esa-sceva/satcom-chunk-collection huggingface dataset:
# Can Anaerobically Digested Food Effluent Support _Arthrospira platensis_ Cultivation in Open Ponds?
###### Abstract  
The cultivation of _Arthrospira platensis_ (Spirulina) is well-established in applied phycology, but the high cost of conventional media limits large-scale production. Anaerobically digested food effluent (ADFE), rich in nitrogen and phosphorus, offers a cost-effective alternative while mitigating environmental impacts. This study evaluated ADFE as a partial replacement for Zarrouk's medium, with 37.5%, 50%, and 70% substitutions, the latter two added incrementally. Cultivation was conducted in paddlewheel-driven raceway ponds under outdoor conditions for 22 days during the Australian autumn. The highest biomass productivity (8.83 g m\({}^{-2}\) d\({}^{-1}\)) was achieved with 70% ADFE, significantly outperforming Zarrouk's medium (\(p<0.05\)). Chlorophyll \(a\) content remained unaffected (\(p>0.05\)), and ammonium (N-NH\({}_{4}\)\({}^{+}\)) declined to near zero by day 9, indicating efficient nutrient uptake. These findings demonstrate that staged ADFE addition can successfully replace up to 70% of Zarrouk's medium while maintaining robust _A. platensis_ growth, highlighting its potential as a sustainable alternative for large-scale microalgal cultivation.  
raceway ponds; microalgae; biomass productivity; Spirulina; wastewater treatment 2025153115
# An Overview of Shared Mobility Operational Models in Europe
## 5 Scooter Sharing
### Operational Models  
Scooter services are the same as other previously mentioned shared mobility transportation models: docked and dockless system models. However, as there is confusion about models and services in previous models of sharing (carsharing and bikesharing), there is also confusion about scooter sharing services. While [83] defines service models of scooter sharing as docked and dockless, [81; 82] define that scooter sharing can only be dockless. As in [81], which references [84; 85; 86], it is defined that shared e-scooters have the particularity of being dockless, where the pick-up location and the drop-off location can be anywhere within the designated service area, and there is no need for physical docking stations. Although most shared e-scooters are dockless, some systems require users to return them to designated spots to complete the rental process. These spots do not need to have physical objects like totems or stands; they are, mostly just painted on the sidewalk where the e-scooter needs to be placed to finish the rental. As soon as there are designated spots to pick-up or drop-off a vehicle, the system is no longer dockless, but it becomes a docked system.  
In the Shared Mobility Manual [59], system models are categorized as either free-floating or station-based. The manual does not specify whether station-based systems must be docked; however, free-floating systems are also called dockless. The question of whether free-floating systems are actually dockless or a combination of several types was discussed in the previous chapter. In the case of scooter sharing, this aspect is especially important because many systems allow users to pick-up and drop-off scooters in flexible zones, but they still need to return to pre-designated sites, which are sometimes marked visually or with no infrastructure. Compared to bikesharing or carsharing systems, these characteristics make it harder to distinguish between dockless and docked.
## 2 Materials and Methods
### Data  
#### 2.2.1 Surveys and Elevation Models  
Aerial photos from surveys commissioned in the scope of several research projects were used to obtain orthomosaics and digital elevation models (DEMs) for the study area. Series of overlapping photos were taken from a small manned airplane carrying a digital photogrammetric camera (ZI-DMC, 7680 \(\times\) 13,824 pixels, for the 2008-2010 surveys, and Vexcel UltraCam Falcon, 9420 \(\times\) 14,430 pixels, for the 2018-2019 surveys) and flying at about 1000 m and 1600 m heights for the 2008-2010 and the 2018 and 2019 surveys, respectively, to provide high-resolution images with 10 cm and 12-13 cm ground-sampling distance, respectively. Images were directly georeferenced using an on-board GNSS/INS system. For postprocessing, the GNSS relative positioning mode was used. For each image, the position of the camera projection centre and the attitudinal angles were obtained, and a boresight alignment with ground control points was carried out to correct slight systematic effects in the attitude angles of about 0.02 degrees [31, 41, 42]. In situ measurements in built-up areas were used for calibration, as these contain features that can be used as accurate ground control points.  
Surveys were taken on 14 November 2008, 23 April and 11 November 2009, 5 May 2010, 17 May 2018 and 20 February 2019 during spring low tides. DEMs with 1 m resolution were computed from the pairs of stereoscopic aerial images after extracting correlated points through stereo-matching using the Agisoft software [43]. Final DEM accuracies were in the order of 10 cm and, therefore, close to the image resolution [42].  
Additionally, a Digital Terrain Model (DTM) from 2014 (kindly provided by the Direcao Geral do Territorio, available at [[http://mapas.dgetritorio.pt/inspire/atom/downloadservice.xml](http://mapas.dgetritorio.pt/inspire/atom/downloadservice.xml)]([http://mapas.dgetritorio.pt/inspire/atom/downloadservice.xml](http://mapas.dgetritorio.pt/inspire/atom/downloadservice.xml)) (accessed on 15 March 2022)) with a 2 m resolution was used to complement the elevation data.
# MapReduce Algorithm for Variants of Skyline Queries: Skyband and Dominating Queries
## 2 Related Works
Nowadays, the parallel computing paradigm becomes very popular for processing and analyzing \"big data\". Therefore the computation of skyline and its variants are becoming challenging today. Noted that [10; 11; 13] cannot be directly applied to evaluate top-\(k\) dominating queries. Moreover, the computation of skyband query requires a separate algorithm. This paper proposed an efficient algorithm for computing both types of queries(top-\(k\) dominating and skyband) over a large volume of data, such as \"big data\". For such data intensive applications, the most notable platform, which has attracted a lot of attention, is MapReduce For this kind of data-intensive application, the MapReduce framework has attracted much attention as the most prominent platform [20; 21; 22]. It facilitates the deployment of scalable parallel applications on the share-noting machines cluster for processing large dataset. Google's MapReduce or its open source equivalent Hadoop is a powerful tool for building such applications [23]. The MapReduce framework has also been utilized for some of the recent research works on the computation of skyline and \(k\)-dominant skyline [24; 25; 26]. Recently, [PERSON] et al. [27] exploits the MapReduce framework for computing top-\(k\) dominance on incomplete big data. Besides, [PERSON] et al. [28] utilized the Spark streaming framework to process top-\(k\) dominating query over the distributed data stream. Both [27; 28] divided the data by using the method of the hash map to process the data through distributed computing nodes. This paper complements the existing efforts to address the \(K\)-skyband and top-\(k\) dominating query problems by the rank of objects obtained using two intuitive scoring functions. Specifically, our algorithm can provide solutions for these two types of queries within the same framework. To the best of our knowledge, there is no such MapReduce algorithm had been proposed for the \(k\)-dominating query and the \(K\)-skyband query so far.
## 3 Results and Discussion
### Effects on Photoelectrochemical Performance  
#### 3.4.1 Current-voltage (I-V) Plots  
Figure 7 shows the I-V plots of the as-prepared \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) samples. The equilibrium potential of water oxidation (i.e., E(H\({}_{2}\)O/O\({}_{2}\))) is 0.1572 V vs. SCE in 1 M KOH electrolyte. For the undoped \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) in dark, the initial potential for the occurrence of current is 0.36 V, more positive than the equilibrium potential due to the existence of overpotential. When the undoped \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) sample is under solar irradiation, the initial potential moves to \(-\)0.22 V, much more negative than the equilibrium potential, indicating an obvious PEC effect. The doped \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) samples exhibit a similar initial potential to the undoped \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) under illumination. The initial potential of photocurrent is generally considered as flat band potential. The three samples have similar flat band potentials, which suggests that the doping of 5% Co or Ni does not change the energy band structure of the \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) nanorod array [42]. This conclusion is consistent with that derived from the Tauc plots (see Section 3.3).  
In addition to the initial potential, photocurrent at a certain potential is another index of the PEC activity. At 0.2 V vs. SCE, the photocurrent density of the Co-doped and the Ni-doped \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) are 1.28 mA/cm\({}^{2}\) and 0.79 mA/cm\({}^{2}\), respectively, which are 2.1 times and 1.3 times that of the undoped \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\). This result suggests the incorporation of Co and Ni into \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) nanorod array could enhance its PEC activity. The photocurrent densities of doped and undoped \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) reported in the literature are summarized in Table 1.  
Figure 6: Optical absorption features of the \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) nanorod arrays: **(a)** ultraviolet (UV)–visible absorption spectra; **(b)** Tauc plots.
## Appendix A Qualitative Analysis of Hurst Exponent and Entropy: Case-by-Case Description
### Okech (2008)  
In a similar form, but with an opposite trend to the Landoh time series, the Okech time series (Kenya, 2008) [27] also reveals a steady decreasing trend. In the Okech time series, malaria incidence consistently decreases from an initial peak of \(\sim\)400 cases _phy_, to a final value close to 50 cases _phy_.  
Consistent with the steady downward trend in \(I_{36}\) during the entire time series, we find an upper trend in the 36-month moving average of Hurst exponent (\(H_{36}\)), from an all-time-low of \(\sim\)0.6 at month 42, to a peak of \(\sim\)1.2 at month 82. Along with this upper trend in \(H_{36}\), there is a consistent decrease in entropy in the form of a 36-month moving average (\(S_{36}\)) over the whole time series. In the Okech time series, the behaviors of \(H_{36}\) and \(S_{36}\) are also quite correlated with the behavior of \(I_{36}\) in time--see Figures 13, 14 and 15.
# Nexus between Building Information Modeling and Internet of Things in the Construction Industries
## 1 Introduction
[20] presented an extensive review on integrating BIM and IoT to create more energy-efficient and environmentally friendly environments. The authors inferred that, with the integration of BIM and IoT, the built environment can be better managed, and the environmental effect of the construction industry can be reduced. [PERSON] et al. [21] investigated BIM, IoT, and blockchain technologies in the system design of a smart building. The authors viewed these understudies' technologies as complementing innovations that may work together to provide the safe storage and management of building-related data and information and to improve the IoT services offered. As the integration of BIM and IoT is still in its early stages, it is vital to get an awareness of the current situation related to its implementation in the construction industry. Vital questions such as what are the most often encountered BIM and IoT device integration scenarios? What classification system should be used to classify these application domains? what is the best way to combine BIM with IoT devices? what are the constraints, both in terms of application domains and integration methodologies, when it comes to both? What research gaps that need to be filled, and where should we go from here to conduct more successful investigations? Furthermore, this study highlights the obstacles connected with implementing the integration of BIM and IoT in construction projects, as well as determining the most critical challenges associated with the implementation. To address these research questions, this study performed a comprehensive review of BIM and IoT implementation in the construction industry, including a summary of application areas, and integration methods used in existing studies. The study also examined inherent limitations and anticipated areas for further research.
## 2 Background and Definitions
### Unmanned Aerial Vehicles (UAVs)  
An aerial network consists of multiple unmanned aerial vehicles (UAVs). Since UAVs are capable of flying, it is very attractive to deploy them as aerial base stations and relays [14]. The airborne UAVs can communicate directly with other airborne UAVs or with ground stations [15]. However, the management of UAV airborne networks poses significant challenges. These networks involve the exchange of vast amounts of information, including flight and control information, protocol stack information, sensing information, and data obtained from ground terminals. Furthermore, due to the constant motion of UAVs, wireless links and network topologies are continuously changing. As a result, managing and utilizing information, handling intermittent links, and maintaining a fluid topology have become highly challenging tasks [16; 17]. In maritime environments, UAV communication also faces challenges to the channel characteristics, including temperature of troposphere above the ocean, pressure, waveguide impact due to humidity, signal attenuation due to climate change, and uneven scatterer effect on UAV-to-ship communication due to irregular sea waves [18]. Current 5G cellular networks mainly focus on the terrestrial scenarios and do not cover maritime areas, causing difficulties in developing maritime IoT [19; 20].  
Due to the difficulty of deploying communications infrastructure on the ocean, the performance of existing maritime communication networks (MCNs) is far behind 5G [19]. However, the ubiquitous deployment of UAVs for wireless communication purposes can offer a potential solution to bridge the 5G gap between networks in the air and those on ground. With agile UAVs, there is an opportunity to provide maritime coverage in fixed sea lanes, without relying on costly satellite systems or on-shore stationary base stations. By employing a hybrid architecture, UAVs can establish connections with terrestrial base stations along the coast while utilizing satellites for backhaul over long distances. To better optimize the UAV deployment in response to the sporadic presence of ships in shipping lanes, it can be tailored to address the specific needs and requirements of users [19]. The use of tethered UAVs and helicopters is an alternative option for large ships and cruise ships. Tethering UAVs simplifies the provision of energy by allowing continuous power supply through the tether. This eliminates the challenge of limited battery life and enables the UAVs to operate for an extended duration [21, 22]. Tethered UAVs provide a reliable and continuous power source for aerial operations, making them suitable for various applications in maritime contexts.
## 5 Simulation Results and Discussion
### Sensitivity Analysis  
Sensitivity analysis is performed for the proposed controller under a wide change in system parameters [4,10]. Sensitivity is defined as the ability of the plant to work effectively while its variables are perturbed within a certain acceptable range [10,25]. In this study, the operating load conditions, \(T_{sg}\), \(K_{r}\) and \(T_{12}\), are changed in the range of \(-50\%\) to \(+50\%\) from their nominal values, individually. The quantitative analysis of the suggested FOFP-iPID controller in terms of ITAE, settling times, peak overshoots/undershoots with these changed conditions are furnished in Table 5 for 0.01 p.u SLP in area-1. It can be noticed from Table 5 that by enforcing \(\pm 50\%\) with the uncertainties mentioned above, the values of the ITAE, settling times, maximum overshoots and minimum overshoots of the fluctuations swerve from their prescribed values slightly. However, it can be observed that by enforcing the \(\pm 50\%\) extreme changes, the power plant is still dynamically stable since the damping measures are close to the prescribed values. For a better insight into the performance, the area frequencies and transmission-line power deviations are displayed in Figures 9-12. It can be concluded from these discussions that in the case of utilizing FOFP-iPID controller the large and imposing uncertainties (\(\pm 50\%\)) have a negligible impact on the plant performance. Briefly, the sensitivity  
Figure 8: Dynamic responses of the RLP in area-1: (**a**) RLP, (**b**,**c**) Frequency deviation in area-1 and area-2, respectively (**d**) ACE deviation in area-1 and (**e**) deviation power in tie-line 12.  
analyses demonstrated that the system equipped with the FOFP-iPID controller is meaningfully robust to the concerned variations. As a result, when adjusting the scaling factors (SFs) of the suggested FOFP-iPID controller that is optimized for the specified condition, there is no need to re-adjust for the \(\pm 50\%\) perturbation in parameter variations. Figure 10: _Cont_. Figure 9: Dynamic responses of the plant equipped with the suggested FOFP-iPID controller under uncertainties in loading condition. Figure 11: Cont. Figure 10: Dynamic responses of the plant equipped with the suggested FOFP-iPID controller under variation in (\(T_{sg}\)). Figure 11: Dynamic responses of the plant equipped with the suggested FGFP-iPID controller under variation in (\(K_{r}\)). Figure 12: Dynamic responses of the plant equipped with the suggested FGFP-iPID controller under uncertainties in synchronizing coefficient (\(T_{12}\)).
## 4 Example from the Heihe Station
Resolving these issues is the core scientific aim of the Heihe Station and the VRPC. Our observation activities and studies will focus on this topic continuously. Figure 3: Distribution of the validation sites in the HRB. At the Heihe Station, WSN is adopted widely to realize continuous, high-frequency, multi-point data acquisition of key ecological and hydrological parameters, such as LAI, FPAR, vegetation coverage, land surface temperature (LST), albedo, soil moisture, soil temperature, and snow depth; these parameters can be used to capture the spatiotemporal variations of key eco-hydrological parameters over a heterogeneous land surface at a remote sensing pixel scale [12, 24]. In practice, the sampling optimization method can consider the relationship of a target variable and environmental variables and can calculate the spatial autocorrelation of regression residuals to obtain the optimization design for the WSN nodes in the geographic space and simultaneously attribute that space at the Heihe Station [21, 22, 25]. To date, the Heihe Station has accumulated more than six years of ground-based observation data. Satellite data and airborne data during the same period are also obtained [23, 24]. These data have been widely used to validate the remote sensing products and to develop the remote sensing retrieval algorithms in the HRB. The validated and estimated variables include LAI [26, 27, 28], Gross Primary Productivity (GPP) [29], ET [15], LST [30], snow depth [31], and soil moisture [32]. The data are available for using and sharing online through the website of the Cold and Arid Regions Scientific Data Center.
# Emerging Perspectives of Blockchains in Food Supply Chain Traceability Based on Patent Analysis
## 4 Discussion
### Application Areas
The authors of [64] also agree that it is important that the introduction of blockchain technology in FSCs is not limited to this single technology, but rather to a whole stack of new technologies, including sensing technologies, big data analytics, artificial intelligence, Internet of Things robotics, digital twins, cyber-physical systems, 3D printing, and others. As the patents on topic C are mainly dealing with the implementation of IoT and other novel technologies, it could be assumed that development IT (development of mobile networks and accessibility of satellite communication) can be used to overcome remote agricultural production, but also remote consumption in Australia, while development of IT communications in India allows for overcoming the problem of missing conventional infrastructure. Finally, online trade is becoming part of the daily activities in many economic sectors, including food [63], and the application of BCs as a technology supporting online trade solutions is, therefore, another tenable field of innovation and patenting. [PERSON] [64] agrees that benefits of introducing BC technology in FSCs may address much wider issues related to food security and safety and human health in general, reduction of food waste and losses, animal welfare and climate change [65], as well as the development and digitalization of rural areas [66].
# Augmented Reality, Mixed Reality, and Hybrid Approach in Healthcare Simulation: A Systematic Review
## 3 Results
### Implementation of the Virtual Component of the Simulators (FQ2-5)
#### 3.4.2 Visualization Modality (FQ4)  
Available display technologies to provide the user with computer-generated information include: 2D monitors, hand-held displays (mobile phones and tablets), head-mounted displays (HMDs), and spatial projection-based AR displays.  
Most of the revised simulators [25; 26; 27; 28; 29; 33; 34; 36; 38; 39; 41; 43; 44] use a traditional 2D display. In these simulators (except for the commercial LapSim(r) and ProMIS(r) systems), the virtual information is not designed to interact in real-time with the real content (physical objects). Moreover, most of these simulators are for minimally invasive procedures not performed under direct vision. Indeed, [25; 26; 36; 44] are designed for laparoscopy, for endoscopic surgery [33], and for wire navigation in minimally invasive procedures [41; 43]. Finally, in [27] the monitor is used to show simulated fluoroscopic images to guide spine surgery. Among the other simulation systems for procedures involving the direct visualization of the anatomy, a particular solution is presented in [38]. This system uses a traditional monitor in a tilted position coupled with a half mirror placed horizontally between the user's head and his/her hands to visualize the virtual information superimposed onto the anatomical physical replica.  
Six papers [23; 29; 30; 34; 35; 40] report the use of a HMDs. These intrinsically provide the user with an egocentric viewpoint and allow handsfree work; for these reasons, HMDs are deemed the most ergonomic solution for applications including manual tasks performed by the user under direct vision, similar to what happens in open surgery. The devices selected by the AR/MR simulators evaluated are optical see-through HMDs (OST HMDs): these displays offer an instantaneous and unobstructed full resolution view of the real environment allowing a naturalistic experience. In more detail, the simulators in [23; 40] are based on Microsoft HoloLens (1 st generation), [30] is based on AiRScouter WD-200B, and [35] presents the design of an innovative custom-made OST HMD. Finally, HMDs are also used in [29] (NVIS nVisor ST50) and [31] (HTC VICE MIS) for virtual reality immersive experience.  
Only two simulators [22; 32] employ a hand-held display: these systems are designed for AR visualization of VR anatomical models for surgical planning [22] or training of medical and anatomy students [32]. None of the simulators employ a spatial projection-based AR display.