esa-sceva/satcom-chunk-collection huggingface dataset:
# Incomplete Similarity Error Analysis Method of Steel Frame Structure Based on Correlation
## 1 Introduction  
Similarity theory is one of the basic theories in the structural scaled down model test and plays a vital role in engineering-oriented design [1]. However, this theory is facing the challenges of complicated theoretical derivation, identification of the number of similarity factors and a lack of research into showing the numerical error between the scale model and the prototype [2]. In addition, the effect of the incomplete geometric similarity in steel joints and its contribution to similitude error of the entire steel frame has rarely been evaluated until now. In test data analysis, prior research has not thoroughly investigated the similitude problem, most likely leading to errors in the experimental results [3]. This paper investigates the effect of three incomplete geometric similarity factors on the similitude error between the scale model and the prototype, which are the geometric similarity of steel components, the stiffness of steel joints and the stiffness of the column base and the contribution of each to the similitude error within the whole structure. The remaining similarity factors demonstrate complete similarity.  
First of all, much is known about the influence of the geometric similarity of steel components. [PERSON] et al. studied the scaling laws in a model test of steel beam-to-column connections and, demonstrated that geometric similarity is the main cause of simulation errors [4]; however, this study was only concerned with the geometric similarity of steel joints. In the entire frame, prior studies have failed to evaluate the result when many parts of the scaled down frame are dissimilar to those of the prototype. [PERSON] et al. studied the semi-rigid characteristic of steel beam-to-column connections, which play a vital role in the whole frame [5]. Thus, the similitude of the semi-rigid characteristic of steel beam-to-column connections is also an important aspect of overall similarity. However, little is known about the mechanisms. In the same way, the similarity of the stiffness of the column base, also has an important influence on the overall similarity of the structure [6].  
This paper is based on similarity theory--by adding the semi-rigid characteristics of both the beam-to-column connections and the column base to the derivation of similar conditions, the similarity conditions of semi-rigid steel frame are developed. The three incomplete geometric similarity factors are thoroughly examined to obtain the sensitivity of each factor. Sensitivity analysis based on BP (Back Propagation) algorithm shows that each factor has different influence on overall similarity. The purpose of this paper is to study the effects of three incomplete similar factors on the overall incomplete similarity error of steel frame structures and its mechanism. This paper presents a method to evaluate the similitude error of a scaled down model, which can correct errors in experimental results.
## 2 Materials and Methods
### Finite Element Model and Optimization Setup
#### 2.3.3 Thickness Optimization Procedure  
The goal is to maximize and compare the specific energy absorption capabilities of each approach while restricting the mass of the geometry to a constant value. SEA is defined as the integral of the transient reaction force, \(F_{R}\), at the moving plate over its travelled distance, s, normalized by the structure's mass, m\({}_{0}\), as shown in Equation (4).  
\[\text{SEA}=\frac{1}{m_{0}}\int_{0}^{s}F_{R}(a,b,c,s)ds \tag{4}\]  
The goal is, therefore, the maximization of SEA by altering the parameters \(a\), \(b\), and \(c\) as expressed by Equation (5). Their limits, provided in Table 2, are chosen such that a broad design space is covered to permit numerous explorable combinations. More important than these limits are the constraints imposed on each region's minimum and maximum radiuses, which can lie between 0.4 and 1 mm. The lower bound ensures reasonable manufacturability, while the upper bound leaves sufficient space between their outer edges such that the lattice is not entirely compressed at the chosen compression level.  
\[\underset{a,b,c}{\text{max}}(\text{SEA}) \tag{5}\]A mass limit is imposed to prevent the optimization algorithm from simply increasing the thickness endlessly to fulfil the maximization goal and to keep the relative density constant, ensuring comparability between models. It is equal to each reference lattice's mass with a 1.3 mm uniform beam diameter, which is the thickness of the uniform lattice structures to which the optimized ones are compared. The standard constraint enforcement of HyperStudy is enabled, which considers a constraint violation of 0.5% acceptable, reducing the required optimization iterations. The mass is only parsed once in the initial step of the simulation to avoid any influence of mass scaling that may occur during the simulation.  
A Design of Experiment (DOE) study using the Modifiable Extensible Lattice Sequence (MELS; see [31]) approach is run first with 50 iterations to explore the design space and provide initial sampling points for the optimization procedure. It is then relayed into the optimization run, which employs the Global Response Search Method (GRSM; see [32]) algorithm with an upper limit of 500 iterations. The GRSM algorithm is a gradient-based optimization method that uses a response surface fit with global sampling to increase the probability of finding the global optimum. Its fundamental principle is represented schematically in Figure 9. The exact methodology is proprietary and not available to the public; therefore, no further information can be provided here.
## Data and Methods  
### Study Area  
The Loess Plateau is one of the most corrodible regions in the world which is located at latitude of 34 deg-40 degN and longitude of 103 deg-114 degE and is approximately 1000 km long from west to east, and 700 km wide from south to north. The Loess Plateau stretches across a region north to the Yinshan Mountains in Inner Mongolia, south to the Qinling Mountains, west to the Riyue Mountains, east to the Taihang Mountains which covers a total area of approximately 6.4 \(\times\) 105 km\({}^{2}\), 6.5% of the territory in China, with average elevations ranging from 1500 to 2000 m above sea level. This region covers seven provinces, including Gansu, Henan, Ningxia, Inner Mongolia, Qinghai, Shanxi, and Shaanxi (Figure 1). It has complex topography which is full of hills, basins, and alluvial plains with continuous loess of 100-300 m in thickness. It has the continental monsoonal climate which lies in a semi-humid and semi-arid transitional zone with an annual average temperature of about 6 to 14 degC and annual precipitation of about 200 to 700 mm [31]. Approximately 70% of annual precipitation occurs between June and September during summer. The Loess Plateau is one of the most severely eroded regions globally because of frequent storms, highly erodible soil, low vegetation cover, and steep landscape [32; 33]. The major regions of the Loess Plateau are undergoing heavy soil erosion because of human disturbances over a long period of time. Therefore, forests mainly exist in some mountainous areas of the plateau.  
Wuqi County was the first place to carry out the GGP, which is located in the northwest of Yan'an County, Shaanxi Province. In 1998, the county took the lead in launching the project. In early 2000, it  
Figure 1: The study area and location of the Loess Plateau (LP) in China.  
was listed as a pilot site for forest and grass vegetation restoration on the Loess Plateau of the State Forestry Administration, and implemented conversion from farmland to forests. The county is located in the transitional zone between agriculture and pasture in the southern margin of the Mausu Sandy Land. It covers the middle reaches of the Yellow River, the Beiluo River, and the upper reaches of the Wuding River. It belongs to the Liangzhugou area of the Loess Plateau. The geographical position is 107 deg38'57''\(\sim\)108 deg32'49'' east longitude, 36 deg33'33''\(\sim\)37 deg24'27'' north latitude, the total area is 3791 km2, and the altitude is 1233\(\sim\)1809 m.
# Lignin to Materials: A Focused Review on Recent Novel Lignin Applications
## 3 Medical Applications
### Pharmaceuticals
For instance, ethanol was an effective eluent for ibuprofen with a yield of 82.2%, while methanol was an effective eluent for acetaminophen with a yield of 80.8%. In another application, lignin was used as a carbonaceous precursor with TiO\({}_{2}\) to form a photocatalyst that degraded acetaminophen, or Tylenol, in one hour of solar radiation [37]. Photocatalysts that experienced thermal treatment in nitrogen rather than in air maintained more carbon from the lignin. This caused a higher light absorption and decreased the photocatalytic efficiency. In another study investigating the use of lignin to adsorb fluoxetine, alkali lignin with low sulfur content and PVA were dissolved to form a solution used for electrospinning [38]. Nanofibers recovered from the electrospinning process then went through a thermostabilization processes and an acidic bath to increase the strength of the fibers. A lignin:PVA ratio of 1:1 resulted in the optimal adsorption capacity; this lignin-PVA nanofibrous membrane adsorbed around 38% of the fluoxetine. The authors  
Figure 4: Biosorbent consisting of chitin and lignin removing ibuprofen and acetaminophen with high efficiency. Reprinted from reference [36], with permission from Elsevier. of the study hypothesized the sorption mechanism to be the phenol groups in lignin-forming hydrogen bonds with the amino or Fluor groups of the fluoxetine.
## 3 Research Framework  
The research framework is shown in Figure 1. The composite robustness criterion with start time deviation \(r_{s}\), structural deviation \(r_{p}\), and completion probability \(r_{c}\) is established so as to measure the schedule robustness of both solution and quality robustness. The improved prospect theory is adopted to determine the subjective weights, the Copula-CRITIC method is adopted to determine objective weights, and the information-entropy-based evidence reasoning method is adopted to combine the subjective and objective weights so that the bounded rationality of subjective weights and the inherent importance and nonlinear intercriteria correlations of objective weights can be considered. Then, an underground power station in China is used for a case study, and the advantages of the proposed criterion and methods are discussed and verified.
## 7 Collection and Processing of Thermal Images  
The impacts of the use of GSM devices on the physical condition of a person can be assessed by the thermal effects caused by the electromagnetic waves emitted by GSM devices. The experimental scenario includes a speaker with a GSM device for 20 min and a FLIR P640 thermal camera to capture their head in profile and full face. During the conversation, the GSM device was located about 1 cm from the head of the participant in the experiment, and the thermal camera was about 2 m away, focused on their head. The average room temperature was around 22 \({}^{\circ}\)C.  
As a result of the 20 min conversation and the irradiation with the electromagnetic waves from the GSM device, the head of the participant in the experiment warms up by about 1-2 \({}^{\circ}\)C as can be seen from Figure 5. The increase in head temperature depends on the duration of the conversations. When talking for up to 30 s, no change in intracranial temperature is observed; however, when talking for more than 2 min, first, the ear begins to warm up and then the soft tissues around the ear. The increase in temperature is a result of prolonged irradiation of the human body with high-frequency radio signals from the GSM device.  
The obtained results show that the temperature on the surface of the head is the highest and decreases in depth. The temperature change near the mobile phone is on the order of 0.6 \({}^{\circ}\)C and decreases rapidly inside the head. The thermal effects obtained from the model largely coincide with the results of a real experiment conducted with a thermal camera (Figure 5).  
Averaging the temperature of the head before and after the experiment resulted in a temperature difference of about 1.3 \({}^{\circ}\)C. After checking the number of pixels exceeding the temperature of 34 \({}^{\circ}\)C before and after the experiment, we found that, after the experiment, the area heated above this value was three-times larger than before the experiment. The thermal images were processed using MATLAB. The study found that the temperature of the head on the side of the GSM device heated up much more than the other side. The areas around the ear, forehead, and neck heated up much more than the rest of the head.  
The study of the processes of penetration of the electromagnetic field into the human head and the effects caused by this is an extremely important scientific task. The interaction between the human head and the electromagnetic radiation caused by cell phones can cause electric currents and electric fields in the human head, which can lead to negative health effects.  
Figure 4: Visualization of the thermal effects in the human head for several horizontal layers.
## 3 RUL Prediction Methodology
### First Detection Time, End-of-Life Time and RUL Prediction Time
#### 3.3.2 End-of-Life (EOL) Time and EOL Threshold  
As can be concluded from multiple endurance experiments on REBs [5; 6; 7], bearings operated under identical loading conditions could end up with different failure modes, either single or compound faults, and the individual lifespans of the same type of bearings could vary greatly due to multiple factors such as manufacturing and mounting errors. For this reason, the determination of the accurate EOL threshold for bearing health indicators is one of the key challenges in RUL prediction.  
Assume that the spectral energy of the FCF components accumulates to the highest level when functional failures occur, i.e., the replacement should be made; the EOL time of the rolling bearing \(t_{EOL}\) can be selected as the time when the extracted ESI reaches the maximum,  
\[t_{EOL}=\underset{t}{\text{argmax}}ESI(t), \tag{5}\]  
Empirically, the EOL threshold for RUL prediction is calculated based on the average of the maximum ESI values computed from each set of test bearing data across the lifespan [7], as given by  
\[\overline{\gamma}=\frac{1}{j}\sum_{j}^{J}ESI_{j}(t_{EOL}), \tag{6}\]  
where \(ESI_{j}(t_{EOL})\) denotes the ESI amplitude at the end-of-life time of the \(j\)-th bearing and \(J\) the total number of available test bearings.
## 4 Conclusions  
This study allowed us to identify the chemical composition of a decoction extract of _C. cardunculus_ leaves and to evaluate the antimicrobial activity of several extracts of _C. cardunculus_ as well as their influence on melanin bioproduction. It was found that CL is mainly composed of chlorogenic acid and its derivatives. The antimicrobial activity in solid medium and in liquid medium was evaluated for 15 bacterial strains using CA, RA, CL, CI, CA:RA, CL:CI as antimicrobial agents. RA showed an MBC of 1 mg/mL in 80% of the strains. In liquid medium, CL showed the greatest reduction in the growth of _P. putida_ ESACB 191, around 6.20 Log CFU/mL, which corresponded to 66% of bacteria growth on average. The influence of these extracts and phenolic acids on the bioproduction of melanin was also studied. Chlorogenic acid showed 50% reduction in melanin bioproduction by _P. putida_ ESACB 191 in 48 h.  
Figure 4: _P. putida_ ESACB 191 melanin bioproduction (mg/L/h) by action of several _C. cardunculus_ extracts: CL:CI—50% Leaf decoction + 50% Inflorescence decoction. CI—Influorescence decoction. CL—Leaves decoction. CA:RA—50% Chlorogenic acid + 50% Rosmarinic acid. RA—Rosmarinic acid. CA—Chlorogenic acid. The concentration 1 mg/mL was used for all samples tested in Müller–Hinton Broth with 1% of L-tyrosine. The a-d letters correspond to statistically different values (\(p\leq 0.05\)).  
Chlorogenic acid is one of the main components of phenolic acid derivatives of _C. cardunculus_ leaves extract (CL), which may justify the inhibitory action on bacterial growth and melanin bioproduction found with the plant extract. Thus, in the future, the application of CL extracts with antimicrobial activity in edible films and/or coatings to cheese find to increase the shelf time can be studied.  
A.R.F.: Investigation, method development C.M.B.S.P.: Microbiology supervision, microbiology resources, funding acquisition, paper reviewing M.L.S.: Work conceptualization, formal analysis; funding acquisition; project administration. All authors have read and agreed to the published version of the manuscript.  
The study was funded by Fundacao para a Ciencia e Tecnologia (FCT) with financial support to IPCB-CERNAS (UID/AMB/00681/2020) Research Unit Grant from FCT; to BioISI Research Unit through the contract UIDB/04046/2020 from FCT; to CESAM (UID/AMB/50017/2019), through FCT/MEC National funds, and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. This work is recipient of a project (PTDC/Bia-BQM/28355/2017) grant and [PERSON] acknowledges a PhD fellowship (SFRH/BD/135692/2018) from FCT (Portugal).  
Not applicable.  
We thank [PERSON] for the help provided in the Laboratory of Microbiology (IPCB/ESA) and [PERSON] for analyzing the extract of _C. cardunculus_ by LC-HRMS/MS.  
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
###### Abstract  
This paper considers the navigation of a solar-powered unmanned aerial vehicle (UAV) for securing the communication with an intended ground node in the presence of eavesdroppers in urban environments. To complete this task, the UAV needs to not only fly safely in the complex urban environment, but also take into account the communication performance with the intended node and eavesdroppers. To this end, we formulate a multi-objective optimization problem to plan the UAV path. This problem jointly considers the maximization of the residual energy of the solar-powered UAV at the end of the mission, the maximization of the time period in which the UAV can securely communicate with the intended node and the minimization of the time to reach the destination. We pay attention to the impact of the buildings in the urban environments, which may block the transmitted signals and also create some shadow region where the UAV cannot harvest energy. A Rapidly-exploring Random Tree (RRT) based path planning scheme is presented. This scheme captures the nonlinear UAV motion model, and is computationally efficient considering the randomness nature. From the generated tree, a set of possible paths can be found. We evaluate the security of the wireless communication, compute the overall energy consumption as well as the harvested amount for each path and calculate the time to complete the flight. Compared to a general RRT scheme, the proposed method enables a large time window for the UAV to securely transmit data.  
unmanned aerial vehicles (UAVs); solar-powered UAVs; wireless communication; secure communication; eavesdropping; security; unmanned aerial vehicles; navigation; autonomous systems; path planning; rapidly-exploring random tree navigation +
Footnote †: journal:  
_Future Internet_
## 2 Related Works
### Ambient Assisted Living Systems  
Several surveys in the literature describe recent trends in smart homes aimed at assisted living systems [6; 7; 8; 9]. These monitoring systems can use exclusively ambient sensors (i.e., RGB and/or infrared cameras) to limit user discomfort as much as possible [10; 11; 12], can use wearable sensors if health parameters need to be monitored [13], or can exploit different modalities at the same time [6; 7; 8].  
The following systems make a pervasive use of ambient and wearable sensors. Necessity [14] is an ambient assisted living system, which monitors the states of the elderly (out, active, inactive, resting, sleeping and inactive anomalous), through different ambient sensors (pressure, door and activity) scattered into the environment. Both [15; 16] present an elderly healthcare system aimed at monitoring different activities using body sensors. A significant issue for systems based on body sensors is the need to apply them onto the subject, for better accuracy or to detect more actions or activities. This can be considered a critical aspect because wearable sensors can lead to physical discomfort for the user. A different kind of sensor, less invasive and more discreet, is used in the system presented by [17], which can both track and detect the fall of elderly people using smart tiles.  
Regarding video-based systems, ref. [18] propose a method for human posture-based and movements-based monitoring, limited however to only 5 postures (standing, bending, sitting, lying and lying toward) and 4 movements (running, jump, inactive, active). IFADS (Image-based FAll Detection System) [19] focuses on falls that might happen while sitting down and standing up from a chair, a situation of potential danger for elderly people.  
In this work we design a monitoring system which exploits visual data. This type of information is easily acquired using RGB cameras that can be placed in the environment with minimum effort. As an indication of the pervasiveness and affordability of this kind of sensors, the survey [8] reports more than 60 works on activity monitoring systems exploiting visual data, and about 20 works for wearable sensors. Moreover, different from existing solutions in the literature, our system is carefully designed to support the recognition and monitoring of a wider variety of actions, including status,different alerting situations as well as daily life activities. These actions have been specifically selected for monitoring elderly people at home.