esa-sceva/satcom-chunk-collection huggingface dataset:
# Sustainability Assessment on an Urban Scale: Context, Challenges, and Most Relevant Indicators
## 3 Results and Discussion Regarding the Selected Indicators within the Potential Categories
### Transportation Infrastructure  
The second proposed category of the environmental dimension of sustainability assessment focuses on analysing issues related to transportation infrastructure. Figure 2 shows that this category is promoted by all of the studied sustainability assessment methods and is addressed through four indicators. Urban mobility concerns the ease of movement of people and goods. Many cities increasingly face problems caused by transport and traffic. According to the EU commission, efficient and effective urban transport can significantly contribute to achieving objectives in a wide range of policy domains for which the EU has an established competence. However, urban mobility is broad and involves intermodal articulations, where different means of transport, alternative transport options, and efficient accessibility must be planned in an integrated way. This approach is guided by the SDGs, focusing on convenient access to public transport, according to SDG 11 and SDG 9. Moreover, ISO promoted measuring the distance of public transport systems and providing access to public transportation near living areas. Therefore, the essential indicators are described below:  
Availability and access to public transport facilities (accessibility, quality): This indicator focuses on the analysis of the accessibility to the alternative transport options, quality of the public transport road network, and transit facilities to increase the quality of transport, as well as local and intermodal connections, which have the potential to reduce the use of private vehicles. This indicator is addressed by SBtoolPT_Urban (2018), SNTool (2020), BREEAM-C (2012), and LEED ND (2018), and supported by SDGs and ISO 37120.  
Quality of pedestrian and bicycle networks: This indicator consists of pedestrian path accessibility and cycling network and facilities indicators (Figure 2). It focuses on the analysis of cycling and walking as alternatives to using cars by providing safe and efficient pedestrian and bicycle networks. This indicator is addressed by SBtoolPT_Urban (2018), SNTool Min (2020), BREEAM-C (2012), and LEED-ND (2018), and supported by SDGs and ISO 37120. The study proposed a combined form of the indicator based on how SNTool promotes it.
# Improvement of the Zienkiewicz-Zhu Error Recovery Technique Using a Patch Configuration
###### Abstract  
The Zienkiewicz-Zhu (ZZ) super-convergent patch recovery technique based on a node neighborhood patch configuration is used most widely for recovery of the stress field of a finite element analysis. In this study, an improved ZZ recovery technique using element neighborhood patch configuration is proposed. The improved recovery procedure is based on recovery of the stress field in the least-squares sense over an element patch that consists of the union of the elements surrounding the element under consideration. The proposed patch configuration provides more sampling points and improves the performance of the standard ZZ recovery technique. The effectiveness and reliability of the improved ZZ recovery approach is demonstrated through plane elastic and plastic plate problems. The problem domain is discretized with triangular and quadrilateral elements of different sizes. A comparison of the quality of error estimation using the ZZ recovery of derivative field and recovery of the displacement field using similar element neighborhood patch configurations is also presented. The numerical results show that the ZZ recovery technique and the displacement recovery technique, using a modified patch configuration, yield better results, convergence rate, and effectivity as compared with the standard ZZ super-convergent patch recovery technique. It is concluded that the improved ZZ recovery technique-based adaptive finite element analysis is very effective for converging a predefined accuracy with a significantly smaller number of degrees of freedom, especially in an elastic problem. It is also concluded that the improved ZZ recovery technique captures the plastic deformation problem solution errors more reliably than the standard ZZ recovery technique.  
error estimation; effectivity; Zienkiewicz-Zhu techniques; stress recovery; displacement recovery; patch recovery; least-squares techniques Article  
Improvement of the Zienkiewicz-Zhu Error Recovery Technique Using a Patch Configuration  
[PERSON], [PERSON], [PERSON], [PERSON], M.A.  
1 Civil Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia; [EMAIL_ADDRESS]  
2 State Insurance Corporation, New Delhi 110077, India; [EMAIL_ADDRESS]  
3 Mechanical Engineering Department, Royal Commission of Jubali & Yanbu, Yanbu 41912, Saudi Arabia; [EMAIL_ADDRESS]  
4 Correspondence: [EMAIL_ADDRESS]; Tel.: +966-172-418-439
## 3 WEEE and ELV Management and Circular Economy
### Recovery and Destruction
#### 3.1.3 Other Technologies  
The destruction of ozone-depleting substances can also be achieved by converting them into other useful by-products, instead of incinerating them. Different technologies have been approved for the destruction of those substances and have shown potential to also be used for the destruction of HFCs. These technologies include: (i) the conversion by hydration of the compounds into HF, HCl, and CO\({}_{2}\) in a superheated steam reactor whose walls are heated up to 1000 \({}^{\circ}\)C, followed by quenching and neutralization of the acids using a Ca(OH)\({}_{2}\) solution [39]. This technology, which is being applied in commercial facilities in Japan and China, is safe, easy to operate and has high destruction efficiency and low emissions of pollutants [39]; (ii) the Gas Phase Catalytic Dehalogenation of the compounds at 400 \({}^{\circ}\)C with the neutralization of produced HCl and HF in a Ca(OH)\({}_{2}\) solution [39]. Japan reported the utilization of this technology to destroy CFCs, HCFCs and HFCs or HFC blends, such as R-134a (GWP 1300), R-245 fa (GWP 858), R-404A (GWP 3922), R-407C (GWP 1774), R-407D (GWP 1627), R-407E (GWP 1552), R-410A (GWP 2088), R-417A (GWP 2346), R-507A (GWP 3985) and R-508A (GWP 13,214) [39]; and (iii) the conversion of the compounds into HF, HCl, CO, and H\({}_{2}\)O by chemical reaction with H\({}_{2}\) and CO\({}_{2}\)[39]. The produced acids are not neutralized but collected as high purity products [39]. This technology is used by a company in the United States and has been tested for the degradation of HFCs in China [39].  
Other technologies have been investigated for the degradation of HFCs, including the photodegradation of R-134a (GWP 1300) [49] and R-152 (GWP 16) [50] with TiO\({}_{2}\) and UV light, and the degradation of HFCs using Bi\({}_{2}\)O\({}_{3}\) as a photocatalyst under visible light irradiation [51].
# Effect of the Inter-Ring Delay Time on Rock Fragmentation: Field Tests at the Underground Mine
## 3 Theoretical Analysis of IRDT in Tunnel Excavation Blasting
### Explosive Load and Rock Interaction Processes  
The processes of rock damage due to explosive blasts are shown in Figure 4. First, the rock is under the action of the shock wave to form a burst cavity and a crushed area. Second, the shock wave decays into a compressive stress wave, the action of the stress wave in the rock under the circumferential and radial fractures, while the role of explosive gas under the fracture further expands. Again, the compressive stress wave is reflected towards the free surface, generating tensile stress waves that cause spalling of the rock near the free surface and further propagation of radial cracks. Finally, the high temperature and high-pressure burst of gas expands to push the rock mass, forming a bulging phenomenon on the surface of the rock. The study conducted by [PERSON] revealed that initiating blasting in post-blast holes is appropriate when the first blast hole just formed a blast funnel and the blasted rock from the rock formed a 0.8-1.0 cm wide fracture [20]. The formula for calculating the delayed time is given as:  
\[\Delta T=t_{1}+t_{2}+t_{3} \tag{4}\]  
where is delay time, ms; \(t_{1}\) is the time for the elastic wave to travel to the free surface and return, ms; \(t_{2}\) is the time to form a fracture, ms; and \(t_{3}\) is the time for the broken rock to leave the rock body at a certain distance, ms. It is evident that the length of blast holes and the timing of delays in mine blasting are interrelated and have a significant effect on the ore fragmentation. The blast hole length determines the depth and range to which explosive energy is applied to the rock mass; extended blast holes can impart energy more profoundly, leading to broader rock fracturing. With judicious design of the delay timing, the outcomes of blasting can be optimized; a well-calibrated delay facilitates better interconnection of the fractures induced by the blast, thereby improving the quality of ore fragmentation and the evenness of the fragment size distribution.  
Based on this, the total times \(t_{1}\) and \(t_{2}\) were considered to be the time of the free surface formation after the explosive detonation, the action of shock waves and explosive-generated gas, and the fracture has been fully formed, with an obvious blast funnel contour line (Figure 5a). Here, \(t_{3}\) is the time to throw the rock a certain distance, while the explosive-generated gas continues to expand to throw the debris a certain distance (Figure 5b) until a blasting funnel is formed (Figure 5c).
# Conductive Ink Printed Fabric Antenna with Aperture Feeding Technique
###### Abstract  
Screen-printed and inkjet-printed conductive fabric antennas have been investigated in this manuscript. The former showed optimal radiation performance after fabrication and measurement, which was the basis for developing a new fabric antenna feeding technique. The aperture-fed technique is achieved with a single coaxial cable overlayed on a cut-out slot on the ground layer of the patch antenna. The cable is connected with conductive silver-based epoxy paste with high resilience to mechanical stress. Two antenna models for Bluetooth low energy (BLE) and long-range (LoRa) wireless applications were designed, fabricated, and measured at 2.44 GHz and 868 MHz, respectively, with good impedance and radiation performance. The measured antennas operated from 2.4 to 2.48 GHz (BLE) and 853 to 886 MHz (LoRa) at \(-10\) dB \(S11\). Measured results also showed a 56% radiation efficiency at BLE and 44.9% at LoRa. The screen-printing procedure and feeding technique have been presented in this manuscript.  
antenna feeds; aperture-fed antennas; BLE; conductive textile; inkjet-printed antenna; LoRa; screen-printed antenna; wearable antennas Article
# Headspace Solid-Phase Microextraction Analysis of Volatile Components in Peanut Oil
## 2 Results and Discussion  
### Optimal Absorption Fiber  
In this study, five different adsorption fibers were used, including 50/30 \(\upmu\)m divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS), 65 \(\upmu\)m polydimethysiloxane/dvinylbenzene (PDMS/DVB), 75 \(\upmu\)m polydimethysiloxane/carboxen (CAR/PDMS), 85 \(\upmu\)m polyacrylate (PA), and 100 \(\upmu\)m polydimethysiloxane (PDMS), to extract volatile components in peanut oil. For black shell-140, the results indicate that 75 \(\upmu\)m CAR/PDMS exhibited poor separation efficiency for compounds at 10 min prior to the retention time, and 65 \(\upmu\)m PDMS/DVB exhibited poor adsorption capacity for small molecules. Therefore, the use of 50/30 \(\upmu\)m DVB/CAR/PDMS produced a better effect on peanut oil and exhibited excellent extraction capacity (Figure 1).  
The polarity of a fiber is an important criterion for extraction. Different fiber coatings affect the types of adsorbed volatile compounds. Compared to DVB/CAR/PDMS, CAR/PDMS fibers are more suitable for adsorbing low-molecular-weight compounds; however, as the DVB/CAR/PDMS fiber is bipolar, both polar and nonpolar compounds can be extracted. Because DVB, CAR, and PDMS are highly sensitive to polar, small-molecule, and nonpolar volatile compounds, respectively, using a 50/30 \(\upmu\)m DVB/CAR/PDMS adsorption fiber can extract a greater amount of volatile components from edible oil.  
The 50/30 \(\upmu\)m DVB/CAR/PDMS fiber is typically used for flavor analysis; it is particularly effective for pyrazine extraction [17] and is most suitable for identifying volatile oxygen-containing substances in vegetable oils. This method has been successfully used to track oil and the formation of volatile substances (such as hexanal, _trans_-2-hexenal, _trans_-2-heptenal, nonanal, 2-pentylfuran, and 1-octen-3-ol) when the product is oxidized [18].
# Optimization and Experimental Verification of Lower
## 3 Experimental Verification of Lower Articulation
### Structural Test
#### 3.1.2 Structural Test Results  
To validate the structural analysis, load resistance, and local strain of the lower articulation, structural tests were conducted. The tests were performed using a displacement control in each direction to obtain the strain measurements, which were then used to assess the structural safety of the lower articulation. Figure 11 illustrates the load-time behavior during the structural tests for each direction. As shown, the tests were conducted three times at 50%, 75%, and 100% of the load, with each load maintained for 10 s. The required loads in each direction were achieved, confirming the safety of the lower articulation. To evaluate the validity of the optimization analysis, the measured strains were converted into stress. Figure 12 presents the stress contours for different attachment locations. The stress results indicated varying locations of maximum stress for each direction. For a thorough evaluation of the optimization analysis, structural analysis results were compared with  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Direction of Structural Testing** & **Test Equipment** & **Load Conditions** & **Testing Speed** \\ \hline \multirow{2}{*}{Tension and Compression Right and Left} & MTS Tension and Compression Tester & 1000 kN & 2 mm/min \\  & MTS Hydraulic & & \\  & Actuator & 100 kN & 2 mm/min \\ \multirow{2}{*}{Vertical Vertical} & MTS Hydraulic & & \\  & Actuator & 100 kN & 5 mm/min \\ \hline \hline \end{tabular}
\end{table}
Table 4: Structural test conditions.  
Figure 10: Structural test of lower articulation: (**a**) tension and compression; (**b**) right and left; (c) vertical.  
Figure 9: Location of strain gages.
# Low-Latency Bit-Accurate Architecture for Configurable Precision Floating-Point Division
## 6 Conclusions  
This paper has presented a novel Predict-Correct iterative architecture for configurable FP division arithmetic. It can be dynamically configured for SP, DP, QP, or other user-defined precisions. Aiming at fast and efficient FP division processing, the architecture is also proposed with period and power trade-offs.  
The Predict-Correct algorithm is based on the very high-radix arithmetic. The entire logic path has been tuned to perform a low-latency computation. The proposed FP division unit has \(\approx\)63.6% latency and \(\approx\)30.23% total time overhead over [58]. Moreover, the proposed FP division unit outperforms the prior arts in terms of total energy (power \(\times\) latency \(\times\) period) and efficient average energy (power \(\times\) latency \(\times\) period/efficient length), which are two unified metrics relevant to effective energy. From the implementation results, it is much more favorable for the proposed FP division to perform in DP, QP, or other high-precision computations.  
Based on the current proposed division architecture, similar units for division can be formed using other algorithms, such as Newton-Raphson, Goldschmidt, and series expansion. Moreover, the proposed division architecture can also be employed in fast fixed-point division after simple adjustment.  
Conceptualization, M.W. and M.L.; methodology, J.X.; software, J.X.; validation, J.X.; writing--original draft preparation, W.F.; writing--review and editing, W.F.; funding acquisition, M.W. and M.L. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & & \multicolumn{3}{c}{**SP**} & \multicolumn{2}{c}{**DP**} \\ \cline{4-7}  & **Algorithm** & **Tech.** & **Clock Speed** (Hz)** & **Latency** & **Total Time** & **Latency** & **Total Time** \\  & & & **(Cycle)** & **(ns)** & **(Cycle)** & **(ns)** \\ \hline AMD K7 & multiplicative & – & 500 M & 16 & 32 & 20 & 40 \\ \hline AMD Jaguar & multiplicative & 28 nm & 2 G & 14 & 7 & 19 & 9.5 \\ \hline IBM zSeries & radix-4 & 130 nm & 1 G & 23 & 23 & 37 & 37 \\ \hline IBM z13 & radix-8/4 & 22 nm & 5 G & 18 & 3.6 & 28 & 5.6 \\ \hline HAL Sparc & multiplicative & 150 nm & 1 G & 16 & 16 & 19 & 19 \\ \hline Intel Penryn & radix-16 & 45 nm & 2.33 G & 12 & 5.14 & 20 & 8.57 \\ \hline This paper & Predict– & 90 nm & 300 M & 3 & 9.9 & 4 & 13.2 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Division Latency Comparison.  
**Funding:** This research was funded by the Natural Science Foundation of Guangdong Province, China (Grant No. 2020B1515120004), Shenzhen Science and Technology Plan-Basic Research (Grant No. JCY20180503182125190), Shenzhen Science and Technology Plan-Basic Research (Grant No. JCYJ20180507182241622) and Scientific research project in school-level (SZIIT2019 KJ026).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Related Research  
### Environmental Monitoring  
WSNs have become an important tool in environmental monitoring. The relatively low cost of the devices allows the installation of a dense population of nodes that can adequately represent the variability present in the environment. They can provide risk assessment information, like for example alerting farmers at the onset of frost damage and providing better microclimate awareness.  
[PERSON] and [PERSON] monitored the agroclimate in the Amazon, analyzing short range WSN transmissions. They found that more distant nodes suffered a performance loss, while nodes closer to the sink maintained their throughput levels.  
Another example of climate supervision is flood prediction by means of wireless sensors which can detect rainfall, water levels and weather conditions. The sensors supply information to a centralized database system [10]. [PERSON] and [PERSON] extended the implementation to a regional and on-farm sensor network operating at 900 MHz that provides remote, real-time monitoring and control of farming operations in two agricultural applications, a weather monitoring network and an on-farm frost monitoring network [11].  
[PERSON] and [PERSON] presented a moisture distribution map obtained through the integration of a WSN with a GIS (Geographic Information System). The wireless nodes with moisture sensors were located at predetermined locations; geographic coordinates of these points were obtained with GPS and then, all the information was evaluated using the GIS [12].  
[PERSON] _et al._ developed a wireless data transmission system using wireless ZigBee motes, developed to remotely monitor in real time sediment runoff at a low-water crossings. The gateway transmitted the sensor signals to an Internet server using the GPRS [13].  
[PERSON] and [PERSON] developed a lab prototype for wireless measurement of soil temperatures. The system was based on a commercial 13.56 MHz RFID tag. Measurements showed a high correlation (greater than 99%) with those obtained using a thermocouple [14].
## 3 Limitations of Existing Work  
Although existing methods have made progress in the multi-hop KGQA task, there are still problems in interpretability, semantic gap, knowledge hallucination, and dynamic knowledge adaptability (Table 1). The details are as follows:  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method Categories** & **Advantages** & **Limitations** & **Interpretability** \\ \hline Embedded & & Black-box & Low \\ Methods & Efficient retrieval & reasoning & \\ Symbolic Methods & Path transparency & Highly dependent & High \\ LLM-Driven & Strong semantic & Knowledge illusion & Middle \\ Methods & understanding & & \\ \hline \hline \end{tabular} (1)  
\begin{table} \end{table}
Table 1: Summary of existing work.  
are based. Although some LLM methods generate intermediate plans, the plans are disconnected from the retrieval process, potentially resulting in \"seemingly reasonable but actually wrong\" reasoning chains.
2. Semantic Gap: There is a semantic mismatch between natural language questions and structured knowledge representation. For example, the word \"leader\" in a question may correspond to CEO, founder, or director in the knowledge graph, and traditional methods struggle to achieve precise alignment. Although LLM can understand language diversity, the relationship descriptions it generates may not be consistent with the relationship labels in the knowledge graph (e.g., expressing \"direct\" as \"direct works\").
3. Knowledge Hallucination and Path Divergence: LLM-driven models may generate relationships that do not exist in the knowledge graph, leading to incorrect answers. In multi-hop scenarios, embedding methods may deviate from the correct path due to vector combination errors (e.g., wrongly jumping from \"director\" to \"screenwriter\").
4. Poor Dynamic Knowledge Adaptability: Symbolic methods rely on static knowledge graphs and have difficulty handling real-time updated knowledge (such as information about newly released movies). Most methods do not consider the noise in the knowledge graph (such as incorrect edges or missing entities), resulting in interruption of the reasoning chain.
# Modelling, Analysis and Performance of a Low Inertia AC-DC Microgrid
## 2 System Model
### Model of Induction Machine  
The relationship between the stator and rotor voltages and currents of the IM in the rotating reference frame is given in (6). It is possible to write the IM equations using any of the fluxes and currents as the state variable (noting that they are not independent variables). However, using currents as state variables is preferable for integrating IM state equations into the whole microgrid state-space model. Hence, the relationship between the stator and rotor voltage and current is expressed as follows in the common synchronous DQ reference frame [30]:  
\[V_{qs}=R_{s}\ I_{qs}+L_{s}i_{qs}s+L_{m}i_{qr}s+w_{r}L_{s}I_{ds}+w_{r}L_{m}I_{ dr}, \tag{6a}\] \[V_{ds}=R_{s}\ I_{ds}+L_{s}i_{ds}s+L_{m}i_{dr}s-w_{r}L_{s}I_{qs}-w_{r}L_{m}I_{ dr},\] (6b) \[V_{qr}=R_{r}\ I_{qr}+L_{r}i_{qr}s+L_{m}i_{qs}s+(w_{s}-w_{r})L_{r}I_{dr}+(w_{s}-w_ {r})L_{m}I_{ds},\] (6c) \[V_{dr}=R_{r}\ I_{dr}+L_{r}i_{dr}s+L_{m}i_{ds}s-(w_{s}-w_{r})L_{r}I_{qr}-(w_{s}- w_{r})L_{m}I_{qs}, \tag{6d}\]  
where \(L_{s}\) and \(L_{r}\) represent the stator and rotor inductance. While \(R_{s}\) and \(R_{r}\) represent the stator and rotor resistance; \(Lm\) and \(\omega r\), represent the mutual inductance and rotor speed, respectively. The electromagnetic torque is formulated as follows:  
\[T_{e}=\frac{3}{2}*\frac{\rho}{2}L_{m}\big{(}I_{qs}I_{dr}-I_{ds}I_{qr}\big{)}. \tag{7}\]  
The relationship between torque and mechanical speed may be determined using motor slip \(s\) and \(\omega_{r}\) as follows:  
\[(T_{e}-T_{m})*\frac{\rho}{2J}=\omega_{r}s. \tag{8}\]  
In (7) and (8), \(\rho\), \(J\) and \(Tm\) represent the number of poles, combined motor and load inertia and the load torque, respectively.  
Figure 4: Virtual Inertia Loop based on LPF.  
Figure 3: Proposed Virtual Inertia Loop based on HPF.