esa-sceva/satcom-chunk-collection huggingface dataset:
# Opportunities for Integrating Underground Railways into Low Carbon Urban Energy Networks: A Review
## 3 Urban Waste Heat Sources
### Sewage Systems  
Sewage systems and treatment plants generate waste heat and are usually closer to dense heat demands that could be efficiently met with district heating. Heat can be recovered from wastewater using a heat exchanger and upgraded by a heat pump. Wastewater can be used at different stages, so the system can be implemented to recover waste heat within households, from sewer systems or at treatment plants. This possibility was highlighted by the authors of [27], who investigated the feasibility of recovering heat from wastewater in Bologna, Italy, by analyzing varying flow and temperatures at several locations of the city's sewage system. The authors found that wastewater temperatures vary from 10 to 22 \({}^{\circ}\)C, proving to be especially advantageous during winter months, when there is a peak heat demand and sewage temperatures vary between 11 and 16 \({}^{\circ}\)C, while air temperature can drop below 0 \({}^{\circ}\)C. Heat recovery from wastewater was also researched by the authors of [28], who analyzed 27 design options for heat recovery heat exchangers that could be applied to sewage systems, as well as showed successful commercial projects that have been implemented in Germany, Japan and Switzerland. The authors highlighted that recovering waste heat from treatment plants is more efficient and technically feasible, although the distances between the plant and consumers usually pose a challenge. The authors of [28] also reported that temperatures for wastewater typically vary from 9 to 14 \({}^{\circ}\)C during winter and can reach up to 29 \({}^{\circ}\)C in summer.
## 4 Parametric Studies on Sv Wave Transmission through the Horizontal Layered-Structure Rock Slope  
### Parametric Study on Normalized Fracture Stiffness \(K\)  
In order to study the effect of normalized fracture stiffness \(K\) on dynamic response of the horizontal layered-structure rock slope, the dimensionless fracture spacing \(\xi\) is fixed at \(\xi=0.4\). Other parameters of the slope are the same as described above. The numerical simulation results of different parts of the slope are described below.  
In Figure 8, the horizontal coordinate is the normalized fracture stiffness \(K\), the vertical coordinate is the acceleration amplification coefficient of the slope crest \(\eta_{\text{crest}}\), which is defined by Equation (6). It can be found that \(\eta_{\text{crest}}\) decreases with the increase of \(K\), which may be caused by the increase of \(k_{s}\). Figure 9 shows \(\eta\) versus \(H\), where \(\eta\) is the acceleration amplification coefficient of monitoring points on the slope surface and \(H\) is the vertical distance of monitoring points on the slope surface to the horizontal coordinate. It can be found that \(\eta\) wavily increases with the increase of \(H\), and the peak values occur at \(H=7.5\) m, \(17.5\) m, and \(27.5\) m in turn, whereas the points near the bottom of joints (the valley values) are at \(H=12.5\) m and \(22.5\) m respectively, shown in Figure 9. In order to highlight the area we are most concerned about, only the dynamic response result of the part of the slope above its foot is given. Figure 10 shows the distribution regularity of acceleration amplification coefficient of the slope with different \(K\) (\(K=0.1\), \(0.5\), \(2\), and \(4\), respectively).  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Parameters**} & \multicolumn{6}{c}{**Value**} \\ \hline \(\xi\) & 0.01 & 0.0125 & 0.02 & 0.05 & 0.1 & 0.2 & 0.3 & 0.4 \\ \hline \(f\) (\(s^{-1}\)) & 2.89 & 3.61 & 5.77 & 14.44 & 2  
Figure 10: _Cont._  
Figure 9: The acceleration amplification coefficient of monitoring points on the slope surface with different \(K\) (\(K\) = 0.25 to 5) (where \(\zeta\) = 0.4).
## 4 Discussion
### Effect of Drought-Induced VOCs on the \(g_{\rm s}\) of Co-Located WWr  
Eight days after withholding water from the drought-stressed treatment vines, both the isolated (DS\({}_{\rm c}\)) and co-located (DS\({}_{\rm e}\)) Shiraz vines experienced severe drought stress as indicated by the low soil moisture content (\(\sim\)4%) and presented lower \(g_{\rm s}\) at PD compared to the well-watered treatment vines (Table 2). No significant changes were observed in the \(g_{\rm s}\) of the Shiraz receivers throughout the nine-day period of the present experiments. This was in contrast to observations from several other drought recovery experiments involving potted plants in greenhouses that reflected a synchronised decrease in \(g_{\rm s}\) between well-watered and drought-stressed Shiraz grapevines [30; 40]. It was hypothesised that the decrease in the \(g_{\rm s}\) of the well-watered vines was elicited by VOCs emitted from the neighbouring drought-stressed vines. It cannot, however, be excluded that changes in environmental conditions such as light, temperature [41], and vapour pressure deficit (VPD) [42] could have accounted for these fluctuations in \(g_{\rm s}\) in the well-watered plants. Parallel to these findings, in a study that investigated the effect of salt-induced VOCs in priming for defence responses in lima beans, [PERSON] et al. [18] reported a similar decline in the \(g_{\rm s}\) in the receiver plants co-located with salt-stressed plants. Their results suggested a possible role of methanol, terpen, and several GLVs as airborne signalling molecules for communication between plants during salt stress. The effect of VOC exposure of plants in triggering stomatal responses has been demonstrated with several VOCs such as the plant growth regulators MeJA and MeSA [26; 27; 28], as well as (Z)-3-hexen-1-ol and its esters [29], and several monoterpenes [25]. However, the lack of stomatal responses from the receivers (WW\({}_{\rm r}\)) in the current study may be related to the type and severity of stress, and/or the specific composition of the volatile \"cocktail\" that may have a bearing on the stomatal responses in the receivers.
# A Survey on LoRaWAN Architecture, Protocol and Technologies
## 2 LoRa & LoRaWAN Technologies
### MAC Layer--LoRaWAN  
LoRaWAN is a layer two protocol to provide LoRa end devices Adaptive Data Rate (ADR), Security, GPS-free Geolocation, Channel Access and Energy Saving functionalities. LoRaWAN is introduced by LoRa alliance [7; 48; 49; 50; 51]. By version 1.1 LoRaWAN supports roaming and adds additional security features to Class B (see Section 2.4.1 for LoRaWAN classes). Regional parameters are specified by a companion document [52].  
LoRa and other narrowband technologies have to be efficient that's any overhead will cost more energy or latency (frame air time Figure 8). To overcome this problem LoRaWAN uses a quite simple channel management strategy to keep end devices to be cost-effective. LoRaWAN adopts pure Aloha [7] with additional ACK mechanisms to simplify medium access control. MAC layer protocol defines one mandatory and two optional classes for different possible use cases and an overview of this class representations is presented in Figure 9.
# Application of Ultrafiltration for Recovery of Bioactive Phenolic Compounds from Rose Wastewater
###### Abstract  
The process of rose oil distillation generates a huge amount of waste byproducts, which often remain unused, and poses serious environmental challenges; at the same time, they contain polyphenols with antioxidant, antimicrobial, and therapeutic properties. The purpose of this work is to investigate the possible application of ultrafiltration using three polyacrylamidepharmaceu (molecular weight cut-off 1 kDa, 10 kDa, and 25 kDa) to recover the total polyphenic compounds, phenolic acids, and flavonoids from rose wastewater. The permeate flux, energy demand, contents of total polyphenic compounds, phenolic acids, and flavonoid phenolic compounds were determined during ultrafiltration at a volume reduction ratio of 2, 4, 6 and 8, and the rejections and concentration factors were established. The optimal operation conditions for permeate flux, energy demand, rejection, concentration factor, and antioxidant activity were established at a volume reduction ratio of 8, transmembrane pressure of 0.5 MPa, and 1 kDa membrane. These working conditions will be used in our future investigations to obtain extrudates from rice semolina enriched with ultrafiltered rose wastewater. Protocatechuic and vanillin acid, determined by HPLC, increased in the reentate when the 1 kDa membrane was used, while gallic acid, catechin, \(p\)-coumaric acid, rutin, hesperidin, and rosmarinic acid decreased.  
ultrafiltration; rose wastewater; bioactive phenolic compounds Article
# A Novel Searching Method Using Reinforcement Learning Scheme for Multi-UAVs in Unknown Environments
###### Abstract  
In this paper, the important topic of cooperative searches for multi-dynamic targets in unknown sea areas by unmanned aerial vehicles (UAVs) is studied based on a reinforcement learning (RL) algorithm. A novel multi-UAV sea area search map is established, in which models of the environment, UAV dynamics, target dynamics, and sensor detection are involved. Then, the search map is updated and extended using the concept of the territory awareness information map. Finally, according to the search efficiency function, a reward and punishment function is designed, and an RL method is used to generate a multi-UAV cooperative search path online. The simulation results show that the proposed algorithm could effectively perform the search task in the sea area with no prior information.  
multi-UAV; cooperative search; reinforcement learning; dynamic target +
Footnote †: journal: Applied Sciences
## 4 To Remove Titanium-Based Osteosynthesis Materials or not: A Present Debate  
The removal of titanium-based alloys used in maxillofacial osteosynthesis is still an open dispute. The causes that imply the use of osteosynthesis materials in maxillofacial surgery are multiple and the proper treatment targets the regain of various functions. Titanium devices are composed of titanium alloy or fully titanium that assure good biological and physical properties [100]. They have been used for rigid internal fixation and have been considered a 'gold standard' since 1978 [101]. However, sometimes complications did occur, such as infection, screw loosening, material exposure, dark staining of the local tissue, and chronic inflammation that determined the removal of the material. Still, the routinely removal of the titanium-based alloys used for osteosynthesis is a controversial matter. Several studies focused on outlining the negative influences upon the local and general health, suggesting that a new protocol regarding the management of the osteosynthesis materials should be taken into consideration. More authors consider that routine removal is mandatory in order to avoid potential implications. [PERSON] et al. [84] concluded that a certain immune-inflammatory response was present near the titanium materials that were used in the treatment of mandibular fractures, and the metallic particles that were released had a contribution to the persistence of the inflammation. Other authors speculated a potential carcinogenic effect of the titanium materials by presenting cases of malignant tumours of the surrounding tissue [102]. The retrospective study conducted by [PERSON] et al. [103] reviewed 2325 cases that were treated for maxillofacial fractures using titanium-based materials. Among these patients, 2162 (92.99%) did not have the titanium osteosynthesis materials removed and 163 patients had them removed for symptomatic (5.25%) and asymptomatic (1.76%) reasons. Taking into consideration that this study was based on a large number of patients and a long-term follow-up (ten years), the conclusion would be
# An Anonymous Offline RFID Grouping-Proof Protocol
## 7 Security Analysis and Comparison
### Security Analysis
#### 7.1.6 Resist to Eavesdrop Attack  
If the adversary eavesdrop the protocol, the message set it can collect is \(\{M\), \(T_{i}\), \(m_{i}\}\), all the information is transferred in the ciphertext. Without knowing the secret key of tag, the adversary cannot deduce the tag's identity and forge valid grouping-proof without scanning legal tags.
###### Abstract
Although this approach shows promise in detecting fake news, distinguishing between real news and articles that employ humor or satire may face challenges, as they often rely on linguistic subtleties and context-specific meanings. To address this issue, ref. [8] introduced an ensemble-based ML technique incorporating a deep neural network model for classifying fake news. However, many existing methods, including [19], rely on a single prototype embedding model. Such models often overlook polysemous terms, which pose multiple interpretations or meanings depending on the context [15]. The lack of multiple prototype embeddings for each can result in difficulties in accurately processing and understanding polysemous sentences [16]. The primary goal of this study was to identify the most effective approach for accurately classifying false information. The driving force behind this endeavor is the need to combat the widespread dissemination of misleading information and to maintain international peace by identifying and rectifying incorrect information. The major contributions of this research are as follows:  
* We propose a comprehensive fake news detection classifier for news article, considering the platform's unique characteristics and challenges. * We conduct experiments and analyze multiple ML and DL techniques to evaluate their performance on the fake news dataset, aiming to address the problem effectively. * Exploring various deep features, such as TF-IDF, n-gram, Word2 Vec, and global vectors for word representation (GloVe), to find the optimal combination that enhances the detection process and improves classifier accuracy. * Comparing diverse ML and DL techniques provides insights into their strengths and weaknesses for fake news detection, aiding researchers in making informed decisions about their applications. The remainder of the study is organized as follows. Section 2 discusses recent research studies relevant to fake news detection methods. Section 3 presents the proposed research methodology, deep features, diverse ML and DL methods, and their architecture to resolve the challenges of fake news detection. Section 4 presents a detailed empirical analysis of the model with comprehensive analysis. Finally, in Section 5, conclusions, implications, and future work are discussed.
# End-of-Life Scenarios for Mass Timber: Assumptions, Limitations and Potentials--A Literature Review
## 3 Results
### End-of-Life Scenarios: Reuse, Recycling, Energy Recovery and Landfill
#### 3.5.3 Incineration With/Without Energy Recovery  
Another common EoL scenario is incineration, which can occur with or without energy recovery. In many cases, incineration and energy recovery are presented separately, even though incineration is a broader term that may include energy recovery but does not always entail recovery or benefits. Incineration refers to the combustion of waste in incineration plants, while incineration with energy recovery, sometimes referred to simply as energy recovery, involves burning materials to release the embedded primary energy stored in wooden products, generating heat as a byproduct [41; 50]. During this process, stored carbon returns to the atmosphere as CO\({}_{2}\), along with smaller quantities of methane and nitrous oxide. Modern incineration technology, known as carbon capture and storage (CCS), can capture significant amounts of CO\({}_{2}\) generated during combustion and store it in underground facilities, preventing its release into the atmosphere [51]. Although the environmental impact of all other categories apart from GHG increases when CCS is implemented. The heat generated through incineration with energy recovery can typically be harnessed for other uses, offsetting GHG emissions from other systems [48]. Conversely, incineration without energy recovery releases heat into the environment without being utilized for any practical purposes [52].  
Incineration with energy recovery is currently the most assumed industry option for EoL of mass timber due to its competitive market situation [46]. It is also said to be a typical method for dealing with offcuts from CLT production [23]. Although being the most common practical EoL option today, this method is only discussed by 18 out of 56 scholars in this literature review.
# Theoretical Investigation of All Optical Switching by Intersystem Crossing
###### Abstract  
The dynamics of spin flips induced by the femtosecond laser are theoretically investigated in this article. The spin flips in this scenario are attributed to the intersystem crossing (ISC) described within the frame of the Rabi model. This new explanation is a step attempting to explain the mechanism of the all-optical magnetic orientation switching in the perspective of the conservation of the angular momentum and breaks of the selection rule, which is ignored in the Raman scattering related explanations. The final spin states discussed herein are closely related to the intensity of the incident laser and the ISC decay rate. The quantitative analysis of the relation between decay rate, temperature and the intensity of the laser is discussed.  
Keywords:intersystem crossing; spin-orbit coupling; all-optical switching; angular momentum +
Footnote †: journal: Applied Sciences
# Assessment of Injury Risk in Professional Soccer Players: A Long-Term Study
###### Abstract  
The aim of this study was to record and interpret external load parameters in professional soccer players in competitive microcyles with one or two matches per week, while investigating the interaction between training load and non-contact musculoskeletal injuries during training and matches. Musculoskeletal injuries in athletes are closely associated with workload fluctuations, particularly the acute:chronic workload ratio (ACWR) over preceding weeks. This study analyzed the physical workload of 40 high-level soccer players competing in the Greek championship across two seasons, encompassing 50 competitive microcyles, 60 official matches, and 300 training sessions. GPS-based assessments recorded total distance (TD), running speeds (15-20 km/h, 20-25 km/h, 25-30 km/h), accelerations (>2.5 m/s\({}^{2}\)), and accelerations (>2.5 m/s\({}^{2}\)). An independent sample \(t\)-test was conducted to compare injured and uninjured athletes, with statistical significance set at \(p<0.05\). Results showed that 20 injured athletes frequently exceeded the ACWR threshold (>1.3) compared to uninjured players. Analysis of the four weeks preceding the injury revealed that increased workload in high-intensity categories significantly contributed to non-contact injuries. Specifically, high running speeds of 15-20 km/h (\(p=0.015\)), 20-25 km/h (\(p=0.045\)) and >25 km/h (\(p=0.008\)), as well as accelerations (\(p=0.010\)), were linked to a higher risk of injury. The three-week ACWR model indicated statistically significant differences in the ACWR index for total distance (\(p=0.033\)), runs at 15-20 km/h (\(p=0.007\)), >25 km/h (\(p=0.004\)), accelerations (\(p=0.009\)), and accelerations (\(p=0.013\)). In the two-week model, significant differences were found in runs at 15-20 km/h (\(p=0.008\)) and >25 km/h (\(p=0.012\)). In the final week, significant differences were observed in runs at 15-20 km/h (\(p=0.015\)), >25 km/h (\(p=0.016\)), and accelerations (\(p=0.049\)). Additionally, running speeds of 25-30 km/h (\(p\) values between 0.004 and 0.016) played a key role in injury risk when limits were exceeded across all weekly blocks. These findings highlight the importance of monitoring ACWR to prevent injuries, particularly by managing high-intensity workload fluctuations in elite athletes.  
noncontact injuries; external load; soccer; GPS; ACWR 2025; 15, 5039
# Energy-Efficient LoRa Routing for Smart Grids
## 3 Proposed IoT-Based Communication in Smart Grid Environment
### Clustering
As a result, if node (\(i\)) was not a CH in the previous \([1/c]\) round, the threshold value will gradually increase. The condition for a node to be nominated as the cluster head is then specified in Equation (4). \[\aleph_{CH(i)}= \begin{cases}\aleph_{i}=1,&\text{ if }\Omega_{cdf(\ell)}< \lambda(i)\\ \aleph_{i}=0,&\text{ otherwise}\end{cases}  \tag{4}\]  
where \(\aleph_{CH(i)}\) denotes the number of CHs selected. Once the node is selected as a CH, it cannot become a CH again until all the nodes of the cluster have become cluster heads once. In this way, each node is given an equal opportunity to become a cluster head and an equal energy dissipation throughout the sensor nodes. 2. Set-up stage: After the selection phase, the announcement of CHs is made by the CH node broadcasting a small-sized message called an advertisement message (ADV) to all other non-CH nodes to form clusters. Each node selects the cluster head that is closest to them for communication regarding the received signal strength. A message is transmitted to that CH to be a member of a cluster when the node chooses its potential CH. The acknowledgements and time-division multiple access (TDMA) schedule are relayed by the CH node to its cluster member nodes. To avoid collisions, a time slot is allotted by TDMA to each sensor node. 3. Steady-state:Using TDMA, the sensed data are sent by the SN to the CHs in their time slots assigned by the CHs in steady-state usage. The CH collects the data and transmits them to the BS. In the process of transmitting the test packets to the destination, if the source and destination are separated by a huge distance, the data are transmitted via intermediate devices between the source and the destination. For that purpose, the optimal lightweight on-demand ad hoc distance vector routing (LOADng) protocol was used. In the case of a nearby destination, the proposed system creates multiple routing paths between the nodes.
## 2 Materials and Methods
### Fuzzy Similarity-Based MCDM  
The MCDM problem involves selecting the optimal option from a set of \(m\) alternatives, \(P=\left\{P_{1},P_{2},\ldots,P_{m}\right\}\), according to \(n\) criteria \(C=\left\{C_{1},C_{2},\ldots,C_{n}\right\}\), in which \(P_{i}=\left\{\left(C_{j},y_{ij}\right)\left|C_{j}\in C\right.\right\}\), \(y_{ij}\in[0,1]\) for all \(i=1,2,\ldots,m\); \(j=1,\ldots,n\). The relationship between \(m\) alternatives and \(n\) criteria can be represented in the form of a fuzzy decision matrix.  
\[D=\begin{array}{cccc}&C_{1}&C_{2}&C_{n}\\ &P_{2}&\left[\begin{array}{ccc}y_{11}&y_{12}&y_{1n}\\ y_{21}&y_{22}&y_{2n}\\ &y_{m1}&y_{m2}&y_{mm}\end{array}\right]\\ &P_{m}&\left[\begin{array}{ccc}y_{m1}&y_{m2}&y_{mm}\end{array}\right]\end{array}\]  
Next, TOPSIS was applied using the new similarity measure to solve this MCDM problem, as described in Algorithm 2.  
```
Step 1: Normalize the data table according to each criterion to obtain a fuzzy decision matrix. Step 2: Determine weight of each criterion. Step 3: Define the best option \(P^{+}=\left\{\left(C_{j},y_{ij}^{+}=\max\limits_{i=1,\ldots,m}y_{ij}\right) \middle|C_{j}\in C\right\}\) and worst option \(P^{-}=\left\{\left(C_{j},y_{ij}^{-}=\max\limits_{i=1,\ldots,m}y_{ij}\right) \middle|C_{j}\in C\right\}\). Step 4: Use Equation (2) to compute the similarity measures \(S_{i}^{+}\) and \(S_{i}^{-}\) for each alternative \(P_{i}\)\((i=1,2,\ldots,m)\) to identify \(P^{+}\) and \(P^{-}\), respectively. Step 5. Determine the close coefficient \(CC_{i}=\frac{S_{i}^{+}}{S_{i}^{+}+S_{i}^{-}}\)\((i=1,2,\ldots,m)\), whereby \(CC=\left\{\left.(P_{i},CC_{i})\middle|P_{i}\in P\right\}\right.\) can be considered the decision set of alternatives. Step 6. Rank \(P_{i}\prec P_{k}\) if \(CC_{i}\leq CC_{k}\) for all \(i,k=1,2,\ldots,m\).
```  
**Algorithm 2** The fuzzy similarity-based TOPSIS model