esa-sceva/satcom-chunk-collection huggingface dataset:
# Utilizing Sequential Control Scheme to Stabilize Squeezed Vacuum States
## 1 Introduction
Thus, there is no direct way to extract the error signals of locking the single-resonant cavity length and relative phase. Therefore, squeezed vacuum states are usually generated by manually scanning the bias voltage imposed on the piezo-driven coupling mirror over the OPO cavity resonance. Its drawback is the lack of stability, and hence, it cannot meet the requirement for practical applications. By employing a quantum noise locking scheme [38] or using two additional coherent, but frequency-shifted auxiliary beams to control the cavity length and relative phase, long-term stable squeezed vacuum states can be achieved [39]. The scheme is derived from frequency-division multiplexing ideas. In this paper, we realize a steady quasi-continuous output of squeezed vacuum states by utilizing a sequential control scheme that was derived from time-division multiplexing ideas [40; 41], which operate an independent signal at different time periods. The control algorithm was managed by a self-designed program compiled on a field programmable gate array (FPGA) hardware platform. The operation process was divided into ready mode and carry mode. In ready mode, the locking beam (seed beam) has a coherent amplitude that can be used to extract the error signal for cavity- and phase-locking, generating a bright squeezed state. In carry mode, the voltage hold circuit starts working, and the locking beam is blocked, generating squeezed vacuum states. The presence of a locking beam reduces the squeezing strength due to classical noise coupling between the pump and locking beams, and it worsens below the MHz range. The sequential control scheme, originating from time-division multiplexing, can realize the stable generation of squeezed vacuum states within a certain period of time without the locking beam, which eliminates the influence of noise coupling between the pump and locking beams on the squeezing strength in carry mode. The measured non-classical noise reduction of squeezed vacuum states was 11.6 dB and 10.4 dB at the analysis frequencies of 2 MHz and 500 kHz, respectively. The setup operated stably for a 3-h running test, with an 80% duty ratio and 5-s cycle time. The stable quasi-continuous generation of high-level squeezed vacuum states has great significance in practical quantum systems.
# A Vehicle-Infrastructure Cooperative Perception Network Based on Multi-Scale Dynamic Feature Fusion
## 1 Introduction
To address these challenges, we propose a vehicle-infrastructure cooperative perception network that achieves comprehensive fusion of vehicle-infrastructure features. This network takes point clouds from both vehicle and infrastructure sensors as input and facilitates feature sharing to perform 3D object detection. Additionally, we present a multi-category real-world dataset called DZGSet, which offers richer and more diverse scenarios for vehicle-infrastructure cooperative perception. This dataset captures multiple categories of traffic participants, addressing the limitations in existing datasets. To evaluate our approach, we conduct experiments on DZGSet and DAIR-V2X dataset, comparing it with single-vehicle perception method and state-of-the-art cooperative perception methods. In summary, the main contributions of our work are as follows:  
* We introduce a vehicle-infrastructure cooperative perception network that employs a Multi-Scale Dynamic Feature Fusion Module, incorporating the Multi-Source Dynamic Interaction (MSDI) and Per-Point Self-Attention (PPSA) modules to effectively integrate features from vehicle and infrastructure, thereby significantly enhancing their cooperative perception capabilities. * We construct DZGSet, a self-collected real-world dataset featuring high-quality annotations for various traffic participants, including \"car\", \"pedestrian\", and \"cyclist\", which addresses the limitations of existing datasets. * Our extensive experimental evaluations demonstrate that the proposed vehicle-infrastructure cooperative perception network successfully fuses vehicle and infrastructure features, resulting in improved accuracy and a more holistic understanding of the cooperative perception. The rest of this paper is arranged as follows: Section 2 discusses the recent works that have been undertaken in cooperative perception and autonomous driving datasets. Section 3 portrays information on the proposed vehicle-infrastructure cooperative perception network. The results acquired with the proposed modules are discussed briefly in Section 4. Section 5 concludes this paper.
# LoRa Enabled Smart Inverters for Microgrid Scenarios with Widespread Elements
## 2 LPWAN Overview
### Ingenu  
The proprietary Ingenu communication system operates in the 2.4 GHz band. This is in contradiction with other LPWANs that operate in sub-GHz ISM bands. This fundamental difference affects the coverage, power consumption, and throughput of this technology. Furthermore, Ingenu proposed and patented random phase multiple access (RPMA), which is based on direct-sequence-spread-spectrum (DSSS) modulation.  
In comparison to LoRaWAN and SigFox, RPMA has wider coverage (especially in rural areas) and higher throughput, since it uses a much broader 1 MHz bandwidth. However, the end devices consume more energy to operate. RPMA-PHY specifications have been standardized under IEEE 802.15.4k standard [13; 16; 23; 24].  
Table 1 summarizes the important technical specifications of the aforementioned LPWAN technologies. Paying attention to the table, entries show some similarities and also major differences among the different technologies. However, the selection of one of them over the others strongly depends on the application.  
For the application of interest of this study, LoRaWAN is considered as the selected LPWAN technology due to some key features:  
* Open-source medium access control (MAC) protocol.
* Low-cost and easy to implement end-devices.
* Non-limited daily messaging.
* The possibility of creating private networks.  
From this point forward, the communication part of this paper is focused on LoRaWAN and LoRa from both theoretical and experimental viewpoints.
## 4 Proposed Fault-Prone Software Requirements Specification Detection Model
### Fault-Prone Software Requirements Specification Detection Model
#### 4.2.2 Phase 2: Data Processing  
Before the dataset is utilized for training the FPDM, the data undergo a process of cleaning and pre-processing utilizing the same method employed in the ambiguity classification model. This involves the elimination of redundant information, formatting of the text, and ensuring the uniformity of data across all documents. To determine the quality of the SRS, several criteria were employed.  
* SRS Title: The SRS title was evaluated to ensure that the title provides a clear idea of the system that will be implemented.
* SRS Description: The frequency of words present in the SRS description was analyzed by counting each word from the SRS title in the SRS description. To ensure consistency, the titles were converted into root word before calculating the frequency of words. The Computer Science Academic Vocabulary List (CSAVL) was excluded to ensure that the SRS description is related to the SRS title and is clear. A clear SRS description must contain more than three words related to the SRS title. For example, if the SRS title is Hotel Reservation System, the words \"hotel\" and \"reserve\" are checked, and the word \"system\" is excluded as \"system\" is part of the CSAVL.  
* SRS intended users: We checked the presence of intended users of the system in the SRS.
* SRS requirements: Using custom Python scripting, we classified the requirements in each SRS based on the five types of ambiguity generated by the ACM.  
Furthermore, subject matter experts comprising six respondents with experience in leading and managing software projects, system analysts, and/or a background in computer science with requirement engineering knowledge were invited to evaluate the SRS. Among the respondents, two had more than 10 years of experience, and four had 2 to 3 years of experience in requirement engineering. The experts were provided with a questionnaire containing 100 SRS documents, and the task was to label fault-prone SRS based on knowledge and understanding. A brief description of fault-prone and clean SRS criteria was also provided to aid the experts in the evaluation. The experts were given 20 days to provide feedback, allowing them to review it at their convenience (Figure 5).
## 3 The Multilevel Approach
### Fourth Level  
At the end of the previous step, the numerical design phase can be considered to be finished, as an optimized model has been obtained such that it well satisfies the requirements in terms of the shape quality of the deformation and, at the same time, it does not violate structural limitations. Last step, but not the least important, allows us to verify the structural performance of the complete active adaptive wing device, to simulate the three-dimensional and time-varying nonlinear elasticity and the structural dynamics. The starting point of the fourth level is the three-dimensional CST representation of the external wing shape and the set of optimal compliant structure solutions that are computed for different sections along the wing span. To generate the finite element model of the entire morphing device to be installed on the wing, an automatic interface between the CST technique and computer-aided engineering software, including Abaqus and CATIA, has been developed. This level enables the manual creation of manufacturing details, actuation kinematics, and connections between different parts of the structure, and it provides greater capabilities for modification. Moreover, it is possible to adjust the thickness of each compliant rib to meet the forces that are needed. Modeling of all of these details allows for a more realistic estimation of the stress distribution inside the structure and three-dimensional shape quality verification. The structural solution shown as an example in Figures S1 and S2 is used to generate the finite element model of a complete compliant trailing edge device. It can produce a spanwise twist deformation, as shown in Figure S3, exploiting the capability of the designed compliant structure to achieve both upward and downward deflections.  
A CAD model of the compliant mechanism can also be created starting from the automatic generation of different plane sketches along the span. They exhibit the actual internal point positions, the load path thicknesses and suitable fillets that link the lines at the intersection of the optimal solution. Starting from the CAD model of a compliant rib, the corresponding full-solid finite element model can be generated and used to optimize the shape of the fillets. This structural shape optimization allows to reduce the stress peaks inside the compliant structure, by increasing the fatigue life and the reliability of the compliant device.  
The availability of the complete device model enables the evaluation of other three-dimensional effects that are essential for the integration of the device with the wing. The complete model can be connected to a wing-box finite element model that reproduces the correct flexibility of the wing. In this way, the interaction between the adaptive structure and the wing-box can be evaluated while considering the static aeroelastic effects of the entire wing, for each flight condition. In the following application, the effects of the wing-box deformation on the shape quality of the actuated device are evaluated.
# The Early Detection of Cardiac Fatigue: Could the HRV Be Used as a Physiological Biomarker by AI?
## 3 Results
### Sensorized T-Shirt and Unsupervised ML  
In order to create algorithms that could identify respondents' levels of physical and cognitive weariness, the efficacy of several ML techniques based on multimodal data was evaluated by [42]. Using a sensorized t-shirt and a MUSE S headband, [PERSON] et al. (2022) [56] recorded various physiological signals (EEG; ECG; electromyography--EMG; EDA/GSR) from 32 healthy volunteers aged between 18 and 33 (average age: 24 years). While their data were being collected, participants were put through a series of standardized exercises designed to induce both physical and cognitive tiredness, such as running on a treadmill and performing N-Back tests. Following each task, participants used the VAS to rate their own level of weariness. In order to train the ML models, 113 time-domain and frequency-domain features--including HRV metrics--were finally extracted by using time segments of data recorded from every participant. For identifying physical weariness, the Random Forest classifier produced the best results (80.5% accuracy), whereas for cognitive fatigue, the Long Short-Term Memory (LSTM) NN produced the best results (84.1% accuracy).
# Dynamics of Monoterpene Formation in Spike Lavender Plants
## 4 Materials and Methods
### NMR Measurements  
NMR analyses were performed as follows: For \({}^{1}\)H spectra, an Avance I 500 (UltraShield 500 MHz, SEI 500 S2 probe head (5 mm, inverse with Z-gradient), Autosampler B-ACS 60) from Bruker Instruments (Karlsruhe, Germany) was used. The software installed was TopSpin 2.1 (Bruker Instruments, Karlsruhe, Germany). For \({}^{13}\)C spectra, either an Avance I 500 (Cryomagnet BZH 500 MHz, Autosampler B-ACS 60) or an Advance III 500 system with an UltraShield PLUS 500 MHz magnet and a cryo probe head (5 mm CPQNP, \({}^{1}\)H/\({}^{13}\)C/\({}^{31}\)P/\({}^{19}\)F/\({}^{29}\)Si (Z-gradient), Autosampler B-ACS 120) both from Bruker Instruments (Karlsruhe, Germany) were used. The software installed was TopSpin 3.0, respectively (Bruker Instruments, Karlsruhe, Germany). The measurements were performed at magnetic fields of 11.75 Tesla. The resonance frequencies of \({}^{1}\)H and \({}^{13}\)C were 500.13 MHz and 125.77 MHz, respectively, and the temperature was 300 K. Data analysis was performed with the MestReNova Software (Mestrelab Research, Santiago de Compostela, Spain), TOPSPIN or XWIN NMR. The one-dimensional \({}^{1}\)H and \({}^{13}\)C NMR spectra, and the two-dimensional COSY (magnitude mode or phase-sensitive), HSQC, HSQC-DEPTedited, HSQC-TOCSY, NOESY (with 1 s mixing), TOCSY (with 60 ms mixing) and HMBC spectra were measured with standard Bruker parameter sets.  
**Supplementary Materials:** The following are available online at www.mdpi.com/2218-1989/7/4/65/s1, Table S1: Experimental overview, preliminary experiments, Table S2: Absolute \({}^{13}\)C enrichments in 1,8-cineole for each carbon atom as calculated from \({}^{13}\)C NMR and GC/MS, Table S3: Main components of spike laser laser self essential oil, including comuarine, from lines HMGR5 and WT extracted with chloroform-d and determined by GC/MS. Table S4: Experimental overview of WT and HMGR5 lines. Pulse period of 5 h for all samples, Figure S1: Isotopologue excess values and distribution of isotopomers of cineole for 51 \({}^{13}\)CO\({}_{2}\) feeding experiments, Figure S2: Isotopologue excess values and distribution of isotopomers of camphor in 28 \({}^{13}\)CO\({}_{2}\) feeding experiments.  
**Acknowledgments:** This work has been funded by the Valencia Regional Government (Generalitat Valenciana): PROMETEOII/2014/052; and the Spanish Ministerio de Educacion y Cultura (AP2007-04606): FPU fellowship to [PERSON].  
**Author Contributions:** [PERSON] prepared and perform the experiments and wrote a first draft of the manuscript. [PERSON] and [PERSON] collaborate in the labelling experiments. E.K. analysed the NMR data. [PERSON], [PERSON] and [PERSON] analyzed the GC/MS data. [PERSON] and [PERSON] designed and supervised the labelling experiments. [PERSON] and [PERSON] designed the study. All authors discussed the results. [PERSON], [PERSON] and [PERSON] prepared the final version of the manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## Materials and Methods
### Experimental Characterization  
The following experimental measurements were carried out on loose fibers obtained from Aegagropiles:  
* Porosity by the air volume compression method [26];
* Airflow resistivity according to ISO 9053-2 [27], as the density of the loose fibers varies (range from 65 to 191 kg/m\({}^{3}\));  
Figure 2: Collected Posidonia Balls (**a**), fibers obtained from the aggregates (**b**), microscope pictures of the fibers (**c**), fibers inside the sample holders for the measurement of airflow resistance (**left**) and sound absorption at normal incidence (**right**). In the center, the front grid for the compression of the sample (**d**).  
Sound absorption at normal incidence according to ISO 10534-2 [28], as the thickness and density of the fibers vary (range from 48 to 210 kg/m\({}^{3}\)).  
The experimental tests aim to determine the variation of the physical and acoustic parameters of the fibrous material as a function of the apparent density of the fibers.  
The equivalent dissipative fluid model proposed by [PERSON] (JCA) [29; 30] was used, which describes complex effective density \(\rho\) and the complex effective bulk modulus \(K\) as a function of five physical parameters: porosity \(\phi\), tortuosity \(\alpha_{\infty}\), airflow resistivity \(\sigma\), and viscous and thermal characteristic length \(\Lambda\) and \(\Lambda^{\prime}\):  
\[\rho(\omega)=\frac{\alpha_{\infty}\rho_{0}}{\phi}+\frac{\sigma}{i\omega}\sqrt {1+\frac{4i\alpha_{\infty}{}^{2}\eta\rho_{0}\omega}{\sigma^{2}\Lambda^{2}\phi ^{2}}} \tag{1}\]  
\[K(\omega)=\frac{\frac{\gamma\cdot P_{0}}{\phi}}{\gamma-(\gamma-1)\left[1+ \frac{8\eta}{ip_{0}\omega Np_{\Lambda^{\prime}}}\sqrt{1+\frac{ip_{0}\omega Np_{ \Lambda^{\prime}}}{16\eta}^{2}}\right]^{-1}} \tag{2}\]  
where \(\rho_{0}\) is the density and \(\eta\) the viscosity, \(P_{0}\) the static pressure, and \(\gamma\) the specific heat ratio of air.  
From the complex effective density \(\rho\) and the complex effective bulk modulus \(K\), the characteristic impedance \(Z_{c}\) and the complex wavenumber \(k_{c}\) can be computed as:  
\[Z_{c}=\sqrt{\rho K} \tag{3}\]  
\[k_{c}=\omega\sqrt{\frac{\rho}{K}} \tag{4}\]  
Considering a homogeneous porous material of thickness \(h\) placed on a rigid boundary, the surface impedance for normal incidence \(Z_{S}\) can be determined as:  
\[Z_{S}=-iZ_{C}\text{cot}(k_{c}h) \tag{5}\]  
and the normal incidence sound absorption coefficient \(\alpha_{n}\) as:  
\[\alpha_{n}=\frac{4 Re\Big{(}\frac{Z_{S}}{\rho_{0}\omega}\Big{)}}{\left|\frac{Z_ {S}}{\rho_{0}\omega}\right|^{2}+2 Re\Big{(}\frac{Z_{S}}{\rho_{0}\omega}\Big{)} +1} \tag{6}\]  
where \(c_{0}\) is the speed of sound in air.  
In the following subsections, the procedures for deriving the density dependence of the five physical parameters are described.  
A schematic diagram of the procedure proposed in this article is shown in Figure 3.
## 5 Performance Comparison and Validation
### Results and Discussion
#### 5.2.3 Scenario Analysis
It can be seen in Figure 9(c) that DQAAR can effectively reduce the amount of data when the amount of data in the network increases, while the delay does not cause a significant change. Its comprehensive energy efficiency is much greater than that of the other three routing protocols. The cycle and delay maintain stable performance with the increase in data volume.The lifetime index and delay index of the network system using each protocol are shown in Figures 11 and 12. Figure 7: Performance of each protocol in Scenario 1. Figure 8: System lifetime utility of each protocol in Scenario 1. Figure 9: System delay utility of each protocol in Scenario 1. Figure 11: System lifetime utility of each protocol in Scenario 2. Figure 10: Performance of each protocol in Scenario 2. Finally, the simulation verification results can be summarized into the following three points:  
(1) Compared with AUMRP, the life of the network system using DQAAR is improved to a certain extent, and both MVECR and MTECR are improved to a certain extent, which effectively prolongs the dead time of the first node in the network system. It ensures the balance of network energy consumption and allows the longer survival of nodes with heavy loads in the network when the energy level is low to ensure the monitoring quality of the network. (2) In the high-speed railway monitoring system, the life cycle of the network and the delay of data transmission are both important performance indicators, and the single-objective network optimization algorithm is difficult to meet the actual needs. The adaptive routing algorithm based on double-Q-values proposed in this paper can effectively improve the network life and obtain good real-time performance. The comprehensive energy efficiency index is used to evaluate the routing protocol and verify the superiority of DQAAR in these two aspects. (3) The design of the adaptive operator and Q-value in this paper comes from the business requirements of each sensor in the high-speed railway monitoring network system. In different application scenarios, the adaptive operator and Q-value can be designed differently. This ensures the multi-scene adaptability of the adaptive model based on double Q-values established in this paper.
# Advances in Graphene Field Effect Transistors (FETs) for Annine Neurotransmitter Sensing
## 4 Challenges and Limitations  
Although several of the advancements reported in the previous section highlight the development of GFET-based biosensors with an LOD close to what is found in blood, the intrinsic characteristics of graphene and the complexity of biological environments pose significant challenges to GFET biosensing for NTs, which hurdles GFET practical implementation.
# Fast Ferroelectric Liquid Crystal Based Optical Switch: Simulation and Experiments
## 5 Conclusions  
In summary, the feasibility of a free space fast optical switch concept was studied theoretically and experimentally using FLC material. Even if they have the disadvantage of slightly excessive cross-talk, LC switches offer large electro-optic effects over a short distance, are very reliable, and also their optical performance is satisfactory. The switching speed of the FLC material under study, KCFLC 10R, is much faster (\(<\)10 \(\upmu\)s) than conventional non-mechanical switches. For optimal FLC parameters at fixed temperature, the best achieved crosstalk measured was approximately \(-\)19 dB. The use of cross-talk removal stages helps to reduce cross talk to better than \(-\)30 dB. The main idea of a faster FLC matrix switch is to use conventional LCD technology to perform parallel switching in optical channels, without disturbing each other. Due to the faster response time and reliability, FLC modulators are attractive for scientific research and have many potential applications in optical communication networks.  
The experiment was designed by [PERSON]. The result analysis was performed by [PERSON] and [PERSON]. Additionally, [PERSON], [PERSON], and [PERSON] were responsible for interpretation of results and writing the paper.  
This work is supported by Strand-1 project funded by Science Foundation Ireland and Dublin Institute of Technology's Fisraigh Post Graduate Research program.  
The authors declare no conflict of interest.