esa-sceva/satcom-chunk-collection huggingface dataset:
# A New String Edit Distance and Applications
## 1 Introduction
### Short Tandem Repeats
Beyond the issue of edit cost, stutters and single-character edits can interact in complicated ways, and algorithms like the Levenshtein distance and its relatives do not begin to address the issues that arise in that interaction. String edit distances have been in use for decades, with many papers published on different applications. Review of the literature revealed diverse uses, but multi-characterextensions of edit distances were rarer. One paper described a spelling correction algorithm using a generalized metric that allows for generic word-to-word edits [18]. The aim and methods described in the study are different than those presented here; however, if the code and details for implementation were included in [18], direct comparison with the independent method presented here would be of interest. Another paper working with multi-character edits introduces some theoretical ideas relevant to dictionary based searches and generalizations of the Damerau-Levenshtein distance [19], but their searches are approximate and require symmetry, which cannot be used here since insertions and deletions of both characters and motifs happen with different frequencies. There is a variation on the dynamic programming approach that allows for generalized edits from one substring to another with non-symmetric costs, but it also prohibits multi- and single-character edit interactions, and no code or software was available for comparative testing [20]. Generalized edit distances were infrequently mentioned in the literature, and attempts to find comparable algorithms described with code attached were unsuccessful. The work presented in this paper uses an algorithm readily available for public use that also allows for a large set of overlapping edits. The ideas behind the RFL distance are applicable to any situation requiring a minimal edit distance solved via dynamic programming, notable among which is graph edit distance [21]. By extending the idea of precomputed motifs to other dynamic programming settings, one could consider a minimal graph distance that allows the addition or loss of an entire subgraph as its own edit to have an individual cost. Therefore, this idea could have implications wherever graph edit distances are used, such as handwriting recognition [22], fingerprint recognition [23], and cheminformatics [24]. The proposed algorithm to compute RFL distance has fully customizable costs, and is therefore capable of reflecting the idea that lower costs correspond to higher probability edits. This connects to the notion that more frequent events would be favored in a maximum likelihood approach over lower probability events. The Python code for the RFL algorithm is available on GitHub [25].
###### Abstract  
Knee joint distraction (KJD) treatment has shown cartilage repair and clinical improvement in patients with osteoarthritis, as has high tibial osteotomy (HTO). Following KJD, TGFp-1 and IL-6 were increased in synovial fluid (SF), factors related to cartilage regeneration, but also to osteophyte formation. As such, osteophyte formation after both joint-preserving treatments was studied. Radiographic osteophyte size was measured before, one year, and two years after treatment. Changes were compared with natural progression in patients from the CHECK cohort before undergoing total knee arthroplasty. An additional KJD cohort underwent SF aspiration, and one-year Altman osteophyte score changes were compared to SF-marker changes during treatment. After two years, both KJD (\(n=58\)) and HTO (\(n=38\)) patients showed an increase in osteophyte size (\(+6.2\) mm\({}^{2}\) and \(+7.0\) mm\({}^{2}\) resp.; both \(p<0.004\)), with no significant differences between treatments (\(p=0.592\)). Untreated CHECK patients (\(n=44\)) did not show significant two-year changes (\(+2.1\) mm\({}^{2}\); \(p=0.207\)) and showed significant differences with KJD and HTO (both \(p<0.044\)). In SF aspiration patients (\(n=17\)), there were significant differences in TGFp-1 changes (\(p=0.044\)), but not IL-6 (\(p=0.898\)), between patients with a decrease, no change, or increase in osteophyte Altman score. Since KJD and HTO showed joint space widening and clinical improvement accompanied by osteophyte formation, increased osteeophyltosis after joint-preserving treatments may be a bystander effect of cartilage repair activity related to intra-articular factors like TGFp-1 and raises questions regarding osteophyte formation as solely characteristic of the joint degenerative process.  
knee joint distraction; osteophyte; osteoarthritis; high tibial osteotomy; TGFp-1; joint-preserving
## 3 Simulations and Discussion
### Impact on Forecast of Typhoon Mittag (2019)
We did not examine an optimal combination of various physics schemes for use in MPAS in this study. Figure 17: **(a)** The CWB best track (black line), the JTWC best track (red line), and the forecast tracks for NoDA (blue line), GTS (green line), BND (pink line), and BND_RV (purple line) for Typhoon Mitag (2019) starting from 0000 UTC 27 September 2019. **(b)** as in **(a)** but for the track errors, and **(c)** as in **(a)** but for the central sea-level pressure. In **(b)**, the red line shows the difference in the JTWC best track from the CWB best track.
# Study of the Precipitation Process in Aging Steel Pipeline Weldments by Thermoelectric Power Means
## 1 Introduction  
Steel pipelines with low carbon contents, welded by an electric arc, have been used for many years in the oil industry. However, the failures that are found frequently during its operation over many years have prompted several studies to study the design, construction, operation and maintenance of equipment and metallic structures that are used in this industry. In general, the steel pipes undergo a natural aging process that is accelerated due to prolonged exposure at operating temperatures (between 25 and 70 \({}^{\circ}\)C) and variations in the operating pressure. These operating conditions can cause changes in the microstructure, mechanical properties (elastic limit, hardness, ductility and toughness), type of fracture and probability of failure after several years of service. This natural aging process is described by two factors: the peak of aging associated with the maximum resistance and precipitation of carbides that interact with the dislocations and causes hardening by precipitation; and the over-aging related to the decrease in resistance and thickening of carbides after a long aging time [1,2].  
On the other hand, the thermoelectric power (TEP) is a valued intrinsic material property, which depends on microstructural features. Since the micro-alloyed steel microstructure correlates directly to the material properties, TEP provides an effective way to characterize the microstructural changes, which can potentially lead to significant localized imperfections and possible structural failures in a time-dependent phase transformation (including aging). It is also well known that TEP is a function of electronic scattering behavior, electron concentration and effective mass of the electrons in a metallic alloy. These physical factors are influenced by the material microstructural and phase transformation changes. In this present study, the relationship between the TEP and the microstructure was obtained using the conventional contact TEP technique (hot-tip) and SEM for weldments of X60 and X65 micro-alloyed steel that are artificially aged.
## 4 System Simulation and Performance Analysis
### Model Validation and Dynamic Characteristics of SCRS  
Under full load condition, four operating processes were completed in one cycle of the compressor, namely suction, compression, discharge, and expansion. Under part-load conditions, a reverse stroke followed after the suction process [10]. The movement of the suction valve plate was changed by the actuator when the capacity regulation system was operated. The movement of the actuator was determined by the hydraulic pressure and the reset spring force, which influenced the working process of regulation system.  
The measured and predicted cylinder pressure in one cycle of the compressor under three typical load conditions (100%, 70%, 40%) is shown in Figure 5. A step decrease was designed for the first-stage load ratio (80-60%) and the second-stage load ratio (80-50%) at 50 s, respectively. The change of the buffer tank pressure is shown in Figure 6. Compared with the measured results, the simulation results exhibit good consistency over different load conditions. The results verify that the presented model is acceptable and valid.  
The relationship among the control signal (60% load), the displacement of the suction valve plate, the displacement of actuator, and the pressure in cylinder with a crank angle under the capacity regulation condition is shown in Figure 7. It can be clearly seen that the delay from the high-level control signal to the start of the movement of the unloader is about 50\({}^{\circ}\) caused by the opening delay of the solenoid valve, and the moving time of the unloader is about 6\({}^{\circ}\). The delay from the low-level control signal to the start of the reset of the unloader is about 47\({}^{\circ}\) caused by the closing delay of the solenoid valve, and the reset action time of the unloader is about 12\({}^{\circ}\).  
Figure 5: Dynamic pressure in the cylinder under different loads.  
Figure 6: Simulation and experimental data of buffer tank pressure; (**a**) the first stage; (**b**) the second stage.  
In order to study the influence of the control parameter characteristics on the system's dynamic performance and controllability [23], different loads and a different exhaust flow were realized by changing the duty cycle of the control signal. As shown in Figure 8, when the duty cycle of the control signal was too low (less than 30%), the unloader reset before the compression process started, and the valve plate reset automatically. Hence, the cylinder was working at full load, and the exhaust flow was not adjusted. When the duty cycle was large enough (greater than 75%), the suction valve plate could not be withdrawn during the whole operation cycle of the compressor, all gas was returned, nothing was compressed, and the exhaust flow of the compressor was zero.
## Discussion  
### Choosing the Best Models  
The conventional studies considered the study site as one point where the spatial heterogeneity of the study area was neglected. But our study reconstructed GPP for every pixel in the whole area, and we also ran reconstruction models for two nested time periods (Phase 1 and Phase 2). We tried to make full use of all plots in Phase 2 and build a robust model with less error. In the meantime, we extended our study period to 1895 with fewer plots (Phase 1). In Phase 1 (1895-1937), we chose the GRNN with the highest adjusted R\({}^{2}\) and lowest RMSE, MAPE, and MAE among all three approaches. In Phase 2 (1938-1985), we selected the RF with the lowest RMSE, MAPE, and MAE. Previous researchers [14] only ran the model in Phase 1 and guaranteed model performance with as many plots as possible. They chose the intersection of all plots as their starting year, which shortened their study period. But if we intended to directly reconstruct our GPP from 1895 to 1985, we would only have four plots for the whole temporal period with more errors.  
From the best model in Phase 1 and Phase 2, the performance using the best model in Phase 2 (RF) outperformed that in Phase 1 (GRNN) for all four evaluation metrics (RMSE, MAPE, MAE, and adjusted R square). Even for the same model in two phases, the model in Phase 1 was worse than that in Phase 2, which confirmed that the number of variables may determine model performance. The four metrics (RMSE, MAE, MAPE, and adjusted R square) of the two selected models were acceptable (Figure 4). Even when we compared our results with other GPP reconstruction studies using in situ data, our model performance exceeded theirs. Our RMSEs in Phase 1 and Phase 2 were 559.45 g C m\({}^{-2}\) year\({}^{-1}\) (1.53 g C m\({}^{-2}\) day\({}^{-1}\)) and 520.21 g C m\({}^{-2}\) year\({}^{-1}\) (1.43 g C m\({}^{-2}\) day\({}^{-1}\)), while the GPP reconstruction with eddy covariance flux towers was 2.01 g C m\({}^{-2}\) day\({}^{-1}\)[35]. Our study not only extended the study period but also presented the reconstruction with lower errors.
## 3 Results and Discussion
### Electrochemical Properties
Such stability has been previously observed for similar materials and may be due to the presence of nanorod structures in their composition, which, as shown in [28], enable stabilization of the active material volume change in the process of hydroxide-ion incorporation/extraction according to reactions 9-11. The electrochemical characteristics of the pristine substrate without active material were additionally studied (Figure S1a,b). The CV curves show that the current values as well as the CV-integrated area in the case of a pure substrate are several times smaller compared to the substrate with nanostructures printed on its surface. The capacitance value of the pure substrate calculated with the galvanostatic charge-discharge data was about 3.5 mA/cm\({}^{2}\) at 0.030 mA/cm\({}^{2}\), which is about 3 times lower than the capacitance value for the studied electrode. Additionally, the electrochemical kinetics of the obtained electrode was studied by impedance spectroscopy. The corresponding Nyquist plot (Figure 9d) includes two components: a semicircle (in the high-frequency range) and a straight line (in the low-frequency range). The diameter of the semicircle represents the charge transfer resistance (R\({}_{\text{ct}}\)), and the interval cut by the curve at high frequencies from the real axis indicates the diffusion or solution resistance (R\({}_{\text{s}}\)) of the electrolyte [70]. The electrode material under study exhibits relatively low R\({}_{\text{s}}\) (0.386 Ohm) and R\({}_{\text{ct}}\) (1.6 Ohm) resistances, indicating active ion transport at the electrode/electrolyte interface. The Nyquist plot under consideration also contains a linear part described by the Warburg impedance (Figure 9d, inset), which determines the electrolyte ion penetration into the active material of the electrode [70]. Analyzing the obtained functional characteristics of the formed electrode material, one can judge that the demonstrated specific capacitance values are generally comparable with similar materials (Table S1) obtained earlier by other researchers when creating the miniature supercapacitor electrodes [31; 71; 72]. In addition, it is important to note the high cyclic stability of the electrode material obtained in our study, which is important in terms of the final device lifetime. Further increases in the specific capacitance value of the electrode material we proposed could be achieved by increasing the active material mass as well as the substrate surface area modified by it. Nevertheless, in the course of the study, it was shown that the proposed technology of synthesis and printing gives a fundamental possibility for the effective formation of the corresponding miniature electrode nanostructures as promising components of miniature supercapacitors. The results of the electrochemical characteristics comparison of the materials obtained by us with similar ones obtained in other works are given in Table S1 in the Supplementary Materials.
# The Current State and Future Potential of Microbial Control of Scarab Pests
## 5 Fungi  
Entomopathogenic fungi are the most widely used microbes for insect control. Entomopathogenic fungi can be found in almost all fungal lineages, with the exception of Glomeromycota [77]. Entomopathogenic fungi can be found in the orders Hypocreales (_Beauveria_, _Metharizum_, _Isaria_, _Lecanicillium_), Entomophtondaries, Onygenales (_Ascosphaera_ species), and Neozygitales (_Entomoplthornycota_) [77]. Entomopathogenic fungi infect insects through spore attachment to the cuticle, where enzymatic and mechanical processes eventually allow germination inside the insect. The fungi then use the nutrients in insect tissues to grow and proliferate, killing their host. The ability of entomopathogenic fungi to infect a broad range of arthropod pests and to easily be mass-produced have led to the development of many commercial products (Table 1). Some genera contain species/strains that are species-specific, while others have broad insecticidal activity. Various species, including those from the genera _Beauveria_, _Metharizum_, _Entomophtona_, _Lecanicillium_ (formerly _Verticillium_), and _Isaria_ (formerly _Paecilomyces_), have been isolated from different scarab species and documented in epizootics [78; 79; 80; 81; 82; 83; 84]. However, of these, _Beauveria bassiana_ and _Metharizum anispoliae_ dominate in soil systems, and as a result, are the most widely used for insect biocontrol (Table 1).
## 4 Experimental Simulation and Results Analysis
### Analysis of the Impact of Different Improvement Strategies on Algorithm Performance
The MSEChoA algorithm surpasses both the original algorithm and those with individual strategy improvements in optimization accuracy, convergence speed, global search capability, and algorithm stability. This demonstrates the significant advantages of the multi-strategy fusion approach in addressing complex optimization problems, validating its effectiveness and superiority.
# A Review of Traffic Flow Prediction Methods in Intelligent Transportation System Construction
## 1 Introduction
### Research Status  
The core of traffic flow prediction tasks lies in analyzing historical data to forecast future traffic flow trends, thus providing decision-making support to traffic management authorities. This requires a substantial number of data, many of which are collected through sensors, cameras, and other monitoring technologies, and they exhibit both temporal and spatial dependencies. Temporal dependency is mainly reflected in patterns such as the similarity in peak travel times during weekday rush hours and holidays. Spatial dependency is manifested in how the current traffic situation is influenced by the historical traffic conditions of upstream, downstream, and adjacent road monitoring points. Additionally, the traffic flow is also affected by external factors such as the weather conditions, holidays, and the distribution of points of interest, all of which significantly impact the accuracy of traffic flow predictions [3]. The related data are highly nonlinear and complex, making them difficult for traditional statistical and machine learning methods to accurately capture and model.  
In recent years, the development of deep learning technologies has introduced powerful capabilities in feature extraction and pattern recognition, showing great potential in the field of traffic forecasting. Deep learning models such as deep neural networks, recurrent neural networks, and long short-term memory networks are capable of processing complex spatiotemporal data, leading to significant improvements over traditional methods. Moreover, the adaptive ability of deep learning allows it to maintain prediction accuracy even when faced with substantial noise and multidimensional features in traffic data.  
Academia, both domestically and internationally, has conducted extensive and in-depth research in the field of traffic forecasting, developing a range of methods tailored to different application scenarios. These include traffic flow prediction for multi-intersection systems [4], highway traffic volume forecasting [5], and urban road traffic flow prediction [6], among others. Commonly used techniques include statistical analysis methods, machine learning approaches, and deep learning methods, which will be discussed in detail in the main body of this paper.
## 4 Routing Layer
### Future Challenges  
In this section, known open research issues are discussed which must be considered during future work on underwater environments. In the case of failure, routing must be self-configuring. According to the underwater environment, algorithms should provide strict or loose latency bounds for time-critical applications. For delay-tolerant applications, protocols must try to develop mechanisms to handle a loss of connectivity without immediate retransmissions. A handful of security solutions have been purposed for WSN [129]. However security is a relatively new research topic in UWSN that needs to be further explored.  
In summary, future work in this area must consider intelligence techniques, QoS, node mobility and security. In applications where nodes are mobile, new routing protocols are needed to handle the frequent topology changes and to ensure reliable delivery.
# Detecting and Mitigating Attacks on GPS Devices
## 6 Countermeasures and Their Comparison
### Countermeasures for GPS-Denied Environment--Alternate Positioning  
Researchers have proposed many techniques for positioning and navigation in GPS-denied environments over the past two decades [23]. These different approaches are all predicated upon using measurements from onboard sensors to understand its environment, from which position can be inferred. Different approaches utilize different sensors, while some utilize values from multiple sensors. These proposed approaches generally belong to one of six categories (Figure 5) [110].  
Not all systems will possess all sensor types. Consequently, not all alternate positioning methods will universally apply to all unmanned systems. Furthermore, these various approaches have strengths and weaknesses that may make them more applicable to certain use cases. The advantages and disadvantages of these various alternative positioning approaches are summarized in Table 14 [110].
## 3 Results and Discussion  
MSCs, in a 2D culture, were initially observed to migrate toward an IL-6 gradient in response to IL-6, at a concentration previously noted to induce MSC migration from 3D spheroids (350 pg/mL; [12]). Upon IL-6 exposure, cells were tracked over 24 h using time-lapse light microscopy. A clear directionality was observed toward the IL-6-spiked DMEM, where large filopodia were noted extending in the direction of IL-6, inducing a leading edge and migration (Figure 2) [31]. Cell migration was analysed to assess global migration over 24 h; a rose plot confirmed MSC preferential migration toward IL-6 (positive axis; Figure 3B). A vector plot further supported the motility of each analysed cell from the point of origin (Figure 3A). Thus, MSCs preferentially moved \(>\)50 \(\upmu\)m toward [IL-6] within the 24 h period.  
Cytokines are secreted, principally, by lymphocytes and macrophages. They act by altering the function of target cells in a paracrine or autocrine fashion. However, invading breast cancer cells, within the bone marrow, have been noted to secrete cytokines initiating an epithelial-to-mesenchymal transition leading to a metastatic phenotype. This signalling occurs at very low concentrations (pg/mL-ng/mL) [32]. MSCs are known to respond to TNF\(\alpha\), IFN\(\gamma\), IL-1, and IL-6 concentration gradients [12; 33], permitting movement toward the site of damage [22] through initiation of cell signalling pathways [34].  
Figure 2: A montage of six images taken from the 24 h time-lapse following a single MSC cultured within an Ibidi \(\upmu\)-Slide Chemotaxis 2D assay plate with IL-6/DMEM (1 ng/mL) in the first reservoir and culture media alone in the reservoir on the right.