esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
In this research, the impact of the pulsed electric fields (PEF) pretreatment on the infrared-convective drying (IR-CD) of apples and selected quality indicators (antioxidant capacity, color, and total phenolic content) of dried apples was evaluated. PEF pretreatment was carried out at the following parameters: electric field strength of 1 kV/cm, specific energy inputs of 1, 3.5, and 6 kJ/kg. Moreover, variable IR-CD process parameters were also assessed (peak wavelength of 1.2 um, distance between the infrared lamps and the apple slices of 10, 20, and 30 cm). PEF pretreatment, by disintegrating apple cells, reduced the drying time of that fruit by 11-20%. The IR-CD of apples was the most effective at the shortest distance (10 cm) between the infrared source and the apple slices; it was associated with the intense heating of its surface. PEF-pretreated samples exhibited lower retention of antioxidants and were darker and redder than untreated ones. PEF could increase the activity of enzymes responsible for oxidizing phenolic compounds to brown pigments. The use of a medium distance (20 cm) during IR-CD promoted the highest retention of antioxidant compounds (relatively prompt drying with moderate heating of the sample surface).  
ABTS assay; antioxidant capacity; CIELab; DPPH assay; hybrid drying; IR-CD; NIR; PEF; total phenolic content Article
## 3 Methodology
### Stage 3: ANOVA Test
\begin{table}
\begin{tabular}{l l r r r r r r r} \hline \hline
**Source** & **DF** & \multicolumn{6}{c}{**R2 Tr**} \\ \cline{3-10}  & & **Adj SS** & **Adj MS** & **F-Value** & \(p\)**-Value** & **Adj SS** & **Adj MS** & **F-Value** & \(p\)**-Value** \\ \hline Regression & 13 & 1.0433 & 0.0803 & 31.9400 & 0.0310 & 1.0445 & 0.0803 & 2780.6000 & 0.0000 \\ NoF & 1 & 0.0008 & 0.0008 & 0.3300 & 0.6250 & 0.0033 & 0.0033 & 113.4200 & 0.0090 \\ FSM & 1 & 0.0001 & 0.0001 & 0.0500 & 0.8480 & 0.0000 & 0.0000 & 0.4700 & 0.5640 \\ MLM & 3 & 0.0051 & 0.0017 & 0.6700 & 0.6450 & 0.0057 & 0.0019 & 65.8000 & 0.0150 \\ NoF*NoF & 1 & 0.0020 & 0.0020 & 0.8100 & 0.4640 & 0.0021 & 0.0021 & 72.5800 & 0.0130 \\ NoF*FSM & 1 & 0.0037 & 0.0037 & 1.4900 & 0.3470 & 0.0013 & 0.0013 & 44.0600 & 0.0220 \\ NoF*MLM & 3 & 0.0053 & 0.0018 & 0.7000 & 0.6320 & 0.0025 & 0.0008 & 28.7400 & 0.0340 \\ FSM*MLM & 3 & 0.0414 & 0.0138 & 5.4900 & 0.1580 & 0.0394 & 0.0131 & 454.0900 & 0.0020 \\ Error & 2 & 0.0050 & 0.0025 & & & 0.0001 & 0.0000 & & \\ Total & 15 & 1.0484 & & & & 1.0446 & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: ANOVA for Crack Length Prediction.
## 5 Conclusions  
We showed a new configuration for the polarized interferometer with in-plane radial sensitivity using divergent illumination. We performed measurements of deformations due to the dilatation of an aluminium plate that was heated by the rear by contact with a small cylindrical element connected to electric resistance. The implemented system allowed us to measure deformations mainly in the radial direction. The results were compared to a simulation by the finite element analysis technique, which had comparable results. According to the mathematical model, the contribution of the out-of-plane sensitivity vector is less than 1% near the centre of the measurement, and this increases in function of the radius of less than 3%. We can conclude that the contribution of the out-of-plane sensitivity vector increases proportionally to the radius; this represents a disadvantage in determining the in-plane deformation at these points. On the other hand, it is not possible to obtain reliable measurements at the centre of the conic mirror due to the convergence of the illumination beam. As a perspective, we propose to carry out further research to determine the error of the measurement in this condition.  
Figure 9: The comparison between ESPI radial-in-plane sensitivity measurement and the calculation of the deformation by finite element analysis.  
**Author Contributions:** Conceptualization, J.R.P.-M. and D.G.-H.; Methodology, J.R.P.-M. and D.G.-H.; Software, R.M.-P and M.A.E.; Validation, J.R.P.-M., M.A.E. and D.G.-H.; Formal Analysis J.R.P.-M., D.G.-H, and M.A.E.; Investigation, J.R.P.-M.; Resources, J.R.P.-M. and D.G.-H.; Data Curation J.R.P.-M. and R.M.-P.; Writing--Original Draft Preparation, J.R.P.-M. and D.G.-H.; Writing--Review & Editing, J.R.P.-M. and D.G.-H.; Visualization, J.R.P.-M. and D.G.-H.; Supervision, J.R.P.-M.; Project Administration, J.R.P.-M.; Funding Acquisition, J.R.P.-M. and D.G.-H. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the Consejo de Ciencia y Tecnologia del Estado de Guanajuato, grant number 14-IJ-DPP-Q182-31 and The APC was funded by the Universidad De La Salle Bajio.  
**Acknowledgments:** The author wants to express his acknowledgement to the Secretary for Innovation, Science and Superior Education, from the state of Guanajuato (Secretaria de Innovacion, Ciencia y Educacion Superior del Estado de Guanajuato, SICES) and to the Universidad De La Salle Bajio for the given facilities.  
**Conflicts of Interest:** The authors declare no conflict of interest and the funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
# A New Foot Trajectory Planning Method for Legged Robots and Its Application in Hexopod Robots
## 4 The Three-Element Trajectory Determination Method
### Verification of the Three-Element Trajectory Determination Method  
The trajectory of one foot based on the three-element trajectory determination method during one movement period in Cartesian space is simulated in Figure 8, in which counter clockwise is selected as the positive direction and \(T_{b}=0.2\), \(T_{f}=1\).  
From Figure 7(a), it can be observed that, during the time \(t\in(0,T_{f})\), the foot's coordinates in \(X\) and \(Z\) axes remain unchanged, and the robot only moves along the \(Y\) axis, which confirms that the robot is moving in a straight line. Figure 7(b) is the foot's trajectory in space, the straight line is the trajectory in support phase, and the arc line is the trajectory in transfer phase.  
Here, we also provide the angle curve of the three joints as in Figure 9. We can observe that, while moving, all of the three angle curves are continuous and smooth, which further demonstrates the stability and practicability of our trajectory planning method for legged robots.  
Figure 8: Trajectory in Cartesian space.  
Figure 7: Trajectory in joint-space.
# Tunable Fano Resonances in an Ultra-Small Gap
## 3 Results and Discussion  
### Observation and Proof of Fano Resonance  
When the nano-gap thickness is greater than 10 nm in the NPoM structure, the scattering spectrum shows one resonance peak. While the thickness decreases and is less than 10 nm, this resonance peak will be a gradual red-shift and splits into two resonance peaks [41]. As shown in Figure 2, when \(d=72\) nm, \(r=9\) nm, and the nano-gap thickness is 4 nm, two scattering resonance peaks are clearly observed with wavelengths of 588 nm (peak II) and 640 nm (peak I). From the profile view of the spectrum, the scattering spectrum shows an asymmetric shape. To investigate the origin of this asymmetric shape, the electric field magnitude profiles of peak II and peak I on the x-z plane are given in Figure 2b,c, respectively. Figure 2d,e are charge distribution diagrams corresponding to Figure 2b,c, respectively. The silver nanocube-Al\({}_{2}\)O\({}_{3}\) film-silver film structure forms a plasmonic nanocavity. In Figure 2b,c, there is a \"hot spot\" on the left and right sides of the nanocavity. It indicates that the electric field profile follows the pattern of the charge distribution on the bottom of the nanocube with two areas of intense field at either side of the nanocube. Compared to Figure 2b, the top surface of the cube in Figure 2c has stronger field enhancement, although both are smaller compared to the bottom surface of the cube. From the charge distributions in Figure 2d,e, peak II is a quadrupole mode and peak I is a dipole mode. This charge distribution pattern is related to the substrate. The substrate effect generally has two mechanisms: the pure screening effect and the substrate mediated interaction of the initial cube plasmons. The former is the image charge generated by the plasmon mode acting on itself, and the latter is the interaction with other plasmon modes [33]. The dipole mode and the quadrupole mode interfere with each other under the action of the substrate, thereby generating the Fano resonance in the scattering spectrum of the NPoM nanostructure.
## 3 Structure and Function of the _B. thuringiensis_ Binary Toxins  
### Vpb1/Vpa2  
Vpb1/Vpa2 align neatly within the binary toxin paradigm. That is, only when Vpb1 and Vpa2 are both present will toxicity towards the digestive tracts of certain species of _Coleoptera_ and _Henipteran_ manifest [17; 27]. While the mechanism of action for Vpb1/Vpa2 is not fully established, the process by which cellular intoxication occurs has been partially elucidated by exploring Vpb1 and Vpa2 association and function from various strains of _Bt_ and _B. cereus_. Generally, a toxin is secreted by _Bt_ in the midgut, where Vpb1/Vpa2 are then proteolytically cleaved by trypsin/trypsin-like proteases in the basic environment (pH 9-11) of insect midgut juices [17; 28]. This digestion processes prootoxins Vpb1 (100 kDa) and Vpa2 (52 kDa) into mature, active proteins of 80 kDa and 45 kDa size, respectively [17; 29]. This proteolysis is critical for Vpb1 oligomerization and Vpa2 translocation [30]. Structural analyses of mature Vpa2 identified two domains, the N-terminal Vpb1-binding domain, and an NAD-binding, ADP-ribosylating C-terminal domain [31]. Unsurprisingly, Vpa2 shares sequence and structural homology with the catalytic domains of CDTa and Ia [30]. In agreement with the binary toxin B subunits expressed by clostridial bacteria, proteolytic cleavage of its N-terminal domain activates Vpb1, promoting heptamerization [28]. This is observed for Vpb1 Ac (expressed in _Bt_ strain HD201), which forms a circular heptameric assembly after proteolytic processing of its N-terminus [17; 28]. The bound Vpb1 Ac-Vpa2 Ac complex is then endocytosed by brush border membrane vesicles (BBMVs) within the midgut of cotton aphids [17; 28; 32].  
This Vpb1/Vpa2 system is found across many strains of _Bt_, culminating in varying insectile specificities. For example, Vpb1 Ad1 and Vpa2 Ag1 produced by _Bt_ strain HBF-18 (CGMCC 2070) exhibits toxicity against the larvae of _Holotrichia parallela_, a notcuid moth that devastates cash crops across East Asia [27; 33]. As expected, in the absence of Vpa2 Ag1, histopathology revealed no obvious degradation of _H. parallela_ midgut tissue [27]. Alternatively, in the presence of both Vpb1 Ad and Vpa2 Ag, considerable destruction of the midgut occurred as a product of actin dissociation, culminating in vacuolization of the cytoplasm and microvilli abcission [27]. These findings further reinforce the role Vpb1 serves as a receptor of Vpa2, highlighting this binary toxin relationship and showcasing their potential as tools for protecting crops from insects with increasing resistance to the currently employed _Bt_-derived toxins [27].
# Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review
## 2 Wireless Communication Technologies for Agriculture
### Performance Comparison of Wireless Communication Protocols
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline \multicolumn{1}{c}{**Parameters**} & \multicolumn{1}{c}{**Zigabe**} & \multicolumn{1}{c}{**Cluster BF**} & \multicolumn{1}{c}{**BLE**} & \multicolumn{1}{c}{**W91**} & \multicolumn{1}{c}{**GFR**} & \multicolumn{1}{c}{**Lobs**} & \multicolumn{1}{c}{**Selgue**} \\ \hline Standard & I288 021.54 & I288 021.51 & I288 021.51 & I288 021.51 & I288 021.14.0g & N/A & I288 021.54.6g & I28 021.54.6g \\ \hline Frequency band & 800/913 MHz and 24.4 GHz & 2.4 GHz & 2.4 GHz & 2.4 GHz & 900-1800 MHz & 800/9135 MHz & 800/9135 MHz \\ \hline Modulation type & IPW/COPSK & GPR, DPSK, and DPSK & GMSK & BPSK, OOPS & GMSK, MPSK, MPSK & GPR & GPR & GPR/SNSNULL, GMSK(LDL) \\ \hline Speeding & DPSK & IPWBS & IPWBS & MC-OSS, CTS & TDMA, DPSS & CSS & N/A \\ \hline Number of BP channels & 1,10, and 18 & 70 & 40 & 11 & 124 & 10 in L/A, F/N = US & 300 \\ \hline Channel bandwidth & 2.3 MHz & 1.3 MHz & 1.3 MHz & 22 MHz & 230 MHz & -400 MHz & -400 MHz \\ \hline Power consumption in T\({}_{\rm e}\)s & Medium & Ultra-layer & 140 & Medium & Low & Low \\ \hline mode [\(\times\)0.4,5,6,7,8,9,10] & 25.9 mW & 10 mW & 85.5 mW & 800 mW & 100 mW & 122 mW \\ \hline Data rate & 20.40, and 250 Mbps & 1-3 Mbps & 1.3 MHz & 11.54 and 150 & Up to 100 Mbps & 50 Mbps & 1001 ps \\ \hline Latency [20-43] & (20-30 ms) & 100 ms & 6 ms & 50 ms & \(<\)1 s & N/A & N/A \\ \hline Communication range [4/6] & 100 ms & 10-50 m & 100 ms & 100 m & 1-10 m & 5.10 & 100\% \\ \hline Network size & 60000 & 8 & Limited by the application & 32 & 1000 & 10000 (nodes per BS) & 10000 (nodes per BS) \\ \hline Cost [5] & Low & Low & Low & Low & High & Medium & Low Cost & Low Cost \\ \hline Security capability & 1288 MHz AS & 64 or 128 bits AS & 64 or 128 bits AS & 128 bits AS & GMA, M5-GGS, M5-host & AS 128 & Encryption not supported \\ \hline Network topologies & PZZ, tree, star, mesh & Switzerland & Starphone & Star-to-light & Cellular system & Star-to-light & Star \\ \hline \multirow{2}{*}{Application} & WYNA, WSNs & \multirow{2}{*}{WPANs} & \multirow{2}{*}{WPANs} & \multirow{2}{*}{WLAN} & All, demand & Agriculture, Smart grid, & Agriculture and environment control, & Agriculture, Smart grid, \\  & and Agriculture & & & & response, HAN & and lighting control, & temperature, and lighting control, & temperature, and lighting control, \\ \hline \multirow{2}{*}{Limitations} & I28-node-light (LOS) between the sensor node and the coordinate node normal & Short communication range & Short communication range & High power consumption and huge access & Power consumption problem & Network size (probability), data rate, & Low data rates \\  & & & & time (1374) & & and message capacity & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Different wireless communication technologies.
## 3 Results and Discussion
### Uniaxial Compressive Test  
#### 3.3.1 Damage Features  
Under uniaxial compressive strength (UCS), various damage patterns were observed, mainly related to loading methods, loading rate, and the water content of specimens, etc. Basically, two patterns were encountered, namely, compressive shear failure and tensile fractures, as shown in Figure 1.
# Performance Optimization of MANET Networks through Routing Protocol Analysis
###### Abstract  
A Mobile Ad Hoc Network (MANET) protocol requires proper settings to perform data transmission optimally. To overcome this problem, it is necessary to select the correct routing protocol and use the routing protocol's default parameter values. This study examined the effect of route request parameters, such as RREQ_RETRIES and MAX_RREQ_TMOUT, on the Ad Hoc On-demand Distance Vector (AODV) protocol, which was then compared with the default AODV performance Optimized Link State Routing (OLSR) protocols. The performance metrics used for measuring performance were Packet Delivery Ratio (PDR), throughput, delay, packet loss, energy consumption, and routing overhead. The results show that the OLSR protocol has a smaller delay than the AODV protocol, while in other measurements, the AODV protocol is better than OLSR. By reducing the combination value of RREQ_RETRIES, MAX_RREQ_TIMEOUT in AODV routing to (2, 10 s) and (3, 5 s), the protocol's performance can be improved. The two combinations result in an average increase in throughput performance of 3.09%, a decrease in delay of 17.7%, a decrease in packet loss of 27.15%, and an increase in PDR of 4.8%. For variations in the speed of movement of nodes, 20 m/s has the best performance, while 5 m/s has the worst performance.  
MANET; routing; AODV; OLSR; RREQ_RETRIES; MAX_RREQ_TIMEOUT
## 4 Discussion
Coordinated deformation in space between the structure and the soil occurred, and the sand behind the wall could have experienced significant plastic flow deformation, resulting in settling [27]. More importantly, in this study of the relationship between normalized maximum ground settlement and the maximum lateral displacement of retaining structures in excavations, it was also found that the mutual relationship between the excavations' deformation largely conformed to the summaries of [PERSON] [5] and [PERSON] [6]. However, after excavating the first layer (\(Z\) = 0.37 m), the ground settlement rate was slightly less than half of the lateral displacement. This was likely due to the shallow excavation depth and the limited plastic flow range of sand, resulting in minimal settlement. It is also possible that the contact friction between the structure and the earth resulted in reduced settling. Compared with a previous investigation of excavation deformation also using 3D printing [13; 14], the experimental conditions were different. Firstly, U-shape sheet piles were used in this article, while pipe piles were used in the above investigation, and the flexural rigidity of the retaining structure was 13.4 times that of this test. Secondly, the stiffness of the strut was 4.5 times that of the above investigation [14]. The strut location was also different, and the first strut was set from the top in the above investigation. The research results indicated that during the excavation process, the retaining structures in the two investigations had similar deformation patterns, and the ground surface settlement patterns were roughly the same. However, the lateral displacement of the retaining structure in this article was greater, and there were significant differences in the final deformation mode. This was because the retaining structure in this investigation was generally more flexible, with a large amount of deformation, and because of the influence of the location of the strut. The experimental investigation yielded numerous discoveries, but it also had limitations. On the one hand, the experimental results were limited to sand conditions and cannot be used to generalize the deformation characteristics of all retaining structures. On the other hand, no in-depth investigation of the interaction between the structure and the soil was conducted to investigate the specific influence of the interaction on the deformation of the excavations. However, these limitations could be improved. For example, by considering conducting experiments in various soil environments or using numerical model methods to study the excavations under complex soil conditions. Additionally, the interaction between structure and soil should be studied together with lateral earth pressure. In summary, the deformation characteristics of strutted flexible retaining structures are complex and related to the struts, soil, and structure-soil interactions. Therefore, future investigations should concentrate on strut variations, multiple soil choices, and the relationship between earth pressure and displacement.
## 2 Related Work
The authors in [62] focused on most of the frequency bands between 2 GHz and 26 GHz, apart from studying their relationship between the frequency dependent path loss models in an urban macro-cell scenario. Their results depicted similar dependence in the LOS scenarios, while a relationship of directly proportional was observed in NLOS environment. Another approach in [63] investigated shadowing models that established correlation distances, varied offsets, shadowing, fading variance, and PL slope for the urban street canyon environment of New York City. The proposed model was largely dependent upon huge calibrated raytracing (RT) simulation and the dataset was set with over 60,000 PL data points with a total of 11 varied BS locations. The authors established a path loss model for spatially-consistent stochastic street-by-street (SBS) for a 28 GHz microcell scenario. The results depicted in the paper proved that the proposed SBS modelling principle scenario performed better after spatial consistency was taken into account. Table 1 illustrates the main findings and the variances of the related work.
# Degradation Assessment of In-Service Transformer Oil Based on Electrical and Chemical Properties
## 4 Discussion
### Relationship Between Different Characteristics
#### 4.1.1 Dielectric Dissipation Factor and Breakdown Voltage Relationship  
The electrical characteristics, namely breakdown voltage and DDF, both have tendencies to vary according to the presence of foreign objects and charged particles in the insulating oil; hence, the two electrical characteristics are plotted in Figure 5 to understand the relationship. The high values of breakdown voltage relate to the higher resistivity of the oil insulation, which is reflected as low values in the DDF. However, from the DDF and breakdown voltage results, a weak correlation was found between them. As transformers age, the concentration of by-products and foreign particles increases. These by-products include acids, sludge, and polar compounds, while foreign objects contain particles and moisture [37; 38]. The high levels of these substances significantly affect the breakdown voltage and DDF. In the current study, the transformers being examined exhibited breakdown voltage and DDF values below the acceptable range. Consequently, there was minimal impact of aging on the transformer oils, resulting in a weak correlation between breakdown voltage and DDF, which led to an ineffective control trend.
# The IoT/IoE Integrated Security & Safety System of Pompeii Archeological Park
## 3 Integrated Technology Systems in Cultural Heritage
The analysis not only characterized the natural environment but also identified historic structures that shaped the region. As a pilot project, the creation of this visual database aims to support the conservation of heritage sites across the area, contributing to a broader sustainable development strategy at the regional level [21]. Satellite-based monitoring of archeological sites has become common practice, demonstrating its importance for conservation and preservation, especially when used in an integrated way with other technologies [22]. In addition, a lot of other technologies have been applied to cultural heritage to date to also ensure proper risk management [23]. The novelty of this paper is the presentation of a case study of a unique UNESCO heritage site where the intensive use of innovative technology was carried out to create an integrated security/safety IoT/IoE-based system for security, safety, management, and visitor services at the Pompeii Archeological Park.