esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimization of Submodularity and BBO-Based Routing Protocol for Wireless Sensor Deployment
## 3 Routing Protocols for Wireless Sensor Networks
### Routing Protocol Based on BBO Algorithm
```
0: node coordinates, energy model
0: residual energy per round, number of dead nodes, number of surviving nodes
1: Initialize parameters: number of habitats \(n\), maximum emigration rate \(E\), maximum immigration rate \(I\), probability of species number for each habitat \(p_{s}\), maximum number of species \(p_{max}\), maximum number of rounds \(round_{max}\)
2:for\(l=1\):\(round_{max}\)do
3:for\(j=1\):\(n\)do
4: Select CH according to Equation (19)
5: Initialize population randomly
6: Calculate the fitness value of habitat \(j\) according to Equation (25)
7:end
8: Keep habitat with the smallest fitness values as elite habitat
9:while habitat does not reach minimum fitness value do
10:for k = 1:\(n\)do
11: Calculate the migration rate \(\lambda_{k}\) according to Equation (26)
12:if\(\lambda_{k}\) is greater than a uniformly distributed pseudo random number in [0,1] then
13:for t = 1:\(n\)do
14: Calculate the migration rate \(\mu_{t}\) according to Equation (27)
15:if\(\mu_{t}\) is greater than a uniformly distributed pseudo random number in [0,1] then
16: The roulette selection method is used to select the population to move out of the habitat \(t\) and move into the habitat \(k\)
17:end
18:end
19:end
20:end
21:for\(i=1\):\(n\)do
22:if Habitat \(i\) is not an elite habitat then
23: Calculate the mutation rate \(m_{i}\) according to Equation (28)
24:if\(m_{i}\) is greater than a uniformly distributed pseudo random number in [0,1] then
25: Select population mutations in habitat \(i\) randomly
26:end
27:end
28:end
29: Calculate fitness value
30: Replace the worst habitats with elite habitats
31:end
32: Calculate the shortest distance from ordinary nodes to CH
33: Calculate the energy consumed by ordinary nodes to CH to transmit and receive data packets
34: Calculate the energy consumed by CH to sink nodes to transmit and receive data packets
35: Calculate the remaining energy, dead nodes, and surviving nodes of the sensor network
36:if All network nodes are dead then
37:return
38:end
39:end
40:return
```  
**Algorithm 2** Biogeography-Based Optimization (BBO)-based routing protocol process.
## 1 Introduction
Unfortunately, the effect of temperature, moisture, and ionic contamination on high-voltage insulation failure is rarely reported. Nevertheless, among all the failure modes of EPC, insulation failure in a temperature and humidity environment is the most serious one, and further affects the reliability of the EPC. As a result, in order to improve high-voltage insulation, it is necessary to investigate the effect of thermal and moisture stress on the insulation of ionic contamination of the high-voltage PCB of an EPC. In this work, NaCl was used as the equivalent ionic contamination, and an EPC sampling equivalent circuit was used as the research object to study the insulation performance change of the EPC under the condition of temperature-humidity-bias. The sampling value of the divider resistance was used to characterize this change, which in actual products causes telemetry abnormality of TWTA. The influence of temperature, humidity, voltage, and surface ionic contamination on the insulation performance of the EPC was obtained. The temperature and humidity boundary conditions from the start point of failure to the occurrence of surface discharge were determined.
## 2 Results and Discussion
### Application of the HS-SPME/GC-MS Method to Strawberry Jams
This means that esters and alcohols in most jam samples were destroyed during strawberry jam processing, and these compositional changes in jam would be responsible for a poorer sensory impression. Additionally, furanones were not detected in all jams except Jam 3, which showed a higher furanone content represented by mesifurane (5.34%) than the fresh fruits (0.10%). In contrast, acid content increased in all jam samples, whereby Jam 3 showed the highest acid amount (32.03%), and Jam 2 demonstrated the lowest acids level (3.48%), compared to 0.12% in fresh fruits. The acids detected were hexanoic acid, acetic acid, octanoic acid, and 2-methylbutanoic acid, with hexanoic acid being the major one in Jam 4 and Jam 3, accounting for 17.59% and 19.96%, respectively. Hexanoic acid was reported as an off-flavor which contributes to an unpleasant aroma impression [33; 43]. Lactones, including \(\gamma\)-butylolactone, \(\gamma\)-caprolactone, \(\gamma\)-decalactone, and \(\gamma\)-dodecalactone were identified in the jam samples (Table 1). Total lactone amounts were increased in all jam samples except Jam 2, compared to fresh fruits. It was reported previously that lactones were correlated with peach note levels in the sensory study [25]. Lastly, strawberry aroma was modified by heat treatment during jam processing. In fact, the volatile compounds characteristic of fresh strawberries were mostly replaced in processed strawberry by certain heat-induced volatile compounds, such as furfural and 5-hydroxymethylfurfural, by the disappearance of other compounds (e.g., esters were missed except traces in Jam 2, as well as most alcohols), or by an increase (e.g., \(\gamma\)-decalactone, \(\gamma\)-dodecalactone, \(D\)-limonene, (\(E\))-nerolidol, \(\alpha\)-terpineol, hexanoic acid) or decrease (e.g., \(\gamma\)-butylolactone, Inal, 1-hexanol) in some existing compounds, which led to a poorer sensory impression compared to fresh fruits; these results are in a good accordance with other authors [16; 17; 28]. These compounds (e.g., furfural and 5-hydroxymethylfurfural) are a key source of flavor and color and are responsible for the enjoyment of most heat-processed foods, but some of them are also regarded as carcinogenic in such a way that their control is necessary [17]. Interestingly, natural strawberry aroma compounds are mostly replaced by Maillard reaction products, most of them with carcinogenic properties, in commercial jam. For these reasons, shorter heating periods using whatever the temperature applied represent an alternative to industrial jam processing to obtain a healthier and more pleasant product; in this case, homemade jam using low temperature is more favored as the natural strawberry aroma compounds will be more preserved and retained.
# Current Uncertainties and Future Challenges Regarding NAD+ Boosting Strategies
## 12 None, Continuous, or Intermittent NAD+ Supplementation?  
[PERSON] and colleagues [178] hypothesized that circadian rhythmicity was a mechanism that prevented disruption of the negative feedback loops of organismal homeostasis. Circadian rhythmicity inhibited the loss of the cell's response to various endogenous substances, while the constant stimulus, like the constant concentration of endogenous substances, could have the opposite effect. Thus, problems could arise when people consume NAD+ boosters continuously or those with extended release and eliminate the intracellular circadian fluctuations of NAD+ during the 24 h period. It should be emphasized that NAD+ is required for over 500 enzymatic reactions in the human body [180], and it is estimated that the expression of one in ten genes is under the circadian control [181; 182]. There are no scientific studies that prove or disprove to take NAD+ boosters at intervals. In the case of resveratrol (3,5,4'-trihydroxystilbene), a potent natural sirtuin activator, lifespan extension was observed in mice fed a high-fat diet only when the animals were treated every other day (intermittently) [62; 183; 184]. Such intermittted exposure seems necessary to prevent the resistance development. [PERSON] et al. [120] observed that repeated administration of NR and pterostilbene increased NAD+ levels by 40% during continuous supplementation after 4 weeks in 60- to 80-year-old adults and observed no side-effect in 8 weeks of trial.  
Nevertheless, the concern remains that constant activation of sirtuins by NAD+ boosters is not beneficial. For example, mice with consistently elevated SIRT1 in the brain show increased anxiety; variations in the SIRT1 gene are also associated with an increased risk of anxiety in humans [185; 186]. Since nicotinamide mononucleotide (NMN) is produced by the enzyme NAMPT, high concentrations of NMN may induce a \"feedback inhibition effect\" on NAMPT, inhibiting the formation of NAD+. Although this effect has not been proven so far, a similar NAM \"feedback inhibition effect\" has been observed in NAD-dependent processes such as PARP/Sirtuin/CD38 reactions [53; 164]; in vivo PARP-1 activity inhibition by NAM remains arguable. As it has been reported that treatments with NMN and NR have beneficial health effects in various model organisms and in humans [17; 22; 23; 33; 40; 105], the question arises whether the beneficial effects are even greater when NMN and NR are administered at intervals (e.g., every other day). Indeed, the continuous supply of NMN or NR could suppress the enzyme NAD(P)H dehydrogenase, quinone 1, which regulates the NAD/NADH ratio by oxidizing NADH to produce NAD+ [187]. In conclusion, the potential feedback suppression and adaptive response caused by elevated NAD+ levels and the role of elevated NAD+ concentrations on circadian rhythms should be carefully investigated in the future.
## 3 Results  
### Structure Identification and Bioassay of Antioxidant  
The structure of compound 1 was verified as a polyketide, and the name (\(\pm\))-differolide by consulting published literature [17; 18] (Figure 1a). Herein, the structure of the compound was verified by a combination of X-ray crystal diffraction (Figure 1b), NMR, and HR-LC-MS (Figure 1c). The molecular formula of (\(\pm\))-differolide was C\({}_{12}\)H\({}_{12}\)O\({}_{4}\), and the m/z of the compound was 221.0803 according to HR-LC-MS.  
Compound 1 was a pale yellow solid: \({}^{1}\)H NMR (400 MHz, DMSO-\(d_{6}\)) \(\delta\) 7.32 (d, \(J\) = 2.2 Hz, 2H), 6.82 (p, \(J\) = 3.1 Hz, 2H), 4.91-4.74 (m, 5H), 4.46 (t, \(J\) = 9.1 Hz, 2H), 3.89-3.75 (m, 2H), 3.55-3.39 (m, 3H), 3.15 (q, \(J\) = 4.6, 4.2 Hz, 2H), 2.70-2.55 (m, 1H), 2.46-2.10 (m, 6H), 1.93-1.73 (m, 4H), 1.35-1.25 (m, 1H), 1.24 (s, 2H), 0.84 (dd, \(J\) = 9.8, 6.6 Hz, 1H).  
\({}^{13}\)C NMR (101 MHz, DMSO-\(d_{6}\)) \(\delta\) 174.85, 169.56, 148.96, 147.31, 136.53, 135.24, 134.81, 130.09, 129.76, 127.52, 72.07, 71.19, 71.09, 68.74, 38.39, 37.07, 34.12, 30.32, 30.26, 29.89, 29.47, 29.20, 29.01, 28.13, 25.00, 22.99, 22.11.  
In a previous study, (\(\pm\))-differolide, the compound was proposed to be a biological regulator, with biological activity of promoting growth of _Streptomyces_ aerial hyphae and spore maturation [19]. However, such bioactivity has not been supported by experimental evidence. Considering that spore maturation was associated with _Streptomyces_ stress resistance, (\(\pm\))-differolide may have had an antioxidant bioactivity. In this study, we  
\begin{table}
\begin{tabular}{c c} \hline
**Primer** & **Sequence (5’-3’)** \\ \hline Left-for & gtaaaacgacggccagtccagtccagtccagcgtcgtcgacggc \\ Left-rev & ctggaaacctctggcgcgcgcgcgcgc gcccaggaggccaagctcg \\ Right-for & gegeccgcgcgcgaggttccag \\ Right-rev & aacagcttagacalgattac \\ \hline \end{tabular}
\end{table}
Table 1: Primers used in this study.  
measured the scavenging of (\(\pm\))-differolide to DPPH radicals with four concentration gradients. The results showed that the DPPH scavenging rate was 20.7-57.3% in the range of (\(\pm\))-differolide concentration of 0.25-1.5 mg/mL, and the calculated half-inhibition concentration (IC50) was 1.24 mg/mL (Figure 1d). This suggested that the compound was definitely an antioxidant that may have the effect of enabling _S. qaidamensis_ to survive in desert niche.
## 3 Proposed VC-FFs
### VC-DFF Circuit Architecture and Operations
#### 3.1.1 Normal Mode  
In this state, the traditional NVFF [14; 15; 16; 17; 18] separates the MTJs from the FF circuits via the transmitting transistors. As a result, the NVFFs work like traditional FFs. However, if the data are not backed up in time, there is still a risk of data loss, especially in the case of intermittent powering off. Traditional NVFFs need to perform the data backup operation  
Figure 2: (a) VC-SOT MTJ device structure; (b) bit-cell structure.  
before switching off the power supply in case of unexpected power failure. Unlike the traditional NVFFs, the proposed VC-DFF does not easily lose the data of the DFF. The input data can be saved in normal operation mode, so the VC-DFF does not require an additional backup operation in case of system power failure. In this state, the signal Cr is determined by the signal CLKB. As shown in Figure 3a, when CLK = \"1\", N\({}_{1}\) turns on while N\({}_{6}\)-N\({}_{9}\) turn off. The state of Q is consistent with that of the input signal D. The state diagram of the VC-DFF is the same as shown in Figure 1d. The voltages of the two write control signals V\({}_{\text{sot}}\) and V\({}_{\text{bia}}\) are set to V\({}_{\text{dd}}\). N\({}_{4}\) and N\({}_{5}\) are turned on, and the bias voltages of MTJs (M\({}_{\text{data}}\) and M\({}_{\text{ref}}\)) rise to V\({}_{\text{dd}}\). Increasing the bias voltage reduces the energy barrier of the VC-MTJ devices. It is particularly noteworthy that the two VC-SOT-MTJ devices are connected back to back. The structure can ensure that the magnetization direction of two devices is always reversed to a complementary state when the write current passes through the two devices. Specifically, for D = \"0\", a SOT write current flows from M\({}_{\text{ref}}\) to M\({}_{\text{data}}\). The write operation is completed by switching the magnetization of M\({}_{\text{ref}}\) and M\({}_{\text{data}}\) to the AP (\"1\") and P (\"0\") states, respectively. It should be noted that the voltage of Cr is always locked at GND when CLK = \"1\", causing the node out\({}_{+}\) (out\({}_{-}\)) in the PCSA to rise to V\({}_{\text{dd}}\) before the read operation. As shown in Figure 2b, when CLK = \"0\", N\({}_{6}\)-N\({}_{9}\) turn on while N\({}_{1}\)\(\sim\)N\({}_{5}\) turn off. In this case, Q follows the state of out\({}_{+}\). The data voltage signal (V\({}_{\text{TI+}}\)) and the reference voltage signal (V\({}_{\text{TI-}}\)) are involved in the sensing operation of the PCSA. Finally, the PCSA generates the readout output. As mentioned above, data are always stored in a complementary state in the MTJ devices. Therefore, this symmetrical structure can maximize the read margin and the stability of the PCSA.
## 3 NFV Network Architecture with AI-Based Resource Allocation  
An example of ETSI compliant NFV network [11; 12] is reported in Figure 1. It is composed by NFVI-PoPs interconnected by a network infrastructure. The interconnection of the NFVI-PoPs is accomplished by means of either electrical [27] or optical [28; 29] networks. Let \(\bar{G}=(\bar{U},\bar{L})\) denote the graph in which \(\bar{U}=\bar{U}_{NP}\cup\bar{U}_{S}\) characterizes the set of NFVI-PoPs (\(\bar{U}_{NP}\)) and the set of network switches (\(\bar{U}_{S}\)) and \(\bar{L}\) characterizes the set of network links. We assume that the NFVI-PoP \(\bar{u}\in\bar{U}_{NP}\) is equipped with \(N_{a}\) cores. In view of a multi-provider scenario we assume that the processing resource costs may be different for the various NFVI-PoPs and denote with \(c_{core}^{\bar{u}}\) the cost of renting one core per one hour (\(\$/\)h) for the NFVI-PoP \(\bar{u}\in\bar{U}_{NP}\). The NFVI-PoPs are able to instantiate VNF Instance (VNFI) than can execute a given Service Function (SF), i.e., Firewall, Proxy, DPI,...We assume that the VNFIs can belong to \(Q\) types; the \(i\)-th (\(i\in[1..Q]\)) type VNFI is characterized by the allocation of \(n_{i}^{c}\) processing cores when the maximum processing capacity (Gbps) \(C_{i}^{pr,max}\) is provided by the VNFI. The traffic variation is handled by a vertical scaling technique [3] that assigns more/less cores when the traffic increases/decreases. In particular we assume that the \(i\)-th (\(i\in[1..Q]\)) type VNFI can work in \(n_{i}^{c}\) operation modes. The \(j\)-th (\(j\in[1..n_{i}^{c}]\)) operation mode is characterized by the allocation of \(j\) cores and the guarantee of a processing capacity of \(C_{i,j}^{pr}=j\frac{C_{i}^{pr,max}}{n_{i}^{c}}\). The instantiated VNFIs are shared for the execution of SFs belonging to a set given of \(N\) Service Function Chains (SFC). The \(i\)-th (\(i\in[1..N]\)) SFC is characterized by an ordered set of \(M_{i}\) SFs. The following functional blocks are reported in Figure 1[11]:  
* the VNF Manager (VNFM) manages the lifecycle of VNFIs; it is provided with a Monitoring Agent (MA) whose task is to measure the processing capacity used by the VNFI;
* the Virtual Infrastructure Manager (VIM) controls and manages the NFVI-PoP resources; it is provided with an Allocation Agent (AA) whose task is to collect the data measured by the VNFIs and execute the algorithm for evaluating the processing capacities to be allocated to the VNFIs;
* the NFV Orchestrator (NFVO) manages the lifecycle of Network Services; it is provided with a Reconfiguration and Placement Agent (RPA) whose task is to execute an algorithm for the resource reconfiguration and the VNFI placement on the basis of the processing capacities to be allocated to the VNFIs. The proposed procedure consists of four main steps:  
* Step-1: The MAs continuously monitor on a periodic basis with duration \(T_{m}\) and using the Ve-Vnfm-vnf ETSI interface [12] the processing capacity required by the VNFI; let us consider the reference NFVI-PoP \(\bar{u}\in\bar{\varOmega}_{NP}\) of Figure 1 and let \(N^{\bar{u}}_{VNFI}\) be the number of instantiated VNFIs.
## 3 Results and Discussion
### FTIR Analysis  
Figure 6 shows the infrared spectra of the self-adhesive membrane specimens in their unaged state, as well as after 5, 7, 14, and 28 days of thermo-oxidative and freeze-thaw aging. The chemical bonds and functional groups present in the material can be identified by analyzing the position of the absorption peaks, as well as the shapes and intensities of the peaks in the infrared spectra. When the unaged and aged self-adhesive membrane specimens are compared, the characteristic peak areas near 2930 cm\({}^{-1}\) and 2846 cm\({}^{-1}\) significantly decreased with increasing aging time, which was attributed to the degradation and breakage of butadiene chain segments in bitumen, leading to a reduction in the content of C=C double bonds. Additionally, the characteristic peak area near 1400 cm\({}^{-1}\) increased due to the formation of oxygen-containing groups such as carbonyl (C=O) and sulfinyl (S=O) after oxidation at high temperatures, which resulted in an increase in the content of these groups. The aging mechanism and degree of different self-adhesive membranes can be analyzed by comparing and calculating the indices for double bonds, sulfoxide groups, carbonyl groups, and sulfide ether functional groups, with the results shown in Table 3.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline Aging time (day) & 0 & 2 & 5 & 7 & 14 & 28 \\ \hline Cracking temperature (\({}^{\circ}\)C) & \(-28.5\) & \(-26\) & \(-22\) & \(-21\) & \(-18\) & \(-15\) \\ \hline \end{tabular}
\end{table}
Table 2: Cracking temperature for low-temperature flexibility test.  
Figure 6: Fourier infrared spectral test plot after thermo-oxygen-freeze–thaw cyclic aging.  
As shown in Figure 6 and Table 3, the self-adhesive membrane subjected to the combined effects of thermo-oxidative aging and freeze-thaw cycle aging exhibited a decrease in the carbonyl index, alongside increases in both the sulfoxide index and the butadiene double-bond index. The sulfide index, however, decreased. This indicates that the specimen underwent oxidation reactions during the aging process, leading to a reduction in light components, such as the aromatic fraction of the asphalt. This also corroborates the presence of impurities observed on the surface in the SEM tests mentioned earlier.
###### Abstract  
With the development of techniques, such as the Internet of Things (IoT) and edge computing, home energy management systems (HEMS) have been widely implemented to improve the electric energy efficiency of customers. In order to automatically optimize electric appliances' operation schedules, this paper considers how to quantitatively evaluate a customer's comfort satisfaction in energy-saving programs, and how to formulate the optimal energy-saving model based on this satisfaction evaluation. First, the paper categorizes the utility functions of current electric appliances into two types; time-sensitive utilities and temperature-sensitive utilities, which cover nearly all kinds of electric appliances in HEMS. Furthermore, considering the bounded rationality of customers, a novel concept called the energy-saving cost is defined by incorporating prospect theory in behavioral economics into general utility functions. The proposed energy-saving cost depicts the comfort loss risk for customers when their HEMS schedules the operation status of appliances, which is able to be set by residents as a coefficient in the automatic energy-saving program. An optimization model is formulated based on minimizing energy consumption. Because the energy-saving cost has already been evaluated in the context of the satisfaction of customers, the formulation of the optimization program is very simple and has high computational efficiency. The case study included in this paper is first performed on a general simulation system. Then, a case study is set up based on real field tests from a pilot project in Guangdong province, China, in which air-conditioners, lighting, and some other popular electric appliances were included. The total energy-saving rate reached 65.5% after the proposed energy-saving program was deployed in our project. The benchmark test shows our optimal strategy is able to considerably save electrical energy for residents while ensuring customers' comfort satisfaction is maintained.  
energy saving; electric appliance utility function; prospect theory; energy-saving cost +
Footnote †: journal: