Miracle-dz/UniFAR-FTUs huggingface dataset:
Fully Implicit Dynamic Pore‐Network Modeling of Two‐Phase Flow and Phase Change in Porous Media

Dynamic pore‐network model (PNM) has been widely used to model pore‐scale two‐phase flow. Numerical algorithms commonly used for dynamic PNM including IMPES (implicit pressure explicit saturation) and IMP‐SIMS (implicit pressure semi‐implicit saturation) can be numerically unstable or inaccurate for challenging flow regimes such as low capillary number (Ca) flow and unfavorable displacements. We perform comprehensive analyses of IMPES and IMP‐SIMS for a wide range of flow regimes under drainage conditions and develop a novel fully implicit (FI) algorithm to address their limitations. Our simulations show the following: (1) While IMPES was reported to be numerically unstable for low Ca flow, using a smoothed local pore‐body capillary pressure curve appears to produce stable simulations. (2) Due to an approximation for the capillary driving force, IMP‐SIMS can deviate from quasi‐static solutions at equilibrium states especially in heterogeneous networks. (3) Both IMPES and IMP‐SIMS introduce mass conservation errors. The errors are small for networks with cubic pore bodies (less than 1.4% for IMPES and 1.2% for IMP‐SIMS). They become much greater for networks with square‐tube pore bodies (up to 45% for IMPES and 46% for IMP‐SIMS). Conversely, the new FI algorithm is numerically stable and mass conservative regardless of the flow regimes and pore geometries. It also precisely recovers the quasi‐static solutions at equilibrium states. The FI framework has been extended to include compressible two‐phase flow, multicomponent transport, and phase change dynamics. Example simulations of two‐phase displacements accounting for phase change show that evaporation and condensation can suppress fingering patterns generated during invasion.
THE MEDIATING ROLE OF MOTIVATION BETWEEN REMUNERATION AND PERFORMANCE

Purpose- This research aims to examine the remuneration effect on performance using motivation as the mediating variable. Design/methodology/approach- The population of the research is all educational staff who work in one of public education institutions in Malang which have been applied remuneration system. Sample selection was conducted through a stratified random sampling technique. This study used a structured questionnaire to collect data and Pearson correlation and regression models were used to analyze data. Findings- The results showed that remuneration had a significant effect on motivation and employee performance, and there was a significant effect of motivation in mediating the remuneration effect on employee performance. This study recommends the need for more attention to motivation because of its essential role in improving employee performance Implication- The significant motivation role in improving employee performance is expected to be a concern for leaders to encourage employees in carrying out and completing their work rather than merely focused on remuneration itself. The goal is not only for individual purposes but also for the benefit of the organization. Limitation- This research uses a case study approach so that it only takes the perception of the remuneration implementation which occurs in one place. Future research should be able to expand sampling in order to generalize the results.
ESR Spectra of Charge Carriers in the α'- and β- Phases of (BEDT-TTF)2IBr2 Single Crystals

High-frequency dynamic magnetic properties of quasi-two-dimensional organic conductors (BEDT-TTF)2IBr2 of α'- and β-phases have been studied by Electron Spin Resonance (ESR) spectroscopy. The heating of crystals in the α'-phase is accompanied by their phase transition to the β-phase, so, the Dyson distortion of the ESR line is appeared. Contributions from the crystal field and symmetry of the system as well as the orbital magnetic moment admixture to the total magnetic moment of charge carriers have been judged by the comparison of the orientation and temperature dependencies of the ESR spectra for the α'- and β-phases. Experimental data have proved localized states of charge carriers either in α'- or β-phases.
Predictive Analysis of Machine Learning Schemes in Forecasting Offshore Wind Speed

High variability of wind in the farm areas causes a drastic instability in the energy markets. Therefore, precise forecast of wind speed plays a key role in the optimal prediction of offshore wind power. In this study, we apply two deep learning models, i.e. Long Short-Term Memory (LSTM) and Nonlinear Autoregressive EXogenous input (NARX), for predicting wind speed over long-range of dependencies. We use a four-month-long wind speed/direction, air temperature, and atmospheric pressure time series (all recorded at 10 m height) from a meteorological mast (Vigra station) in the close vicinity of the Havsul-I offshore area near Ålesund, Norway. While both predictive methods could efficiently predict the wind speed, the LSTM with update generally outperforms the NARX. The NARX suffers from vanishing gradient issue and its performance declines by abrupt variability inherited in the input data during training phase. It is observed that this sensitivity will significantly decrease by integrating, for example, the wind direction at low frequencies in the learning process. Generally, the results showed that the predictive models are robust and accurate in short-term and somewhat long-term forecasting of wind.
A novel method of adrenaline concentration detection using fiber optical biosensor based on the catalysis of iron(II) phthalocyanine

As an effective alternative to the nature enzyme, metallophthalocyanine (MPc), having the advantages of easy accessibility, good stability and low cost, are used as catalyzer for the adrenaline (AD) oxidation. In this paper, the oxidation of AD by dioxygen using iron(II) phthalocyanine (FePc) as the catalyst was studied by electronic absorption spectra. The experimental results indicate that the oxidation product of AD catalyzed by FePc is adrenochrome with characteristic peaks at 298 nm and 267 nm. The catalytic activities of FePc are evaluated by the ratios of the absorbance at 298 nm of adrenochrome. The optimal concentration, pH and temperature for the oxidation of AD are 5.0×10-5 M, 8.0 and 55 oC, respectively. By using lock-in technology, the fiber optic adrenaline biosensor based on FePc catalysis and fluorescence quenching was fabricated and studied. A linear relationship between φ, the phase delay of the sensor head, and AD concentration was observed in the range of 2.0×10-6 to 9.0×10-6 M and 2.0×10-5 to 9.0×10-5 M. The standard deviation (SD) values are 4.7×10-8 (n = 5) and 5.9×10-7 (n = 5) M, respectively, while the detection limit is 4.0×10-7 M. The biosensor has the response time of about 15 min and the preferred reproducibility and stability.
Connectedness percolation in athermal mixtures of flexible and rigid macromolecules: Analytic theory

A semianalytic theory is developed for calculating percolation thresholds for rod-like nanoparticles dispersed in a flexible polymeric matrix. Methods of macromolecular integral equation theory are combined with the connectedness Ornstein–Zernike equation and an explicitly two-component model in which both the molecules constituting the matrix as well as the filler species are accounted for. The effects on the percolation threshold of explicitly including the matrix species are examined and compared with predictions based on an analogous approach which restricts attention to the rod–rod second virial coefficient. Explicit inclusion of the polymeric matrix does not alter the qualitative dependence of the percolation threshold on rod aspect ratio. However, accounting for the matrix leads to a quantitative reduction of the critical volume fraction by a factor independent of the rod length. Although the present work focuses on the athermal situation (excluded volume interactions alone), the methodology develo.
Validation of Novel Completely Sealed Nasal Positive Airway Pressure Device: SuperNO2VA™ EtCO2 Measurement and Pressure Test Performance

Background: SuperNO2VA™ Et Nasal Mask (Vyaire Medical, Inc., United States) is a new nasal mask with an integrated sampling hood to capture exhaled gases and enable accurate measurements of end tidal carbon dioxide (EtCO2). The authors hypothesized that the SuperNO2VA Et design would measure EtCO2 more accurately than a predicate EtCO2 sampling line, the Smart CapnoLine® Plus, Adult/Intermediate CO2 Oral-Nasal Set (Medtronic, United States). Methods: A simulated patient setup enabled comparison of the accuracy of CO2 measurements within the SuperNO2VA Et and a predicate device for eight condition combinations of input CO2; breath rate and tidal volume (VT); and O2 flow rates. These tests were repeated with simulating Nasal Breathing and Oral Breathing. Results: Testing demonstrated that measurements of 1% and 5% input CO2 within the SuperNO2VA Et were accurate for a range of respiratory rates, VT, O2 flows, and CO2 concentrations. CO2 measurement errors were significantly larger for the Oral-Nasal Set compared to the SuperNO2VA Et for both 1% Input CO2 (-0.12%vol vs. -0.01%vol, p = 0.0005) and 5% Input CO2 (-0.93%vol vs. -0.08%vol, p 0.0001). At 5% Input CO2, eight of the 12 trials for the Oral-Nasal Set failed to meet the ISO accuracy specification, while all SuperNO2VA Et measurements met the specification. The accuracy of CO2 measurement within the SuperNO2VA were not different for Oral and Nasal Breathing trials for both CO2 concentration (1%: p = 0.33, 5%: p = 0.064). With the Oral-Nasal Set, CO2 measurements were lower during Oral compared to Nasal Breathing (1%: p = 0.0005, 5%: p = 0.0091). Conclusions: Based on performance outcomes, use of the SuperNO2VA Et offers significantly more accurate measurement of EtCO2 than the predicate EtCO2 sampling line. Measurements of EtCO2 within the SuperNO2VA Et are accurate over a range of CO2, breathing rates, tidal volumes, and O2 flows, as well as for nasal and oral breathing.
Structural features and electronic properties of group-III-, group-IV-, and group-V-doped Si nanocrystallites

We investigate the incorporation of group-III (B and Al), group-IV (C and Ge), and group-V (N and P) impurities in Si nanocrystallites. The structural features and electronic properties of doped Si nanocrystallites, which are faceted or spherical-like, are studied by means of an ab initio pseudopotential method including spin polarization. Jahn–Teller distortions occur in the neighborhood of the impurity sites and the bond lengths show a dependence on size and shape of the nanocrystallites. We find that the acceptor (group-III) and donor (group-V) levels become deep as the nanocrystallites become small. The energy difference between the spin-up and spin-down levels of group-III and group-V impurities decreases as the size of the Si nanocrystallite increases and tends to the value calculated for Si bulk. Doping with carbon introduces an impurity-related level in the energy gap of the Si nanocrystallites.
Evolution of a Geothermal System with Fluid Re-Injection

In this paper, we study the stationary configurations of a vapor-dominated geothermal system. We propose a general mathematical model, which turns out to be a free boundary problem, and we focus on the stationary solutions. The analysis, developed considering the data of the geothermal field in Larderello, Tuscany (Italy), shows that steady-stable states may exist both when the re-injection takes place in depth and when the natural recharge is distributed both in the area occupied by vapor and in the one occupied by liquid.
Predicting the EEG Level of a Driver Based on Driving Information

Driving is an essential activity in today’s busy and complex society, and it demands physical and mental abilities, collectively known as a driving workload. For safe and comfortable driving, it would be useful to detect when drivers are being overloaded. Analyzing driver’s workload using an electroencephalograph (EEG) is useful for this purpose. However, it is very inconvenient to obtain an EEG during actual driving, since the measuring device needs to be attached to the driver. In this paper, we develop a model to predict the driver’s EEG level utilizing basic information obtained while the vehicle is being driven. We divided the EEG values into two classes, “normal” and “overload”, and extracted useful features from the vehicle driving information, such as engine RPM, vehicle speed, lane changes, and turns. A classification model using a support vector machine was built to predict normal and overload states during actual driving. We evaluated the performance of the proposed method using field-of-test data collected when driving on actual roads, and suggest directions for future research based on an analysis of the experimental results.
Integrated Multifunctional Laryngoscope for Medical Diagnosis and Treatment

Laryngeal lesions can cause great inconvenience to patients. Early diagnosis and corresponding treatments are critical to the survival of patients. However, the diagnosis and precise removal of tumors remain a challenge under the use of a white light laryngoscope. In this work, an integrated, multifunctional laryngoscope was designed and tested for the imaging evaluation and precision laser surgery for laryngeal tissue. This integrated diagnostic and therapeutic endoscopic system included two imaging modes (i.e., optical coherence tomography and white light endoscopy) and a laser ablation treatment mode. The endoscope had a common-path design to ensure that the same position could be imaged and treated simultaneously. The ex vivo porcine larynx experimental results showed that the system imaging modes could simultaneously acquire both superficial and cross-sectional images of the sample tissue, and the ablation treatment could be performed under imaging guidance. This multifunctional laryngoscope has great potential for the early diagnosis of and accurate laser ablation surgery for laryngeal tumors.
Measurement of in-plane and out-of-plane elastic properties of woven fabric composites using digital image correlation

The digital image correlation (DIC) technique is employed to measure the strain fields and the five independent elastic material constants of a glass/vinyl ester plain weave laminated composite. Transverse (through-thickness) tensile and Iosipescu shear properties were measured using thick (∼19 mm) laminates, and the strain fields were compared against those predicted by a homogenized linear elastic finite element analysis. DIC reveals that the strain fields of the laminates may present heterogeneous zones, which are attributed to the heterogeneous nature of the woven fabric architecture. Homogenization of the DIC strain fields to produce two-dimensional stress-strain plots yields average strains and elastic properties of the woven composite which can be similar to those measured by conventional (localized) strain gages. Important differences were found for the transverse tensile and Iosipescu shear tests, where differences of 26.4%, 28.6% and 11.9% were obtained for the measured transverse elastic modulus (Ez), in-plane shear modulus (Gxy) and transverse shear modulus (Gxz), respectively.
An Efficient Algorithm to Extract Control Flow-Based Features for IoT Malware Detection

Control flow-based feature extraction method has the ability to detect malicious code with higher accuracy than traditional text-based methods. Unfortunately, this method has been encountered with the NP-hard problem, which is infeasible for the large-sized and high-complexity programs. To tackle this, we propose a control flow-based feature extraction dynamic programming algorithm for fast extraction of control flow-based features with polynomial time O($N^{2}$), where N is the number of basic blocks in decompiled executable codes. From the experimental results, it is demonstrated that the proposed algorithm is more efficient and effective in detecting malware than the existing ones. Applying our algorithm to an Internet of Things dataset gives better results on three measures: Accuracy = 99.05%, False Positive Rate = 1.31% and False Negative Rate = 0.66%.
Design of Balanced Filtering Components Based on Isosceles Right-Angled Triangular Patch

In this paper, a balanced bandpass filter (BPF), a balanced-to-balanced filtering power divider (FPD), and a balun filter are implemented using the isosceles right triangular patch element. Two isosceles right triangular patch elements are coupled through an open stub for a triple-mode passband response under differential-mode operation and wide common-mode suppression simultaneously. To further improve the selectivity, an open stub is loaded on each feed-line. Based on these elements, a balanced BPF with excellent performance can be implemented. As an extension, a balanced-to-balanced FPD and a balun BPF are implemented based on the structure of the filter. For validation of the proposed configurations, all the balanced BPF, FPD, and balun BPF have been fabricated and measured. All measured results are found to be in a reasonable agreement with the simulation results.
Structural factors affecting Aryl Hydrocarbon Hydroxylase induction by Dibenzo-p-dioxins and Dibenzofurans

Quantitative structure-activity relationships have been developed to rationalize the experimental data obtained with a series of dibenzo-p-dioxins and dibenzofurans in the assays for receptor binding and aryl hydrocarbon hydroxylase (AHH) induction. Lateral substituents (in positions 2, 3, 7, and 8 of the tricyclic system) do not affect receptor binding and AHH induction in the same manner. Various hypotheses are suggested to explain this finding. Of special interest is the possibility that the lateral substituents are directly involved in the mechanism which transforms the receptor to the active state. The implications of this possibility are considered with regard to the design of an antidote for poisoning caused by the chlorinated congeners which occur as contaminants in certain commercial products.
Probing disorder and charged impurities in graphene by Raman spectroscopy

Disorder and doping can strongly affect the properties of graphene. Here we analyze these effects on several samples by Raman spectroscopy. In particular, we show that pristine and unprocessed graphene samples deposited on silicon, covered with a thin silicon oxide layer, show strong variations in their Raman spectra, even in absence of disorder. The variation in the Raman parameters is assigned to charged impurities. This shows that as‐deposited graphene is unintentionally doped, reaching charge concentrations up to 1013 cm–2 under ambient conditions. The doping varies from sample to sample and the charges are inhomogeneously distributed on a submicron scale. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Ceilometers as planetary boundary layer height detectors and a corrective tool for COSMO and IFS models

Abstract. The significance of planetary boundary layer (PBL) height detection is apparent in various fields, especially in air pollution dispersion assessments. Numerical weather models produce a high spatial and temporal resolution of PBL heights; however, their performance requires validation. This necessity is addressed here by an array of eight ceilometers; a radiosonde; and two models – the Integrated Forecast System (IFS) global model and COnsortium for Small-scale MOdeling (COSMO) regional model. The ceilometers were analyzed with the wavelet covariance transform method, and the radiosonde and models with the parcel method and the bulk Richardson method. Good agreement for PBL height was found between the ceilometer and the adjacent Bet Dagan radiosonde (33 m a.s.l.) at 11:00 UTC launching time (N=91 d, ME =4 m, RMSE =143 m, R=0.83). The models' estimations were then compared to the ceilometers' results in an additional five diverse regions where only ceilometers operate. A correction tool was established based on the altitude (h) and distance from shoreline (d) of eight ceilometer sites in various climate regions, from the shoreline of Tel Aviv (h=5 m a.s.l., d=0.05 km) to eastern elevated Jerusalem (h=830 m a.s.l., d=53 km) and southern arid Hazerim (h=200 m a.s.l., d=44 km). The tool examined the COSMO PBL height approximations based on the parcel method. Results from a 14 August 2015 case study, between 09:00 and 14:00 UTC, showed the tool decreased the PBL height at the shoreline and in the inner strip of Israel by ∼100 m and increased the elevated sites of Jerusalem and Hazerim up to ∼400 m, and ∼600 m, respectively. Cross-validation revealed good results without Bet Dagan. However, without measurements from Jerusalem, the tool underestimated Jerusalem's PBL height by up to ∼600 m.
Spatial abundance distribution of prokaryotes is associated with dissolved organic matter composition and ecosystem function

Diverse prokaryotic communities consume and transform a broad suite of molecules in the dissolved organic matter (DOM) pool, which controls major biogeochemical cycles. Despite methodological advancements that provide increasingly more detailed information on the diversity of both prokaryotic communities and DOM components, understanding how these two component parts are structured to influence ecosystem functioning remains a major challenge in microbial ecology. Using empirical data collected along a gradient of productivity in the Labrador Sea, we characterized relationships among DOM compounds, metabolic processing, and prokaryotic diversity by structuring prokaryotic communities using spatial abundance distribution (SpAD) modeling. We identified strong associations of different SpAD taxonomic groups with specific organic substrates as well as with metabolic rates. Amplicon sequence variants (ASVs) with more cosmopolitan distributions (i.e. normal‐like) such as Bacteroidia were related to fresher DOM substrates such as free and combined amino acids whereas rare ASVs (i.e. logistic) like δ‐proteobacteria were associated with complex forms of organic matter. In terms of ecosystem function, rates of respiration and production were most strongly predicted by the abundance of certain SpAD taxonomic groups. Given the importance and complexity of linking environmental conditions, prokaryotic community structure, and ecosystem function, we propose a framework to bridge the gap between prokaryotic diversity, microbial ecology, and biogeochemistry among methods and across scales. Our work suggests that SpAD modeling can be used as an intermediate step to link prokaryotic community structure to both finer DOM details and larger ecosystem scale processes.
Nanostructured lithium titanate and lithium titanate/carbon nanocomposite as anode materials for advanced lithium-ion batteries

Abstract Lithium-ion (Li-ion) batteries with high energy and power are promising power sources for electric vehicles (including hybrid electric vehicles). One of the challenges is to develop advanced anode materials with high safety, good cycling stability, and fast charge/discharge capabilities. The Li4Ti5O12 spinel is a state-of-the-art Li-ion battery anode material owing to its outstanding safety and excellent structural stability during cycling. However, Li4Ti5O12 large particles still suffer from low ionic conductivity and electronic conductivity, which result in poor rate performance and inhibit its wide practical application. Developing nanostructured electrode materials is one of the most attractive strategies to dramatically enhance the electrochemical performance, including capacity, rate capability, and cycling life. Currently, extensive efforts have been devoted to developing nanostructured Li4Ti5O12 and Li4Ti5O12/carbon nanocomposites to improve their rate performance for high-power Li-ion batteries. In this article, we review the recent progress in developing nanostructured Li4Ti5O12 and Li4Ti5O12/carbon nanocomposites and discuss the benefits of nanostructure and carbon incorporation for the electrochemical performance of Li4Ti5O12-based anodes.