esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions and Future Work  
This study presented an example-based XAI approach, using the Pix2 Pix model to generate synthetic images of polyps and the LIME technique to provide visual explanations of the classifiers' predictions. The analysis provided a better understanding of the classifiers' responses to variations in polyp size and their limitations. Although Pix2 Pix's quality of the images generated was limited, it effectively controlled characteristics such as the size of the polyps, allowing for an accurate assessment of the predictions. LIME offered useful visual explanations but revealed inconsistencies in some situations, suggesting the need to explore complementary techniques. For future work, improving Pix2 Pix or exploring other generative architectures could generate higher-quality images, contributing to the robustness of the classifiers. Developingmore controlled generative models and adjusting characteristics such as texture and colour would also be a promising way of improving model training. In addition to these technical improvements, a crucial next step will be to conduct a formal evaluation of the synthetic images with clinical experts. This would involve a task-based study where gastroenterologists assess the clinical realism and diagnostic utility of the generated examples, providing essential validation beyond the current quantitative metrics. Furthermore, applying this methodology to other classification tasks and architectures could expand its generalisation and effectiveness, improving the performance of image generation and classification models. Methodology, M.F.F. ; Validation, A.H.N. ; Investigation, M.F.F. ; Writing--original draft, M.F.F. ; Writing--review and editing, A.H.N. ; Supervision, J.D.A. and A.T.C. All authors have read and agreed to the published version of the manuscript. National funds finance this work through the Portuguese funding agency, FCT--Fundacao para a Ciencia e a Tecnologia, within project PTDC/EEI-EEE/5557/2020 and the project LA/P/0063/2020. The work is co-funded by the European Union (grant number 101095359) and supported by UK Research and Innovation (grant number 10058099). However, the views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible. [PERSON]'s work is also funded by the individual FCT grant reference number 2022.13770.BD. This work is also supported by advanced computing projects through a collaborative effort between FCT and Google Cloud Platform, under the project reference CPCA-IAC/AF/594668/2023. Not applicable.
# A Comprehensive Study of the Use of LoRa in the Development of Smart Cities
## 5 Discussion
### Research Contribution  
According to the qualitative analysis carried out in this work, Figure 19 shows the high level of interest of researchers in using the IoT technology in the field of smart energy and smart environment. Additionally, it is important to indicate that, even though there are important contributions related to smart waste management, there is still an important gap is this field; other situations offer opportunities to researchers.  
Figure 19: Rate of publications related to different smart cities subcategories.  
Figure 18: Trends of IoT solutions in smart cities.  
Figure 20 shows that research works on smart energy has had a constant growth rate in the last three years. There is a significant increase in the rate of research works in smart environment and in smart transportation. The important growth of research works in the field of energy is associated with the increase of the number and variety of IoT smart devices (e.g., smart meters) and the automation of operations in power grids for developing complete smart grid architectures. These changes could be the basis for improving the economy of cities in the era of the fourth industrial revolution [94].  
The aim of the use of IoT in smart cities has been evolving. On the basis of the qualitative analysis carried out in this study, we have noticed that evolution has occurred at three levels.  
Level 1, Monitoring: IoT solutions gather data from a specific part of the IoT ecosystem, e.g., temperature or humidity values of a farm.  
Level 2, Automation: IoT solutions automate daily operations of the smart city, e.g., the control of an irrigation system.  
Level 3, Intelligence for decision-making: IoT solutions deliver smartness to a city, e.g., the prediction of pest in plants based on data analysis.  
Figure 21 shows the result of the word density analysis performed in the qualitative analysis. We identified that the most relevant aspect in the analyzed articles is the term \"data\". This is logic, since data are used at all levels (i.e., monitoring, automation, and intelligence) of IoT solutions.  
Figure 20: Rate of research works related to smart cities in the last three years.  
According to our literature review, IoT research works started to include machine learning or data mining techniques to establish data analytic processes just a couple of years ago. Of the papers analyzed in this study, only around 35% of the publications considered the incorporation of data science approaches, and only 15% considered aspects related to decision support systems.  
LoRa is an open, scalable, and flexible technology that can work with different protocols. These characteristics of LoRa make possible the implementation of the aforementioned three phases benefiting smart cities. Data generated for IoT solutions are sent using LoRa networks even to long distances. The data are sent in real time, allowing citizens and city managers to make effective decisions in a timely manner.
## 3 Results and Discussion
### Factors Influencing the Quality of Classification Results
#### 3.1.2 The Misclassification and Confusion of Classes  
The variation in the percentage of the area edited as buildings did not follow a specific tendency. The difference of the percentage between HRC and HRC_e for this category varied in a range between \(-\)3.6% and \(+\)1.6% due to a combination of different factors. On the one hand, the percentage increased after converting 'Shadows' or 'Clouds,' and after the manual editing. However, the latter can also lead to reducing its percentage if temporal elements, such as vehicles, which were falsely classified as buildings but later corrected. On the other hand, a decrease of areas classified as 'Buildings' is likely to occur after superimposing street layers. In fact, the classes 'Paved' and 'Unpaved' increasedto up to 6% in the images where they were defined. This suggests that sections of streets tend to be classified erroneously as buildings, among others, showing overrated initial values for this category. This misclassification was observed in some street sections of several images. In general, the small range of variation after edition corresponding to the land cover 'Buildings' cannot be interpreted as a satisfactory initial classification but as a result of the post-processing phase.  
Another common misclassification was observed between the class 'Bare land' and both 'Unpaved' and 'Paved.' Due to the similitude of their pixel colors, these classes were falsely classified at the initial stage and only corrected in the post-processing. As a consequence, the selection of ROIs was preferred for 'Bare land,' since the superimposition redefines the streets.  
A similar conflict was observed between 'HighVeg' and 'LowVeg.' Although it is visually possible to discern these areas, the diversity of green color tones for several species of vegetation made it complicated, in certain cases, to differentiate them after running the classification algorithm. Nevertheless, their percentages increased after editing in all the cases, as a result of reassigning shadows, also because an erroneous classification with other features happened in a few cases. One of these cases occurred when green roofs were present on the image, which was solved by editing the buildings.  
In conclusion, the misclassification of LULC classes is inevitable when following our methodology, because the procedure is based on pixel colors, and some features share very similar colors despite belonging to different classes. To overcome this, manual editing can be applied to reassign specific features, such as rivers or temporal elements. The editing proposed in the post-processing stage consists of a set of tools which are useful to redefine misclassified pixels. In any case, the effort incurred in the editing will depend, among others, on the image quality, the classification algorithm, and the training input.
# Ultra-Low-Power Wide Range Backscatter Communication Using Cellular Generated Carrier +
## 2 Background
### Backscatter Communication  
#### 2.2.1 Traditional  
In a traditional BC, a transmitter indirectly communicates with the receiver, which is also referred to as a reader along with a passive or semi-passive backscatter device in the middle. In case of BC, a dedicated transmitter generates a radio signal, which is reflected/modulated by the BD and is then received at the reader. The received signal at the BD from the transmitter can be used for two purposes i.e., to power up the circuitry of the backscatter device, and to carry the information to the reader in the form of the modulated signal. There are three main modes of traditional backscatter communication i.e., monostatic, bi-static co-located, and bi-static dislocated configuration, as shown in Figure 1. Each BC mode possesses different link budget and margins, as explained in references [19; 20; 21]. First, in monostatic backscatter mode, a single antenna is used at thereader for both transmission and reception purpose, where the forward link is from the transmitter to BD and the backscatter link is from BD to the Rx as shown in Figure 1a. The main challenge of monostatic architecture is self-interference, and that limits the range of data transmission. To improve this, active cancellation can be implemented to remove the self-interference signal. Second, in a bi-static co-located mode, the reader has two antennas; one for transmission and one for reception, and they are located quite close to each other i.e., separated by few wavelengths (lambdas), as shown in Figure 1b. In bi-static co-located mode, the Tx antenna and Rx antenna of the reader may have different gains. Third, in bi-static dislocated mode, the Tx and the Rx are placed at two separate locations, as demonstrated in Figure 1c. There also exists a direct path between the Tx and the Rx, different from the backscatter path, and the direct path is much stronger than backscatter path [19; 20; 21].  
2.2 Ambient backscatter communication (AmBC) utilizes the ambient RF signal to realise a communication between BD and the reader, and the source of signal at BD can be any existing RF signal, as demonstrated in Figure 1d. The main advantage of the AmBC is that it utilizes the abundant existing radio frequency signal (e.g., cellular network, WLAN, TV, and radio broadcast) for transmitting information from the BD to the Rx, and also for harvesting the energy at the BD. More specifically, ambient BD needs no dedicated energy provider, and it reduces the cost of installation and maintenance. Also, ambient backscatter enables D2D communication, different from the traditional backscatter that must communicate exclusively with a reader, without sensing and communicating with other nearby BDs. [PERSON] et al. [22] discussed a fundamental scenario of AmBC, where two battery-free devices communicate via ambient backscatter.  
Figure 1: Traditional and ambient backscatter configurations, (**a**) monostatic, (**b**) bi-static co-located, (**c**) bi-static dislocated, and (**d**) ambient.
# Functional and Antimicrobial Properties of Propolis from Different Areas of Romania
## 4 Discussion
Similarly, extract A, which exhibited robust antimicrobial effects, contained elevated levels of caffeic acid, CAPE, and chrysin. These compounds are antimicrobial and synergistic. CAPE is effective against _S. aureus_ and _S. epidermidis_ but not _E. coli_ and _K. pneumoniae_. Extract H, with low antimicrobial activity, had lower levels of bioactive compounds, including chrysin and pinocembrin. This shows that both the concentration and composition of phenolics affect propolisis extract antimicrobial potential. The antioxidant activity of the extracts, as evaluated by FRAP, DPPH, and ABTS assays, also correlates with antimicrobial activity. Extract A, with the highest antioxidant values (7.4 mg Trolox Eq./g in FRAP, 31.6 mg Trolox Eq./g in DPPH, and 34.0 mg Trolox Eq./g in ABTS), exhibited strong antimicrobial effects. Antioxidants may enhance antimicrobial activity by neutralising oxidative stress, which can weaken bacterial defences, as noted by [PERSON] et al. [20]. The high efficacy of C1 and A against _E. faecalis_, _S. aureus_, and _L. monocytogenes_ correlates with their high levels of naringenin, apigenin, and pinocembrin. These compounds may act synergistically to enhance antimicrobial activity. While C1 and A showed moderate efficacy against _E. coli_ and _P. aeruginosa_, the overall activity against Gram-negative bacteria was lower. This could be due to the outer membrane of Gram-negative bacteria, which reduces permeability to polyphenols. Extract C2 demonstrated better activity against _E. coli_ and _S. enterica_, potentially due to its specific phenolic profile, including higher quercetin levels (4.25 \(\mu\)g/g), which is known to disrupt Gram-negative bacterial membranes [76]. The strong antifungal activity of C1 against _C. albicans_ may be attributed to its high chrysin content (188.48 \(\mu\)g/g), which has been reported to effectively inhibit fungal growth. The presence of multiple bioactive compounds in C1 and A, such as CAPE, naringenin, apigenin, and pinocembrin, likely contributes to their synergistic effects. Studies indicate that combinations of these compounds exhibit enhanced antimicrobial activity compared to individual compounds [47]. In contrast, extracts like H, which lack some of these key compounds, exhibit reduced efficacy.
## 5 Results and Discussion
### The Role of Advanced-Perception Algorithms and V2X in Adverse Weather  
VRDeepSafety enhances weather resilience through advanced sensor fusion, combining data from various sensors and mitigating individual sensor limitations. Machine learning models also boost performance, with CNNs handling object detection and LSTMs managing temporal analyses. Trained on diverse weather datasets, these models filter noise and artifacts, with CNNs being effective in detecting objects despite partial occlusions or distortions.  
V2X communication plays an essential role in addressing challenges caused by adverse weather conditions. By enabling real-time data exchange, V2X enhances VRDeepSafety awareness and improves its safety. These data facilitate informed decision-making, and shared sensor data enable swift action to prevent collisions, particularly at intersections or in crowded traffic. By receiving traffic signal data and alerts from nearby vehicles, VRDeepSafety can predict changes, adjust speed, or steer for safer and more efficient navigation.  
The analysis shows the optimal VRDeepSafety performance in clear weather, demonstrating its readiness for deployment in such regions. Although functionality is limited in fog and rain, sensor fusion and V2X enable the system to withstand adverse weather conditions. Leveraging these features and the machine learning algorithms designed for such conditions makes VRDeepSafety reliable for autonomous driving in unfavorable weather conditions.
# Advanced SDR-Based Custom OFDM Protocol for Improved Data Rates in HF-NVIS Links
## 2 Materials and Methods
### Transmitter Application Flow Chart Development  
In Figure 3, the implementation starts with a file source block, reading data from a specified text file and inserting it into a byte division block. The byte splitting block assigns a length identifier (packet_len) to each packet, which is essential for the correct handling of the packets in the blocks that follow. The purpose of this configuration is to have a continuous repetition of the contents of the file, and therefore a continuous flow of data.  
The output of the byte splitter is split into two parallel paths, each leading to a block from the stream to the tagged stream. These blocks process the data, using the packet_len tag to mark the boundaries, by converting the stream into tagged packets of a specified length (in this case, 94 bytes). The processed streams are then fed into two identically configured OFDM transmitter blocks. Each OFDM transmitter block modulates the incoming stream on multiple orthogonal carriers of 64 and 16 symbols, respectively. The transceivers use BPSK for the header and QPSK for the payload, with pilot symbols and timing words to ensure proper receiver demodulation.  
Figure 4 shows an implementation for processing and visualizing OFDM signals. The diagram starts with two parallel signal chains, each with a throttling block to set the sampling rate to 24 kHz, followed by an interpolated resampling block to increase the sampling rate to 240 kHz. The next channels are set in spectrum. This is done by multiplying the 50 kHz and \(-\)50 kHz cosine waves generated by the source blocks. The modulated signals, representing two parallel OFDM channels, are combined by an adder block that adds the OFDM aggregation into a single mixed signal.  
This mixed signal is sent to a UHD receiver block: the USRP sink block, which interfaces with a USRP hardware device configured to transmit the signal at a center frequency of 7 MHz, with a sampling rate of 240 kHz and a gain value of 15. The diagram also includes QT GUI spectrum sinks to visualize the spectrum in real time at different stages: before and after resampling, modulation, and final transmission. This setup demonstrates  
Figure 3: Data preparation for parallel OFDM transmission.  
a practical OFDM transmitter, showing how signals are generated, modulated, aggregated, and transmitted with GNU Radio and USRP hardware, while providing detailed spectral analysis to aid debugging and optimization of the communication process.
###### Abstract  
Acetaminophen (APAP) is the most commonly used nonprescription antipyretic-analgesic drug. This medication is thought to be safe at the suggested dosage (4 g/24 h), but its overdose (up to 2.5 g/kg) can cause severe injuries to the human body, including renal injury. APAP has various toxic effects on nephrons, as it leads to an excessive free radical generation that, in turn, results in a disturbance in the redox homeostasis of cells, causing oxidative stress. To replenish this oxidative stress, there is an ultimate urge for natural therapies that can retain the cellular homeostasis of nephrons by diminishing the overdose impression of acetaminophen. The principle objective of this work is to appraise nephrotoxicity due to APAP and its amelioration through the antioxidant properties of aqueous extracts of selected medicinal plants: _Urtica dioica_, _Capsella bursa-pastoris_, and _Inula racemosa_ (UD, CBP, and IR, respectively). The pH stability of the nutraceuticalals used was examined by determining the impact of pH 4, pH 7 and pH 9 on the DPPH radical scavenging activity of aqueous plant extracts. Gas chromatography-Mass spectroscopy (GC-MS) analytical technique was performed to determine the volatile organic phytochemical profiles of all three medicinal plants. Male Swiss albino mice were used for the present investigation. The animals were distributed into five groups of (\(n=6\)), a total of 30 mice, for in vivo analysis. Group 1 served as the control group; group 2 received a single IP dose of APAP (600 mg/kg); group 3 received APAP pretreated with UD (300 mg/kg); group 4 received APAP pretreated with CBP (300 mg/kg); and group 5 received APAP pretreated with IR (300 mg/kg). Overdose of the APAP- induced a significant (\(p<0.05\)) alterations in the total protein concentration, weight and the nephrological architecture in renal tissue, as observed through biochemical assays and histopathological examinations. Due to nephrotoxicity, there was a substantial (\(p<0.05\)) drop in body weight and total protein contents in the APAP alone group when compared to the treatment groups. There was remarkable protection against APAP-induced alterations in the total protein of renal homogenate in the treatment groups. Histopathological analysis (H&E staining) of the mice kidneys indicated severe deterioration in the APAP alone group, whereas the therapy groups showed considerable nephoprotection towards APAP-induced abnormalities. The biochemical findings and histopathological study of the kidneys revealed that the herbal extracts (UD, CBP, and IR) have a nephoprotective potential against APAP-induced nephropathy. The trend of efficacy was observed as UD \(>\) CBP \(>\) IR. However, extensive study is needed to determine the likely ameliorative mechanism of these nutraceuticals.  
Keywords:nephrotoxicity; acetaminophen; _Urtica dioica; Capsella bursa-pastoris; Inula racemosa;_ renor protection; swiss albino mice +
Footnote †: journal: Accepted in 2020
## 2 Related Work  
Surveys in the literature [9; 10; 11; 12] have identified four main sources of energy waste at the MAC level: (1) idle listening, which occurs when a node listens the channel but no one is sending; (2) collisions, which occur when two or more nodes transmit at the same time, causing packet loss and possibly subsequent retransmissions; (3) overhearing, which occurs when a node listens for a packet targeted to another node; and (4) overhead due to the control messages that support MAC/routing operations. These surveys also provide an insight into MAC protocols for WSN.  
In a recent work [13] the authors provide a classification of MAC protocols in three categories:  
* _Scheduled protocols_ are synchronous protocols based on Time Division Multiple Access (TDMA). Here, each node must know the time slots assigned to its neighbors in order to wake up (_i.e._, turn its radio on) during these transmission slots. These approaches require an ad-hoc scheduling of the nodes' activity periods based on their communication needs. Furthermore, communication delays due to this schedule can be limited only when the network traffic is low.
* _Asynchronous protocols_ do not manage a common schedule for all the nodes, rather, each node decides independently its radio activation period. To ensure that the communication among two nodes takes place, even if the nodes have chosen different radio activation periods, these protocols use strategies such as _preamble sampling_ or _receiver-initiated communications_. Asynchronous protocols are particularly interesting in WSN since they do not have overhead due to node synchronization and they may enable very low duty cycles. For these reasons their energy consumption can be lower than in other approaches. On the other hand, they can incur communication delays caused by the lack of synchronization of the nodes and the channel access contention.
* _Protocols with Common Active Periods_ can be considered hybrids between the two former approaches. In these protocols, the nodes share the scheduling time of the radio activity periods (which are typically longer than those used by other approaches). A node can send data at any time during its radio activity period. Channel contention is typically managed by a handshake protocol (for example based on RTS/CTS [14]). In these strategies, the overhead due to the maintenance of the common scheduling and the longer duration of the active periods tend to increase the energy consumption. However, since these protocols need a certain degree of synchronization among nodes, they can reduce the contention delays as compared to asynchronous-like approaches.  
In this work we focus on asynchronous protocols based on preamble sampling. A survey of these approaches is provided in [13]. Next, we provide a more detailed explanation of the operation of these protocols.