bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the photovoltaic effect asymmetry in ferroelectrics
Authors: Semak S , Kapustianyk V , Eliyashevskyy Yu , Bovgyra O , Kovalenko M , Mostovoi U , Doudin B , Kundys B 
Published: December 2022

Abstract
Despite symmetrical polarization, the magnitude of a light-induced voltage is known to be asymmetric with respect to poling sign in many photovoltaic (PV) ferroelectrics (FEs). This asymmetry remains unclear and is often attributed to extrinsic effects. We show here for the first time that such an asymmetry can be intrinsic, steaming from the superposition of asymmetries of internal FE bias and electro-piezo-strictive deformation. This hypothesis is confirmed by the observed decrease of PV asymmetry for smaller FE bias. Moreover, the both PV effect and remanent polarization are found to increase under vacuum-induced expansion and to decrease for gas-induced compression, with tens percents tunability. The change in cations positions under pressure is analysed through the first-principle density functional theory calculations. The reported properties provide key insight for FE-based solar elements optimization.
A non-axisymmetric temperature field reconstruction method based on the interferometric fringe schlieren method
Authors: Wu Jun , Pan Zhixiang , Zhang Chenping , Song Fengcheng , Zhang Xiaoyu , Guo Runxia 
Published: December 2022

Abstract
The typical non-axisymmetric temperature field distribution in the tail nozzle outlet area of the combustion chamber of an aircraft engine can reflect the operating state of the engine. As an effective non-contact method for measuring a non-axisymmetric temperature field, the traditional background-oriented schlieren (BOS) method has the problem that the extraction accuracy of light deflection is not high. In this paper, interference fringes are introduced into the schlieren measurement, and the highly sensitive fringe offset replaces the traditional background speckle offset for measurement, which realizes accurate reconstruction of the non-axisymmetric temperature field. Firstly, through the interferometric fringe schlieren (IFS) method comprising multiple sets of double-slit interferometric systems and imaging sensors, the offset of the interference fringe after passing through the non-axisymmetric temperature field is measured by image processing. The spatial refractive index field is then reconstructed by the filtered back-projection algorithm under the sector model proposed in this paper and the spatial temperature field is obtained. The experimental results show that the temperature field reconstruction error is smaller for the IFS method than the BOS method, the measurement area is accurate from 0.5 mm for the BOS method to 0.2 mm for the IFS method and the temperature error range is reduced from 50 K for the BOS method to 25 K for the IFS method.
FDO-Calibr: visual-aided IMU calibration based on frequency-domain optimization
Authors: Liu Yunfei , Li Zhitian , Xiao Linhui , Zheng Shuaikang , Cai Pengcheng , Zhang Haifeng , Zheng Pengcheng , Zou Xudong 
Published: December 2022

Abstract
Nowadays, multi-sensor fusion technology is a fundamental prerequisite to achieve highly autonomous robots and robustness. Many studies have been conducted, such as visual–inertial odometry (VIO), integrated navigation, and LiDAR–inertial odometry. Typically, for VIO, gratifying results have been achieved, ascribing to the complementary sensing capabilities of inertial measurement units (IMUs) and cameras. However, this work mainly focuses on the fusion of visual and inertial data, while the IMU error is less considered, especially for low-cost or poorly calibrated microelectromechanical system (MEMS) IMU. Such errors may have a significant effect on the VIO performance. In this study, we compensated for the IMU using camera assistance. The key characteristic of the method is that we optimize the compensation parameters (scale factor) from coarse to fine by combining the time domain with the frequency domain. The proposed method is to use the time-domain and frequency-domain optimization to suppress large noise in the dynamic calibration process of the extremely low-cost sensor platform. The effectiveness of this method is validated through experiments and simulations. The minimal calibration error (0.46%) is commensurate with the advanced work. By feeding the compensated IMU into the VIO algorithm, the localization accuracy is improved by 9% to 15%. This method improves the performance in the VIO algorithm, which is equipped with the low-cost or poorly calibrated MEMS IMU and reduces the hardware and deployment costs of the system.
Passive resonant laser gyroscope with improvement of the suppression of residual amplitude modulation effects through correlation analysis
Authors: Feng Xiaohua , Liu Kui , Chen Yuxuan , Zhang Haobo , Li Zongyang , Zhang Fenglei , Lu Zehuang , Zhang Jie 
Published: December 2022

Abstract
Passive resonant gyroscopes (PRGs) utilizing the Pound-Drever-Hall (PDH) method are expected to have a lower shot-noise limit in rotational rate measurement. However, there are also many technical obstacles in the way to touch the intrinsic noise floor. In this article, we find that the residual amplitude modulation (RAM) effect in the phase locking process deteriorates the accuracy and stability of the output signal of PRGs, and becomes a dominant limiting factor, especially in the low-frequency range. Since the suppression is not good enough in the PRGs due to the strict requirements, we propose to use the Pearson correlation coefficient to evaluate the correlation between the RAM signal and the PDH signal to achieve a sufficient correlation before active servo control. With the implementation of this improvement, the RAM-induced fractional frequency stability for the 12 m optical ring cavity is reduced down to

1.2
×

10

−
18

. The contribution of the RAM effect to the rotational sensitivity of our 3 m × 3 m PRG is lowered to 8.0 × 10−9 rad s−1

Hz

−
1

at 1 mHz, which is one order of magnitude better than the unconstrained situation. With this upgrade, a rotational resolution of

5.2
×

10

−
10

rad s−1 of the PRG is achieved, which is the best performance among all PRGs so far.
N-doped carbon dots as the multifunctional fluorescent probe for mercury ion, glutathione and pH detection
Authors: Chen Shenna , Hao Yunping , Li Ronghui , Liu Yanxu , Li Jinxia , Geng Lina 
Published: December 2022

Abstract
Recently, carbon dots (CDs) have exhibited promising applications in the fluorescence detection of various ions and biomolecules. In this work, one kind of nitrogen-doped CDs (N-CDs) with high fluorescence intensity was synthesized, characterized by transmission electron microscopy, x-ray diffraction, x-ray photoelectron spectroscopy, Fourier-transform infrared, UV–vis absorption spectra, and fluorescence spectra. The results show that the spherical and uniform N-CDs (quantum yield: 60.2%) have remarkable fluorescence properties and photostability, which makes N-CDs can be utilized as an ‘on-off-on’ sensor for Hg2+ and glutathione (GSH). In addition, the pH-sensitive behavior of N-CDs makes it also applicable to H+ detection under acid conditions (pKa = 3.53). The linear range of the ‘turn-off’ sensor detecting Hg2+ was 0.014–50 μM, with a 0.014 μM limit of detection (LOD). GSH was detected by the fluorescence ‘turn-on’ method with a linear range of 0.125–60 μM and a LOD of 0.125 μM. The outstanding performance of N-CDs makes it potential applications in ecological pollution and biomolecule visualization monitoring.
Could the digital literacy of preservice physics teachers be improved by Learning Management System Supported Smartphone (LMS3) application in a physics online lecture?
Authors: Rizal Rahmat 
Published: December 2022

Abstract
Digital literacy is a vital competency needed by physics teachers, so it should be trained through lectures using technology, one of which is LMS3. The study aims to describe the LMS3 implementation in school physics lectures to train digital literacy and elucidate an enhancement of prospective physics teachers’ digital literacy in school physics lectures using LMS3. One-group pre-test–post-test design was conducted on 38 prospective physics teachers who enrolled in school physics lectures. The instruments consisted of digital literacy tests, lecture implementation forms, and interview guides. Besides, LMS3 is an application designed independently using the ADDIE (analysis, design, development, implementation, and evaluation) development model. The learning process using LMS3 occurred synchronously after the lecturer activated the learning process menu and adopted problem-based learning syntax. In general, the enhancement of digital literacy of prospective physics teachers after attending school physics lectures using LMS3 was the high category (N-gain = 0.72). In conclusion, school physics lectures using LMS3 had a significant impact on enhancing digital literacy. This study suggests developing lectures using various technologies that support the improvement of teacher competence in facing challenges in education.
Bonding performance monitoring between CFRP and timber column interfaces based on piezoelectric ceramics
Authors: Yang Wenwei , Lv Bowen , Meng Huien , Yang Xia 
Published: December 2022

Abstract
To address the problem that carbon fibre reinforced polymer (CFRP) composite material is not easy to directly measure the bond strength of the CFRP-timber column interface during the process of strengthening timber column, a real-time monitoring method of CFRP-timber interface bond strength based on piezoelectric ceramic active sensing is proposed to determine the interface bond strength directly from the structural response signal. A total of 15 specimens were designed for the active monitoring test and tensile test, and the monitoring signals at different enhancement times were compared and analysed using wavelet packets, power spectral density, and short-time Fourier transform, and it was found that the amplitude and power spectral density of the signals increased as the reinforcement time increased. The mapping relationship between wavelet packet energy and bond strength is obtained, providing a more efficient and robust way of monitoring the bond strength between CFRP and timber columns during reinforcement.
Untwining multiple parameters at the exclusive zero-coincidence points with quantum control
Authors: Yang Yu , Belliardo Federico , Giovannetti Vittorio , Li Fuli 
Published: December 2022

Abstract
In this paper we address a special case of ‘sloppy’ quantum estimation procedures which happens in the presence of intertwined parameters. A collection of parameters are said to be intertwined when their imprinting on the quantum probe that mediates the estimation procedure, is performed by a set of linearly dependent generators. Under this circumstance the individual values of the parameters can not be recovered unless one tampers with the encoding process itself. An example is presented by studying the estimation of the relative time-delays that accumulate along two parallel optical transmission lines. In this case we show that the parameters can be effectively untwined by inserting a sequence of balanced beam splitters (and eventually adding an extra phase shift on one of the lines) that couples the two lines at regular intervals in a setup that remind us a generalized Hong-Ou-Mandel interferometer. For the case of two time delays we prove that, when the employed probe is the frequency-correlated biphoton state, the untwining occurs in correspondence of exclusive zero-coincidence (EZC) point. Furthermore we show the statistical independence of two time delays and the optimality of the quantum Fisher information at the EZC point. Finally we prove the compatibility of this scheme by checking the weak commutativity condition associated with the symmetric logarithmic derivative operators.
DAGAM: a domain adversarial graph attention model for subject-independent EEG-based emotion recognition
Authors: Xu Tao , Dang Wang , Wang Jiabao , Zhou Yun 
Published: December 2022

Abstract

Objective. Due to individual differences in electroencephalogram (EEG) signals, the learning model built by the subject-dependent technique from one person’s data would be inaccurate when applied to another person for emotion recognition. Thus, the subject-dependent approach for emotion recognition may result in poor generalization performance when compared to the subject-independent approach. However, existing studies have attempted but have not fully utilized EEG’s topology, nor have they solved the problem caused by the difference in data distribution between the source and target domains. Approach. To eliminate individual differences in EEG signals, this paper proposes the domain adversarial graph attention model, a novel EEG-based emotion recognition model. The basic idea is to generate a graph using biological topology to model multichannel EEG signals. Graph theory can topologically describe and analyze EEG channel relationships and mutual dependencies. Then, unlike other graph convolutional networks, self-attention pooling is used to benefit from the extraction of salient EEG features from the graph, effectively improving performance. Finally, following graph pooling, the domain adversarial model based on the graph is used to identify and handle EEG variation across subjects, achieving good generalizability efficiently. Main Results. We conduct extensive evaluations on two benchmark data sets (SEED and SEED IV) and obtain cutting-edge results in subject-independent emotion recognition. Our model boosts the SEED accuracy to 92.59% (4.06% improvement) with the lowest standard deviation (STD) of 3.21% (2.46% decrements) and SEED IV accuracy to 80.74% (6.90% improvement) with the lowest STD of 4.14% (3.88% decrements), respectively. The computational complexity is drastically reduced in comparison to similar efforts (33 times lower). Significance. We have developed a model that significantly reduces the computation time while maintaining accuracy, making EEG-based emotion decoding more practical and generalizable.
State of the art of evapotranspiration models for plant cultivation in open fields, greenhouse systems and plant factories
Authors: Arcasi A , Mastrullo R , Mauro A W , Pantaleo A M 
Published: December 2022

Abstract
The scarcity of water, the need to reduce of pesticides, the demand for on-site production of vegetables are moving the interest from greenhouse cultivation to indoor farming. Compared to greenhouses, indoor farms allow to reduce considerably the water consumption, requiring more energy, which could be provided by renewable sources. In order to assess the convenience of such a system, accurate preliminary calculations are needed for productivity, energy requirements and costs as a function of the type of cultivation and the operating conditions. While some knowledge (e.g. production rate or cooling system performance) are available from open literature, some specific predictive methods are required. Based on the few works available in literature about indoor farming, evapotranspiration rate resulted as a critical term. An assessment of different methods based on literature data with a critical analysis of their effectiveness based on several aspects (level of fidelity of the model, complexity in the calibration and use, potential strengths and weaknesses) is proposed in this work.
Social impact assessment of wind power generation. An innovative method for decision making processes
Authors: Fois V , Lecis L , Cocco D 
Published: December 2022

Abstract
This paper explores the social impact for population in the energy sector combining LCA and SIA (social impact assessment). As case study, a new 66 MW wind power plant under development in the countryside of Southern Sardinia has been considered. The innovative method, based on the analysis of the context, aims to empirically analyze some selected sustainability indicators. The proposed method starts from a detailed analysis of the wind power project, with particular reference to the plant site characteristics, technical features of the wind farm, opinions of the stakeholders, environmental and social impacts and expected economic benefits. The acquired data are validated with a Severity statistical method that identifies the KPIs. The indicators are classified into general categories of damage Human life, Safety guarantee, Social resources, Public participation and analyzed through a combined SIA-LCA method to identify indicators damage weights.
This work shows the importance of putting together indicators already explored in the environmental field such as Human health, Ecosystem quality, Resource, Climate Change and as social indicators Renewable Energy with Noise, Visual Impact, Shadow Flichers, the perceptions of the local community.
Data driven fault detection and diagnostics for hydronic and monitoring systems in a residential building
Authors: Abdollah M A F , Scoccia R , Aprille M 
Published: December 2022

Abstract
Buildings are responsible for 40% of the global energy use and associated with up to 30% of the total CO2 emissions. The drive to reduce the environmental impact of the built environment was the catalyst to the increasing installation of meters and sensors to monitor the energy use and environmental monitoring. This is key to cost effective Fault Detection and Diagnostics (FDD) which guarantees enhanced thermal comfort for the occupants and reduction in energy use. Most of FDD research work in buildings was focused on the commercial buildings due to the higher consumption and the higher saving potential, while limited work was directed towards residential buildings. This paper investigates the usage of two supervised machine learning algorithms, namely Random Forest, K nearest neighbour, to detect and diagnose twelve faults in both the monitoring system of the indoor/outdoor conditions, and the hydronic circuit inside an apartment located in Milan using minimal features that are easy to access and inexpensive to monitor to cut down in both computational and financial costs. The thermal zones are being conditioned using an electric air to water heat pump connected to fan coils for cooling and radiant floor for heating. The faults include valve leakage, faulty temperature sensors and recirculating pump’s inadequate flow rate. The faults were modelled in a Modelica based detailed model of the apartment. After tuning the hyper-parameters of all three algorithms, the Receiver Operator Characteristics curve for each fault were compared for each algorithm to compare the optimal one to be used. The Random Forest algorithms showed the highest accuracy with almost 89% across the twelve faults. Generalization of the trained algorithm across different weathers were tested but the results were not promising.
Decarbonization of the heating sector from a system point of view: the case study of the Lombardy Region.
Authors: Marianna Pozzi , Muliere Giuseppe , Mezzera Francesco , Fattori Fabrizio , Dénarié Alice , Motta Mario , Mazzarella Livio 
Published: December 2022

Abstract
This work aims at defining the optimal technological mix which minimizes the total cost of the energy system in 2030 in the Lombardy region, in northern Italy. The goal is reached through a bottom-up model built on a linear optimization problem considering different technical and economic inputs and constraints. Civil sector is one of the sectors to focus on for the decarbonization process. Different areas, types of buildings and thermal systems are included in the model to consider the peculiarities of the available solutions in each context. The overall technological mix is constraint by a CO2 emission limit. For the civil sector the more the emission is constrained, the higher is the penetrations of electric heat pumps, coupled with envelope retrofit, (10% of the total thermal energy demand) and of district heating (18%), while natural gas boilers decrease (66%). Biomass boilers reach a maximum penetration of 29% in mountain areas. District heating is relevant in areas with available sources (max 29%). Natural gas boilers coupled with air conditioners have an important role and they reach a maximum penetration of 89% in certain areas. Electric heat pumps are quite homogeneous through the areas for residential buildings.
A comparison between new European technical standards and dynamic simulation tools for chiller modelling
Authors: Bianco Mauthe Degerfeld F. , De Luca G. , Ballarini I. , Corrado V. 
Published: December 2022

Abstract
In the last years, new technical standards for the assessment of the energy efficiency of technical building systems were developed by the European Committee for Standardization (CEN). These procedures were conceived as to combine the easiness of the calculation methodologies and their related assumptions with a sufficient level of accuracy. While the former objective is often achieved, the latter is a challenging task as the procedures sometimes fail to simulate in a proper way the actual performance of the technical systems. On the other hand, the detailed procedures applied by detailed dynamic energy simulation tools are more precise and complex; however, for their application, they need a wide range of input data that are often hard to collect. For this reason, simplified procedures are now commonly applied, above all in the case of existing buildings. Nevertheless, these procedures need to be deeply analysed and validated. In this paper, the main standard calculation procedures addressed to chillers and specified in EN 16798-13:2017 were analysed, with a focus on the required input data and the calculation procedures. The same approach was then applied to the more detailed calculation methods used in the dynamic tools EnergyPlus and TRNSYS, and the results were compared. The theoretical analysis was then followed by a case study approach. A reference office building, representative of the Italian building stock, was selected and analysed in two different Italian climatic zones. The determination of the thermal energy need for cooling was performed by means of EnergyPlus, while the assessment of the energy demand related to technical building systems was performed both with EnergyPlus and with the standard procedures. This paper is part of a wider research activity finalised to the analysis of the technical building systems calculation procedures, taking into account different generation systems and thermal coupling modes between the technical systems and the building itself.
Numerical study of shell and tube latent thermal energy storage partially filled with metal foam and corrugated internal tube with external heat losses
Authors: Buonomo B , Golia M R , Manca O , Nardini S , Plomitallo R E 
Published: December 2022

Abstract
In the present work, a vertical shell and tube Latent Heat Thermal Energy Storage System is analyzed. The cylinder is filled with phase change material and parts of metal foam. The inner face of the cylinder is corrugated, and it is assumed a constant temperature over the melting temperature of the paraffin wax to simulate the heat transfer. The external surface loses heat to the outside and the top and bottom surfaces are adiabatic. Paraffin wax is used as phase change material that melts over a range of temperatures and has a high latent heat of fusion. The thermal conductivity of the phase change material is low and due to this, it is enhanced with metal foam. In this numerical simulation, it is used the aluminum foam. Enthalpy-porosity theory is used to simulate the phase transition process, and the Local Thermal Equilibrium and Darcy-Forchheimer models are used to examine heat transport between the paraffin and the metal foam. Using the commercial code Ansys-Fluent, the governing equations’ solutions are calculated. In the paper, it is considered different conductivity variations on the external wall and the distinct filling ratio of metal foam. The melting time, enthalpy stored, and energy loss from the numerical simulations of the LHTESS charging phase are provided as a function of time and evaluated.