esa-sceva/satcom-chunk-collection huggingface dataset:
# The Importance of Gram-Negative Rods in Chronic Rhinosinusitis
In healthy individuals, commonly identified upper respiratory tract bacteria genera include _Staphylococcus_, _Corynebacterium_, _Peptoniphilus_, and _Cutibacterium_[20, 21]. Interestingly, the total bacterial load in healthy and diseased sinuses seems to be very similar, and many opportunistic pathogens are present in low numbers in healthy sinuses. Studies have shown that a loss of microbial diversity characterizes the CRS microbiome. The development under favorable conditions of pathogenic bacteria and a collapse of the commensal population disrupt the microbiota, which may contribute to the exacerbation of chronic inflammatory disease. Recent evaluations of microbes in CRS revealed a significant degree of interpersonal variation of the sinonasal microbiome and reduced bacterial diversity compared with healthy subjects. These studies noted that CRS bacterial microbiota can exist in at least four distinct taxonomic states dominated by _Streptococcaceae_, _Pseudomonadaceae_, _Corynebacteriaceae_, or _Staphylococcaceae_. Although bacteria such as _S. aureus_ and _S. epidermidis_ predominated in CRS, recovery of gram-negative rods, including _Proteus_ spp., _Enterobacter_ spp., _Escherichia coli_, and _Klebsiella pneumoniae_ were also reported [22, 23, 24, 25]. Since Gram-negative rods are rarely recovered from healthy individuals, the isolation of these bacteria from symptomatic patients suggests their pathogenic role in CRS. However, the differences in the isolation rates of Gram-negative rods have been reported [26, 27]. An important role in the pathogenesis and maintenance of the recalcitrant inflammation for CRS may be played by biofilm-forming bacteria. Biofilm is a possible method by which bacteria can evade normal host defense mechanisms and antibiotic treatment [28]. In fact, both appear to be risk factors for therapy failures and CRS recurrence. Therefore, recognizing the microbiology of CRS is important when selecting the antimicrobial therapy for this multifactorial disease. This study aimed to evaluate the incidence of Gram-negative rods in chronic rhinsinusitis in adults, in vitro ability to biofilm formation, and resistance to antibiotics as a part of a prospective microbiological study.
# A Survey of Algorithms and Systems for Evacuating People in Confined Spaces
## 3 Evacuation Wayfinding Algorithms
### Off-Line Evacuation Wayfinding Algorithms
#### 3.1.7 Animal Agent-Based Algorithms  
Owning to the scarcity of human emergent behavioural data and the difficulty in conducting genuine emergency evacuation experiments, the studies of emergent behaviours have largely depended on simulations. Hence, in recent years, animals have been used in escape panic experiments to study crowd evacuation. For example, the research in [61] employed mice to study an indoor evacuation process; mice were released into a rectangular container (to simulate a large single room) filled with tap water and were left to swim towards a dry platform; an exit was placed between the wet and dry areas to simulate the door of the single room; the effect of exit width and exit number on the mouse escape rate was investigated over different experimental sessions, which were recorded with a digital video camera; the experiments demonstrated some well-known behaviours of a panicking crowd: when the exit width approximately was equal to the size of a mouse, the diffusive evacuation flow was observed; when the exit width became larger, the mice evacuated throughout the exit in bursts of different sizes that yield the power-law distributions depending on the exit width. The work in [62] employed a species of Cuban leafcutter ants called _Atta insularis_ to investigate the effect of panic-induced herding on an evacuation process from a two-exit room; ants were introduced into a circular acrylic cell with two exits symmetrically situated at the left and right; in the first experiment, which simulated a normal evacuation process, when the ants were placed into the cell, the two exits were opened synchronously, so that the ants could escape; in the second experiment, which mimicked an emergency evacuation process, the only difference from the first experiment was injecting a dose of insect-repelling liquid to generate a panic before opening the exits; the experimental results showed that ants escaped from both exits in approximately equal proportions in normal conditions, but preferred one of the exits in emergency conditions; the experiments demonstrated the theoretical prediction that the herding behaviour in confined spaces can generate a non-symmetrical use of two identical exit doors; in addition, the observed evacuation dynamics were reproduced with a computer model inspired by [36].
## 7 Experimental Demonstration
### Analysis of Special Cases
The PU governor will verify the percentage of the request based on its state information, and if an attacker performs an attack through DRAS Y, it will be verified by the DRAS Y governor since it knows how the exact percentage of load needs to be shed based on the state information received from the PU governor. **Critical Infrastructure Scenario. ** Suppose a generation loss occurs in area X where a critical infrastructure (such as a hospital) is present and DRAS X cannot supply enough power to the hospital by shedding load in just area X. In this case, it requests PU to perform shedding in one of the adjacent areas because it is necessary to supply power to the hospital. We assume that the hospital has already used its power backup storage and DRAS X does not have enough storage to satisfy hospital demand. PU performs load shedding in another area: area Y. If the percentage of the load to be shed is within the threshold limits, the governor will allow commands to go through according to Rule 2 and Rule 6. However, if it is more than the threshold limit, it will not be allowed. We need to update the rule to accommodate this edge case. In such a case, the governor will disconnect area X from the rest of the grid and perform load shedding so that over-frequency changes do not cascade to the rest of the grid. Therefore, it will be able to shed load and supply power to the hospital. **Reduce Load Shedding Attack. ** Suppose in DRAS 1 area, 20% of generation loss (32.6 MW) occurs, and in order to maintain frequency above the under-frequency threshold, DRAS 1 must send load shedding signals to reduce 30% of the load on bus 5. Since we have assumed that DRAS 1 has already been compromised, an adversary reduces the percentage of load shedding to be performed in the region in order to cause overloading. With the current governor rules, the governor cannot detect an attack, and it will allow commands to go through. We need to update the rule for this scenario. For the percentage of contingency, in reality, RTDS will simulate the minimum percentage of the load L(t) to be shed so that frequency is above the under-frequency threshold. In the safety rule, the governor checks whether the percentage of the load shed is within the lower bound L(t) and upper bound P(t). If yes, it will allow commands; otherwise, it notifies the SOC. Similarly, we can update rules for other DR functions.
## 1 Introduction
Additionally, vegetation indices, such as the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the vegetation conditions index (VCI), the temperature condition index (TCI), the normalized difference water index (NDWI), and the vegetation health index (VHI), are commonly used to assess crop health during drought [33]. While these indices provide valuable insights, Solar-Induced Chlorophyll Fluorescence (SIF) has proven more sensitive to SM deficits and responds more rapidly to drought stress, making it an important indicator for estimating drought-induced crop losses [34]. While existing indices based on ground observations can estimate drought events well, they suffer from poor spatial continuity, high data capture costs, and limited comparability across different spatiotemporal scales. Satellite-based drought indices, which are timely, extensive, continuous, and inexpensive, have been proposed and widely applied in global and regional agricultural drought monitoring [35]. However, satellite-based indices that rely on a single or limited set of factors are insufficient for capturing the complexity of drought conditions. To improve drought assessment accuracy, several comprehensive remote sensing (RS) drought indices have been developed, i.e., the temperature-vegetation-soil moisture drought index (TVMDI) [36], temperature-vegetation-precipitation dryness index (TVPDI) [37], and temperature-SIF-Water Balance Dryness Index (TSWDI) [38]. While these indices offer a more holistic view of drought, they are often complicated, require large amounts of data, and face challenges with regional applicability [39]. Additionally, indices with low spatiotemporal resolution are not suitable for agricultural drought assessments. Therefore, it is necessary to construct a novel integrated index that can accurately capture drought dynamics and meet the needs of agricultural management. Consequently, in this study, a novel integrated RS drought index, the Vapor Pressure Deficit-Soil Moisture-Sun-Induced Chlorophyll fluorescence Dryness Index (VMFDI), based on high-resolution multisource data and key drought-causing factors (VPD, SM, and SIF) and drought principles was constructed via a three-dimensional spatial distance model. The objectives of this study are as follows: (1) to validate the VMFDI's accuracy and reliability through multiple validation methods; (2) to apply the VMFDI to analyze the spatiotemporal dynamics of drought in the Yellow River Basin and the agroecosystem and assess the main factors influencing drought conditions; and (3) to explore the responses of crop growth, productivity, and yields in the agroecosystem to droughts, providing critical insights into drought-induced agricultural risks. Based on these findings, this study aims to propose evidence-based strategies for enhancing agricultural drought resilience, informing smart agriculture practices, and guiding high-quality agricultural development.
# QoS-Aware Flexible Handover Management in Software-Defined Mobile Networks
## 6 Conclusions  
In this paper, we propose a flexible handover management scheme in SDN-based mobile networks. Firstly, flows are classified into four classes considering QoS requirements in terms of loss and delay sensitiveness. Then, according to the flow classifications, the QoS-based differential handover procedure for each class can be provided by the interaction between the forwarding plane nodes and SDN controller. From the analytical results, compared to the conventional schemes which can only provide their own individual handover procedure (which can be too strict or too loose), the proposed scheme provides efficient network operations without any service degradation based on the flexible handover management according to the service characteristics. In future work, the proposed scheme will be validated to measure the practical benefits based on a virtualized network environment using OpenFlow-based components and real network events.  
**Author Contributions:** Conceptualization, Y.K.; methodology, Y.K.; validation, Y.K.; formal analysis, Y.K, and T.-K.K.; investigation, T.-K.K.; resources, Y.K. and T.-K.K.; data curation, Y.K. and T.-K.K.; writing--original draft preparation, Y.K.; writing--review and editing, Y.K. and T.-K.K.; visualization, Y.K.; supervision, T.-K.K.; funding acquisition, T.-K.K. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Acknowledgments:** This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP: Ministry of Science, ICT & Future Planning) (No. 2017R1C1B2011285).  
Figure 5: Packet loss according to the rate of user mobility (**a**) and average residence time (**b**).
_Forests_**2015**, \(6\), 3528-3546; doi:10.3390/f6103528  
_forests_  
**ISSN 1999-4907**  
www.mdpi.com/journal/forests  
_Article_  
**Carbon Budgets for Caribbean Mangrove Forests of Varying Structure and with Phosphorus Enrichment**  
**[PERSON] 1,*, [PERSON] 2,3, [PERSON] 2 and [PERSON] 2**  
1 School of Biological Science, The University of Queensland, St Lucia, Queensland 5072, Australia  
2 Smithsonian Environmental Research Center, 647 Contees Wharf Rd, Edgewater, MD 21037, USA; E-Mails: [EMAIL_ADDRESS] (L.T.S.); [EMAIL_ADDRESS] (L.J.D.); [EMAIL_ADDRESS] (I.C.F.)  
3 Smithsonian Marine Station at Fort Pierce, 701 Seaway Dr, Fort Pierce, FL 34949, USA  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +61-7-3365-2304; Fax: +61-7-3365-4075.  
Academic Editor: [PERSON]  
_Received: 13 August 2015 / Accepted: 28 September 2015 / Published: 7 October 2015_  
**Abstract:** There are few detailed carbon (C) budgets of mangrove forests, yet these are important for understanding C sequestration in mangrove forests, how they support the productivity of the coast and their vulnerability to environmental change. Here, we develop C budgets for mangroves on the islands of Twin Cays, Belize. We consider seaward fringing forests and interior scrub forests that have been fertilized with phosphorus (P), which severely limits growth of trees in the scrub forests. We found that respiration of the aboveground biomass accounted for 60%-80% of the fixed C and that respiration of the canopy and aboveground roots were important components of respiration. Soil respiration accounted for only 7%-11% of total gross primary production (GPP) while burial of C in soils was ~4% of GPP. Respiration by roots can account for the majority of soil respiration in fringing forests, while microbial processes may account 80% of respiration in scrub forests. Fertilization of scrub forests with P enhanced GPP but the proportion of C buried declined to ~2% of GPP. Net ecosystem production was 17%-27% of GPP similar to that reported for other mangrove forests. Carbon isotope signatures of adjacent seagrass suggest that dissolved C from mangroves is exported into the adjacent ecosystems. Our data indicate that C budgets can vary among mangrove forest types and with nutrient enrichment and that low productivity mangroves provide a disproportionate share of exported C.  
_Forests_**2015**, \(6\)  
**Keywords:**_Rhizophora image_; respiration; fertilization; carbon burial; Belize
## 6 Performance Assessment  
To evaluate the performance of the classifier, we use standard statistical indexes such as Sensitivity (Sens), Specificity (Spe), Accuracy (Acc), and Precision (Pre), as shown by Equations (2)-(5), where TP are the True Positives, FN the False Negatives, TN the True Negatives, and FP the False Positives [33].  
\[Sensitivity(\%)=\frac{TP}{TP+FN}\times 100 \tag{2}\]  
\[Specificity(\%)=\frac{TN}{TN+FP}\times 100 \tag{3}\]  
\[Accuracy(\%)=\frac{TP+TN}{TP+FN+TN+FP}\times 100 \tag{4}\]  
\[Precision(\%)=\frac{TP}{TP+FP}\times 100 \tag{5}\]  
The calculation of the value of the global specificity, accuracy and Precision of one of the types (\(VF\), \(VT\), \(Normal\), \(Others\)) is obtained by using the specificity, accuracy, and Precision of this type of pathology before the sum of the remaining pathology types. The execution time of each of the tests performed was measured using a Fujitsu AH544 (Tokyo, Japan) laptop computer with an Intel (R) Core (TM) i7-3612 [EMAIL_ADDRESS] GHz processor with 8 GB RAM, 64-bit operating system using Matlab (R).  
For completion, the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) values are also calculated.  
Figure 4: Parallel classifier combination and final voting. All classifiers receive all data and must obtain a four-class decision through a majority voting among results generated by each classifier.  
Figure 5: Hierarchical topology classifier. Multi-class classification is obtained by joining several binary classifiers.
## 4 Data Processing Scheme
### Tracking Networks  
The tracking network plays a very important role in POD. Thus IGS puts a large effort into optimizing its tracking network in terms of station density and distribution. In general, a tracking network with about 100 globally even distributed stations is used for POD of the GPS and/or GLONASS systems. For the BeiDou regional system, its constellation consists mainly of GEO and IGSO satellites whose movement is restricted over a dedicated region instead of around the Earth like MEOs. Obviously, these satellites can only be tracked by stations in a certain region and each station may contribute quite differently to different satellites. Therefore, the impact of tracking geometry is different from POD for GPS and further investigation is necessary for possible improvement. From Figure 1, the BETS network has five stations outside the Chinese territory. Among them SIGP and  
Figure 4: Procedure for precise orbit determination processing.  
PETH extend the network towards the southern hemisphere and LEID, JOHA, and DHAB enlarge the network westward towards Europe and South Africa.  
For the impact study of the tracking geometry, we selected four tracking networks displayed in Figure 5: the Chinese regional network (violet), Asian-Pacific network (red), Asian network (green), and the global network (yellow). The four networks will be processed with the same strategy and the orbits are compared to assess the impact of network geometry on satellite orbits.
###### Abstract  
A coherent optical (CO) orthogonal frequency division multiplexing (OFDM) scheme gives a scalable and flexible solution for increasing the transmission rate, being extremely robust to chromatic dispersion as well as polarization mode dispersion. Nevertheless, as any coherent-detection OFDM system, the overall system performance is limited by laser phase noises. On the other hand, extreme learning machines (ELMs) have gained a lot of attention from the machine learning community owing to good generalization performance, negligible learning speed, and minimum human intervention. In this manuscript, a phase-error mitigation method based on the single-hidden layer feedforward network prone to the improved ELM algorithm for CO-OFDM systems is introduced for the first time. In the training step, two steps are distinguished. Firstly, pilots are used, which is very common in OFDM-based systems, to diminish laser phase noises as well as to correct frequency-selective impairments and, therefore, the bandwidth efficiency can be maximized. Secondly, the regularization parameter is included in the ELM to balance the empirical and structural risks, namely to minimize the root mean square error in the test stage and, consequently, the bit error rate (BER) metric. The operational principle of the real-complex (RC) ELM is analytically explained, and then, its sub-parameters (number of hidden neurons, regularization parameter, and activation function) are numerically found in order to enhance the system performance. For binary and quadrature phase-shift keying modulations, the RC-ELM outperforms the benchmark pilot-assisted equalizer as well as the fully-real ELM, and almost matches the common phase error (CPE) compensation and the ELM defined in the complex domain (C-ELM) in terms of the BER over an additive white Gaussian noise channel and different laser oscillators. However, both techniques are characterized by the following disadvantages: the CPE compensator reduces the transmission rate since an additional preamble is mandatory for channel estimation purposes, while the C-ELM requires a bounded and differentiable activation function in the complex domain and can not follow semi-supervised training. In the same context, the novel ELM algorithm can not compete with the CPE compensator and C-ELM for the 16-ary quadrature amplitude modulation. On the other hand, the novel ELM exposes a negligible computational cost with respect to the C-ELM and PAE methods.  
keywords: coherent detection; extreme learning machine (ELM); laser phase noise; orthogonal frequency division multiplexing (OFDM); subcarrier modulation format +
Footnote †: journal: Journal of Scientific Computing
# Biosorption of Heavy Metals by the Bacterial Exopolysaccharideaccharide FucoPol
## 3 Results and Discussion
### Pp2+ Removal by FucoPol: Overall Assessment  
FucoPol revealed very promising Pb2+-binding ability, attaining high removal efficiency values (above 90%, for an initial metal concentration of 10 mg/L) at certain conditions, namely pH around 4.3 and temperatures up to 40 \({}^{\circ}\)C. Moreover, specific metal uptake values above 100 mg/gEPS were achieved for Pb2+ concentrations \(\geq\)48 mg/L. The demonstrated Pb2+ removal ability of FucoPol is comparable to that of other natural biosorbents reported in the literature, both in terms of removal efficiency (79.7-98.3%) [27, 33] and specific metal uptake (16.6-1103 mg/g biosorbent) [21, 46, 47]. The comparison of biosorbents' performance is difficult because different methodologies are implemented and different experimental conditions (pH, temperature, metal and biosorbent concentration, presence of other contaminants) are used. Therefore, comparing results of different studies must be made with caution. Nevertheless, the values obtained suggest FucoPol might be suitable for the development of environmentally friendly and sustainable processes for the removal and recovery of lead from contaminated waters.