esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Structure and Function of Clostridial Binary Toxins  
### CDTb and Ib Oligomerization  
Oligomerization of CDTb and Ib occurs under certain conditions upon proteolytic cleavage of pro-CDTb (99 kDa) and pro-Ib (100 kDa) by trypsin or chymotrypsin at their respective N-termini [11; 12; 43]. During CDTb proteolysis, the signaling peptide (SD; residues 1-43) and the activation domain (AD; residues 44-211) are removed, producing active CDTb (75 kDa) that consists of residues 212-876 [11; 12], whereas the active form of Ib (80 kDa), after removal of its SD and AD, consists of residues 216-875 [14; 41]. Interestingly, sizing studies of active CDTb performed via sedimentation velocity analytical ultracentrifugation (AUC) and size-exclusion chromatography/multiangle light scattering (SEC-MALS) to determine the stoichiometry of CDTb oligomerization found monomeric CDTb to be the predominant species present in vitro (95 \(\pm\) 2%), with a novel di-heptameric macromolecular assembly (1.0 MDa) detected at lower levels (<4-6%) [11]. Subsequent addition of CDTa shifted the equilibrium towards the di-heptameric species (>25%). This was followed by single-particle cryoelectronic microscopy (cryo-EM) studies showing that, in the absence of CDTa and under soluble conditions with millimolar Ca\({}^{2+}\) ion concentrations, the only higher molecular weight species observed for activated CDTb were the di-heptameric oligomerization states [11]. They included two unique structures: (1) Asymmetric CDTb (AsymCDTb), where one of the CDTb heptamers hasan extended \(\beta\)-barrel domain (\(\beta\)BD; residues 298-401) while the other is in the prepore state, and (2) symmetric CDTb (\({}^{\mathrm{Sym}}\)CDTb), where both CDTb heptamers are in the prepore state (Figure 4) [11]. These findings are a deviation of the heptameric or octameric (in respect to anthrax toxin PA) assemblies that binary toxin B subunits typically form. It is hypothesized that these di-heptamers represent a mechanism employed by CDTb to protect its central core against proteolytic cleavage by extracellular enzymes and/or evade host immune responses [11; 12; 13]. Regardless of whether CDTb is in the asymmetric or symmetric conformation, both share a unique central, donut-shaped assembly consisting of an interface between the receptor-binding domain 2 (RBD2) domains of one heptamer with the RBD2 domains of the other [8; 11; 15]. Despite the presence of an RBD2 analogue, this donut-shaped assembly has yet to be observed in the iota toxin.
## 2 Indoor and Outdoor Thermal Environment  
### Field Survey and Testing of Solar Buildings  
The winter in Lhasa is cold and the local residential buildings are in the heating period from November 15 th to March 15 th of the following year. To obtain the characteristics and current situation of the local solar houses in the Lhasa area, a field survey was conducted from December 26 to 30, 2016. A typical local single-story rural single-family house (Figure 1) was selected to be tested and surveyed in Lhasa area. The testing building is a traditional north-south oriented passive solar building. The main rooms are located in the south, and the auxiliary rooms in the north. The building envelope parameters were measured, as well as the space layout, indoor and outdoor thermal environment, etc. The survey results show that the 500 mm thick adobe walls delimit the indoor and outdoor space, the living room and the kitchen are separated by a thin plate, and the remaining inner partition walls are 500 mm thick adobe walls. Single glazed windows and wooden doors are used and the exterior walls are painted white. The window-to-wall ratios for the south, east, and north directions are 0.42, 0.20, and 0.10, respectively.  
Figure 1: Images of the measured rural building in Tibet.  
A field measurement was conducted to obtain the indoor and outdoor thermal environment parameters. For the indoor air temperature measurement, the position of the room center 1.5 m from floor was selected as the representative measurement point. The location of the measurement point of the outdoor thermal environment parameter was set in an open space near the testing building. More specifically, the test point of the outdoor air temperature was placed at a position that was not exposed to sunlight and was at a height of 1.5 m from the ground. Measurement of solar radiation intensity was carried out in an open space without any shade. The measuring points of the indoor air temperature were arranged as shown in Figure 2.  
A 175-H1 type self-recording high precision temperature meter with an accuracy of 0.1 \({}^{\circ}\)C was selected for the measurement of the indoor and outdoor air temperature. All the indoor and outdoor thermal environment parameters were measured and recorded every 10 min. The geometric sizes of building and envelope were measured using a laser distance meter. The main information about the testing process is shown in Table 1.
# ICENET: An Information Centric Protocol for Big Data Wireless Sensor Networks
## 4 ICENET--Information Centric Protocol for sEnsor NETworks
### ICENET Architecture  
The ICENET protocol stack is shown in Figure 8. Communication at the Physical (PHY) and Medium Access Control (MAC) layers are supported by IEEE 802.15.4 [38], which is the standard protocol for communication at lower layers in IoT architectures. The 6 LoWPAN adaptation layer [50] allows the transmission of IPv6 packets over IEEE 802.15.4, whose most pertinent functionalities are compression, fragmentation, and reassembly of IPv6 packets. The reason for choosing UDP as transport protocol is to avoid the overhead and complexities of TCP. Moreover, since ICENET has its own reliability mechanism suitable for WSNs, the reliability functions of TCP are not necessary.
# Smart Recommendations for Renting Bikes in Bike-Sharing Systems
## 5 Evaluation of User-Centred Recommendation
### Simulation Experiment Setup
Given the ranking, the user filters out all stations that they have already tried. If no stations are left, the user will abandon the system without renting a bike. Otherwise, they walk towards the first station in the list of recommendations in order to rent a bike;
4. In case the user gets to a station and there are no available bikes, they repeat the whole process until they either abandon the search or finally find a bike. In this case, the value of the maximum acceptable distance (\(md\)) is reduced by the distance the user has walked already. With this behaviour, a user will effectively abandon the system if they do not find any bikes within \(md=600\) m.  
For finding a return station, the process is as follows:  
1. In the moment a user \(u_{k}\) has rented a bike at a station \(s_{i}\), they issue a return request \(return_{k}=\langle l_{k},t,l_{d}\rangle\), where \(l_{k}\) and \(t\) are the current position and time, and \(l_{d}\) is their final destination location;
2. The recommendation system returns a ranking of stations for returning the bike;
3. Given the ranking, the user filters out any stations that they have already tried, and selects the first remaining station for returning the bike;
4. In case the user gets to a station and there are no available slots, they repeat the whole process until they finally find a station to leave the bike (there is no possibility to abandon the attempt).
## 6 Scheduling Algorithm Performance Test Using TLS-VaD
### Experimental Scenarios  
The experiment uses TLS-VaD as a tool to analyze the performance of the scheduling algorithms applied to network topologies that increase in dimension from 10 to 100 nodes, in increments of 10. In the meantime, starting from a network of 50 nodes, node addition is done in two ways, horizontal and vertical increments. With horizontal increments, network nodes are increased by adding children to the master node, whereas with vertical increments, network nodes are increased by adding new leaf nodes. The two types of node additions are illustrated in Figure 36.  
Therefore, to get a performance comparison between IRByTSA, FTSA, and FLSA, the algorithms are applied to a network with two scenarios. In the first scenario, the scheduling algorithm is applied to a network that grows horizontally, and in the second scenario it is applied to a network that grows vertically. To collect all data at the master node, networks that increase in size vertically will require more cycles and timeslots than networks that increase horizontally. This happens because with vertical increase, the number of child nodes of the master node does not increase when the network dimensions increase, which will cause a bottleneck in the network. Thus, if a scheduling algorithm can show good performance in the second scenario, it indicates the reliability of the algorithm. In this test, we will see which of the scheduling algorithms (IRByTSA, FTSA, or FLSA) can produce the minimum number of active timeslots (\(\lambda\)), duty cycles (D), and cycles (C). The tests were performed using slotframe sizes of 200 timeslots.
# The Optimization of Covert Communication in Asymmetric Jammer - Assist Systems
## 2 System Model
### Transmission Scheme  
Alice encode a message \(M\) into a codeword \(D^{n}=\left[D_{1},...,D_{n}\right]\in\mathbb{C}^{n}\) by random coding generation and \(i\)-th symbol \(D\) is independently drawn from \(\{-\beta,\beta\}\) with equal probability [5; 31]. The codeword \(D^{n}\) is generated independently and identically distribution (i.i.d.) randomly as follows:  
\[\mathbf{P}(D^{n})=\prod_{i=1}^{n}P_{D}(D_{i}). \tag{5}\]  
[PERSON] employs his contextual understanding to decode the covert messages, based on the observation of \(Z_{b}^{n}=\left[Zb,1,...,Zb,n\right]\in\mathbb{C}^{n}\). The quantification of the transmission rate is accomplished through the assessment of mutual information between the discrete input \(D^{n}\) and the channel output \(Z_{p}^{n}\), which is given by  
\[\mathbb{I}(Zb^{n};D^{n})=\mathbb{I}(Zb,1,...,Zb,n;D_{1},...,D_{n}). \tag{6}\]  
[PERSON] possesses knowledge regarding the construction of the codebook, i.e., \(\{-\beta,+\beta\}\), and he receives the symbols corrupted by AWGN. Then, we give the following joint distribution of \(Z_{b}^{n}\) and \(D^{n}\) as follows:  
\[P(Z_{b}^{n}D^{n})=\mathbf{P}_{D}^{n}(D^{n})\times W_{Z_{b}^{n}|D^{n}}(Z_{b}^{n }|D^{n}). \tag{7}\]  
where  
\[P_{Z_{b}^{n}D^{n}}(x,y) =\frac{1}{2}\frac{1}{2\pi\sqrt{\sigma_{b,x}\sigma_{b,y}}}\Bigg{[} \exp\bigg{(}-\frac{(x+h_{b,x}\beta)^{2}}{2\sigma_{b,x}^{2}}-\frac{(y+h_{b,y} \beta)^{2}}{2\sigma_{b,y}^{2}}\bigg{)}\] \[+\exp\bigg{(}-\frac{(x-h_{b,x}\beta)^{2}}{2\sigma_{b,x}^{2}}- \frac{(y-h_{b,y}\beta)^{2}}{2\sigma_{b,y}^{2}}\bigg{)}\Bigg{]}, \tag{8}\]  
with \(h_{b,x}\) and \(h_{b,y}\) denote the channel coefficient of complex value \(h_{b}\) on \(x\)-axis and \(y\)-axis, \(\sigma_{b,x}^{2}\) and \(\sigma_{b,y}^{2}\) denote the variance of the complex Gaussian noise at [PERSON] on the \(x\)-axis and \(y\)-axis.
## 5 Measurement Equipment and Testing Setup
### Sensor Location in the Building  
Before strengthening, the soil was examined, and in the beginning, the foundations were strengthened, and one sensor was located on the ground. Before beginning the construction works related to the building strengthening and upgrading, 4D and 3D sensors were installed. The sensors were placed on the roof and ground floors of the existing building as well as on the ground outside the building (Figure 3). As the upgrading works progressed, the sensors were located on the top floor after completing the ceiling of each floor.  
At each stage of the building strengthening and upgrading, the building's velocities were recorded for 7 days. After analyzing the recorded data, it was decided to use mainly the 3D sensors since their sensitivity was higher by about 3 orders of magnitude.  
Figure 3: Location of sensors inside and outside the building. Sensor 1—on the ground, 10 m from the building, sensor 2—on the ground floor, sensor 3—on the top floor.  
This allowed for measuring micro-vibrations due to traffic loading and investigating the measured signal.  
Experimental and Numerical Evaluation of the Building's Dynamic Characteristics in Each Stage of Its Strengthening and Upgrading
## 3 Discussion and Assessment of Future Application Areas
Additionally, a large degree of electricity supply blackout resistance provided by on-site distributed generation using these building-material-integrated PV can be expected, provided that suitable battery storage systems are installed. Other expected future application areas of highly transparent energy-generating construction materials and solar windows will likely include roof-top canopies, balcony glazings, skylights, and airport roofs.
# RDSP: Rapidly Deployable Wireless Ad Hoc System for Post-Disaster Management
## 4 Performance Evaluation
### Deployment Environment  
A multihop communication network is deployed in Comsats university Islamabad-attack campus as shown in Figure 8.  
The total area of the university is 153,000 m\({}^{2}\). As shown in the figure, the server device is installed at point S and the client device is installed at point C. The relays are deployed all over the area in a manner to establish four different paths between server device S and client device C. The first path defined by points C, Y, Z, S contains 7 relays, second path defined by points C, Z, S contains 6 relays, third path defined by points C, S contains 5 relays and fourth path defined by points C, X, S contains 8 relays. The relays are placed at fixed positions at equal distance of 90 m. To find the shortest paths between the client and server devices, the proposed RDSP system utilizes DIA and MMN algorithms whereas the UF scheme uses Destination-Sequenced Distance Vector (DSDV) [28] routing algorithm. In the DSDV, each node maintains a routing table with routes to destinations. An entry for a given destination consists of the ID of the next-hop, total hops to the destination, route's sequence number, and the time for the recent route update. In the case of the proposed RDSP, each node periodically broadcasts a hello message every 2 s containing only the node ID. However, in the UF scheme, each node periodically broadcasts an entire routing table every 1 s containing the route destination, the advertising node's next-hop node for that route, the number of hops to the destination, and the sequence number. Following the deployment of the multihop communication system, both the client device and server device are tested to communicate wirelessly with each other across all four paths.  
Figure 7: Sample network deployment scenario.  
One hundred request messages were generated to collect the results for each path. The experiment duration was set at 550 s. The results presented for each path are averaged over 5 repeated experiments. The experimental parameters are summarized in Table 1.
## 3 Pre-Processing of Multi-Sensor Data from the Unmanned Ship
### System Modeling
#### 3.1.3 Multi-Sensor Data Definition for the Unmanned Ship  
In order to facilitate the description of the subsequent algorithm, the following data definition was carried out in this paper: The data collected by the sensor or the known data was defined as the measurement data, which involves the reference node coordinates \((x^{R},y^{R})\) in the ZigBee system and the geodetic coordinates \((B,L)\) collected by the GPS/BD system. The data obtained by calculation and conversion was defined as positioning data, which involves the coordinates of blind nodes \((x^{z},y^{z})\) in ZigBee system, and the plane positioning coordinates \((x^{G},y^{G})\) and \((x^{B},y^{B})\) in GPS/BDS system. The GPS positioning data set was defined as \(\mathbf{H}^{S}=\{h_{1}^{S},\,h_{2}^{S},\,\ldots,\,h_{n}^{R}\}\), the BDS positioning data set as \(\mathbf{H}^{b}=\{h_{1}^{b},\,h_{2}^{b},\,\ldots,\,h_{n}^{b}\}\), and the ZigBee blind node positioning data set as \(\mathbf{H}^{a}=\{h_{1}^{z},\,h_{2}^{z},\,\ldots,\,h_{n}^{z}\}\), where \(h_{i}^{z}=(x_{i}^{z},y_{i}^{z})\), \(h_{i}^{S}=(x_{i}^{G},\,y_{i}^{G})\), \(h_{i}^{b}=(x_{i}^{B},\,y_{i}^{B})\) are the \(i\)th positioning data in the ZigBee GPS, and BDS data sets, respectively, \(i=1\), \(2\), \(\ldots\), \(n\).
## 4 Results and Discussion
### Comparative Performance Analysis
When the position obtained from map matching was used to correct SINS/OD, the position obtained from SINS/OD/MM converged significantly, as shown in Figure 14. As shown in the heading attitude angle in Figure 15, the train makes a big turn at 500 s, at which time the northward position error turns from negative to positive, and thereafter, the position error stays within 10 m until 2000 s, which is a significant improvement compared to the position error of SINS/OD that was dispersed all the time, illustrating the validity of the proposed SINS/OD assisted by the digital map of the track. Combined with Figures 9 and 15, after 2500 s, the train's movement state is close to being in a uniform linear state,  
Figure 11: Comparison of combined SINS/OD navigationally solved trajectories and ground truth overlays. Figure 12: Comparison of latitude, longitude, and ground truth overlays for the combined SINS/OD navigation solution. and at this time, the position error is slowly increasing, which is mainly due to the fact that the projected map-matching method can well constrain the lateral error of the train, and the longitudinal error will still be affected by the cumulative effect of the error such as the OD scale factor. And after the train is in a uniform straight-line state, according to the observability theory analysis results, the zero heading deviation was still not observed; at this time, the attitude error will be further transferred to the position error of SINS/OD. However, using the map-matching position proposed in this paper to significantly reduce the speed of the position error dispersion, the eastward and northward position errors at the end of navigation are \(-23.82\) m and \(3.13\) m, respectively, and the detailed results are shown in Table 2.  
Figure 14: SINS/OD/MM navigation solves position errors. Figure 13: SINS/OD navigation solves position errors.
## 4 Empirical Insights from Sectorial and Regional Studies
### AI Synergies and Revenue Growth in European SMEs
#### 4.2.2 A Comprehensive Systematic Literature Review [112]  
This systematic review provides valuable information on the challenges that SMEs face when adopting AI, specifically within the industrial sector. Based on a PRISMA-guided analysis of 71 studies, the review identifies 27 distinct challenges and organizes them using the PESTEL framework. These findings directly align with the TOE-DOI lens applied in this article, particularly highlighting technological and organizational barriers such as lack of digital maturity, data availability and quality, and insufficient AI knowledge. In particular, more than 90% of SMEs reported having no AI applications in place, and knowledge gaps were cited in 35 of the studies analyzed, emphasizing the critical role of internal readiness (TOE: Organizational).  
In terms of technological readiness, poor IT infrastructure and fragmented data practices were frequently mentioned, while social challenges such as management skepticism and low acceptance of AI surfaced as major inhibitors. Quantitative indicators such as low ROI visibility and high risk of failure were also emphasized, especially in cases where AI implementation lacked strategic alignment or adequate planning. This review reinforces the complexity and interdependence of SME-specific constraints, underscoring the urgent need for tailored support structures to bridge the adoption gap between SME and AI.
## 2 Finite Element Model and Working Conditions  
### Model Establishment  
Shield tunnel excavation is a complex process. To enhance the precision of the model's results and ensure the fidelity of the simulation, the following assumptions are postulated in the model:  
* Segments are prefabricated and assembled, and the joint is easily affected to reduce the strength of the lining. The relevant researchers have studied the stiffness efficiency value between 0.6 and 0.8 [33; 34]. The stiffness reduction is used to reduce the strength of the segment by 20%.
* When the shield machine is excavated, the face will be affected by the earth pressure, so the excavation pressure should be applied to the soil of the excavation face to simulate the support pressure of the shield.
* The lining segment is 1.5 m wide and 0.3 m thick. In the simulation, the length of the two rings, namely 3 m, is used as an excavation step.
* In the simulation, the length of the shield machine is defaulted to 9 m, namely three excavation steps, and the lining and grouting layer are added in the fourth excavation step.
* The soil material model adopts the Mohr-Coulomb model; the lining segment and grouting layer material model adopts the elastic constitutive model.
# Assessment of Word-Level Neural Language Models for Sentence Completion +
###### Abstract  
The task of sentence completion, which aims to infer the missing text of a given sentence, was carried out to assess the reading comprehension level of machines as well as humans. In this work, we conducted a comprehensive study of various approaches for the sentence completion based on neural language models, which have been advanced in recent years. First, we revisited the recurrent neural network language model (RNN LM), achieving highly competitive results with an appropriate network structure and hyper-parameters. This paper presents a bidirectional version of RNN LM, which surpassed the previous best results on Microsoft Research (MSR) Sentence Completion Challenge and the Scholastic Aptitude Test (SAT) sentence completion questions. In parallel with directly applying RNN LM to sentence completion, we also employed a supervised learning framework that fine-tunes a large pre-trained transformer-based LM with a few sentence-completion examples. By fine-tuning a pre-trained BERT model, this work established state-of-the-art results on the MSR and SAT sets. Furthermore, we performed similar experimentation on newly collected cloze-style questions in the Korean language. The experimental results reveal that simply applying the multilingual BERT models for the Korean dataset was not satisfactory, which leaves room for further research.  
BERT; bidirectional RNN; cloze test; Korean dataset; machine comprehension; neural language model; sentence completion +
Footnote †: This paper is an extended version of our paper published in the proceedings of 2018 IEEE International Congress on Information Science and Technology (CiSt).