esa-sceva/satcom-chunk-collection huggingface dataset:
Trehalose in particular proved to be suitable due to its lower hygroscopicity and the lack of intramolecular hydrogen bonds [17]. A number of methods are available for visualization of the LAMP amplification products (ii), which can be divided into the categories of real-time reaction monitoring and endpoint detection. Despite their ease of use, techniques like the lateral flow assay (LFA), colorimetric detection by pH indicators or fluorescence-based detection by addition of calcein or Sybr Green are limited to endpoint detection, resulting in lower information content compared to real-time methods [15; 21; 22; 23]. Real-time fluorescence measurements are used routinely in research and testing laboratories to carry out and monitor amplification reactions. The obtained fluorescence curves allow a reliable assessment of the reaction process and in some cases also a quantitation, or at least a relative estimation, of the target DNA content in the sample. The combination of LAMP with a handheld device for fluorescence measurements enables real-time connectivity (real-time quality control, REASSURED criteria R). Researchers and manufacturers have developed connectivity solutions that use smartphones for the read-out of the results [24; 25]. Only a few on-site LAMP-based tests systems are commercially available, none of them in the food sector. One published and commercially available on-site LAMP-based test system is the lab-on-phone COVID-19 assay by Stab Vida (Doctor Vida(r) pocket COVID-19 assay, Cat no. 133001001, STAB VIDA Lda, Caparica, Portugal) [26]. The authors did not provide further information on storage and transportation in the associated publication. Kits are also available for the detection of tuberculosis and malaria (Loopamp(tm) MTBC Detection Kit, Loopamp(tm) MALARIA Pv Detection Kit, Eiken Chemical Co., Ltd., Tokyo, Japan). The reagents are provided in lyophilized form, but a real-time fluorometer, a turbidimeter or incubator and a source of UV light must be provided by the user. The aim of this work was to investigate the stability of LAMP reaction mixtures during storage prepared on a small scale. The main goal was to demonstrate and document the applicability of the method outside the laboratory environment at the point of care. Since, to our knowledge, no LAMP-based test systems are commercially available for in-field food diagnostics, this represents an interesting challenge for the development of DNA-based test systems. Without the ability to simplify the test systems so that DNA isolation, amplification and evaluation of the results can be carried out by untrained personnel, the potential of the LAMP reaction remains largely unexploited.
# A Near-Ultraviolet Photodetector Based on the TaC: Cu/4 H Silicon Carbide Heterostructure
## 2 Materials and Methods
### Fabrication of the Device  
The deposition of the TaC (80%): Cu (20%) alloy was conducted using a commercial co-sputtering system (AJA ATC 2200, Scituate, MA, USA) equipped with six sputtering sources. The TaC target was powered by a 300 W radio frequency (RF) supply, while the Cu target was driven by a direct current (DC) power supply. To prevent surface contamination, both targets were pre-sputtered for two minutes without the substrate in the chamber. Afterward, the cleaned SiC substrate was inserted, pre-heated at 200 \({}^{\circ}\)C for 45 min to remove residual air and moisture and then allowed to cool to room temperature (approximately 30 \({}^{\circ}\)C). During sputtering, the chamber pressure was held at 1 \(\times\) 10\({}^{-4}\) mbar, and 99.99% pure argon gas was introduced at a flow rate of 20 sccm. The target-to-substrate distance was set to 9 cm to ensure a uniform deposition. TaC and Cu were co-deposited onto the SiC substrate over 37 min, forming a TaC: Cu/4H-SiC heterostructure. The copper doping concentration was adjusted by regulating the DC power supply to the Cu target. The deposition rate of the TaC: Cu alloy was measured using a surface profiler, yielding a rate of 4.5 nm/min.  
Subsequently, the photodetector was fabricated by depositing two aluminum (Al) electrodes, each 150 nm thick. One electrode was applied to the top surface of the alloy film, while the other was placed on the bottom side of the substrate. This deposition was carried out using a Temescal BJD-2000 (FerroTech, Livermore, CA, USA) electron beam evaporator under ambient conditions at a fixed temperature of 30 \({}^{\circ}\)C. The overall fabrication process of the proposed device is illustrated in Figure 1.
# Hate Speech Detection by Using Rationales for Judging Sarcasm
## 3 Methods
### Model  
In this section, the details of the BERT model are provided. The model was trained on both HateXplain and the newly proposed dataset. Here, how the cross-entropy loss is calculated is explained for ground truth attention.  
_Bidirectional Encoder Representations from Transformers (BERT)_  
In the BERT model, there are approximately 12 layers, and each layer consists of 12 attention heads, resulting in a total of 144 attention heads. Typically, a subset of these heads, denoted as \"supervised heads\", is utilized in the last layer of BERT for attention supervision, Figure 2(a). HateXplain [13] employs this term to describe the selected attention heads. For each supervised head, the attention weights corresponding to [CLS] are utilized, and the cross-entropy loss is calculated against the ground truth attention vector. This process ensures that the final weighted output corresponding to [CLS] focuses on words aligned with the ground truth attention vector. The same procedure is repeated for all supervised heads. The resultant loss from attention supervision is the average of the cross-entropy losses from each supervised head, further multiplied by the regularization parameter, denoted as \(\lambda\). The utilization of attention weights associated with [CLS] in conjunction with the cross-entropy loss helps align the model's attention with the ground truth attention vector.  
Following the computation of ground truth attention, the BERT model undergoes training using the preprocessed data and ground truth attention. Subsequently, a loss from attention supervision is computed, employing cross-entropy between attention values and the ground truth attention as the loss function for attention, Figure 2(b). The total loss, denoted as \(L_{total}\), is determined by the sum of the prediction loss (\(L_{prediction}\)) and the attention loss (\(\lambda\cdot L_{attention}\)). In this equation, \(\lambda\) acts as a weighting factor, regulating the influence of the attention loss on the overall loss.  
Figure 3: (a) Representation of the HateXplain [13] paper’s model, showing the attention supervision for a particular head in the nth layer of the BERT model. (b) Representation of the BERT model showing how the attention of the model is trained using the ground truth attention and the total loss calculation.
# Adaptive Satellite Navigation Anti-Interference Algorithm Based on Inverse Cosine Function
## 1 Introduction
Section III illustrates the improved ICVS-LMS algorithm and compares it with the three existing algorithms. In Section IV, the algorithm is applied to weaken the navigation interference signal, and the results prove the effectiveness of the algorithm. Finally, the conclusion expounds the main work content and contribution of this paper.
# Failure Identification Method and LMI-Based Control System for Small Spacecraft
## 4 Reaction Wheels Failure Identification and Control Correction
Finally, the right plot shows the failure estimation from Equation (11) when assuming that the first reaction wheel fails, matching the failure case. Figure 2: In this figure, observer’s output is shown for a single simulation with the first reaction wheel failing. Failure estimation with the reaction wheel observer, Equation (9) (**left**). Failure estimation with the attitude dynamics observer assuming no failure (**center**). Failure estimation with the attitude dynamics observer matching the correct failure case, Equation (11) (**right**). Finally, the disturbances are partially recovered by the remaining reaction wheels by considering  
\[\tau=\text{sat}(-\text{sat}(Z^{+}u_{cmd})-Z^{+}(\hat{d}-Z\hat{f})) \tag{12}\]  
where the \(\text{sat}(\cdot)\) function is the saturation of the control torque according to the maximum and minimum requirements.
# Energy Efficiency in Short and Wide-Area IoT Technologies--A Survey
## 2 IoT Technologies
### Low-Power Wide-Area Networks (LPWANs)
#### 2.2.1 Proprietary Technologies in Unlicensed Spectrum
Sigfox devices emit in the available frequency band, and the closest base station detects, decodes and forwards the signal to the network back-end. Bidirectional communication is possible but, similarly to Class A LoRaWAN, the communication is always initiated in uplink. Sigfox uses the so-called Random Frequency and Time Division Multiple Access (RFTDMA), which allows active nodes to randomly access time and frequency resources. Uplink transmissions are scheduled by adopting a so-called Fire and Forget model [54]: in order to increase transmission reliability, packets are sent by the device on three different frequencies at three different times, and correct reception is not acknowledged. The MAC layer adds device identification/authentication (HMAC) and error correcting code (ECC), but no signaling and control mechanisms are provided. A unique device ID is used for authentication and correct data routing. \begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline
**Technology** & **Modulation** & **Bandwidth** & **Frequency Range** & **Data Rate** & **Coverage Range** & **Topology** & **Ref.** \\ \hline \multirow{3}{*}{RFID and NFC} & OOK (RFID), & 9 kHz (LE), HF, 3.2, & 125-134 kHz (LE), & 135-134 kHz (HE), & 4 Mbps (RFID); & 10 cm-7 m (RFID); & 10 cm-7 m (RFID); & \\  & ASK, NNEZ-L, RPSX (NFC) & 26 MHz (GHz) RFID & 860 MHz (GHz) RFID & 10-125 MHz (35-MHz) RFID & 10-212, 424, 548 kbps (NFC) & 10 cm (NFC) & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\ \hline Zigbee & DSS, BPSK, O-QPSK & 2 MHz & 24 GHz & 20 kbps (868 MHz & \\  & & & & band)-280 kbps (2.4 GHz, & \\  & & & & band) & & \\ \hline \multirow{3}{*}{Bluetooth and BLE} & \(\frac{\pi}{2}\)/4-QPSK, & 1 MHz (per channel), & 24 GHz (Bluetooth); & 1 Mbps (GPSK, 2-3 Mbps & \\  & & & Bluetooth); 2 MHz & 24-2.483 GHz (BLE) & (Bluetooth); 1-3 Mbps (BLE) & (BLE) & \\  & & & & & & \\  & & & & & & \\ \hline LoRa & CSS & 125 kHz & 968 MHz (LE), & 0.3-375 kbps (LoRa) & 5 km (urban), 15 km & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\ \hline \multirow{3}{*}{Sigfox} & UNB, DBPSK (UL), & 100 Hz & 502 MHz (LE) & 100 kbps (UL), 600 bpps (DL) & 10 km (urban), 50 km & \\  & & & & & & \\  & & & & & & \\ \hline LTE-M & QPSK, 16 QAM (UL, DL) & 5 MHz (Rel-14) & Licensed 700–900 MHz & 384 kbps (DL), 1 Mbps (UL) & 3-10 km (urban), 50 km (urban) & \\  & & & & & & \\ \hline NB-IoT & QPSK (DL \(\pi\) /4 QPSK, & 87/2 BWK (UL) & 180 kHz & Licensed 700–900 MHz & \(<\)100 kbps & 1 km (urban), 10 km & \\  & & & & & \\  & & & & & & \\ \hline EC-CSM-IoT & 8 PSK & 220 kHz & Licensed CSM & 70 kbps (GSMR), & \\  & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: LFSAN and LLPWAN Technologies.
# Lightweight Integrity Preserving Scheme for Secure Data Exchange in Cloud-Based IoT Systems
## 4 Proposed Scheme
### Definitions and Framework  
This paper employs explanations that are identical to the explanations presented within formerly suggested systems within the circumstances of remote data integrity confirmation and utilizes guidelines for the public integrity checking system [6; 10; 11].  
The public integrity checking system is composed of the four algorithms of KeyGen, SigGen, GenProof, and VerifyProof. KeyGen can be defined as the primary creation algorithm that smart device users' conduct and that helps semi-trust servers to establish the system, while semi-trust servers employ SigGen to confirm the metadata. The semi-trust server's procedures for confirming the metadata can be composed of digital characteristics. Additionally, the IoT-cloud system utilizes GenProof to confirm accurate information storage and semi-trust servers employ VerifyProof to confirm the audit. The suggested system is composed of three stages: setup, upload, and audit.  
* The setup stage involves the smart device user starting the confidential guidelines through conducting the KeyGen and encrypting raw data file \(F^{\star}\) to \(F\) through the elliptic curve cryptography (ECC).
* The upload stage involves the semi-trust server utilizing the information's confidential guidelines through completing the KeyGen and prior information procedures \(F\) through SigGen, which creates metadata. The semi-trust server stores the information \(F\) and metadata on the IoT-cloud system and removes the local replica. As part of the pre-processing, the user may alter data file \(F\); in such a case, the user should notify the semi-trust server.
* The integrity check stage involves the semi-trust server submitting an audit appeal to the IoT-cloud system to guarantee that the IoT-cloud system has stored the suitable information file \(F\) during the audit. The IoT-cloud system then formulates a response through employing the GenProof and \(F\). Within this stage, the metadata serves as an input. VerifyProof is then employed by the semi-trust server to confirm the reaction.  
This paper's regulations presume that the semi-trust server is independent and, as such, does not need to sustain and inform circumstances between audits. Independence is an attractive characteristic for semi-trust servers, especially within a public integrity checking scheme [11]. Broadening the suggested guidelines to include an independent integrity checking scheme is not complicated as the confirmation of metadata only has to be divided in half and kept with the semi-trust server and IoT-cloud system. The plan presented in this paper does not presume further characteristics of the information file.
# Optimization Dubins Path of Multiple UAVs for Post-Earthquake Rapid-Assessment
## 3 HGSA Algorithm
### Initialization
#### 3.1.3 Constraint Check and Adjustment  
There are two constraints in the MURARP model: the UAV endurance constraint represented by Equation (9) and the overnight stay forbidden constraint represented by Equations (10) and (11). In this paper, chromosomes that do not satisfy Equation (9) are called class A violators, chromosome that do not satisfy Equations (10) and (11) are called class B violators, and chromosomes that do not satisfy Equations (9)-(11) are called class C violators.  
In view of the above three classes of violator chromosomes, three chromosome adjustment strategies are designed as follows:  
1. For class A violators, randomly delete a gene and repeat this deletion operation until the chromosome is no longer a violator.
2. For class B violators, keep only one gene with the same target indices and delete others.
3. For class C violators, keep only one gene with the same target indices and delete others first, and then randomly delete a gene and repeat this deletion operation until the chromosome is no longer a violator.  
After the constraint checking and adjustment on the population, all chromosomes are feasible routing schemes for MURARP.  
Figure 3: Sample diagram of an integer-encoded chromosome with variable lengths of the HGSA algorithm, which corresponds to the UAV routing scheme shown in Figure 2.
###### Abstract  
The aim of this study was to determine the associations between the front and back squat, countermovement jump (CMJ) and deep squat jump (DSJ) force-time metrics, and weightlifting performance in top-level weightlifters. Thirteen top-level weightlifters who classified for the World Championship 2023 participated. The heaviest successful snatch and clean and jerk were recorded within a preparation session as performance indicators. The front and back squat one-repetition maximum (1 RMs) were evaluated in separate training sessions. The average of three maximum CMJs and DSJs were recorded using a force plate, and jump height, propulsive net impulse, and peak power were calculated for further analysis. Pearson's correlation coefficients were used to determine the associations between variables. Statistical significance was set at \(p\leq\) 0.05. The front and back squat 1 RMs were significant and nearly perfectly associated with weightlifting performance (\(p<\) 0.001, \(r\) = 0.98-0.99). CMJ and DSJ propulsive net impulse displayed nearly perfect associations with weightlifting performance (\(p<\) 0.001, \(r\) = 0.96-0.99), while jump height is a less promising metric to assess the weightlifters' ballistic capabilities. This study reinforces that lower body maximum strength and ballistic capabilities are closely associated with top-level weightlifters' performance and are of practical importance to monitor their neuromuscular function.  
force plates; vertical jumps; snatch; clean and jerk; maximum strength Article
## 4 Discussion  
Electrets are insulating materials with a quasi-permanent electric polarization once the incorporated charge persists for \(\approx\)10\({}^{9}\) s [28]. To charge the polymer electret used as a second dielectric layer in OTFT, a \(-\)80 V bias was applied to the Gate electrode. The positive charges are induced from pentacene to the polymer electret and trapped in the electret. The trapped holes near the interface with pentacene induce a more negative shift of the threshold voltage. Radiation can erase the trapped charges and shift the threshold voltage back to the original state.  
The sensitivity of OTFTs with PS electret dosimeters was checked in wireless and wired readout configurations. For the wireless readout configuration, the average sensitivity of the devices was 60 \(\pm\) 5 nA/Gy for the 6 MV beam and 80 \(\pm\) 10 nA/Gy for the 100 kVp beam. This was potentially due to the influence of high Z electrodes and a silicon wafer introducing an enhancement to the photon interactions that would not be present in a water medium (the medium in which the dose is being reported). At lower photon energies where the cross section for photoelectric interactions increases rapidly, the influence of high Z metal electrodes and non-tissue equivalent substrate on the collected current may not be negligible [10; 11; 12]. In a wired configuration, Compton current can be induced in the wires to increase the signal in a way that might not be proportional to the dose in the active volume of the detector. That process will not happen in the wireless configuration since the current is not collected while the beam is on. However, the presence of the Si wafer and the gold electrodes may induce a signal in the active volume of the device that will not be proportional to the dose in tissue because of the relative enhancement of the photoelectric cross section. Future work will explore the fabrication of these devices on organic substrates and use of conducting organic polymers as electrodes to determine if energy dependence can be reduced.  
For the wired, real-time readout, the device demonstrated a linear response with dose rate over a range of 60 cGy/min to 600 cGy/min, with the sensitivity ranging from 1.0 nA/s to 8.1 nA/s, respectively at V\({}_{\text{d}}\) = \(-\)15 V and V\({}_{\text{g}}\) = \(-\)15 V.  
Electron-hole pairs created after X-ray photon interactions must be separated and drift to certain electrodes to be able to erase the trapped charges. Therefore, the dosimeter response to radiation can be higher due to the better charge separation in a higher electric field and smaller in a lower electric field. Applying higher biases during readout, however, may perturb the programming of the device. Future work will investigate the optimization of the programming and readout cycles of these devices to maximize sensitivity and reproducibility.
## 2 Materials and Method
### Life Cycle Assessment  
The environmental impacts associated with the conversion of olive trees into AC are investigated by means of life cycle assessment to identify the critical stages and areas of improvement. The experimental data collected during the process were used to implement the ISO 14040 (2006) LCA approach. In this study, two types of materials are used for AC production: _Lantana camara_ and olive trees, but only olive tree is considered for the LCA study as both the processes are relatively the same. An LCA is divided into four phases, each of which contributes to a comprehensive procedure: (1) goal and scope definition: this assists in defining the study's purpose, indicating how the results will be used, and specifying the intended audience. The LCA functional unit and boundary are defined in the scope definition. (2) Life Cycle Inventory analysis (LCI): All of the input and output flows of energy and material within the LCA boundary are collected, quantified, and adapted based on the functional unit. (3) Life Cycle Impact Assessment (LCIA) aims to comprehend and evaluate the degree and relevance of a system's possible environmental impact. It classifies and identifies the major impact categories into environmental impact indicators and (4) the interpretation, which assesses the study in order to make recommendations and draw conclusions. The environmental impact related to this study's steps was assessed by utilizing open LCA 1.10.3 software. For background data, the ecoinvent database v2.2 was used. The CML 2 Baseline 2000 was used for the impact assessment method. Only the mandatory steps of the impact assessment stipulated by ISO 14040 rules, namely categorization and characterization, were carried out because they are more objective. Table 2 lists the LCA impact categories that were investigated in this study. The total energy  
Figure 1: Preparation steps of AC from “Lantana camara and Olive trees” by chemical activation.  
demand, measured in primary energy, that results from the disposal, use, and production of an economic good is referred to as the cumulative energy demand [23].
## 3 Trusted Relay  
QKDON is composed of multiple nodes and fiber links. However, the limited transmission distance of point-to-point QKD cannot accommodate QKD between two remote nodes. Hence, the distance of key distribution needs to be extended using relay technology [46]. In this paper, we use trusted relay-based networking technology.  
As shown in Figure 2, assuming that [PERSON] and [PERSON] share a quantum key K via a trusted relay node, its relay principle can be summarized in the following steps: 1 The shared key K\({}_{1}\) is generated between the sender [PERSON] and the relay node in the form of QKD. 2 The shared key K\({}_{2}\) is generated between the relay node and the receiver [PERSON]. 3 The relay node performs XOR operation on key K\({}_{1}\) and key K\({}_{2}\) and stores the obtained key K\({}_{1}\)\(\oplus\) K\({}_{2}\) temporarily. 4 [PERSON] uses key K\({}_{1}\) to encrypt the key K to be shared with [PERSON] and sends the obtained key K\(\oplus\) K\({}_{1}\) to the relay node. 5 The relay node performs an XOR operation with the temporarily stored key K\({}_{1}\)\(\oplus\) K\({}_{2}\) and key K\(\oplus\) K\({}_{1}\) to obtain the encryption key K\(\oplus\) K\({}_{2}\) and sends it to [PERSON]. 6 [PERSON] decrypts the obtained key K\(\oplus\) K\({}_{2}\) with the key K\({}_{2}\) to obtain key K. 7 Finally, [PERSON] and [PERSON] obtain the shared key K.  
The QKD path with multiple relay nodes has to be established for two end nodes with long distances. Then, the keys are transmitted along the QKD path using hop-by-hop encryption and decryption. As specified in the above steps, each relay node can obtain the key shared between two end nodes through decryption; hence, these relay nodes must be trusted. In QKDON, all QKD nodes can act as the source and destination nodes to request services and also as relay nodes to share quantum keys.