esa-sceva/satcom-chunk-collection huggingface dataset:
# Surface Plasmon Resonance-Based Fiber Optic Sensors Utilizing Molecular Imprinting
## 6 Fiber Optic SPR Sensor Based on MITs
### Developments on FO-SPR-MIP-Based Sensors
#### 6.3.3 Vitamin B\({}_{3}\)  
Among the eight vitamins in the B group necessary for the correct body functioning, B\({}_{3}\), also known as niacin/3-pyridinecarboxamide, is essential for maintaining a healthy skin, proper breathing and metabolism and to keep the nervous system fully functional. An increase in its amount may create skin problems, diarrhea, wheezing, etc. Hence, the quantification of vitamin B\({}_{3}\) is necessary in body as well as in pharmaceuticals. In 2013, a molecular imprinted hydrogel-based SPR fiber optic sensor utilizing colloidal crystal templating was reported [159]. The polymer was prepared using vitamin B\({}_{3}\) with acrylamide/bis acrylamide as cross-linker, TEMED as catalyst and APS as initiator. The fabrication of sensor probe was performed by coating silver film of 40 nm over unclad fiber. The colloidal crystal templates were prepared by dip coating it in diluted solution of monodispersed polystetene spheres. The fiber was then tilted by 15-20\({}^{\circ}\) and the polymerized solution was added drop by drop. The fiber was dipped in dimethylbenzene for 30 min to remove the colloidal crystals and then in acetic acid solution for 6 h to create the imprints. The finalized probe was named \"colloidal crystal template-vitamin B\({}_{3}\) imprinted optical fiber probe\". The sensor probe was characterized for analyte concentration of 0 to 10 mg/mL with a red shift in resonance wavelength of 16.651 nm for the SPR curves recorded as shown in Figure 12.  
Riboflavin/vitamin B\({}_{2}\) is another nutrient that belongs to the same family. The sources of riboflavin are egg, milk and leafy vegetables. A riboflavin sensor using SPR and a molecularly imprinted hydrogel has also been reported in the literature [160]. The sensor was characterized for riboflavin concentration range of 0-320 ug/mL where the sensor showed a blue shift in resonance wavelength with the increase in riboflavin concentration.
# Recent Trends of Authentication Methods in Extended Reality: A Survey
## 6 Discussions and Future Research Directions
Most of the proposed biomechanical schemes used head or hand movement patterns for authentication rather than other body parts' movements due to the ease of data collection through embedded IMUs in HMDs. Bio-signal-based biometrics appear more promising than the other two types of behavioral biometrics in terms of usability due to their naturally seamless user interaction and adaptability, coupled with robust security due to their uniqueness and continuity. Two-factor (2F) knowledge-based schemes represent 72% of the total studies of multifactor and multimodal authentication schemes in XR. Multifactor-knowledge-based schemes constitute only 6%, while the rest is shared equally between biometric-based multifactor and biometric-based multimodal schemes with 11% each. Multifactor authentication schemes (including 2F schemes) provided enhanced security compared to single-factor ones because they required attackers to breach multiple layers of security, making unauthorized access more difficult. However, multimodal authentication schemes excel in security by combining knowledge-based factors with biometric-based factors, significantly reducing the risk of potential attacks. Attackers found it challenging to simultaneously overcome a knowledge factor and replicate a biometric trait, which enhances the overall system's security. We also extracted a few key findings, identified research gaps, and proposed suitable recommendations. By addressing these recommendations, researchers can significantly contribute to advancing the field of XR authentication, ensuring robust security and improved user experiences. * _Addressing Imbalances:_ There exists an imbalance in survey research dedicated to security, privacy, and authentication in the metaverse in comparison with its subfields. We motivate researchers to contribute more review papers targeting authentication in AR, VR, XR, and MR individually. Additionally, detailed surveys on knowledge-based and biometric-based authentication methods and their applications in XR are encouraged. * _Focus on Biometrics:_ There is a lack of surveys investigating technologies, techniques, and mechanisms specific to each biometric authentication method. We suggest focusing on XR authentication by considering individual biometric factors such as eye tracking, bio-signals, etc. * _Explore Portability:_ We encourage researchers to explore the transferability, security, and usability of well-established authentication techniques from devices like smartphones and ATMs to XR environments and devices. * _Include Essential Metrics:_ Accuracy and usability metrics such as EER, F1 score, etc. are essential in determining the success of an authentication system. We highlight the absence of such important measures in many papers and suggest their inclusion in future research for a better understanding of the proposed systems' feasibility.
# Numerical Analysis on Spanwise Correlation of Vortex-Induced Force of Split Double-Box Beam
## 2 Basic Theory and Methods
### Numerical Simulation of Turbulent Flow
#### 2.2.2 SST k-\(\omega\) Turbulent Flow Model  
The SST (Shear Stress Transport) \(k\)-\(\omega\) model is a hybrid model proposed by [PERSON] [21], whose core idea is to combine the \(k\)-\(\varepsilon\) model and the \(k\)-\(\omega\) model. The \(k\)-\(\omega\) model is used for the boundary layer region and the \(k\)-\(\varepsilon\) model for the free shear flow region, making full use of their respective advantages to improve the reliability and accuracy of the model. The expression of the SST k-\(\omega\) model is given by:  
\[\rho\frac{Dk}{Dt}=\frac{\partial}{\partial x_{j}}\Bigg{(}\mu_{eff,k}\frac{ \partial k}{\partial x_{j}}\Bigg{)}+S^{k} \tag{8}\]  
\[\rho\frac{D\omega}{Dt}=\frac{\partial}{\partial x_{i}}\Bigg{(}\mu_{eff,\omega} \frac{\partial k}{\partial x_{i}}\Bigg{)}+S^{\omega} \tag{9}\]  
where: \(\mu_{eff,k}\) and \(\mu_{eff,\omega}\) is equivalent viscosity of the turbulent term, \(S^{k}\) and \(S^{\omega}\) are the source term of the specific dissipation rate of turbulent kinetic energy.  
The reliability of the computational results using the SST \(k\)-\(\omega\) model has been confirmed by many scholars. Given this, the SST \(k\)-\(\omega\) model is used to simulate the turbulent viscosity in this paper [22; 23; 24].
# Exploring the Potential of Yellow Mealworm (_Tenebrio molitor_) Oil as a Nutraceuticalal Ingredient
###### Abstract  
During defatted _Tenebrio molitor_ (TM) larvae powder production, oil is obtained as a by-product, mainly intended for feed enrichment or as a biofuel component. In 2021, EFSA authorized TM as the first insect to be a novel food. Thus, the study aimed to assess the composition, including fatty acids (FAs), tocopherols, carotenoids, phenolics, volatiles, antioxidant capacity, sensory aroma attributes, physical properties, and oxidative and hydrolytic stability of TM oil. The FAs profile was dominated by oleic--C18:19\(c\) (36.8%) and linoleic--C18:29\(c\)12\(c\) (32,4%) acids, resulting in a PUFA/SFA ratio similar to vegetable oils. Thus, TM oil was characterized by a beneficial Health Promoting Index (HPI) (2.42), which was 10-fold higher than the HPI of common animal fats. TM oil contained bioactive compounds such as carotenoids (13.65 mg/kg), tocopherols (105.8 mg/kg), and phenolic compounds (74 mg GAE/kg). A noticeable amount of apigenin was also noted among nine detected phenolic compounds. The substantial presence of lipophilic and phenolic compounds contributed to antioxidative potential. Sensory estimation revealed the dominance of fried and nutty aromas, probably because of the abundance of Strecker aldehydes and pyrazines in their volatile profile. The results indicated that the technological process needs modification to limit the formation of lipid oxidation volatile compounds such as aldehydes and eliminate some differences between batches. This preliminary study on the composition and properties of TM oil encourages its use as an ingredient for food, pharmaceutical, and cosmetics purposes.  
Tenebrio molitor oil; volatile compounds; sensory aroma attributes; phenolic compounds; antioxidant properties; fatty acids; carotenoids; tocopherols 2024  
2024/133867/10.3390/foods13233867
## 2 Materials and Methods
### iTransformer-BiLSTM Prediction Method  
This study proposes a hybrid iTransformer-BiLSTM prediction method, as shown in Figure 5. The method leverages the advantages of both global feature extraction and local temporal modeling to achieve high-precision cooling load prediction in complex industrial scenarios. The method takes multivariate time series data (including outdoor temperature, humidity, indoor temperature, historical load, and other features) as input. First, the iTransformer module, through multi-head attention and feedforward neural networks, encodes the entire time series of each variable as independent tokens, avoiding the noise interference from cross-variable embeddings in traditional Transformers, and fully exploring the nonlinear interactions and global dependencies between variables. Considering that the output of the iTransformer is organized along the variable axis, this study introduces a projection layer with positional awareness to transform it into a time-axis feature sequence, thereby achieving the structural alignment required by the BiLSTM. On this basis, the BiLSTM module captures the forward and backward dependencies of local temporal features through a bidirectional gated recurrent mechanism, and combineswith a dropout layer to mitigate overfitting risks. Finally, the cooling load prediction value is output through a fully connected layer. Compared to single models, this hybrid approach integrates the global modeling capability of iTransformer for cross-variable interactions and the temporal dynamic analysis advantage of BiLSTM, significantly improving the prediction performance for multi-peak and periodic cooling load fluctuations.
## 5 Conclusions  
This paper uses a novel approach based on a variant of the famous particle swarm optimization algorithm using a cooperative coevolution framework and a motion-encoded mechanism to search for dynamic targets using multiple UAVs. On the one hand, the target search problem was converted from a Cartesian problem to a motion-based one via space transformation using the motion encoding feature. This transformation effectively prevents the algorithm from generating invalid search paths in the search process. On the other hand, the introduction of the co-evolution mechanism allows individuals to be guided by dynamic elite individuals in multiple populations during the updating process, thus preventing the algorithm from falling into premature convergence. The created algorithm was tested on six distinct scenarios with increasing levels of complexity, using different quantities of UAVs. The algorithm's performance was assessed by comparing it with five well-regarded swarm-based intelligent algorithms. The analysis of the results showcased the efficacy and dependability of the suggested approach when employed for dynamic target search with numerous UAVs.  
This paper solely focused on cumulative probability in the objective function. Additional objectives, such as minimizing fuel usage and avoiding restricted regions, barriers, and other limitations, may be explored in future research. These factors would transform the problem into a multi-objective one, which would require future extensions. Meanwhile, the primary focus of this paper is algorithmic investigation and subsequent validation through simulation. Nevertheless, real experiments are crucial and indispensable. Exploring the practical implementation of the algorithms proposed in this study for real search situations is a crucial area of future study.  
**Author Contributions:** Conceptualization, Y.L. and B.F.; methodology, Y.L.; software, Y.L.; validation, Y.L., W.C. and Z.W.; formal analysis, Y.L.; investigation, Y.L.; resources, L.H.; data curation, G.Y.; writing--original draft preparation, Y.L.; writing--review and editing, Y.L.; visualization, L.H.; supervision, G.Y.; project administration, G.Y.; funding acquisition, Z.W. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Nature Science Foundation of China, grant number 11774432.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to confidentiality agreement.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 11 Further Research Directions and Future Considerations
### Energy-Efficient Interconnection  
As previously mentioned, one of the key challenges in the DCN design is the associated energy consumption of the infrastructure. The employed optical technology in DCNs is predominantly a point-to-point communication among switches. This is achieved with the aid of optical fibers and transceivers. Usually, regarding the fiber, low-cost MMFs that are operating at 850 nm are employed, while for the optical transceivers, they are based on SFP technology. With this approach, for effective communication, it is essential for the optical transmitters to transform the packets into optical signals, while optical receivers have to convert the signal to the electrical domain. This is due to the fact that packet switching is executed by means of electronic switch fabrics. In light of this, for packet switching, a significant amount of energy is wasted in the process of O/E and electrical-to-optical (E/O) conversions not only at the transceiver modules, but also on the switch fabrics. Considerable latency is also incurred in the conversions process. Likewise, there is further latency aggravation because of electrical buffering that is required at the respective switch to address packet contention. To attend to these challenges in the DCNs, an all-optical interconnect in which switching can be entirely executed in the optical domain to prevent energy-intensive electrical switches' implementation is a promising solution. In this context, it is desirable to replace both electrical and opaque networks with transparent all-optical networks [74].
# Detection of Frozen Soil Using Sentinel-1 SAR Data
## 4 Results  
### Behavior of the Dielectric Constant with the Temperature  
Figure 3 shows the modeling results of the relative dielectric constant of soil (real part \(\varepsilon^{\prime}_{mf}\), and imaginary part \(\varepsilon^{\prime\prime}_{mf}\)) at different temperatures for the three typical soils used in this study (Table 1). \(\varepsilon^{\prime}_{mf}\) and \(\varepsilon^{\prime\prime}_{mf}\) increase strongly, especially for temperatures between \(-5^{\circ}\) and \(0^{\circ}\)C. The highest difference of the real part of the dielectric constant before and after freezing is approximately 10 for soil of silty clay, 11 for soil silt loam and 13 for soil sandy loam (for soil moisture content of 30 vol%). The imaginary part of the dielectric constant decreases from 3.2 to 0 for silty clay and silt loam soils and from 3.6 to 0 for sandy loam soil.
## 4 Core Insights and Critical Reflections
### Constraints of Policies, Regulations, and Standardization Systems
With the rapid development of UAV technology and the continuous expansion of its application domains, existing regulatory systems often struggle to fully adapt to new circumstances. Regulatory policies may suffer from being outdated, ambiguous, or overly complex, thereby creating confusion and compliance risks for UAV operators [218]. For example, some regulations lack clear or flexible provisions regarding UAV definitions, classifications, operator qualifications, and operational licensing. Additionally, challenges remain in terms of coordination between regulatory bodies and the harmonization of cross-regional oversight. A dynamic and adaptive regulatory framework is urgently needed--one that keeps pace with technological advancements, clearly delineates regulatory responsibilities, simplifies approval processes, and strengthens enforcement against violations. (5) Liability Attribution and Insurance Mechanisms. During flight or operational activities, UAVs may encounter unexpected accidents that result in personal injury or property damage. Determining liability--whether it lies with the operator, manufacturer, or a third party--and establishing corresponding insurance mechanisms are critical for safeguarding stakeholders' interests and ensuring the sustainable development of the industry. At present, relevant laws, regulations, and insurance products remain underdeveloped. In the event of an accident, the attribution of responsibility and compensation may prove challenging. It is essential to clearly define the legal responsibilities associated with UAV operations and to promote the development of diversified UAV insurance products to help mitigate and distribute operational risks.
###### Abstract
However, there is a lack of efficient strategies to utilize the characteristic of both GEO and LEO in a hybrid GEO/LEO quantum satellite network, resulting in the resource wastage. In this work, we remedy the lack of routing schemes for secret-key provisioning in hybrid GEO/LEO quantum satellite networks. We present a novel routing scheme that improves the efficiency of secret-key provisioning and propose three algorithms to fully utilize the superiorities of GEO and LEO. The main contributions of this paper are described as follows. 1. A layered architecture for quantum satellite networks is proposed, where the quantum key pool layer is decoupled from the dynamic physical topology for implementing efficient key management. 2. We present a novel topology abstraction-based routing scheme for secret-key provisioning, where the quantum key pools are utilized to construct the abstracted topology for routing over the classical channels. 3. We propose three heuristic algorithms, namely the GEO-free topology abstraction-based routing (GF-TAR) algorithm, the LEO-first topology abstraction-based routing (LF-TAR) algorithm, and the mixed satellite topology abstraction-based routing (MS-TAR) algorithm. The rest of this paper is organized as follows. The related works are reviewed in Section 2. The network architecture is presented in Section 3. Section 4 describes the novel topology abstraction-based routing scheme for secret-key provisioning. Section 5 proposes the heuristic algorithms. Section 6 presents the simulation results and analyzes the performance of the proposed algorithms. This paper is concluded in Section 7.
## 3 Discussion
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Clinical Application** & **Software** & **PICO** \\  & & **(Populations, Intervention, Comparison, Outcome)** \\ \hline \multirow{4}{*}{\begin{tabular}{c} Maxillectomy and orbital \\ reconstruction [30] \\ \end{tabular} } & CMF 1.4 & \begin{tabular}{c} P: Patients with maxillary and orbital defects: 19; benign \\ tumor: 11, malignant tumor: 8, median age: 44 years. \\ \end{tabular} \\  & (Materialize, Belgium) & I: Surgery under guidance of a navigation system. \\  & iPlan CMF 3.0 & C: CT scan analysis, globe projection, and orbital volume. \\  & (BrainLab, Germany) & O: Average maximum deviation was 24 \(\pm\) 0.2 mm. \\ \hline \multirow{4}{*}{\begin{tabular}{c} Maxillectomy and deep circumflex \\ iliac artery (DCIA) flap \\ reconstruction [31] \\ \end{tabular} } & \multirow{4}{*}{3D printing guide system (Aview, Coreline soft, Korea)} & P: A 59-year-old male patient with squamous \\  & & cell carcinoma. \\  & & cell carcinoma. \\  & (Aview, Coreline soft, Korea) & I: Total maxillectomy with surgical guide. \\  & & C: Postoperative CT image was compared. \\  & & O: Accurate positioning of DCIA flap as planned. \\ \hline \multirow{4}{*}{\begin{tabular}{c} Maxillectomy and fibular \\ reconstruction [32] \\ \end{tabular} } & \multirow{4}{*}{Advantage Windows 3D} & P: A 21-year-old woman with squamous cell carcinoma. \\  & & I: Surgery under rapid prototyping 3D resin models of \\  & & Analysis Package Version 1.2 & total maxillectomy and fibula model. \\  & & with GE scanner & C: 3D CT reconstruction after 1 year. \\  & & O: Adeuate functional and esthetic results. \\ \hline \multirow{4}{*}{\
\begin{tabular}{c} Maxillectomy and orbital \\ reconstruction [33] \\ \end{tabular} } & \multirow{4}{*}{
\begin{tabular}{c} iPlan CMF 3.0 \\ (BrainLab, Germany) \\ \end{tabular} } & P: Patients who underwent maxillectomy, including the \\  & & orbital floor: 10, benign tumor: 4, malignant tumor: 6, \\  & & mean age: 42.1 years. \\  & & I: Surgery under computerized navigation system, \\  & & prefabricated titanium mesh was fitted to the orbital \\  & & floor defect. \\  & & floor \\  & & C: Postoperative globe projection and orbital volume on \\  & & the reconstructed and unaffected sides were measured \\  & & using iPlan CMF. \\  & & O: Globe projection was 15.91 \(\pm\) 1.80 mm on the \\  & & reconstructed side and 16.24 \(\pm\) 2.24 mm on the unaffected \\  & & side (P = 0.505). The orbital volume was 26.01 \(\pm\) 1.28 mL \\  & & on the reconstructed side and 25.27 \(\pm\) 1.89 mL on the \\  & & unaffected side (P = 0.312). \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Previous studies of surgical interventions for maxillectomy. was evaluated in this study. Assessment of the accuracy and practicality of the AR guide is necessary through additional studies.
## 5 Results and Discussion
### Benchmark Model  
To evaluate the effectiveness of the proposed anomaly detection network, comparison experiments were conducted on the custom dataset with four benchmark models. These models included the Deep Auto-Encoder (DAE) from [28], Generative Adversarial Network (GAN) with one and multiple discriminators from [26], Anomaly Transformer from [29], and TadGAN from [30].  
DAE builds the reconstruction network using solely fully connected layers. It consists of one encoder and one decoder, but without frequency domain processing or a skip connection. Moreover, to ensure a fair comparison, the sliding window size of DAE was also set to three and the input size was set to 15. Both the encoder and decoder have one fully connected hidden layer. To enable model training and online testing, the GAN model employs a second submodule called the discriminator in addition to the main reconstruction network called generator. The discriminator network, representing a more complex mathematical representation, can further improve the reconstruction ability of the generator. The Anomaly Transformer introduces a unique anomaly attention mechanism to calculate the association discrepancy. Employing a minimax strategy, it enhances the ability to distinguishing between normal and abnormal associations; more specifically, it  
Figure 5: Example of the time series data for energy consumption in the custom dataset.  
utilizes the distance between the association discrepancies measured by the KL divergence as the detection criterion. TadGAN utilizes LSTM recurrent neural networks in both the generator and discriminator to capture the temporal correlations of time series distributions. The model is trained using a cycle consistency loss, facilitating efficient reconstruction.