esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
The determination of the contamination grade by pesticide residues in cereals and legumes coming from Italy and foreign countries in the years 2018-2019 was performed through the QuEChERs procedure coupled to GC-MS/MS. The multi-residue pesticide determination allowed to perform high throughput analysis, providing reliable results and quick turnaround of data. The results of method validation demonstrated the conformity of the analytical method with provisions of the European directives for pesticide analysis in monitoring programs, along the food production chain. The evaluation of the contamination grade performed on more than 200 cereal and legume samples highlighted the presence of pesticide residues in the grain samples (with a contamination percentage of 7%), although below the maximum residue levels, while no pesticide was found in the analyzed legumes. PYRs (cyfluthrin, deltamethrin, phenothrin, cypermethrin, and fenvalerate) and OPPs (chlorpyrifos and pirimiphos-methyl) were the most found pesticides in cereal samples (in 18 samples on a total of 209); pirimiphos-methyl was the only residue found not only in wheat samples but also in bran and oats. In terms of risk assessment, pirimiphos-methyl was the pesticide associated with the highest levels of exposure deriving from the consumption of pasta, bread, and breakfast cereals. However, the percentages of exposure are very low, even if evaluated under the highest exposure scenario.  
The following are available online at [[https://www.mdpi.com/article/10.3390/app11167283/s1](https://www.mdpi.com/article/10.3390/app11167283/s1)]([https://www.mdpi.com/article/10.3390/app11167283/s1](https://www.mdpi.com/article/10.3390/app11167283/s1)), Table S1: Risk exposure by pesticide residues of pirimiphos-methyl, cypermethrin, cyfluthrin, deltamethrin, fenvalerate, and phenothrin in pasta under high exposure scenario, Table S2: Risk exposure by pesticide residues of pirimiphos-methyl and chlorpyrifos in bread under high exposure scenario, Table S3: Risk exposure by pesticide residues of pirimiphos-methyl in breakfast cereals under high exposure scenario.  
Conceptualization, V.N. and M.Q.; Data curation, M.I. ([PERSON]) and D.N.; Formal analysis, M.I. ([PERSON]) and F.C.; Funding acquisition, V.N.; Investigation, V.D., M.I. ([PERSON]), I.D.R. and F.C.; Methodology, V.D., M.I. ([PERSON]), I.D.R. and M.I. ([PERSON]); Project administration, V.N.; Resources, V.N.; Supervision, D.L. and M.Q.; Validation, A.C.; Writing--original draft, D.N.; Writing--review & editing, M.Q. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Ministero della Salute (Rome, Italy), who financed the pro-ject IZS PB 08/20 RC.  
Not applicable.  
Data available on request.  
Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata (Foggia, Italy) is thanked for providing research support.  
The authors declare no conflict of interest.
# Toward Long-Term Implantable Glucose Biosensors for Clinical Use
## 3 Continuous Glucose Monitoring Systems
### Semi-Implantable CGMS with Electrochemical Sensors  
In virtue of advancements in CGMS over the past decades, CGMSs are commercially available and even replace SMBG for clinical decision (Table 2). The first FDA-approved sensor for CGM was the Minimed Continuous Glucose Monitoring System, which was composed of the needle-type implantable sensor, the transmitter connected to the sensor, and the monitor to display. The sensor was implanted under the skin of abdomen or forearm and the measured data was sent to the monitor through the attached transmitter. The first CGM sensors required calibration at least four times a day. Although the composition of CGMS has not changed significantly, the current CGMSs (Dexcom G6(r) and Abbott FreeStyle Libre) do not require calibration anymore. Since revolutionary change in CGMS is due to advance in sensor manufacturing, Dexcom G6(r) and Abbott FreeStyle Libre do not need in vivo calibration, thus reaching zero-finger pricing glucose monitoring [41]. As a result, diabetic patients can now relieve from painful, daily, routine finger-pricking calibration. The zero finger-pricking glucose monitoring dramatically increases qualify of lives of diabetic patients. The other revolution in CGMS is that CGMS can replace standard home glucose monitoring devices to decide diabetic treatment. FDA limited CGM sensors as aid in the detection of episodes of hypo-and hyperglycemia, not replacing devices of standard home glucose monitoring devices. However, since Dexcom G5(r) has received the FDA approval to replace SMBG in 2016, Dexcom G6 and Abbott FreeStyle Libre now also can replace SMBG. Furthermore, the FDA classifies the new class of CGMS with implantable sensors as integrated continuous glucose monitoring system (iCGM) in \"moderate-risk\" class II in 2018 (Table 2) [42]. Considering that FDA classified the CGM sensors as \"Sensor, Glucose, Invasive\" in class III, such regulation change can accelerate advancement of commercial CGMS. The iCGM does not need to pass the most rigorous review for the \"highest risk\" medical devices anymore and now hasan opportunity to reduce the regulatory burden. If any CGMS can meet the accuracy criteria of iCGM, the CGMS can transmit glucose monitoring data to digitally connected devices, including automated insulin dosing systems and any other medical devices for managing diseases or blood-glucose.
# Internet Video Delivery Improved by Super-Resolution with GAN
## 2 Background and Related Work
### JND-Based Video Quality Assessment  
The JND is the difference between two signals at the threshold of detectability[45]. It is applied to understand the sensitivity of the human visual system. In [46], the author introduced the JND concept as a metric for measuring video quality. In [47], the author proposes an interactive JND-based method to establish the encoding bitrate of consecutive video representation, which makes encoding distortions noticeable to the human eye. A dataset of encoded videos using this method was created and presented by [48]. This dataset includes 220 videos with four resolutions and 52 encoding representations. By applying the JND methodology, three JND points per resolution were defined, showing the inefficiency of video encoding in the 52 range.  
In [49], the authors presented a metric called LPIPS, which measures the perceptual distance between two images. The extraction of features uses a deep neural network and defines the LPIPS values. The authors compared the LPIPS and JND outcomes to conclude that there is a strong correlation between the extracted features and the artifacts that catch the attention of the human visual system.  
In this work, we use the dataset presented in [48] to conduct experimental studies. Moreover, a novel method is presented based on the LPIPS metric mapping JND points of super-resolved videos.
## 3 Results and Discussion
The parameters derived from the fitting of the experimental creep data according to [PERSON]'s model are summarized in Table 4, together with the corresponding adjusted R-squared (_adj_\(R^{2}\)) values. As can be also noticed by examining the fitting of the creep compliance curves in Figure 7, the [PERSON] model effectively captured the creep behavior of the prepared samples, displaying _adj_\(R^{2}\) values higher than 0.995 for all the formulations. Moreover, the incorporation of MWCNTs and M6D led to a considerable decrease in both the \(D_{el}\) term \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **Modulus Chord (MPa)** & **Stress at Break (MPa)** & \
\begin{tabular}{c} **Strain at Break** \\ **(mm/mm)** \\ \end{tabular} &
\begin{tabular}{c} **Specific Energy at** \\ **Break (J/mm\({}^{2}\))** \\ \end{tabular} \\ \hline TPU & \(6.3\pm 0.4\) & \(9.1\pm 0.9\) & \(7.1\pm 0.5\) & \(0.90\pm 1.35\) \\ TPU\_0.5 MWCNT & \(7.8\pm 0.7\) & \(8.3\pm 1.1\) & \(6.1\pm 1.1\) & \(0.91\pm 1.77\) \\ TPU\_1 MWCNT & \(7.9\pm 0.5\) & \(7.6\pm 0.7\) & \(4.8\pm 0.3\) & \(0.62\pm 0.86\) \\ TPU\_30M6D\_0.5 MWCNT & \(10.5\pm 1.0\) & \(5.2\pm 1.7\) & \(2.2\pm 0.5\) & \(0.29\pm 0.28\) \\ TPU\_30M6D\_1 MWCNT & \(10.9\pm 0.4\) & \(5.3\pm 0.3\) & \(0.8\pm 0.1\) & \(0.08\pm 0.12\) \\ TPU\_40M6D\_0.5 MWCNT & \(12.3\pm 0.8\) & \(4.9\pm 0.4\) & \(0.6\pm 0.1\) & \(0.05\pm 0.09\) \\ TPU\_40M6D\_1 MWCNT & \(12.7\pm 0.1\) & \(3.8\pm 0.3\) & \(0.3\pm 0.1\) & \(0.01\pm 0.06\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Overview of Key Mechanical Properties for 3D-Printed TPU/MWCNT/PCM Composites: Modulus, Chord Stress at Break, Strain at Break, and Specific Energy at Break. Figure 7: Creep compliance curves of 3D-printed samples, together with the fitting according to [PERSON]’s model (dotted lines (see Equation (2))). and the \(k\) coefficient, the latter being associated with the retardation of strain within the macromolecular structure [44]. The extent of this decrease is proportional to the nanofiller and microcapsule amounts. Also, the coefficient n, which represents the kinetics of the macromolecular flow during the creep process [45], experienced a reduction of about 30% with respect to neat TPU.
###### Abstract  
Silicon photonics (SiPh) are considered a promising technology for increasing interconnect speed and capacity while decreasing power consumption. Mode division multiplexing (MDM) enables signals to be transmitted in different orthogonal modes in a single waveguide core. Wideband MDM components simultaneously supporting wavelength division multiplexing (WDM) and orthogonal frequency-division multiplexing (OFDM) can significantly increase the transmission capacity for optical interconnects. In this work, we propose, fabricate and demonstrate a wideband and channel switchable MDM optical power divider on an SOI platform, supporting single, dual and triple modes. The switchable MDM power divider consists of two parts. The first part is a cascaded Mach-Zehnder interferometer (MZI) for switching the data from their original TE\({}_{0}\), TE\({}_{1}\) and TE\({}_{2}\) modes to different modes among themselves. After the target modes are identified, mode up-conversion and Y-branch are utilized in the second part for the MDM power division. Here, 48 WDM wavelength channels carrying OFDM data are successfully switched and power divided. An aggregated capacity of 7.682 Tbit/s is achieved, satisfying the pre-forward error correction (pre-FEC) threshold (bit-error-rate, BER = \(3.8\times 10^{-3}\)). Although up to three MDM modes are presented in the proof-of-concept demonstration here, the proposed scheme can be scaled to higher order modes operation.  
silicon photonics (SiPh); mode division multiplexing (MDM); orthogonal frequency-division multiplexing (OFDM); optical interconnect +
Footnote †: journal: Sensors **2023**, 23, 711. [[https://doi.org/10.3390/s23020711](https://doi.org/10.3390/s23020711)]([https://doi.org/10.3390/s23020711](https://doi.org/10.3390/s23020711))
# Remote Low-Cost Differential Isolated Probe for Voltage Measurements
###### Abstract  
The growing development of communication technologies has given rise to the Internet of Things, which has led to the emergence of new cities, smart grids, and smart buildings, and the development of energy generation using renewable sources, as well as the emergence of new electrical loads such as the electric car. These advances give rise to the need for new media devices with remote communication, and require a greater control and monitoring of the state of the electrical grid in order to verify its correct state, as well as the detection of faults or alterations that are occurring in it due to these new generation systems or new loads. These remote, unsupervised measurement devices require galvanic isolation to protect the measurement and communication system, so that even if there is a break in the isolation, the integrity of the measurement and communication system is maintained. In addition, as it is a device prepared for multipoint measurement, the cost of the probe must be contained. This article details the design, implementation, and validation of a low-cost remote isolated differential voltage probe. This probe is intended for monitoring at network supply points, as well as for the verification of the European standard EN 50160 as a means of detecting disturbances in network behaviour. Its characteristics as a differential and isolated probe provide it with the possibility of floating voltage averaging, guaranteeing the integrity of the electronics of the low-voltage probe, i.e., the digitalisation and communication system. The measurements collected are sent via an MQTT protocol, which makes the remote probe a device compatible with the Internet of Energy. For the validation of the probe, a full functional test is performed, including FFT spectral analysis to verify the compliance of the mains voltage with the aforementioned European standard EN 50160.  
active probes; isolated probes; instrumentation; voltage measurement; Internet of Energy
# Dynamic Information Flow Tracking: Taxonomy, Challenges, and Opportunities
## 6 Discussion and Prospect
### Overtaint on DIFT  
The problem of overtaint refers to the tag polluting other data when the tag is propagating at runtime without being restricted. Furthermore, it is the main cause of high false positive rates. For example, the tag is propagated to the general purpose register through ALU instructions. The data in the memory location are also tagged when executing memory instructions, e.g., store operations. Similarly, the data in the general purpose register are also polluted by tagged data from memory. In this case, the benign data are also tagged once they are involved in DIFT operations. As a result, the exception is raised even if there are no actual attacks or security risks. Even worse, multiple processors' data in CMPs platform are polluted because they share the same data sources, e.g., memory or a cache data page.  
A better solution to this problem is to restrict the valid region for a tag. The authors in [18] used a watchdog timer to ensure that the control flow is bounded between trusted entities and untrusted entities. However, this type of design is not suitable for tag-based systems because you cannot make sure the exact time bounds for different system events, e.g., system calls, exception handling and memory access. The target program needs to be analyzed and be divided into entities of different granularities, e.g., task, function, basic block and variable. Furthermore, different tags are assigned to different entities to indicate their granularity. In addition to recording the entity type, the tag also needs to record the data source, e.g., using a unique identifier in a limited scope to represent a different source. The tag design also needs to be combined with the actual software context. For example, the security-critical function is treated especially and using a special tag.
## 4 Conclusions  
Fundamental studies on the (thermal) inactivation mechanisms of RF require the use of lab-scale setups that are more easily controllable than the various (expensive) commercially available RF setups. Therefore, in this study, a lab-scale low-power free-running RF oscillator was developed specifically with this goal in mind. The setup was calibrated to treat two typical microbiological growth media (i.e., TSB and BHI) within a predefined frequency range of 27.12 \(\pm\) 0.50 MHz. Using fairly low power levels of 12-13 W and small volumes of 3 mL, temperatures above 60 \({}^{\circ}\)C were reached within treatments times relevant for microbiological inactivation experiments (approximately 10 min). Thermal treatments were repeatable among different replicates, and the influence of the presence of bacterial cells (i.e., _S. Typhimurium_ and _L. monocytogenes_, for TSB and BHI, respectively) on the operating parameters was insignificant. The microbial inactivation potential of the setup was validated, illustrating its potential use in more fundamental microbiological studies on RF inactivation in the future. In such studies, the treatment parameters can be further calibrated to comply with specific research goals by, e.g., constructing more complex temperature profiles as a function of the input voltage and/or narrowing the target frequency range. While only two medium-microorganism combinations were tested in this study, the developed setup can also be used to treat other liquid products containing different microorganisms, although a recalibration may be required for each product to obtain the desired frequency. Barring a more elaborate recalibration, the setup can in future studies also be adopted to treat more complexly structured products of different origins (e.g., dairy, meat, fish, vegetables), including semi-solid and solid products and powders.  
Conceptualisation, D.S.K., D.V., S.A. and J.F.M.V.I.; methodology, D.S.K., D.V and S.A.; software, D.V.; validation, D.S.K., M.T., P.C., J.E., D.V. and S.A.; formal analysis, D.S.K., M.T., P.C., D.V.; investigation, D.S.K., M.T., P.C. and J.E.; resources, J.F.M.V.I.; data curation, D.V.; writing--original draft preparation, D.S.K., D.V. and S.A.; writing--review and editing, D.S.K., M.T., P.C., J.E., V.S.T., D.V., S.A. and J.F.M.V.I; visualisation, D.S.K. and D.V.; supervision, J.F.M.V.I.; project administration, V.S.T., D.V. and J.F.M.V.I; funding acquisition, D.S.K., D.V., S.A. and J.F.M.V.I. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the KU Leuven Research Fund through project C24/18/046, by the Research Foundation Flanders (FWO) through project G0B4121N, and by the EU H2020 research and innovation program under the [PERSON] grant agreement no. 956126. Authors [PERSON] and [PERSON] were funded by the Research Foundation Flanders (FWO), grant numbers 1254421N and 1224620N, respectively.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
## 7 Results and Discussion
### Evaluation Metrics
#### 7.1.3 Packet Delivery Ratio  
The packet delivery ratio is the proportion of received data packets, \(\mathit{Pkt}_{(recited)}\), by a base station to the sum of sent data packets \(\mathit{Pkt}_{(send)}\). Equation (28) shows a numerical form of the packet delivery ratio.  
\[\mathit{Pkt}_{(DR)}=\frac{\mathit{Pkt}_{(received)}}{\mathit{Pkt}_{(send)}} \times 100. \tag{28}\]
## Materials and Methods
### NRPS and PKS Gene Screening  
Identified bacterial isolates were further screened for the presence of biosynthetic gene clusters of nonribosomal peptide synthetases (NRPS) and type-I polykeletides synthases (PKS-I). The oligonucleotide primer set NRPS-IF (5\({}^{\prime}\)-GCSTACSYSATSTACACSTSCSG-3) and NRPS-1R (5\({}^{\prime}\)-SASGTCVCCSGTSCGGTAS-3\({}^{\prime}\)) (Eurofins Genomics, Ebersberg, Germany) was used to amplify partially the adenylation (A) domain (approximately 750-800 bp) and the primer set PKS-IF (5\({}^{\prime}\)-GTGCCCGSTNCCRTGNSYTTC-3\({}^{\prime}\)) and PKS-IR (5\({}^{\prime}\)-CGATGGAYCCNCARKYG-3\({}^{\prime}\)) (Eurofins Genomics, Ebersberg, Germany) for the amplification of partially KS domain (approximately 600-750 bp) [32]. PCR reactions were carried out in 50 \(\mu\)L final volume, using Primas 25 thermal cycler (PEQLAB Biotechnology, Erlangen, Germany). The reaction mixture for NRPS A domain contained 1.5 U FastGene Taq DNA Polymerase (NIPPON Genetics, Tokyo, Japan), 1\(\times\) PCR buffer B, 25 pmol of each primer, 1 mM dNTPs and 5 \(\mu\)L DNA template. The amplification conditions were the following: initialization at 95 \({}^{\circ}\)C for 3 min, followed by 35 cycles of denaturation at 95 \({}^{\circ}\)C for 30 s, annealing at 59 \({}^{\circ}\)C for 2 min and elongation at 72 \({}^{\circ}\)C for 4 min with a final elongation step at 72 \({}^{\circ}\)C for 1 min. For the KS domain the reaction mixture contained 1 U Taq DNA Polymerase (Invitrogen, UK), 1\(\times\) PCR buffer, 25 pmol of each primer, 1 mM dNTPs, 1.5 mM MgCl\({}_{2}\), and 5 \(\mu\)L DNA template. The initialization at 94 \({}^{\circ}\)C for 3 min was followed by 40 cycles of denaturation at 94 \({}^{\circ}\)C for 30 s, annealing at 60 \({}^{\circ}\)C for 1 min and elongation at 72 \({}^{\circ}\)C for 30 s. The final elongation step was performed at 72 \({}^{\circ}\)C for 5 min. Sequencing was performed via Sanger dideoxy termination method by CeMIA SA (Larissa, Greece). Sequencing data were subjected to a BLASTN ([[https://blast.ncbi.nlm.nih.gov/Blast.cgi](https://blast.ncbi.nlm.nih.gov/Blast.cgi)]([https://blast.ncbi.nlm.nih.gov/Blast.cgi](https://blast.ncbi.nlm.nih.gov/Blast.cgi)), BLAST, NIH) (accessed on 21 June 2021) search and to BLASTX (E value: 1 \(\times\) 10\({}^{-5}\)) in order to identify the closest known homologues and determine the level of homology of the amino acid sequence.
## 4 Model Calibration and Square Lattice Surrogate Models
### Relating the Diffusivities
#### 4.3.2 Multisize Obstacles Model  
Considering the horizontal and vertical effective diffusivities independently, and using (2) with \(d=1\), we can define \(\kappa_{H}\) and \(\kappa_{V}\) as  
\[\kappa_{H}=\frac{\langle r_{H}^{2}\rangle}{2N\Delta t},\;\;\;\kappa_{V}=\frac{ \langle r_{V}^{2}\rangle}{2N\Delta t}, \tag{35}\]  
where \(\langle r_{H}^{2}\rangle\) and \(\langle r_{V}^{2}\rangle\) are the horizontal and vertical mean squared displacements. In the multisize obstacles model, we identified horizontal and vertical components of diffusivity in terms of the corresponding probabilities (see (31)).  
In contrast to the equally spaced obstacles model, here we do not directly identify the probabilities \(q_{x}\) (of a horizontal transition) and \(q_{y}\) (of a vertical transition) in the square lattice surrogate model. In particular, \(q_{x}\) is not explicitly identified from our simulations, since our results delineate (1) a horizontal transition in the original RVE and (2) a horizontal transition to the extended domain. We, instead, relate the following ratios:  
\[\frac{D_{H}}{D_{V}}\approx\frac{\kappa_{H}}{\kappa_{V}}\approx\frac{\langle r _{H}^{2}\rangle}{\langle r_{V}^{2}\rangle}\approx\frac{q_{x}}{q_{y}}. \tag{36}\]  
Note that in the case where all obstacles are the same size, this yields \(D_{H}\approx D_{V}\).  
For the lattice-based surrogate model, the four probabilities \(p_{1},p_{2}\), \(p_{3}\), \(p_{4}\) correspond to the transitions depicted in Figure 5b. Recall that \(q_{1}+q_{x}+q_{y}=1\) in the square lattice surrogate model and \(p_{1}+2p_{2}+p_{3}+p_{4}=1\) in the lattice-based surrogate model. Equating these two relations and assuming that \(q_{1}=p_{1}\) and that \(2p_{2}=q_{y}\), we obtain the reduced equation  
\[q_{x}=p_{3}+p_{4}. \tag{37}\]  
Assuming \(\kappa_{H}\approx D_{H}\) and \(\kappa_{V}\approx D_{V}\), we can use simulation results to calibrate \(\Delta x\) using each of the two relations in (31) (see Section 5.2.2). Moreover, we note that the ratio of diffusivities in (36) is independent of the square lattice grid size.
# Improved Likelihood Probability in MIMO Systems Using One-Bit ADCs
## 1 Introduction
Previous studies have addressed the challenges posed by one-bit ADCs by employing complex machine learning-based algorithms, such as supervised learning and reinforcement learning. However, to reduce the inherent complexity associated with machine learning algorithms, this study focuses on improving likelihood probability for low-complexity data detection. The remainder of this study is organized as follows. Section 1 describes the frame structure and the MIMO receiver using one-bit ADCs. Section 2 presents the estimated likelihood probability using the detected data symbols and an optimization problem that minimizes the MSE between the true- and estimated-likelihood probabilities. Section 3 explains the proposed method for solving the optimization problems. Section 4 presents the simulation results obtained using the proposed method. Finally, the conclusions are presented in Section 5.