dataesr/scientific-paragraphs-categorization huggingface dataset:
Range of Application of Fit model (Range of Data Fitted) Figure  12  (a) shows the range of fitted thermochemical data obtained from NUCLEA database. Clearly it can be seen that fitting covers values of C uz ranging from 0. 8 to 1. 5 and C ox ranging from 0. 3 to 0. 9. This data set is larger than the available experimental data points, thus making the fitting relevant to various inventory compositions found in different nuclear reactors like PWR, BWR, etc. Another illustration, showing the globalness of the fit data can be seen in Fig. 12   In this section we present an algorithm for using the simplified thermochemical model developed in section 3 for fast thermochemical equilibrium calculations. Global data: C uz , C ox , C sz Calculate: m = m ref 1+C ref uz 1+Cuz b = n st o -m Set: N z = 1 N u = C uz N o = 2(C uz + C ox ) N s = C sz N tot = N z + N u + N o + N s n i = N i /N tot (i = o, s) Calculate the fit function f (y): f (y) = y + y 2 + bmn s where: y = 1 2 (n o + mn s -b) Calculate thermochemical equilibrium parameters: Calculations of mass fractions of Uranium and Zirconium in metal phase (X m U , X m z ) by the Salay's correlation and the new simplified model is shown in Fig.
This quick variation happens over a very low moles of iron (N F e ). This can be seen from red dots in Fig. 15. To correctly fit the points spanned by low moles of iron for all high values of C ox = 0. 9 and C uz = 0. 8 -1. 45, Salay's single set of fit parameters can no longer be used. This is evident from the black dashed curve missing the NUCLEA red dotted data of mole fraction of F e in metal, for very low values of moles of iron. A better viable method to address this inconsistency for higher values of C ox is to perform independent curve fittingto find different values of fit parameters best suitable for each case -using the simplified model proposed in this work. This methodology of using different set of fit parameters unique to each case ensures the best fit to NUCLEA data for wide range of values of C uz and C ox , covered in the present study.
This database covers the entire range, from metal to oxide domains. The quaternary system (U, Zr, F e, O) was developed from binary data, later completed by the ternary (U, Zr, O) Chevalier & Fischer (1998); Barrachin et al. (2008). The whole database was recently improved, as explained in Bakardjieva et al. (2014). It is useful to mention the importance of data from the MASCA experiments for the validation of the quaternary system. After the MASCA program, several alternative thermochemical models of the quaternary were proposed in Asmolov et al. (2007); Fukasawa et al. (2005); Fukasawa & Fukasawa.
Figure12(a) shows the range of fitted thermochemical data obtained from NUCLEA database. Clearly it can be seen that fitting covers values of C uz ranging from 0. 8 to 1. 5 and C ox ranging from 0. 3 to 0. 9. This data set is larger than the available experimental data points, thus making the fitting relevant to various inventory compositions found in different nuclear reactors like PWR, BWR, etc. Another illustration, showing the globalness of the fit data can be seen in Fig. 12 (b), which is showing a pseudo-binary form (U -Zr, F e, O) of a full quternary system (U, Zr, F e, O) in a cross-sectional ternary phase diagram. Yet again, it can be seen that the fit data covers broader range than the experimental data.
Acknowledgements This work is funded by the  IRSN  and the HORIZON 2020  IVMR  Project No. 662157. Alderman, O. L. G. , Benmore, C. J. , Weber, J. K. R. , Skinner, L. B. , Tamalonis,  A. J. , Sendelbach ,  S. , Hebden ,  A. ,  & Williamson , M. A. 2018. Corium lavas: Structure and properties of molten  UO2-ZrO2  under meltdown conditions. Scientific Reports, 8(1). Asmolov, V. , Abalin, S. , Degaltsev, Yu. , Strizhov, V. ,  & Shakh , O. 2000. RASPLAV final report: Behaviour of the corium melt pool in LWR lower head with external cooling. Tech. rept. Kurtchatov Institute. Asmolov, V. G. , Zagryazkin, V. N. ,  & Tsurikov , D. F. 2007. The thermodynamics of U-Zr-Fe-O melts. High Temperature, 45(3),  305-312. Bakardjieva, S, Barrachin, M. , Bechta, S, Bezdicka, P, Bottomley, D, Brissonneau, L, Cheynet, B, Dugne, O, Fischer, E.
Accurate determination of plant water status is mandatory to optimize irrigation scheduling and thus maximize yield. Infrared thermography (IRT) can be used as a proxy for detecting stomatal closure as a measure of plant water stress. In this study, an open-source software (Thermal Image Processor (TIPCIP)) that includes image processing techniques such as thermal-visible image segmentation and morphological operations was developed to estimate the crop water stress index (CWSI) in potato crops. Results were compared to the CWSI derived from thermocouples where a high correlation was found (r Pearson = 0. 84). To evaluate the effectiveness of the software, two experiments were implemented. TIPCIP-based canopy temperature was used to estimate CWSI throughout the growing season, in a humid environment.
In addition, there is an additional scaling factor (S x , S y ) (unitless) as a result of the different lenses' FOV and the corresponding sensors' spatial resolution (pixel quantity and size). Such parameters can be calculated a priori using a one-time calibration protocol based on the methodology described in  [13]. Fifty pair of IRT and RGB images acquired with θ ≈ 60 • and d object ≈ 3 m over the potato crop, and including the AWRS in the scene, were utilized for calibration. A MATLAB script was developed to allow the user to manually select correlated control points in both images through visual inspection, and consequently, provide averaged displacement vector and scaling factors (Figure  3 ). The presence of the AWRS in both images serves to locate additional control points due to its higher contrast (see Figure  3 ).
Response Variables In E1, six thermocouples (TT-T-36-SLE, Omega Engineering Inc. , Manchester, UK) with an accuracy greater than 0. 5 • C or 0. 4% (above 0 • C) were attached to each plot into the abaxial surface of the leaf center of target plants using surgical tape  [34]. In both experiments, thermal images were acquired (interdaily from 34 to 82 DAP) and processed according to the methodology described in Section 2. 3. Data from thermocouples and IRT images correspond to the same plots. Canopy temperature data from IRT images were used to estimate the CWSI following the empirical method used for potatoes in  [12] : CWSI = T canopy -T wet T dry -T wet , (5) where T canopy is the measured canopy temperature, T wet is the AWRS measured temperature, and T dry is the artificial dry reference surface estimated temperature.
Accuracy of the Canopy Temperature Estimations The range of values of T canopy recorded by the thermocouples was between 23. 0 and 39. 6 • C. The overall average values of T canopy estimated by the TIPCIP software showed a positive linear relationship with the average T canopy values by thermocouples (r Pearson = 0. 84, p-value < 0. 01) (Figure  4 ). In addition, 87. 0% and 82. 6% of the T canopy values using TIPCIP, corresponding to the T1 and T2 treatments, underestimated T canopy as compared to the thermocouple values, in a range from -2. 05 to -0. 15 and -3. 27 to -0. 61 • C, respectively (Figure  4 ). Furthermore, 60. 9% of T3 treatment values overestimated T canopy as compared to the thermocouple values, in a range of +0. 21 to +3. 80 • C (Figure  4 ). The accuracy of T canopy estimations was better in T1 (r Pearson = 0.
Advantages and Disadvantages of the Developed Software (TIPCIP) Several agricultural analyses based on IRT imagery and image processing did not provide a user-level software; this is because the authors were mainly concerned about validating the physiological meaning of IRT-based treatments  [21, 23, 37]. As a result, similar software packages were implemented but not distributed to the scientific community. In this context, this research not only reveals the various steps involved in canopy identification and temperature calculation using IRT images, but also offers the open-source TIPCIP software to perform those tasks. Hence, TIPCIP allows the user to automatically identify the canopy section in the scene and provides the average temperature, processing up to 50 image pairs (RGB-IRT) in a single run, and reporting formatted (CSV, XLS, among others) results.
Furthermore, as a result of the available access to the source code, a scientific developer could include additional image processing steps to adapt the software to other crops or to the use of NDVI images instead of RGB images, thus increasing the accuracy of the canopy detection. Notwithstanding, TIPCIP is currently limited to working with FLIR-format images for the extraction of raw data as well as calibration parameters. However, a developer could include additional libraries or functions facilitating it to read other formats and increase the current structure of the software. In addition, commercial thermal image processing tools for general purposes can be found on the internet. For example, the FLIR Tool Plus (U. S. $250) enables the user to visualize, edit, and analyze IRT images acquired with FLIR cameras.
However, such analyses are conducted only with thermal images, and consequently, image classification/segmentation is solely performed based on temperature thresholds. A zero-cost programming tool, which is still in development, can be found at https://github. com/micasense/imageprocessing for Micasense cameras. The Altum Micasense multispectral camera includes an IRT sensor and allows the users to generate their code based on the Python programming language. The user requires specific programming skills to interpret the examples but then can construct software and include segmentation as well as generate several vegetation indexes. In sum, TIPCIP provides an option for image processing related to CWSI generation based on FLIR-format images. Its source code allows for modification but requires programming skills in the C++ programming language.
Conclusions The accurate estimation of a plant water stress index via thermal imaging amounts to the need for a simple and efficient image processing algorithm. In this study, the Thermal Image Processor (TIPCIP) software was implemented, and through image segmentation and morphological operations, determined the canopy region and its average temperature. A comparison with in-situ measurements using thermocouples showed that our estimated values of T canopy yield were in good agreement (r Pearson = 0. 84). On the basis of these results, an irrigation schedule was implemented using a CWSI-based threshold, specifically CWSI < 0. 4 and CWSI < 0. 7 for T2 and T3, respectively, in two experiments carried out during the hot and wet season. A water saving without yield penalization was found for T2 (341.
6 ± 63. 7 and 515. 7 ± 37. 7 m 3 ha -1 ) in E1 and E2, respectively. Finally, the authors have made the developed TIPCIP software available under the Creative Commons (CC 4. 0) policy and encourage the agricultural remote sensing community to assess it and provide feedback (the executable files can be downloaded from  [46]  and source code files from  [47] ).
Nevertheless, a mechanical and electronic workshop, even modestly equipped, is often required for construction of purposemade and open-source CE systems. Exception can be found only for the simplest CE setup with syphoning injection in which an operator only needs a ready-to-use high voltage (HV) module, one capillary and different small vials to carry out electrophoretic separations. Nevertheless, this mode of injection which is the least reproducible, together with manual capillary flushing with a plastic syringe is not fully appreciated by users due to a high risk of contamination during operation and from the air  [6]. Construction of more elaborated versions avoiding the syphoning injection normally require some electronic and mechanical skills that are not always available in analytical laboratories with routine operations.
This hinders the wider adoption of in-house built CE instrumentation. With the goal to drastically improve the CE popularity as a simple and affordable approach to the population, we present herein a Lego CE concept to facilitate technology/methodology transfer between different laboratories and eliminate the workshop facility requirement. This design is inspired by the Lego toy concept, in which the users with no mechanical and electronic competences can easily assemble a CE system from different commercially available ready-to-use electrophoretic and microfluidic modules. This new CE instrument was coupled with a laser induced fluorescence (LIF) detector that was also constructed with the Lego design, using off-the-shelf optical, electronic and microfluidic parts. The performance of Lego CE-LIF was evaluated in terms of injection reproducibility and detection sensitivity.
Apparatus and material Method development for establishment of new BGEs for CE-LIF was performed with a Beckman Coulter PA800þ system (Sciex Separation, Brea, CA) coupled with a LIF detector (l excitation : 488 nm, l emission : 520 nm). Instrument control was carried out using Karat 8. 0 software (Sciex Separation). A standalone LED induced fluorescence (LEDIF) detector was purchased from Adelis (Zetalif, Picometrics, Toulouse, France). Data acquisition (for Zetalif or Lego LIF detector) was done with a Mini-corder ER181 data acquisition system (eDAQ Europe, Warszawa, Poland) connected to the USB-port of a personal computer. Polyimide coated fused silica capillaries of 50 mm id and 375 mm od (TSP050375, Polymicro, CM Scientific, Silsden, UK) or UV transparent coated fused silica capillaries of 50 mm id and 375 mm od (TSH050375, CM Scientific, Silsden, UK) were used for all CE experiments.
Deionized water was purified using a Direct-Q3 UV purification system (Millipore, Milford, MA, USA). pH values of buffer solutions and samples were acquired with a SevenCompact pH meter (Mettler Toledo, Schwerzenbach, Switzerland). Selection of BGE compositions and buffer ionic strength (IS) calculations were based on simulations with the computer program PhoeBus (Analis, Suarl ee, Belgium). For Lego CE instrumentation, all fluid connections were made with 0. 02 in. inner diameter (id) and 1/16 in. outer diameter (od) Teflon tubing from Upchurch Scientific (Oak Harbor, WA, USA). The electrophoresis module was based on a dual polarity high voltage power supply with ±30 kV maximum output (HVPS for CZE, Villa Labeco, Slovakia). The high voltage safety cage is a regular Perspex box purchased from Amazon.
Note that any pressure in the range from 0 to 1000 mbar (or from 0 to -800 mbar) can be set and monitored for injection or capillary flushing purposes either with physical knob and a digital screen integrated on the pressure controller or with a computerlinked control program (see Fig. S2 ). In addition, pressure assistance during electrophoresis, which is not trivial in in-house-made CE instruments, can also be applied to accelerate the analysis time or improve the separation resolution, as pressure can be precisely controlled and monitored during application of high voltages (see section below). In in-house made CE instruments [6,9,13,23e27], a desired pressure value sometimes can not be precisely set and monitored. Thus, optimization of hydrodynamic injection in these cases is generally done with injection time variation rather than pressure adjustment.
Both optimization modes (time and pressure) are now available in our Lego CE version. Solutions to be injected in the capillary (i. e. sample, BGE or other generating solutions) can be easily changed by plugging the corresponding vial to the fluiwell or electrowell interface (Fig. S2A  and B in ESI for their setup). In our case with the electrowell (Fig. S2C ), a platinum electrode is already integrated in this interface so a ground connection can be made easily without any further module modification. If the fluiwell interface is used instead on the GND side, a steel tubing commonly used for HPLC can be employed for ground connection. In this case the capillary end is centered and extruded from the GND steel electrode so that they are both in contact with the working solution (Fig. 1 ). For high voltage generation, a commercial module containing a ±30 kV Spellman unit with an integrated digital display was employed, allowing control and monitoring of the voltage and current during electrophoresis.
Lego LIF The detection module is one of the most critical parts of the whole CE instrument. Among all detection types commonly employed for CE, fluorescence detection, or laser-induced fluorescence (LIF) detection in particular, is often used to improve significantly the detection sensitivity, especially for determination of biomolecules such as proteins and peptides. The popularity of fluorescence detection in CE however is often hindered (at least partially) by very high purchase costs of commercial LIF or LEDinduced-fluorescence (LEDIF) detectors. Efforts to produce purpose-made fluorescence detectors adapted to modest budgets and infrastructure were already communicated [29e31], but normally require electronic and mechanical skills and workshop, with 3D-printing facilities in some cases  [29, 31].
For teaching purpose, Thompson et al. introduced a low-cost CE-LEDIF device for testing some fluorophore standards  [32]. As part of the Lego-CE instrument, we developed a new Lego LIF detector. The Lego-LIF design exploits off-the-shelf components commonly used in microfluidics and optics in order to minimize (or eventually eliminate) the need for workshop and skills that are not always available in laboratories with routine analyses. The schematic design of Lego LIF detector is demonstrated in Fig. 2  whereas a photo of the system can be seen in Fig. S3  in ESI. A miniature LIF module from Integrated Optics, powered with a USB cable from a personal computer, was used for the first time in CE-LIF to provide the excitation wavelength of 488 nm which is most commonly used for fluorescence detection of biomolecules.
All these optical, microfluidic and electronic components are ready-to-use modules and can be plugged together using the adaptors provided by the suppliers. Users can choose different laser/LED types for the light source from various suppliers, depending on the budget available and the target applications. In our particular case where cost-effectiveness and miniaturization are the two most important criteria, a miniature USB-powered high-performing laser module was chosen. The overall cost for such Lego LIF detector was estimated to be 5000 euros, which is much cheaper (less than 25%) than the purchase cost of a commercial fluorescence detector for CE.
Performance evaluation To evaluate the injection function of the new Lego CE, a series of tests were implemented with injection of a standard FITC solution at different pressures and injection times conventionally used in commercial CE systems. The reproducibility data for peak areas obtained at different injection pressures and times are shown in Table  1. Good injection reproducibility was achieved at any injection pressure and time, except for the case of 30 mbar over 5 s. The poorest reproducibility under this condition could be probably due to the too short time for pressure manipulation at a relatively low pressure range. The reproducibility for migration time was excellent (RSD % < 0. 5%) under a delivery pressure of 400 mbar, proving again the added value of this system, exhibiting precise pressurization.
For evaluation of detection signals, the performance of Lego LIF detector was compared to that of a commercial LEDIF detector, using the same separation capillary and CE conditions. Electropherograms for analysis of FITC at 110 nM that were obtained with both detectors are shown in Fig. 3 , whereas comparison data are presented in Table  2. Very good linearity (R 2 better than 0. 997) was acquired, whether the calibrations were made with peak areas or peak heights, proving a very good response of the Lego LIF to the variation of FITC concentrations. The detection sensitivity was approximately 10 times better for the commercial LEDIF (see Table  2 ). This can be explained by the fact that no focusing lens or special optical setups were employed for the Lego LIF as otherwise required for a costly commercial fluorescence detector.
6C ). Note that the unit displayed for LIF signals in Fig. 5  was RFU as the electropherograms were obtained with a LIF detector from Sciex, whereas that in Figs. 3  and 6  was in a mV scale as the signals were converted with an external data acquisition module. With this demonstration, we expect to open a door for various applications exploiting both hydrodynamic and electrokinetic principles with Lego CE-LIF. We also provide here a tool that could be tuned to get it adapted for any kind of prospective glycan analysis. Indeed by playing on voltages and pressures we would achieve the best separation performances whatever the kind of glycans to be analyzed (i. e. N-or O-glycans, smaller or longer ones or even a mixture of these types).
Conclusions We successfully developed a new Lego CE-LIF instrument that can be constructed from off-the-shelf modules. Recourse to mechanical and electronic workshops can therefore be avoided. A high degree of standardization with an affordable construction cost can be achieved with this Lego CE-LIF design. The Lego design would allow the users to setup their own analytical devices at a cost at least 70% cheaper than the purchase price of a commercial system while keeping a high degree of standardization (i. e. a 'standard' setup) and facilitation of technology transfer that are not offered by in-house-made versions. This design was demonstrated for separation of fluorescently labelled oligosaccharides that serve as a reference for glycoprotein-derived glycan analysis. We also successfully developed a new BGE based on large weakly charged and zwitterionic molecules at very high concentrations for such analyses.
Nationale de la Recherche (ANR, France) with the grant no. ANR-18-CE29-0005-01. The VNU Key Laboratory of Analytical Technology for Environmental Quality and Food Safety Control (KLATEFOS) is also acknowledged for some instrumental support. We thank Dr. Thuy Tran-Maignan and Ms. Bin Yang (Institut Galien Paris Sud) for useful discussions and their help in sample preparation, as well as Mr. Jean-Jacques Vachon (Institut Galien Paris Sud) for his help in instrumental setup.
These optimizations consist of some data packing dedicated to the Paillier cryptosystem and the use of multi-exponentiation algorithm to reduce the cost of multiplications. • The empirical results show that our protocol can compute the prediction within a neural network with two activation layers in 10 seconds with 1. 73 MB bandwidth usage which is 30-fold better in computation cost than the HE-based solution and 28-fold more efficient in bandwidth usage than the 2PC-based solution.
Optimizing Computations In our implementation, we use several optimization techniques which help reduce the computation and communication cost by enabling simultaneous execution. To optimize 2PC operations, we use single instruction multiple data (SIMD) techniques  [Smart and Vercauteren, 2014]. SIMD techniques cannot be fully utilized for the computations with the Paillier cryptosystem. Therefore, to improve the efficiency in HE, we adapt two techniques to Paillier which enables simultaneous computation. We first use data packing  [Bianchi et al. , 2010] : It packs multiple data items into a single ciphertext. Accordingly, we create slots of t + κ bits for each data item where κ is the security parameter and t is the length of the data item. Given the plaintext modulus N, we can pack ρ = log 2 N t+κ items in a single ciphertext as in (2).