esa-sceva/satcom-chunk-collection huggingface dataset:
# Implementation of a Blood Cold Chain System Using Blockchain Technology
## 3 Design of Blood Cold Chain System
### New Blood Cold Chain System Based on Blockchain Technology
#### 3.2.4 Emergency Blood Supply Situation  
In an emergency, a medical institution far from the blood bank will not be able to receive a blood supply quickly. To address the limitations of the existing centralized blood supply, the system designates this as a special situation and allows the medical institution to request the type of blood and the amount of blood required from nearby medical institutions. Figure 5 shows the transaction flow and consensus process for this situation. Since Hyperledger Fabric uses a distributed consensus algorithm via a specific verification node, the role of verifying the requested transaction in this case is the peer of hospital A and the peer of hospital A's neighbor (hospital B).  
(1) shows that the client of hospital A requests a blood transaction. (2) and (3) show that when the proposal is delivered to the assurance peer, the peers of hospital A and the neighboring hospital (hospital B) corresponding to the assurance peer execute the chaincode to verify the transaction. In (4) and (5), the application examines the results received from the guaranteed peer. (6) shows that the application submits the transaction to the ordering service. In (7) and (8), the ordering service defines the transaction sequence, creates one block, and sends it to all peers. (9) shows that each peer verifies the  
Figure 5: Blood supply in emergency situations.  
transaction and confirms the transaction after verifying that the guarantee condition is met. (10) shows that the neighboring hospital (hospital B) ultimately supplies the surplus blood supply to hospital A.
## 3 Results and Discussion
### Sgs Cases
#### 3.2.2 SGS Cases: Vocal Fold Vibration and Glottal Flow Dynamics
Figure 9: (**a**) The energy percentage of the two dominant proper orthogonal decomposition (POD) modes of the vocal fold vibration versus SGS severity in the parametric cases; (**b**) the similarity of the corresponding POD modes of the vocal fold vibration versus SGS severity in different parametric cases; (**c**) the three-dimensional shape of these POD modes for the baseline case and the 96% SGS severity case; 2D cross sections of each mode shows the two extreme phases of the mode; narrow lines are baseline case and thick line is 96% case. To evaluate the consistency of mode shapes across different SGS severities, the dot product of each mode shape with its corresponding baseline case mode shape was calculated, as shown in Figure 9b. A dot product value of 1 indicates identical modes, while 0 indicates orthogonal modes. Our analysis reveals that the 1 st mode shape remains largely unchanged across all SGS severities. However, the 2 nd mode shape undergoes significant alterations in the 96% severity case, where the dot product drops to 0.68, suggesting a substantial deviation from the baseline mode shape. Figure 9c illustrates the two extreme states (referring to two peak displacement state during a vibration cycle generated by each POD mode) of the 1 st and 2 nd shapes for both the baseline and 96% severity cases, along with two-dimensional cross-sections of the vocal fold in the y-z and x-z planes. Comparing these two severity cases, we observe that the 1 st mode remains relatively stable, while the 2 nd mode shape exhibits noticeable differences between the baseline and 96% severity cases. It's important to note that while the 90% severity case maintains mode shapes similar to the baseline, we observe an increase in the 1 st mode's energy and a decrease in the 2 nd mode's energy (Figure 9a). This suggests that for the 90% case, the lateral motion strengthens while the convergent-divergent motion weakens. For the 96% case, although the energy distribution is comparable to the 90% case, we see more substantial changes in the mode shapes, particularly in the convergent-divergent motion. These findings align with our previous study, confirming that vocal fold vibration is significantly affected by SGS severities above 90%. These higher severities correspond to Grade III and Grade IV SGS classifications, underscoring the clinical relevance of these observations.
# Resource Management in Cloud Radio Access Network: Conventional and New Approaches
## 3 Resource Management Techniques in C-RAN
### Radio Resource Management Techniques
#### 3.1.3 Sum-rate Optimization  
In [47], [PERSON] et al. investigated the impact of available computing resources on the PHY transmission characteristics by formulating a user-RRH association problem for uplink transmission in a C-RAN. The main objective was to maximize the network sum-rate under limited computing resources. At first, the binary integer non-linear programming problem was transformed to a general non-linear programming problem for reducing complexity. Then, an iterative sub-optimal algorithm was proposed to solve the problem by updating the objective function iteratively until the optimal solution is achieved.  
Table 2 presents the research activities mentioned in this paper on RRM techniques in C-RANs. The application, goal, problem formulation, and techniques that are used in the relevant works are mentioned.
## 5 Conclusions  
A survey of the current and state-of-the-art routing protocols for UWSNs is presented. Challenges associated with the underwater channel are characterized. The routing protocols are classified into two groups: localization-based and localization-free protocols. The former requires two- or three-dimensional position coordinates information of the sensor nodes for establishing the routing paths. The latter requires only the depth (or pressure) information. Each category of the protocols is further subdivided according to the problem(s) it addresses or the major parameter(s) it considers for routing. They include node's mobility, energy balancing, channel properties, energy consumption and void zone. Every protocol is described in terms of its routing strategy, merit(s) and demerit(s). Such a description of the protocols is useful in a number of ways for researchers, as compared to the existing surveys. The routing strategies help in understanding the routing operation of the protocols. The demerits lead to the design of new protocols that are more efficient and effective. The merits help in the selection of the right protocol for the right underwater application. Open research challenges and directions that need to be addressed in the future are specified.
Effects on Cell Growth, Lipid and Biochemical Composition of _Thalassirosira weissflogii_ (Bacillusariophyceae) Cultured under Two Nitrogen Sources  
[PERSON]  
1 Centro de Investigaciones Biologicas del Noroeste (CIBNOR), La Paz 23096, Mexico;  
[EMAIL_ADDRESS] (B.O.A.-V.); [EMAIL_ADDRESS] (A.L.C.-C.); [EMAIL_ADDRESS] (M.M.-L.)  
[PERSON]  
2  
[PERSON]  
1 Centro de Investigaciones Biologicas del Noroeste (CIBNOR), La Paz 23096, Mexico;  
[EMAIL_ADDRESS] (B.O.A.-V.); [EMAIL_ADDRESS] (A.L.C.-C.); [EMAIL_ADDRESS] (M.M.-L.)  
[PERSON]  
3 Departamento de Plancton y Ecologia, Centro Interdisciplinario de Ciencias Marinas (IPN-CICMAR),  
Instituto Politecnico Nacional, La Paz 23096, Mexico; [EMAIL_ADDRESS] (C.J.B.-S.);  
[PERSON] (L.J.F.-H.)  
4  
E.J.  
allow them to digest formulated diets completely [3; 4]. Accordingly, natural microalgae are still considered as the main live food source for marine larvae [2; 5].  
As a consequence of their nutritional value, diatom species, such as _Skeletonema costatum_, _Thalassiosira_ sp., _Phaeodactylum_ sp., _Chaetoceros gracilis_, _C. calcitrans_ and the _flagellates Pavlova lutheri_, _Isochryssi galhana_, _Tetraselmis chuii_ and _T. suecica_ are all grown as food for rearing marine organisms of commercial value [6; 7]. Their biochemical composition is important for their nutritional value because of their ability to synthesize and accumulate essential fatty acids and other nutrients [8; 9].  
Among the species previously mentioned, _Thalassiosira weissflogii_ has been provided successfully for feeding shrimp larvae [10] because of its shape, digestibility and biochemical composition [11], which can vary as a result of changes in the environment [12; 13; 14]. Thus, the effects of temperature, salinity, pH, nutrients and their interactions have been addressed [14; 15; 16]. Additionally, the growth phase is recognized as an important factor influencing the biochemical composition of microalgae. For example, during the stationary phase, when nitrogen becomes limiting, microalgae shift their metabolism to carbohydrate and lipid production [17]. Among all the physical-chemical factors, nitrogen influences lipid metabolism and its deficient conditions increase fatty acid concentration in various microalgae [18; 19]. Nitrogen in the form of nitrate, ammonia or urea (or their combinations) is added to most media for commercial aquaculture in high concentrations and changes in nitrogen supply are known to strongly influence the growth and biochemical composition of microalgae [20]. Furthermore, nitrogen is easy to manipulate and less expensive compared to other growth factors. Comparatively few studies have analyzed the effects of different nitrogen sources on the biochemical composition of the diatom _T. weissflogii_. Therefore, this study evaluated different concentrations of two nitrogen sources, sodium nitrate (NaNO\({}_{3}\)) and ammonium chloride (NH\({}_{4}\)Cl), on the growth, biochemical composition (protein, carbohydrate and lipid) and main fatty acids in the microalga _T. weissflogii_.
## 4 State Feedback Control Design
### Stability Analysis  
The system stability and constraint property of the AUV surge motion is established by the following theorem.  
**Theorem 1**.: _Consider the closed-loop surge motion AUV system consisting of (1), (18)-(21). The boundedness of all signals in the closed-loop system and \(|z_{1}|<b_{z}\) are guaranteed. The rectification error \(z_{1}\) converges to a tunable set as follows:_  
\[\lim_{t\to\infty}|z_{1}|\leq\sqrt{\frac{\rho_{1}}{\lambda_{1}}}. \tag{22}\]  
_The definitions of \(\rho_{1}\) and \(\lambda_{1}\) in (22) are available in (30)._  
Proof.: Let us define a Lyapunov function as  
\[V=V_{1}+V_{2}+\frac{1}{2\gamma_{3}}\mathbf{\ddot{\omega}}^{T}\mathbf{\ddot{\omega}}+ \frac{1}{2\gamma_{4}}\mathbf{\ddot{\theta}}^{T}\mathbf{\ddot{\theta}}+\frac{1}{2\gamma _{5}}\xi_{\rho}^{2}, \tag{23}\]  
where \(\mathbf{\ddot{\omega}}=\mathbf{\omega}-\mathbf{\dot{\omega}},\mathbf{\ddot{\theta}}=\mathbf{ \theta}-\mathbf{\dot{\theta}},\dot{\varepsilon}_{\rho}=c_{\rho}-\dot{\varepsilon}_ {\rho}\).  
Applying (18), we have  
\[\dot{V}\leq -\frac{\gamma_{1}}{2}\frac{z_{1}^{2}}{b_{z}^{2}-z_{1}^{2}}+\sigma |z_{1}|\bar{\epsilon}_{\rho}+\zeta-\gamma_{1}z_{1}^{2}-\gamma_{2}z_{2}^{2}+z_{ 2}[\mathbf{\ddot{\omega}}^{T}\mathbf{\psi}(\mathbf{X})+\epsilon(\mathbf{X})+\mathbf{\ddot{\theta} }^{T}\mathbf{\varphi}]\] \[+\frac{1}{\gamma_{3}}\mathbf{\ddot{\omega}}^{T}\mathbf{\dot{\omega}}+ \frac{1}{\gamma_{4}}\mathbf{\ddot{\theta}}^{T}\mathbf{\ddot{\theta}}+\frac{1}{\gamma _{5}}\bar{\epsilon}_{\rho}\dot{\epsilon}_{\rho}. \tag{24}\]  
Hence, by setting proper parameters \(\zeta,\mu\), \(k_{1}-k_{3}\) and \(\gamma_{1}-\gamma_{4}\), we can achieve the desired steady-state accuracy. On the other hand, since \(b_{z}>|z_{1}(0)|\) holds, from (30), we can see that \(b_{z}^{2}-z_{1}^{2}>0\) holds for \(t>0\), which implies  
\[|z_{1}(t)|<b_{z},\forall t>0. \tag{32}\]  
According to the construction of \(x_{d}^{*}\), it follows from (32) that \(|x_{1}(t)-x_{d}(t)|<b_{z}\) holds for \(t\geq t_{d}\). Furthermore, we can see that \(|x_{1}(t)|<b_{z}+|x_{d}|\) holds for \(t\geq t_{d}\).
# Analysis of Vehicle-Bridge Coupling Vibration Characteristics of Curved Girder Bridges
## 5 Conclusions  
This article took a three-span curved uniform section continuous box girder bridge as the research object. It used Fortran language to develop a highway bridge vehicle-bridge coupling vibration analysis program called Cmck. The influence laws of curvature radius, constraint method, and vehicle type on the vehicle-bridge coupling vibration of highway curved girder bridges were explored. The results showed that:  
1. Through comparison with the results of general finite element program calculations, it was shown that the overall and separate methods in the program Cmck had good agreement with the results via general FEA software, indicating that the calculation program based on the two methods of overall and separate vehicle-bridge coupled vibration analysis can effectively analyze the vibration.
2. As the radius of curvature increased, the dynamic response of the bridge showed a gradual decreasing trend. The peak vertical displacement decreased by 22.3%, the peak vertical acceleration decreased by 28.9%, and the peak torsional angular displacement decreased by 83.9%. Within the radius of curvature less than 100m, the decrease in the dynamic response of the bridge was more pronounced; compared to the vertical dynamic response, the torsional response was more sensitive to the radius of curvature.
3. Different bridge constraints significantly affected bridges' dynamic responses. Bridges' vertical and torsional dynamic responses under rectangular coordinate constraints increased significantly compared to polar coordinates. As the axle weight of vehicles decreased, the mid-span vertical and torsional dynamic responses decreased while the lateral dynamic response gradually increased.  
Conceptualization, H.C. and Y.L.; methodology, D.C.; software, D.C.; validation, Y.L. and D.C.; formal analysis, Y.L.; investigation, H.C.; resources, H.C. and D.C.; data curation, Y.L.; writing--original draft preparation, H.C.; writing--review and editing, Y.L.; visualization, H.C.;  
Figure 18: Mid-span dynamic response peaks of the bridge under different vehicle types: (**a**) vertical displacement peak; (**b**) vertical acceleration peak; (**c**) lateral displacement peak; (**d**) lateral acceleration peak; (**e**) and torsional displacement peak.  
supervision, Y.L.; project administration, D.C. and Y.L.; funding acquisition, H.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (51408557), the China Postdoctoral Science Foundation (2013M541995), and the Program of the Department of Transportation of Henan Province (2020J-2-6), which has made this chapter possible.  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflict of interest.
# Smartphones as a Light Measurement Tool: Case of Study
## 2 Prior Research
### Light Evaluation Software  
Programs used to evaluate lighting requirements in different spaces enable a quantitative analysis of scenarios thanks to its capability of creating a 3D virtual world where lighting effects are recreated and analyzed in both artificial lighting and daylighting scenes [17]. In this field, the most important software is called DIALux (DIALux evo 7, Dial, Ludenscheid, Germany). The main strength of this software is the complete database about lighting products of the main manufacturers, giving more accuracy to the analysis. It also provides information about power consumption of elements to guarantee compliance with the regulations [18].  
Similarly, the software called RELUX (version 2017.1.9.0, Relux Informatik AG, Munchenstein, Switzerland) allows us to generate quantitative and qualitative analysis of buildings' lighting thanks to simulation models created with specific materials; colors; reflection factors; natural and artificial lighting elements in order to get a closer possible view of reality [19].  
Another renowned and well-known tool to evaluate energy efficiency is the SEAD (Super-efficient Equipment and Appliance Deployment) Street lighting evaluation toolkit. This tool can help to make better choices regarding street lighting fixtures, which can lead to a maximum of 50% in energy savings [20], by providing an easy way of performing evaluations of light quality, energy consumption, and life cycle costs of efficient street lighting alternatives. This tool is supported by Mexico's National Commission for Energy Efficiency, India's Bureau of Energy Efficiency, Natural Resources Canada, the Swedish Energy Agency and the U.S. Department of Energy.  
Finally, the program BTwin (version 2.9.5.8, IMventa Ingenieros, Campanillas, Spain) [21] was designed to plan the street lighting installation based on the standard EN 12464-2 [10], as the program can import the manufacturer's luminance information to give more accuracy to the calculations. In addition, an evaluation of the installation's energy efficiency to obtain the energy label before carrying out its implementation can be performed by using the extended feature called AEwin. Vertical obstacles can be considered as well, as they can affect the lighting, and, by doing so, it is possible to increase the precision of the program.
## 2 Bird Strike and Rotor Dynamic Modeling
### Bird Strike Modeling
Therefore, 1/2 fan blade height as the impact position and the head side as the orientation were chosen, which is given in Figure 4.  
In the simulation, the sucked-in velocity of the bird was 116 m/s. Some of the previous studies [5] on the bird impacting fan did not take the rotation of the fan into account, namely, the blades were stationary. As a result, two problems that made the simulation deviate the actual impact process arose: (1) the dynamic stiffening effect on the blade due to the centrifugal force was ignored; (2) the direction of the contact force was constant, as the relative velocity between the bird and the blade was not considered. For a more realistic simulation of the bird strike onto the fan, the rotor system was run at different rotational speeds. Bird strike occurs in several stages of flight [1]. The differences of fan speed at each stage leads to the different dynamic responses of the fan blade and thus the rotor system. According to the fan rotation speed in QAR (quick access recorder) data of an aero engine, four rotational speeds were 836 r/min, 3772 r/min, 3344 r/min, and 1984 r/min corresponding to five typical operating conditions of the ground idle stage, approaching stage, climbing stage, cruising stage, and descending phase. The noted speeds were selected as the initial fan rotational velocities. The bird model was verified by comparing the numerical results with [PERSON]'s experimental results [41; 45]. Comparing the experimental data of [PERSON], the simulation data of the traditional model (sphere model), and the mallard model built in this paper, we monitored the pressure magnitude of the model after striking on the target. From Figure 5, when using the mallard model, the magnitude of the pressure values and the pattern of its variation with time are close to those of the [PERSON]'s experiment compared to the conventional model. The pressure difference does not exceed 15%, other than the peak value, so the bird collision model can be considered to reflect the real bird collision process to some extent. Figure 4: The selected impact position and bird orientation.
## 2 Methods
### Description of the Newly Proposed PSEMDI Method  
The _IMFs_ decompose the original signal into a set of different simple nonperiodic or periodic time series. Despite these differences, it is interesting to note that each _IMF_ has one dominant frequency, which is the basis for applying the phase shift principle. Thus, the phase shift principle is applied to every individual _IMF_ mode of the original acceleration data, and the new shifted modes are added together to form the velocity function, and subsequently the displacement [35]. The following simple example explains this method. Assuming that \(a_{i}cos(w_{i}t)\) represents an _IMF\({}_{i}\)_, then:  
\[a(t)=a_{1}cos(w_{1}t)+a_{2}cos(w_{2}t)+...+a_{n}cos(w_{n}t) \tag{8}\]  
with the corresponding integration:  
\[v(t)=\int a(t)dt=-\frac{a_{1}}{w_{1}}sin(w_{1}t)-\frac{a_{2}}{w_{2}}sin(w_{2}t )-...-\frac{a_{n}}{w_{n}}sin(w_{n}t)+K \tag{9}\]  
Thus, applying the phase shift principle:  
\[v(t)=\int a(t)dt=\frac{a_{1}}{w_{1}}cos(w_{1}t+\frac{\tau_{1}}{4})+\frac{a_{2 }}{w_{2}}cos(w_{2}t+\frac{\tau_{2}}{4})+...+\frac{a_{n}}{w_{n}}cos(w_{n}t+ \frac{\tau_{n}}{4})+K \tag{10}\]  
where \(v(t)\) is the velocity, \(a(t)\) is the acceleration, \(a_{i}\) is the amplitude, \(w_{i}\) is the frequency, \(t\) is the time, \(\tau\) is the main period, and \(K\) is the integration constant. The subscripts represent each _IMF_ of the signal obtained by EMD.  
Similarly, the method is repeated one more time to transform the velocity into displacement.  
Table 1 describes the steps for the proposed integration method. For the double integration, the same process has to be applied twice.  
It is important to remark that, for this method, the _IMF_ with the lowest frequency determines the amount of data in the analysis. This can usually be considered half of the original amount of data in the spectrum. Thus, in the analyses, it is crucial to consider this limitation of the method.
## 3 Proposed Stereoscopic Image SR Method with View Incorporation and CNN
### Estimation of View Difference Image with Modified CNN
#### 3.1.2 Mapping and Estimation of View Difference Image and Right View Image  
After extracting an \(n_{1}\)-dimensional feature map for each image patch in the first CNN layer, these \(n_{1}\)-dimensional vectors are mapped into \(n_{2}\)-dimensional vectors in the second CNN layer. The high-precision view difference image is estimated in the third CNN layer. Finally, we estimate the right view image after the three layer operation.  
Similar to the first layer, the second layer is built through the convolution and the RELU, as follows:  
\[I_{d2}=\max(0,W_{2}*I_{d1}+B_{2}) \tag{6}\]  
where \(W_{2}\) and \(B_{2}\) represent \(n_{2}\) filters of the support \(f_{2}\times f_{2}\times c_{2}\) and the biases, which comprise an \(n_{2}\)-dimensional vector, respectively. Output \(I_{d2}\) is composed of \(n_{2}\) feature maps, which can be conceptually used as representations of high-precision view difference image patches that will constitute a full high precision view difference image.  
According to the representations of high-precision view difference image patches in the second layer, the convolutional operation in the third CNN layer is defined to produce the high-precision view difference image, \(\mathbf{I}_{d3}\), as:  
\[I_{d3}=W_{3}*I_{d2}+B_{3} \tag{7}\]  
where \(W_{3}\) and \(B_{3}\) represent \(n_{3}\) filters of the support\(f_{3}\times f_{3}\times c_{3}\) and the biases, which comprise an \(n_{3}\)-dimensional vector.  
After the three layer operation, the right view image is estimated as:  
\[X_{1}=Z-I_{d3} \tag{8}\]  
where \(\mathbf{X}_{1}\) is the estimated right view image which is the output of the first stage.
# Autonomous Load Regulation Based Energy Balanced Routing in Reshargeable Wireless Sensor Networks
## 5 Routing Algorithm Based on Autonomous Load Regulation Mechanism  
The node accepts the relay request of its neighbor unconditionally in traditional multi-hop routing and cannot remove its overload by itself in a timely manner. The load balance efficiency of the network is limited by this passive mechanism. In this section, the autonomous load regulation mechanism is formulated based on data relay radius control and the corresponding routing algorithm combined with the charging scheme.