esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Results
### Efficacy of PM 477 Compared to Standard Antimicrobials  
To compare the efficacy of PM-477 in suspension to the standard antimicrobials used to treat BV, we determined the minimum inhibitory concentrations (MICs) of PM-477, CLI, MDZ, and TDZ for 20 strains of _Gardureella_ by following the Clinical and Laboratory Standards Institute protocol [44]. All the _Gardureella_ species tested were highly susceptible to PM-477 with a MIC\({}_{\mathrm{\Phi}0}\) value (the MIC value which inhibits 90% of strains) of 8 \(\mathrm{\SIUnitSymbolMicro g}\)/mL (Table 2). The _G. swidsinskii_ strains had MICs in the range of 0.25-1 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, whereas the _G. vaginalis_ strains had MICs of 0.13-8 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, and _G. leopoldii and G. piotiti_ strains had MICs of 1-8 \(\mathrm{\SIUnitSymbolMicro g}\)/mL. Among this small number of strains tested for each species, there was no evidence that the four _Gardureella_ species differed with regard to their susceptibility to PM-477. Whereas 12 of the 20 _Gardureella_ strains were resistant to MDZ and 15 were resistant TDZ, CLI was effective against all strains at MICs \(\leq\) 1 \(\mathrm{\SIUnitSymbolMicro g}\)/mL. All tested strains of three _Lactobacillus_ species (_L. crispatus_, _L. gasseri_, and _L. jensenii_) were resistant to the highest  
Figure 3: PM-477 is highly specific for _Gardureella_ and spares lactobacillus and other BV-associated microbiome components. (**a**) _Gardureella_ strains, (**b**) _Lactobacillus_ spp., (**c**) and _Mobiluncus curtisii, Mobiluncus mulieris, Streptococcus agalaciae, Atopobium vaginae_, and _Prerotella bivia_ were tested for their susceptibility to PM-477 (20 \(\mathrm{\SIUnitSymbolMicro g}\)/mL for 5h; treated, black squares) and compared to buffer control-treated (untreated, white circles) bacteria suspensions. For statistical purposes, CFU/mL values from the untreated and the treated groups were log-normalized prior to applying the unpaired two-tailed multiple Student’s _t_-test. _p_-values \(\leq\) 0.05 were considered statistically significant; \(\boldsymbol{{}^{**}}\)_p_\(\leq\) 0.01, \(\boldsymbol{{}^{***}}\)_p_\(\leq\) 0.001, \(\boldsymbol{{}^{***}}\)_p_\(\leq\) 0.0001.  
concentrations of PM-477, MDZ, and TDZ (MICs \(>\) 128 \(\upmu\)g/mL), whereas only one strain was resistant to CLI. The concentration which killed \(>\)99.5% of cells (minimal bactericidal concentration MBC\({}_{99.5}\)) was also determined and is presented in the Appendix A Table A1.  
Figure 4: _Cont._  
Figure 4: PM-477 selectively kills _Gardnerella_ in a co-culture with lactobacillus. (**a**) Phase contrast microscopy of dense cultures of _G. vaginalis_ (ATCC14018T) (first row) and _G. swidäsinskii_ (GS10234) (second row), or co-cultures of _G. vaginalis_ (ATCC14018T) and _L. crispatus_ (LABCRI FB020-08c) (third row), as well as _G. swidäsinskii_ (GS10234) and _L. gasseri_ (LAB GAS LMC 9203T) (fourth row) treated with PM-477 (460 \(\mathrm{\SIUnitSymbolMicro\SIUnitSymbolMicro\SIUnitSymbolMicro\
## 1 Introduction
In addition, several other studies have analyzed the crystallization assisted by static electric fields. [PERSON] et al. found that with the increase in applied voltage, the nucleation temperature was shifted toward higher values [12]. The first study of crystallization assisted by an external electric field was conducted by [PERSON] in 1861 [13]. Later, in 1961, [PERSON] et al. found that certain types of insects were frozen at relatively high temperatures when exposed to a static electric field [14]. After, in 1963, [PERSON] found that freezing could be initiated in water drops at a temperature that was only a few degrees below 0 \({}^{\circ}\)C by applying external electric fields [15]. [PERSON] and [PERSON] studied the effect of electric currents on the nucleation of ice crystals [16]. On the other hand, considering the microscopic effects of static electric fields on the crystallization of water, molecular dynamics studies have been carried out with which critical electric field magnitudes have been identified to polarize the crystals with a structure similar to that of cubic ice [17; 18]. Electrofreezing also has potential applications in atmospheric sciences, where the freezing of supercooled raindrops in strong electric fields has been studied. [PERSON] et al. (1971) [3] found that supercooled water drops could be nucleated more efficiently when disrupted in the presence of an electric field, highlighting the relevance of electrofreezing in natural processes such as cloud formation and precipitation. This study aims to systematically investigate the impact of the Al electrode surface roughness induced by Laser Shock Processing (LSP) on the electrofreezing of deionized water. By fabricating Al electrodes with varying degrees of roughness and applying a consistent electric field, we will examine how surface texture influences the nucleation rate, the degree of supercooling, and the growth patterns of ice crystals. This research seeks to bridge the gap in existing knowledge by providing a comprehensive understanding of how surface characteristics affect the electrofreezing process. The findings could have significant implications for the design and application of electrofreezing technologies in various industrial and scientific fields, including enhanced cryopreservation techniques, improved food processing methods, and more accurate climate models. This study aimsto contribute to the fundamental knowledge of electrofreezing and to provide practical guidelines for improving/optimizing the electrode design to achieve better control over ice formation processes. By exploring the effects of the electrode surface roughness induced by the LSP method, we hope to open new avenues for research and application in this area of study. An understanding of the mechanisms behind electrofreezing and the involved factors that influence the process is essential for advanced applications.
# Optimal Meshing Degree Performance Analysis in a mmWave FWA 5G Network Deployment
## 5 Experimental Simulation and Results
### Comparative Performance Analysis of Topologies in Terms of Throughput  
Next, Figure 11 illustrates the results of the throughput analysis across the topologies shown in Table 1.  
In this case, the median throughput (the positive gain) is the highest in Topology 2, followed by Topologies 3 and, finally, 1. The median throughput is approximately 19% higher in Topology 2 than in it is Topology 3 and 12% higher in Topology 3 than it is in Topology 1. However, the CVs of Topologies 1, 2, and 3 are 64%, 107%, and 73%, respectively. In other words, in terms of throughput, switching from Topology 2 to Topology 3 decreases the risk by about 43% and switching from Topology 1 to Top  
Figure 11: Throughput performance results.  
Figure 10: PDF performance results.  
As a result, the throughput rate is the highest for Topology 2, as shown in Figure 11, but it also has a much taller box plot, which indicates its CV underestimates the real level of volatility. However, the distance between the median (red) and the upper end of the upper whisker is much longer than the distance between the median and the lower end of the lower whisker. That means the higher throughput values are mainly contributing to the resulting volatility and, therefore, risk. Topology 3 is the second-best topology since it offers better performance with lower risk than Topology 1.
# A Review on Applications of Fuzzy Logic Control for Refrigeration Systems
## 3 Fuzzy Driver Applications on RACs
### Fuzzy Control in Heat Pumps
The table includes detailed information about the design and application for each controller. Additionally, the table presents the number of control loops as well as the input and output variables of the controller. Even though the number of variables, the shape of the membership functions, and the number of inference rules are independent variables of the operating conditions of the system and the knowledge of the person designing the system, the error and the derivative of the error are used as input variables despite the flexibility of fuzzy controllers that allow the use of the crisp values of the variables. Additionally, was found the common use of fuzzy sets with 3 and 5 triangular membership functions and 25 inference rules. It was also found that the most commonly used output variables are the speed or frequency of the compressor and the speed of the fans. Although a fuzzy control has a flexible design, it was found that in most cases it is implemented together with a PID controller or artificial neural networks. Inthese cases, fuzzy logic allows for better adjustment of controller parameters and reduces the use of complex mathematical models, jointly improving system efficiency.
# A Robust Mutual Authentication with a Key Agreement Scheme for Session Initiation Protocol
## 2 Review of [PERSON] et al.'s Scheme
### Stolen Memory Device Attack  
A stolen memory device attack means that an attacker \(A\) steals a certain user's memory device and extracts the data stored in it, and then \(A\) can impersonate the user to log in to the system.  
From the above-stated analysis, we can conclude that when a memory device is lost or stolen, and the secret data stored in it are extracted, it is easy for \(A\) to obtain the client's registered value \(V_{i}\). In the following, it will be shown that [PERSON] et al.'s scheme cannot withstand a stolen memory device attack since \(A\) can impersonate a certain client with \(V_{i}\). **Case-1** of [PERSON] et al.'s login and authentication phase is taken as an example.  
1. \(A\) extracts the secret data \(\{A_{i},C_{i},N_{i}\}\) stored in a memory device.
2. \(A\) obtains \(V_{i}\) with the assistance of memory device using Steps 1 to 4 presented in Section 3.1.
3. \(A\) generates a random integer \(r_{a}\) and timestamp \(T_{1}\), and then computes \(R_{a}=r_{a}\cdot P\), \(F_{a}=h(V_{i}||A_{i}||C_{i}||T_{1})\), \(k_{1}=r_{a}K_{s}\), \(H_{a}=E_{k_{1}}(realm||F_{a}||A_{i}||C_{i}||T_{1})\). Lastly, the REQUEST message \(\{H_{a},R_{a}\}\) is sent to the server.
4. When the server receives the REQUEST message from \(A\), it obtains data \(\{realm||F_{a}||A_{i}||C_{i}||T_{1}\}\) by decrypting \(H_{a}\) with \(k_{2}=k_{s}R_{a}\). Then, the server verifies \(T_{1}\), which is valid, computes \(B_{a}^{\prime}=h(A_{i}||k_{s})\), and obtains \(V_{i}^{\prime}\) by decrypting \(C_{i}\). Next, the server computes \(F_{a}^{\prime}=h(V_{i}^{\prime}||A_{i}||C_{i}||T_{1})\) and checks \(F_{a}^{\prime}\). The same as \(T_{1}\), the value passes the verification.
5. The server generates \(r_{s}\) and timestamp \(T_{2}\), and then computes \(k_{2}=k_{s}R_{a}\), \(R_{s}=r_{s}\cdot P\), \(J_{a}=h(V_{i}^{\prime}\oplus F_{a}^{\prime}\oplus r_{s}R_{a}\oplus T_{2})\), \(SK=h(V_{i}^{\prime}\oplus r_{s}R_{a}\oplus T_{2})\), and \(L_{a}=E_{k_{2}}(R_{s}||J_{a}||T_{2}||realm)\). Finally, it sends the ACCEPT message \(\{L_{a}\}\) to \(A\).
6. On receiving the ACCEPT message, \(A\) obtains \(\{R_{s}||J_{a}||T_{2}||realm\}\) by decrypting \(L_{a}\) with \(k_{1}\). Then, the shared session key \(SK=h(V_{i}\oplus r_{a}R_{s}\oplus T_{2})\) is computed. Until now, \(A\) was seen as a legal client and established a session key \(SK\) with server. This means that \(A\) can pretend to be a legal user to log in and obtain the user's personal information.
## 1 Introduction
To our knowledge, a THG-based technique such as THG-FROG using a gaseous medium has not been reported to date. In this study, we used argon or air as a nonlinear optical medium for THG to measure the pulse width of a fundamental beam of a Ti:sapphire laser emitting at 800 nm as a proof-of-principle experiment. Two types of AC systems, _i.e._, fringe-resolved AC (FRAC) and intensity-AC (IAC), were developed and were utilized for measuring the pulse width. In addition, a FROG system was developed that permits the pulse width and the chirp of the pulse to be evaluated more accurately. The results were compared with values obtained using FRAC and IAC.
# Energy-Efficient Industrial Internet of Things in Green 6G Networks
## 1 Introduction
### The Research Gap of the Study
Power allocation and transmission algorithms can enhance 6G-enabled cyber-physical system-IoT industrial environments [26] using sensors and actuators for energy efficiency resource optimization and channel allocation. IoT devices across 6G networks, radio-frequency-based energy harvesting techniques, and green Industry 4.0 wireless systems and real-time data digitization, gathering, and analysis articulate low-carbon net zero [27] by battery-less wireless sensing and operation and autonomous low-power, energy-efficient circuits, mitigating maintenance costs. Related previous research focused mainly on sustainable vehicular communications and UAV-based green Internet of Things [28; 29; 30], energy-efficient self-governing wireless networks [31; 32; 33; 34; 35; 36; 37; 38; 13; 14; 31; 32; 31; 33; 38], 6G Internet of Things in relation to big data and artificial intelligence technology [39; 40; 41; 42; 43; 44; 45], sustainable 6G IIoT network automation [46; 47; 48; 49; 50; 51; 52], IoT green smart cities [53; 54; 55; 56; 57; 58; 59; 60; 61], digital twin intelligent planning and IoT smart industry energy management [62; 63; 64; 65; 66; 67; 12].
# Integrating AIoT Technologies in Aquaculture: A Systematic Review
## 3 Components of AIoT in Aquaculture
### IoT Sensors  
IoT sensors are critical in modernising aquaculture by enabling real-time monitoring of critical environmental and biological factors, ensuring optimal conditions for aquatic life [29]. For instance, continuous tracking of dissolved oxygen levels helps mitigate risks associated with sudden drops, allowing farmers to activate aeration systems promptly and prevent hypoxic conditions that could harm stock [50]. Similarly, temperature sensors detect abrupt fluctuations, helping farmers maintain stable water conditions to minimise fish stress and reduce the risk of thermal shock [51]. Beyond environmental monitoring, IoT sensors also serve as early-warning systems, identifying potential threats such as disease outbreaks, inefficient feeding patterns, and water contamination, thereby enabling proactive interventions to enhance aquaculture sustainability and productivity [52].
## 7 Discussion and Conclusions
### Crack Propagation by SBFEM  
The crack propagation process by SBFEM, enhanced via hybrid balanced quadtree polygon meshes, requires the polygon representation of domain features as input, including the crack. The points comprising the polygons constitute the subdivision criterion for the quadtree decomposition. If more than a user-specified number of points fall within a quadrant, this is subdivided. Together with the balancing operation, these steps entail minimal computational effort. The explicit neighbours of each cell do not need to be calculated, but simply the size of its neighbour. This is efficiently achieved by querying the center of each element, offsetting them by the element size in all four cardinal directions, passing them through the tree structure, and finally returning the size of the final cell. Assuming a balanced mesh, all possible element realizations are precomputable. When  
Figure 41: Steps comprising an XFEM/GFEM crack propagation analysis.  
the domain features, such as the boundary and strong & weak discontinuities do not align with the Cartesian axes, polygon clipping algorithms are required. Although efficient algorithms exist for polygon clipping, the resulting polygonal elements are no longer precomputable and must therefore be calculated individually. In order to construct the stiffness matrix of an SBFEM element, a Hamiltonian eigen-problem must be solved. This entails a real Schur decomposition, sorting of the eigenvalue blocks and subsequent block-diagonalization, as well as the inversion of the matrix [\(E^{0}\)] and the evaluation of a matrix exponential, if quantities of interest inside the SBFEM element need be determined. For smaller elements, commonly employed on quadtree meshes, this additional step when compared to the standard FEM procedure, does not generate a significant computational overhead. Specifically, Ooi et al. [51] report a reduction of computational effort close to 50% on typical analysis domains, when employing precomputable alongside clipped elements. When larger domains are investigated by using a single SBFEM element for the whole domain and hp-refinement is employed, determining the stiffness matrix dominates the computational effort of the analysis. Unfortunately, the stiffness matrix is fully populated, yet symmetric. Hence, this type of analysis is best suited for problems with small boundary to domain ratios. Determining the gSIFs entails post-processing calculations localized to the element containing the crack tip. The singular modes are identified according to Equation (44) and the gSIFs are calculated by evaluating the components of the stress tensor \(\sigma^{(s)}\) in crack extension direction (Figure 2b). The crack propagation angle is selected based on a suitable criterion (Equation (13)), while the crack propagation increment \(\Delta a\) is user specified. After definition of the updated crack tip location, the crack path polyline is updated accordingly and provided as input to the meshing phase of the next iteration. The steps to a standard SBFEM analysis are summarized in Figure 42.
# SPR-Optical Fiber-Molecularly Imprinted Polymer Sensor for the Detection of Furfural in Wine +
## 4 Discussion  
In the SPR-POF sensing apparatus here considered, the operative RI ranges were from about 1.33 to 1.41 (see Figure 2). In aqueous matrices with low RI, an RI in this range is obtained when a thin MIP layer is deposited on the gold surface so that the plasmonic wave partially penetrates in the overlying aqueous medium, as shown in Figure 1b. The preparation of the MIP layer reported in the experimental part allowed this goal to be achieved, i.e., having an RI of the layer (MIP plus water solution) in the suitable range. The resonance wavelength shift of the sensor with MIP in water, with respect to that of the bare platform in water, was around 50-150 nm. Similar shifts were previously observed in sensors with MIP's receptor. For example, a value as high as 150 nm in sensors for TNT [13] and nicotine [19], and about 80 nm in a 2-FAL sensor [27] were obtained. Lower \(\Delta\lambda\) was observed in the case of a monolayer of molecular receptor as in the case of an aptamer [17] or a metal ligand [16; 19], confirming that the shift is higher when a higher amount of receptor is present at the resonant surface. As shown in the present investigation (Figure 2), the resonance wavelength should not exceed about 800 nm, so that an MIP layer that is not too thick must be used.  
On the other hand, this makes the sensor sensitive to the RI of the overlying liquid, which thus must be carefully controlled.  
For this reason, when measuring a real life sample, for example wine, using the sensing method proposed, any RI variation due to the matrix composition must be avoided. This aspect is relevant when thin MIP layers are considered, i.e., thinner than the plasmonic wave penetration in the dielectric. In that case, the \(\Delta\lambda\) must always be measured in solution with the same RI. The matrix effects are avoided by equilibrating the sample with the sensor and then changing the sample with a solvent with a proper RI (for example, an aqueous buffer), for recording the spectrum and measuring \(\Delta\lambda\). In the present work, to demonstrate the method's effectiveness, pure water was selected as the liquid for registering the spectrum for the analysis of 2-FAL in a white wine sample. An alternative  
Figure 7: SPR spectra obtained by the SPR-MIP sensor in wine sample.  
approach could be applied, using a much thicker MIP layer; however, in this case, the RI of the dielectric over gold could not be suitable for the measurements since the resonance wavelength could be outside the operative range.
# Approaching Breakthrough: Resource-Efficient Micropolitan Removal with MBR-GAC Configuration
## 3 Results
### Full-Scale Implications  
Removal rates for pharmaceuticals and PFASs in the MBR-GAC pilot can be compared to removal rates in the current full-scale WWTP, which consists of a conventional activated sludge process (Figure 4). Because the main focus initially was on the treatment performance of the MBR-GAC pilot only, analysis of pharmaceuticals and PFASs have not been performed in the full-scale WWTP in the beginning of the study and not at all samplings as indicated in Figure 4. As observed in the MBR process, removal rates in the full-scale WWTP vary across different sampling campaigns. On average, diclofenac was removed by 13%, the sixteen most persistent pharmaceuticals by 3%, PFOS by 13%, and \(\Sigma\)PFAS11 by 11%. It should be noted that when high negative removal efficiencies were observed in the MBR pilot (Figures 2 and 3), similar observations were made in the full-scale process (Figure 4), indicating the composition of the incoming wastewater as the main influencing factor, rather than the treatment process itself.  
An initial evaluation of the two different backwash strategies indicates that the need-based strategy reduces backwash events by more than 50% compared to standard design. This results in less downtime for the GAC filters and a substantial reduction in the backwash water that needs to be re-treated in the main treatment process.  
The increased utilization of the GAC capacity further implies substantial cost reductions in future full-scale implementations. The pre-design of the quaternary treatment at the Himmerfjardsverket WWTP estimated 430 MSEK as investment and approximately 42 MSEK/year as operational cost for the GAC filter installation with a standard design of 20,000 EBVs before GAC replacement [35]. While investment costs are not affected by  
Figure 3: Removal efficiency in the MBR-GAC pilot for all analyzed PFASs (\(\Sigma\)PFAS11) and only PFOS for sample occasions (calendar week and treated EBVs).  
reduced GAC consumption, the increased number of EBVs that can be treated according to the pilot trials implies a reduction of at least 50% in operational costs, with less need for human resources due to fewer replacements. This, as already at the current state more than 50,000 EBVs have been treated and the capacity of the GAC filters is yet to reached.  
Additionally, the environmental impact caused by the production of virgin GAC and the reactivation of spent activated carbon can be reduced with every additional EBVs treated compared to conventional design.
## 4 Flight Planning and Data Acquisition  
Flight plans are made with X-TRACK Flight Management Software Suite (Track'Air Aerial Survey Systems, Oldenzaal, The Netherlands), using a nominal flight altitude of 335 m AGL, 60\({}^{\circ}\) FOV and 30% swath overlap. This configuration results in a LiDAR, spectrometer and thermal swath of 387, 310 and 173 m. The pixel size of the pushbroom imaging spectrometer is \(\sim\)1 m and is limited by the  
Figure 8: Radiometric response of the for the Xenics Gobi-384 long wave infrared (LWIR) thermal imaging camera as a function of instrument body temperature.  
Figure 7: **(a)** Hg and Ar lamp emission lines as viewed through G-LiHT’s imaging spectrometer; **(b)** relationship between band number and band center wavelength using Gaussian iterative curve fitting.  
inircraft speed and frame acquisition rate. The instantaneous per pixel resolution of the thermal camera is approximately 3 times coarser than the imaging spectrometer, but oversampling with the 2D detector allows us to create a product of equal resolution (Section 5.2.4).  
Flight lines are uploaded onto a 696 GPS (Garmin International, Inc., Olathe, KS, USA) for pilot navigation and onto the instrument operator's computer, which is using Reigl's RiAcquire acquisition software. Each instrument is separately controlled and triggered to collect data using vendor-supplied software. Ejectable, solid state hard drives provide fast input/output and quick retrieval upon conclusion of the flight.