Miracle-dz/UniFAR-FTUs huggingface dataset:
A molecular dynamics investigation on fuel vaporization and mixing characteristics under sub/supercritical conditions

Molecular dynamics simulation is performed to study the influence of environmental pressure on the mixing process. Based on the OPLS-AA full-atomic potential function, the "gas-liquid-gas" simulation box model is used to study the evaporation characteristics of n-heptane at different environmental conditions. The results show that compared with the subcritical environment, the nitrogen molecules in the supercritical condition can diffuse into the liquid phase region earlier, and the temperature of the liquid phase rise faster, and then a unified supercritical fluid could be formed. Based on the density profile, a ? gas-liquid-gas? interface thickness is defined and the interface thickness is widened as the ambient pressure increase, resulting in the conventional subcritical evaporation transition to turbulent mixing process.
Super-Nyquist signal transmission and digital signal processing

Super-Nyquist, also known as Fast-than-Nyquist (FTN), signal generation based on optical or electrical spectrum shaping methods has been demonstrated to be an efficient scheme for future high-capacity transmission systems. Super- Nyquist signal demodulations based on maximum a posteriori (MAP) or maximum likelihood sequence estimation (MLSE) on receiver side have been demonstrated in 100G, 200G and 400G systems, which enables PDM-QPSK transmission with 4bit/s/Hz net spectral efficiency (SE) at lower OSNR requirement and longer transmission distance. Further studies also show the highly filtering-tolerant advantage of the super-Nyquist signal when using the 9-QAMbased multi-modulus equalization. This feature is quite useful for signals transmission under the aggressive optical filtering in multiple reconfigurable optical add-drop multiplexers (ROADMs) transmission link. In this paper, we review the newly reported super-Nyquist experiments using the optical super-Nyquist filtering 9-QAM like signals based on multi-modulus equalization (MMEQ). We directly recover the Nyquist filtered QPSK to a 9-QAM like signal. We first successfully transmitted 100-GHz-grid, 20 channels single-carrier 440-Gb/s super-Nyquist 9-QAM-like signal over 3600-km ultra-large effective-area fiber (ULAF) at record a net SE of 4b/s/Hz (after excluding the 7% hard-decision FEC overhead). The highly filtering-tolerant performance of the 9-QAM liked super-Nyquist signal is also experimentally demonstrated. Using this scheme, we then successfully transmit 10 channels 440-Gb/s signal over 3000- km ULAF and 10 cascaded ROADMs with 100-GHz-grid based on the single-carrier ETDM 110-GBaud QPSK. It is the highest baud rate of all-ETDM signal reported with the highest net SE at this baud rate for PDM-QPSK signal.
A proposed stacked microstrip antenna structure for bandwidth enhancement

A new stacked microstrip antenna structure that enhances the bandwidth without changing the resonance frequency is proposed and studied in this paper. The effect of the various antenna parameters on the bandwidth is investigated. The resulting antenna, using the proposed structure, has an ultra‐wide bandwidth of 35%, compared to 21.8% for the conventional stacked antenna structure. The proposed structure has little effect on the antenna's radiation characteristics. The analysis of the proposed structure is carried out using the FDTD method. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 36: 26–28, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10660
Development of a general symmetrical condensed node for the TLM method

A general symmetrical condensed node (GSCN) for the transmission line modeling (TLM) method, with six different link line characteristic impedances, six stubs, and six lossy elements is described for the first time. It unifies all the currently available condensed nodes into a single formulation and provides the basis for the derivation of an infinite set of new nodes, including nodes with improved numerical characteristics. The GSCN is derived in two ways: (1) from an equivalent network model and (2) directly from Maxwell's equations using central differencing and averaging. The direct correspondence established between the GSCN TLM and a finite difference scheme for Maxwell's equations provides a rigorous theoretical foundation for all available TLM methods with condensed nodes.
Resonant frequencies of post-wall waveguide cavities

A new method is presented for predicting the resonant frequencies of post–wall rectangular waveguide cavities, in which the narrow walls of the guide are composed of rows of vias. By interpreting the fields inside the guide as a superposition of plane waves, the surface impedance of a row of wires, when illuminated by a plane wave, is used to model the narrow walls of the waveguide. The derivation leads to equivalent rectangular waveguide dimensions that are then used to calculate the resonant frequencies of the cavity. Theoretical results are compared with the observed TE10m resonant frequencies of several post–wall waveguide cavities fabricated in low temperature cofired ceramic (LTCC). The results confirm that the method improves the resonant frequency prediction when the pitch of the vias is at least ten times greater than their radius.
Structural basis of dynamic P5CS filaments

The bifunctional enzyme Δ1-pyrroline-5-carboxylate synthase (P5CS) is central to the synthesis of proline and ornithine. Pathogenic mutations in P5CS gene (ALDH18A1) lead to neurocutaneous syndrome and skin relaxation connective tissue disease in humans, and P5CS deficiency seriously damages the ability to resist adversity in plants, which has an essential role in agriculture and human health. Recently, P5CS has been demonstrated forming the cytoophidium in vivo and filaments in vitro. However, the underlying mechanism for the function of P5CS filamentation and catalyze the synthesis of P5C is hardly accessible without structural basis. Here, we have succeeded in determining the full-length structures of Drosophila P5CS filament in three states at resolution from 3.1 to 4.3 Å under cryo-electron microscopy, we observed the distinct ligand-binding states and conformational changes for GK and GPR domain separately. These structures show the distinctive spiral filament is assembled by P5CS tetramers and stabilized by multiple interfaces. Point mutations that deplete such interactions disturb P5CS filamentation and greatly reduce the activity. Our findings reveal a previously undescribed mechanism that filamentation is crucial for the coordination between GK and GPR domains, and provide insights into structural basis for catalysis function of P5CS filament.
Time-domain analysis of switching converters based on a discrete-time transition model of the spectral coefficients of state variables

In this paper, a new method for the large-signal time-domain analysis of switching converters is presented. It is based on a discrete-time transition model for the coefficients of time-domain spectral form of state variables describing the behavior of the converter between each pair of switching instants. The variables controlling the zero-current and zero-voltage switching instants are represented by finite-order approximating polynomials, whose zeros are determined by means of a fastly convergent interval analysis technique; the analysis of synchronous commutations is carried out by means of the compensation theorem. In order to illustrate the effectiveness and accuracy of the proposed method the example of a regulated dc-dc converter is given.
Islamic school leadership and social justice: an international review of the literature

ABSTRACT This literature review responds to global concerns regarding the state of Islamic schools and their leadership. A socio-religious conceptual framework guided the inquiry and informed the analysis. The review offers a counternarrative to hegemonic discourses, provides meaning to the complex work of Islamic school leaders in varying contexts, and informs the literature on educational leadership for social justice. Findings suggest Islamic school leaders working to advance social justice converged and diverged in their worldviews, manipulated formal and informal power dynamics, supported the development of Muslim students’ differing expressions of identity, and were responsible to others as a moral calling. The review makes international research connections in leadership for social justice and aims to deepen the knowledge base in educational leadership.
Dynamics of oversowing machine MSPD 2.5 related to working and constructive parameters.

In the paper, the equipment and methodology of experimental research concerning the dynamics of the individual sowing section and the complete machine, are presented. Depending on working conditions (depth: 2 and 4 cm, speed: 5.5 km/h (1.52 m/s) and 7.5 km/h (2.08 m/s)) and constructive solutions (attack angle of share: 25 o , 35 o and 45 o ), analyzing the data of experimental trials, there is possibility to find optimal constructive and functional solutions to reduce traction forces and finally fuel consumption of the aggregate.
Stability and dynamics of a spectral graph model of brain oscillations

We explore the stability and dynamic properties of a hierarchical, linearized, and analytic spectral graph model for neural oscillations that integrates the structuring wiring of the brain. Previously we have shown that this model can accurately capture the frequency spectra and the spatial patterns of the alpha and beta frequency bands obtained from magnetoencephalography recordings without regionally varying parameters. Here, we show that this macroscopic model based on long-range excitatory connections exhibits dynamic oscillations with a frequency in the alpha band even without any oscillations implemented at the mesoscopic level. We show that depending on the parameters, the model can exhibit combinations of damped oscillations, limit cycles, or unstable oscillations. We determined bounds on model parameters that ensure stability of the oscillations simulated by the model. Finally, we estimated time-varying model parameters to capture the temporal fluctuations in magnetoencephalography activity. We show that a dynamic spectral graph modeling framework with a parsimonious set of biophysically interpretable model parameters can thereby be employed to capture oscillatory fluctuations observed in electrophysiological data in various brain states and diseases.
A Machine Learning Model for the Determination of Macro-Scale Masonry Properties based on a Virtual Laboratory at Micro-Scale

Cutting-edge methods in the computational analysis of structures have been developed over the last decades. Such modern tools are helpful to assess the safety of existing buildings. Multi-scale techniques have been proposed to combine the accuracy of micro-modelling and the computational efficiency of macro-modelling. Machine-learning tools have been utilized successfully to train specific models by feeding big source data from different fields, e.g. autonomous driving, face recognition, etc. This research proposes a continuous nonlinear material law that can reproduce data from micro-scale analysis. The proposed method is based on a machine-learning tool that links the two scales of the analysis by training a macro-model smeared damage constitutive law through benchmark data from numerical tests derived from micro-models.
Sample arrangements and spatial variability characterization of dendometrics parameters of Eucalyptus camaldulensis and physical soil attributes

Submitted on August 7, 2019 and accepted on September 1 1, 2021. 1 Universidade Estadual Paulista, Campus Ilha Solteira, Faculdade de Engenharia, Ilha Solteira, São Paulo, Brazil. cesar.lima@unesp.br; maa.carvalho@hotmail.com; nelsongiovanini@outlook.com; pauloteodoro@agronomo.eng.br 2 Universidade Estadual Paulista, Campus Jaboticabal, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, São Paulo, Brazil. alan.panosso@unesp.br 3 Universidade Estadual Paulista, Campus Botucatu, Faculdade de Ciências Agrárias, Botucatu, São Paulo, Brazil. nidiarcosta@gmail.com *Corresponding author: cesar.lima@unesp.br Sample arrangements and spatial variability characterization of dendometrics parameters of Eucalyptus camaldulensis and physical soil attributes
Scaffolding vocational high school students’ computational thinking with cognitive and metacognitive prompts in learning about programmable logic controllers

Abstract With the rapid development of artificial intelligence in many disciplines, computational thinking (CT) has become an important skill for the 21st century. To promote vocational high school students’ CT skills in learning about programmable logic controllers, this study intended to examine how cognitive and metacognitive prompts separately or together influenced students’ development of CT. The findings revealed that metacognitive prompts significantly improved students’ CT outcomes, self-efficacy, and motivation for learning. The study offers important implications regarding the strategies to promote CT in vocational high schools.
Operational Heat Balance Model with Parameterized Geometry for the Prediction of Car Cabin Heat Loads

Abstract The paper presents the development of a mathematical model and a simulation tool for the transient prediction of the indoor climate and the heat loads in a car cabin, under real operating conditions. The main objectives were to develop a tool which facilitates, for example, the design of a cabin HVAC system or an on-line control. The model is based on the energy balance between the cabin and the outdoor environment accounting for conduction, convection and shortwave and longwave radiation. Inside the car cabin, the heat exchange is calculated between the human body, the air zone, the interior cabin surfaces and the incoming air from the HVAC system. The heat balance model assumes a simplified 3D geometry of a cabin, which is specified by seven basic parameters. The model also allows simulating the incidence angle of the sun rays onto the individual parts of the exterior surface during parking as well as during a journey. The model was tested and evaluated for a Škoda Felicia Combi car in situations of summer parking and an autumn journey. Measured data were used both as boundary conditions for the model and as validation and calibration data. The air temperature inside the car cabin, predicted by the model, was in a very good agreement with the measured mean air temperature. The model is able to correctly predict the indoor cabin air temperature and the heat loads into the car cabin, thus it is well suited as a software support tool in the process of HVAC design and on-line cabin climate control.
Visualizing Standardized Model-Based Design and Inspection Data in Augmented Reality

Augmented reality (AR) has already helped manufacturers realize value across a variety of domains, including assistance in maintenance, process monitoring, and product assembly. However, coordinating traditional engineering data representations into AR systems without loss of context and information remains a challenge. A major barrier is the lack of interoperability between manufacturing-specific data models and AR-capable data representations. In response, we present a pipeline for porting standards-based design and inspection data into an AR scene. As a result, product manufacturing information with three-dimensional (3D) model data and corresponding inspection results are successfully overlaid onto a physical part. We demonstrate our pipeline by interacting with annotated parts while continuously tracking their pose and orientation. We then validate the pipeline by testing against six fully toleranced design models, accompanied by idealized inspection results. Our work (1) pro-vides insight on how to address fundamental issues related to interoperability between domain-specific models and AR systems and (2) establishes an open software pipeline from which others can implement and further develop.
Simplified Model for the Operation of Chilled Water Cooling Coils Under Nonnominal Conditions

This study presents a cooling coil model for calculating energy consumption in air-conditioned buildings that has a minimal number of inputs. The model accurately determines the cooling energy rate and dehumidification energy rate under nonnominal conditions, and takes into account operation under variable air and water flows. In this manner, the model enhances the simplified ASHRAE Toolkit model without requiring more input data. The main assumptions are justified considering the common existing configurations of cooling coils in the air-conditioning industry. The parameters of the model are identified from only one nominal rating point. The model has been validated on a VAV facility with an average deviation of 5% for total energy rate. Errors are mainly due to the assumption that the coil is either completely wet or dry even if the surface is partially wet.
Investment Evaluation and Partnership Selection Model in the Offshore Wind Power Underwater Foundations Industry

With a plan to achieve a target of 5.7 GW offshore wind power capacity in 2025, Taiwan anticipates building a 36-billion USD industry, which makes Taiwan a center of attention in the global marketplace of civil engineering construction. Aimed at Taiwan’s underwater foundations industries, this study is the first to develop an investment evaluation model (IEM) by applying FPR to obtain risk factor weights and calculate the overall investment risk value with a numerical scoring method. In a context where no precedent exists for reference, this study provides auxiliary and supportive tools to help builders to make the decision, based on objective indicators, whether to undertake an investment. To date, no research has been conducted to introduce a reasonable mathematical model that discusses the issue of partner selection in the field of offshore wind power. This study is the first paper to construct a SWARA-FTOPSIS partner selection model, which enables underwater foundations builders to take specific Taiwanese characteristics into account in their selection of the best partners to meet transportation, construction, and installation requirements. Finally, the study uses the case of the Taipower Offshore Wind Power Project (2nd phase) to verify the feasibility of this model.
Projecting lifetime of deep submicron MOSFETs

A detailed examination of hot-carrier-induced degradation in MOSFETs from a 0.25-/spl mu/m and a 0.1-/spl mu/m technology is performed. Although the worst case stress condition depends on the stress voltage, channel length, and oxide thickness, I/sub b,peak/ is projected to be the worst case stress condition at the operating voltage for both nMOSFETs and pMOSFETs. Post-metallization anneal (PMA) in deuterium can significantly improve the device lifetime if the primary degradation mechanism at the stress condition is interface trap generation due to interface depassivation by energetic electrons.
Hybrid Lateral Aerodynamic Modeling Based on WNN and Kernel Principal Components Feature Extraction

In order to better describe the dynamic characteristics of aircraft through aerodynamic modeling, a Wavelet Neural Network (WNN) aerodynamic modeling method based on Kernel Principal Components Analysis (KPCA) is proposed. Firstly, the training samples are used to execute KPCA for extracting basic features of samples, and then using the extracted basic features, WNN aerodynamic model was established. The simulation result shows that, the modeling ability of the method proposed is better than that of another 3 methods. It can easily determine of model parameters. This enables it to be effective and feasible to establish the aerodynamic modeling for aircraft.
Fabrication of biopolymer nanofibers from natural sources

The methods available for the disposal of synthetic polymers are not advanced in an environment-friendly way. Consequently, their waste persists as a non-degradable pollutant that discharges toxic substances, which have now reached the deepest parts of the ocean. As an alternative, biopolymers such as polylactic acid, polyhydroxyalkanoates, and poly(butylene succinate), synthesized from natural sources such as plants, animals, and microbes, are an eco-friendly option, as they are biodegradable and a better option to shift from synthetic polymer dependency. The fabrication of electrospun nanofibers (NFs) using biopolymers is a novel approach, by which new ideas have been proposed in various fields, such as agriculture, biomedical, food packing, textiles, adsorption, drug delivery, three-dimensional printing, etc. Electrospun NFs are receiving increasing attention due to their diverse properties, including flexibility. This review provides a perception of the novel biopolymers that are currently utilized by the electrospun technique and their various applications.
Combined Layer-by-Layer/Hydrothermal Synthesis of Fe3O4@MIL-100(Fe) for Ofloxacin Adsorption from Environmental Waters

A simple not solvent and time consuming Fe3O4@MIL-100(Fe), synthesized in the presence of a small amount of magnetite (Fe3O4) nanoparticles (27.3 wt%), is here presented and discussed. Layer-by-layer alone (20 shell), and combined layer-by-layer (5 shell)/reflux or /hydrothermal synthetic procedures were compared. The last approach (Fe3O4@MIL-100_H sample) is suitable (i) to obtain rounded-shaped nanoparticles (200–400 nm diameter) of magnetite core and MIL-100(Fe) shell; (ii) to reduce the solvent and time consumption (the layer-by-layer procedure is applied only 5 times); (iii) to give the highest MIL-100(Fe) amount in the composite (72.7 vs. 18.5 wt% in the layer-by-layer alone); (iv) to obtain a high surface area of 3546 m2 g−1. The MIL-100(Fe) sample was also synthesized and both materials were tested for the absorption of Ofloxacin antibiotic (OFL). Langmuir model well describes OFL adsorption on Fe3O4@MIL-100_H, indicating an even higher adsorption capacity (218 ± 7 mg g−1) with respect to MIL-100 (123 ± 5 mg g−1). Chemisorption regulates the kinetic process on both the composite materials. Fe3O4@MIL-100_H performance was then verified for OFL removal at µg per liter in tap and river waters, and compared with MIL-100. Its relevant and higher adsorption efficiency and the magnetic behavior make it an excellent candidate for environmental depollution.