esa-sceva/satcom-chunk-collection huggingface dataset:
# Homogeneity and Trend Analysis of Climatic Variables in Cap-Bon Region of Tunisia
## 1 Introduction
A long-term time-series trend analysis involves the trend slope and its statistical significance [19]. Non-parametric tests, such as the Mann-Kendall test, Sen's slope and Spearman's Rho, are largely used by scientists to detect the trends in historical series of climatic variables [10; 20; 21; 22; 23; 24]. Nevertheless, non-climatic factors can bias climate patterns and signals, which mislead the conclusions of climatic-related studies. Thus, testing the homogeneity of the long-term time series of climate variables before their use is highly recommended. Different homogeneity tests have been proposed in the literature, including the Pettitt test [25], the Standard Normal Homogeneity Test (SNHT) [26], the Buishand range test [27] and the Von Neumann ratio test. The SNH test detects abrupt shifts at the extremes of the series. However, the Pettitt and Buishand tests identify breakpoints in the middle of the series [28]. The sources of abrupt changes in climate data might be related to the relocations of meteorological stations, the changes in observation time and methods of variable calculation [29]. Another factor likely to lead to climate change is the modification of large-scale atmospheric circulation [30]. Detailed analysis of the hydro-climate trend and variability is essential for better national and local water resources management and, therefore, for better agricultural planning activities, hydrological modeling and climate change studies. Comprehension of water balance components and their pattern in the future is essential for water resources management and sustainable development. Previous research indicates that most climate variables, except temperature, are expected to present varying trends in time and space [16]. Tunisia is facing a moving up of aridity from the south to the north of the country. This has led to a decrease in cultivable areas and a risk of a considerable drop in yields and national agricultural production. In addition, a clear downward trend in water resources availability and a significant increase in water demand have occurred as a consequence of the increase in ET0, resulting in a water balance deficit being observed [31; 32]. However, limited information is available on Tunisia, in particular on the Cap-Bon region, which is considered an important agricultural hub contributing 15% of the national agricultural production value. In this study, different methods of trend detection and breakpoint analysis have been employed for long-time series of climatic variables of minimum and maximum air temperature and precipitation of the Nabeul region. The present study could help different actors (scientists, hydrologists, environmentalists, crop producers, irrigation managers, water resources managers, etc.) to adopt strategies for sustainable water resources management and therefore to ensure agricultural and food sustainability.
## 2 In the Beginning
### The Message Broker  
A message broker is a software module that allows applications, systems, and services to communicate with each other, translating a message from the sender's formal communication protocol to the receiver's one. This allows interdependent services to \"talk\" directly with each other, even if they have been written using different languages or implemented on different platforms. Message brokers act as intermediaries between different applications, so senders can send messages without knowing where the recipients are, whether they are active or not or how many of them are present. This clearly facilitates the decoupling of processes and services within systems. The task of a message broker is obviously not only to pass data, as it also deals with aspects related to security, priority, and orderly forwarding of messages.  
Typically, the message broker is instantiated in a server process communicating with both the sender and the receiver using their respective communication protocols, thus providing status control and tracking of all customers who are involved in the communication, in order to avoid that individual applications should implement the aforementioned functionalities and complex message delivery.  
Generally speaking, the entities that interact in the Message Broker context are:  
* One or more Producers, i.e., processes generating messages;
* One or more Consumers, i.e., processes dealing with the handling of messages;
* The Message Broker himself, storing messages coming from Producers and forwarding them to the Consumers.  
The nature of middleware allows a message broker to decouple heterogeneous systems which, with other configurations, would be strongly coupled; a message broker can validate, store, direct, and deliver messages to the correct destinations, in fact they are typically used as intermediaries between applications. This implies that producers can deliver messages to brokers without even knowing which consumers will process them. To provide a reliable message storage system and a guarantee of message delivery, brokers typically rely on a structure called a message queue that stores and sorts messages until consumers have processed them.  
Message brokers commonly use an asynchronous model of message communication: This prevents the loss of important data and allows systems to continue operating even in presence of intermittent connectivity or latency problems, as typical in public networks. Asynchronous messaging ensures that messages will be delivered once (and only once) in the correct order relative to other messages.
## 2 Composite Signal's Distribution and the Dataset  
This section describes how an outgoing composite signal is generated using multiple M-ary quadrature amplitude modulated (MQAM) signals. The residual sum of squares (RSS) and Kullback-Leibler (KL) divergence [26] are used to determine a theoretical distribution that closely fits the voltage distribution of the summed signal. This theoretical distribution is used to generate a dataset to train a DNN to estimate the distribution's parameters [3].
# Design of an Isolated Bidirectional Symmetric Resonant Converter
## 2 Circuit Structure and Operation Analysis
### Description of Operating Range
#### 2.3.5 Stage V [\(t_{5}<t\leq t_{6}\)]  
As shown in Figure 6e, \(Q_{1}\) and \(Q_{4}\) are cut off at \(t=t_{5}\) while \(Q_{2}\), \(Q_{3}\) still remain at the cut-off state. This exactly marks the dead time region with resonant current \(i_{L71}\) charging the parasitic capacitors \(C_{OSSI}\) and \(C_{OSS4}\) as well as helping \(C_{OSS2}\) and \(C_{OSS3}\) to discharge. In the secondary side, \(D_{B6}\) and \(D_{B7}\) conduct, and \(D_{B5}\) and \(D_{B8}\) cut off. When the voltages on \(C_{OSS2}\) and \(C_{OSS3}\) are discharged to 0 and simultaneously \(C_{OSS1}\) and \(C_{OSS4}\) are charged to \(V_{DC\_Grid}\), this stage terminates.  
The abovementioned process from Stage I to Stage V constitutes the whole operation procedure during the positive cycle. The negative cycle has similar operating stages and thus is omitted here.
## 2 Theoretical Strength of Plate-to-RHS Connections
### Bolded Joint of Branch Member  
The connection strength \(P_{CP}\) in the direction of the branch axis, computed by Equation (3), should not exceed the maximum force that the bolted joint of the branch member can carry. The design limit states those that need to be accounted for at the bolted joint include bolt shear yielding, connection slip, hole bearing, and the tensile yielding and block shear rupture of the gusset plate (see Figure 3b). Among various failure modes at the bolted joint, the slip and subsequent hole bearing are critical in the truss connection investigated in this study. According to AISC 360-16 [1], the slip strength and hole-bearing strength, \(P_{slip}\) and \(P_{bearing}\), respectively, can be computed as follows.  
\[P_{slip}=\mu h_{f}(N_{b}T_{o})N_{s} \tag{10}\]  
\[P_{bearing}=1.2L_{c}t_{g}F_{ug}\leq 2.4d\,t_{g}F_{ug} \tag{11}\]  
where \(\mu\) = slip coefficient at the faying surface, taken as 0.33 for unpainted clean mill scale steel surfaces; \(h_{f}\) = filler coefficient, which is taken as 1.0 if a filler is not used; \(N_{b}\) = total number of bolts at the joint; \(T_{o}\) = pretension of a single bolt; \(N_{s}\) = number of frictional surfaces; \(L_{c}\) = clear distance in the direction of the force between the edge of the hole and the edge of the adjacent hole or edge of the gusset plate; \(d\) = bolt diameter; \(t_{g}\) = thickness of the gusset plate; and \(F_{ug}\) = ultimate strength of the gusset plate.  
For the K-connection where both tensile and compressive branch members are jointed, the strengths of the bolted joints in the longitudinal direction of the chord member, \(V_{slip}\) and \(V_{bearing}\), respectively, can be determined as follows.  
\[V_{slip}=2P_{slip}\cos\theta\text{ for K-connections} \tag{12}\]  
\[V_{bearing}=2P_{bearing}\cos\theta\text{ for K-connections} \tag{13}\]  
If slip is not allowed at the bolted joint, the chord face plastification strength \(V_{CP}\) by Equation (4) should not exceed \(V_{slip}\). However, even after slip occurs, the bolted joint may not fail until \(V_{CP}\) reaches \(V_{slip}\) plus \(V_{bearing}\) because hole bearing that is activated after the slip provides additional resistance.
# The Effect of Varying Out Beverage Ratios on the Characteristics of Fermented Dairy-Oat Beverages
## 3 Results  
### Primary Chemical Components of Beverages Prior to Fermentation  
The initial dry matter content of cow's milk was 11.84% and decreased gradually with increasing oat beverage addition (Table 2). Significant differences (\(p<0.05\)) in dry matter were observed from as low as 25% oat beverage addition, suggesting that even small additions of oat beverage significantly diluted the solid content. The lowest dry matter value was achieved with 100% oat beverage (10.14%), which is attributed to the lower nutrient density of oat beverage compared to milk. As the proportion of oat beverage increased, protein content decreased from 3.16% in pure cow's milk to only 0.74% in 100% oat beverage (Table 2). The oat beverage contains significantly less protein than milk, explaining the systematic decrease. These differences were statistically significant at all addition levels (\(p<0.05\)). Lipid content decreased gradually from 3.20% in pure milk to 1.14% in 100% oat beverage (Table 2). The differences were statistically significant, indicating a lower fat concentration in oat beverage compared to milk. The total carbohydrate concentration demonstrated a positive correlation with the increasing proportion of oat beverage, ranging from 4.66% in pure milk to 7.62% in 100% oat beverage (Table 2). The increase in carbohydrates was statistically significant at all levels of oat addition (\(p<0.05\)). This is due to the high carbohydrate content in oat beverage, which primarily consists of starch and beta-glucans. Lactose content decreases as the proportion of oat beverage increases, since oat beverage is lactose-free (Table 2). Even with a 50% oat beverage mixture, the lactose level was already more than halved compared to pure milk, suggesting that mixtures with a higher oat content may be better tolerated by individuals with lactose intolerance. In 100% oat beverage, lactose is completely absent.
# A Complete Pipeline for Heart Rate Extraction from Infant ECGs
## 3 Discussion
### Limitations  
The research carried out here tested the performance of existing open source approaches on an infant ECG dataset. There are other approaches not included in these open source packages that can show improved performances on infant datasets, and the nature of open source software means that these approaches are susceptible to change. This research was carried out on version 0.2.3 of Neurokit2 and version 1.2.6 of HeartPy. Version 1.1.1 of PyEMD was used for the EMD analysis.  
An additional limitation of the Neurokit2 peak-detection method was that heart rates faster than 200 bpm were often mislabelled (with only alternate peaks being detected). It is rare, but not impossible, for an infant heart rate to exceed 200 bpm, and so care must be taken if this occurs.  
As is usual with the filtering methodology, our HR pipeline is also dependent on filter selection. We accounted for this by verifying the effect of different parameters on clean and noisy HR signals and generated a set of optimal parameters for both scenarios. Additionally, the pipeline was developed on a typically developing population without known cardiac issues. An ECG containing a lot of arrhythmias or other HR irregularities may not be suitable for an automated cleaning approach carried out in this manner. Similarly, the SQI portion of the heart rate pipeline is also dependent on tuning parameters.  
Finally, while we endeavoured to label a ground truth, there was some fundamental uncertainty regarding R-peak locations in noisy ECGs. Noise is exacerbated in free-moving individuals and such a movement is often heightened in infants. While we did our best to adjust for this uncertainty (see Appendices B and E), it must be considered alongside the results.
## 4 Findings and Discussion
### Environmental Impact Produced
#### 4.4.1 Carbon Footprint  
The production, treatment, and disposal of PPE implies a carbon footprint (CF); moreover, the total carbon footprint for surgical masks used from March 2020 to December 2021 was calculated to be approximately 240 kton [70]. Some studies used life cycle assessment (LCA) techniques to determine the CF of PPE. For example, a study on disposable medical face masks revealed a CF of 21.5 g CO\({}_{2}\)-eq, of which the main contributor was the raw material supply (40.5%), followed by packaging (30.0%) and production (15.5%) [71]. Other studies reported CF values between 22 and 59.5 g CO\({}_{2}\) per mask [10, 11, 12, 13], attributing 60% to PPE production, especially textile production (40%), with the remaining 40% linked to disposal [10]. A computational model estimated that the use of each disposable surgical mask and embedded filtration layer (EFL) reusable face mask produced between 18.7 g CO\({}_{2}\)-eq and 0.338 kg CO\({}_{2}\)-eq [72]. On the other hand, reusable cotton masks have a total carbon footprint of 285.484 kg CO\({}_{2}\)-eq/FU, which implies that they reverse the trend and become more environmentally friendly after 17 washes [72]. Studies that determined greenhouse gas emissions during the production, transport, sterilization, and end-of-life processes of FFP2 face masks showed that the CF was 58% in the case of face masks that were reused five times after a sterilization process compared with new single-use face masks [29]. In any case, all these studies revealed the relation between the composition of face masks and the CF, as well as the reduction in the CF of reused masks; therefore, future research on developing environmentally friendly PPE should focus on innovative materials that are easily washable, disinfectable, or susceptible to recycling.
## 5 Experiments and Results
### Comparison of SC-M* to Baselines
#### 5.3.1 Path Cost
Agents \(r1\) and \(r2\) attempt to move from vertexes \(a\) and \(f\) to vertexes \(e\) and \(g\), respectively. The individually optimal paths (shortest distance) for both agents are \(a\to b\to c\to d\to e\) with distance 4 for \(r1\) and \(f\to b\to c\to d\to g\) with distance 4 for \(r2\), respectively. The total cost of the joint individually optimal path is 8. \(r1\) and \(r2\) softly collide on the edge \(b\to c\) and \(c\to d\), where \(r2\) can tolerate the dissatisfying experience with distance 2. However, \(r1\) can only tolerate the dissatisfying experience with distance 1 and announces a collision at the vertex \(d\). When using SC-CBS, we record the collision that occurred to \(r1\) as [\(r1\), \(d\), \(3\)], indicating that agent \(r1\) will collide at vertex \(d\) at the third step. Then, SC-CSB will avoid any paths leading \(r1\) to \(d\) at Step 3 (including \(a\to b\to x\to d\to e\) and \(a\to b\to c\to d\to e\)) and will end up with a longer detour through vertex \(y\). The SC-CBS solution has a cost of 5 for \(r1\) and 9 in total. When using SC-M*, the collision at \(d\) triggers the sub-dimensional expansion of the search graph in dimension 1, which includes both \(x\) and \(y\). Thus, it can find a cheaper collision-free path through \(x\) and end up with a path \(a\to b\to x\to d\to e\) with a dissatisfying experience of distance 1 and a cost of 4.5 for \(r1\) (8.5 in total). However, SC-M* does not expand dimension 2 because no collision has been announced by \(r2\). When using SC-A*, the joint search space of both dimension 1 and dimension 2 is expanded and searched. Instead of vertexes \(x\) and \(y\), SC-A* will first investigate vertex \(z\) in dimension 2 according to some heuristics. This process leads to another cheaper path \(f\to b\to z\to d\to g\) with distance 4 for \(r2\) (8 in total, which is the same as the individually optimal cost) and avoids all interference by moving through this path. As a result, SC-A* returns an optimal solution that satisfies the soft-collision constraint at the expense of search space. The example in Figure 8 illustrates the optimality of SC-A* and the advantage of SC-M* in path cost over SC-CBS. To be specific, SC-M* provides a better solution than SC-CBS by searching thoroughly  
Figure 8: Illustration of the difference in planning among soft-collision A* (SC-A*), soft-collision M* (SC-M*), and soft-collision conflict-based search (SC-CBS). through the expanded dimensions, whereas the way SC-CBS identifies collisions is inappropriate in the soft-collision context. To the best of our knowledge, no other methodology capable of dealing with the soft-collision path planning defined in Equation (11) has been developed. It is expected that, in the future, more high-performance algorithms will be developed for solving the problem.
###### Abstract  
The development and study of a novel and very miniaturized ultra-wideband (UWB) wearable band-notch antenna for body sensor networks (BSNs) and mobile healthcare system have been presented in this paper. A very user-friendly and reliable software Computer Simulation Technology (CST)(tm) Microwave Studio was used for the modeling and simulation purpose of this antenna. The antenna is a textile-based UWB notch antenna, as it was printed on jeans' textile substrate. The simulated performance parameters, such as return loss, bandwidth, gain, radiation efficiency and radiation patterns of this antenna are demonstrated and analyzed. The main aim of this paper was to design a textile-based compact UWB antenna with the characteristics of band notch in X-band to reject the down link band (7.25 GHz-7.75 GHz) of satellite communication in the UWB frequency ranges of 3.1 to 10.6 GHz in order to avoid interference. The simulated results show that this antenna has very well band notch characteristics in the frequency range of 7.25-7.75 GHz. The overall dimension of the antenna is 25 mm in length and 16 mm in width, which is very compact. The antenna is printed on 1 mm Jeans' textile with the dielectric constant of 1.7. This antenna shows very good results; it has compact size and is printed on textile material, and has band notch characteristics to avoid interference. Due to all these attractive characteristics, it will be a good candidate for body sensor networks for a mobile healthcare system.  
noc 2020 2020 3 1 [datech]organization
# A Review on Standardizing Electric Vehicles Community Charging Service Operator Infrastructure
## 5 The Proposed Architecture
### Standardized Layer  
The EV charging connector layer comprises different types of EVs along with the compatible charging standards that need to be standardized. Therefore, the key criterion of the standardized layer is to work on developing the required standardized pins and  
Figure 9: The proposed EV charging station standardization architecture.  
communication protocol that to fulfill the basic configuration and specifications of the arriving EVs with different charging standards at the charging station. For example, the SAEJ1772 charging standard contains five pins, including Line 1, neutral, control pilot (CP), proximity pilot (PP), protective earth (PE), signalling, and the powerline communication (PLC) protocol. Line 1 is used as a single phase power supply for slow EV charging.  
The other component control pilot is responsible for charging EVs from the electric grid with the help of a transferred signal. Another is PP, which transfers the signal to the vehicle while connected to the CS to avoid any kind of interruption during charging. On the other hand, Type-AC also includes similar components with the additions of Line 2 and Line 3 to accentuate the three-phase supply for fast EV charging, and power can be supplied from the charger to the EV through the electric cable using the signaling communication protocol. Similarly, charging standards such as CCS Combo 1 and combo 2 also resemble the Type-2 AC charging standard along with the two additional pins, i.e., the DC+ and DC\(-\) lines to facilitate fast DC charging for EVs using High level communication (HLC) protocol. Alternatively, CHADEMO consists of ten pins with two additional pins, i.e., DC+ and DC\(-\) with one more pin to communicate the signal for charging to the EV using the Controller Area Network (CAN) bus protocol. On the other hand, Bharat AC and DC-001 charging standards have a similar number of pins to the Type-2 AC charging standard, but do not contain the CP and PP pins, respectively. Therefore, we incorporated the standard features and communication protocols of these charging standards to develop a standardized charging standard for sustainable and adaptable EV charging (we will analyze the important aspect of charging time and charging cost while implementing the EV standardized charging infrastructure for efficient charging in the future).
# Applications of Water Jet Cutting Technology in Agricultural Engineering: A Review
## 3 Applications of Water Jet Cutting Technology on Different Agricultural Materials
### Vegetables
#### 3.1.1 Harvesting and Fresh Cutting  
As early as 1972, [PERSON] [33] designed a horizontal jet cutting machine for harvesting lettuce crops and found that the complex field environment and cleanliness of lettuce after cutting would limit its application. Moreover, the mobile harvester must carry enough water, which requires more space and increases its weight. [PERSON] et al. [42] added a catcher device near the horizontal jet nozzle of the sugar beet harvester to recycle cutting water to reduce the water carried. They advised that the catcher on a mobile machine should be designed as a compact device to collect cutting water. Furthermore, they proposed dissipating the water jet energy into kinetic energy of many small obstacles to minimize the abrasion caused by water jet splash.  
Comparably, the trimming and cutting of vegetables in the factory can be achieved more easily than harvesting in the field with fewer limitations of equipment and environment. Soft leafy vegetables and rhizes with stable structures have achieved fresh cutting operations using water jets, including lettuce, carrots, potatoes, etc. [PERSON] et al. [43] conducted water jet cutting experiments using polycarbonate, polystyrene, and polyethylene materials with a thickness of 2 mm as samples to replace agricultural goods with similar characteristics. The results indicated that water jet cutting technology could process post-harvest products. [PERSON] et al. [44] successfully cut carrots with diameters of 90 mm using a water jet to trim carrot crowns.  
Figure 2: Different jet nozzle structures of two mixing methods: (**a**) Pre-mixing jet nozzle; (**b**) Post-mixing jet nozzle.