Miracle-dz/UniFAR-FTUs huggingface dataset:
Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Capacity Estimation and Box-Cox Transformation

Remaining useful life (RUL) prediction of lithium-ion batteries plays an important role in intelligent battery management systems (BMSs). The current RUL prediction methods are mainly developed based on offline training, which are limited by sufficiency and reliability of available data. To address this problem, this paper presents a method for RUL prediction based on the capacity estimation and the Box-Cox transformation (BCT). Firstly, the effective aging features (AFs) are extracted from electrical and thermal characteristics of lithium-ion batteries and the variation in terms of the cyclic discharging voltage profiles. The random forest regression (RFR) is then employed to achieve dependable capacity estimation based on only one cell's degradation data for model training. Secondly, the BCT is exploited to transform the estimated capacity data and to construct a linear model between the transformed capacities and cycles. Next, the ridge regression algorithm (RRA) is adopted to identify the parameters of the linear model. Finally, the identified linear model based on the BCT is employed to predict the battery RUL, and the prediction uncertainties are investigated and the probability density function (PDF) is calculated through the Monte Carlo (MC) simulation. The experimental results demonstrate that the proposed method can not only estimate capacity with errors of less than 2%, but also accurately predict the battery RUL with the maximum error of 127 cycles and the maximum spans of 95% confidence of 37 cycles in the whole cycle life.
X-ray Structure of Ammonia−Cellulose I: New Insights into the Conversion of Cellulose I to Cellulose IIII

A supercritical ammonia treatment has been used to trap an ammonia−cellulose complex during the conversion of cellulose I to cellulose IIII. The crystal and molecular structure of this complex, designated ammonia−cellulose I, has been determined by using X-ray fiber diffraction data (space group P21; a = 4.47 A, b = 8.81 A, c = 10.34 A, γ = 92.7°). Although the existence of ammonia−cellulose I has been known for some time, this is the first report of its crystal structure. A one-chain monoclinic unit cell has an asymmetric unit that contains only one glucosyl residue and one ammonia molecule. The ammonia molecule acts as a bridge between hydrogen-bonded sheets, forming extended chains of cooperative hydrogen bonds. The sheets are similar to those found in cellulose IIII, with O2···O6 intrasheet hydrogen bonds and the gt conformation of the hydroxymethyl group providing potential bifurcated O3···O5 and O3···O6 intrachain hydrogen bonds. This new structure provides a number of insights into the structural t.
Synthesis and Characterization of Luminescent Nanoclays

Hydrotalcite nanocrystals doped with Eu(III) ions were prepared by the microemulsion method. XRPD measurements revealed that europium ions are very likely incorporated in a low-symmetry hydrotalcite-type layer. TEM and AFM imaging indicated that nanocrystals have a 150 nm width and a plate shape. Luminescence measurements showed that the doped powder is luminescent and the Eu(III) ions are located in a low symmetry site.
SOLVATION STRUCTURE AROUND AQUEOUS ALCOHOLS

Molecular dynamics simulations have been used to characterize the structure of water around n-alcohols (methanol to butanol) in dilute aqueous solution. A number of different analyses have been used to examine the extent to which the alcohol modifies the behavior of neighboring water molecules. These include radial distribution functions, specific order parameters designed to probe for ice- and clathrate-like local structures, and velocity and orientational time correlation functions. The static structure of water around the hydrophobic end of the alcohol was found to be essentially the same as that found in bulk water; in particular, there was no evidence of clathrate-like cages around the hydrophobic end of the alcohol. Some enhancement of the water structure was found in the vicinity of the alcohol hydroxyl group, with the hydrogen bonding network being closer to tetrahedral in the solvation shell than in bulk water; however, this enhancement was unaffected by the length of the associated hydrophobic c.
Synthesis of fluorine-doped multi-layered graphene sheets by arc-discharge

Fluorine-doped graphene sheets (F-doped GSs) were synthesized by arc discharge. The products were characterized by scanning and transmission electron microcopies, X-ray diffraction, Raman and X-ray photoelectron spectroscopies. The F-doped GSs contain about 10 wt% F. They are mainly multi-layered, with a much larger size than pure GSs, and are super-hydrophobic.
Collaboration: Reflections on an Academic Career

One recently retired nurse educator reflects on the role of collaboration in her academic career, especially in developing an innovative curriculum and a programme of research. The paper traces the author’s experiences over time and how an academic career can be cultivated through collaborations, some planned and some unplanned. The paper culminates in seven lessons learned about collaboration the author is passing along as a result of her experiences.
Resonance Raman and absorption characterization of cationic Co(II)-porphyrin in its complexes with nucleic acids: binding modes, nucleic base specificity and role of water in Co(II) oxidation processes

A comparative study of Co(II) and Co(III) complexes of the water-soluble cationic tetrakis(N-methyl-4-pyridiniumyl)porphyrin [CoII- and CoIIITMpyP(4)] with calf thymus DNA (CT DNA) and synthetic double-stranded (ds) and single-stranded (ss) polynucleotides, namely, poly(dA-dT)2, poly(dG-dC)2, [poly(dA)·poly(dT)], poly(A), poly(dT), poly(G) and poly(C) was carried out by resonance Raman (RR) as well as stationary absorption spectroscopy. It is shown that free CoIITMpyP(4) in aqueous solution is easily oxidized to CoIIITMpyP(4) by dissolved molecular oxygen, but Co(II) to Co(III) oxidation ability fundamentally changes when CoIITMpyP(4) is bound to nucleic acids (NA). In double helical DNA and AT-containing polynucleotides, where the porphyrin is assumed to be outside bound mainly in the minor groove near AT sites, Co(II) is stable for weeks and even months. It is suggested that Co(II) axial ligation by immobilized water (i.e. water molecule that is hydrogen bound to O or N atoms from DNA bases) results in such CoIITMpyP(4) stabilization. In contrast, CoIITMpyP(4) binding with ds and ss guanine-containing polynucleotides results in instantaneous Co(II) to Co(III) transformation. This can be explained by Co ion ligation by the guanine N7 atoms, which are known to be strong electron-donating ligands. It is assumed that partial intercalation occurs when CoIITMpyP(4) is bound with poly(dG-dC)2, in particular, at low ionic strength values, where cobalt ion is Co(III) in character. Copyright © 2005 John Wiley & Sons, Ltd.
Synthesis of Calcium Phosphate Nanofilaments in Reverse Micelles

Reverse micelles of calcium bis(2-ethylhexyl)phosphate (Ca(DEHP)2) were used to synthesize calcium phosphate nanostructures from a reaction mixture initially containing a water-in-cyclohexane emulsion of Ca(DEHP)2, ammonium hydrogen phosphate, and triblock copolymer, P123. Bundles of DEHP-coated amorphous calcium phosphate nanofilaments, 2 nm in width and >300 μm in length were formed in the oil layer of a phase-separated reaction mixture prepared at a [Ca]:[PO4] molar ratio of 1:1 and pH of 8.2. The nanofilament bundles were stable in the reverse micelle phase up to around 5 days, after which they transformed into 5-nm-wide surfactant-coated hydroxyapatite nanorods. In contrast, similar experiments at a higher supersaturation level (pH = 9, [Ca]:[PO4] = 1.66) produced discrete nanofilaments (100−500 × 10−15 nm in size) that consisted of a linear superstructure based on the side-on stacking of surfactant-coated amorphous calcium phosphate nanorods. Possible factors giving rise to these ordered nanostructu.
Multiscale 2-D Singular Spectrum Analysis and Principal Component Analysis for Spatial–Spectral Noise-Robust Feature Extraction and Classification of Hyperspectral Images

In hyperspectral images (HSI), most feature extraction and data classification methods rely on corrected dataset, in which the noisy and water absorption bands are removed. This can result in not only extra working burden but also information loss from removed bands. To tackle these issues, in this article, we propose a novel spatial–spectral feature extraction framework, multiscale 2-D singular spectrum analysis (2-D-SSA) with principal component analysis (PCA) (2-D-MSSP), for noise-robust feature extraction and data classification of HSI. First, multiscale 2-D-SSA is applied to exploit the multiscale spatial features in each spectral band of HSI via extracting the varying trends within defined windows. Taking the extracted trend signals at each scale level as the input features, the PCA is employed to the spectral domain for dimensionality reduction and spatial–spectral feature extraction. The derived spatial–spectral features in each scale are separately classified and then fused at decision-level for efficacy. As our 2-D-MSSP method can extract features and simultaneously remove noise in both spatial and spectral domains, which ensures it to be noise-robust for classification of HSI, even the uncorrected dataset. Experiments on three publicly available datasets have fully validated the efficacy and robustness of the proposed approach, when benchmarked with 10 state-of-the-art classifiers, including six spatial–spectral methods and four deep learning classifiers. In addition, both quantitative and qualitative assessment has validated the efficacy of our approach in noise-robust classification of HSI even with limited training samples, especially in classifying uncorrected data without filtering noisy bands.
On-Line Fault Diagnosis of DC-Link Electrolytic Capacitors in Boost Converters Using the STFT Technique

Faults in aluminum electrolytic capacitors (AECs) are classified as the major cause for power electronics equipment breakdown, mainly due to AECs wear out through the vaporization of the electrolyte, as a result of both aging and temperature effects. The majority of manufacturers identify the end-of-life threshold of such capacitors as their equivalent series resistance (ESR) increases by 80% or their capacitance (C) decreases by 20%, relative to their initial values. Therefore, the online estimation of these two parameters can provide valuable and timely information that allows detecting any potential capacitor failure. Changes in C and ESR parameters influence the relationship between the capacitor voltage and current ripples. This ratio is dominated by C at low frequencies, and by ESR in the high-frequency range. The aim of this article is to propose an algorithm allowing a continuous estimation and tracking of both parameters (ESR and C). This algorithm should be simple, fast, and suitable for online implementation. Therefore, this article introduces the use of the short-time Fourier transform (STFT) technique to determine and track C and ESR values, starting from some always-existing harmonics at low and high frequencies. The STFT is based on applying the discrete Fourier transform algorithm on a sliding window, which makes it more appropriate for online implementation. The effectiveness of the proposed method is proved by simulation and laboratory experiments, using a boost dc–dc converter.
Network-Assisted Full-Duplex Distributed Massive MIMO Systems With Beamforming Training Based CSI Estimation

Network-assisted full-duplex (NAFD) distributed massive multiple-input multiple-output (MIMO) systems enable simultaneous uplink and downlink communications by dynamically allocating the numbers of uplink and downlink remote antenna units (RAUs), which potentially improve the spectral efficiency in wireless communications. In such systems, channel state information (CSI) plays a critical role in uplink reception and downlink transmission, as well as the cross link interference cancelation caused by downlink RAUs to uplink RAUs. Moreover, downlink terminals need to estimate CSI to reliably decode the received signals due to the reduced channel hardening effect. However, high training overhead makes it generally impossible to directly estimate CSI. This paper proposes to estimate effective CSI (inner products of beamforming and channel vectors) instead based on beamforming training scheme. Under this scheme, we derive closed-form expressions for uplink and downlink achievable rates with different receivers and beamforming. Given these expressions, we propose an efficient power allocation scheme which is only dependent on slowly varying large-scale fading from the perspective of multi-objective optimization. Numerical results verify the accuracy of the derived closed-form expressions and effectiveness of beamforming training based CSI estimation. Moreover, trade-off regions between the considered optimization objectives under various system parameters offer numerous flexibilities for system optimization.
Design and Experimental Validation of Robust Self-Scheduled Fault-Tolerant Control Laws for a Multicopter UAV

In recent years, multicopter unmanned aerial vehicles (UAV) have been widely used in many commercial and military applications. Due to the increasing requirement for high autonomy and safety, UAVs should possess a fault-tolerant ability to accommodate malfunctions during flight. This article presents two fault-tolerant control (FTC) designs for a multicopter UAV subject to actuator faults. The proposed FTC approach is based on gain-scheduling (GS) control in the framework of structured $\mathcal {H}_\infty$ synthesis. The scheduled gains of the first controller are parameterized as polynomial functions of the loss of actuator effectiveness, given by an appropriate fault detection and diagnosis system. In order to facilitate the tuning process, the second controller uses the loss of virtual control effectiveness as the GS variable. Experimental results performed on an hexacopter UAV show the effectiveness and the robustness of these methods subject to multiple critical actuator faults.
Energy-Efficient Operation of Massive MIMO in Industrial Internet-of-Things Networks

Massive multiple-input–multiple-output (MIMO) can be effectively applied to the data gathering system of Industrial Internet-of-Things (IIoT) networks. For long-term maintenance of industrial electronic systems with battery-limited IIoT devices, it is essential to increase the energy efficiency (EE) of the system. The high EE should be achieved with ultrareliability and low latency because there are a lot of critical information for the IIoT networks. With this in mind, in this article, we propose high EE operation schemes for the massive MIMO-based IIoT networks. An orthogonal multiple access (OMA) scheme is used and a signal clipping technique is applied to increase the EE of the industrial data gathering system. Clipping distortion for uplink massive MIMO with massive IIoT connectivity is analyzed, and we show that clipping distortion of maximum ratio (MR) processing is directly proportional to the number of service antennas and the number of IIoT devices, while that of zero-forcing (ZF) processing can be reduced as the number of IIoT devices increases. We define the EE metric and derive the closed-form inverses of the EE metric to determine the relevant parameters. Based on the derived closed-form equations, we introduce the EE operation schemes using low-latency parameter determination methods. Simulation results validate the theoretical analysis.
Design and Implementation of a Criticality- and Heterogeneity-Aware Runtime System for Task-Parallel Applications

Heterogeneous multiprocessing (HMP) is an emerging technology for high-performance and energy-efficient computing. While task parallelism is widely used in various computing domains, such as embedded, big-data, and machine-learning computing domains, it still remains unexplored to investigate the efficient runtime support that effectively utilizes the criticality of the tasks of the target application and the heterogeneity of the underlying HMP system with full resource management. To bridge this gap, we propose CHRT, a criticality- and heterogeneity-aware runtime system for task-parallel applications. CHRT dynamically estimates the performance and power consumption of the target task-parallel application and robustly manages the full HMP system resources (i.e., core types, counts, and voltage/frequency levels) to maximize the overall efficiency. Our quantitative evaluation based on widely-used task parallel benchmarks and two full HMP systems (i.e., the XU3 and HiKey970 HMP systems) demonstrates the effectiveness of CHRT in that CHRT achieves significantly higher energy (e.g., 60.4 and 57.2 percent on average on the XU3 system) and energy-delay product (e.g., 52.2 and 44.0 percent on average on the HiKey970 system) efficiency than the baseline runtime system that employs the breadth-first scheduler and the state-of-the-art criticality-aware runtime system and incurs low performance overheads.
Autoregressive Model-Based Signal Reconstruction for Automotive Radar Interference Mitigation

Automotive radars have become an important part of sensing systems in vehicles and other traffic applications due to their accuracy, compact design, and robustness under severe light and weather conditions. The increased use of radars in various traffic applications has given rise to the problem of mutual interference, which needs to be mitigated. In this paper, we investigate interference mitigation in chirp sequence (CS) automotive radars via signal reconstruction based on autoregressive (AR) models in fast- and slow-time. The interference is mitigated by replacing the disturbed baseband signal samples with samples predicted using the estimated AR models. Measurements from 77GHz frequency modulated continuous wave (FMCW) static and moving radars are used to evaluate the signal reconstruction performance in terms of the signal-to-interference-plus-noise ratio (SINR), peak side-lobe level (PSLL), and mean squared error (MSE). The results show that the interference is suppressed down to the general noise floor, leading to an improvement in the SINR. Additionally, enhanced side-lobe suppression is achieved via AR signal reconstruction, which is compared to a commonly used inverse-cosine method. Furthermore, the paper notes that the slow-time signal reconstruction can be more beneficial for interference suppression in certain scenarios.
Characterization of styrene recovery from the pyrolysis of waste expandable polystyrene

Catalytic and thermal degradation of waste expandable polystyrene (WEPS) have been studied in a semi-batch reactor with continuous flow of nitrogen to achieve greater oil yield and maximize styrene monomer recovery. Effect of temperature, nature of catalyst and its size, reaction time of catalytic pyrolysis, and effect of repyrolysis have been also investigated. Higher reaction temperature favors the oil yield and also decreases the reaction time with maximum styrene selectivity (76.31 wt %) at 450 °C. Among the catalysts studied, solid base BaO is found to be the most efficient and increases the styrene selectivity (84.29 wt %) significantly at a reaction temperature of 350 °C in comparison to thermal and acid catalytic degradation. Modified catalyst Fe−A/Al (A = basic material) also shows better activity than Fe2O3 or Fe/Al. Increase in the size of the catalyst and repyrolysis decrease the oil yield, and styrene production also decreases on repyrolysis.
Dielectric spectra of mono- and disaccharide aqueous solutions

Complex (dielectric) permittivity spectra of aqueous solutions of the monosaccharides D-Xylose, D-Galactose, D-Glucose, D-Fructose, Methyl-β-D-xylose, and Methyl-β-D-glucose, as well as the disaccharides D-Lactose, D-Maltose, and D-Sucrose have been measured. In order to avoid any systematic errors, various experimental setups, each matched to a particular measuring range, have been used to cover the frequency domain from 300 kHz to 40 GHz. In some characteristic details our spectra for maltose solutions deviate from those recently reported by Weingartner et al. [J. Chem. Phys. 115, 1463 (2001)]. The monosaccharide spectra at c=1 mol/l and the disaccharide spectra at c⩽0.5 mol/l reveal a rather homogeneous relaxation of the carbohydrate and water dipole moments, which can be well represented by a Cole–Cole relaxation time distribution. At higher solute concentration the dielectric spectra are favorably represented by two relaxation terms, though interpolation of the experimental data by the Cole–Cole spec.
Learning to Generate Explainable Plots for Neural Story Generation

Story generation is an importantnatural language processing task that aims to generate coherent stories automatically. While the use of neural networks has proven effective in improving story generation, how to learn to generate an explainable high-level plot still remains a major challenge. In this article, we propose a latent variable model for neural story generation. The model treats an outline, which is a natural language sentence explainable to humans, as a latent variable to represent a high-level plot that bridges the input and output. We adopt an external summarization model to guide the latent variable model to learn how to generate outlines from training data. Experiments show that our approach achieves significant improvements over state-of-the-art methods in both automatic and human evaluations.
Influence of the Emission Site on the Running Durability of Organic Electroluminescent Devices

The influence of the emission site on the running durability of organic electroluminescent devices was examined. The fundamental device structure of MgIn/BeBq2/TPD/MTDATA/ITO ( BeBq2=bis(10-hydroxybenzo[h]quinolinato)beryllium, TPD=N,N′-diphenyl-N,N′-(3-methylphenyl)-1,1′-biphenyl-4,4′-diamine, MTDATA=4,4′,4′′-tris(3-methylphenylphenylamino)triphenylamine) was employed. BeBq2 has the electron transport property, and TPD and MTDATA have the hole transport property. The emitting material [rubrene] was doped in the TPD layer of device A and in the BeBq2 layer of device B. Both devices A and B showed high luminance of more than 10000 cd/m2. However, the running lifetimes of devices A and B, in which the initial luminance of 500 cd/m2 was reduced to one-half under a constant driving current, were 3554 h and 110 h, respectively. It was thus found that the emission site exerts an influence on the running durability.
Field Measurement of Ambient Odors with a Butanol Olfactometer

ABSTRACT A1-butanol olfactometer was used to measure ambient odor intensities at feedlots, meat packing and rendering plants, oil refineries, and other sources. The ambient odor intensities determined by odor panels using the butanol olfactometer were equivalent to 1.25 and 56.6 ppm of 1-butanol vapor in air. The precision of ambient odor measurements was within one-half step on the butanol scale. The method is precise enough for most odor investigations and abatement research.