esa-sceva/satcom-chunk-collection huggingface dataset:
# Artificial Intelligence in Ophthalmology: Advantages and Limits
## 2 Technical Introduction to AI for Clinicians
### Deep Learning (DL)
#### 2.4.5 Multimodal Learning  
Multimodal learning finds and combines information from different sources to enable improved results compared to those obtained by assessing the sources of information separately. Thus, it provides synergistic behavior.  
The structure of CNNs can be changed to receive more images in the form of extra channels [28].  
Multimodal strategies and DL have recently been used in the diagnosis of eye diseases. Recently, it has been proven that a union of certain sources of information can offer models with higher predictive magnitude and robustness [28]. They have applications in volumetric OCT image analysis or in techniques that merge fundus with OCT images for the diagnosis of age-related macular degeneration (AMD) [29].  
Recent works have targeted the segmentation and classification of glaucoma and AMD. In [30], a method was proposed to register retinal vessels by combining information from fundus and OCT images. This combination has been studied for the diagnosis of AMD and for cup and optic disc segmentation for the diagnosis of glaucoma.  
Some issues derived from these studies include the following: In what way can the correct depiction for each origin of information be found? In what manner and where should representational characteristics be merged in the given model? Data from different modalities may have different statistical properties, so a simple concatenation of representative features is not necessarily a good strategy. The so-called _latent spaces_ must be searched, and various strategies can be applied.  
In terms of data hybridization, there are three types: Primary, tardy and hybrid fusion.  
_Primary fusion_ makes a mixture of the depictions of every category prior to resolving the issue. _Tardy fusion_ combines the outcomes of the individual models.  
An example of this was shown in [24], in which structural and non-structural characteristics were selected from the fundus pictures, and, afterwards, they are combined in a late fusion strategy.  
_Hybrid fusion_ may, for example, contain images and text. The first study on this topic was presented in [31], in which CNN was combined with semantic information issued from medical reports to analyze OCT images. The fusion consisted of a hybridization of characteristics into a fully joined layer. An advance in the accuracy of retinal tissue imaging was reported.  
Additionally, one can hybridize visual and morphological data by integrating deep neural networks with morphological characteristics for glaucoma identification and categorization [32]. Image processing and morphological feature release can be provided separately and combined into one layer then passed to a fully joined layer.
## 5 The Biological Properties of Camphor
### Camphor as a Potential Skin Penetration Enhancer  
It has been suggested that terpenes, present in plant essential oils, are clinically acceptable skin penetration enhancers [87]. Previous studies also indicated menthol in combination with camphor enhanced the skin penetration of methyl salicylate and inhibited both the _in vivo_ and _in vitro_ hydrolysis of methyl salicate to salicylic acid [88]. The efficacy of some terpen on skin permeation of tea catechins and theophylline were systemically evaluated using a series of _in vitro_ and _in vivo_ methods [89]. It was found that all the evaluated terpen had significant effects on the (+)-catechin delivery relative to the control. The rank order of enhancement was \(\alpha\)-terpineol \(\geq\) menthone \(>\)linalool \(>\) 1,8-cineole \(>\) farnesol \(\geq\) fenchone \(>\) cymene \(\geq\) nerolidol \(>\) (+)-limonene \(>\) camphor. Camphor and fenchone showed the least enhancement amongst the oxygen-containing monoterpenes, which may be related to their bicyclic structure.  
[PERSON] _et al_. [90] reported the flux of carvedilol obtained from solutions containing camphor, transcutol, \(d\)-limonene, carvone, labrasol and menthol were 7.81, 7.26, 6.52, 5.91, 4.21 and 2.28 times higher respectively, than that observed with the control, using excised rat abdominal skin mounted in Franz diffusion cells. Camphor showed maximum permeation and basil oil (_Ocimum basilicum_) containing methyl chavicol, eugenol, linalool, camphor and methyl cinnamate showed potential _in vitro_ penetration enhancement of labetolol hydrochloride [91]. In a recent study, camphor was found to markedly prevent the permeation of benzocaine across the skin while promoting skin accumulation after 12 h [92].
## 3 Result and Discussion
### Load--Displacement Behaviour
#### 3.1.3 Triple-Cell Panels with Infill  
The load-displacement relationship of triple-cell panels is shown in Figure 7, reporting an average ultimate load of 98.15 kN. The ultimate load of the triple-cell specimen is also tabulated in Table 5. It is shown that the addition of any number of cells to the panels improves the load-carrying capacity of the floor slabs proportionally. This is mainly attributed to the overlap at the side of each cell. It is worth noting that the double- and triple-cell specimens have the same overall width of 600 mm, with a length of 1200 mm. The only difference is the additional partitioning, which led to a 35.6% increase in the load-carrying capacity. The influence of chopped basalt fibres in infill material for panels has been well established from the tests of single- and double-cell panels. Hence, the triple-cell panels were both tested without fibres.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Sample Type** & **Sample Designation** & **Infill Type** & **Ultimate Load (kN)** & **Displacement (mm)** \\ \hline Double cell & Double cell (Fibre) & \
\begin{tabular}{c} SCGC + BFRP + \\ Chopped Basalt fibre \\ SCGC + BFRP \\ \end{tabular} & 73.34 & 29.92 \\ Double cell & Double cell (No fibre) &
\begin{tabular}{c} SCGC + BFRP \\ \end{tabular} & 72.35 & 30.71 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Results of double-cell composite slabs.  
Figure 6: Load vs. displacement of double-cell infill panels.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample Type** & **Sample Designation** & **Infill Type** & **Ultimate Load (kN)** & **Displacement (mm)** \\ \hline Triple cell & Triple cell (No fibre) & \
\begin{tabular}{c} SCGC + BFRP \\ SCGC + BFRP \\ \end{tabular} & 103.77 & 35.35 \\ Triple cell & Triple cell (No fibre) &
\begin{tabular}{c} SCGC + BFRP \\ \end{tabular} & 92.53 & 27.77 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Results from triple-cell infill panels.
# Portuguese Grapevine Leaves: A Neglected By-Product with High Potential
## 2 Chemical Composition of Portuguese Grapevine Leaves
Eucalypt was tested in an oral long-term study with mice (up to 32 mg eucalypt, kg/day) and no treatment-related effects on body weight, food consumption, survival, weight of adrenals, kidneys, liver, lungs, or spleen, on the microscopic appearance of brain, lungs, liver and kidneys and on the tumor incidence were observed [121]. The toxicity of cedrol and cedrenol were evaluated by Bhatia et al. (2008) [122], and these compounds were considered very safe. \begin{table}
\begin{tabular}{c c c c} \hline
**Compound/Formula** & **Cultivar** & **Toxicity** & **Bioactivity** \\ \hline \multirow{4}{*}{Linalool C\({}_{10}\)H\({}_{18}\)O} & \multirow{4}{*}{Red TN, TR [123]} & Low toxicity [110]; maximum safe intake of 0.6 mg/kg/day [120] & Antimicrobial, anti-inflammatory, anticancer, neuroprotective, anxiolytic, antidepressant, anti-stress, hepatoprotective, and lung-protective [109; 110] \\  & & Low acute oral toxicity; no adverse effects in rodents at 0.6 doses lower than 210 mg/kg of 0.6 body weight/day with a 2-year exposure, or 335 mg/kg of body & Expectorant, appetite-stimulating, spasmolytic, anti-inflammatory, antiseptic, and antimicrobial [117] \\ \hline Cedrenol & Red TN, TR [123] & Rat LD50 oral: \(>\)5 g/kg & None found \\  & & & Rabbit LD50 skin: \(>\)5 g/kg [122] & None found \\ \hline \end{tabular}
\end{table} 
Table 4: Terpenoids and derivatives identified in Portuguese grapevine leaves. Chlorophyll and carotenoid pigments (Table 5) were identified and quantified in the red grape leaves of the cultivars Bastardo, Trincadeira, Tinta Barroca, and Castelao [77], where chlorophyll a or b (198.53-18.29 \(\upmu\)g/g) and auroxanthin (34.16-61.48 \(\upmu\)g/g) were the pigments with higher content. All the pigments identified in these grape leaf varieties exhibited antioxidant activity [134; 135; 136], but the majority of them also showed anti-inflammatory (chlorophyll, pheophyrin, _trans_-lutein, \(\beta\)-carotene, neoxanthin, violaxanthin, zeaxanthin) [137; 138; 139], anticancer/antiproliferative/chemoprereentive (chlorophyll, pheophyrin, _trans_-lutein, neoxanthin, violaxanthin, zeaxanthin) [140; 141], antimicrobial (pheophyrin, \(\beta\)-carotene) [142; 143], anti-obesity (chlorophyll, \(\beta\)-carotene) [136], antihyper-holesterolemic (pheophytin) [144], anti-hepatitis (pheophytin) [145], and/or neuroprotective (zeaxanthin) properties [146]. Chlorophyll and carotenoid pigments are nontoxic when ingested. They are used as food additives and dietary supplements due to their health benefits, including their antioxidant properties. There is no reported LD50 for chlorophyll in humans, indicating it has a very high safety threshold. Chlorophyll is generally non-irritating to the skin. However, concentrated forms, such as chlorophyll solutions, can sometimes cause mild
# Towards Bio-Hybrid Energy Harvesting in the Real-World:
## 3 Research Progress in Energy Harvesting from Microorganisms
### Classification of MFCs
#### 3.2.3 Aquatic MFCs
This category includes examples of improving power generation by the addition of silica colloid in rice paddy fields [123], cellulose in aquatic ponds [124], biomass like _Acorus calamus_ leaves and wheat straw [136], iron oxide [137] in anode burial sediments as well as an experimental test of adding biochars from coconut shells into a lab-scale sediment MFC [117]. This is due to the fact that inclusion of sediment ameliorations can reduce the usual high resistance values of mass and electron transport in soil [117]. Theoretically, aquatic MFC cathodes should be closer to an open water surface for the required oxygenation and the distance between the anode and the cathode should be small enough to keep the load resistance value small. Thus, for very deep configurations, sediment MFCs whose cathodes are submerged under water might not be optimal [138] and for such cases floating cathode MFCs or in short floating MFCs emerged as a viable solution. Floating cathodes have been used for open water MFCs. For example, a floating cathode system was developed that could be attached with a buoy and does not require fine adjustments for changing water depths [138]. A similar study [68] was performed with a floating, distributed electrode configuration that was not dependent on water column depth but was very sensitive to temperature changes. They have also been used in closed water systems like domestic wastewater treatment systems [70]. A floating biocathode system was found to be efficient for removing toxicity related to scarlet RR dye, a disperse dye extensively used for dyeing polyester fibers in textile industry [139], while generating power [140]. There are also reports of long-term monitoring of anoxic wastewater [69], biosensing of floating heavy metals [141] and harvesting energy with floating cathodes from food waste [142]. A series of floating MFC configurations were reported by [PERSON] et al. [143,144]. Applicability of the first configuration [143] was tested both in wastewater as well as in a natural water body. Performance of the second configuration [144] was tested for powering remote sensors and wireless data transmission. A 3D floating biocathode for overcoming the effect of oxygen depletion was tested in a lab with the sediment collected from river [145]. [PERSON] et al. [146] also reported a floating MFC with carbon felt-based anodes for facilitating anodic biofilm formation in uncontrolled environments and their system found to produce electricity efficiently by using seawater both as fuel and electrolyte.
# The Role of Correlation in the Performance of Massive MIMO Systems
## 6 Numerical Results  
In this section, we provide simulation and theoretical results, which describe the system performance in terms of the normalized MSE and SE for the RZF precoder. The results are presented for the ULA and URA with realistic configurations in order to emphasize the importance of our results in a realistic channel model. A summary of the simulation parameters, which are used in the performance evaluation, is provided in Table 1. It is worth noting that 10,000 channel realizations are considered for simulating the MSE and the spectral efficiency. The angle of departure of the UEs is distributed in the range of \(\theta_{u}\in[-\pi,+\pi)\). A dense urban scenario is assumed where the UEs are located within the range of 200 m.
# Study on Spray Characteristics and Breakup Mechanism of an SCR Injector
## 2 Numerical Models and Methods
### Model Description and Methods of Primary Breakup
#### 3.1.3 Inclination Angle of Liquid Jet  
The inclination angle of the liquid jet refers to the angle between the liquid jet and the axis of the nozzle. Figure 8 shows the comparison between the numerical simulation result and the experimental result of [PERSON] et al. [15] for the inclination angle at an inlet pressure of 0.5 MPa. The comparison shows that both are well consistent. In addition, the inclination angles were also measured at inlet pressures of 0.4 and 0.6 MPa. The results show that the inclination angle is insensitive to the inlet pressure, which is about 9.9\({}^{\circ}\) under all operating pressures. The inclination angle is related to the deviation of the connected domain from the axis of the nozzle, as shown in Figure 8c.  
Figure 6: Jet breakup regimes.  
Figure 7: Comparison of simulated mean breakup length with empirical curve.  
There are some differences between the experimental and simulated results of the breakup modes in Figure 8. The simulation failed to realize the phenomenon of liquid filament peeling in the experiment. The main reason is that the accuracy of the grid cannot be further improved due to the computing power. However, the simulation results have certain accuracy in comparison with the fragmentation form and key parameters of the liquid jet.
## 3 Scenario
### Physical Architecture  
To build a real environmental dataset, data were obtained by modelling observations from authentic temperature sensors in the Centre for Information and Communications Technology Research (CITIC) Data Center [8]. The data centre structure consists of three elements with sensors: the racks, the power strips (PDU), and the refrigeration machines (InRow). In the proposed scenario, only the sensors of the InRows will be considered. The other sensors in the data centre maintain static temperature values; therefore, they are not susceptible to analysis. Each InRow has control over four sensors: (a) unit entering fluid temperature (TFEU), which measures the temperature of the input fluid to the InRow unit, (b) unit leaving fluid temperature (TFSU), which measures the temperature of the fluid leaving the InRow back to the outside cooler, (c) unit return air temperature (TAR) unit, which measures the temperature of the air entering the InRow air conditioning unit of the closed hot corridor, and (d) unit supply air temperature (TAS), which measures the temperature of the air coming out of the InRow into the cold corridor.  
Based on how the CoAP protocol works, a client node can command each InRow node sending a CoAP packet. Every sensor is identified by a uniform resource identifier (URI) address (ex. www.inrow15.gal/1), where the resource indicates the InRow, and the number that follows the slash corresponds to its sensor: (1) TAS, (2) TAR, (3) TFEU, and (4) TFSU. Then, when performing virtualisation, there will be a virtual machine for each InRow, with the host machine acting as a client.
# Joint Power Charging and Routing in Wireless
## 2 System Model and Problem Formulation
### Problem Formulation  
In this section, we formulate our joint model, including both the charging efficiency and routing optimization.  
Figure 1: A mobile charger periodically visits each resident location once and charges those nodes in its charging radius.  
**Charging efficiency problem**: Charging efficiency is conventionally regarded as the ratio between the working time and charging schedule. On the basis of this criterion, the objective of this problem is to maximize the charging efficiency for the networks. This can be achieved by searching the optimal resident locations, the optimal routing tree and the optimal traveling path. This problem is formulated as  
\[\begin{array}{l}\max\frac{\tau_{\text{Int}}}{\tau}\\ s.t.(1)\sim(12)\end{array} \tag{13}\]  
We note that the constraints of Equations (1)-(7) are the routing constraints, whereas the constraints of Equations (8)-(12) are the charging constraints. Instinctively, both of these two optimization problems are in the form of a non-linear programming (NLP) problem, which are generally non-deterministic polynomial-time hardness (NP-hard) and cannot be solved by traditional optimization methods [30]. In the next section, we develop the bio-inspired GA to solve these two optimization problems.
# Multi-Objective Pareto Optimization of Tensile Membrane Architecture for Energy Harvesting
## 4 Discussion
TMA architects are recommended to consider an energy harvesting TMA to collect the wasted ambient energy. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multicolumn{2}{c}{**Region:**} & \multicolumn{5}{c}{**Shape Type**} \\ \cline{2-7}
**Inner Mongolia (Left)** & \multicolumn{2}{c}{**Hypar**} & \multicolumn{2}{c}{**Conic**} & \multicolumn{2}{c}{**Barrel Vault**} \\ \hline \multirow{3}{*}{Wind frequency} & High & 96.3\% & 97.5\% & 25.4\% & 21.3\% & 16.6\% & 19.2\% \\ \cline{2-7}  & Medium & 93.2\% & 97.6\% & 19.6\% & 32.9\% & 17.3\% & 24.8\% \\ \cline{2-7}  & Low & 91.1\% & 97.1\% & 25.4\% & 24.8\% & 26.8\% & 30.2\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Reduction rate of the acceleration value. Figure 7: Three existing TMAs. To understand the energy harvesting TMA, shape, orientation, material, and vibration-based energy harvesting have been confirmed by examining Pareto optimal solutions with Pareto front graphs. Conic and barrel vault types had dominant shapes that performed maximum energy efficiency through the whole material stiffness range. The hypar type also had a dominant shape but two non-dominant shapes consisted of identical height/edge lengths with the dominant shape performed in Texas. The orientation did not attract much attention because it varied all in the optimization result. Material stiffness influenced the electric generation differently in hypar when compared to conic and barrel vault types. Not only a reduction rate but also the degree of decrease or increase showed a similar pattern between conic and barrel vault. Low material stiffness is significantly essential, especially for the hypar, to maintain high energy efficiency.
## 1 Introduction  
### RC Frame with Curtailed Wall  
In the earthquake-prone area, the reinforced concrete (RC) shear wall is used together with the RC frame to increase the bearing capacity and rigidity against earthquakes. For low-rise to mid-rise buildings, it is appropriate to install the RC shear walls up to the top floor. Studies by [PERSON] et al. [1], [PERSON] et al. [2], [PERSON] et al. [3], and [PERSON] et al. [4] suggested that installing RC shear walls with the full height of the high-rise building is not effective. The reason is that the multi-story shear walls in a high-rise building are subjected to predominant bending deformation under earthquakes, and the inter-story deformation of the building increases in the upper floors.  
On the other hand, in order to utilize the shear walls, a design method was proposed using shear walls until a certain level of the building. This shear wall is generally called the curtailed wall. Studies by [PERSON] et al. [5], [PERSON] et al. [6, 7], and [PERSON] et al. [8, 9] suggested that the optimum height of the curtailed shear walls adopted for RC frames depends on several parameters such as the ratio of wall flexural rigidity to frame shear rigidity, axial stiffness coefficient, and the top deflection of the building. However, these studies [5, 6, 7, 8, 9] use only a linear approach without considering the nonlinear dynamic behavior of the building. Based on the results of nonlinear dynamic analysis of RC frames with curtailed shear walls, [PERSON] et al. [10] and [PERSON] [11] pointed out that the structure above the curtailed shear wall has a significant inter-story drift. It is a challenge to reduce this notable large inter-story drift.  
Therefore, the objective of this study is to propose a new structural system for the buildings with curtailed shear walls by installing buckling-restrained braces (BRBs) in the upper frame to reduce its deformation under earthquakes.
## 2 Materials and Methods
### SDS-PAGE and Immunoblot Analysis  
To examine time-dependent changes in the expression of stress-related proteins during exposure to increasing salinity levels, SDS-PAGE/immunoblot analysis was carried out according to well-established protocols. Briefly, homogenization of liver and gill samples for the total protein extraction was conducted in cold lysis buffer as described in [40]. Protein concentration was determined using the BioRad protein assay.  
Equivalent amounts of protein (80 \(\upmu\)g) were loaded and separated on 10% (_w/v_) acrylamide and 0.275% (_w/v_) bisacrylamide slab gels and then electrophoretically transferred to a nitrocellulose membrane (0.45 \(\upmu\)m, Schleicher & Schuell, Keene, NH, USA). Ponceau staining of the membranes was performed to assure equal protein loading and transfer efficiency. Following blocking of non-specific binding sites in 5% (_w/v_) non-fat milk in Tris-buffered saline/Tween (TBST) (20 mM Tris-HCl, 137 mM NaCl, 0.1% (_v/v_) Tween 20, pH 7.5), membranes were thoroughly rinsed in TBST (3 times, 5 min each) and subsequently incubated overnight at at 4 \({}^{\circ}\)C with the appropriate primary antibodies. The antibodies used were as follows: monoclonal rabbit anti-heat shock protein, 60 kDa (Cat. No. 12165, Cell Signaling, Beverly, MA, USA), monoclonal rabbit anti-phospho-p44/42 MAPK (Thr202/Tyr204) (Cat. No. 4370, Cell Signaling, Beverly, MA, USA) and polyclonal rabbit anti-phospho-p38 MAPK (Thr180/Tyr182) (Cat. No. 9211, Cell Signaling, Beverly, MA, USA). Thereafter, blots were thoroughly rinsed in TBST (3 times, 5 min each) and subjected to incubation for 1 h with horseradish peroxidase (HRP)-conjugated secondary antibody (anti-rabbit IgG, HRP-linked antibody (Cat. No. 7074, Cell Signaling, Beverly, MA, USA)). The immunoreactive bands were visualized using the enhanced chemiluminescence (ECL) detection system (Cat. No. 7003, Cell Signaling, Beverly, MA, USA) followed by fluorography on Fuji Medical X-ray films. Densitometric analysis using Image Studio Lite (LI-COR Biosciences, Lincoln, NE, USA) was employed for bands quantification.