esa-sceva/satcom-chunk-collection huggingface dataset:
# Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping
## 6 Approximate Complexity Discussion
### Computational Complexity
We see that there is a computational complexity vs. required storage tradeoff between ESS (and (Algorithm 1 in [23])) and SM. ESS requires larger storage but can be implemented with a smaller complexity, and only demands additions and subtractions. On the other hand, SM can be realized with a smaller storage, however requires many multiplications and divisions. In fact, by modifying the corresponding shaping and deshaping algorithms, it is also possible to adjust the balance between computational complexity and required storage as explained in (Section 4.3.4 in [10]), i.e., operate between the ESS and SM clusters in Figure 12. Furthermore, there is also a difference in computational complexities of ESS and (Algorithm 1 in [23]). An initial step is required in (Algorithm 1 in [23]) where the \(n\)-shell that the corresponding sequence is located on is determined. This step requires at most \(L-1\) additions and comparisons. Finally, Figure 12 also shows that BP AC-CCDM can be implemented with moderate computational complexity and minimal storage. Furthermore, these requirements do not heavily depend on blocklength \(n\). Therefore, for large \(n\) where its rate losses are small, and for applications for which high serialism of AC is not problematic, AC-CCDM is an effective and low-complexity choice as a shaping algorithm.
## 3 Control Algorithm Design  
### Sun-Oriented Spin-Stabilized Attitude Control  
For the ADCS shown in Figure 1 with the simplest configuration, the sketch of the attitude control method proposed in this paper is shown in Figure 2, which can be used as the safe mode of the satellite.  
The TAM installed on the main body of the satellite obtains the measured value of the geomagnetic field. Then, the output of the TAM is used by the rate filter to estimate the 3-axis angular rates of the satellite. According to the measurement data of the geomagnetic field and the estimated value of the satellite's 3-axis angular rates, the attitude controller calculates the control torque and transforms it into the control commands of the 3-axis MTQs. In addition, the measurement output of the sun sensor is also used to calculate the control torque. Finally, the magnetic torquers execute the generated control commands and then control the satellite to achieve the sun-oriented spin-stabilized attitude.
## 4 Experimental Results and Discussion
### Performance of Different Feature Extractors  
VGG16 [1] and ResNet101 [2] were used as feature extractors for the Faster R-CNN [5]. In this section, we present the mAP measurements, training and validation loss, and visual comparisons for these two architectures.  
As presented in Table 2, the mAP values of the models with VGG16 [1] and ResNet101 [2] as feature extractors were 0.7535 and 0.8497, respectively. The mAP values in the brackets of Table 2 are the performance values from Table 1, which are presented for clear and easy comparison. The performance levels were compact. No classes were predicted with extremely high or low mAP. For our nighttime case, an mAP value of approximately 0.85 was achieved. This noteworthy achievement was only possible because we labeled objects meticulously, as described in the labeling conventions (Section 3.2.1). We usually obtained a lower mAP for the class \"Pedestrian\" than for the other classes because of the difficulty of distinguishing a pedestrian's features with insufficient lighting background. Nevertheless, pedestrians were still labeled in our study.  
Figure 15: Faster R-CNN [5] with ResNet101 [2] trained with different amounts of our nighttime data.  
The reader can subjectively and visually compare outputs from ordinary models trained with PASCAL VOC 2007 [6] and outputs from our proposed systems trained with our nighttime data. The evidence indicates that our proposed system could detect objects under insufficient lighting conditions, as depicted in Figures 18-21. Models trained with our nighttime data can detect distant and blurry objects, especially the Faster R-CNN [5] with ResNet101 [2] trained using our nighttime data. This model exhibits satisfactory performance of localization and classification (lower row of Figure 20). The models trained with our nighttime data can also deal with occluded objects and objects that appear partially, such as a row of bikes or a motorbike with only half of its body in the image.  
Figure 17: Training and validation loss of the Faster R-CNN [5] with ResNet101 [2]. **Upper left:** Cross-entropy loss. **Middle left:** RPN cross-entropy loss. **Upper right:** Bounding box loss. **Middle right:** RPN bounding box loss. **Bottom:** Total loss.  
Figure 19: Outputs from two variants of the Faster R-CNN [5] with VGG16 [1]. **Upper row:** Ordinary model trained with PASCAL VOC 2007 [6]. **Lower row:** Proposed system trained with our nighttime data.  
Figure 18: Output from two variants of the Faster R-CNN [5] with VGG16 [1]. **Upper row:** Ordinary model trained with PASCAL VOC 2007 [6]. **Lower row:** Proposed system trained with our nighttime data.
## 4 Advantages of Single Photon Detector (SPD) Arrays  
Single photon sensitivity can significantly reduce link requirements on laser power and/or telescope aperture size. Furthermore, arrays of such detectors allow the system to monitor a much larger angular region of space in order to sense a weak return on the perimeter of the array and guide the pointing mechanism to the central pixel in order to coalign the telescopes at both ends of the communications link [10]. Single photon sensitive detectors and arrays have been used successfully in a wide variety of laser sensors including:  
Laser ranging to both retroreflector-equipped satellites (e.g., NASA Goddard 2 KHz NGSLR [10]) and orbiting space debris (e.g., Graz Austria SLR station [11]).  
Multibeam airborne (e.g., Sigma Space, six million surface measurements per second using a 532 nm 60 kHz Q-switched laser split into 100 beamlets and the returns recorded by a 10 \(\times\) 10 pixel array [12]) and spaceborne laser altimetry (e.g., NASA ICESat-2 in a 500 km orbit, 60,000 measurements per second with six beamlets from a single 10 kHz laser [13].  
Moon to Earth laser communications (NASA HQ/MIT LLCD Mission) demonstrated PPM modulation at 620 Mbits/s [14].  
Accurate ranging and time transfer between Earth-based and space-based atomic clocks for improved spacecraft positioning and trajectory adjustment during transit to the planet.  
Currently available single photon sensitive array detectors include microchannel plate photomultiplier tubes (MCP/PMTs), in which the tube anode can be segmented with each segment having its own output, single-photon avalanche photodiodes (SPADs), Geiger-mode avalanche photodiodes (GM/APDs), and more recently nanowire detectors. It must be mentioned, however, that GM/APDs (typically used at 1064 nm) are unable to record multiple photons per bit and therefore do not appear to be well suited to the communications application. Commercially available SPADs have demonstrated detection efficiencies as high as 70% at 532 nm, and recent nanowire experiments have suggested similar efficiencies are possible.
## 2 Mathematical Model of Multi-Satellite Scheduling  
### Symbol Definitions  
For the convenience of description, the relevant symbol definitions are given, as shown in Table 1.
## 2 Air Quality Monitoring in Terms of Particulate Matter  
### The Need of Measurements and Legal Aspects  
The need of air quality monitoring in terms of atmospheric pollution with particulate matter is directly related to its impact on human health, climate and ecosystems [12; 34; 58]. It also results from the necessity to identify PM sources and to estimate the specific effects of actions aimed at reducing the levels of ambient PM [12; 29; 59]. The air quality monitoring system operates on the basis of a number of legal acts announced at the European Union level, among which the most important are:  
- Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe (O.J. UE, L 152/1 of 11.06.2008, p.1);  
- Directive 2004/107/EC of the European Parliament and of the Council of 15 December 2004 relating to arsenic, cadmium, mercury, nickel and polycyclic aromatic hydrocarbons in ambient air (O.J. UE L 23/3 of 26.01.2005, p. 3);  
- Commission Implementing Decision of 12 December 2011 laying down rules for Directives 2004/107/EC and 2008/50/EC of the European Parliament and of the Council as regards the reciprocal exchange of information and reporting on ambient air quality (O.J. UE, L 335/86 of 17.12.2011, p. 86);  
- Commission Directive (EU) 2015/1480 of 28 August 2015 amending several annexes to Directive 2004/107/EC and 2008/50/EC of the European Parliament and of the Council laying down the rules concerning reference methods, data validation and location of sampling points for the assessment of ambient air quality (O.J. UE, L. 226/4 of 29.08.2015, p.4).  
The assessment of air quality in EU Member States should be based on the common methods and criteria [21]. The principal requirements in this regard are related to specific threshold concentrations of a given pollutants as well as exposure of populations and ecosystems to these pollutants. As indicated in Art. 6 of the Directive 2008/50/EC, measurements carried out at a fixed sampling points should be mandatory in zones where long-term goals for ozone or thresholds for other pollutants have been exceeded. Data obtained from monitoring can also be supplemented with modelling or objective-estimation techniques to provide adequate information on the spatial distribution of air pollutants. The use of complementary assessment methods should also allow to limit the minimum required number of fixed sampling points.
## 2 Materials and Methods
### Identification of Volatile Compounds by HS-SPME-GC-MS  
Solid-phase microextraction (SPME; Supelco, Bellefonte, PA, USA) combined with 7890A-5975C chromatography-mass spectrometry (GC-MS; Agilent, Santa Clara, CA, USA) was used to determine the volatile compounds of samples collected at Day 35. After equilibration of 9 g samples in a 15 mL extraction flask at 70 \({}^{\circ}\)C for 15 min, 50/30 \(\upmu\)m PDMS/CAR/DVB fiber (Supelco) was inserted into the flask (1 cm from the sample) for extraction of the volatiles at 70 \({}^{\circ}\)C for 45 min. Finally, the SPME device was inserted into the injection port of the GC, and desorption was carried out by exposing the fiber in splitless mode to 250 \({}^{\circ}\)C for 3 min. GC conditions were as follows: HP-5 MS capillary column (30 m \(\times\) 250 \(\upmu\)m \(\times\) 250 \(\upmu\)m; Agilent); column oven temperature: 40 \({}^{\circ}\)C for 3 min, 3 \({}^{\circ}\)C/min to 120 \({}^{\circ}\)C, and finally increased at a rate of 5 \({}^{\circ}\)C/min to 240 \({}^{\circ}\)C, kept for 5 min; carrier gas: He; flow rate: 1.0 mL/min. MS conditions were listed as follows: electron ionization (EI) mode, voltage 70 eV, ion source temperature 230 \({}^{\circ}\)C, mass scanning range \(m/z\) 30-550. The volatile compounds (VCs) were identified by referring to their mass spectra in the NIST 14.0 database and by comparison with their retention index (RI). The relative percentages  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Biogenic Amines** & **LOD/(mg/kg)** & **RSD/\%** & **Regression Equation** & \(\mathbf{R^{2}}\) \\ \hline PUT & 0.80 & 2.36 & y = 29.554x \(-\) 5.7576 & 0.9991 \\ CAD & 0.80 & 2.74 & y = 30.636x \(-\) 32.384 & 0.9993 \\ HIS & 1.20 & 1.24 & y = 26.431x \(-\) 26.907 & 0.9990 \\ \hline \end{tabular}
\end{table}
Table 1: Validation parameters of the HPLC method.  
of each VC were calculated by dividing the peak area of the VC by the sum of the peak areas of all VCs.
## 5 Conclusions  
In this paper, we have designed a load-adaptive multi-channel communications system for WSNs. LPMC controls the channel allocation and deallocation at the sink and dynamically adds or removes channels. The dynamic channel allocation utilizes the limited channels of WSNs very efficiently and adds channel(s) only when necessary. LPMC increases the channel utilization and network throughput, and reduces the delay. LPMC works very efficiently in a dynamic environment in which traffic pattern changes very frequently, wireless environment is very dynamic, and even the presence of external interference might destroy the communications of one or more channels. LPMC dynamically divides a branch of the networks into smaller branches if the load of the branch is more than the capacity of a single channel. Finally, the simulation results demonstrate that LPMC outperforms the existing mechanisms.  
In the future, we would like to test the performance of LPMC in a real testbed. Another future interest lies in designing a multi-channel communications scheme for large-scale WSNs where multiple sinks are considered.
# External Slot Relationship Memory for Multi-Domain Dialogue State Tracking
## 6 Conclusions  
Regarding the existing problems in multi-domain DST models, (1) learning the relationships between multi-domain slots from a single sample reduces the model's learning capacity and fails to capture the most important features between slots and (2) it is challenging to exclude irrelevant slot information, leading to redundant information. In this paper, we propose ER-DST, which leverages an external slot relation memory. In our approach, we utilize an additional key-value memory to learn relationships between multiple domain slots from the entire dataset, which serves as a dictionary for slot relations. Then, we introduce a small constraint mechanism to reduce the weight of unrelated slot information. To evaluate the performance of our method, we conducted experiments on two large-scale, multi-domain task-oriented dialogue systems, MultiWOZ 2.0 and MultiWOZ 2.1. From the experimental results, it can be observed that the external slot relationship memory has improved the model's ability to predict slot values to some extent.  
However, in our model, the slot-value matching approach is relatively limited, which can lead to missing slot values, especially for difficult-to-enumerate slot value types such as time, and for unseen domain and slot combinations. In future work, we plan to address this issue in the following ways: (1) By combining two methods of selecting slot values from system response and slot description, we can increase the flexibility of slot value selection and further enhance the model's ability. (2) By adopting slot value generation techniques to improve the model's performance in few-shot and zero-shot scenarios. This will enable the model to effectively handle unseen domain and slot as well.  
Figure 4: The accuracy of 30 specific slots in the 5 domains of the MultiWOZ 2.1.  
**Author Contributions:** Conceptualization, X.X.; methodology, C.Y.; software, D.L.; validation, C.Y., D.L., and P.C.; formal analysis, X.Z.; investigation, D.T.; resources, P.C.; data curation, D.T.; writing--original draft preparation, C.Y.; writing--review and editing, X.X.; visualization, D.L.; supervision, X.X.; project administration, X.Z. and Y.Y; funding acquisition X.Z. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the Key Research Program of Chongqing Science & Technology Commission (Grant No. cstc2021 jscx-dxwtBX0019) and the Scientific Research Foundation of Chongqing University of Technology (Grant No. 2021 ZDZ025).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Effect of Physical Exercise on the Release of Micorparticles with Angiogenic Potential
## 6 MPs and Angiogenesis  
Vesicle-like structures have recently emerged as important mediators for cellular communication in both physiological and pathological processes [30]; in particular, MPs released by various cell types may play an important role in angiogenesis [62; 63], by modulating the production of proangiogenic factors through changes in the secretome of endothelial cells [64; 65]. Like exosomes, MPs can communicate with other cells through ligands on their membrane that interact with specific receptors of the target cells; alternatively, MPs can fuse with the plasma membrane of the target cells, delivering its cytoplasmic content (e.g., proteins, miRNAs, RNAs). In this way, MPs may elicit the synthesis of proangiogenic or antiangiogenic factors and affect the main processes involved in formation of new vessels, such as endothelial cells adhesion, migration, and proliferation [66].  
Endothelial cells-derived MPs (E-MPs) are clearly involved in the formation of blood vessels. A pioneer in vitro study highlighted that vesicles released by endothelial cells can transport integrin-\(\beta\)1 and active matrix metalloproteinases-2 and 9 (MMP-2 and MMP-9), thus inducing endothelial cells invasion and tube-like structure [67]. In addition, it has been demonstrated that upon stimulation with the proinflammatory interleukin-3, endothelial cells release vesicles containing pro-angiogenic factors such as miR-126-3p and Stat5 [68]. Moreover, another study shows that endothelial MPs are able to transfer miR-126 from endothelial cells to vascular smooth muscle cells, corroborating the angiogenic properties of endothelial MPs [69].  
Additionally, Plt-MPs are involved in angiogenesis. These vesicles can promote angiogenic effects by transferring various cytokines, such as PDGF, VEGF, FGF-2, and activating key proteins such as Pl3k, ERK, and src kinase [70]. Various studies found that the angiogenic potential of the platelet-derived MPs can have both functional positive and negative effects: when Plt-MPs were infused in a rat model of myocardial ischemia, indeed, they increased the quantity of functional capillaries [70]; on the other hand, MPs shed by platelets can favor angiogenesis involved in tumor progression, upregulating important angiogenic factors, such as VEGF, HGF, and interleukin-8 [71].
# Real-Time Object Tracking Algorithm Based on Siamese Network
###### Abstract  
Object tracking is aimed at tracking a given target that is only specified in the first frame. Due to the rapid movement and the interference of cluttered backgrounds, object tracking is a significant challenging issue in computer vision. This research put forward an innovative feature pyramid and optical flow estimation based on the Siamese network for object tracking, which is called SiamFP. The SiamFP jointly trains the optical flow and the tracking task under the Siamese network framework. We employ the optical flow network based on the pyramid correlation mapping to evaluate the movement information of the target in two contiguous frames, to increase the accuracy of the feature representation. Simultaneously, we adopt spatial attention as well as channel attention to effectively restrain the ambient noise, stress the target area, and better extract the features of the given object, so that the tracking algorithm has a higher success rate. The proposed SiamFP obtains state-of-the-art performance on OTB50, OTB2015, and VOT2016 benchmarks while exhibiting better real-time and robustness.  
object tracking; Siamese network; optical flow; feature pyramid; attention mechanism +
Footnote †: journal: Applied  
0000-0001-5000-5000-5000]M.W.Zhao  
0000-0001-5000-5000-5000-5000-5000-5000-5000-5000-5000-5000-5000-50000-50000-50000-50000-5000-50000-50000-50000-50000-5  
1. This study puts forward an optical flow pyramid Siamese network, which is able to enhance the character representation as well as tracking precision.
2. This paper trains the end-to-end feature pyramid optical flow network, which makes it better solve the occlusion problem of the objective.
3. Experiments on OTB2015 and VOT2016 reveal that compared to the current state-of-the-art approaches, the approach which is put forward possesses better performance.
## 2 Materials and Methods  
Vacuum arc melting (Arc Melter AM 200 (Edmund Buhler GmbH, Bodelshausen, Germany)) of pure (\(\geq\) 99.9 wt. %) metals was used to produce laboratory-scale (20 g) ingots of the alloys with the nominal compositions of HfCo, (HfCo)\({}_{90}\)(NbMo)\({}_{10}\), (HfCo)\({}_{75}\)(NbMo)\({}_{25}\), (HfCo)\({}_{40}\)(NbMo)\({}_{60}\), (HfCo)\({}_{25}\)(NbMo)\({}_{75}\), and NbMo (at. %). From the as-cast ingots, the rectangular (6 \(\times\) 4 \(\times\) 4 mm\({}^{3}\)) samples were cut by electric discharge machine. The specimens were mechanically gritted and polished, then ultrasonically cleaned in isopropanol.  
A Nabertherm furnace (LT 5/12/P320, Nabertherm, Lilienthal/Bremen, Germany) was used for oxidation tests under static laboratory air at 1000 \({}^{\circ}\)C for 100 h. The samples were put on alumina plates, then placed into the preheated furnace and held there for 1 h, 5 h, and further with intervals of every 5 h. After each period of oxidation test, the samples were cooled in the laboratory air for mass measurements. This process was repeated until reaching 100 h or complete disintegration of the specimen, whichever occurred first. Mass measurements were performed using an HR-200 analytical balance (A&D Company, Ltd., Tokyo, Japan) with an accuracy of 0.1 mg. Only bulk samples were weighed after oxidation. The spalled oxide scales or fragmented parts of the specimens were not included. At least two specimens were tested for each alloy.  
X-ray diffraction (XRD) was employed for phase identification of the oxides in the scales using a Rigaku diffractometer (Rigaku Corporation, Tokyo, Japan) with Cu-K\(\alpha\) radiation; the scanning rate was 4\({}^{\circ}\)/min and the 2\(\Theta\) was in a range of 20-100\({}^{\circ}\). Cross-sections of the oxidized specimens were studied using an FEI Quanta 600 FEG (Thermo Fisher Scientific, Brno, Czech Republic) scanning electron microscope (SEM) with back-scattered electron (BSE) and energy-dispersive X-ray spectroscopy (EDS) detectors. Samples for SEM studies were mounted in Buehler KonductoMet via Buehler SimpliMet4000 mounting press (Buehler, Lake Bluff, II., USA) to preserve the integrity of the oxide scale. The mounted specimens were polished using a Buehler VibroMet 2 Vibratory Polisher (Buehler, Lake Bluff, IL, USA) and Buehler MasterMet 2 Suspension to mirror surfaces.