esa-sceva/satcom-chunk-collection huggingface dataset:
# Spatial Variation of Water Chemistry in Aries River Catchment, Western Romania
## 3 Results
### Pollution Index  
The water quality of the study area was analyzed using several pollution indices. The HPI is used to characterize the potential environmental risk of heavy metals in water bodies, while HEI gives an overall quality of the water regarding the heavy metal concentration [13; 38]. The spatial trends for the HPI and HEI in the Aries River catchment were calculated based on the following heavy metals: Cd, Cu, Fe, Mn, Ni, Pb and Zn. The number of heavy metals was reported to the standard values established by the Romanian Legislation, Order 161/2006/OD and Directive 2008/32/CE [34; 35].  
HEI ranged from 2.65 to 16.9, indicating a medium level of heavy metal pollution in 5 out of the 30 water samples. The highest HEI results were obtained in the case of A12 (HEI = 16.9), samples collected from the vicinity of Valea Sesii. Based on scaled HEI values, 83% of samples were classified as having low pollution levels and 17% with medium pollution levels (Figure 7b).  
Studies from Africa indicated low and moderate-heavy metal pollution in the Malopane region (Dorpsrivier, Mogalakwena Deep pool, Dithokeng, Rooisloot, South Africa), a region with intensive agriculture and mining activities [56].
# Application of Surge Arrester in Limiting Voltage Stress at Direct Current Breaker
## 4 Components Selection  
Capacitors are selected based on the maximum allowed rate of change of voltage across the breaker contacts \(\frac{dV_{C}}{dt}<80\) V/ us that is needed for the air breakers to prevent restrikes and is an appropriate speed for typical fast breakers [23]. The maximum fault current \(I_{fault}=C\frac{dV_{C}}{dt}\) is used to calculate the capacitors with \(\frac{dV_{C}}{dt}<80\) V/ us, i.e., \(C>\frac{I_{fault}}{80\times 10^{6}}\). For example, a 1000 A fault current requires C \(\geq\) 12.5 uF. Slower mechanical breakers require larger capacitors. Capacitors must tolerate transient overvoltage beyond the nominal source voltage.  
\(I^{2}t\) curves are used to select diodes due to the short duration of the fault current. Diodes can be rated slightly higher than the supply voltage as they experience \(V_{SAB}\) in the proposed topology.  
Surge arresters are selected based on their leakage current and voltage for the target fault current via the surge arrester's V-I characteristic. For example, for a 500 V, 10 kA fault scenario, one must choose a surge arrester that is capable of conducting 10 kA at slightly above 500 V. Such a surge arrestor may conduct a significant amount of current under 500 V (normal condition) and thus is disconnected by a controlled switch in the proposed breaker (see Figure 1).
# Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring
## 2 Sensor Types
### Thermal Infrared Sensors  
Thermal infrared sensors are a widely adopted technology for crop monitoring. It has shown good results in crop and parameter monitoring (Table 1). Particularly, it delivers a nondestructive estimation. However, thermal infrared sensors are manually operated devices [80], controlled through mobile systems [81] and installed in aircrafts [82], satellites [83] or UAVs [84]. Aircraft and satellite-installed thermal infrared sensors can estimate crop parameters remotely. They can spatially map the crop parameters by a thermal image to estimate delicate and heterogeneous features of the crop [85]. The imagery data are composed of pixel arrays representing pixel resolution of the sensor. Crop parameter observation with thermographic features allows to utilize the thermal sensing for particular features estimation [86; 87; 88; 89; 90], each plant temperature estimation [91], and develop variable rate irrigation strategies [92; 93; 94]. However, these applications do not generally provide a better spatial or temporal resolution [95]. The reduced resolution of the sensor and the distance to the target considerably minimize the quality of the data [96; 97]. Thermal infrared sensors are sensitive to atmospheric conditions. Despite the sensitivity, they provide a high potential to be applied in precision agriculture and especially in irrigation strategies to estimate the right time, the right place and the right quantity of water to apply to minimize the quantity of water used per unit yield [98].
## 1 Introduction  
The protein source in a hen's diet is of utmost importance as it directly influences the bird's growth and health, egg quality, and overall production performances [1].  
Soybean meal is considered a high-quality protein source, widely used in poultry diet formulation [2], which contains a balanced amino acid profile, crucial for egg production and overall growth. These amino acids contribute to the synthesis of proteins, enzymes, and hormones, supporting various physiological functions in hens [3]. Soybean protein can be compared to proteins found in meat, milk, and eggs. Among plant-based protein sources, soybean protein is widely regarded as having the highest biological value [4]. [PERSON] et al. [5] consider that the increasing competitiveness of feedstuffs for poultry nutrition presents a challenge to food security; therefore, ongoing efforts are made to explore alternative protein sources that can partially replace soybean meal in poultry diets.  
Microalgae are being increasingly explored as a valuable and sustainable alternative in animal and poultry nutrition due to high protein content [6], and are primary sources of omega-3 fatty acids, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) [7]. Moreover, they are considered environmentally friendly due to their minimal impact on land and water resources [8]. Furthermore, microalgae contain bioactive compounds that exhibit antioxidant [9], antimicrobial, and immunomodulatory properties [10], thereby contributing to disease prevention and supporting the immune system.  
Chlorella (_Chlorella vulgaris_) is a naturally single-celled green microalgae considered as an alternative for partially replacing soybean meal included in poultry diets [11]. Previous studies found that _Chlorella_ has a positive impact on egg production and quality, enhancing the intensity of the yolk color due to carotenoid transfer (canthaxanthin and \(\beta\)-carotene) [12]. Furthermore, it promotes the growth of lactic-acid-producing bacteria in the intestines and lowers the total cholesterol and triglyceride level concentration in serum and liver [13].  
Spirulina (_Sp. platensis_), a blue-green spiral filamentous alga [14], is a natural product with high nutritional value and increased antioxidant potential. Its utilization improves production efficiency, egg production [15], and yolk redness, while also exhibiting favorable amino acid profiles and high digestibility [16]. Spirulina is recognized as a sustainable protein source with a low-impact environmental footprint that can vary significantly depending on factors such as the production system and regional climate [17].  
Despite previous research on this topic, the results of previous experiments involving the inclusion of microalgae in poultry diets have generated inconsistent findings with regard to both poultry productivity and egg quality. As a result, our study aims to investigate the partial substitution of soybean meal in the diet of laying hens, and to examine the potential impacts and effects of chlorella and spirulina, both at equivalent inclusion levels, on these specific parameters.
## 5 Simulation
Figure 8 illustrates the motor's speed response when subjected to a sudden load of 3 N\(\cdot\) m applied at 0.2 s. The results demonstrate that the FTSTRL method exhibits a significantly smaller deviation from the target speed compared to the CSTRL and NSMRL methods, indicating superior performance in maintaining speed stability. Figure 9 shows the corresponding variations in current in response to the load change. Additionally, Figure 10 provides an in-depth comparative and quantitative analysis of the simulation results for this sudden load test, utilizing metrics such as ISE, ITSE, IAE, and ITAE. These analyses highlight the effectiveness of the FTSTRL method in handling abrupt disturbances and maintaining system performance. Figure 8: Comparison between CSTRL, NSMRL, and FTSTRL for sudden load test. Figure 7: Performance metrics such as ISE, IAE, ITAE, and ITSE for speed tracking. approach represents a significant advancement in control strategies, particularly in the context of embedded systems. The FTSTRL was achieved through collaboration with an ESDO and integration with an FTSTSMC. By combining these elements, the FTSTRL facilitates feedforward compensation, which is essential for improving the system's responsiveness and accuracy. The inclusion of the FTSTRL within the FTSTSMC significantly enhances the system's robustness by effectively reducing the impact of interferences. Comparative performance evaluations were conducted to assess the effectiveness and reliability of the FTSTRL against other existing models, such as the CSTRL and NSMRL. These evaluations employed key performance metrics, including ISE, ITSE, IAE, and ITAE, providing a comprehensive quantitative basis for comparison, ensuring that the advantages of the FTSTRL are clearly demonstrated in simulations. Future research will involve applying the FTSTRL to real motors in practical applications. This step is crucial for validating the control strategy's performance under real-world conditions, ensuring that the FTSTRL not only performs well in simulations but also delivers robust, reliable control in the field. This paper was produced by all the authors. [PERSON] and [PERSON] conceived the idea, performed the analysis, and designed the simulation; [PERSON] and [PERSON] carried out the numerical simulations; and [PERSON] wrote the manuscript. All authors have read and agreed to the published version of the manuscript. This work was supported in part by the Science and Technology Innovation Project of the National Shuohuang Railway Company (SHTL-22-17) and in part by the Key Research Development Project of Nanjing Polytechnic Institute under Grant NJPI-2021-14. Not applicable. The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author. The authors declare that this study received funding from National Shuohuang Railway Company. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.
# Investigation of Data Quality Assurance across IoT Protocol Stack for V2I Interactions
## 6 Findings and Discussion  
### Mapping  
Each protocol within the protocol suite plays a specific and pivotal role in the overall network performance, with combined responsibilities ranging from formatting, managing, routing, forwarding, and receiving data packets between nodes. Ensuring communication efficiency in a multifaceted V2I communication landscape requires each protocol to perform optimally to ensure reliable data transmission across diverse use cases, e.g., beacon message broadcasting [103]. It's imperative to understand the most suitable protocols for V2I communications within the context of DQ. In achieving this, mapping the protocols to our identified DQ dimensions is essential in identifying: 1. The most suitable protocols to deploy in specific use cases. 2. Providing a structured way to effectively manage the layered suite to achieve efficiency in data transmission, and 3. Making it easier to pinpoint areas for optimisation which leads to an operational improvement in the overall performance of the network.  
This mapping can act as a blueprint to support network engineers and managers working on V2I systems in deploying IoT devices within traffic infrastructures, providing a useful guide in selecting the most suitable protocols based on their identified DQ requirements inherent in their specific V2I use-case, such as traffic light managements requiring XMPP protocol to communicate traffic light information to upcoming traffic simultaneously, the application of MQTT to timely update the availability of parking space in a smart parking scenario, the use WebSocket to continually communicate real-time traffic information and the use of SCTP to support vehicle infotainments by reliable streaming multimedia data. In addition, software developers can also leverage this mapping when designing IoT applications, as observed in [104], providing them with a detailed understanding of how different protocols may impact their application's performance. Another useful application is that this research can provide a support framework for policy formation and standardisation when setting guidelines for IoTprotocol development and deployments, ensuring that protocols are optimised for the IoT paradigm's diverse and evolving communication demands.  
In a broader sense, this research can stimulate networking communication innovations to support V2I communication ecosystems by providing a clear understanding of the strengths and weaknesses of various IoT protocols, which could lead to more robust and efficient V2I systems, enhancing safety, improving traffic management, and ultimately paving the way for fully autonomous driving systems. Refer to Table 3 for the mapping of DQ dimensions against the various protocols.
# Design of Novel Laser Crosslink Systems Using Nanosatellites in Formation Flying: The VISION
## 5 Formation Flying Nanosatellite Bus
### Subsystems Design
#### 5.2.2 Electrical Power Subsystem (EPS)  
The satellites have two deployable and one body-mounted solar panels integrated with highly efficient multiple-junction GaAs cells. They are connected to buck-boost regulators, which guarantee a DC-to-DC conversion efficiency of 90%. The orbit average power generation was up to 21.9 W. The battery pack selected was 4S-2P lithium-ion cells with a capacity of 77 Wh capacity with 14.8 V as a nominal voltage. Table 9 summarizes the electrical power budget analyses for the operation scenarios. For the analysis, the maximum eclipse duration was applied over the mission's lifetime. With duty-cycled operation, the average power consumption was calculated. Given the DC-to-DC conversion efficiency of the regulators, the DOD for each mode was smaller than 20% according to the system requirements.
## 3 Simulation Setup and Results
The influence of the block size for each of the stages that comprise the proposed scheme on the BER performance is illustrated in Figure 5 for C-16 QAM and C-64 QAM. The results are obtained for a \(\Delta vT_{s}\) corresponding to 1 dB OSNR sensitivity penalty. It is observed that, in this case, a larger block size in the first stage, compared to the block size of the second stage, provides the optimum performance of the algorithm. This is attributable to the wrongly classified symbols during the ring selection process in the first stage that require a larger block size for its averaging.
# Electrochemical Characteristics of Amorphous Ni-P Electroplated Thin Film
## 1 Introduction
However, these synthesis methods require a high-temperature environment of 300 \({}^{\circ}\)C or more, as well as complicated devices, and it is difficult to control the particle size distribution of Ni-P powder [32]. On the other hand, the device required for the electroplating method is relatively inexpensive [33,34,35], and it is possible to synthesize an anode in the form of a thin film [32,36,37]. In addition, because the composition and microstructure can be easily controlled by adjusting the plating conditions [38,39,40], it is viable to synthesize Ni-P with suitable characteristics for the application. When synthesizing Ni-P using electroplating, as the phosphorus content increases, more phosphorus penetrates the nickel lattice, making the Ni-P deviate from the crystalline structure. When the phosphorus content is above a certain value (14-20 au%), it becomes an amorphous crystal structure [23,41]. As reported [17,42,43,44,45,46], amorphous structures exhibit a faster conversion-reaction rate than the corresponding crystalline structures. [PERSON] et al. reported that the cycling stability of an amorphous MnOx anode was improved because it had less deformation than a crystalline anode when it reacted with lithium, suggesting that amorphous materials could enhance the structural stability [42]. In this work, Ni-P amorphous thin films with different phosphorus contents were synthesized using electrolytic plating and tested as negative active materials for secondary lithium batteries. In particular, uniform Ni-P thin films containing 16-28 au% phosphorus were obtained at different plating conditions. To explore the possible use of amorphous Ni-P as an anode for a secondary battery, the initial characteristics (charge and discharge capacities, coulombic efficiency) and cycling stability were analyzed. In addition, the effect of surface morphology on the electrode performance was exploited by creating the globular electrodeposits on the surface of the thin film with a high phosphorus content.
## 5 Discussion
### Upholding Ethical Standards and Data Security While Enhancing PE Teachers' Digital Literacy  
Technology is a double-edged sword, presenting both unprecedented opportunities and risks through the integration of AI into systems for evaluating teaching behaviors in PE classrooms. Classroom interactions have been gradually quantified through increasing collection, analysis, integration, and sharing of data on teaching behaviors, making the teaching process and student performance more observable and measurable. While this transformation facilitates evaluations of teaching behaviors and instructional improvement, it also raises concerns about potential information leakage and privacy infringements, posing challenges to personal data security [36]. Prioritizing information security and privacy protection during the collection, analysis, and application of data on teaching behaviors is imperative. This requires strict adherence to relevant legal regulations and ethical guidelines to ensure the legitimacy and propriety of data handling activities [37].  
In this study, high-resolution video recordings that captured facial expressions, body movements, and interaction details were used for behavioral analysis [38; 39]. Accordingly, the system complies with stringent data protection regulations. Advanced encryption technologies, secure cloud storage, and routine security audits are implemented to safeguard data against unauthorized access, leaks, and cyberattacks [40]. Given the CogVLM2-Video model's reliance on extensive training data, it is critical to ensure data neutrality to avoid biases that could result in discriminatory outcomes. This means addressing issues of fairness, accountability, and transparency in algorithm design and application to comply with ethical requirements and reasonableness [41].  
Ensuring the digital literacy of PE teachers is also essential. According to Institute of Electrical and Electronics Engineers (IEEE)'s global initiative, \"All technical professionals must be educated, trained, and certified to prioritize ethical considerations in the design, development, and application of intelligent systems\" [42]. As users of this system, PEteachers need to acquire proficiency in interpreting and applying AI-generated data while leveraging their domain expertise. Targeted training programs are crucial to enabling teachers to gain a comprehensive understanding of the strengths and limitations of AI-based evaluation systems and of related ethical considerations. Teachers need to develop critical skills for evaluating AI insights judiciously, ensuring that instructional decisions are effective and aligned with their students' best interests.
# Present and Future Marine Microwave Satellite Missions in China
## 2 Development of Marine Satellites in China  
According to the overall planning policies, China will develop and build three series of marine satellite constellations: (1). The oceanic colour satellite constellation; (2). The marine dynamic environmental satellite constellation; and (3). The marine surveillance satellite constellation. The oceanic colour satellite constellation also referred to as HY-1 series satellites, mainly focuses on the observations of suspended sediment, seawater transparency, and chlorophyll concentrations in ocean areas. The development of this series was considered to be beyond the scope of this review [12; 13]. The marine dynamic environmental satellite constellation, also known as the HY-2 series satellites, mainly aims at the observations of sea surface wind fields, waves, sea surface heights, sea surface temperatures, and other ocean dynamic environmental elements [14]. The marine surveillance satellite constellation, which is also referred to as the HY-3 series satellites, mainly aims at the observations of sea surface targets, waves, sea surface wind fields, and internal waves. The progress and development plans of the HY-2 series and HY-3 series satellites are the focus of discussion in this review.
# Mapping Temperate Forest Phenology Using Tower, UAV, and Ground-Based Sensors
## 3 Results  
### Above- and Below-Canopy Comparisons  
NDVI explained a large portion of variance in GCCUAV for both center and composite below-canopy imagery based on linear regressions with R\({}^{2}\) values of 0.88 at 20 m for center imagery and 0.92 at 20 m for composite imagery (Figure 4a). R\({}^{2}\) for both center and composite imagery continued to rise with increasing buffer size, before stabilizing around 35 m. RMSE values dropped consistently with buffer size as well, with RMSE at 20 m buffer size of 0.12 for center imagery and 0.08 for composite imagery (Figure 4b). Regression slopes were consistently positive with increasing buffer size (Figure 4c). While composite imagery showed increased explanatory power, confidence intervals show this effect is small to insignificant, though confidence intervals do become more constrained after \(\sim\) 15 to 20 m buffer sizes.  
Figure 4: Linear regression output statistics of coefficient of determination (R\({}^{2}\)), residual mean standard error (RMSE), and slope for NDVI **(A–C)**, leaf area index (LAI) **(D–F)**, and gap fraction (**G–I**) from below-canopy imagery regressed against GCCUAV data where GCCUAV data at each iteration is averaged over an increasingly larger buffer size, starting at 5 m from center and increasing iteratively to 50 m in radius. Each point represents all plot-level measures of each variable against unoccupied aerial vehicle (UAV) with error bars indicating 95% confidence intervals.  
There were only small differences in LAI between center and composite imagery, though confidence intervals were consistently large, showing no constraint as buffer size increased. At 20 m, R\({}^{2}\) was 0.80 for both center and composite imagery, while RMSE was 0.56 for center imagery and 0.53 for composite imagery. Slopes for both were nearly identical and increased steadily with buffer size. Peak agreement, based on R\({}^{2}\), between above- and below-canopy imagery was in the 14 to 16 m buffer sizes, showing that increasing area of above-canopy GCC\({}_{\text{UAV}}\) averaging did not add additional information as it did in the case of NDVI. For scaling purposes, linear regression fit at 15 m buffer size was chosen for the scaling analysis, with coefficients of \(a=25.77\) and \(b=-7.71\) (Equation (3)). These data provide us with confidence that, 15 m and 20 m, are appropriate resolutions to scale LAI and gap fraction, respectively. A non-linear function was chosen over a linear function to scale gap fraction, with coefficients of \(a=65{,}354.32\) and \(b=-21.55\) for Equation (4). The non-linear function was chosen as the residual standard error was lower (3.20 vs. 4.87 for NLS and linear, respectively).