esa-sceva/satcom-chunk-collection huggingface dataset:
# Experimental Study on Anti-Icing Performance of NS-DBD Plasma Actuator
## 3 Experimental Results
### Thermal Properties
Figure 10 plots the spanwise (direction of X axis) variation in temperature rise at the location of Y = 20 mm. Almost 20 \({}^{\circ}\)C temperature differentials are observed between two different discharge conditions near the exposed electrodes edge, while it gets relatively minor at the middle of two adjacent electrodes. Figure 11 shows the temperature distribution over the surface of the wing model 80 s after the NS-DBD plasma actuator was switched on under conditions of cold airflow. Due to the occurrence of convection heat transfer, the surface temperature of both two discharge conditions is decreased. The spanwise (direction of X axis) temperature variation in Y = 10 mm, Y = 20 mm, Y = 30 mm are also selected, and are plotted in Figure 12. In the X direction, the temperature rise near the exposed electrode edge is the highest, which is well matched with Figure 10, when actuated at room temperature and normal atmospheric pressure. In contrast, along the chordwise (direction of Y axis), the surface temperature gradually increased within the discharge region. On the one hand, the closer to the leading edge, the more intense convective heat transfer occurs between the cold incoming flow and the airfoil [37]. On the other hand, heated gas by plasma actuation occurs at the front part flow downstream along with the cold airflow [21], which strengthens the forced convection heat transfer between heated gas and the dielectric surface in the downstream to some extent. The trend of temperature variation below the location of Y = 55 mm in Figure 12 also confirms this viewpoint; the temperature downstream the electrode edge is comparatively higher. Figure 10: The spanwise (direction of X axis) variation in temperature rise at the location of Y = 20 mm. Figure 9: The surface temperature distribution 10 s after NS-DBD plasma actuator was switched on at room temperature (25 \({}^{\circ}\)C) and normal atmospheric pressure: (**a**) LV-HF discharge; (**b**) HV-LF discharge. Beyond that, it is interesting to note that temperature change near the edge of the exposed electrode is slowly when HV-LF discharge is used, in contrast to LV-HF discharge. This can be attributed to the different heating areas of two discharge conditions. The heating of the dielectric barrier is a function of the heating of the air in the discharge volume above it [36]. As mentioned in the previous section, HV-LF discharge can promote the discharge filaments propagating towards the middle of the adjacent electrode, which leads to a larger area of discharge. Heat transfer between heated gas and the dielectric surface causes a different spanwise temperature distribution under the two discharge conditions.
## 1 Introduction
It was found that significant discrepancies exist between the HVAC (Heating, ventilation and Air Conditioning) standards and the actual thermophysiological comfort of both the surgical team and the patient. Several studies dedicated to the topic [4; 5; 7; 8; 9; 10] have found that it might be difficult to find out a general solution for the problem, having in mind the current design of HVAC systems and the thermal requirements of the different players in the OR. The predicted mean vote (PMV), developed by [PERSON] in 1972 [11], is the most used model for predicting thermal comfort in enclosures. Other models used in the literature are the wet bulb globe temperature (WBGT) [12; 13], effective temperature (ET) [14] and thermal acceptance ratio (TAR) [12]. Details about the indexes for the evaluation of thermal comfort and hot stress can be found in review works [15; 16]. According to the PMV model, the thermophysiological comfort of a person is assessed based on the body's heat balance, mean skin temperature and sweat rate. The determination of the PMV index requires several input variables and its computation, which requires several iterations, might be done using different programs, including black box [17] and white box [18] software. The PMV index allows the number of the occupants of the indoor premises who are not satisfied with the provided thermal conditions (feel cold or warm) to be predicted. This feeling stays at the bottom of the determination of the predicted percentage of dissatisfied (PPD) index [11]. It allows the assessment of how many of the occupants will feel uncomfortable in a particular thermal indoor environment. Predicted heat strain (PHS) is evaluated on the basis of the ISO 7933 international standard [19], and the following stress/strain criteria are taken into account: the maximum sweat rate and maximum skin wettedness. Two strain criteria are also assessed: the maximum water loss and maximum rectal temperature, which is used as equivalent to the core body temperature. The present paper aims to perform an analysis of thermophysiological comfort in an OR from the point of view of both the patient and the surgeons during an operation. Different surgical clothing ensembles are tested. A computational program for the prediction of the heat strain, following ISO 7933:2004 [16], was applied to calculate the PMV-PPD indexes, according to the model developed by [20]. Interpretations in terms of the predicted heat strain are also made.
# MSEANet: Multi-Scale Selective Edge Aware Network for Polyp Segmentation
## 4 Experiments
### Datasets  
To evaluate the performance of the proposed MSEANet, we conducted extensive tests on three publicly available polyp segmentation benchmark datasets: Kvasir-SEG [12], Kvasir-Sessile [13], and BKAI [14]. Sample images from these datasets, along with their corresponding edge prediction maps, are presented in Figure 4.  
Figure 4: Image refers to sample images from the Kvasir-SEG and BKAI datasets. GT represents the ground truth annotations of polyps; Edge mask is the ground truth of polyp edges generated using the Canny operator; Edge pred denotes the predicted polyp edge maps generated by the EFE module.  
**Kvasir-SEG**[12]: Kvasir-SEG is a publicly available endoscopic image dataset specifically designed for polyp segmentation tasks. It consists of 1000 annotated polyp images with a variety of shapes, sizes, positions, and appearances. The image resolutions range from 332 \(\times\) 487 to 1920 \(\times\) 1072 pixels, offering diverse challenges for segmentation models. All images are derived from endoscopic examination videos and have been meticulously annotated by experts from the University Hospital of Oslo, Norway. These reliable annotations serve as high-quality labels for model training and evaluation, making Kvasir-SEG a widely used benchmark for assessing segmentation performance.  
**Kvasir-Sessile**[13]: Kvasir-Sessile is an extended dataset developed by researchers at the Norwegian University of Science and Technology (NTNU) to target the segmentation of flat polyps, a challenging and less prominent type of polyp. These polyps often feature ambiguous boundaries and irregular shapes, complicating the segmentation task. The dataset's images are annotated by medical experts, including trained endoscopists, ensuring precise labeling of polyp boundaries and morphology. This high-quality dataset supports model development and testing for more challenging segmentation scenarios.  
**BKAI**[14]: The BKAI dataset, curated by the BKAI laboratory in Vietnam, is a diverse collection of endoscopic images for polyp segmentation. It includes images of various types of polyps and represents a range of complex clinical scenarios, including variations in image quality, lighting conditions, and background complexities. The dataset's annotations are manually generated by experienced endoscopists, ensuring accurate boundary localization and precise labeling. This dataset provides a robust foundation for training and evaluating models in challenging clinical contexts.
## 4 Experiments  
### Experimental Setup  
To validate the effectiveness of the proposed Hybrid Multi-Agent Reinforcement Learning (Hybrid MARL) framework, we conduct extensive experiments on a simulated traffic network. The simulation is implemented using SUMO (Simulation of Urban Mobility), a widely used open-source microscopic traffic simulator. The experimental setup includes multiple road network configurations, varying traffic flow intensities, and comparisons with state-of-the-art baseline methods. Figure 5 illustrates the experimental environment and road network topology used in this study.  
Figure 5: The experimental road network setup used in SUMO, showing intersections and vehicle flow patterns. The figure provides a schematic representation of an urban road network organized into a grid pattern, where gray lines depict roadway segments and lanes, green squares indicate intersections with traffic signals currently permitting vehicle passage, and red squares represent intersections where vehicles must stop and wait for the traffic signal to change, collectively illustrating typical traffic signal control at intersections.  
The experimental road network is configured to mimic real-world traffic conditions, incorporating intersections of varying complexities. Traffic demand patterns follow a Poisson distribution to simulate realistic vehicle arrivals, ensuring diverse and dynamic traffic conditions. The simulation runs for 10,000-time steps, with each agent making decisions at predefined intervals. The performance of each traffic signal control strategy is evaluated based on multiple key performance indicators (KPIs), including average vehicle waiting time, throughput, congestion level, and fairness of green light distribution.  
To ensure consistent comparability, all scenarios are based on a regular 4 \(\times\) 4 grid layout representing a medium-sized urban road network. Each intersection has four incoming approaches, and each lane receives an identical vehicle inflow rate unless specified. Directional imbalances in flow patterns are not modeled in this study.  
The theoretical value of 2000 vehicles/hour/lane is cited as an idealized saturation flow from traffic flow theory. In practice, our simulation maintains much lower demand rates (ranging from 800 to 1500 vehicles/hour/lane), and this theoretical upper limit is only used as a normalization constant for throughput metrics. All performance results in Tables 1 and 2 are reported under the same simulation conditions for fair comparison.
## 6 Design Strategies and Case Studies
### Design Strategy
#### 6.1.1 Technology Support  
To give users an immersive experience, the technological support level of the system should incorporate cutting-edge 3D modeling and virtual reality technology to create incredibly realistic reconstructions of historical scenes and cultural treasures. It should ensure that various input techniques, including gesture, speech, and touch, are supported so that users can naturally engage with the virtual environment, increasing the presence sensation. Simultaneously, the system's technological stability and response speed should be optimized to guarantee seamless user interaction, minimizing lag and delays and offering a seamless and uninterrupted experience. Different users with varying task challenges are also required for pairing to make the task and technology compatible.
# Handover-Driven Interference Management for Co-Channel Deployment of Femto- and Macro-Cells
## 4 The HO-FIM Architecture
### Overview of HO-FIM  
The objective of HO-FIM is to offload both DLs and ULs to mitigate the interference between macro- and femtocells while preserving the users' quality of service (a _load_ is defined in the next subsection). To meet this objective, HO-FIM hands over users dynamically between macro- and femtocells. Basically, HO-FIM is required to make the following important decisions:  
* when to trigger handovers;
* which macrocell users to be handed over; and
* which femtocell to hand a selected user over to.  
Figure 2: Procedure of a handover from a macrocell to a femtocell.  
Besides, HO-FIM needs to minimize the number of triggered handovers and suppress ping-pong handovers while reaching a desired system condition. HO-FIM is composed of three interacting decision-making controllers, as illustrated in Figure 3. In what follows, each of these controllers and their complementary interactions are described.
## 4 Multi-Threaded Control with C/S Architecture Incorporating AES Encryption and TLS Protocol  
In this paper, the security and confidentiality of data transmission was improved by using AES encryption with the TLS protocol to secure the C/S architecture multithreaded control. By using the AES encryption algorithm to encrypt the communication data, combined with the transport layer security provided by the TLS protocol, it can be ensured that the communication between the client and the server is adequately protected during the transmission process. This section focuses on the process optimization design and security analysis of this paper.
## 5 WBAN and the Communications Protocol Stack
### MAC Layer
#### 5.3.1 MAC Mechanisms  
Channel access mechanisms can be grouped into: _Schedule-based_: predominantly TDMA but also Code Division Multiple Access (CDMA); _Contention-based_: usually CSMA/CA; and _Hybrid Schemes_: combining contention and scheduled methods as part of an adaptive scheme [34].  
In a schedule-based system such as TDMA, the channel is split into fixed or variable time slots with a fixed frame length that is assigned to nodes that wish to communicate. Collision is avoided as nodes can only transmit during their allocated time slot thereby avoiding any collision and wasted energy. Each of the nodes must be synchronized using separate control packets to ensure nodes send their packets in the allocated time slot. In some applications, schedule-based protocols can be more efficient using less energy due to the reduced radio duty cycle, but they do have the overhead of requiring frequent synchronization. This overhead could be significant in large networks where overall network synchronization could be problematic. Other issues with schedule-based schemes include: assigning slots to nodes and identifying the collision free slot [34].  
In CSMA/CA there is no reservation of the channel. Each node will initially listen to the channel, check it's free or not then transmit. If the channel is busy the node will back off for a period of time before trying again. Contention-based schemes such as CSMA/CA can suffer from the hidden node problem together with node idle listening and packet collision. This could result in CSMA/CA incurring significant overhead in WSNs and WBANs. The main advantages of contention-based approaches are low complexity, ability to adapt to fluctuations in traffic load, and low infrastructure implications. However contention-based protocols can suffer from overhearing, idle listening and collisions, all of which will have an energy cost implication. Additionally, QoS levels cannot be guaranteed in a contention-based channel unless the number of nodes and traffic levels are stable in relation to the available bandwidth.  
Comparisons between contention and schedule schemes shown in Table 1 highlight variances between the schemes depending on the performance metric. Although these sorts of comparisons are useful in an overall sense in terms of understanding the constraints of each method, the performance of each is tightly coupled to the specifics of the application environment and traffic characteristics of the network.  
Hybrid schemes aim to improve the performance of the MAC layer by combining schedule- and contention- based schemes, e.g., TDMA with CSMA/CA. This type of architecture [34] can improve performance over existing schemes by adapting to network traffic conditions as they arise. A hybrid MAC can function in contention-based scheme mode when traffic is light and convert to a reservation based scheme when traffic is heavy. Simulation results show that hybrid schemes can outperform both contention- and schedule-based MAC, as they are more able to adapt to increased traffic loads thereby using less energy in the process.
# Short-Range Noncontact Sensors for Healthcare and Other Emerging Applications: A Review
## 3 Recent Technical Advancements
### Random Movement Cancellation
Since the large body movement may produce large signals that may saturate the baseband circuitry, phase compensation using phase shifter at the radar RF front end helps to relieve the radar circuitry from potential saturation. The other two strategies are implemented in the baseband digital domain so they can be more precisely controlled to perform fine tuning to remove the artifacts. The aforementioned approaches are for compensating the body movement while the radar system is stationary. Researchers have also proposed approaches to tackle the movement of the radar platform itself, which can be useful as radar sensors are expected to be integrated in mobile platforms such as smart phone or tablet. For example, [71] demonstrated a complete compensated single transceiver radar system for vital sign detection in the presence of platform movement. By putting a custom designed tag near the subject, it produces a reference signal for the radar platform to compensate the movement of itself. Figure 6: Setup of noncontact vital sign detection using two radars with random body movement cancellation.
# Systematic Review and Meta-Analysis of Melatonin Quantification in Wine
###### Abstract  
The identification of melatonin in grapes has led to the publication of numerous studies on melatonin in wines, and the aim of this study was to perform a systematic review and meta-analysis of published data on melatonin concentrations in wines. In this context, international databases such as Scopus, Web of Science and PubMed were searched for relevant articles (437) up to 29 March 2025. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used. A total of 15 studies from eight countries, involving various wine types and analytical methods, were included in the meta-analysis. Considerable analytical variation was observed across studies, and high-performance liquid chromatography (HPLC) coupled with either mass spectrometry (MS) or fluorescence (FL) detection was shown to be the most accurate and sensitive method for quantifying melatonin. The highest concentrations were found in Spanish red Tempranillo wine, Romanian white Noah wine, and Romanian rose Lidia wine. Red wines, particularly those produced from Cabernet Sauvignon (CS) grapes, were the most frequently studied. The results of this work provide a clearer picture of melatonin levels in wine. Further research is needed to explore the implications of melatonin content in wine for human health and the wine industry.  
melatonin; wine; PRISMA; Cochran's Q; analytical methods 2025
## 3 Analysis  
### Complaint Processing Time Data Overview  
This study analyzed 65,680 complaints recorded by the RPRS app from January 2021 to December 2022. The dataset includes various details such as the types of complaints, dates of complaint submission, action dates, addresses, and brief descriptions provided by the complainants. Additionally, it contains photos taken by the complainants, along with the longitude and latitude coordinates of each complaint location.  
The date the service receives a complaint is automatically recorded by the app and referred to as the \"complaint report date.\" The \"action date,\" which marks the completion of complaint processing, is manually entered by the responsible official. The time between action dates and complaint report dates indicates the time required for processing the corresponding complaints, although differences from the actual processing time may exist due to manual entry.  
Prior to analyzing the complaint processing time (CPT) data, 452 complaints that showed processing times exceeding five weeks (0.7% of the total dataset) were removed, as such lengthy durations are considered highly atypical. Additionally, 767 complaints processed in less than 4 h (1.2% of the dataset) were excluded, presuming that a minimum of 4 h is necessary for a complaint to be acknowledged and processed by an official. After these adjustments, the analysis proceeded with 64,461 valid complaint records.  
In addition to analyzing CPTs, this study utilized longitude/latitude coordinates to determine the locations of complaints. Conducting a meaningful analysis with only these coordinates is not feasible. To enhance the utility of the geographic data, we employed the Nominatim (Version 4.5.0) georeferencing application programming interface (API) [20], provided by OpenStreetMap [21], to obtain detailed information regarding the locations where individual complaints were reported. The specific locations of complaints are classified into the following categories: (1) areas around buildings, (2) neighborhood facilities, (3) roads, (4) social overhead capital (SOC) facilities, and (5) railways, as outlined in Table 1. Notably, roads are further divided into detailed sub-types. As appeared in the sub-types in Table 1, this research deals with complaints reported from any types of roads in and around the presented location types.  
Finally, we measured the CPTs using the complaints data from 2021 to 2022, categorized by both complaint type and location type. We applied statistical analysis techniques to identify factors influencing the prioritization of complaints based on these categories. Considering the severity of different road sub-types, we also analyzed how each sub-type affects the processing time of complaints.