDMA time-division multiple access  
TOA time of arrival  
UE user equipment  
USRP universal software radio peripheral
# Compression Challenges in Large Scale Partial Differential Equation Solvers
## 2 Compression Aspects of PDE Solvers
### Compression Speed and Complexity Follow the Memory Hierarchy  
Compression plays different roles on all levels of the memory hierarchy, depending on application, problem size, and computer architecture. Due to the speed of computation growing faster than memory, interconnect, and storage bandwidth, a multi-level memory hierarchy has developed, ranging from several memory cache levels over main memory, nonvolatile memory (NVRAM) and solid state disk burst buffers down to large storage systems [47]. Lower levels exhibit larger capacity, but less bandwidth than higher levels. The larger the data to be accessed, the deeper in the memory hierarchy it needs to be stored, and the slower is the access. Here, data compression can help to reduce the time to access the data and to exploit the available capacity on each level better. While this can, in principle, be considered and tuned for any of the many levels of current memory hierarchies, we limit the discussion to three prototypical levels: main memory, interconnects, and storage systems.  
Compression of in-memory data aims at avoiding the \"memory wall\" and reducing the run time of the simulation (see Section 3). The available bandwidth is quite high, even if not sufficient for saturating the computed units. In order to observe an overall speedup, the overhead of compression and decompression must be very small, such that only rather simple compression schemes working on small chunks of data can be employed.  
In distributed systems, compression of inter-node communication can be employed to mitigate the impact of limited network bandwidth on the run time of simulations (see Section 4). The bandwidth of communication links is about an order of magnitude below the memory bandwidth, and the messages exchanged are significantly larger than the cache lines fetched from memory, such that more sophisticated compression algorithms can be used.  
Mass storage comes into play when computed solutions need to be stored for archiving or later analysis. Here, data size reduction is usually of primal interest, such that complex compression algorithms exploiting correlations, both local and global, in large data sets can be employed (see Section 5). For an evaluation of compression properties on several real-world data sets we refer to [41]. Due to the small available bandwidth and the correspondingly long time for reading or writing uncompressed data, the execution time even of complex compression algorithms can be compensated when storing only smaller compressed data sets. This aspect is relevant for the performance of out-of-core algorithms for very large problems. If compression data can be kept completely in memory, out-of-core algorithms can even be turned to in-core algorithms. A recent survey of use cases for reducing or avoiding the I/O bandwidth and capacity requirements in high performance computing, including results using mostly SZ and zfp, is given by [PERSON] et al. [48].
# Real-Time Communication Aid System for Korean Dysarthrie Speech
## 1 Introduction
& \multirow{2}{*}{AAC} & ASR + Message & Extremely & \multirow{2}{*}{Self-collection (English)} & 96\% \\ (2012) [10] & & Reconstruction + TTS & & & (Restrict specific \\  & & & & & words) \\ \hline [PERSON] & \multirow{2}{*}{ASR} & CRNN & Word, Phrase, & \multirow{2}{*}{Torgo (English)} & \multirow{2}{*}{40\%} \\ [PERSON] and & & & (CNN + RNN) & & & \\ [PERSON] & \multirow{2}{*}{(2020) [22]} & & & & \\ (2020) [22] & & & & & \\ \hline [PERSON] (2021) & \multirow{2}{*}{ASR} & Spatial-CNN (Using Voicegram) & Word Level & UA-Speech (English) & 64\% \\ \cline{1-1} \cline{5  
dyasarthric ASR model, we address the limitations of previous studies and provide real-time support for dysarthria. The proposed dysarthric ASR model efficiently learns the phonetic and visual features of dysarthric speech through a conformer encoding structure, and its performance is validated by comparing it with existing transformer-based ASR models. For integration with the developed dysarthric ASR model, various existing TTS models with universal and excellent performance were compared, and JETS, which demonstrated the highest performance in Korean speech synthesis, was selected. This enables individuals with dysarthria to freely produce normal speech in real-time across diverse situations, significantly enhancing their communication capabilities.
# A Tale of Many Networks: Splitting and Merging of Chord-like Overlays in Partitioned Networks
## 2 Related Work
### Re-Chord and Ca-Re-Chord--Self Stabilizing Chord Overlay Network  
Re-Chord [9] is a version of Chord that has been extended through small modification to become self-stabilizing, i.e., the Chord network can recover from any initial state in which the network is still weakly connected. Using a single contact from another separated network might suffice for linearizing and merging the two networks. The paper shows that, in theory, within \(O((log\,n)^{2})\) communication rounds, the overlay is stable and reestablished again. While this characteristic has been proven theoretically, we simulated Re-Chord's behavior under churn in [10] and show that, in Re-Chord during the stabilization procedure, the lookup operation is drastically limited and objects cannot be found to a high degree, as long as nodes enter or leave any of the merging networks. Thus, we have proposed  
Figure 2: Several groups can form after one region has been isolated.  
Ca-Re-Chord in [10] as an extended Re-Chord to address its struggles with churn and to stabilize the network despite nodes joining or leaving.  
While Ca-Re-Chord is capable of handling simple churn, it cannot handle drastic events, such as instances when more than 50% of the nodes leave the network; this is a case which is assumed in a network separation. This paper directly aims to offer solutions for use in such drastic scenarios with the proposal of Ring Reunion; this can, in addition, also deal with more simple scenarios.
## 4 Discussion
### Current Approaches  
Users wanting to map their proprietary units to UCCUM currently have two ways to do so. The first solution relies on accessing the LOINC data set either via RELMA or the web-based SearchLOINC application. Here, users can look up specific LOINC codes in order to find information on them that ranges from a full description of all its axes to an example UCCUM unit. The biggest drawback of this approach is that not all LOINC codes have an example unit associated with them. Secondly, the examples displayed do not necessarily fit the unique circumstances of each laboratory and mapping scenario. One also has to be mindful of the fact that not all given examples are inherently correct. Although smaller in the total amount of choices compared to the second solution, this approach is automated. By being able to look up specific LOINC codes, users are already pointed in the correct direction by drastically decreasing the possible search space.  
The second approach that users may take into consideration is making use of aggregations of UCCUM units as a reference. One such document pointed to on the LOINC and UCCUM web presence consists of common UCCUM units aggregated by Intermountain Healthcare, a joint effort of the National Library of Medicine and the Regenstrief Institute. It consists of 848 UCCUM units commonly used in electronic reporting sourced from the raw units of more than 23 laboratory sources and the HL7 table of units. At the time of writing, the latest version 1.5 was published in June 2020 ([[https://ucum.org/trac/wiki/adoption/common](https://ucum.org/trac/wiki/adoption/common)]([https://ucum.org/trac/wiki/adoption/common](https://ucum.org/trac/wiki/adoption/common)) (accessed on 29 April 2022)). The explicit goal of this effort was to aid users who felt intimidated by UCCUM in standardizing their proprietary unit terms [10]. Users wanting to utilize resources of this kind have to do so by combing through the documents manually. There is no software tool or explicit connection to LOINC codes associated with them which could help automate the process. On the other hand, they are more extensive in scope compared to the LOINC data set.  
Contributing to enhancing the Data Quality of LOINC  
During our initial assessment of LOINC's 210 _Properties_, we took notice of the fact that not every example unit in the LOINC data set is an appropriate match for the _Property_ it is associated with, thereby lowering the overall data quality. Our results can contribute to automatically finding such errors before they get included into future iterations of the standard; secondly, it can be used to sanitize the current data set. By matching the example units given against our base unit ground truth, we are able to verify if they represent a valid pairing.