esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 PDT in Veterinary Oncology
### Other Tumors
Changes included necrosis and a 25% volume reduction in cancerous nodules of the partially treated area [126]. PDT protocols used to treat other veterinary neoplasms are presented in Table 5.  
Legend: 5-ALA, 5-aminolevulinic acid; BPD-MA, benzoporphyrin derivative monoacid ring A; HPD, hematoporphyrin derivative; iv; intravenous PS, photosensitizer; WST09, palladium-bacteriopheophorbide; ZnPCs\({}_{4}\) zinc phthalocyanine tetrasulfonate. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Ref.** & **Neoplasm** & **Patients** & **PDT Protocol** & **Main Results** \\ \hline \multirow{2}{*}{[79]} & Eosinophilic granuloma & \multirow{2}{*}{1 Cat} & **PS:** HPD, 2.5 mg/kg, iv & \multirow{2}{*}{\(\bullet\)} & The patient showed a complete response at the last follow-up (6 months) \\ \cline{3-5}  & Eosinophilic granuloma & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \hline \multirow{3}{*}{[79]} & Sebaceous glands adenoma & \multirow{2}{*}{1 Dog} & **PS:** HPD, 2.5 mg/kg, iv & \multirow{2}{*}{\(\bullet\)} & The patient showed a complete response at the last follow-up (9 months) \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \hline \multirow{3}{*}{[71]} & \multirow{3}{*}{Mammary gland tumor} & \multirow{2}{*}{2 Cats} & **PS:** 5-ALA, 40 mg/kg, oral & \multirow{3}{*}{\(\bullet\)} & \multirow{3}{*}{Stable disease and partial response} \\  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \hline \multirow{3}{*}{[71]} & Inflammatory mammary gland tumor & \multirow{2}{*}{1 Dog} & **PS:** 5-ALA, 40 mg/kg, oral & \multirow{3}{*}{\(\bullet\)} & \multirow{3}{*}{Partial response} \\  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \hline \multirow{3}{*}{[71]} & \multirow{3}{*}{Myeloma} & \multirow{2}{*}{1 Dog} & **PS:** 5-ALA, 40 mg/kg, oral & \multirow{3}{*}{\(\bullet\)} & \multirow{3}{*}{Progressive disease} \\  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \hline \multirow{3}{*}{[105]} & Ameloblastoma & \multirow{3}{*}{2 Dogs} & **PS:** BPD-MA, 0.5 mg/mg, iv & \multirow{3}{*}{\(\bullet\)} & PDT used as anti-angiogenic \\  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & Tumor necrosis at the treatment site was observed \\ \hline \multirow{3}{*}{[84]} & \multirow{3}{*}{Viral papilloma} & \multirow{3}{*}{1 Dog} & **PS:** ZnPCs\({}_{4}\), 4 mg/kg, iv & \multirow{3}{*}{\(\bullet\)} & \multirow{3}{*}{Progressive disease} \\  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \hline \multirow{3}{*}{[126]} & Spontaneous advanced primary prostate cancer & \multirow{3}{*}{1 Dog} & **PS:** WST09, 2.0 mg/kg, iv & \multirow{3}{*}{\(\bullet\)} & \multirow{3}{*}{\(\bullet\)} & \multirow{3}{*}{\(\bullet\)} \\  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \cline{3-5}  & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Clinical studies on PDT in animals with other tumors.
## 3 Experiment
### Experimental Parameter Settings  
The experimental platform utilized a server equipped with an Intel i9-12900k CPU (Intel Corporation, Santa Clara, CA, USA) and Nvidia RTX 3080 Ti GPU (Nvidia Corporation, Santa Clara, CA, USA). The proposed algorithm was implemented using the Adam optimizer in PyTorch. For training on the DBP15K dataset, the number of epochs was set to 500, with a learning rate of 0.001. To ensure fair comparison, the experimental setup employed the same training/testing split as common methods: 30% of pre-aligned entities were used for training, while the remaining 70% of anchor links were used for testing, with 20% of training entity pairs reserved for validation. To demonstrate the model's stability, the visual encoder was set to ResNet-152 with visual feature dimensions of 2048. Each experiment was conducted 10 times, and the results were averaged to reduce randomness.  
In the experiments, the effectiveness of multimodal entity alignment was evaluated as an indicator of the proposed model's performance. Specifically, three common metrics were employed: the average percentage of triplets ranked 1 in the test samples (Hits@1), the average percentage of triplets ranked below 10 in the test samples (Hits@10), and the mean reciprocal rank (MRR).  
The experimental parameters, including regularization parameters and network model parameters, were adjusted within given ranges to maximize classification accuracy. To achieve this, a 10-fold cross-validation was performed on the training set to determine parameter combinations for different methods. Additionally, feature dimensionality was identified as a key parameter affecting the quality of the final learned feature representations. Therefore, the optimal feature dimensionality was determined by testing values ranging from 100 to 500 at intervals of 5, based on the best classification performance on the training set.
## 4 Discussion
Moreover, previous studies have confirmed that the larger the thigh muscles, including the quadriceps and hamstrings, the better the performance of sprinters in events such as the 100 m sprint [1; 3; 7]. This suggests that not only structural differences but also differences in muscle mass should be considered. However, since this study measured lower limb length using anthropometric methods, the muscle mass of the athletes' lower limbs was not assessed. In this study, the analysis of group differences revealed that the correlation between tibia length and agility (through the 10 m shuttle run-sprint and turn test) was stronger in the HD group (r = \(-\)0.455, \(p\) = 0.001) compared to the other groups (LD: r = 0.117, \(p\) = 0.497, MD: r = \(-\)0.028, \(p\) = 0.808). This suggests that the HD group, which consists of athletes from sports requiring frequent forward-backward directional changes (such as soccer, hockey, and handball), may benefit from longer tibia in terms of agility during offensive and defensive maneuvers. In addition, for another agility factor (side-step test--lateral direction change), the correlation between femur length and performance was significantly higher in the MD group (r = 0.405, \(p\) = 0.001) compared to the other groups (LD: r = 0.086, \(p\) = 0.593, HD: r = 0.014, \(p\) = 0.855). This suggests that athletes in sports that involve lateral move ments, such as tennis and baseball, may benefit from longer femora for improved agility during lateral direction changes. In the analysis of group differences, the correlation between femur length and performance in muscular power or explosiveness (standing long jump) was significantly higher in the MD group (r = 0.453, \(p=0.001\)) compared to the other groups (LD: r = 0.075, \(p=0.642\), HD: r = 0.047, \(p=0.523\)). This suggests that athletes in sports requiring explosive, short bursts of performance, such as sprinting, baseball, and fencing, may benefit from longer femora for more effective power generation. In the LD group, no significant correlations were observed with any physical performance factors. This lack of correlation is likely due to the nature of the sports with lower activity levels (such as shooting, archery, and diving), which may have a limited impact on the physical attributes measured in this study. In addition to physical structure, a combination of performance indicators such as speed, strength, endurance, agility, and flexibility can have a positive impact on an athlete's performance. Physical characteristics vary according to physiological abilities, which significantly influence athletic performance. To achieve satisfactory results, physical performance is crucial in the context of sports [37]. Future research should focus on the notable correlation between leg length and physical attributes such as power and agility in moderate dynamic sports groups, including baseball, fencing, sprinting, tennis, and wrestling. It would be highly meaningful to investigate the biomechanical and physiological mechanisms underlying this correlation through in-depth measures.
## 1 Introduction
### Main Contributions  
In this paper, we introduce a new hybrid opportunistic scheduling method that achieves the optimal sum DoF of the full-duplex system addressed in Section 1.1, i.e., the full-duplex system consisting of a \(2M\)-antenna full-duplex BSs and \(N\) single-antenna half-duplex MSs, under an improved user scaling law. We consider a practical scenario that the system operates in the time-divisionduplexing (TDD) mode and the effective channel gain information is only available at the transmitter via offline pilot signaling sent during the scheduling period. In such a partial CSIT scenario, how to achieve the optimal DoF is a challenging task, especially for full-duplex systems since, with the existing opportunistic scheduling methods, it is not straightforward to effectively manage the inter-terminal interference that does not appear in half-duplex systems. Under the partial _CSIT_ assumption, our method combines the following beamforming and scheduling strategies: (i) downlink random beamforming at the BS, (ii) opportunistic scheduling at both the downlink MSs and uplink MSs, and (iii) uplink ZF beamforming at the BS. More precisely, a set of downlink MSs is selected in the sense that the downlink interference is minimized, and a set of uplink MSs is selected in the sense that the MS-to-MS interference is minimized by virtue of utilizing the channel reciprocity of the TDD system, which is the most distinguishable feature compared to the scheduling method in [26]. We remark that our method only requires each MS to feed back \(M\) real values along with the corresponding beamforming vector indices, which is significantly less than the full CSIT case. As our main result, when \(M\) uplink and \(M\) downlink MSs are served through our full-duplex system with hybrid opportunistic scheduling, it is shown that the sum DoF of \(2M\) is achievable provided that the number of MSs, \(N\), scales faster than SNR\({}^{M}\). That is, the full DoF is guaranteed under an improved user scaling law without any extra CSI as it was shown in [26] that \(N\) need to scale faster than SNR\({}^{2M-1}\) to guarantee the DoF optimality. The interference decaying rate, defined as the average decaying rate of the total amount of received interference and/or generating interference with respect to the number of MSs, is also analyzed asymptotically. In addition, numerical results are provided to validate our analysis. It was examined that the proposed hybrid opportunistic scheduling outperforms the state-of-the-art method in [26] in terms of achievable sum-rates.  
Our main contributions are four-fold and summarized as follows:  
* A new hybrid opportunistic scheduling method is presented in the sense that the scheduling role between downlink MSs and uplink MSs is well-balanced.
* The DoF and user scaling law are newly derived by analyzing the distributions of our scheduling metrics.
* The average interference decaying rate is also analyzed.
* Numerical examples are provided to not only validate our analysis but also show superiority of the proposed method over the state-of-the-art method.
# Designed Circularly Polarized Two-Port Microstrip MIMO Antenna for WLAN Applications
## 6 MIMO Antenna System Parameters
### Envelope Correlation Coefficient  
The proposed antenna diversity presentation is analyzed in terms of ECC, to ensure good MIMO performance. Isolation and correlation of communication channels can be observed from envelope correlation coefficient (ECC) value. ECC can be derived from the radiation pattern of all the antennas in a multi-antenna system that shows how much the radiation pattern of each antenna affects the radiation pattern of other antenna. Having a low ECC is very important for the \"robustness\" of the proposed MIMO antenna [48]. The radiation pattern can be used to calculate it for a two-port MIMO antenna, as shown in Equation (1) [49].  
\[\rho e=\frac{\mid\int\int_{4\pi}[\vec{F}_{1}(\theta,\phi)\times\vec{F}_{2}( \theta,\phi)d\Omega]\mid^{2}}{\mid\int\int_{4\pi}[\vec{F}_{1}(\theta,\phi)]\mid^ {2}d\Omega\mid\int\int_{4\pi}[\vec{F}_{2}(\theta,\phi)]\mid^{2}d\Omega} \tag{1}\]  
The ECC (\(\rho e\)) is computed from the far-field radiation pattern, as in Equation (1). Where \(\vec{F}_{1}(\theta,\phi)\) is the MIMO array far field property when port-1 is excited. The solid angle is denoted by \(\Omega\). From Figure (a)a, given a simulated and measured ECC of less than 0.001  
Figure 14: Simulated and measured radiation patterns when port-1 is excited and port-2 is matched. (**a**) E-plane. (**b**) H-plane.  
Figure 15: Simulated and measured radiation pattern that occur when port-1 is excited and port-2 is terminated. (**a**) E-plane LHCP and RHCP. (**b**) H-plane LHCP and RHCP.  
at over the entire frequency range, it shows a low correlation between the two antennas. For a better MIMO antenna, ECC should have less than 0.5 [50].
## 3 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**Samples**} & \multirow{2}{*}{**Process**} & \multicolumn{1}{c}{**Hue Angle**} & \multicolumn{1}{c}{**Color**} & \multirow{2}{*}{**Saturation**} \\ \multicolumn{2}{c}{} & \multirow{2}{*}{Hornbeam} & Before drying & 73.4 & 28.9 & 38.2 \\  & & After drying & 72.7 & 22.1 & 31.4 \\ \cline{2-5} \multirow{2}{*}{**60 \({}^{\circ}\)C**} & \multirow{2}{*}{Maple} & Before drying & 69.0 & 35.3 & 47.2 \\  & & After drying & 65.5 & 30.0 & 43.5 \\ \hline \multirow{4}{*}{**120 \({}^{\circ}\)C**} & \multirow{2}{*}{Hornbeam} & Before drying & 71.7 & 27.7 & 37.2 \\  & & After drying & 71.0 & 26.8 & 40.5 \\ \cline{1-1} \cline{2-5} \multirow{2}{*}{**120 \({}^{\circ}\)C**} & \multirow{2}{*}{Maple} & Before drying & 72.6 & 29.2 & 36.2 \\  & & After drying & 64.5 & 28.3 & 44.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Calculated values of hue angle, color saturation and saturation in the hot-air drying (60 \({}^{\circ}\)C) and high-temperature drying (120 \({}^{\circ}\)C) processes.
## 4 Simulation Results and Discussion
### Simulation Parameter Setting and Criteria of the Control Performance
Similarly, the noise reduction in target area 1 \(NR_{e\_area1}\), the noise reduction in target area 2 \(NR_{e\_area2}\), and the noise reduction in the far-field observation area \(NR_{ob\_far}\) can be computed as:  
\[NR_{e\_area1}=10\log\left(\frac{\left\|\textbf{P}_{e\_area1\_ANCoff}\right\|_{ 2}^{2}}{\left\|\textbf{P}_{e\_area1\_ANCon}\right\|_{2}^{2}}\right) \tag{12}\]  
\[NR_{e\_area2}=10\log\left(\frac{\left\|\textbf{P}_{e\_area2\_ANCoff}\right\|_{ 2}^{2}}{\left\|\textbf{P}_{e\_area2\_ANCon}\right\|_{2}^{2}}\right) \tag{13}\]  
\[NR_{ob\_far}=10\log\left(\frac{\left\|\textbf{P}_{ob\_far}\_ANCoff}{\left\| \textbf{P}_{ob\_far}\_ANCon}\right\|_{2}^{2}\right) \tag{14}\]  
where \(NR_{e\_area1}\) is the ratio of the squared sum of the sound pressure before and after noise control for the 169 error points in target area 1, and \(NR_{e\_area2}\) is the ratio of the squared sum of the sound pressure before and after noise control for the 325 error points in target area 2. \(NR_{ob\_far}\) is the ratio of the squared sum of the sound pressure before and after noise control for 360 observing points in the far-field observation area.
## 3 Proposed System
### Detailed Operation of System  
Figure 7 shows the detailed operations of the system.  
First, the certification body executes the preparation step. The certification authority generates security parameter k to support delegation of authority and then follows the key generation steps to communicate with the policy manager and the delegator. The certification body and policy manager can be one administrative body with a trusted third party.  
Privilege delegation uses the transmitted security parameters and the session key to provide the policy administrator with settings for encryption. Then, a random value is generated and sent to the authority auditor (the proxy). It then provides the delegate with the value set using the session key.  
A permissions examiner generates a random value and a temporary value based on this and goes through the confirmation process with the policy administrator. The policy administrator uses the random value transmitted from the proxy and the information that authenticates the authority delegation to generate the encrypted data to be passed and sends the encrypted data to the delegate.  
Finally, the delegate uses a random value as the session key that allows the policy administrator to authenticate the preissued delegator with the data encrypted and sent on behalf of the delegate. It can be decrypted. The detailed operation process has been simplified into seven stages (preparation, key generation, encryption, delegation, secondary delegation, secondary decryption, and decryption) as follows.
## 3 Results and Discussion
### Characterization of Non-Volatile Metabolites of FAA Tea at Four Harvest Times  
#### 3.3.1 Comprehensive Analysis of Non-Volatile Metabolites in FAA Tea  
A total of 45,982 peaks, comprising 23,407 negative ion peaks and 22,575 positive ion peaks, were detected in FAA tea across four different harvest periods. Specifically, a total of four sample groups with three biological replicates were explored in this study. Ion peaks with inaccurate characterizations were excluded based on reference thresholds, resulting in the detection of 8627 metabolites, including 5009 in positive mode and 3618 in negative mode. Of these, 509 compounds were identified at the secondary level.
# Exploring the Evolution of Drought Characteristics in Balochistan, Pakistan
## 3 Results  
### Drought Regionalization  
The SKATER technique applied to Balochistan created six contiguous zones based on the similarity of 24-month SPEI time series (Figure 4). The zones produced reflect the climatology of this region.  
Figure 4: Homogeneous zones produced after running Spatial “K”luster Analysis using Tree Edge Removal (SKATER).
## 3 Constellation Construction  
### Construction of the Satellite  
The HN-1 01/02 and WC-1 01/02 satellites are integrated micro-satellites equipped with Earth observation and AIS information acquisition capabilities. They can be utilized for remote sensing and collecting ship information, such as speed, direction, and position.  
In particular, HN-1 01 features a dual-line array wide camera with a spatial resolution of 5 m and a swath width of 110 km, enabling autonomous image processing for efficient ship detection and information transmission over large ocean areas. Moreover, HN-1 02 has a spatial resolution of 1.5 m and features both push-scan and video imaging working modes (12 km swath width for the push-scan working mode and 5.8 km \(\times\) 3.3 km swath width for the video imaging working mode). The primary application of HN-1 02 is to monitor land and ocean properties as well as to retrieve ship information.  
WC-1 01 and WC-1 02 are equipped with a panchromatic plus eight-band wide imaging camera, characterized by a spatial resolution of 5 m and a swath width of 115 km. Both satellites share identical technical specifications, making them suitable for networked observations.  
The technical specifications of the HN-1 01/02 and WC-1 01/02 satellites are outlined in Table 1.
## 2 Experiments
### Preparation of the Anchor and Beam Specimens  
The concrete breakout failure of an anchor installed in concrete is strongly associated with the tensile performance of concrete. Steel fibers mixed in concrete have a great influence on the generation and growth of concrete cracks. Thus, to investigate the effect of steel fibers on the concrete edge breakout failure of an anchor, the anchor specimens of SFRC with fiber volume percentages of 0.33, 0.67, and 1.00%, which correspond to approximately 26, 54, and 80 kg/m\({}^{3}\), respectively, were designed, as shown in Table 2. The steel anchor used in the study was an M30-S45C with a diameter of 30 mm and yield strength of 450 MPa. One steel anchor was installed in the center of each edge of a concrete block. Thus, four anchor specimens per test variable were prepared in one concrete block. One concrete  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Cement** & **Fine Aggregate** & **Coarse Aggregate** & **Fly Ash** & **Superplasticizer** \\ \hline
279 & 931 & 929 & 31 & 1.17 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Mix proportion of concrete (kg/m\({}^{3}\)).  
block without steel fibers was also prepared, and a total of 16 anchor specimens were fabricated (four anchors in one concrete block per test variable).  
To induce the concrete edge breakout failure of an anchor, the edge distance of the anchor was defined as 75 mm (=2.5 times the diameter of the anchor). The embedded depth of the anchor in concrete was 240 mm, which was 8 times the diameter of the anchor. Thus, the concrete block was designed to have a square top surface with a length of 500 mm so that the inclined cracks generated on the surface of the block due to the shear load could not affect the other edge faces. The height of the block was defined as 680 mm in consideration of the embedded depth of 240 mm of the anchor. Figure 1 shows the dimensions of the concrete block and anchor specimens. The concrete blocks with steel anchors were cured in air for around 90 days.  
Beam specimens were also manufactured to assess the tensile capacity of the SFRC according to the ASTM C 1609 standard [35]. The dimensions of the beam specimens were \(150\times 150\times 500\) mm\({}^{3}\). The beam specimens were cast at the same time as the anchor specimens using the same concrete mixture and fiber volume fractions. Control beam specimens without steel fibers were also prepared. The same number of beam specimens as anchor specimens was prepared to ensure the reliability of the experiments (four specimens per fiber volume fraction). Thus, 16 beam specimens were manufactured in total. After de-molding, the beam specimens were cured in air under the same conditions as the anchor specimens.