esa-sceva/satcom-chunk-collection huggingface dataset:
# Investigation of the Influence of Splitter Blades on the Resonance Conditions of Impellers
## 4 Validation and Discussion
### Significance in Guiding the Compressor Design  
As mentioned earlier, there are two configurations for the vaned diffuser: the 19-vane diffuser and the 21-vane diffuser. As for the mistuned mode with this specific mistuning pattern, the result of the hazard evaluation for the excitations of various engine orders can serve as a guide for choosing a more appropriate number of diffuser vanes. For example, the excitation of EO21, which corresponds to the 21-vaned diffuser configuration, is capable of exciting the 13 th harmonic component of the mode. The excitation of EO19, which corresponds to the 19-vaned diffuser configuration, is capable of exciting the 15 th harmonic component of the mode. From the mistuned harmonic response result, we have found that the excitation of EO19 is more harmful than the excitation of EO21. Therefore, the 21-vaned diffuser configuration is the better choice when only considering this particular mistuned mode. It should be pointed out that the matching between the impeller and diffuser is a complex process which involves effort from both the aerodynamic side and structural side. So, the example here is only used to illustrate the significance of the proposed resonance conditions in guiding compressor design.  
In addition, as a means of vibration reduction, intentional mistuning has been studied and gradually applied to the conventionally designed bladed structures [38; 44]. The mechanism of it is to change the harmonic contents of the certain modes by introducing a special form of mistuning and thus to change the excitability of the determined excitation of these modes [37]. This indicates that the harmonic content of a mode must be determined when designing the intentional mistuning. From the research above, we know that as for impellers with splitter blades, the harmonic contents can be determined with the help of the concept of the blade-based RMV and the resonance can be identified by the proposed resonance conditions.
## 5 Flight Tests
### Task 1: Numerical Simulation  
The numerical simulation test, shown in Figure 3, is conducted using the nonlinear dynamics model of the prototype unmanned helicopter, together with a simplified closed-form trim calculation. The manipulated input signal is generated from a joystick device. Various moderately aggressive maneuvers are conducted during the simulation to evaluate the performance of the proposed algorithm at different operate points of the flight envelope. A comparison is made between the output of the plant and that of the model, as shown in Figure 3a,b, which demonstrates that the tracking error can rapidly approach zero  
Figure 3: Numerical simulation results of the proposed algorithm. (**a**) \(q_{{}_{m}}\) and \(q\) ; (**b**) \(e\) ; (**c**) \(\theta\); (**d**) Adjustable parameters.  
in 0.9 s and remain in a bounded range. We can therefore conclude that the proposed adaptive algorithm achieves a guaranteed model reference tracking performance and has a good convergence property. The tracking error remains in a bounded range even though the adjustable parameters vary rapidly during the test. However the conventional MRAC approach is not applicable to the case where the variations of the plant parameters are significant.
# Safety and Security Considerations for Online Laboratory Management Systems
## 3 Literature Review
### Security in Remote Laboratories and OLMS  
The security of remote laboratories is focused on two main areas: data security and instrument security. Most OLMSs are designed primarily for educational purposes, but they collect and store student personal data and login credentials. Data stored in the system database must be secured to prevent unauthorized use of the instruments. Because the students can manipulate the laboratory instruments remotely without supervision, the laboratory station's instruments can be at significant risk of being damaged. For this reason, instrument security is one of the most critical security aspects of the OLMS. There are three different levels of instrument security in remote laboratories:  
* Inflexible or static sharing: An instrument in a remote laboratory has some possible user input areas; a unique combination of these inputs related to specific functions is required in each laboratory experiment. In this situation, the security level must be controlled by the number of functions related to the inputs and restricting some instrumentation uses.
* Flexible or partial sharing: In this scenario, any input is connected with the corresponding function, and several combinations of this function can perform a range of values in a laboratory experiment activity. Here, the level of security is given by the number of functions allowed to the users over the instrumentation. Given that the user has more control over the instrumentation, it increases the risk of invalid inputs; for that reason, a stricter validation scheme is needed.
* Complete or total sharing: In this case, each input must be attached to an available function over the network with the capability of turning on/off the instruments, giving the user complete control over the remote laboratory instrumentation. The user controls the instrumentation, so strict and strong scheme validation is needed [64].
# Effect of Topography Truncation on Experimental Simulation of Flow over Complex Terrain
## 2 Experimental Method  
### Terrain Scale Model  
The topography investigated herein is an island located in the coastal region of South China. A view of this region is shown in Figure 1 along with the measurement locations for this study. For the wind tunnel test, wind speeds were measured at a total of five locations on the island, which are potential wind power sites. The center region of the island has the highest elevation with a mountain running northwest to southeast. There is a valley to the east of the mountain with another mountain stretching from the northeast to the southwest to the east of the valley. Overall, the topography of the island can be characterized as high-west and low-east. According to the topographic features of the island and the incoming flow direction, measurement locations were divided into three regions: windward region, leeward region, and valley region. As shown in Figure 1, location A1 was situated in the windward region, which is the windward slope of the center mountain, while locations A2 and A3 were situated at the leeward slope. The valley region representing the valley terrain at the island center included measurement locations of A4 and A5.  
For the wind tunnel testing, a 1:1300 scale terrain model was made of polyethylene foam and overlapped layer by layer according to the terrain contour line. The scale ratio was much larger than the ratio of 1:5000 recommended by [PERSON] [32] to avoid the error of turbulence viscous dissipation. The diameter of the test terrain model was 10 m for the full island model and 5 m for the truncation model with a maximum height of 0.41 m. The covered area of the terrain model was different according to the model diameter. The large one covered an area of approximately 132.7 km\({}^{2}\), and the small one covered an area  
Figure 1: Topography of island and measurement locations.  
approximately one-fourth the size of the larger one. The terrain of the full island is shown in Figure 1, and two circles indicate the areas covered by the terrain model with diameters of 10 m and 5 m. The blockage ratio was approximately 3.27% for the terrain model with a diameter of 10 m, which is lower than the maximum allowable blockage ratio of 5% recommended by [PERSON] (2018).
## 2 Macroscopic Unit-Cell
### Out-of-Plane Kinematics  
The variational principles of energy conservation and virtual displacements were followed to compute the elastic stiffnesses of the out-of-plane FE trusses; as provided for the in-plane case. Figure 3 depicts the out-of-plane basic cell of the macro-element. The geometrical parameters and the respective tributary areas for flexural and torsional FE trusses are given. Additionally, the kinematics of each allowable deformation mode is associated with a moment quantity defined in the input, or by integrating the in-plane stress-strain curves in the thickness direction.  
Equivalence between the bending energies of the discrete \(\left(U_{discrete}^{bending}\right)\) macro-element and a continuum \(\left(U_{continuum}^{bending}\right)\) plate media is postulated to retrieve the latter expressions. In such regard, the \(U_{continuum}^{bending}\) of a continuous FE plate subjected to bending is derived from Equation (9):  
\[U=\frac{1}{2}\int_{l}\frac{M^{2}}{EI}dl \tag{9}\]  
and given by:  
\[U_{continuum}^{bending}=\frac{1}{2}\big{(}\overline{E}_{ii}I\big{)}\chi^{2}(H+ e)=\frac{\overline{E}_{ii}H^{3}}{24(1-v^{2})}(H+e) \tag{10}\]The stored strain bending energy of the discrete system is derived through an ad-hoc formulation. Bearing that the strain of the axial out-of-plane truss-beams is \(\epsilon=\
icefrac{{\theta e}}{{t}}\) and \(\theta=\chi(H+e)\), \(U_{discrete}^{bending}\) is given as:  
\[U_{discrete}^{bending}=\frac{1}{2}M\theta=\frac{1}{2}\frac{E_{ii}^{bending\ truss}A_{t}e}{t} \theta^{2} \tag{11}\]  
By equating \(U_{continuum}^{bending}=U_{discrete}^{bending}\) the correct Young's modulus of the OOP flexural trusses is calculated according to Equation (12):  
\[E_{ii}^{bending\ truss}=\frac{\overline{E}_{ii}t^{4}H}{24e(1-\
u^{2})(H+e)eA_{t}} \tag{12}\]  
For torsion, the same procedure is followed. Briefly, the stored strain torsional moment energies of the discrete and continuum homogeneous media are given by Equations (13) and (14), as follows:  
\[U_{continuum}^{torsional}=\frac{\overline{G}Ht^{3}\theta^{2}}{24(2L+e)} \tag{13}\]  
\[U_{discrete}^{torsional}=\frac{E^{torsional\ truss}eH^{3}\theta^{2}}{16t} \tag{14}\]  
in which \(\overline{G}\) is the homogenised shear modulus given directly by the slope of the in-plane shear constitutive law. Thus, by respecting the energy equivalence between the systems, the correct Young's modulus of the torsional trusses is defined through Equation (15).  
\[E^{torsional\ truss}=\frac{2\overline{G}t^{4}}{3H^{2}e(2L+e)} \tag{15}\]  
Figure 3: Out–of–plane unit cell: the tributary area for each truss and kinematics of each allowable deformation mode.
## 4 Conclusions  
Applied HS-SPME/GC-MS/FID and USE/GC-MS/FID methodologies of monitoring nectar/honey-sac/honey pathways of the headspace, volatiles, and semi-volatiles was successful and complementary for the characterisation of _C. unshiu_ honey. The major headspace compounds from all nectar varieties were linalod, \(\alpha\)-terpineol, 1\(H\)-indole, methyl anthranilate, and phenylacetonitrile. Corresponding extracts contained, among others, 1\(H\)-indole, methyl anthranilate, 1,3-dihydro-2\(H\)-indol-2-one and caffeine. The major headspace compounds of the honey-sac were linalod, \(\alpha\)-terpineol, 1,8-cineole, 1\(H\)-indole, methyl anthranilate, and _cis_-jasmone. Characteristic compounds from related extract were caffeine, 1\(H\)-indole, 1,3-dihydro-2\(H\)-indol-2-one, methyl anthranilate, and phenylacetaldehyde. However, the honey headspace composition was significantly different in comparison to the nectars and the honey-sac content with respect to phenylacetaldehyde and linalod derivatives' abundances that appeared as the consequence of the hive conditions and the bee enzymes' activity. All extracts contained higher aliphatic compounds as the major constituents not useful for botanical origin determination, since they can originate from the comb environment. _C. unshiu_ honey traceability is determined by the following chemical markers: phenylacetaldehyde, phenylacetonitrile, linalool, and its derivatives (from the headspace), as well as 1\(H\)-indole, 1,3-dihydro-2\(H\)-indol-2-one, and caffeine (from the extracts). 1\(H\)-Indole, 1,3-dihydro-2\(H\)-indol-2-one, and phenylacetonitrile were found as particular compounds of _C. unshiu_ honey, not pointed out in previous studies of other _Citrus_ honey types.  
This research has been fully supported by the Croatian Science Foundation under the project (HRZZ-IP-11-2013-8547 \"Research of natural products and flavours: chemical fingerprinting and unlocking the potential\").  
I.J., S.P., L.S. and D.B. designed the experiments. S.P., Z.M., L.S. and M.Z. performed the experiments. S.P., Z.M., M.Z., C.I.G.T. and I.J. analyzed the data. All the authors discussed and planned the paper. I.J. and C.I.G.T. drafted the manuscript.  
The authors declare no conflict of interest.
# Resonance-Driven Passive Folding/Unfolding Flapping Wing Actuator
###### Abstract  
The wings of flapping-wing micro aerial vehicles (MAVs) face the risk of breakage. To solve this issue, we propose the use of a biomimetic foldable wing. In this study, a resonant-driven piezoelectric flapping-wing actuator with a passive folding/unfolding mechanism was designed and fabricated, in which the folding/unfolding motion is passively realized by the centrifugal and lift forces due to the stroke motion of the wings. Although the passive folding/unfolding is a known concept, its feasibility and characteristics in combination with a resonant system have not yet been reported. Because the resonant actuation is necessary for extremely small, insect-scale MAVs, research is required to realize such MAVs with a foldable-wing mechanism. Therefore, we first examine and report the performance of the resonant-driven passive folding/unfolding mechanism. We also present a simplified theoretical model demonstrating an interaction between the resonant actuation system and folding/unfolding mechanism. We successfully demonstrate the folding/unfolding motion by the fabricated actuator. In addition, the theoretical model showed good agreement with the experiment.  
foldable wing; piezoelectric actuator; biomimetics; resonant system Article
## 2 Thematic Review and Analysis
### Heat Source
#### 2.4.2 Combined Heat and Power
Their study, represented by the 'z-factor' (Equation (1) and Figure 10), finds that DH supply temperature significantly impacts electricity loss more than DH return temperature. However, unlike back-pressure cogeneration cycles, reducing the return temperature can yield substantial electricity savings under fixed supply temperatures in existing DH systems. \[z-factor=\dot{W}_{loss}/\dot{Q}_{produced}\ [MWh_{el}/MWh_{th}] \tag{1}\]  
The same relation for the z-factor (as a function of the supply and return temperature) can be seen for a nuclear plant at a capacity of 1 GW\({}_{\rm el}\), as cited from [79] (the same z-factor can also be found for a nuclear plant at a capacity of1.3 GW\({}_{\rm el}\) in this reference), as shown in Figure 11.  
[PERSON] et al. [11] reports an increase of 5 kWh\({}_{\rm el}\)/MWh\({}_{\rm th}\) for a 2-stage heat extraction cogeneration plant if the return temperature is reduced by a degree of 10 \({}^{\circ}\)C.  
* Extraction and Back-Pressure [PERSON] et al. [106] investigated the impact of return temperature on a cogeneration unit comprising: a back-pressure condenser used as a pre-heater for DH water, and a secondary condenser, fed by extraction from the low-pressure turbine, utilized to elevate DH water to the designated supply temperature. Figure 10: Illustration of the z-factor (electricity loss per produced heat) as a function of the DH return temperature at various degrees of the DH supply temperature (the degree values given in the graph legend), reproduced from the source data shown in [111; 112]. The electricity-to-heat ratio, defined as the cogeneration electricity output minus the electricity consumption of the DH and cogeneration cycle pumps, relative to the heat delivered to the DH, was assessed across varying DH heat loads and supply temperatures as functions of the return temperature. The return temperature shows minimal impact on the electricity-to-heat ratio across all DH heat loads and supply temperatures. For example, lowering the return temperature from 54 \({}^{\circ}\)C to 38 \({}^{\circ}\)C with a heat load of 43 MW\({}_{\text{th}}\) results in a minor increase in the ratio, with a difference of 0.013. Conversely, the DH supply temperature significantly affects the ratio; reducing it from 98.5 \({}^{\circ}\)C to 88.5 \({}^{\circ}\)C at the same heat load of 43 MW\({}_{\text{th}}\) results in a notable increase in the ratio, with a difference of 0.05 [106]. [PERSON] and [PERSON] [113] simulated a fuel-cell micro-cogeneration unit with a capacity of 1.5 kW\({}_{\text{el}}\) and 0.85 kW\({}_{\text{th}}\), employing a control scheme that maintains a fixed electricity output rate while allowing the thermal output to vary with the return temperature. The study illustrates how the return temperature affects the heat output of the solid oxide fuel cell, as depicted in Figure 12.
# A Novel TLS-Based Fingerprinting Approach That Combines Feature Expansion and Similarity Mapping
## 5 Discussion  
The results indicate that a combination of the two-fold approach of increased fingerprint granularity through feature expansion with similarity mapping can indeed improve malicious domain detection. Fingerprint granularity was improved in all the sample datasets resulting in improved similarity mapping in each dataset, with Dataset B, specifically relating to CDNs, being the most improved. As stated in the results section, Chapter 4, the aim of the approach was not to create clusters based on features but to calculate and visualise the similarities between application configurations. The fact that many applications formed natural clusters was an artefact of the process. This confirms that with many types of malware applications, there are limited variations in the way they are deployed.  
One of the major benefits of the approach is its ability to identify evolving threats and hidden malicious domains. The technique of TLS fingerprinting has been used successfully in cyber security for many years now, but the technique is not infallible, and small changes to configurations produce very different fingerprints. This leads to a new cycle of detection, where new malicious fingerprints must be identified and lists of known malicious fingerprints must be updated. In this situation, it is difficult to understand changes to malicious applications, because the fingerprints themselves are either overly verbose and require analysis to understand the changes or they are hashed and subsequently cannot be reversed. Although the technique presented here produces a 'hashed', enriched fingerprint, the similarity-mapping process ensures that small changes are maintained and represented visually. The benefit of this is that new fingerprints that appear close to known branches and clusters of bad domains can be instantly highlighted and flagged for further investigation.  
This approach has demonstrated a clear ability to discover new fingerprints and domains that are otherwise unidentified or have been classified as good. Across Datasets A and B, in just the five areas of mixed good, bad and unknown that were evaluated  
Figure 13: The LSH visualisation of dataset C, known malicious domains. Clear similarity patterns can be seen forming by capability. Go Phish domains are seen in yellow, Cert Pl orange, Metasploit pink, Tactical RRM purple and Burp Collaborator Blue.  
in the results, 67 new malicious domains were discovered, based on their similarity to known malicious domains alone. Of those, 37 were known good domains taken from the Tranco top 1 million [18], indicating that even maintaining and evaluating known goods against the most reputable list is not enough on its own to defend against phishing and malicious domains.
## 7 Conclusions  
In this paper, a trust mechanism FLTEM and reliable routing protocol TAFLRLR are proposed for UANs. Extensive simulation experiments are performed to evaluate the performance of the FLTEM and TAFLRLR protocols. We compare the performance of the network with and without FLTEM. The experimental results show that (1) The network without MN achieves the largest PDR and the lowest TEC. (2) The performance in terms of PDR and energy efficiency significantly drops when there are some MNs in the network. (3) The performance of the network with FLTEM is significantly improved compared with that without FLTEM. Therefore, the trust mechanism FLTEM and the routing protocol TAFLRLR proposed in this paper can improve the PDR and reduce the TEC of the network.  
In future research, we will further optimize the FLTEM mechanism and the TAFLRLR protocol by using deep reinforcement learning, swarm intelligence algorithms, and clustering algorithms to further improve the PDR, energy efficiency, and reliability of the network.  
Figure 19: The effect of the number of nodes on TEC.  
Figure 18: The effect of the number of nodes on PDR.  
**Author Contributions:** Methodology, D.H., X.L. and X.T.; Writing--original draft preparation, D.H.; Writing--review, D.H., X.D. and L.W.; Supervision, X.D. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported in part by the National Natural Science Foundation of China (61962052), the Key Laboratory of IoT of Qinghai (2022-ZJ-Y21).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data are contained within the article.  
**Conflicts of Interest:** The authors declare no conflict of interest.