esa-sceva/satcom-chunk-collection huggingface dataset:
# Image Scanning Microscopy to Investigate Polycomb Protein Colocalization onto Chromatin
## 3 Results and Discussion
### Single-cell Analysis of EZH2/H3K27 me3 Correlation  
The moderately positive EZH2/H3K27 me3 colocalization prompted us to verify whether a stoichiometric correlation between the methyltransferase enzyme and its product would be visible at the whole nuclear level, taking advantage of the intrinsically heterogeneous protein expression across different cells. Accordingly, we measured the fluorescence given by both proteins for a large number of nuclei (n = 186). Figure 5 shows the H3K27 me3 vs. EZH2 plot. Qualitatively, the trend of H3K27 me3 with increasing EZH2 expression posited a positive stoichiometric correlation between the two partners, as quantitatively demonstrated by the Spearman non-parametric correlation test (\(r\) = 0.435, \(p\) < 0.0001). In addition to a minor effect due to the immunolabeling procedure quantified in ref. [19], the presence of scattered values that reduce the monotonicity of the H3K27 me3 vs. EZH2 reflects the cell heterogeneity with respect to the extent of methylated H3 per EZH2 molecule. Albeit some genomic heterogeneity of the cell population could be envisaged (due, for instance, to a variable number of chromosomes), a realistic contribution to the observed dispersion should be attributed to the non-synchronous cell cycle within the cell population. Indeed, a perfect stoichiometric correlation between the concentrations of an enzyme and its product in an ensemble of independent units occurs only if they are synchronized in time, owing to the monotonic dependence of the catalyzed reaction rate from the enzyme concentration.  
Overall, our findings highlight a partial spatiotemporal overlap between EZH2 and its enzymatic product H3K27 me3 at target genomic regions, whereas the functional correlation at the whole nuclear level is well established. This may hint to a mechanism where some PRC2 complexes remain stably bound to chromatin after deposition of the H3K27 me3 mark, whereas another pool of PRC2 acts more according to a hit-and-run methylation mechanism, similarly to what was observed for PRC1 [17; 30].  
Figure 4: Pearson colocalization coefficients (R) of EZH2/RING1b (blue), EZH2/BMI1 (red), and EZH2/H3K27 Me3(black) in HCC827 cells as determined by ISM. EZH2/RING1b: \(R\) = 0.27 \(\pm\) 0.02 (FR-ISM), \(R\) = 0.20 \(\pm\) 0.02 (ISM**); EZH2/BMI1: \(R\) = 0.17 \(\pm\) 0.02 (PR-ISM), \(R\) = 0.13 \(\pm\) 0.02 (ISM**); EZH2/H3K27 me3: \(R\) = 0.27 \(\pm\) 0.01 (PR-ISM), \(R\) = 0.22 \(\pm\) 0.01 (ISM**); values expressed as average \(\pm\) SEM, \({}^{*}p\) < 0.05, \({}^{**}p\) < 0.01, \({}^{***}p\) < 0.001.
## 3 Model Development
### Steady-State Model Development  
The un-symmetric electrolyte NRTL model is the property method used to represent the capture system, being able to handle various concentrations, aqueous and mixed solvents. While the ENRTL-RK and PC-SAFT equations of state compute the liquid and vapor properties, respectively. Carbon dioxide, nitrogen, oxygen, and sulfur dioxide are chosen to be the Henry components for the model to which [PERSON]'s law is applied. The Electrolyte NRTL model is based on two fundamental assumptions: like-ion repulsion assumption and the local electroneutrality assumption. The first assumptions indicate that due to the large repulsive forces between the different ions having similar charges, the local composition of cations or anions present around their similar ion is zero. Local electroneutrality refers to the assumption that the cation and anion distribution surrounding a central solvent molecule results in a net local ionic charge of zero. The ENRTL model expresses the excess Gibbs free energy as a summation between the molar excess free energy resulting from the long-range forces and from the local forces [11]. All thermodynamic data proposed in the current study are available to the user in the Aspen Plus(r) database.  
The acid gas loading is defined as the ratio of the apparent moles of CO2 to the apparent moles of MEA solvent, by apparent, we mean before reacting. The loading is calculated by dividing the moles of CO2 and all the carrying species dissolved in one mole of MEA and all the carrying species [11] under enough pressure to completely dissolve the gas, regardless of their forms after the reaction. The weight percent of MEA in our study is calculated without the carbon dioxide gas, thus in order to achieve a 30 wt% MEA solvent, 1 mole of MEA has to be added to about 7.9 moles of water [36]. The lean loading comes into the absorber with a loading of about 0.2-0.3 and leaves after absorbing the gas. The maximum loading of CO2 into MEA solvent that could theoretically be achieved in the absorber is 0.5 (mole of CO2 per two moles MEA) [9]. An equilibrium-based model is developed for both the absorption and desorption columns. The equilibrium model divides the column into a number of stages under the assumption that the vapor and liquid phases leaving each stage are in equilibrium. From the equilibrium model, initial unit operating values and stream flows are obtained for a further robust rate-based simulation, which greatly differs from the equilibrium simulation due to the reactive nature of the process [11]. For the dynamic simulation, the equilibrium-based model is the one converted, as Aspen Plus(r) Dynamics does not support rate-based model units.
## 3 Results
### Effects of Solution pH and Adsorbent Dosage on Adsorption of Cd on DMSA/PDA/ZnO  
Aquatic pH could change the distribution of adsorbate and the surface charge of adsorbent (Figure S2), which could subsequently influence the adsorption efficiency. The surface of DMSA/PDA/ZnO was negatively charged after modification by DMSA and PDA (Figure S3). The results are in line with the report that PDA is a negative polyelectrolyte [33]. The negative surface of DMSA/PDA/ZnO favored the binding of positive charged Cd(II) other than metal-ligand chelation. As shown in Figure 7a, aquatic pH had a significant influence on the adsorption of Cd(II) on DMSA/PDA/ZnO. The adsorption ratio increased from 70% to 98% for a pH increase from 3.0 to 7.0 and decreased to 80% at pH 9.0. The decrease in the adsorption ratio at pH 9.0 might also be due to the formation of CdOH\({}^{+}\) ion.  
Figure 6: Dependence of the adsorbed Cd(II) per gram adsorbent (\(q_{\rm e}\)) on the equilibrium concentration (\(c_{\rm e}\)). The solid lines correspond to the fitting of the data to [PERSON] (**red line**) and [PERSON] (**dark green line**) isotherm model.  
Figure 7: Effects of (**a**) solution pH, and (**b**) DMSA/PDA/ZnO on the adsorption ratio of Cd(II).  
Figure 7b shows the effects of DMSA/PDA/ZnO dosage on the adsorption of Cd. The adsorption ratio of Cd increased from 86% to 94% with the increase of loaded DMSA/PDA/ZnO from 0.1 to 0.2 g/L. The adsorption ratio further increased to 98% with a further increase in DMSA/PDA/ZnO up to 1.0 g/L. The increase in adsorption rate with the increase of loaded DMSA/PDA/ZnO was likely to have been caused by the additional chelating sites for Cd(II). Therefore, a dosage of 0.5 g/L was adopted for Cd(II) preconcentration due to the accepted adsorption ratio and the relatively low consumption of acid for dissolution.
###### Abstract  
Wildfires pose an escalating threat to ecosystems and human settlements, making accurate forecasting essential for early mitigation. This study compared three deep learning models for wildfire prediction: Deep Reinforcement Learning (DRL) with Actor-Critic architecture, Convolutional Neural Network (CNN), and Transformer-based models. The models were trained and evaluated using historical data from Chile (2000-2023), including wildfire occurrences, meteorological variables, topography, and vegetation indices. After preprocessing and class balancing, each model was tested over 100 experimental runs. All models achieved outstanding performance, with F1-Scores exceeding 0.999 and perfect AUC-ROC scores. The Transformer model showed a slight advantage over the CNN (99.94%) and Actor-Critic DRL (99.93%) in accuracy. Feature importance analysis identified wind speed, temperature, and vegetation indices as the most influential variables. While DRL offers theoretical benefits for adaptive decision-making, Transformer architectures more effectively capture spatiotemporal dependencies in wildfire dynamics. The findings can support the integration of deep learning models into early warning systems, contributing to proactive wildfire risk management. Future work will include validation with diverse regional datasets, real-time deployment, and collaboration with emergency response agencies.  
wildfire prediction; deep reinforcement learning; actor-critic; machine learning; convolutional neural networks; transformer models; AI-driven risk assessment; fire behavior modeling +
Footnote †: journal: Applied sciences  
Article
# Online Streaming Feature Selection via Conditional Independence
## 3 Framework for Streaming Features Filtering  
### Notations, Definitions, and Formalizations  
The entire feature set consists of four types of features: irrelevant, redundant, weakly relevant but non-redundant, and strongly relevant features [6]. Strongly relevant features are indispensable in the sense that they cannot be removed without loss of prediction accuracy. If a strongly relevant feature is removed alone, it will result in performance deterioration of an optimal classifier. Weakly relevant features can sometimes contribute to prediction accuracy. Therefore, they are divided into non-redundant features and redundant features [6]. Irrelevant features are not necessary for improving prediction accuracy [20]. A feature is irrelevant if it is not strongly or weakly relevant [3]. Definitions of these concepts are provided in Section 3.1.2.  
In the feature selection process, the features selected for class attributes include an optimal feature subset [20] that contains all non-redundant features and strongly relevant features [6]. The optimal feature subset is called the _Markov blanket_ of class attributes. The _Markov blanket_ criterion removes only attributes that are unnecessary, including completely irrelevant and redundant features [35].
## 4 Performance Evaluation
### Simulation Environment
#### 4.1.3 Testing Stage  
The model evaluated all the trees using the estimation function, which assessed each random tree individually. The majority vote from the outputs of all the trees was then used as the final predicted value. The accuracy of each tree was computed as the ratio of correct encounters to the total number of encounters in the data, considering only encounters that occurred at a specific point in time, where time is represented by \((U,E)\). The aggregate prediction was obtained by synthesizing the prediction from all the trees.
## Open Issues in DTN Multicasting
### Group Authentication  
From the perspective of DTN group membership, multicast group key management is one of the critical components for multicast group authentication to secure communication and protect data. However, conventional group key management schemes are not applicable in DTN due to its frequent disruption and long propagation delays. For example, the stateful Logical Key Hierarchy (LKH) [81] scheme requires re-keying from the key management center when a user joins or leaves the network,and it is not practical in DTNs with no reliable end-to-end network links. A Chinese Remainder Group Key (CRGK) scheme [82] for DTN environments is proposed, which omits the broadcast of key update messages when a new user joins the network by letting each member derive a new group key using a forward hash function. CRGK only broadcasts the key update message when a user leaves the group, and the complexity depends on the number of users in the group. [PERSON] [83] extended CRGK into the Modified Chinese Remainder Group Key (MCRGK) scheme that does not need to broadcast any key update messages when a user joins or leaves the group. Both CRGK and MCRGK are only able to accommodate small to medium-sized DTN groups. [PERSON], [PERSON], and [PERSON] [84] surveyed these key establishment methods for group communication as part of their proposed taxonomy and discussed them in details with DTN's security requirements.  
[PERSON], [PERSON], and [PERSON] [82] discussed three requirements for group key management schemes in DTN. Firstly, the scheme needs to minimize the number and size of the key update messages to avoid communication overheads. Secondly, an efficient group key management scheme for DTN should be stateless, and re-keying can be done through the latest key update message. Lastly, adding a key lifetime to the scheme is necessary to protect forward security after a user leaves the group. Nevertheless, the scalability of group key management schemes remains one of the most prominent issues. The computational complexity of the key server and length of key update messages grows with the size of the group. The implementation of key management schemes in the DTN multicast protocol will increase the resource overheads, especially for IoT devices, and this is an interesting open issue to be resolved.
## 7 Conclusions  
Most lesions have an otorhinolaryngological (ORL) and oromaxillofacial (OMF) starting point. The infection spreads through contiguity, through the lymphatic or hematogenous route, following contamination of mucosa mainly of dental, buccal, pharyngeal, laryngeal, submaximillary, or parotid glandular inflammatory origin, but also of iatrogenic origin, following endoscopic maneuvers or oortracheal intubations. However, initial evaluation of the airway is a priority, and any signs of respiratory distress or impending airway compromise should be immediately and aggressively managed. A course of wide-spectrum antibiotics should be started empirically and changed according to bacteriological culture and sensitivity reports.  
In the last two decades, progress in diagnostic techniques, surgical treatment, and antibiotics, as well as improvement of anesthesia and intensive care protocols, have led to a significant decrease in mortality rates in patients with DNI and DNM. Early and aggressive treatment instituted based on CT results can stop the evolution of the infection towards DNM. Dynamic CT follow-up 48-72 h after the primary surgical intervention may indicate the need for a reintervention to drain a residual abscess, or excision of the necrotic tissue.  
The use of a multidisciplinary team in the management of DNI associated with DNM can lead to a decrease in serious complications, sepsis, and mortality.  
Conceptualization, G.B., B.M.C. and M.D.C.; methodology, M.D.C. and M.D.; validation, O.D.P.; data curation, L.M., M.C. and M.D.; writing--original draft preparation, C.M. and L.R.; writing--review and editing, F.S. and G.B.; supervision, B.M.C.; project administration, M.D.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Step of Current Management Protocol** & **Level of Evidence** \\ \hline Etiopathology & Level 1 (1) \\ \hline Clinical diagnosis & Level 2 (2) \\ \hline Paracclinical diagnosis & Level 1 (3) \\ \hline Airway management & Level 2 (4) \\ \hline Medical treatment & Level 1 (5) \\ \hline Surgical treatment & Level 1 (6) \\ \hline \hline \end{tabular}
\end{table}
Table 2: The current levels of evidence for each step of the current management protocol of deep neck infections associated with descending necrotizing mediastinitis.
## 2 Design Methodology
### Critical Design Parameters  
In this section, the process from simulation to final design is described. The length of the square of the outer resonator is essential to obtain the correct resonant frequency at the center of the lower bands. Therefore, a sweep of the \(Lq\) parameter is performed, as shown in Figure 4, which influences the meander-line dimensions. Using meanders in a design allows for a decrease in the resonance frequency without altering the cell size, making them an effective tool for fine-tuning the design to meet desired performance requirements.  
Figure 3: FSS structure excited by an incident plane wave (\(E_{i}\)), which is reflected (\(E_{r}\)) and transmitted (\(E_{i}\)).  
Designs with a square length from \(Lq\) = 29 mm to \(Lq\) = 31 mm would be candidates to cover the lower frequency bands (3 GPP and WiFi I, highlighted in grey). As it will shown later, the effect of the second nested resonator will shift further down the filtering frequency, and therefore \(Lq\) = 29 mm is selected to make up the envisaged effect. Although a compact design was achieved with only one resonator, another resonator dedicated specifically to the WiFi II band was added. The new resonator is an exact copy of the first resonator, where its dimensions are scaled and reduced to obtain a filter response in the frequency of the wide WiFi II band.  
The inner resonator was adjusted using a size reduction coefficient, as shown in Figure 5. This coefficient was estimated by the ratio between the resonant frequency of the previous design and the center of the second band, which is 5.5 GHz. The resulting size reduction coefficient is found to be 0.39.  
Figure 4: Simulated effect of increasing square length (\(Lq\) sweep parameter).  
Figure 5: Simulated effect of the inner resonator.  
The figure shows a scale factor parameter sweep around the estimated value to corroborate the hypothesis and test the impact of the mutual coupling corresponding to the nested architecture. As can be seen in Figure 5, if the scale factor is set lower than the calculated parameter, the frequency will overlap with the outer harmonic at the end of the desired band (black line). On the other hand, if the scale factor is set too high, the resonant frequency will be outside the desired band (blue line). Thus, the reduction coefficient of 0.39 turns out to be optimal for this band rejection. This setting causes the lower band to shift down and become centered at the targeted frequency.
# Analytical Solution for the Problem of Point Location in Arbitrary Planar Domains
## 7 Application to Bezier Curves
### Application to the Challenges Given  
By using the previous techniques for linear, circular, and Bezier segments in an integrated and complementary form, it is possible to test situations as those illustrated in Figure 1 for a set of random points, which results as shown in Figure 19.  
From the point of view of programming, three functions were created and used: NRAintLin(), NRAintArc() and NRAintBez(), whose source code is also available at the GitHub repository indicated earlier. These functions return the NRA counting for each respective segment when invoked accordingly to the type of segment: 3 linear and 3 circular arcs on the region on the left, and 2 linear, 3 circular arcs and 2 Bezier segments on the region on the right. These three functions are essential to establish the general algorithm for regions delimited by linear, circular, or Bezier segments, which is the subject of the next section.
# Low-Power Two-Phase Clocking Adiabatic PUF Circuit
## 2 Fundamental Adiabatic PUF
### Conventional Adiabatic PUF  
In 2016, the first PUF circuit (quasi-adiabatic logic PUF (QUALPUF)) that employed the adiabatic switching technique was reported in [29], in which the PUF cell was composed of a cross-coupled inverter (M1, M2, M3, and M4), and a pull-up network transistor to enable or disable the PUF cell. The fundamental QUALPUF circuit topology and its timing chart are shown in Figure 2a,b, respectively. Figure 2b describes the four phases (wait, evaluate, hold, and recovery) of the adiabatic switching operation during challenge-bit (Cb) in the logic low state. Moreover, the adiabatic PUF is supplied with trapezoidal power clock signals that enable PUF response bits to be all zero-level once challenge-bit gets logic \"1\". However, the response-bit of the QUALPUF stays at V\({}_{\text{TH}}\) of M3 (approximately 0.45 V), which yields few floating charges during the recovery phase. The stored charge is not fully discharged/recovered back to the power supply. The novel QUALPUF was again thoroughly investigated using 180 nm and 45 nm CMOS technology in a cadence spectrum simulator to analyze the effect of channel length variations [31]. The post-layout simulation result of 4-bits cascaded QUALPUF was reported in [30], and the fabricated chip of 4-bits cascaded QUALPUF LSI using 0.18 \(\upmu\)m ROHM standard CMOS process was tested in [32].
## 1 Introduction
### Literature Review
This solution considers an accurate model for the DC-link, and the stability of the PV system is formally demonstrated. However, the design of the converter elements is not taken into account, and the output current of this first stage is discontinuous. From the previous discussions, the following conclusions are obtained:  
* The boost converter is the most widely adopted solution to develop PV microinverters. Nonetheless, a design procedure for the converter elements, based on the particular requirements of the PV installation, is needed. * The SMC is widely adopted in PV systems due to its robustness to parametric changes and satisfactory rejection of environmental perturbations. However, the global stability is not ensured; thus, the associated mathematical analysis is needed. * The low-frequency voltage oscillations at the DC-link, caused by the grid connection of the second stage, must be reduced or mitigated. This can be performed by implementing the DC-link with a large electrolytic capacitor at the expense of reliability or by using high-bandwidth controllers in the first stage. * The solutions previously discussed are based on DC/DC converters with discontinuous output current, requiring large DC-link capacitors to reduce the high-frequency current harmonics introduced to the second stage. * The P&O algorithm is the most widely used solution in PV microinverter applications due to its efficiency and simplicity, followed by the INC solution.