esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Optimal One-Shot Estimators
### Second-Order Models  
The first-order solutions presented in Equations (15) and (16) are closed-form, computationally tractable, and relatively simple to implement. If the underlying behavior of the platform motion or the oscillator imperfections is not well modeled by a first-order Markov model, then this solution may underperform. In some cases, a second-order Markov model may better describe the behavior of these variables; so, we extend the derivation in the previous section to include an additional derivative on \(T\) and \(\tau\).  
Here, we assume that the relative propagation delay \(\tau\) and time offset \(T\) between two nodes \(A\) and \(B\) follow a second-order Markov model. During the two-way cycle \(\{(n-1),(n)\}\), the delay and offset in frame \((n)\) are expressed as functions of the previous frame \((n-1)\) as  
\[\tau^{\,(n)} =\tau^{\,(n-1)}+\hat{\tau}^{\,(n-1)}I_{A}^{\,(n-1)}+\frac{1}{2} \hat{\tau}^{\,(n-1)}I_{A}^{\,(n-1)^{2}}, \tag{17}\] \[T^{\,(n)} =T^{\,(n-1)}+\hat{\tau}^{\,(n-1)}I_{A}^{\,(n-1)}+\frac{1}{2}\hat{ \tau}^{\,(n-1)}I_{A}^{\,(n-1)^{2}}. \tag{18}\]  
Using Equations (17) and (18), we can substitute and simplify Equations (1) and (2) into a system of equations given by:  
\[\frac{1}{2}\,\alpha^{(n-1)}\,I_{A}^{\,(n-1)^{2}}-\beta^{(n-1)}\,I_{A}^{\,(n-1 )}+\gamma^{(n-1)}=0, \tag{19}\]  
where the scalar coefficients \(\alpha\), \(\beta\), and \(\gamma\) are given by:  
\[\alpha^{(n-1)}=\hat{T}^{\,(n-1)}, \tag{20}\] \[\beta^{(n-1)}=1-\hat{\tau}^{\,(n-1)},\] (21) \[\gamma^{(n-1)}=T^{\,(n-1)}+t_{B,Tx}^{\,(n)}-t_{A,Tx}^{\,(n-1)}. \tag{22}\]  
To solve this system, let  
\[\
u^{(n-1)}=\hat{\beta}^{(n-1)^{2}}-2\,\alpha^{(n-1)}\gamma^{(n-1)}. \tag{23}\]  
A tractable solution to this quadratic equation, for a reasonable set of parameters, is  
\[I_{A}^{\,2(n-1)}=\frac{\beta^{(n-1)}-\sqrt{\
u^{(n-1)}}}{\alpha^{(n-1)}}, \tag{24}\]  
which exists if and only if \(\
u^{(n-1)}\geq 0\). By substituting Equation (24), Equations (17) and (18) reduce to a system of linear equations in \(\tau^{\,(n-1)}\) and \(T^{\,(n-1)}\). It is not convenient to explicitly write out these estimates, so we rely on real-time solvers to perform the estimation.  
These first- and second-order estimators are referred to as \"one-shot\" estimators because they use a single set of measurements to generate a single set of estimates. These one-shot formulations are advantageous because they are relatively straightforward to understand and implement on an actual system, where accessing memory to perform iterative or memory-driven techniques is notoriously expensive. Unfortunately, these formulations are also sensitive to any channel impairments that may corrupt the measurements. This sensitivity can be mitigated by using any number of tracking filter approaches, which typically incur the aforementioned memory access penalties. In the following section, we derive an efficient extended Kalman filter that mitigates this penalty and still retains the near-optimal performance of the original one-shot estimators.
## 8 Discussion and Open Issues  
### Discussion  
The IoT enables expansion of smart cities by employing protocols at various levels. Application-layer protocols, physical and MAC layer protocols, and IPv6-based networking-layer protocols are designed in such a manner that certain task-oriented solutions are provided and enhanced. Although the developed and designed protocols are sufficient for incurring the current needs of services that the smart cities are intended to own, the  
protocols need certain enhancements for the expanding usage of data, as well as of data-driven IoT nodes.  
According to Gartner's speculation, the IoT will ultimately take 50% of the management share in industry. This means that the current Industry 2.0 and Industry 3.0 will be reshaped by the end of this decade, i.e., 2030. Thus, researchers should be curious not only about the increased demand for data communication channels, but they must also address the issues that arise with the generation of a large amount of data traffic in terms of its collection, storage, analyzing, and even discarding or replacing. Processing power will exponentially increase both at the end nodes and also at the management and data servers.  
As the work focuses on autonomous systems, application layer protocols are thoroughly examined for their use, as well as for the complications that may arise while dealing with large-scale data and wider network scenarios in smart cities. The sensing and data acquisition technologies that are used in smart cities require expandable solutions and relatively constant network throughput. Such networks also use adequate processing power and energy that must be addressed on the application level via certain constrained energy-based application protocols.  
Constrained nodes and environment, low-power and lossy networks, channel-aware and data-aware routing, and state-, energy-, and hop-count-based networking are explored. Various metrics of the stated ingredients are listed in the work that may undergo deep research to collaborate with the engineers of Industry 3.0, Industry 4.0, and smart cities.  
Finally, the addressing of a large quantity of nodes and on-time delivery of information is explored via encapsulation technique perspectives inside 6 Lo frontiers. The area of applications ranges from mobile healthcare, smart metering, enhancement to visual and audio communication, building automation, home automation and climate control, payment systems, secure communication for credit cards and NFC devices, network backhaul aggregation and cellular offloading, and finally industry management and automatic functionality. These areas and applications use heterogeneous modes of communication, while the data centers and logical networks stay unchanged in the majority of cases. For such scenarios, the physical network must cope with the increase in data over the network, as well as more interfaces of IoT nodes.
## 1 Introduction
Similarly, [PERSON] and [PERSON] [18] offered valuable insights into harmonic control and design criteria for harmonic suppression networks, but the calculations were complex and not widely applicable. Additionally, [PERSON] et al. [19] developed analytical expressions for 2 nd-harmonic tuning parallel to the load, although the comparative analysis was insufficient. Furthermore, the study did not adequately address the impact of the efficiency-bandwidth trade-off on performance metrics, highlighting the need for a more generalized approach to understanding the theoretical limits of \(Q_{s}\) across different topologies and harmonic termination strategies. In contrast, this work employs a computer-aided harmonic balance (HB) analysis to offer a generalized approach to finding the bounds. This work begins with mathematical modeling to derive the closed-form design equations for the Class-E RFPA, considering both infinite and finite DC feeds, as presented in Section 2. In the later sections, computer-aided analytical modeling is used to explore the impact of the series resonant circuit (\(L_{s}-C_{s}\)), tuned to the design frequency, which is critical for optimizing the performance of the RFPA. It introduces the key design parameter quality factor, \(Q_{s}\), which is a design parameter that affects Class-E performance and discusses its trade-offs with various performance metrics. Section 3 establishes a novel methodology for determining the bounds of \(Q_{s}\), (\(Q_{\min}<Q_{s}\leq Q_{\text{sat}}\)) through computer-aided HB simulations. This study further extends to a detailed investigation of harmonic termination and its impact on improving efficiency and bandwidth, along with performance metrics in Section 4. Based on these analytical equations, a novel methodology is proposed in Section 5 for designing optimal Class-E RFPAs. This approach aims to eliminate the need for time-consuming load-pull extraction and unnecessary circuit optimizations. This paper concludes by presenting simulated results and discussions that demonstrate the development of highly efficient Class-E RFPAs operating at 145 MHz, delivering 1 watt of output power. The results obtained underscore the robustness and effectiveness of the proposed methodology. The simulations were carried out using the nonlinear, large signal model of the CGH40010 transistor [20].
# Enhancing Communication Security in Drones Using QRNG in Frequency Hopping Spread Spectrum
## 3 Theoretical Background and Considerations  
In secure communication systems, protecting the integrity and confidentiality of transmitted data is crucial. FHSS is a technique used to achieve these goals by distributing the signal across a wider bandwidth, thereby making it more resistant to interference and eavesdropping. This section provides a detailed mathematical foundation for FHSS, explores the generation of frequency hopping sequences, and introduces the concept of using Randomness Processing Units to enhance security through true random sequences.
# Quantum Computing for Healthcare: A Review
## 4 Requirements of Quantum Computing for Healthcare
### Higher-Dimensional Quantum Communication  
Quantum information has been strongly influenced by modern technological paradigms. The literature shows that high-dimensional quantum states are of increasing interest, especially with respect to quantum communication. Hilbert space provides numerous benefits, such as large information capacity and noise resilience [77]. Moreover, the authors in [77] explored \"multiple photonic degrees of freedom for generating high-dimensional quantum states\", using both integrated photonics and bulk optics. Different channels were spun up for propagation of the quantum states, e.g., single-mode, free-space links, aquatic channels, and multicore and multimode fibers.
# Removal of Methylene Blue by Metal Oxides Supported by Oily Sludge Pyrolysis Residues
## 3 Results and Discussion
### Influence of Adsorption Conditions
#### 3.3.2 Effect of Contact Time  
Figure 10 shows the effect of the contact time on the removal of methylene blue. It can be seen that the removal effect of methylene blue by AC-CuO, AC-ZnO, and AC-TiO\({}_{2}\) increased rapidly at the initial stage. Additionally, with the prolongation of contact time, the removal effect slowed down and reached equilibrium after 90 min. Furthermore, comparing with CuO, ZnO, and TiO\({}_{2}\), AC-CuO, AC-ZnO, and AC-TiO\({}_{2}\) were able to improve the removal effect of methylene blue.  
At the initial stage of removal, there were many adsorption sites on the surface of AC-CuO, AC-ZnO, and AC-TiO\({}_{2}\), and the concentration of the methylene blue was high, the mass transfer driving force was large, and the removal rate was faster [41]. Additionally, with the extension of time, the active sites were gradually occupied by methylene blue, the number of empty active sites decreased, and the adsorption rate was relatively slow [42].  
Figure 9: The effect of (**a**) AC-CuO; (**b**) AC-ZnO; (**c**) AC-TiO\({}_{2}\) dosages on the removal of methylene blue (initial concentration = 5 mg/L, contact time = 60 min, temperature = 25 \(\pm\) 0.5 \({}^{\circ}\)C, initial Ph = 7.00).
## 3 Results and Discussion
### Analysis of OAV, Odor Characteristic and Key Compounds in Tea with Different Types
They were \(\beta\)-cyclocitral (263.33) >> \(\beta\)-ionone (94.29) >> 6-methyl-5-hepten-2-one (36.60) > (\(E\))-3-hexen-1-ol (21.71) > furural (16.38) > 1-pentanol (10.71) \(\approx\) methyl salicylate (10.25), as well as six compounds (<4.4). The OAVi of the first two compounds was much higher than that of other compounds, accounting for 75.78% of the OAVt. In terms of odor characteristics, the OAVt (471.88) of red tea was 202.19 for fruity, 74.14 for woody, 72.93 for green, 66.49 for floral, 35.47 for burnt, and 20.66 for fatty. The fruity odor (accounting for 42.85%) was the first feature of red tea, complemented by woody (accounting for 15.71%), green (accounting for 15.45%), and floral (accounting for 14.09%). These four odors (accounting for 88.10% of OAVt) formed the strong and abundant \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Compound**} & \multicolumn{2}{c}{**Ci**} & \multicolumn{6}{c}{**OAV-Splitting of Odor Characteristic**} \\ \cline{3-10}  & **(\(\mu\)g kg\({}^{-1}\))** & **OAVi** & \% & & & **OAVo** & **Floral** & **Burnt** & **Green** & **Fruity** & **Fatty** \\ \hline \(\beta\)-Cyclocitral & 0.79 \(\pm\) 0.09 & 263.33 & 55.80 & 26.33 & 0 & 0 & 52.67 & 184.33 & 0 \\ \(\beta\)-Ionone & 0.66 \(\pm\) 0.04 & 94.29 & 19.98 & 47.14 & 28.29 & 18.86 & 0 & 0 & 0 \\ \(6\)-Methyl-5-hepten-2-one & 1.83 \(\pm\) 0.23 & 36.60 & 7.76 & 0 & 25.62 & 0 & 0 & 10.98 & 0 \\ (\(E\))-3-Hexen-1-ol & 1.52 \(\pm\) 0.02 & 21.71 & 4.60 & 0 & 0 & 0 & 19.54 & 2.17 & 0 \\ Furfurral & 4.62 \(\pm\) 0.41 & 16.38 & 3.47 & 0 & 0 & 13.10 & 0 & 0 & 3.28 \\ \(1\)-Pentanol & 1.61 \(\pm\) 0.13 & 10.71 & 2.27 & 0 & 0 & 0 & 0 & 0 & 10.71 \\ Methyl salicylate & 0.41 \(\pm\) 0.05 & 10.25 & 2.17 & 0 & 7.17 & 3.08 & 0 & 0 & 0 \\ \(2\)(\(\mathrm{\SI}\))-Furanone & 0.26 \(\pm\) 0.02 & 4.33 & 0.92 & 0 & 0.43 & 0.43 & 0 & 2.60 & 0.87 \\ Acetic acid & 22.57 \(\pm\) 0.73 & 4.10 & 0.87 & 0 & 0 & 0 & 0 & 0.41 & 3.69 \\ Hexanal & 1.57 \(\pm\) 0.01 & 3.28 & 0.70 & 0.33 & 0 & 0 & 0.32 & 0.66 & 1.97 \\ Linalool & 1.40 \(\pm\) 0.10 & 2.80 & 0.59 & 0 & 2.80 & 0 & 0 & 0 & 0 \\ Phenethyl alcohol & 2.04 \(\pm\) 0.22 & 2.72 & 0.58 & 0.27 & 2.18 & 0 & 0.27 & 0 & 0 \\ Benzaldehyde & 4.83 \(\pm\) 0.71 & 1.38 & 0.29 & 0.07 & 0 & 0 & 0.13 & 1.04 & 0.14 \\ Total & 44.11 & 471.88 * & & 74.14 & 66.49 & 35.47 & 72.93 & 202.19 & 20.66 \\ \% ** & & & 15.71 & 14.09 & 7.52 & 15.45 & 42.85 & 4.38 \\ \hline \end{tabular} Note.: OAVi = Ci/Ti, where Ci is the content of compound i (\(\mu\)g kg\({}^{-1}\)), and Ti is the threshold value of compound i (\(\mu\)g kg\({}^{-1}\)). * OAVi = COAVi. ** \% is proportion of the each odor OAV accounting for OAVt.  
\end{table} 
Table 4: The content, OAVi and OAV-splitting of key aroma compounds in red tea.
# Visible-Light CDMA Communications Using Inverted Spread Sequences
## 3 MUI Cancellation Schemes with Inverted MPSC
### Shalaby's Scheme with Inverted MPSC  
In Shalaby's scheme with an inverted MPSC, one MPSC codeword in each group is used as a reference word in a way similar to that in the conventional Shalaby's scheme. The other \(q^{2}-q\) MPSC codewords are inverted and assigned to \(N_{\mathrm{max}}\) users, where \(N_{\mathrm{max}}=q^{2}-q\). An example of the codeword assignment for this Shalaby's scheme is shown in Table 4. We note that the reference words \(\mathbf{y}_{0}\), \(\mathbf{y}_{1}\), \(\mathbf{y}_{2}\), and \(\mathbf{y}_{3}\) are non-inverted codewords in Table 4.  
The \(k\)th user's encoder in this Shalaby's scheme is also illustrated by Figure 2a, although \(\mathbf{w}_{k,1}\) is replaced with its inverted codeword \(\mathbf{w}^{\prime}{}_{k,1}\) and \(\mathbf{w}_{k,0}\) is replaced with an all-one sequence having a length of \(q^{2}\). The multiplexed sequence of this Shalaby's scheme is equal to the sequence subtracting the multiplexed sequence of the conventional Shalaby's scheme from the constant-level sequence whose level is the maximum light intensity of \(N_{\mathrm{L}}\) light sources.  
The \(k\)th user's decoder is also represented as Figure 2b. At the decoder, Correlator 1 computes \(\Gamma^{\prime}{}_{1}\), which is the correlation between the received sequence \(\mathbf{r}^{\prime}\) and the non-inverted codeword \(\mathbf{w}_{k,1}\). Correlator 0 computes \(\Gamma^{\prime}{}_{0}\), which is the correlation between \(\mathbf{r}^{\prime}\) and \(\mathbf{y}_{i}\), where \(\mathbf{y}_{i}\) is the reference word in the same group with \(\mathbf{w}_{k,1}\). Thus, the Correlators 1 and 0 are exactly the same as those in the decoder for the conventional [PERSON]'s scheme. \(\Gamma^{\prime}{}_{1}\) and \(\Gamma^{\prime}{}_{0}\) are represented as follows:  
\[\Gamma^{\prime}{}_{1}=\Gamma\left(\dot{\mathbf{r}},\mathbf{w}_{k,1}\right), \tag{12}\]  
\[\Gamma^{\prime}{}_{0}=\Gamma\left(\dot{\mathbf{r}},\mathbf{y}_{i}\right)\,, \tag{13}\]  
where \(i=\lfloor k/(q-1)\rfloor\). Then, the decoder calculates the difference \(\Gamma^{\prime}{}_{0}-\Gamma^{\prime}{}_{1}\). If the value is greater than or equal to the threshold, the decision circuit outputs \(\hat{I}=1\). Otherwise, it outputs \(\hat{I}=0\). The ideal threshold is \(q/2\) when we suppose that the light intensity of each user's positive chip is 1.  
For an ideal link, \(\Gamma^{\prime}{}_{1}\) and \(\Gamma^{\prime}{}_{0}\) are equal to \(qN_{\mathrm{L}}-\Gamma_{1}\) and \(qN_{\mathrm{L}}-\Gamma_{0}\), respectively, where \(\Gamma_{1}\), \(\Gamma_{0}\), \(\Gamma^{\prime}{}_{1}\), and \(\Gamma^{\prime}{}_{0}\) are given by Equations (6), (7), (12), and (13), respectively. Therefore, the difference \(\Gamma^{\prime}{}_{0}-\Gamma^{\prime}{}_{1}\) is equal to \(\Gamma_{1}-\Gamma_{0}\) in the conventional Shalaby's scheme. This means that [PERSON]'s scheme with an inverted MPSC cancels MUI completely if the receiver can estimate the received light intensity of a single positive chip correctly and that its decision distance is \(q\).
## 3 Characterization Results  
### Spectral Characterization  
The spectral characterization of the monochromator was performed using the discrete emission lines in the 12.4-50 eV energy range of a gas-discharge lamp (filled with different noble gases--He, Ne, and Ar). A vacuum level of \(9\times 10^{-6}\) mbar was maintained inside the monochromator chamber, even when the gas-discharge lamp was turned on. All the measurements were performed using a cooled CCD camera detector (Princeton Instruments PIXIS) with low read-out noise (\(3e^{-}\) rms), placed in the image plane, i.e., with the exit slit completely open, in a spectrometer fashion. The CCD format was \(1340\times 1300\) pixels, with \(20\) um \(\times\)\(20\) um pixel size, determining the resolution of the detection. The evaluation of the tangential defocusing aberration was performed by a Gaussian interpolation of the acquired CCD spectral image, before and after a variation of \(k\) from its nominal position (associated to a specific photon energy) of \(0.2^{\circ}\) and \(0.4^{\circ}\). In Figures 4 and 5, the emission lines of He I (\(1\)s\({}^{2}\to 1\)s\(2\)p) at 21.22 eV and He II (\(1\)s \(\to 2\)p) at 40.82 eV are shown.  
Figure 4: Line profile for \(k\) variation of \(0.2^{\circ}\) and \(0.4^{\circ}\) at 21.22 eV, \(G_{1}\) grating.  
Figure 3: Comparison between the subtended angles for focusing condition and maximum efficiency.  
By applying Equation (6), we calculate an image width of 58 \(\upmu\)m with a 35 \(\upmu\)m entrance slit in the entire spectral range. The expression accounts for only the entrance slit magnification and not for residual aberrations. The typical width of the spectral lines at the optimum angle is in the range 60-65 \(\upmu\)m, confirming the correction of defocusing and coma given by the design. The residual mismatch between theoretical and measured values is mainly due to the uncertainty on the width of the entrance slit.
## 2 Materials and Methods
### Other Measurements  
For measuring pigment contents, leaves were also collected in parallel with the SIF measurements. Three leaves were clipped when the spectral measurements were collected and preserved in liquid-nitrogen before the pigment extraction. Chlorophyll a and b (Chl a and Chl b) and the total carotenoid content (Car) were determined in the acetone extracts, and the absorbances were read at 480, 645, and 663 nm, respectively, on a spectrophotometer [36; 37]. The coefficients in [PERSON] et al. (1983) were used to calculate the pigment concentration [36].  
The leaf area index (LAI) of each crop was also measured using a Plant Canopy Analyzer (LAI-2200C, LI-COR, Inc.) in the late afternoon when the sun was near the horizon [18]. Following the instruction manual for row crops, ground measurements were made along diagonal transects between the rows [38]. At least three repeats were made for each measurement, with at least six above the canopy and seven below the canopy readings. For the below canopy measurements, the instrument was held about 5 cm above the background soil. A 270\({}^{\circ}\) view cap was used to shield the sensor from the operator. In the present study, three LAI measurements were obtained for each crop and were averaged to represent the LAI of each crop.  
To analyze the impact of air temperature to the variation of crop photosynthesis, the hourly air temperature and short-wave radiance of solar were collected in a meteorological station, which was 300 m away from our experimental site.
# T-Type Vertical Wall for Decoupling and Pattern Correction of Patch Antenna
## 3 Result Analyses
### Current Distribution Comparison  
The current distribution is compared before and after using the proposed decoupling structure, as shown in Figure 10. Figure 10a indicates the current distribution of the no-decoupling structure, while Figure 10b shows the distribution after using the proposed technique. This means that the coupling is reduced significantly by the T-type metal wall, and the current concentrates on the vertical strip of the T-type metal.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Literature** & **Placement Orientation** & **Decoupling Technique** & **Center Frequency** & **Edge-to-Edge Spacing** & **Tilt** \\ \hline
[3] & E-plane & Dielectric Block & 10.00 GHz & 0.027\(\lambda_{0}\) & \(\sim\)10\({}^{\circ}\) \\
[10] & H-plane & Three Interdigital Lines & 5.80 GHz & 0.07\(\lambda_{0}\) & \(\sim\)30\({}^{\circ}\) \\
[11] & E-plane & Meander-line Slots & 5.00 GHz & 0.06\(\lambda_{g}\) & \(\sim\)30\({}^{\circ}\) \\
[13] & E-plane & Ground Slot & 5.80 GHz & 0.031\(\lambda_{0}\) & \(\sim\)45\({}^{\circ}\) \\
[14] & E-plane & Slotted Ground & 4.00 GHz & 0.037\(\lambda_{0}\) & \(\sim\)30\({}^{\circ}\) \\
[15] & H-plane & Metal Stub \& Slotted Ground & 5.50 GHz & 0.018\(\lambda_{0}\) & \(\sim\)25\({}^{\circ}\) \\
[16] & H-plane & Asymmetrical Coplanar Strip Wall & 5.80 GHz & 0.03\(\lambda_{0}\) & \(\sim\)30\({}^{\circ}\) \\
[18] & H-plane & Half-wave Microstrip Line \& & 3.16 GHz & 0.027\(\lambda_{0}\) & \(\sim\)30\({}^{\circ}\) \\ Our Work & H-plane & T-type Metal Wall & 5.80 GHz & 0.05\(\lambda_{0}\) & 0\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparisons with other works.  
Figure 10: Current distributions before (**a**) and after (**b**) using the proposed structure.
# Clinical Applications of Optical Coherence Angiography Imaging in Ocular Vascular Diseases
## 5 Ocular Ischemic Syndrome
### Current Imaging Techniques for Ocular Ischaemic Syndrome  
FA is useful in establishing the diagnosis of OIS. OIS eyes frequently have prolonged retina arteriovenous transit time and often have patchy or delayed choroidal filling. Staining of retinal vessels occurs and is more pronounced for arteries in OIS, where conversely, in CRVO the staining of veins is more pronounced and in DR no vessel staining is usually seen. Vessel staining in OIS can also be associated with leakage. Occasionally, a well-demarcated leading edge of dye and macular edema can be observed. ICG is also useful for evaluating OIS and often shows a prolonged arm-to-choroid time prolonged intrachroidal circulation time. Areas of choroidal hypoperfusion, filling defects, and slow filling of watershed zones of the choroid and choriocapillaris can also be observed [72].  
A prominent middle limiting membrane sign on SD-OCT can be appreciated in patients with OIS. This segment is found between the outer plexiform layer and ganglion cell layer and is accentuated in peri-venous areas. It is likely that this region represents the location with the largest deficit of oxygen.  
Figure 7: A case of right chronic central retinal artery occlusion. (**A**): Wide-field en face structural OCT demonstrating the presence of retinal vessels. However, the en face OCTA (**B**) shows no flow signal and the cross-sectional OCTA (**C**) shows that the retinal layers (bounded by red lines) are devoid of flow signal.  
However, in CRAO, this sign is overshadowed by the increased reflectivity and thickness of the inner retinal layers [67].