esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Treatment  
The treatment of MRONJ can be non-surgical conservative method and surgical method. Conservative treatment for early-stage MRONJ (stages 0-2) primarily focuses on symptom management, infection control, and preventing the progression of the disease [10]. It includes practices like maintaining good oral hygiene, using chloreachine mouthwash, and taking antibiotics. This approach is particularly recommended for patients who are not eligible for surgery or prefer non-surgical interventions. The study compared three antibiotic regimens for preventing MRONJ in patients undergoing tooth extractions while on antiresorptive therapy, finding no significant difference in MRONJ development among groups treated with intravenous antibiotics for 7 days, oral antibiotics for 14 days, or oral antibiotics for 7 days [61]. This indicates that reduced oral antibiotic administration duration can be sufficient for MRONJ prevention when combined with proper preventive measures [61]. Studies on the systemic administration of ampicillin/sulbactam and clindamycin for MRONJ demonstrate their effectiveness in reaching therapeutic jawbone concentrations [23; 62]. Ampicillin/sulbactam showed that a reduced duration of oral administration could be sufficient for MRONJ prevention [23], while clindamycin achieved sufficient concentrations in both vital and necrotic bone samples to combat common bacteria associated with MRONJ [62]. These findings underscore the viability of tailored antibiotic therapy as a comprehensive strategy for the prevention and treatment of MRONJ.  
Surgical intervention, on the other hand, was identified as a more effective approach, especially for patients with advanced stages of MRONJ. The review also highlighted the potential benefits of adjuvant treatments like hyperbaric oxygen, ozone therapy, and low-intensity laser therapy when combined with conservative treatment, suggesting that these might lead to higher success rates and positive outcomes [10]. Additionally, the use of APCs like platelet rich fibrin and concentrated growth factor, derived from the patient's blood, showed significant improvements in mucosal healing, down-staging, and low relapse rates due to their ability to release high quantities of growth factors that stimulate bone regeneration and tissue healing [8; 9].
## 5 Experimental Results and Analysis
### Experimental Results and Discussion on Algorithms Comparison
* \(a280\_n279\),\(a280\_n1395\), \(a280\_n2790\):
* Performance Summary: In these instances, MOFECO-MS maintained its outstanding performance, particularly in HV and SP indicators, continuing to show the best performance. The PD indicator was close to optimal, demonstrating overall excellence. * The charts show that MOFECO-MS continues to deliver excellent distribution and high quality in these instances, demonstrating the algorithm's robustness in large-scale problems. * Analysis and discussion
* The reason MOFECO-MS performed well across multiple runs is due to its well-balanced global exploration and local exploitation capabilities, allowing it to find high-quality solutions across different scales and complexities of TTP instances. * Convergence: MOFECO-MS's optimization strategy effectively reduces gaps between solutions, ensuring uniform distribution along the Pareto front. * Diversity: Although MOFECO-MS did not achieve the highest PD values in some instances, it still maintained a high level of diversity, meaning it could explore a broader solution space without sacrificing quality. * Stability: MOFECO-MS demonstrated stability across multiple independent runs, indicating that its design is capable of consistently delivering high-quality outputs when addressing complex problems. * MOFECO-MS consistently performed exceptionally well across a wide range of BITTP instances, proving its potential as a powerful tool for solving complex multi-objective optimization problems. Its outstanding performance in HV and SP indicators, combined with its balanced performance in PD, makes it one of the leading algorithms in handling problems of various scales. From the results presented in Figures 8-16, it is evident that the MOFECO-MS algorithm consistently outperforms other algorithms in most of the BITTP instances, particularly in terms of Hypervolume (HV) and Spread (SP) indicators. Its strong performance can be attributed to its ability to balance exploration and exploitation effectively, ensuring both high-quality solutions and diverse coverage of the Pareto front. While it may not always achieve the highest Pure Diversity (PD) values, its performance in this area remains competitive, further demonstrating its robustness across different problem scales.
The dynamics inside of nanoparticle stabilized foams were studied by diffusing wave spectroscopy [24; 25]. Here, two dynamic processes were observed: a fast one caused by the nanoparticle diffusion and a slow one reflecting the foam dynamics. The internal structure of foams can be investigated by SANS [26; 27; 28; 29; 30; 31]. The main measurable feature here is the thickness of foam lamellae inside of the foam. In this context, specific salt and pH effects [29], the chemical nature of the surfactant [31; 32], and different drainage states of the foam [26; 29; 32] were studied. Furthermore, it is possible to detect objects inside the foam such as micelles [26; 27], solid nanoparticles [30], or polymer sufactant complexes [33]. In such experiments, contrast variation is especially powerful, because it allows to selectively mask or unmask objects or structures inside the foam [30]. Since foams are thermodynamically unstable by nature and, with the specific example of aqueous foams, are highly dynamic at a timescale of minutes, SANS experiments were limited to rather stable foams. Different cell designs for SANS on foams were reported in literature [26; 28; 29; 31]. In all of these cells, foam formation is realized by bubbling gas through a porous plate either made of steel or sintered glass. The first cell of this type was designed by [PERSON] et al. and consists of a Plexiglas cylinder with a single quartz window for the neutron beam [26]. Taking into account the changing liquid volume fraction along the height of a foam column, [PERSON] et al. used a cell with three plane parallel windows at different positions along the foam cylinder [29]. This made it possible to probe the foam at different (gravitational) drainage stages. Following this approach, we designed a foam cell that allows SANS measurements at any desired height along the foam cylinder. Since the foam formation before each SANS experiment takes several minutes, the presented SE includes a sample changer for up to three foam cells, allowing foaming the next sample during the measurement of the previous one. As stated above, this is especially important for highly brilliant neutron sources such as the ESS in order to reduce the downtime between sample changes. The high flux and reduced measurement time at the ESS will also enable measurements with more dynamic and less stable foams and will allow studies with high time resolution, which is especially appealing for highly dynamic foams. In order to use the full potential of the ESS from day one, it is crucial to design and test SEs for various experiments before the start of operation. In this article, we present the design and construction of the FlexiProb SE for SANS experiments on foams. Detailed technical aspects of the measurement cell itself and the peripheral components such as temperature control, gas flow control, and sample positioning, as well as first benchmarks for measurements with neutrons, are shown.
# Improving Spatial Reuse of Wireless LAN Uplink Using BSS Color and Proximity Information
## 4 Performance Evaluation
### Simulation Setup
(OBDS/PD, PSR, and Dual-CST were discussed earlier in the related work section.) Finally, \"PSC-UL\" is the proposed method. To obtain each point in the graphs, we ran 100 simulations with different topology and different random number generator seeds, and averaged the results.
# Evaluating the FLUX.1 Synthetic Data on YOLOv9 for AI-Powered Poultry Farming
## 3 Materials and Methods
### Tools Selection and Setup  
The development of a generative AI system for synthetic image generation requires a structured workflow that includes data collection, model selection, training and evaluation. Figure 3 illustrates the proposed workflow, outlining the essential steps involved in the selection and setup of tools. The methodology comprises the key steps shown as follows:  
**Step 1--**Dataset Preparation: Images and sensor data are collected from cameras and sensors deployed in real-world environments, such as poultry farms. The raw data undergo cleaning, transformation and formatting to ensure they are structured and suitable for AI training.  
**Step 2--**Data Annotation: Processed data are annotated to create a structured training set. Most of the annotation process is automated using Roboflow's auto-labeling tools, including models like Grounding DINO [43], minimizing manual effort and improving efficiency.  
**Step 3--**Model Selection and Training: Various generative AI models, including DALL-E 3, Midjourney, and FLUX.1, are evaluated to determine the most suitable option. FLUX.1 [dev] is selected due to its cost-effective fine-tuning capabilities and ability to  
Figure 3: End-to-end workflow for synthetic image generation using AI.  
generate realistic synthetic data. The selected model is fine-tuned using high-performance hardware to ensure high-quality image generation.  
**Step 4--**Model Evaluation and Image Generation: The trained model's performance is assessed based on human feedback, performance metrics, and qualitative analysis. Users provided text-based or parameterized prompts to guide the model in generating specific synthetic images.  
**Step 5--**Final Output: The process generates high-quality, realistic synthetic images, enhancing the dataset, reducing the need for manual data collection, and improving model robustness.  
This structured workflow ensures a systematic approach to synthetic image generation, leveraging AI-driven automation for efficiency and high-quality outputs.  
To facilitate the development and experimentation of predictive models, several software tools and computational resources were selected. Python 3.11 was used as the primary programming language, along with Ultralytics [44] for testing and deploying YOLOv8 and YOLOv9 models. The experiments were conducted using access to A100 GPUs, ensuring efficient model training. For generative AI tasks and data annotation, FLUX.1 [dev] and Roboflow [45] were utilized, while Replicate [46] was employed for fine-tuning FLUX.1 [dev] with H100 GPUs. The dataset annotation process was streamlined using Roboflow's auto-labeling feature, significantly reducing manual effort.
## 4 Results
### RQ6: Issues in WSN and IoT Frameworks
#### 4.6.3 Data Acquisition and Transmission  
The primary goal of IoT is to collect data and transmit it to where it is needed in a network. Sensors are the devices used to collect data from the environment to transmit it to the base station. After the raw data is collected, it is sent to the Sink Hub for processing. Data collection and transmission are other problems in IoT and WSN because data is exposed and modified during transmission. Data acquisition is an energy-consuming process, so extra care must be taken during gathering and transmission. Intruders can steal the data during transmission if it is not encrypted or transmitted over a secure channel. The intruder can take over a node and reprogram it with a malicious code, damaging the entire network. Therefore, security is required for this process. Sometimes intruders attack the databases of organizations to violate the confidentiality of the data [85]. Also, the intruder may destroy the node or collect important or unusual information that could be used against the system. For this reason, researchers present many security mechanisms. They protect end-to-end communication links using one-time-pad (OTP) encryption method and also identify the vulnerabilities in the DBMS application using SEPTIC method.
# Machine Learning Reconstruction of Wyrtki Jet Seasonal Variability in the Equatorial Indian Ocean
## 4 Discussion  
Figure 12 presents a comparison between the XGBoost-reconstructed and OSCAR zonal velocities of the WJ in the study region of 50\({}^{\circ}\) E-80\({}^{\circ}\) E, 3\({}^{\circ}\) S-3\({}^{\circ}\) N in 2013, illustrating distinct seasonal patterns. OSCAR data showed the WJ reaching a peak of 0.32 m/s in May, with velocities at \(-\)0.15 m/s in April and November, a velocity of 0.03 m/s in August, and a low velocity of \(-\)0.16 m/s in February. This indicates the WJ's asymmetric seasonal pattern in 2013, with higher velocities in spring (May) compared to autumn (November). The XGBoost results aligned closely with OSCAR, capturing the minimum (\(-\)0.14 m/s) in February and maximum (0.30 m/s) in May with a high \(R^{2}\) of 0.99 and a low \(RMSE\) of 0.01 m/s. However, a slight underestimation (0.01 m/s error) occurred in December but was within the acceptable error range. The model successfully captured the opposite WJ seasonal modes in 2013 and 2022, confirming the XGBoost's robustness in WJ seasonal reconstruction.  
Combing the daily RAMA observation data, we can extend the XGBoost to long-term sequence reconstruction of the Wyrtki Jet (WJ) at daily intervals, further examining its sub-seasonal to interannual variability characteristics. Additionally, the XGBoost framework demonstrates exceptional efficiency and precision in processing large-scale datasets, with intrinsic regularization mechanisms effectively mitigating overfitting, thereby exhibiting significant potential for subsurface current velocity prediction. In the future, we will deploy the XGBoost model for seasonal reconstruction of the Equatorial Undercurrent (EUC). Nevertheless, we explicitly recognize the inherent limitations in modeling highly  
Figure 11: Seasonal variability of Wyrtki Jet zonal velocity in the region of 50\({}^{\circ}\) E–80\({}^{\circ}\) E, 3\({}^{\circ}\) S-3\({}^{\circ}\) N from the OSCAR dataset (magenta line) and the XGBoost model reconstruction in 2022 (blue line).  
complex nonlinear relationships, manifesting as risks of underfitting or overfitting. To address these challenges, we outline three strategic enhancements: primary implementation of advanced feature engineering to comprehensively extract informational patterns; secondary integration of transformer architectures, leveraging their superior sequential modeling capabilities to elevate reconstruction accuracy; and tertiary incorporation of physical oceanographic knowledge through domain-specific constraints to augment model interpretability and predictive fidelity. Collectively, these methodological refinements will enable more precise reconstruction of subsurface equatorial currents, ultimately delivering innovative solutions for marine hazard mitigation, paraculture operations, and environmental conservation initiatives.
# Research on the Principle of a New Flexible Screw Conveyor and Its Power Consumption
## 6 Conclusions  
The conclusions of this paper can be summarized as follows:  
1. A flexible screw blade which is made of flexible fiber bundles is proposed as the spiral conveying shaft of screw conveyor for powder conveying. The ability to transmit particles whose diameter is bigger than that of the flexible fibers is verified by experiments.
2. According to the theory of particle mechanics and material mechanics, the power consumption and conveying quantity model of flexible screw blades for conveying bulk materials are established. The main parameters affecting the conveying amount and power consumption are: helical diameter, spiral rising angle, blade dispersion coefficient, and so on.
3. The mechanism of flexible spiral blade conveyor is verified by the particle material mechanics software EDEM. From the results of the simulation, we show that the conveying capacity of the particles decreases with the acceleration of the clearance of the flexible helical blades and increases with the speed, diameter, and angle of the screw conveyer; the power consumption of the particle material increases with the speed of the screw conveyor and the diameter of the spiral.
4. The theoretical and simulation results are verified by experiments. By comparing the power (torque) curves at the same speed, the growth trend of the experimental curves is consistent with the results of the theoretical analysis and simulation curves.  
Y.T. and J.G.; Methodology, M.C.; Software, P.Y.; experiment, Y.S. and T.D.; Data Analysis, F.Y. and J.T.; Validation, K.Z.; Writing-Original Draft Preparation, Q.C.; Editing paper format.  
This research was supported by the National Natural Science Fund (41772387), Youth Innovative Talent Support Project of Harbin University of Commerce (2016 QN067), doctoral research startup project (2016 BS07).  
The authors declare no conflict of interest.
# Numerical Study of Internal Flow Field in a Disc Stack Centrifuge Based on Mixture-PBM Model
## 3 Results and Discussion
### Comparison of Experimental and Numerical Simulation Results  
The operating conditions of the test were as follows: a full-size disc stack centrifuge prototype was used, with an inlet water content of 5% and an inlet water droplet particle diameter of 5-200 microns under design flow conditions. The particle diameter and content of water droplets at the inlet and outlet of the disc stack centrifuge were measured using the ML-1 oil-liquid abrasive particle detector. The experimental flow chart is shown in Figure 6. The measurement error when measuring free water with the ML-1 oil-liquid abrasive particle detector is 1 ppm, 1 ppm = 10\({}^{-6}\).  
Calculated from Equation (1), the separation efficiencies of both experimental and numerical simulation results are above 99%; the units of the vertical coordinates in Figure 7 are in ppm to clearly show the differences in the separation efficiencies under different operating conditions.  
Figure 6: Experimental flow chart.  
Figure 7: Separation efficiency of disc stack centrifuges at different rotational speeds.  
The main forms of water existence in oil are dissolved water, emulsified water, free water, and so on. Figure 7 shows the effect of different rotational speeds on the separation efficiency of a disc stack centrifuge at a flow rate of \(Q_{d}\). The experimental data include data on total water content and free water content, and the numerical simulation data are for free water content. The vertical axis indicates the water content at the outlet of the oil phase, and the horizontal coordinate indicates the rotational speed of the disc stack centrifuge. The results show that at the rotational speed coefficients \(N_{h}\) = 1.0\(\sim\)1.06, the total water content at the outlet of the oil phase decreases gradually with the increase in rotational speed, and the separation efficiency of the disc stack centrifuge increases gradually. This is because when the speed of rotation is greater, water droplets with smaller particle sizes can converge into water droplets with larger particle sizes, which can then be separated. With the increase in rotational speed, the free water content at the oil phase outlet always stays within the range of 3-6 ppm, which is basically in perfect agreement with the numerical simulation results.
# Predicting Player Churn of a Free-to-Play Mobile Video Game Using Supervised Machine Learning
## 3 Problem Description
### Initial Churn Analysis  
Before continuing research on ways to combat player churn, a solid case must be made that the churning problem even exists. We conducted a short statistical study on a sample of our dataset (starting from 27 April 2020 until 24 May 2020, the sample is later referred to as dataset D3). From this pool of players, we plot the activity distribution in Figure 4. To clarify, for each of the new players in the dataset, we note whether he/she has been detected in-game within 7 days of the initial day he/she installed the game (day 0 denotes the day the user has installed the game). Considering this sample, we found that, out of the 1.5 million players considered, 61.81% of them did not show in the game after the first 24 h, as shown in Figure 4. After only three days, that number rose to 81.9%. This clearly shows that player churn is a real concern, and the costs and efforts associated with finding ways to combat player churn are justified.  
Figure 3: Estimate accuracy in relation to observation duration.  
Figure 2: Illustration of player churn estimates based on player activity on the day following game, installment as compared to ground truth data considering player activity over a 14-day period.  
We additionally perform a separate analysis to ascertain player churn distribution by considering player activity rather than absolute time frame. In our concrete case of an interactive storytelling game, we consider the number of chapters a player completed reading in a given story prior to churning. The results were unsurprising: a disproportionate percentage of players churned during one of the early chapters, with the first two chapters often exhibiting user retention percentages below 40%. In contrast, players that reached later chapters were significantly more likely to finish them, with completion percentages varying between 48% and 49%, with respect to the total number of players for each chapter. In terms of a single (first) story, more than 75% of the playerbase dropped out before chapter 10, as presented in Figure 5. The analysis presented in Figure 5 was conducted on all players arriving in the game in the period of 4 weeks, from 26 October until 22 November 2020.  
Based on the demonstrated results, we inferred that early churn detection plays a crucial role in its long-term prevention. The insight provided by preliminary analysis led  
Figure 4: Number of players active in the game on a certain day after having installed the game.  
Figure 5: Player churn distribution by story.  
us to conclude that greater focus should be placed on the first several days of a user's playtime, as it could prove to be highly indicative of their willingness to continue playing the game for an extended period. Moreover, focusing on this early period would enable the game provider to engage a large portion of the audience that would stay in the game for a very brief period.