esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In order to determine the pollution status and availability of Hg from the abandoned Hg mine in Puerto Princesa City, this study investigated the soil and sediment samples collected from the surroundings of the abandoned PQMI mine area. Results of the Hg analyses of these samples followed similar contamination patterns from other reported Hg mine sites worldwide. Mercury concentration in mine waste calicines ranged from 52.7-924.2 mg kg\({}^{-1}\), of which some values were higher than those analyzed in 2003. Mercury levels measured in Honda Bay wharf were found to be similar in Hg concentration and characteristic with the mine waste calicines, confirming that the construction of wharf utilized the calicines from the PQMI mine site. Sediment samples obtained from Tagburos River and other tributaries, Honda Bay, and soils also exhibited Hg values that exceeded the global background, due to naturally high Hg concentrations in the mineralized area, and from the erosion and deposition of mine waste calicines into the surrounding areas. A greater range of Hg concentrations were measured at Honda Bay compared to the previous measurements conducted by several researchers in the same area some 20 years ago. These increased Hg concentrations in Honda Bay sediments may undergo methylation and enter the food chain, which was observed in Hg mining sites around the world [3; 7; 12]. This study concludes that one of the pathways of the reported Hg contamination in the area is caused by sediment transport from two point sources: (1) the calicines stocked at the shore of the pit lake and nearby area with scattered calcite, and (2) Honda Bay wharf. Sediment transport from the first  
Figure 4: Mean and range of THg concentrations in surface marine sediments of Honda Bay, from 1982 to present. Data from Honda Bay were compared with data from the dredged Minamata Bay (2006) and global background. * [PERSON] et al. [20], ** [PERSON] et al. [24], *** [PERSON] et al. [21], *** This study.  
point source was facilitated by Tagburos River and its tributaries, while the second point source was due to coastal erosion. Further studies are needed to evaluate the methylmercury levels in biota and particle-bound Hg in the air to evaluate health issues. Mining rehabilitation activities, such as revegetation to reduce soil erosion and soil particle suspension, need to be implemented based on the results of this study.  
Conception and design of study and supervision, J.S. and C.R.G.; acquisition, analysis, interpretation of data, drafting the manuscript, and approval of the version of the manuscript to be published, J.S., C.R.G., A.T., and R.R. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Philippines' Department of Science and Technology's Grants-in-Aid Program (DOST-GIA).  
The authors acknowledge the Department of Science and Technology; the Philippine Council for Industry, Energy, and Emerging Technology Research and Development (DOST-PCIEFED); and the Provincial Science and Technology Center of Palawan.  
The authors declare no conflict of interest.
# Extending the Performance of Hybrid NoCs beyond the Limitations of Network Heterogeneity
###### Abstract  
To meet the performance and scalability demands of the fast-paced technological growth towards exascale and big data processing with the performance bottleneck of conventional metal-based interconnects (wireline), alternative interconnect fabrics, such as inhomogeneous three-dimensional integrated network-on-chip (3D NoC) and hybrid wired-wireless network-on-chip (WiNoC), have emanated as a cost-effective solution for emerging system-on-chip (SoC) design. However, these interconnects trade off optimized performance for cost by restricting the number of area and power hungry 3D routers and wireless nodes. Moreover, the non-uniform distributed traffic in a chip multiprocessor (CMP) demands an on-chip communication infrastructure that can avoid congestion under high traffic conditions while possessing minimal pipeline delay at low-load conditions. To this end, in this paper, we propose a low-latency adaptive router with a low-complexity single-cycle bypassing mechanism to alleviate the performance degradation due to the slow 2D routers in such emerging hybrid NoCs. The proposed router transmits a flit using dimension-ordered routing (DoR) in the bypass datapath at low-loads. When the output port required for intra-dimension bypassing is not available, the packet is routed adaptively to avoid congestion. The router also has a simplified virtual channel allocation (VA) scheme that yields a non-speculative low-latency pipeline. By combining the low-complexity bypassing technique with adaptive routing, the proposed router is able to balance the traffic in hybrid NoCs to achieve low-latency communication under various traffic loads. Simulation shows that the proposed router can reduce applications' execution time by an average of 16.9% compared to low-latency routers, such as SWIFT. By reducing the latency between 2D routers (or wired nodes) and 3D routers (or wireless nodes), the proposed router can improve the performance efficiency in terms of average packet delay by an average of 45% (or 50%) in 3D NoCs (or WiNoCs).  
Keywords:router architecture; 3D NoC; hybrid wired-wireless network-on-chip; surface wave; mm-wave; WiNoC; waveguide +
Footnote †: journal: Low Power Electronics and Applications
## 4 Experimental Results and Analysis
### Impacts of the Orbital Parameters on LEO-LEO Occultation Events
#### 4.1.2 Overall Simulation Results  
The variation in the 3-month LEO-LEO occultation event number with the Rx and Tx orbital elements of inclination, RAAN, and height is shown in Figure 2. One can see from Figure 2 that the 3-month occultation number changes strongly with the variation in the inclination and RAAN, but changes slightly with the variation in height for the Rxi90-Txi90 case. The impact of each of these orbital elements will be analyzed separately.
# Automatic Speech Recognition for Uyghur, Kazakh, and Kyrgyz: An Overview
## 3 Linguistic Analysis of Uyghur, Kazakh, and Kyrgyz
### Individualities of Each Language
#### 3.2.2 Phoneme Set  
All three languages were developed from the ancient Altaic, and their phoneme sets are similar. Kyrgyz best preserves the ancient Altaic phonemes, while Uyghur and Kazakh have developed new phonemes. Table 2 summarizes the vowels used in the three languages, and the consonants are listed in the Appendix section.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline
**Vowels** & **e** & **a** & **o** & **o** & **u** & **y** & **a** & **t** & **i** & **i** & **o** \\ \hline Front (\(\leftarrow\))/Central (\(\bullet\))/Back (\(\rightarrow\)) & \(\leftarrow\) & \(\rightarrow\) & \(\leftarrow\) & \(\rightarrow\) & \(\rightarrow\) & \(\leftarrow\) & \(\leftarrow\) & \(\leftarrow\) & \(\bullet\) & \(\leftarrow\) & \(\bullet\) \\ \hline Top (!)/Bottom (\(\downarrow\)) & \(\downarrow\) & \(\downarrow\) & \(\downarrow\) & \(\downarrow\) & \(\uparrow\) & \(\uparrow\) & \(\downarrow\) & \(\uparrow\) & \(\uparrow\) & \(\uparrow\) & \(\uparrow\) \\ \hline Rounded (o)/Unrounded (\(\sim\)o) & \(\sim\)o & \(\sim\)o & o & o & o & \(\sim\)o & \(\sim\)o & \(\sim\)o & \(\sim\)o & \(\sim\)o \\ \hline Uyghur & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & & ✓ & & ✓ & \\ \hline Kazakh & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & & & ✓ & & ✓ \\ \hline Kyrgyz & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & & & & ✓ \\ \hline \hline \end{tabular}
\end{table}
Table 2: Vowel phoneme sets of Uyghur, Kazakh, and Kyrgyz.  
Specifically, in Kyrgyz, there are 8 short vowels: \(a\), \(e\), \(g\), \(o\), \(\omega\), \(u\), \(i\), and \(y\), and 22 consonants (see Appendix C). The eight short vowels are rooted in the ancient Altaic, and based on these basic vowels, Kyrgyz extended six long vowels: \(aa\), \(oo\), \(uu\), \(ee\), \(oo\), and \(yy\). These long vowels may be formed by the consonant assimilation between vowels [110].  
Kazakh has nine vowels and 24 consonants (see Appendix B). Apart from the same vowels as Kyrgyz, Kazakh has an extra front vowel \(\alpha\), and the front vowel \(y\) is replaced by a central vowel \(i\). Some researchers believe that \(\alpha\) in Kazakh did not appear in the ancient Altaic, instead gradually emerging in the process of language fusion [111]. Besides the vowels, Kazakh also has 24 consonants (see Appendix B).  
Uyghur is based on eight vowels: \(a\), \(e\), \(e\), \(i\), \(o\), \(\theta\), \(u\), and \(y\), and 24 consonants [110] (see Appendix A). The Uyghur vowels are very similar to the Kyrgyz vowels, except that the central vowel \(\alpha\) was substituted with the front vowel \(\varepsilon\).
# Research Developments of Aerostatic Thrust Bearings: A Review
## 2 Theoretical Models and Experiment Methods
### Theoretical Model
#### 2.1.2 Velocity Slip Effect  
For gas in the micro clearance of bearings, the molecular mean free path of the gas cannot be neglected compared with the bearing clearance. Velocity slip is more prone to occur at the solid-gas interface. This phenomenon was verified experimentally by [PERSON] [18]. In addition, [PERSON] carried out an experimental study on gas bearings with clearances below 0.25 microns and validated the slop-flow theory [19]. Moreover, the velocity slip influence on bearing performance was studied in theoretical calculation. [PERSON] applied the surface adjustment coefficient to the traditional gas Reynolds Equation [20]. [PERSON] introduced the Navier velocity slip model to improve the theoretical model of the aerostatic guideways. It was found that the first-order velocity slip model was more suitable to predict the performance of aerostatic guideways [21,22]. All the above results show that it is necessary to consider the velocity slip effect in the design of ATBs.
# Short Text Clustering Algorithms, Application and Challenges: A Survey
## 3 Components of Short Text Clustering
### Document Pre-Processing in Short Text Clustering
#### 3.1.3 Stemming  
This is the third step in pre-processing. We utilize stemmed words to represent the texts in this step. Stemming is a traditional shallow natural language processing (NLP) technique. Word stemming removes all prefixes and suffixes to obtain stem words [60]. Indexing and keyword filtering are crucial steps of stemming because they improve clustering faster and more accurately by reducing the vocabulary quantity and dependence on certain vocabulary forms [61]. Figure 6 illustrates how the stemming transforms the words 'consultant', 'consultants', 'consulting' and 'consultative' into a single stem, 'consult', which is also a word in the dictionary. However, this is not always the case; a stem may not always be an accurate word.
# Smart Warehouse Management System: Architecture, Real-Time Implementation and Prototype Design
## 4 Methodology and Proposed Architecture  
The addition of an automated inventory management system is the prime need of huge warehouses that deal with much stock and many goods on a daily basis. In order to design a methodology, the domain was studied in detail, and the needs were identified. The domain analysis is presented in Section 2. A detailed literature review and background study were used to pinpoint the problems. The major problems identified were the lack of efficient communication between departments, keeping track of the sales orders, transporting the cartons, and the managing and tracking of prepared goods inside the inventory. The stakeholders that were involved in this domain were also identified so that their needs could be prioritized and managed accordingly.  
To cater to these problems, we propose an architecture based on architecture viewpoints taken from [42]. The viewpoints are a template to construct models for information systems based on the needs of the system and its stakeholders' concerns. The views were used to describe the functional elements of a system and their interaction with each other and with the resources outside the systems. They also account for the system requirements regarding the software and hardware support, physical deployment, and communication between different components. They make use of a ubiquitous language in order to create models that are equally understandable to software developers, as well as the business personnel. This helps in modeling the architecture according to the interests of the stakeholders to attain the maximum business profit.  
The warehouse management system was modeled as an information system connected to several internal and external elements. In this paper, we used the context diagram, functional, and operational viewpoints to propose an architecture. These were used to identify the problems in the modeling of the warehouse and then to solve the problems by proposing the models. Furthermore, we also designed and developed an IoT-based hardware prototype to implement the architecture in a textile factory's warehouse.
## 5 Surface Subsidence Prediction Method for UCG
### Basic Roof Subsidence Space Calculate  
When the UCG process is complete, a gasification area will be formed, which is composed of the combustion cavity and isolated coal pillar. Similar to traditional strip mining, the roof stress will be released after the coal resources in gasifiers are consumed, resulting in roof subsidence. The stress of the overburdened strata concentrates on the isolated coal pillar, roof, and floor to form additional load, which causes the compression of the coal pillar, roof, and floor, where the stress concentrates and finally forms the subsidence space of the roof.  
Therefore, the subsidence space of the roof in UCG consists of four main components. (a) The bending and subsidence of the roof in the combustion cavity. (b) The roof subsidence is caused by the compression of the coal pillar. (c) The compression of the floor causes the roof subsidence. (d) The roof subsidence is caused by the compression of the floor. The subsidence of these four components is calculated separately and added together to obtain the final sink space in the roof slab.
## 5 QDAR Algorithm
To calculate the direct reward, sink node keeps the communication record so as to estimate the state transition probabilities: \(P_{x_{ij}}^{a_{j}}\) and \(P_{x_{ii}}^{a_{j}}\) of each node. \(P_{x_{ij}}^{a_{j}}\) and \(P_{x_{ii}}^{a_{j}}\) are the probabilities of successful and failed packet forwarding respectively:  
\[P_{x_{ij}}^{a_{j}}=\frac{m_{t}}{M_{t}}, \tag{11}\]  
\[P_{x_{ii}}^{a_{j}}=1-P_{x_{ij}}^{a_{j}}. \tag{12}\]  
Suppose there have been \(M_{t}\) instances of communication up to time t and \(m_{t}\) is the frequency of successful packet forwarding, we can define the direct reward function as:  
\[r_{i}=R_{x_{ij}}^{a_{j}}P_{x_{ij}}^{a_{j}}+R_{x_{ii}}^{a_{j}}P_{x_{ii}}^{a_{j}} =R_{x_{ij}}^{a_{j}}\frac{m_{t}}{M_{t}}+R_{x_{ii}}^{a_{j}}\left(1-\frac{m_{t}}{ M_{t}}\right) \tag{13}\]  
The highest \(Q\) value among all the actions is described as:  
\[Q^{*}(x)=\max_{a}Q(x,a) \tag{14}\]  
If the next hop is the sink node, the \(Q\) of this node is much higher than the others. According to Equations (5) and (14), we can define the action-utility function for each neighbor node of node \(i\) as:  
\[Q\big{(}x_{i},a_{j}\big{)}=r+\gamma\left(\frac{m_{t}}{M_{t}}Q^{*}\big{(}x_{j} \big{)}+\left(1-\frac{m_{t}}{M_{t}}\right)Q^{*}(x_{i})\right) \tag{15}\]  
Then, we choose the neighbor node with the highest \(Q\) as the next hop and update the previous \(Q\) storied with newly chosen \(Q^{*}\). Initially, if the next hop is not the destination node, \(Q\) values in the matrix are set to 0. Otherwise, \(Q\) values are set to 1. Algorithm 1 for the routing mechanism is conducted as below. The QDAR mechanism can adapt to the dynamic underwater environment quickly. An energy-related cost function and a delay-related cost function are defined in the data_ready phase. After that, the sink node has the collected information and performs QDAR algorithm. Firstly, it defines two reward functions with the cost functions for both successful and failed transmission. In the reward functions, there is an alterable parameter. Based on this parameter, an adaptive detouring path strategy is designed. Thus, QDAR algorithm can work adaptively with different residual energy. Then, with the reward functions and the corresponding probability functions, the action-utility function (Q-value) is determined. Finally, the sink node chooses the global optimal next hop and then determines the routing path. In the next section, the simulation results prove that the adaptive solution in QDAR ensures a longer network lifetime and a relatively shorter delay.
## 2 Materials and Methods
### Characterization of the Cutting Result  
The cut samples were analyzed regarding burr, surface roughness, HAZ, and recast layer. The single methods are described in the following and illustrated in Figure 2.  
The burr inspection was accomplished as illustrated in Figure 2a, by digitalizing the outline of the cut edge using a graphics scanner. The used procedure consisted on dividing the cut length of the sample into five sections and detecting the maximum burr height in each one. Finally, the measured height values were averaged for evaluation.  
Furthermore, average surface roughness R\({}_{2}\) measurements were performed according to DIN EN ISO 4288:1998-04 at three different positions: 1 mm below the top surface, in the middle of the plate thickness, and 1 mm above the bottom surface. Details to the evaluation method of surface roughness  
Figure 2: Characterization methods: (**a**) Cross-sectional view along the cutting direction verifies the cut edge quality: maximum burr height was detected in five sections, surface roughness R\({}_{2}\) was measured along three lines; (**b**) Cross-sectional view across the cutting direction investigates the laser beam energy deposition: heat affected zone (HAZ) and recast layer were studied as area measurements and the height of the recast layer was recorded.  
depict Figure 2a. The stylus tip radius of 2 um in the measuring plane and the deflection accuracy of 12 nm in the orthogonal plane limited the measuring resolution of the tactile method. The mean value of the three measurements evaluated the appearance of the cut edge.  
Finally, metallographic cross-sectional analyses determined the HAZ and recast layer. The analysis required a separation of the samples crosswise to the cutting direction and a subsequently polishing and etching. Microscopic images recorded the cross-sections as schematically shown in Figure 2b. Area measurements characterized the HAZ and recast layer with an accuracy of 1.5 mm\({}^{2}\). In addition, the height of the recast layer was measured (see indication in Figure 2b) with 50 um accuracy. Since the recast layer width changes as a function of plate thickness, the quotient of area and height calculated an average recast layer width.
# Lead Tolerance and Enrichment Characteristics of Three Hydroponically Grown Ormamental Plants
###### Abstract  
Phytoremediation of lead (Pb) in contaminated soils using hyper-enriched plants is an important task. It is a green and sustainable measure. Studies have revealed that three ornamental plants, _Tagetes putula_ (_T. patula_), _Solanum nigrum_ (_S. nigrum_), and _Mirublis jalapa_ (_M. jalapa_), have the ability to enrich for Pb; however, studies on difference between them and root morphology and the relationship between tolerance and capacity are lacking. The ability of three lead-enriching plants, _T. patula_, _S. nigrum_, and _M. jalapa_, to cope with Pb stress was assessed in hydroponic experiments using five Pb stress concentrations (0-1000 mg/L). Under different Pb stress conditions, the growth of the shoots and roots of three tested ornamental plants was inhibited to varying degrees. In the three tested ornamental plants, Pb mainly accumulated in the roots, and the highest levels of Pb observed in the shoots of _T. patula_, _S. nigrum_, and _M. jalapa_ were 1074.1 mg/kg, 958.7 mg/kg, and 975.3 mg/kg, respectively. All plants reached a critical level of Pb hyperaccumulation. Redundancy analysis showed that changes in the root architecture of the three tested ornamental plants were significantly and positively correlated with tolerance as well as the enrichment and transfer ability of the heavy metal Pb. Therefore, these three ornamental plants have the potential to remediate Pb-contaminated water and soil and can increase the tolerance and enrichment characteristics of Pb by regulating the root biomass and root length of the three test ornamental plants via various agronomic measures. In addition, more research should be conducted to assess their effectiveness as phytoextractants under field conditions.  
lead pollution; ornamental plant; root architecture; tolerance; accumulation Article
## 5 Nanocarriers as a Strategy to Fight Biofilms
### Biofilm-Penetrating Efficiency  
EPS matrix serves as a barrier that restricts antibiotics penetration [1]. EPS matrix contains extremely small pores, preventing larger drug molecules from passing through. Also, antibiotics can be adsorbed onto the matrix itself [80]. Thus, enhancing antimicrobials' ability to penetrate biofilms using nanocarriers represents an effective strategy against biofilm infections.  
Nanocarriers with smaller particle sizes can more effectively penetrate biofilms, a characteristic closely tied to the structure of the biofilm. Studies using scanning electron microscopy and confocal microscopy have revealed water channels on the biofilm surface and observed its internal structure facilitating the transfer of nutrients and metabolites [81]. These biofilm channels, crucial for efficient transport processes, typically have a minimum width of approximately 100 nm [82]. Biofilms are structured with water channels, yet many antimicrobials face challenges in penetrating EPS due to their size or adsorption onto the EPS matrix. Notwithstanding, the existence of these channels suggests that nanoparticles smaller than these channels can effectively penetrate biofilms.
# Discrete Semantics-Guided Asymmetric Hashing for Large-Scale Multimedia Retrieval
## 2 Related Works
### Deep Hashing  
Recently, with the great success of deep learning in the field of representation learning, many deep hashing methods [13; 15; 40; 43] have been proposed. For example, Deep Semantic-Alignment Hashing (DSAH) [44] is an unsupervised hashing method, which explores the similarity information of different modalities and proposes a semantic-alignment loss to learn the hash codes. Unsupervised Deep Cross-modal Hashing with Virtual Label Regression (UDCH-VLR) [45] proposes a novel unified learning framework to jointlyperform deep hash function training, virtual label learning, and regression. Deep Saliency Hashing (DSaH) [46] is a two-step end-to-end model, which mines salient regions and learns semantic-preserving hash codes simultaneously. Supervised Hierarchical Deep Cross-modal Hashing (SHDCH) [47] learns the hash codes by explicitly delving into the hierarchical labels. Deep Semantic cross-modal hashing with Correlation Alignment (DSCA) [48] designs two deep neural networks for image and text modality separately, and learns two hash functions. First, due to the non-smooth property of the discrete optimization causing the problem of unavailable gradient in back-propagation, these methods use the relaxation-based optimization strategies to handle the problem. Even though high retrieval performance is considered to be achieved, these methods still have a large quantization error and can only produce sub-optimal hash codes. Second, they all need large computing resources (e.g., GPUs) and a massive training dataset, which makes them fairly computationally expensive.
## 5 Implementation and Evaluation
### Experimental Results
The impact on accuracy is influenced by the complexity of the data patterns and the architecture of the models, as illustrated in Figure 16.