esa-sceva/satcom-chunk-collection huggingface dataset:
## Discussion
The RT-PCR studies of genes involved in the processes support these findings. The expression levels of autolysin like gene (_Alt_E) increased many folds upon exposure to essential oils (MD-1 and MF-1) and CHX, indicating that these test compounds induce apoptosis-like activity in _S. mutans_, resulting in decreased cell metabolism and viability. It has been reported in earlier studies that essential oils from _S. persica_ L. cause cell wall damage in _S. enterica_[11]. Previously, we have also reported that essential oil compounds carvacrol and thymol cause apoptosis-like activity in _S. mutans_[14], which may be due to various reasons, including stress. The increased expression of _sod_A gene shows that exposure to the tested essential oils induces oxidative stress in _S. mutans_. Studies have demonstrated that isothirates can cause general stress in _E. coli_, as evidenced by the increased concentration of general stress regulator molecule guanosine penta/tetraphosphate ((p)ppGpp) [23]. Biofilm formation by oral pathogens is one of the most important traits contributing to their pathogenicity [19; 24; 25]. It was found that MD-1 and MF-1 both reduce the biofilm formation activities of _S. mutans_ significantly, as biofilm formation was inhibited by \(87\pm 6\%\) and \(82\pm 7\%\), in the presence of 10 \(\upmu\)g/mL MD-1 and MF-1, respectively. A decrease in the expression of glycosyl transferase gene _gtf_B supports the observation that exposure to essential oils causes a decrease in biofilm formation. Benzyl isothirate is also known to inhibit biofilm formation in _Pseudomonas aeruginosa_[26]. This inhibition may be due to the inhibition of quorum sensing, which plays an important role in biofilm formation. When the activities of MD-1 and MF-1 were compared, the latter exhibited higher antimicrobial activity. This is probably due to the comparatively higher concentration of benzyl isothiamate (Table 1) in MF-1. Among the three essential oils tested in this study, the least effective was clove oil. These results conclusively prove that the tested essential oil possess strong antimicrobial and antibiofilm activity against _S. mutans_, which is comparable to CHX. Therefore, benzyl isothianate-rich essential oils from _S. persica_ L. can serve as a good antimicrobial agent for oral hygiene and can also replace CHX, which, in addition to being an effective chemical antimicrobial agent, has many disadvantages such as its bitter taste, taste alteration for at least 4 h and tooth discoloration [15]. Other factors such as the toxicity of essential oils of _S. persica_ L. rich in benzyl isothiamate and benzyl isothianate alone should also be checked at realistic doses in human subjects before its commercialization. However, since it has been used traditionally for centuries with no known toxicity, the use of these essential oils for oral hygiene is highly recommended.
## 5 Real-Time Detection  
As mentioned in the previous section, the detector's performance on static photos was sufficient and the model can help to detect specified electronics scattered along a flat surface. However, used products flow into the sorting area through the conveyor in recycling or waste treatment facilities. Therefore, real-time object detection capabilities are also important. To stimulate the supply of used products by a conveyor, randomly selected used small-sized electronics were placed on an experimental conveyor, and a video was recorded. Object detection tests were carried out by applying the trained detector to the videos. The video of real-time detection is provided in Supplementary Materials (Video S1). Figure 12 is an exemplary video frame with a mobile battery, a smartphone, and two electronic cigarettes in the frame. The targets were correctly detected and are shown in green bounding boxes with labels.  
Although the three types of targets mentioned earlier were detected, and no false detections of non-target products were recorded, there were instances where targets were not detected or were erroneously detected. As shown in Figure 13, no smartphone was detected. The glass back of the smartphone reflected the light from the dome illumination, resulting in a high brightness, which affected the detection results. As the smartphone moved away from the dome illumination, the reflection gradually diminished, and the detection of the smartphone became accurate again. Although the dome illumination was setup to eliminate the influence of external light sources and ensure a consistent experimental environment, it introduced a new issue. These products are sometimes designed with highly reflective surfaces to meet esthetic requirements. Therefore, selecting an appropriate lighting device for detecting small household appliances requires further study.  
As shown in Figure 14, a smartphone was mistakenly identified as heated tobacco equipment. During the creation of the dataset for this study, the main body and the stick part of the heated tobacco equipment were not labeled separately. It can be inferred that these misidentified targets are unlikely to be confused with the stick part of the heated tobacco equipment. The targets misidentified as the heated tobacco equipment are typically located at the edges of the video frame, where they are partially visible. Their size and appearance closely resemble the main body of heated tobacco equipment, which increases the likelihood of misidentification. However, when these targets appear in the center of the video window, they can be correctly detected. To eliminate such misdetections, we should label these targets on the edge and add such data to the dataset. Although item  
Figure 12: Frame of detection video of the small-sized electronics flow on a conveyor.  
misdetection was encountered, the fire-causing items were successfully distinguished from other safe, small-sized electronics. Thus, we concluded that the developed detector showed a sufficient performance.
## Appendix A Dipole-Dipole Hamiltonians for \(N=7\) and \(N=8\) BChls  
Joint dipole-dipole interactions among BChls inside each monomer in the FMO complex considering seven or eight BChls have been obtained through spectroscopy studies complemented with theoretical analysis. We report those matrices in units of cm\({}^{-1}\) used in multiple analysis for the behavior of each monomer of FMO complexes. For \(N=7\) BChls in _C.__tepidum_ (from Tables 1 and 4 in [13]) with a constant diagonal offset of 12,210 cm\({}^{-1}\) to set the lowest site energy to zero, \(H_{S}\) is:  
\[H_{S}=\left(\begin{array}{rrrrrrr}200&-87.7&5.5&-5.9&6.7&-13.7&-9.9\\ -87.7&320&30.8&8.2&0.7&11.8&4.3\\ 5.5&30.8&0&-53.5&-2.2&-9.6&6.0\\ -5.9&8.2&-53.5&110&-70.7&-17.0&-63.6\\ 6.7&0.7&-2.2&-70.7&270&81.1&-1.3\\ -13.7&11.8&-9.6&-17.0&81.1&420&39.7\\ -9.9&4.3&6.0&-63.3&-1.3&39.7&230\end{array}\right) \tag{1}\]  
and for \(N=8\) BChls in _C.__tepidum_[37], with a constant diagonal offset of 12,150 cm\({}^{-1}\), \(H_{S}\) becomes:  
\[H_{S}=\left(\begin{array}{rrrrrrr}255&-87&4.2&-5.2&5.5&-14&-6.1&21\\ -87&355&28&6.9&1.5&8.7&4.5&4.2\\ 4.2&28&0&-54&-0.2&-7.6&1.2&0.6\\ -5.2&6.9&-54&150&-62&-16&-51&-1.3\\ 5.5&1.5&-0.2&-62&320&60&1.7&3.3\\ -14&8.7&-7.6&-16&60&425&29&-7.9\\ -6.1&4.5&1.2&-51&1.7&29&225&-9.3\\ 21&4.2&0.6&-1.3&3.3&-7.9&-9.3&280\end{array}\right) \tag{2}\]Despite our main analysis is performed for _C. teridium_, other specie under an intensive research is _P. aestuarii_. Thus, for \(N=7\) BChls in _P. aestuarii_ (from Tables 2 and 4 in [13]) with a constant diagonal offset of 12,230 cm\({}^{-1}\) to set the lowest site energy to zero, \(H_{\rm S}\) becomes:  
\[H_{\rm S}=\left(\begin{array}{ccccccc}215&-98.2&5.4&-5.9&7.1&-15.2&-13.5\\ -98.2&220&30.5&7.9&1.4&13.1&8.5\\ 5.4&30.5&0&-55.7&-1.8&-9.5&3.1\\ -5.9&7.9&-55.7&125&-65.7&-18.2&-58.2\\ 7.1&1.4&-1.8&-65.7&450&88.9&-3.4\\ -15.2&13.1&-9.5&-18.2&88.9&330&36.5\\ -13.5&8.5&3.1&-58.2&-3.4&36.5&280\\ \end{array}\right) \tag{11}\]  
and for \(N=8\) BChls in _P. aestuarii_[1], with a constant diagonal offset of 12,178 cm\({}^{-1}\), \(H_{\rm S}\) is:  
\[H_{\rm S}=\left(\begin{array}{ccccccc}424&94.8&5.5&-5.9&7.1&-15.1&-12.2&39.5 \\ 94.8&320&29.8&7.6&1.6&13.1&5.7&7.9\\ 5.5&29.8&0&-58.9&-1.2&-9.3&3.4&1.4\\ -5.9&7.6&-58.9&334&-64.1&-17.4&-62.3&-1.6\\ 7.1&1.6&-1.2&-64.1&424&89.5&-4.6&4.4\\ -15.1&13.1&-9.3&-17.4&89.5&305&35.1&-9.1\\ -12.2&5.7&3.4&-62.3&-4.6&35.1&298&-11.1\\ 39.5&7.9&1.4&-1.6&4.4&-9.1&-11.1&548\\ \end{array}\right) \tag{12}\]  
While for the \(H_{\rm S}\) in _P. aestuarii_ with \(N=8\) BChls [1], we have developed a similar but more limited parametric analysis of its quantum properties [52]. This \(N=8\) Hamiltonian has been obtained using the charge density coupling method [13; 68] assuming a standard protonation pattern. Values presented consider a relative dielectric constant border between baseplate and RC complex \(\epsilon_{\rm border}=80\), representing the experimental conditions of a fully solubilized FMO complex. In our analysis, we are also applied the HEOM method on _P. aestuarii_ to get a brief comparison of the quantum regime features as for _C. teridium_ in our main analysis.
## 2 Related Works  
### Academic Research  
Since the advent of wireless communication technologies, achieving seamless communication has been a fundamental objective pursued by nearly all communication technologies. Conventional wireless communication networks incorporate radio access network selection algorithms, including handover mechanisms, which predominantly prioritize signal strength as the key determinant in network switching decisions, with the overarching objective of maintaining device connectivity throughout transitions [14]. In the trajectory of mobile communication systems progressing beyond 5G, often referred to as 6G, considerable academic research has been conducted to formulate frameworks and protocols that facilitate seamless provisioning of wireless communication anywhere, anytime [15; 16; 17; 18; 19; 20; 21; 22; 23]. This pursuit seeks to not only enhance throughput and bolster reliability but also to optimize radio resource utilization across various radio access technologies (RATs) within a unified communication ecosystem.  
Within the realm of maritime communication, pertinent related works elucidate approaches for incorporating autonomous ships into a cohesive communication framework, encompassing advancements like 5G and its evolutionary successors (i.e., 6G) with AI-aided solutions for ubiquitous connectivity in the maritime communication environment [24; 25; 26; 27; 28; 29]. The investigation into the harmonious coexistence of autonomous and conventional vessels has also been explored, aiming to facilitate the autonomous ships' effective conveyance of their operational status and intentions to traditional ships via diverse maritime communication methods [30].
## 2 Synthesis
### In-Situ Method  
Carbon doped anatase TiO\({}_{2}\) spheres can be prepared via an in situ method, which was considered to avoid the aggregation of carbon species arises in external carbon precursors addition. Furthermore, carbon can dope in the place of oxygen in the TiO\({}_{2}\) lattice [4]. Some researchers [62; 63; 35; 67] have reported the synthesis of BCPs using the in situ method. [PERSON] et al. [67] proposed an in situ approach to insert TiO\({}_{2}\) in the bacterial cellulose matrix. Typically, bacterial cellulose hydrogel was suspended in H\({}_{2}\)SO\({}_{4}\) solution (65%), followed by dropwise addition of TiO\({}_{4}\)-H\({}_{2}\)SO\({}_{4}\)-H\({}_{2}\)O and constant stirring. Then, the mixture was filtered, washed, and dried under vacuum to obtain the BCPs. The ex situ method was also employed for comparison. Spherical bacterial cellulose hydrogels were mixed with P25 and deionized water, forming a sol-gel solution. Afterwards, the as-fabricated mixture was stirred, separated, and washed to remove the residues for further use. They found that the MB removal rate of 70.83 % and 89.58 % were achieved, through in situ and ex situ route, respectively.  
Very recently, [PERSON] et al. [62] synthesized BCPs via an in situ precipitation method (Figure 2E). The magnetic BC@CoFe\({}_{2}\)O\({}_{4}\) was fabricated by a one-pot method. Pine pollen was mixed with Fe(NO\({}_{3}\))\({}_{3}\).9H\({}_{2}\)O and Co(NO\({}_{3}\))-6H\({}_{2}\)O and stirred overnight, followed by pH adjusting till 12 with NaOH and stirring another 1 h. Then, the obtained solution was heated at 180 \({}^{\circ}\)C for 12 h. Later, the as-prepared powder was pyrolyzed at 500 \({}^{\circ}\)C under nitrogen atmosphere to obtain the magnetic biochar (BC@CoFe\({}_{2}\)O\({}_{4}\)). BC@CoFe\({}_{2}\)O\({}_{4}\)/Ag\({}_{3}\)PO\({}_{4}\) was further synthesized via the in situ precipitation method. BC@CoFe\({}_{2}\)O\({}_{4}\) were added to C\({}_{2}\)H\({}_{6}\)O\({}_{2}\) and sonicated for 30 min, followed by adding 50 mL AgNO\({}_{3}\). Then, 50 mL Na\({}_{2}\)HPO\({}_{4}\).12H\({}_{2}\)O was dropwise added to the above mixture and kept stirring. Later, the as-prepared mixture was washed and collected for further use. They demonstrated that the increased photocatalytic performance for bisphenol A removal was owing to the in situ process.
# Performance Evaluation of LoRa Communications in Harsh Industrial Environments
## 5 LoRa under Noisy Channel
### Many to One Mode  
Figure 12 shows the M\(\mathrm{\ddot{u}}\)O communication mode, where sixteen LoRa transmitters are responsible for sending 1000 packets each to a single LoRa non-coherent receiver. This  
Figure 11: Pocket Error Rate over a fading channel with industrial noise for the OtM mode.  
Figure 10: Pocket Error Rate over a fading channel with AWGN noise for the OTM mode.  
communication takes place in the same configurations as OUM: LOS and NLOS. At the start of the sending process, each transmitter modulates the data into LoRa signals and transmits them in an AWGN or Industrial transmission channel to the receiver. Since there are no physical obstacles in the LOS configuration, LoRa signals propagate easily from each transmitter to the receiver. In contrast, due to obstacles in the NLOS configuration, some signals may be attenuated, weakened, or distorted. The receiver receives the available signals and stores them temporarily in a buffer to synchronize them, then demodulates and processes them independently until the last packet is sent.  
In the M\(\mathrm{O}\) communication mode, the signal is detected for all transmitters, as shown in Figures 13 and 14. However, performance in terms of packet error rate is reduced in all configurations considered as shown in Figure 13. This is due to AWGN noise in addition to the effect of multipath, which causes interference between signals from different transmitters. The channel effect is more pronounced in the NLOS configuration, where signals encounter obstacles in addition to AWGN noise, resulting in reflections, diffractions, and dispersions of the signals. As a result, several components of the same signal reach the receiver with different delays and powers.  
Figure 12: LOS and NLOS configurations for M\(\mathrm{O}\) mode.  
Figure 13: Pocket Error Rate over a fading channel with AWGN noise for the M\(\mathrm{O}\) mode.  
Performance in terms of PER is greatly reduced in the case of industrial noise in both the LOS and NLOS configurations. However, this architecture can correctly receive packets from signal-to-noise ratios of 4 and 18 dB for SF12 and SF7, respectively, in the LOS configuration and from 35 and 49 dB for the same spreading factors in the NLOS configuration, as shown in Figure 14.  
The simulations in this section highlighted a significant degradation in the PER performance of LoRa technology in an industrial environment. This degradation can be problematic, particularly when the data being transmitted is critical. The consequences can include transmission errors, increased latency, or total packet loss. In such situations, the integration of error correction techniques is essential. Forward error correction, as represented by the Hamming code, offers one approach to remedying such errors. This topic will be explored in greater depth in the next section.
# Design, Implementation, and Analysis of a Block Cipher Based on a Secure Chaotic Generator
## 1 Introduction
The diffusion and confusion process required data sequences, which were created by perturbing the chaotic variables with the secret key. The confusion process was controlled by the chaotic points themselves, whereas the diffusion process was controlled by an ergodic chaotic map. [PERSON] et al. [30] developed a new lightweight block cipher to protect the security of data acquired by Internet of things (IoT) sensor. It consisted of a customized AES algorithm with a chaos-based S-box and a chaotic map. Despite having good cryptographic characteristics and a high amount of randomness, this was related primarily to the AES underlying structure and not to the modified S-box. Additionally, AES was not well recognized for its lightweight implementation and could not be appropriate for IoT devices with constrained resource in terms of computing capabilities. In this paper, we propose an efficient encryption/decryption system based on a secure pseudorandom number generator of chaotic sequences (PRNG-CS) and a strong key-dependent S-box. The proposed chaos-based cryptosystem design takes into account the weaknesses and strengths of the systems mentioned above. The proposed PRNG-CS is able to prevent the divide-and-conquer and the SCA attacks. This PRNG-CS is used to build the key-dependent S-box. It also provides the encryption/decryption keys necessary for the substitution and permutation operation [31; 32; 33; 34]. The remainder of this paper is organized as follows: In Section 2, we present the proposed chaos-based cryptosystem architecture with a deep insight of the PRNG-CS, the S-box with the circular substitution process, and the diffusion process, then we give the pseudocode of the encryption/decryption algorithms. In Section 3, we present the experiments results and security analysis of the proposed cryptosystem and its computing performance. Finally, Section 4 summarizes the whole paper.
## 3 Experimental Setup  
The proposed experimental configuration of the underwater photon-counting communication system is illustrated in Figure 1. The system is combined with a directly modulated laser diode (LD) transmitter, simulated underwater channel, and photon-counting receiver. The transmitter included LD, an attenuator, and collimating optics. The computer maps pseudorandom binary sequence (PRBS) to 32-PPM symbols. The 32-PPM symbols from the computer were fed into the arbitrary waveform generator (AWG) to be converted into a modulated analog signal that was amplified by an RF amplifier (SHF 100 AP) by 10 dB. In the experiment, we set the clock frequency and level amplitude of the AWG to 12.5 MHz and 400 mW, respectively. Then, the modulator (Thorlabs LDM9 LP) drove the amplified electrical signal onto the LD to generate the modulated optical signal. The bias tee superimposed a bias current that was controlled by a constant voltage source. The transmitted Gaussian beam generated from continuous wave LD (CW laser, Thorlabs LP450-SF15), after being fed into a subsequent variable attenuator (Thorlabs V450A), was expanded by a beam collimator system (NA = \(0.25,f\) = 10.9 mm). The output of the collimator was launched into a 5 m water tank. The mode field diameter launched was 2 mm, which means that the initial light divergence angle was 286 \(\upmu\)rad. At the received end, an enclosure housing the receiver optics was used to shade the background light. The receiver enclosure's input aperture diameter was 3 cm. A 4f magnification system based on L1 and L2 was used to reshape the beam. For limiting the field-of-view and rejecting the background light, an iris had a variable in the L1 focal plane that could control the angular field-of-view between \(\sim\)3 mrad and 158.5 mrad to reduce the impact of ambient noise and the multipath effect. Subsequently, the 1:1 beam splitter split the light into two paths. One of the paths was focused on the optical power measurement device, another path was focused on the photomultiplier tube (PMT, Hamamatsu H10682-210), and a high-resolution oscilloscope (OS) captured the output signal from PMT. After synchronization, the captured signal was demodulated and decoded into binary bits. The BER was then calculated by comparing the decoded bits to transmitted bits. The 10 nm optical filter (Thorlabs FBH520-10) in the PMT path was used to reject the out-of-band background.
# A Method for Managing ADS-B Data Based on a 4D Airspace-Temporal Grid (GeoSOT-AS)
## 3 A 4D Airspace-Temporal Grid Framework (GeoSOT-AS) for ADS-B Data Organization
### GeoSOT-AS Height Dimensional Profiling Rules and Methods  
#### 3.2.1 Height Dimensional Profiling Rules  
Oriented to the management of airspace and its elements, it was proposed to adopt the principle of flight altitude layers for profile selection across the height dimension. Regarding the flight altitude, the following base definitions were applied:  
The corrected sea level pressure height (QNH) refers to the pressure height with the corrected sea level pressure as the datum.  
Standard barometric height (QNE) refers to that with the standard sea level pressure as the datum.  
The flight altitude layer was divided by a certain altitude difference, with the standard atmospheric level serving as the reference plane. Equipping aircraft on different altitude layers, so that there is a specified safety altitude difference between aircraft, is an important measure to prevent aircraft collisions with each other or ground obstacles.  
In the flight path, if the QNH is used as the altimeter correction value, the aircraft will frequently adjust the QNH after passing through different areas, and it remains difficult to determine the vertical separation between aircraft. Therefore, using QNE as the altimeter correction value can simplify the flight operation, and ensure the altitude safety interval between aircraft.  
Based on the QNE altitude dialing positive values, the basic definition of flight altitude layers, and the division criteria, the following principles of altitude stratification coding were set corresponding to the segmented step function, yielding the following expressions (Equation (2)):  
\[Code(h)=\left\{\begin{array}{ll}Code_{2}&Flevel_{2}\leq h<Flevel_{3}\\ Code_{1}&Flevel_{1}\leq h<Flevel_{2}\\ Code_{0}&Flevel_{0}\leq h<Flevel_{1}\\ &\ldots\ldots\end{array}\right. \tag{2}\]  
Considering that the required flight airspace ranges from 0 to 50,000 m, one must consider the existence of areas on the surface with elevations <0 m (e.g., the Turpan Basin in China lies at \(-\)154.31 m). To ensure the uniformity and multi-scale of the division, while considering the general civil aviation use airspace \(\leq\)50,000 m, the coding support range was set from \(-\)150 to 76,800 m, and the specific division rules were as follows. Firstly, the overall range divided into two parts: \(-\)150 to 0 m, and 0 to 76,800 m, with 0 identifying the area above sea level, and 1 indicating the area below sea level (i.e., the first unsigned integer  
Figure 5: Planar dimensional coding scale and bit representation.  
is used to mark the above or belowground); secondly, combined with the actual Chinese flight altitude layer division standards, the current flight altitude layer was divided into 10 levels via bifurcation, with the finest granularity in the discrete form of 150 m. The corresponding altitude layer interval for each level is shown in Table 2.