esa-sceva/satcom-chunk-collection huggingface dataset:
# Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status  
[PERSON]  
1 Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain; [EMAIL_ADDRESS]
2 Language and Computation Centre, Universitat de Barcelona, 08007 Barcelona, Spain
3 Fundacio TIC Salt Social, Departament de Salut, Generalitat de Catalunya, 08005 Barcelona, Spain; ereziach@ic  
Most of these studies are focused on the analysis of small segments of controlled speech, or even only on sustained sounds of vowels. However, natural speech, either read or conversational, provides information not contained in short speech segments, such as prosodic elements [15]. Further studies have dealt with the automatic detection of breathing signal during conversational speech from low-level spectral features [16], the prediction of exacerbations in high-risk patients using the COPD assessment test (CAT) [17], the identification of clinical factors that modulate the risk of progression to COPD among asthma patients using electronic medical records [18], or the prediction of non-COPD/COPD patients from natural speech by means of pauses and voice quality parameters [19]. All these works represent a step forward in the automatic assessment of COPD measurements, which can greatly benefit the task of clinicians. Nevertheless, a more fine-grained detection is needed, to see to what extent speech features can predict the exacerbations of COPD associated with impairments reflected in parameters such as FEV\({}_{1}\), mMRC (modified Medical Research Council) dyspnea scale [20,21], and CAT (COPD assessment test) questionnaire [22], and to what extent different recording conditions--such as doing a physical effort or medication intake--can affect the widely reported voice variations and thus the accuracy in automatic detection of COPD measurements.  
The main contributions of this paper are:  
1. The analysis of prosodic features in long read speech, apart from low-level acoustic features. Based on the hypothesis that prosodic features are also vulnerable to changes in COPD patients, long speech analysis is needed to extract prosodic parameters apart from mere acoustic features.  
2. The analysis of how these speech features are affected by physical effort and after medication intake. Based on the hypothesis that physical effort and inhaled medication can affect oral airflow and air pressure during speech production, the speech parameters will then be modified under these conditions.  
3. The analysis of to what extent COPD/non-COPD subjects can be predicted from speech, and how variations of speech that feature in different recording conditions affect the automatic prediction of COPD measurements. If COPD is manifested through speech, one should be able to predict--to a certain extent--whether an individual suffers COPD or not. Moreover, if knowledge on COPD measurements can be inferred from speech, and if speech features change due to different recording conditions, then the way in which an automatic detection system is defined from speech recordings is crucial.
# State-of-the-Art in Satellite Communication Networks
## 3 Future  
Satellite systems are and will be an important technology for guaranteeing adequate communications to users, especially in all those areas where infrastructures are difficult to be installed. Nowadays, in the satellite panorama, a new form of satellite object is emerging: the _cubesat_. They are a type of miniaturized satellite that have a cubic shape, the electronics of which are made using COTS components. The simplification of the satellite structure makes it possible to design and build functioning satellites at a low cost. Standardizing the interface between the launcher and the payload reduces the work required to couple the satellite to the launcher. Thus, the exploration of the satellite world continues to be a fascinating universe to explore.
## 4 Discussion
### Unexpected Outcomes  
An unexpected result highlighted by this survey is that no studies conducted to date and analyzed in this review demonstrated the effectiveness of SPs and SWs for monitoring ambient temperature, humidity, and air pressure. Most previous studies also largely overlooked other important environmental risk factors, such as precipitation, daily cloud cover, TVOC, PM\({}_{2.5}\), and CO, which appear in \(\sim\)7% of the studies identified and analyzed in this review. The present paper offers a concise summary that, as we believe, might encourage readers to explore the original studies for more detailed information.
# Energy-Optimized Content Refreshing of Age-of-Information-Aware Edge Caches in IoT Systems
## 4 Model-Driven Cache-Management Optimization
### Energy-Optimized Cache Refresh
#### 4.1.2 Devices with Sampling Energy Consumption Equal to Zero: \(\overline{\beta}=1\)  
When \(\overline{\beta}=1\), i.e., \(c_{\overline{\beta}}=f_{T}\), if we remove the integer constraint on \(w\), it is possible to compute the optimum values of \(w\) and \(s\) in closed form (see Appendix B), obtaining \(s^{*}=s_{min}\) and \(w^{*}=f(s_{min})=\frac{A\circ I_{\alpha}}{A\circ s_{min}}+\frac{e^{-\lambda s _{min}}(1-\alpha)}{\left(1-e^{-\lambda s_{min}}\right)\alpha}\) if \(s\leq A\circ I_{\alpha}\), or \(w^{*}=f(s_{min})=\frac{A\circ I_{\alpha}}{\frac{A\circ s_{min}}{1-e^{-\lambda s _{min}}}}\) if \(s>A\circ I_{\alpha}\). The same result can be also seen graphically in Figure 4.  
In this case, \(c_{\overline{\beta}}\) depends both on the requests rate \(\lambda\) and on the AoI requirement, i.e., \(A\circ I_{\alpha}\) and \(\alpha\).  
When the value of \(\lambda\) decreases, the optimum value of \(c_{\overline{\beta}}\) decreases (see Figure 5), and when \(\lambda\to 0\) it is:  
\[\underset{\lambda\to 0}{\lim}f_{T}(\overline{s},\overline{w})=0\]  
Indeed, in this case, each request triggers a refresh with a high probability, but since the request rate is extremely low, only a few messages are exchanged in the network.  
Instead, when \(\lambda\to\infty\), it is (see Figure 5):  
\[\underset{\lambda\to+\infty}{\lim}f_{T}(\overline{s},\overline{w})=\frac{ \alpha}{A\circ I_{\alpha}}\]  
In this case, the cache is refreshed almost periodically with period \(W\).  
Clearly, also in this case, when the value of \(A\circ I_{\alpha}\) increases, the optimum value of \(c_{\overline{\beta}}\) decreases, and when \(A\circ I_{\alpha}\to\infty\), the objective function tends to 0:  
\[\underset{A\circ I_{\alpha}\to+\infty}{\lim}f_{T}(\overline{s},\overline{w})=0\]And when the value of \(\alpha\) decreases also the optimum value of \(c_{\overline{\beta}}\) decreases, and when \(\alpha\to 0\), the objective function tends to 0:  
\[\lim_{\alpha\to 0}f_{T}(\overline{s},\overline{w})=0\]  
These conclusions remain essentially the same when considering the integer constraint on \(w\): in this case, we cannot compute the optimum values of \(w\) and \(s\) in closed form, but we can only find a numerical solution using some optimization techniques and, as we can observe from Figure 6, the optimal value of \(s\) can be slightly greater than \(s_{min}\) to satisfy the integer constraint on \(w\).
# A Review of SATis5: Perspectives on Commercial and Defense 5G SATCOM Integration
###### Abstract  
This review provides a comprehensive review of past and existing works on 5G systems with a laser focus on 5G Satellite Integration (SATis5) for commercial and defense applications. The holistic survey approach is used to gain an in-depth understanding of 5G-Terrestrial Network (5G-TN), 5G-Non-Terrestrial Network (5G-NTN), SATis5 testbeds, and projects along with related SATis5 architectures. Based on the survey results, the review provides (i) outlook perspectives on potential SATis5 architectures for current and future integrated defense and commercial satellite communication (SATCOM) with 5G systems, and (ii) a thorough understanding of problems associated with anticipated outlooks and corresponding studies addressing these problems. The commercial SATis5 architectures discussed here can be extended to civilian SATCOM applications.  
5G Satellite Integration (SATis5); Commercial SATCOM; Defense SATCOM; Civilian SATCOM; eMBB; mMTC; uRLLC; internet-of-thing; non-terrestrial network; next-generation core network; relay node; single-hop; multiple-hop; communication-on-the-move; cloud; data network +
Footnote †: journal: _encyclopedia_  
emphasizes potential SATis5 architecture outlooks for commercial and defense applications. In addition to the outlooks, the review discusses potential problems associated with the architecture outlook and recommends a set of studies and investigations addressing these problems. Using our holistic survey approach, the review is structured as follows:  
* Section 2 presents overviews of 5G-TN and 5G-NTN with emphasis on a high-level understanding of 5G technologies and key 5G system components--These overviews provide some insights into 5G functions related to SATis5 architectures described in the subsequent sections;
* Section 3 captures existing SATis5 survey results with the goal to understand (i) possible commercial and defense SATis5 architectures, (ii) the proposed commercial SATis5 architecture roadmaps, and (iii) associated technical challenges;
* Section 4 presents an overview of recent and existing commercial SATis5 Testbeds and projects available in the public domain;
* Section 5 describes an overview of recent and existing defense SATis5 Testbeds and projects available in the public domain;
* Section 6 discusses and provides our SATis5 architecture outlooks and associated problems and challenges for commercial and defense applications; and
* Section 7 concludes the review with a summary and discussion of our thoughts on the perspectives of SATis5 architectures presented in Section 6. Additionally, this section recommends a list of studies and investigations addressing the problems and challenges identified in Section 6.
## 4 Conclusions  
In this project, the _VMPSTS_ gene previously isolated from the orchid hybrid, _Vanda_ Mimi [PERSON] has been functionally identified to produce germacrene D, copaene and \(\delta\)-cadinene among others. This was achieved by cloning and expression of the enzyme in _L. lactis_ followed by _in vitro_ enzymatic assays to identify the sesquiterpene products produced via GC-MS analysis. Based on the major sesquiterpene produced, VMPSTS is identified to be a germacrene D synthase. To our knowledge, this is the first terpene synthase gene from the _Orchidaceae_ family to be functionally identified through recombinant technology and only the second plant isoprenoid gene ever to be cloned and expressed in _L. lactis_.
# Water-Use Characteristics and Physiological Response of Moso Bamboo to Flash Droughs
## 4 Discussion
### The Response of SWC and LAI of Moso Bamboo Forests to Flash Drought
[PERSON] et al. [49] reported an observed decrease in maximum sap flow for _Pinus contorta_, _Abies lasiocarpa_, _Populus tremoloides_, and _Pinus flexilis_ when soil moisture decreased from 0.35 to 0.24 m\({}^{3}\cdot\)m\({}^{-3}\) at 0-45 cm. [PERSON] et al. [48] found that the mean sap flow of trees decreased from 0.567 kg cm\({}^{-1}\) to 0.258 kg cm\({}^{-1}\) in response to drought conditions. Canopy transpiration also decreased at the same time [50]. For example, Scot's pine (_Pinus sylvestris_) and Norway spruce (_Picea abies_.) transpiration was reduced by 40% and 67% during the dry summer [51]. The findings from the present study are supported by the results from previous studies. The WUE and precipitation of Moso bamboo forest showed an opposite trend at the seasonal scale in this study. The relationship between WUE and precipitation observed in our study was consistent with previous results based on the site observed [52]. Water-use efficiency significantly decreased to 0.92 gC\(\cdot\)m\({}^{-2}\cdot\)mm\({}^{-1}\cdot\)mon\({}^{-1}\) and 0.99 gC\(\cdot\)m\({}^{-2}\cdot\)mm\({}^{-1}\cdot\)mon\({}^{-1}\) with the reduction of precipitation in July and August 2013. [PERSON] et al. [53] found that WUE of plants was negatively correlated with SWC and decreased significantly with the reduction of SWC during the flash drought period. [PERSON] et al. [54] also found that the WUE of plants showed a decreased tendency under severe drought conditions using observation and remote sensing data. The results from this study are consistent with the findings from previous studies. The reason may be that stomata is much more sensitive to drought when Moso bamboo is under the condition of mild and moderate water stress, which will be further discussed below. Physiological dehydration occurred in Moso bamboo to reduce ET by defoliation, which results in a significant decrease in WUE. Water vapor exchange through transpiration and CO\({}_{2}\) absorption through photosynthesis are carried out in leaf stomata. Therefore, the transpiration rate directly affects plant photosynthesis and then affects the net primary productivity of an ecosystem [37]. [PERSON] et al. [6] reported that an extreme drought that occurred in July and August 2013 significantly reduced the net ecosystem productivity of a Moso bamboo forest by 60-78%. [PERSON] et al. [22] reported that a flash drought resulted in both net and gross primary productivity of a Moso bamboo forest decreasing by 12% and 48%, respectively. [PERSON] et al. [21] observed that a mosaic of oak (_Quercus_ spp.) forests stands accumulated 40% less carbon in a year under flash drought conditions. Leaf area index affects the WUE (WUE = GPP/ET) of an ecosystem by controlling GPP and ET to response to flash-drought events. The consistent response of ET, WUE, GPP, and net ecosystem exchange to extreme drought also indicates the coupling of water and carbon in ecosystems.
# Application of a DC Distribution System in Korea: A Case Study of the LVDC Project
## 2 Design of DC Distribution System
### Grounding and Protection
#### 2.1.2 Fault Detection Device  
In the case of non-grounded systems, it is difficult to detect grounding faults by a conventional method. Therefore, real-time analysis of the insulation resistance in the energized-line is necessary. Thus, an IMD is installed.  
IMD is commonly used to measure insulation resistance in closed circuit rail or medical devices [11]. Currently, the development of IMD technology for the distribution line is in the early stage, and there is no application for outdoor use. Furthermore, it is necessary to study operation standards and procedures. Therefore, this paper confirms the applicability of IMD and presents the operational procedures. It is necessary to set appropriate alarm value to detect ground faults while operating the distribution system and coping with system stoppage or re-input according to the situation. However, there is currently no standard for IMD alarm set-points for DC distribution lines. However, in \"Selection and erection of electrical equipment--isolation, switching and control\" of IEC 60364-5-53 Annex H, the pre-warning is specified as 100 \(\Omega\) per 1 V and the warning as 50 \(\Omega\) per 1 V. The setting value of IMD is recommended to be set to 1.5 times this value. It is essential to select an appropriate alarm set-point because the IMD for the DC distribution line monitors the insulation of the DC distribution line and the associated power converter. Therefore, a flow chart of the operation procedure was proposed for determining the IMD alarm setting value required in the field application (refer to Figure 4). In the case of alarm 1 of IMD, be cautious of the possibility of decreased insulation resistance in the line, while the alarm 2 should immediately trigger stopping of the operation, followed by an inspection. This is to prevent possible grounding caused by animals or humans, which can lead to secondary failure, which may lead to deadly accidents. In this study, the alarm value is set by measuring the real-time insulation resistance value according to the proposed operating procedure for the DC distribution to be applied to the actual grid system.  
Figure 3: Simulation of ground fault in DC distribution line of IT ground: (**a**) underground line; (**b**) overhead line.
## 3 EDAS Prototype Specifications
### The EDAS Platform
#### 3.4.1 Monitoring Agent  
The _Monitoring Agent_ reads, filters and normalizes events communicated by various sources. For each event source, there is a unique component called a plugin that performs the said operations. A plugin reads events from an event queue, a log file or DB, filters them using a white-listing technique and transform them into a standard format for analysis. Potential security events matching a regular expression (RegEx) or an SQL query are forwarded for normalization, considered as critical security events, while the unmatched ones are discarded. During normalization, essential event attributes are extracted as variables that are later used in the risk analysis process. Each event source and event type  
Figure 7: The EDAS platform. (**a**) EDAS platform component diagram; (**b**) The EDAS platform layered architecture.  
are assigned a unique plugin ID and plugin security ID (SID), respectively. These identifiers uniquely identify specific sources and event types in the IoT environment and are utilized in later processes. An example of an event before and after normalization with essential attributes for analysis and adaptation is shown in Figure 8.  
Events can be distinguished based on the information they contain. Based on the type of events and their content, the monitoring agent's (the plugin) filtration criteria decide which of them should be considered for risk analysis. For instance, medical events concerning vital body signs are not to be classified as security events and may be filtered out unless they are involved in a related biometric authentication system. Furthermore, among other essential attributes, events are generated with a key property generally called level, for instance, see Microsoft event properties [15]. The level indicates an event's importance or its severity level. Although the level definition is thing specific, it can provide essential information to distinguish how critical a particular event is and how it should be assessed in the risk analysis process. In the prototype, OSSIM transformed this importance level into event priority, discussed in the next section.
## 4 Results
### Variation of the Waveguide Width  
To find the optimal waveguide width \(w\), we studied the changes in a range of \(w=125\,\mathrm{nm}\) to \(w=250\,\mathrm{nm}\). An increase of \(w\) leads to higher values for \(n_{\mathrm{eff}}\), decreasing with the slot width \(s\). However, regarding the difference in the effective index \(\Delta n_{\mathrm{eff}}\) between the two concentrations, as shown in Figure 8a, we find a more complex relationship. While \(\Delta n_{\mathrm{eff}}\) shows a maximum for \(w=175\,\mathrm{nm}\) at \(s=60\,\mathrm{nm}\), it barely changes for \(w=200\,\mathrm{nm}\) over the entire range of \(s\). A greater linear decrease becomes evident for \(w=125\,\mathrm{nm}\) and \(w=150\,\mathrm{nm}\). In case of \(w=250\,\mathrm{nm}\) even an increase with \(s\) up to \(\Delta n_{\mathrm{eff}}=0.0172\) can be observed. The latter is due to the very wide waveguide wires, where the optical mode less likely enters the slot region, until a certain ratio of \(s/w\) is overcome (Figure 9). For the entire range of \(w\) no higher modes were observed. A distinct maximum for \(\Gamma_{\mathrm{slot}}\) has been found for \(w=200\,\mathrm{nm}\) and \(s=60\,\mathrm{nm}\), up to \(\Gamma_{\mathrm{slot}}=0.1867\). The difference \(\Delta\Gamma_{\mathrm{slot}}\) is very small, though, and even becomes negative below \(s=70\,\mathrm{nm}\), as shown in Figure 8b.  
Figure 8: Difference in the effective refractive index \(\Delta n_{\mathrm{eff}}\) (**a**) and the field confinement factor \(\Delta\Gamma_{\mathrm{slot}}\) (**b**) of both concentrations as a function of \(s\), with \(w\) as parameter.  
Figure 7: Difference in the effective refractive index \(\Delta n_{\mathrm{eff}}\) (**a**) and the field confinement factor \(\Delta\Gamma_{\mathrm{slot}}\) (**b**) of both concentrations as a function of \(s\), with \(\theta\) as parameter.
## 3 Circuit Implementation  
Although there are many types of manufacturing variation that could serve as sources of entropy for a random ID generator, the type chosen for this application is the variation between the threshold voltage, \(V_{T}\), of two identically drawn FETs. Because the variance of \(V_{T}\) is inversely proportional to the device area [19], both devices are drawn as the minimum size available in the technology. A schematic of an \(N\)-bit random ID generator is shown in Figure 1.  
Figure 1: \(N\)-bit ID generator. The organization is similar to that of a memory, where multiple ID cells share a common set of bit-lines and a sense amplifier.  
The organization of the ID generator is similar to that of a memory. Each ID cell produces one random bit, based on the \(V_{T}\) difference between M1 and M2. When equal gate voltages are applied to M1 and M2, the \(V_{T}\) difference creates a difference in drain currents, \(\Delta I_{D}\), the polarity of which is detected by the sense amplifier (SA). A column of \(N\) ID cells is read sequentially to produce an \(N\)-bit random ID number. A simple shift register is used to drive the word-line signals rather than a row decoder, since random access is not necessary, and this requires less energy and area.  
Because the SA should be constructed with negligible input referred offset, a single SA built from large devices is constructed, and shared by the column. A schematic of the latch-based sense amplifier is shown in Figure 2. This structure is preferred for low-energy operation since it draws no static current after it has settled to its final state. Sharing the SA among multiple bits also amortizes the SA leakage current.
## 3 Data-Driven Dynamic Design Model for Product Structure
### Dynamic Design Model Based on Bayesian Network
#### 3.2.2 Parameters Learning of the Bayesian Network  
For a given dataset \(D\) and topological structure \(S^{h}\), the probability density of the network node variable can be determined by using prior knowledge. Let variable set \(X=\{x_{1},x_{2},x_{3},\ldots,x_{n}\}\), where \(n\) is the number of variables. For a random node variable \(x_{i}\), whose range and parent set are \(\{x_{i}^{1},x_{i}^{2},\ldots,x_{i}^{r_{i}}\}\) and \(\pi_{i}\), respectively. \(\theta_{ijk}=P\Big{(}x_{i}^{k}\Big{|}\tau_{i}^{j}\Big{)}\) represents the possibility that both \(x_{i}\) and \(\pi_{i}\) are at the \(j\)-th possible values. Thus, the probability density of the node in the network is \(P(\theta\,|\,D,S^{h})\). Herein, \(\theta ij\) is defined as follows.  
\[\theta_{ij}=[\theta_{ij1},\theta_{ij2},\ldots,\theta_{ijr_{i}}](i=1,2,\ldots, n;j=1,2,\ldots,R_{i}) \tag{4}\]  
Assuming that (1) the sample data is complete, then (2) the values of \(\theta_{ij}\) are, respectively, independent and (3) for every value of \(\theta_{ij}\) there is a Dirichlet prior distribution, then the posterior probability distribution can be expressed as follows:  
\[P(\theta_{ij}\Big{|}D,S^{h})=Dir(\theta_{ij}\Big{|}\alpha_{ij1}+N_{ij1},\alpha _{ij2}+N_{ij2},\ldots,\alpha_{ijr_{i}}+N_{ijr_{i}}) \tag{5}\]  
where \(N_{ijk}\) is the sample number in data set \(D\), when the \(i\)-th node is at \(k\)-th value, meanwhile its parent set is at \(j\)-th value.  
Figure 3: Analysis model based on Bayesian network.
# Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks
## 2 System Model and Problem Formulation
### Problem Formulation
Since \(\mathcal{OP}\) is untrackable and hard to solve, we propose to obtain \(\{P_{k}\}\), \(\{Q_{k}\}\) and \(\{\rho_{k}\}\) in an iterative manner. To be specific, we first optimize \(\{P_{k}\}\) with fixed \(\{Q_{k}\}\) and \(\{\rho_{k}\}\), and then update \(\{Q_{k}\}\) and \(\{\rho_{k}\}\) with the optimized \(\{P_{k}\}\). The obtained results can then in turns help to update \(\{P_{k}\}\) again iteratively.