esa-sceva/satcom-chunk-collection huggingface dataset:
# A Multi-Source Consistency Domain Adaptation Neural Network MCDANN for Fault Diagnosis
## 2 Proposed Model
### Mcdann  
Subdomain Division and Alignment  
In the process of domain adaptation network training, when the adversarial loss and feature distance are small enough and the network approaches convergence, there are still many errors in fault identification in the target domain, and the classification accuracy remains at a certain level for a long time. If the ground truth and predicted labels are printed, it can be observed that the model will always misidentify one type of fault as another.  
Therefore, [PERSON] [36] proposes to divide the original domain into several sub-domains according to the similarity of the samples, and then align the corresponding sub-domains from the source and target domains, as shown in Figure 4.  
Based on the idea of sub-domain adaptation, this paper uses data labels as the basis for sub-domain division and aligns the features of the source domain data and the target domain data with the same label. Since the target domain is unlabeled in the training  
Figure 3: Application of MK-MMD distance.  
process of domain adaptation, we use the predicted pseudo-label of the target domain to align with the real label of the source domain. The label classifier obtained by supervised training on the source domain is used to predict pseudo-labels of the target domain's data; afterward, these pseudo-labels were used to correspond to the real label of the data from the source domain, finally divide these two domains into sub-domains according to the labels and align every two subdomains having the same labels which come from the source domain and target domain, respectively.  
After aligning the subdomains, the distance loss is changed from Equation (6) to the Local MMD distance (LMMD) shown in Equation (8):  
\[d_{k}^{2}(p,q)=\frac{1}{C}\sum_{c=1}^{c}\left\|\sum_{x^{i}\in D_{i}}w_{i}^{sc} \varphi(x_{i}^{s})-\sum_{x^{i}_{j}\in D_{i}}w_{j}^{lc}\varphi\Big{(}x_{j}^{t} \Big{)}\right\|_{H_{k}}^{2} \tag{8}\]  
Among them, \(c\) represents the label, and \(w\) represents the weight. In this paper, since the label is used as a subdomain, the definition of the weight is shown in (9):  
\[w_{i}^{sc}=\frac{y_{ic}}{\sum_{\big{(}x_{j},y_{j}\big{)}\in D}y_{jc}} \tag{9}\]  
However, this method relies on the predicted label from the classifier. The weight update of the label classifier still only relies on the source domain data, while no constraints are imposed on the target domain data. Since the target domain data does not have real labels that can be used to test the correctness of the predictions, it is difficult to correct the predicted labels of the classifier for data from the target domain.  
Therefore, using the pseudo-label method cannot really solve the problem of domain mismatch. In the bearing data studied in this paper, using the LMMD distance is even less effective than using the MK-MMD distance. In order to improve the accuracy of pseudo-labels, a multi-source domain adaptation method is introduced in this paper.
## 5 Conclusions  
Our study showed that multiparametric ultrasound evaluation of focal breast lesions is feasible and may increase their characterization. In particular, the semi-quantitative evaluation with SR significantly improves the diagnostic performance of the BI-RADS classification, having the association SR + experienced radiologist + \"SmartBreast\" with, in our study, a sensitivity of 0.99, while SR alone had a sensitivity of 0.81 and a specificity of 0.86. The semi-automatic \"SmartBreast\" Resona R9, Mindray software showed a good agreement with the investigator in our preliminary results, considering size ([PERSON]'s correlation coefficient of 0.90, \(p\) = 0.07), shape, vascularization, and posterior features during nodule evaluation ([PERSON]'s k of 0.6, 0.65, and 0.94, respectively), except for the margins, echo pattern, and orientation ([PERSON]'s k of 0.33, 0.48, and 0.28, respectively). The automatic analysis, therefore, did not statistically increase the diagnostic performance, either alone or in association with elastographic methods, but it could have a role in guiding and training young, less experienced radiologists.  
Further studies are needed to validate the results of our work, taking into consideration a greater number of breast lesions in multicenter studies.  
**Author Contributions:** Conceptualization, O.G., V.C., L.B., F.P. and V.R.; methodology, V.C., O.G., A.R. and F.P.; software, V.C. and O.G.; validation, V.C., O.G. and C.D.V.; formal analysis, C.D.V. and O.G.; investigation, O.G. and V.C.; resources, M.V., F.P., L.B., L.C., F.T., V.R. and A.S.; data curation, O.G.; writing--original draft preparation, O.G., A.R. and D.F.; writing--review and editing V.C., M.V., G.V., C.C., M.D.S. and V.R.; visualization, O.G.; supervision, V.C.; project administration, V.C. and M.V. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The study was conducted in accordance with the Declaration of Helsinki.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
## 3 Underwater Routing Protocols
### Smic  
The sink mobility with incremental cooperative (SMIC) routing protocol considers the amplify and forward cooperative routing strategy to send packets from a source to a destination [28]. The relay is selected based on its residual energy, depth and quality of the link. A mobile sink gathers data packets from the destination nodes. The protocol shows improved performance in terms of packets received by the sink and network lifetime. However, the use of cooperative routing involves high energy consumption because a source node and a relay node both send the same data packets to a destination node (cooperative routing).
# Recent Developments in Materials Science for the Conservation and Restoration of Historic Artifacts
## 2 Inorganic Nanomaterials in Cultural Heritage Conservation
### Application of Inorganic Nanomaterials
#### 2.2.1 Consolidation of Artifacts  
Inorganic nanomaterials find application in a wide range of consolidation procedures, including both inorganic and organic support materials. For example, nanoparticles such as calcium hydroxide (Ca(OH)\({}_{2}\)) and hydroxyapatite have been used to consolidate deteriorated stone structures. Their small size allows for deep penetration into the substrate, effectively bonding with existing materials and restoring structural integrity [20; 21]. Particularly, the application of hydroxyapatite (and hydroxyapatite derivatives) nanoparticles for the consolidation of stone artifacts (especially calcareous stone) represents a subject of intense studies in recent years and is also the main focus of several recent review works [22; 23].  
Another particular application of inorganic nanomaterials is represented by the conservation of fragile artifacts of organic nature. Hydroxyapatite nanoparticles have been utilized to deacidify paper artifacts, preventing degradation caused by acidic environments. This application has shown promising results in preserving historical documents [24]. Another widely applied class of inorganic materials (hydroxides, in particular calcium and magnesium hydroxide) were proposed for the curative/preventive treatment of archaeological (waterlogged) wood, with their use leading to the adjustment of the pH level to almost neutral values [25].
## 4 Discussion
### Future Directions
#### 4.5.1 Multimodal and Specialized Models  
One major focus involves training multimodal models capable of interpreting medical images such as X-rays or MRIs and integrating these findings with textual data for more comprehensive clinical decision support. By coordinating multiple specialized models, e.g., a retriever for information extraction, a summarizer for condensing relevant data, and a rule-based component for validation, JAVIS can deliver robust and safe results. Early efforts demonstrate promise; for instance, over 10,000 medical records have already been labeled using the JAVIS API, showcasing the framework's potential for large-scale text labeling and retrieval.
## 3 Results and Discussion
### Shear Behavior  
Figure 7 shows the shear stress vs. distortion curves of the BVE (Figure 7a) and BVEL resins (Figure 7b), which showed an initial approximately linear behavior, followed by a non-linear response up to failure characterized by a stiffness reduction with increasing shear stress, typical of polymeric resins; however, this nonlinearity was less pronounced in some of the BVEL specimens, once more being indicative of potentially increased heterogeneity in the polymer structure of this resin. Table 7 summarizes the shear strength, shear modulus (calculated for shear strains between 0.25% and 0.65%, as per ASTM D5379/D5379M) and the ultimate distortion of both resins. The results show that the addition of lignin led to an increase in the average values of the shear properties of the bio-based resin: 4% for shear strength, 11% for shear modulus, and 4% for ultimate distortion. These improvements are consistent with those obtained in the tensile tests, and overall should stem from the same reasons mentioned there.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Resin**} & \multirow{2}{*}{**Specimen**} & \multicolumn{2}{c}{**Tensile**} & **Tensile** & **Ultimate Strain** \\  & & **Strength (MPa)** & **Modulus (GPa)** & **(\%)** \\ \hline \multirow{8}{*}{BVE} & 1 & 45.0 & 3.40 & 1.49 \\  & 2 & 50.9 & 3.31 & 1.86 \\  & 3 & 57.9 & 3.39 & 2.21 \\  & 4 & 52.1 & 3.25 & 1.92 \\  & 5 & 48.9 & 3.44 & 1.70 \\ \cline{2-5}  & \multirow{2}{*}{Average} & 51.0 \(\pm\) 4.7 & 3.36 \(\pm\) 0.08 & 1.84 \(\pm\) 0.27 \\  & & (CoV = 9\%) & (CoV = 2\%) & (CoV = 15\%) \\ \hline \multirow{8}{*}{BVEL} & 1 & 67.4 & 3.43 & 2.56 \\  & 2 & 70.4 & 3.18 & 3.05 \\ \cline{1-1}  & 3 & 57.2 & 3.08 & 2.41 \\ \cline{1-1} \cline{2-5}  & \multirow{2}{*}{Average} & 65.0 \(\pm\) 6.9 & 3.23 \(\pm\) 0.18 & 2.67 \(\pm\) 0.33 \\ \cline{1-1}  & & (CoV = 11\%) & (CoV = 6\%) & (CoV = 13\%) \\ \hline \hline \end{tabular}
\end{table}
Table 6: Tensile test results (average \(\pm\) standard deviation and coefficient of variation (CoV)).  
Figure 6: Tensile test results: axial stress vs. axial strain curves obtained for **(a)** BVE and **(b)** BVEL resins.
## 4 Discussion
### Implication for Ribonucleoside Exogenous Delivery  
Mineralogical analysis of carbonaceous chondrites concluded that hydrothermal conditions could be found in asteroid parent bodies [48; 49]. Indeed, if ribonucleosides could be present in extraterrestrial samples, they needed to be synthesized and be able to persist during their journey. Hydrothermal wet-dry cycles have been proposed as one of the sources of prebiotic ribonucleotides [3]. Depending on the accreted amount of aluminum, planetesimal hydrothermal conditions would inevitably stop, giving rise to a \"freeze-icy\" body. Due to radiation (or other energy source), \"freeze-thaw\" cycles could occur, which are known for promoting the accumulation and oligomerization of RNA [50]. Once formed, ribonucleosides could be stabilized by inorganic ions (or minerals) bonding to the sugar moiety (e.g., the formation of borate-ester species) [7] or accumulate in macrostructures (e.g., hydrogels), enhancing their stability [51]. Planetesimal impact would give rise to asteroids and other extraterrestrial rocky bodies, inevitably inducing chemical transformations into organic matter (e.g., cyclization, decomposition, and agglomeration, among others) [23; 52; 53], as for ribonucleoside/ribonucleotide degradation. Further mechanochemical energy, from atmospheric entry, would induce more modifications, originating organic matter detected and analyzed in meteorites [8; 54; 55].  
Following [PERSON] et al. [8] results, Table 1 comprises the concentration of purine and pyrimidine nucleobases in Murchison, Murray, and Tagish Lake meteorites. The reported content of purines is typically higher than pyrimidines, which, curiously, goes along with the reactivity of ribonucleosides in this study (see Figures 1 and 2). It's known that pyrimidine's ribonucleoside photostability to cosmic rays is lower than purine analogs [15], which could inevitably affect its abundance. In addition to that, the availability of soluble organic molecules (SOM) in meteorites is often related to the implemented extraction methodology. Previous approaches used 95% formic acid solutions at 100 \({}^{\circ}\)C [56], which inevitably decomposed more reactive molecules (e.g., adenine and guanine could be converted into xanthine and hypoxanthine, respectively) [56]. In this case, the acidic media and temperature would inevitably affect ribonucleoside stability. Softer approaches enabled the detection of more reactive species, such as pyrimidines and their isomers [8]. If canonical ribonucleosides (guanosine, adenosine, cytidine, and uridine) would be present among these samples, the \"state-of-art\" extraction methodologies (Table 1) should be tested, and a smaller amount compared with nucleobases should be expected.
## 4 Performance Evaluation
### Evaluation Setup
#### 4.2.2 Simulation Scenario  
The performance of both protocols was evaluated considering a highway scenario with two lanes for cars travelling in one direction and other two lanes for cars travelling in the opposite direction. The length of each lane was set to 3 km and the width to 4 m. When a vehicle reaches the end of the road, it is reinserted in the lane with vehicles traveling in the opposite direction. The maximum allowed speed was set to 60 m/s. The radio channel propagation model introduced in [37] was implemented in the simulation setup. Both protocols were tested considering this model which, as previously mentioned, was specifically developed for V2V highway scenarios. Additionally, performance metrics for both protocols were obtained considering the freespace propagation model. The mobility pattern for each vehicle was generated following the intelligent driver model introduced in [66]. This is a popular model used to generate mobility patterns for highway and urban scenarios, (e.g., [50,72]). Furthermore, as the vehicles acceleration is an important parameter that could modify the network topology [21], both protocols were evaluated under various maximum vehicle acceleration rates ranging from \(\alpha=1.6\) m/s\({}^{2}\) to \(\alpha=5\) m/s\({}^{2}\). Free flow, medium, high and jam vehicle densities were considered in order to evaluate the effects of the vehicle density, \(\lambda\), in the routing metrics. The specific value of \(\lambda\) for each density was taken from [67] as shown in Table 1. The adapted IEEE 802.11a/p model with data rate of 6 Mbps was considered for the vehicle transceiver. The performance metrics for each protocol were obtained considering four transmitters. At the beginning of every simulation trial, every transmitter is set to wait for 5 s before starting any transmission. This 5 s period was set to better allow the exchange of hello messages. When the waiting period concludes each transmitter chooses a random starting time and a random destination node. Once a vehicle starts transmitting, it generates packets for an equivalent user data rate of 2 Kbytes per second. This data rate is maintained during the entire simulation. A minimum of 100 trials were performed for each acceleration-density pair. Each trial lasted 300 s during which different performance metrics were recorded. The particular values of each variable used in the simulation are presented in Table 1.  
\begin{table}
\begin{tabular}{c c} \hline
**Parameter** & **Value** \\ \hline Maximum Velocity & 60 m/s \\ Maximum Acceleration & [1.6–5.0] m/s\({}^{2}\) \\ Vehicle Density & [33,66,100,133] vehicles/km \\ Highway Length & 3,000 m \\ Number of Lanes & 4 \\ Mobility Model & IDM \\ Simulation Time & 300 s \\ Packet Size & 2 Kbytes \\ Base Frequency & 5.880 GHz \\ Data Rate & 6 Mbps \\ Transmission Range & 300 mts \\ \hline \end{tabular}
\end{table}
Table 1: Specific values used for each variable in the simulation scenario.
## 3 Results
### Performance of Classical Ross-Macdonald Parameters in Heterogeneity-Driven Scenarios  
We determined the combined influence of ivermectin treatment on two important Ross-Macdonald model classical metrics, at different levels of heterogeneity affinity: the annual entomological inoculation rate (EIR), defined in Equation (7), and the basic reproductive number (\(R_{0}\)), at different levels of heterogeneity (Figure 8a,b).  
As expected, mosquito mortality progressively increases with higher percentual use of ivermectin in the general population. When the ivermectin treatment rate reaches the value of 0.20, i.e., nearly 93% of all mosquito deaths occur during the 10 days after the initial blood meal, when the parasite is still developing into the next transmissible form, explaining the effectiveness of this drug in blocking disease transmission.  
Nonetheless, our simulations indicate that EIR is a better indicator than \(R_{0}\) in the prediction of malaria transmission, as shown in Figure 8c,d. A possible explanation for this observation is that EIR values are consistently higher with increasing levels of heterogeneity.  
Figure 7: Scatter-plot between annual malaria incidence per 100 inhabitants and (**a**) the \(Z\)-rate, (**b**) the \(X\)-rate, and (**c**) the \(ZX\)-rate. In each case, we merge different levels of heterogeneity and at three different levels of ivermectin treatment, namely \(p_{i0}=\) 0.00, 0.10, and 0.20. Independently of the heterogeneous affinity and ivermectin probability, there is a very accurate relationship given by \(MI\sim\sqrt{ZX}\).  
Additional simulations were performed for other classical Ross-Macdonald model parameters, such as the human feeding rate \(a\), mosquito-to-human transmission parameter \(b\), and human-to-mosquito transmission parameter \(c\), with different results according to the heterogeneity level. While \(a\) is not significantly affected by heterogeneity, we find a consistent reduction in \(b\) with increasing levels of heterogeneity; on the contrary, \(c\) is positively and linearly correlated with higher heterogeneity levels.  
The level of heterogeneity at which \(c\) became higher in magnitude than \(b\) was above the level corresponding to the PW-rule of \(20/60\), where we had previously found an inversion of human infection prevalence. From this relation between \(b\) and \(c\), one may assume the possible existence of some form of proportionality of the fraction \(\xi\) with the biting disparity index \(\alpha\).
# Review of Radiation-Induced Effects in Polyimide
## 3 Results
### Changes in Mechanical Properties
Reduced elongation at break together with increased brittleness and the hardness of proton-irradiated PI is attributed to the formation of carbon-rich moeities on the surface of the PI film as a result of bond breakage of carbonyl, ether, and cyclic imide group during proton irradiation. Formation of a surface layer enriched in carbon as a result of proton irradiation is evidenced by studies of friction and wear properties of PI irradiated with 25 keV protons with fluence of \(2.25\times 10^{17}\) protons/cm\({}^{2}\) performed by [PERSON] et al. [106]. VUV exposure of PI film has not been shown to significantly affect its mechanical properties. For example, the irradiation of PI film, intended to serve as a sunshield in the next generation space telescope (NGST) mission, with VUV radiation of 1000 equivalent sun hours, caused changes in the ultimate tensile strength and elongation of failure of all samples within the experimental uncertainty [137].
## 5 Evaluation Results: Influence of Each Layer to the Overall Performance
### APL Layer
On the other hand, when three packets are transmitted as a result of a periodical event (or even more packets, when adding up several events for one destination), the algorithm may actually do some RTT calculations to find an efficient RTO value. According to [PERSON]'s algorithm [39], RTT measurements may not be taken from retransmissions. While it is likely to get valid measurements at low traffic with a low amount of RTO expirations, the number of valid RTT measurements diminishes at medium and high traffic scales, where RTO expirations happen frequently. The ability to tune the RTO value to the RTT at low and medium traffic allows the RFC 6298 algorithm to achieve lower delay and higher PDR. At high traffic, the average delay changes from being lower to being higher than the one obtained by the default RTO method, due to a greater number of RTO expirations and the consequently applied BEB mechanism. To reduce the amount of RTO expirations and to increase the probability of getting valid RTT measurements at high traffic scales, the initial RTO value could be increased, as higher delays are expected. However, a higher initial RTO value (like the one used by CoAP) would increase the delay and reduce the energy efficiency if packet losses occur on routes that have a low delay. Overall, since the amount of valid SRTT calculations is low, the TCP algorithm mostly uses the default RTO value and the BEB; therefore, it cannot clearly outperform the other algorithms. It can be shown that from the five RTO algorithms that have been analyzed, there is not an optimal one that provides the highest PDR, the lowest delay and the best energy efficiency at the same time. However, the CL algorithm offers a good tradeoff between these three performance parameters. The implementation of this algorithm is a simple alternative to the default ZigBee algorithm; hence, we consider the CL algorithm as an interesting possibility to augment the performance of the default ZigBee stack. Overall, the influence of the RTO algorithm on the overall performance is rather small compared to the impact achieved by modifying the number of MAC layer retries or the routing metric. However, the results show that the effect of the RTO algorithm increases with the amount of traffic.
## 4 Discussion
### Limitations  
This study has several limitations. First, this is a preliminary study with a small sample size from a single institution. Further studies that recruit larger samples are warranted to verify the impact on clinical practice. Second, the study took place in a controlled environment with minimum distracting elements. In real-world settings, healthcare professionals generally need to manage multiple patients in a short period of time, where a higher cognitive demand is required. Therefore, whether highlighting of new information is similarly effective or even more effective under real-world clinical practice conditions is open to question. Third, highlighted clinical notes were entirely new to the study participants, who might not have confidence in the accuracy of highlighting. They might even spend more time reading non-highlighted text. This might increase the time to completion and interfere with the accuracy of task performance. Fourth, because four consecutive preceding clinical notes are required to optimally determine whether the information is redundant, highlighting may not be worthwhile for patients with a short hospital stay. Finally, the majority of the study participants and the writers of clinical notes are not native English speakers even though clinical notes in the study hospital are documented in English. Language barriers may result in different behaviors in copying and pasting clinical text and incur extra cognitive load in extracting information.