esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
This paper presents a bridged-switch energy-efficient switching scheme for SAR ADCs with a low-complexity capacitor drive circuit. In the proposed switching scheme, top-plate sampling technology, closed-loop charge recovery technology, and bridged-switch technology are adopted, and only the last capacitor uses reference voltage V\({}_{\text{cm}}\). As a result, the DAC has lower switching-energy consumption, low drive circuit complexity, and low dependence on V\({}_{\text{cm}}\). In the proposed switching scheme, the average switching energy is 47.5 CV\({}^{2}\)\({}_{\text{ref}}\), which is 96.52% lower and reduces the area by 75% compared with the conventional switching scheme. The key circuit modules to reduce the power consumption of the SAR ADC are a full dynamic comparator, bootstrapped switches, and dynamic SAR logic. The proposed 10-bit SAR ADC was simulated under the conditions of 180 nm CMOS process and 1 MS/s, resulting in an SNDR of 60.76 dB, an SFDR of 69.85 dB, power consumption of 14.7 \(\upmu\)W, and an FoM of 16.55f/conv.-step. In this paper, although bridge switches are used, the ADC is not designed as a bit-adjustable ADC. So, in future work, an ADC could be designed as a bit-adjustable ADC by using bridge switches to extend the application area of ADCs.  
Conceptualization, Y.H.; methodology, Y.H.; software, Y.H. and B.T.; validation, Y.H., B.T. and L.H.; formal analysis, Y.H.; investigation, Q.H. and J.C.; resources, Y.H., B.L. and Z.W.; data curation, B.T. and C.C.; writing--original draft preparation, Y.H. and B.T.; writing--review and editing, C.C., L.H. and Q.H.; visualization, B.T., J.C. and J.X.; supervision, Y.H.; project administration, Y.H. and Z.W.; funding acquisition, B.L. and Y.H. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation of China (No. 60976026), the Key Field Project of Colleges and Universities in Guangdong Province (No. 2021 ZDZX1081), the Key Project of Social Welfare and Basic Research Project in Zhongshan City (2021B2020), the Construction Project of Professional Quality Engineering in 2020 (No. YLZY202001), and the Construction Project of Professional Quality Engineering in 2021 (No. JD202101).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflict of interest.
## 4 Experiment and Analysis
### Ablation Study  
To validate the contribution of each key component in the CLB-BER model, we conducted ablation experiments isolating the effects of the ECDW enhancement in CLUBS clustering and DistilBERT fine-tuning for classification.  
First, we ablated the ECDW method from the Improved-C (CLUBS) clustering phase, reverting to the standard CLUBS algorithm while keeping the downstream DistilBERT classification intact. As shown in Table 6, without ECDW, the silhouette index (SI) drops from 0.63 to 0.62 (consistent with the baseline CLUBS performance in Table 1), indicating reduced clustering quality due to the poorer handling of sequence misalignment and temporal symmetry. This propagates to downstream classification, reducing the accuracy from 94.21% to 92.50%, as the less-accurate cluster labels degrade the fine-tuning process.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model** & **Accuracy (\%)** & **Precision (\%)** & **Recall (\%)** & **F1 (\%)** \\ \hline KNN & 81.45 & 82.32 & 80.48 & 81.39 \\ SVM & 86.73 & 87.26 & 85.91 & 86.58 \\ CNN & 88.47 & 88.92 & 87.69 & 88.30 \\ LSTM & 90.28 & 90.84 & 89.87 & 90.35 \\ Transformer & 92.13 & 92.51 & 91.83 & 92.17 \\ Shapelet Transform & 89.50 & 90.00 & 88.75 & 89.37 \\ Transform Pipeline & 87.00 & 87.50 & 86.25 & 86.87 \\ Fuzzy C-Means + SVM & 94.21 & 94.63 & 94.05 & 94.34 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Assessment of performance across various classifiers.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Metric** & **DistilBERT Mean (Std)** & **Transformer Mean (Std)** & \(p\)**-Value** \\ \hline Accuracy & 94.21 (\(\pm\)0.25) & 92.13 (\(\pm\)0.30) & 0.0017 \\ \hline Precision & 94.63 (\(\pm\)0.22) & 92.51 (\(\pm\)0.28) & 0.0012 \\ \hline Recall & 94.05 (\(\pm\)0.21) & 91.83 (\(\pm\)0.27) & 0.0019 \\ \hline F1-score & 94.34 (\(\pm\)0.20) & 92.17 (\(\pm\)0.25) & 0.0014 \\ \hline \hline \end{tabular} All \(p\)-values are less than 0.05, indicating that the improvements achieved by DistilBERT over Transformer are statistically significant at the 95% confidence level.  
\end{table}
Table 5: Statistical significance test (paired t-test) between DistilBERT and Transformer.  
Second, we replace the fine-tuned DistilBERT with alternative classifiers (SVM and LSTM) while retaining the Improved-C clustering labels for training. This isolates the benefit of DistilBERT's contextual representation learning over simpler models. The results in Table 5 show that SVM achieves 86.73% accuracy (a 7.48% drop from the full model), and LSTM reaches 90.28% (a 3.93% drop), highlighting DistilBERT's superiority in capturing complex temporal patterns in electricity data.
## 3 General Features of Matrix Metalloproteinases (MMPs) and Tissue Inhibitors of MMP (TIMPs)  
Matrix metalloproteinases are a complex group of endopeptidase. They are a family of proteolytic enzymes with similar functional domains and a mechanism of action associated with the degradation of ECM components. MMPs are zinc-dependent proteases that can be activated by a number of cytokines and growth factors [10]. Metalloproteinases have the properties to attach to components of the extracellular matrix and in particular to collagen and elastin. MMPs are secreted by activated macrophages in the wall of arterial vessels. The ability of MMPs to change tissues is important from the point of view of normal and pathological physiology. Approximately 20 different types of MMPs are known, classified into groups according to the type of proteolytic substrate (component of the extracellular matrix) against which they act and degrade, respectively. The MMP group includes collagenases (MMP-1 and MMP-13), stromelysins such as MMP-3, gelatinases such as MMP-2 and MMP-9, and membrane MMPs. This classification based on the substrate of action was particularly useful years ago. With the accumulation of additional knowledge about the enzymatic activity of MMP, the benefit of this classification is questioned, as the substrate profile of the enzyme is more relative than absolute [11].  
TIMPs, consisting of 184-194 amino acids, are inhibitors of MMPs. They are subdivided into an N-terminal and a C-terminal subdomain. Each domain contains three conserved disulfide bonds and the N-terminal domain folds as an independent unit with MMP inhibitory activity. TIMPs inhibit all MMPs tested so far, but TIMP-1 is a poor inhibitor for membrane-type (MT)1-MMP, MT3-MMP, MT5-MMP, and MMP-19 [12].
## 2 Materials and Methods  
### Isolation and Identification of C. Maltaromaticum Probiotic Bacteria  
A probiotic strain of _C. mlataromaticum_ was isolated from water samples collected from the benthic zone of Lake Leginskie (at a depth of 34 m) located in north-eastern Poland (N = 53 deg58'51\" N and E = 21 deg8'4\"). The strain had been isolated during a previous study conducted by the Department of Environmental Microbiology of the University of Warmia and Mazury in Olsztyn.  
The isolate was identified to species level by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF VITEK(r) MS) at the Department of Microbiology, Escuela Nacional de Ciencias Biologicas, Instituto Politecnico Nacional, in Mexico City, Mexico. The identification was additionally verified by 16S rDNA (recombinant DNA) sequencing with the BigDye Terminator v3.1 kit in the ABI 3730 xl genetic analyzer (Applied Biosystems, Foster City, USA). In addition, 16S rDNA genes were sequenced by PCR with the use of 27F (5'-AGAGTTTGATCATTGGCTCAG-3') and 1492R (5'-GGTACC-TTGTTACGACT-3') primers according to the method described by [PERSON] et al. [43]. The BLAST program available on the website of the National Center of Biotechnology Information [44] was used to identify DNA sequences. The results of 16S rDNA sequencing are presented in Table S1 (Supplementary Materials).  
After the identification process, _C. mlataromaticum_ was considered as a probiotic strain based on the hemolysis assay, and its acid and bile tolerance properties, according to the guidelines developed by a joint FAO/WHO working group [45]. The hemolytic activity of _C. mlataromaticum_ was determined on tryptone soya agar (TSA; Oxoid, Basingstoke, UK) with 5% addition of defibrinated sheep blood incubated at 37 degC for 48 h [46]. The bile salt tolerance test of the studied strain was performed in MRS broth culture medium (Sigma - Aldrich, Germany) containing 0.5%, 1.0%, or 2.0% bile salts (Oxoid LP0055) according to the procedure proposed by [PERSON] et al. [47]. The _C. mlataromaticum_ isolate was tested for acid tolerance based on its growth on medium with varying pH (1.5, 2.5, 3.5, and 4.5), as described by [PERSON] et al. [48].  
Determination of the Metabolic Activity of Probiotic Bacteria Based on the Utilization of Different Carbon Sources  
The applicability of the environmental _C. mlataromaticum_ isolate for further analysis was determined by analyzing the bacteria's metabolism based on its utilization of various carbon sources. The biochemical activity of the _C. mlataromaticum_ probiotic isolate and its potential to compete for nutrients with feed microbiota were estimated using the OmniLog(r)System (Biolog, USA). A 96-well plate containing various carbon compounds was inoculated with the evaluated bacterial strain. The plate was incubated, and biochemical parameters were read in a microstation reader. The strain's utilization of different carbon compounds as sources of energy was determined based on the intensity of color reactions.
Appl. Sci._**2015**, 5, 1117-1133; doi:10.3390/app5041117  
_applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
Development of a Fractional Order Chaos Synchronization Dynamic Error Detector for Maximum Power Point Tracking of Photovoltaic Power Systems  
**[PERSON], [PERSON] * and [PERSON]**  
Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan; E-Mails: [EMAIL_ADDRESS] (K.-N.Y.); [EMAIL_ADDRESS] (C.-K.L.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS] or [EMAIL_ADDRESS]; Tel.: +886-04-2392-4505 (ext. 7229); Fax: +886-04-2393-0062.  
Academic Editors: [PERSON] and [PERSON]  
_Received: 6 August 2015 / Accepted: 6 November 2015 / Published: 12 November 2015_  
**Abstract:** In recent years, the photovoltaic (PV) power generation system has been widely discussed and researched. Research on electric energy focuses on the development of Maximum Power Point Tracking (MPPT) technology, and many methods have been proposed. However, these studies have a common defect: the tracking continues near the maximum power point (MPP), so that the waveform of output power jitters, thus causing power loss and rapid wearing of electronic modules. In order to remedy this defect, this paper proposes a new type of fractional order chaos synchronization dynamic error detector for the MPPT design of a PV power system. In this study, the Sprott chaos synchronization dynamic error system was used to control the pulse width duty cycle of PWM and optimize the power oscillation of a PV power system during steady-state response. The simulation and experimental results showed that the voltage detector proposed in this paper can reduce the power oscillation of a PV power system during steady-state response, and increase the overall system efficiency. From the steady-state responses of MPPT, it can be seen that about 0.2 vibration amplitude can be suppressed with control action. Therefore, about 4% of steady-state vibration energy can be saved.  
**Keywords:** photovoltaic; maximum power point tracking; fractional order Sprott chaos system; incremental conductance method
# Hybrid Chirp Signal Design for Improved Long-Range (LoRa) Communications
## 3 Preliminaries  
### LoRa Modulation  
Chirp spread spectrum modulation is used in LoRaWAN to generate the LoRa signal. In LoRa modulation, \(S\) bits are mapped into a LoRa modulated symbol, where \(\mathcal{S}\) is the spreading factor. Hence, we need to create \(2^{\mathcal{S}}\) symbols to accommodate all possible bit combinations. The time-domain LoRa signal for one symbol period can be written as [22]:  
\[x_{k}(t)=\begin{cases}Ae^{j2\pi\left(\left(f_{l}+\frac{kB}{2^{\mathcal{S}}} \right)t+\frac{B^{2}}{2T}\right)}&\text{if $t\leq\tau$}\\ Ae^{j2\pi\left(\left(f_{l}+\frac{kB}{2^{\mathcal{S}}}-B\right)t+\frac{B^{2}}{2T }\right)}&\text{if $t>\tau$}\end{cases} \tag{1}\]  
where \(k\in\{0,2^{\mathcal{S}}-1\}\) is the decimal representation of \(\mathcal{S}\) bits (if \(\mathbf{b}_{k}\) is the bits of the current LoRa symbol to be transmitted, then \(k\) can be defined as \(k=\sum_{i=1}^{\mathcal{S}}\mathbf{b}_{k}(i)\cdot 2^{i-1}\), where \(i\) represents the index of the bits). In (1), \(A\) and \(T\) represent the amplitude and symbol duration of one LoRa signal, respectively. The bandwidth \(B\) of the LoRa signal is defined by \(B=f_{h}-f_{l}\), where \(f_{h}\) and \(f_{l}\) are the maximum and minimum frequencies, respectively. Each LoRa modulated symbol satisfies the time-bandwidth constraint \(BT=2^{\mathcal{S}}\). The time of frequency hopping in one LoRa symbol period \(\tau\) is defined by \(\tau=T-\frac{kT}{2^{\mathcal{S}}}\). The spreading factor establishes a trade-off between the data rate and coverage range. The instantaneous frequency of \(x_{k}(t)\) can be calculated as:  
\[f_{x_{k}}(t)=\begin{cases}f_{l}+\frac{kB}{2^{\mathcal{S}}}+\frac{B}{T}t&\text {if $t\leq\tau$}\\ f_{l}+\frac{kB}{2^{\mathcal{S}}}-B+\frac{B}{T}t&\text{if $t>\tau$}\end{cases} \tag{2}\]  
A simple example of the traditional LoRa modulation scheme is presented in Figure 1 for \(\mathcal{S}=2\), where each \(k\) represents a different bit.
# Railway Lines across the Alps: Analysis of Their Usage through a New Railway Link Cost Function
## 2 The Proposed Cost Function
### Generalized Cost of Rail Links  
As stated in [PERSON] et al. [27], after interviews to experts in the field, monetary costs and travel times are the variables mostly taken into account by carriers and shippers in their transport mode choice. For modelling a multimodal freight transport network, the generalized cost can be determined as follows:  
\[C_{g}=C_{m}+VOT\cdot t \tag{4}\]  
where:  
- \(C_{g}=\) generalized cost (\(\xi\)),  
- \(C_{m}=\) monetary cost (\(\xi\)),  
- \(VOT=\) value of time (\(\xi\)/h),  
- \(t=\) time (h).  
A high variability of \(VOT\) has been observed in the literature. Consequently, in the analysis carried out in this paper, travel times and monetary costs have been considered separately. However, in this paper also generalized costs have been taken into account. The \(VOT\) considered, for the calculation of generalized costs, is 0.96 \(\xi\)/(t-h), proposed by [PERSON] in 2004 [28]. We chose this \(VOT\) as it is an average one, and we think it is the most reliable among those proposed in the literature.  
* _Current scenario_ It involves only Alpine railway lines currently in operation: Ventimiglia line, Frejus line, Sempione line, Lotschberg base tunnel, Gotthard base tunnel, Ceneri line, Luino line, Arlberg line, Brenner line, Tauern line, Tarvisio line, Semmering line, Karavanke line. On the eastern part of the alps (Figure 3): Trieste-Divaca, Koper-Divaca, Rijeka-Divaca, and Rijeka-Zagreb lines.
* _Project scenario_ It involves also Alpine rail lines under construction or planned: the new Frejus base tunnel, the Ceneri base tunnel, the Brenner base tunnel, the new Semmering line (which includes: the 'Koralmbahn', that is the Klagenfurt--Graz new line, the new Semmering base tunnel, and the improvement of the existing lines: Graz--Bruck an der Mur and Bruck an der Mur-Murzzuschlag). The 'project scenario' considers also, on the east part of the Alps (Figure 3): the new lines Trieste--Divaca, Koper-Divaca, and Rijeka-Moravice (part of the Rijeka-Zagreb line). Furthermore, the 'project scenario' considers also, on the north-west part of Italy (near Genoa, Figure 2): the 'Third pass of Giovi' across the Ligurian Apennines. Detailed information, about the railway network model of the European area, shown in Figure 1, is reported in [PERSON] et al. (2020). Herewith, only a focus on rail lines across the Alps is provided.  
Figure 3: Enlargement of Figure 2. Railway lines currently in operation (‘current scenario’) are represented in red, and railway lines across Alpine Passes are represented in light blue; Alpine railway lines under construction or planned (‘project scenario’) are represented in dark blue.
## 7 Effects of Roasting on Lipid Content  
### Hazelnuts  
[PERSON] et al. (2006) examined the lipid profile of hazelnuts subjected to various roasting conditions, including roasting times of 5, 15, and 30 min at temperatures ranging from 125 to 300 \({}^{\circ}\)C. Prior to roasting, the fatty acid profile of raw hazelnuts was determined. Raw hazelnuts exhibited a fatty acid profile comprising 80% oleic acid, 11% linoleic acid, 5% palmitic acid, and 2% stearic acid. Generally, roasting led to an increase in oleic acid and saturated fatty acids, while linoleic acid content tended to decrease. However, an exception was observed at 185 \({}^{\circ}\)C, where a decrease in oleic acid content was accompanied by an increase in saturated and linoleic acid levels, suggesting the potential degradation of oleic acid at this temperature. Raw hazelnuts contained approximately 68% total fat. Roasting at 185 \({}^{\circ}\)C for 15 min slightly increased the total fat content to 70.8%. In raw samples, oleic acid comprised 79.6%, while after roasting at 185 \({}^{\circ}\)C, it decreased to 77.9%. The linoleic acid content increased from 12.7% in raw samples to 13.7% after roasting [86]. [PERSON] et al. (2023) studied the difference in fatty acid composition after roasting at 140 \({}^{\circ}\)C for 30 min in hazelnuts harvested using conventional and organic methods. After roasting, they registered total fatty acids to be at 57% in organic samples and 56% in conventional samples. The oleic acid content was at 84% in organic samples and 85% in conventional samples, and linoleic at 6.8% in organic and 6.9% in conventional. The total saturated fatty acid content was at 8% for organic and 7.3% for conventional harvesting [87]. [PERSON] et al. (2015) investigated hazelnut roasting using a drum roaster oven at 180 \({}^{\circ}\)C for 21 min. They found that roasted hazelnuts contained 83.8% oleic acid among the total fatty acid methyl esters (FAMEs), compared to 82.6% in raw hazelnuts. The linoleic acid content decreased slightly, from 8.7% in raw hazelnuts to 8.0% in roasted hazelnuts. Saturated fatty acids, such as palmitic acid, also showed a slight decrease, from 5.1% in raw samples to 4.8% in roasted samples [88].
# Developing a Fire Monitoring System Based on MQTT, ESP-NOW, and a REM in Industrial Environments
## 5 Performance Results and Evaluation
### Discussion  
The proposed system represents a significant advancement in wireless fire monitoring for large and complex industrial environments. By integrating ESP-NOW, MQTT, and REM, it offers a scalable and resilient solution capable of adapting to the dynamic nature of industrial layouts. This adaptability is critical as it allows the seamless addition of sensors without performance degradation, ensuring consistent coverage and detection accuracy even as facility configurations evolve.  
One of the system's standout features is its use of the REM for optimizing node placement and network configuration. The REM not only maximizes coverage but also minimizes interference, effectively eliminating packet loss across the network. This zero-packet-loss achievement ensures that critical fire detection alerts are consistently relayed in real-time, a capability that is essential in environments where rapid response is crucial to mitigating risks.  
The system's energy efficiency further underscores its practicality. Conventional fire monitoring solutions often face high power consumption challenges due to continuous data transmissions. By leveraging ESP-NOW and MQTT, the proposed system reduces energy expenditure through optimized data relay mechanisms, transmitting only essential updates and utilizing low-power communication modes. This results in prolonged battery life for sensors, reduced maintenance, and significant cost savings, making the system ideal for long-term deployment in energy-sensitive industrial applications.  
Additionally, MQTT's lightweight, reliable architecture enhances the system's ability to handle high message volumes while maintaining low bandwidth usage and resilience against network interruptions. Coupled with REM-optimized node deployment, MQTT ensures minimal delays in data transfer, aligning well with the demands of real-time industrial IoT applications. This combination of ESP-NOW's low-latency communication, REM's optimized node placement, and MQTT's reliable data handling establishes a robust framework for industrial fire monitoring.
# External Field Response and Applications of Metal Coated Hemispherical Janus Particles
## 3 Results and Discussion
### Transmission and Reflection Measurement with a Magnetic Field
The results are shown in Figure 13. Note that a highly controllable manipulation of the particle orientation was realized by applying both the electric and magnetic fields. The electric field defines the axis in the direction parallel to the electric field on the metal surface. Furthermore, the direction can be controlled by rotating around its axis by a magnetic field. Further, it turned out that the particle was rotated when the magnetic field was quickly rotated. It is very important to control the direction of the metal surface in this way when such applications as micromirrors, microshutters, etc. are considered. A micromirror with good controllability can be readily produced by depositing a highly reflective metal on ferromagnetic material that is deposited on the particles. It can also be applied as a minute variable color filter. Surface plasmons can be excited on metal coated hemispherical Janus particles [27], so that the spectrum of the reflected light is varied depending on the incidence angle, because the resonance wavelength is sensitive to the angle [36]. From the fact that the direction of the particles can be precisely controlled by the electric and magnetic fields, as demonstrated here, light can be made incident on the particle at an arbitrary incident angle for the spectrum of the reflected light to be varied. Since the particle can be rotated, it can also be used for the microchannel devices, such as valves and pumps.
## 4 Proposed Methods
### Proposed Superframe Structure
The level of interferences depends on the interferer's power, which is directly proportional to the distance from the interferer devices. Hence, the close proximity of ZigBee and WiFi devices in the overlapping channels from each other increases the interference levels. In order to avoid the interference, we suggest if channel \(CH_{l}\) (for example, ZigBee channel Number 11) is used during the CAP period, then the channel \(CH_{i+4}\) (i.e., ZigBee Channel 15) should be used during the retransmission period. The key features of our proposed superframe structure are that the reserved and unreserved periods are used only for the transmission failure devices to access the channel. Hence, the probability of collision and interference due to WiFi is reduced. The network coordinator is aware of the collision or interference during the CAP period. Hence, it remains active during the retransmission period. Otherwise, it goes for power saving mode. Therefore, the use of our proposed superframe structure reduces the energy consumption, delay and increases the reliability significantly.