A subtraction procedure is proposed to evaluate the logarithmic singularity for matrix‐friendly layered medium Green's functions. In this subtraction procedure, an integral of the Bessel function ...combined with the exponential function and power function, where the sum of the power of kρ$k_{\rho }$ and the order of the Bessel function is −1, is designed to fit the oscillation of the tail integral. After subtracting the designed integral, the integrand of the remainder decreases rapidly. Accordingly, the remainder can be calculated without finding any surface poles or steepest descent path, while the subtracted part can be calculated analytically. Several numerical examples are provided to reveal the feasibility and the accuracy of the proposed method.
As a supplement to the canonical singularity subtraction method, the logarithmic singularities subtraction proposed in this work helps the terms in matrix‐friendly LMGFs be calculated efficiently and accurately without any specific integration paths. Besides, the logarithmic singularities in matrix‐friendly LMGFs, in which the sum of power of kP$k_{\text{P}}$ and the order of Bessel function is −1, are exactly subtracted by the proposed extraction procedure.
The application of electrochemical energy storage materials to capacitive deionization (CDI), a low‐cost and energy‐efficient technology for brackish water desalination, has recently been proven ...effective in solving problems of traditional CDI electrodes, i.e., low desalination capacity and incompatibility in high salinity water. However, Faradaic electrode materials suffer from slow salt removal rate and short lifetime, which restrict their practical usage. Herein, a simple strategy is demonstrated for a novel tubular‐structured electrode, i.e., polyaniline (PANI)‐tube‐decorated with Prussian blue (PB) nanocrystals (PB/PANI composite). This composite successfully combines characteristics of two traditional Faradaic materials, and achieves high performance for CDI. Benefiting from unique structure and rationally designed composition, the obtained PB/PANI exhibits superior performance with a large desalination capacity (133.3 mg g−1 at 100 mA g−1), and ultrahigh salt‐removal rate (0.49 mg g−1 s−1 at 2 A g−1). The synergistic effect, interfacial enhancement, and desalination mechanism of PB/PANI are also revealed through in situ characterization and theoretical calculations. Particularly, a concept for recovery of the energy applied to CDI process is demonstrated. This work provides a facile strategy for design of PB‐based composites, which motivates the development of advanced materials toward high‐performance CDI applications.
A novel tubular‐structured electrode material, i.e., polyaniline nanotubes decorated with Prussian blue nanocrystals, is demonstrated through a simple preparation strategy, which successfully combines the characteristics of two traditional Faradaic materials and achieves high‐performance capacitive deionization toward water desalination.
The 3d‐transition‐metal (hydro)oxides belong to a group of highly efficient, scalable and inexpensive electrocatalysts for widespread energy‐related applications that feature easily tailorable ...crystal and electronic structures. We propose a general strategy to further boost their electrocatalytic activities by introducing organic ligands into the framework, considering that most 3d‐metal (hydro)oxides usually exhibit quite strong binding with reaction intermediates and thus compromised activity due to the scaling relations. Involving weakly bonded ligands downshifts the d‐band center, which narrows the band gap, and optimizes the adsorption of these intermediates. For example, the activity of the oxygen evolution reaction (OER) can be greatly promoted by ≈5.7 times over a NiCo layered double hydroxide (LDH) after a terephthalic acid (TPA)‐induced conversion process, arising from the reduced energy barrier of the deprotonation of OH* to O*. Impressively, the proposed ligand‐induced conversion strategy is applicable to a series of 3d‐block metal (hydro)oxides, including NiFe2O4, NiCo2O4, and NiZn LDH, providing a general structural upgrading scheme for existing high‐performance electrocatalytic systems.
A general ligand‐induced conversion strategy was proposed to boost the electrocatalytic activities of 3d‐block metal (hydro)oxides. After the introduction of an organic ligand, the activity of the oxygen evolution reaction (OER) of NiCo layered double hydroxide (LDH) increased by ≈5.7 times.
A strategy for grid power peak shaving and valley filling using vehicle-to-grid systems (V2G) is proposed. The architecture of the V2G systems and the logical relationship between their sub-systems ...are described. An objective function of V2G peak-shaving control is proposed and the main constraints are formulated. The influences of the number of connected EVs and the average value of the target curve are analyzed. The rms and the standard deviation of the difference between the target and planned curves are proposed as indices for measuring the degree of matching between the two curves. The simulation results demonstrate that peaking shaving using V2G can be effective and controllable, and the proposed control algorithm is feasible.
Faces are the most commonly used stimuli to study emotions. Researchers often manipulate the emotion contents and facial features to study emotion judgment, but rarely manipulate low-level stimulus ...features such as face sizes. Here, I investigated whether a mere difference in face size would cause differences in emotion judgment. Subjects discriminated emotions in fear-happy morphed faces. When subjects viewed larger faces, they had an increased judgment of fear and showed a higher specificity in emotion judgment, compared to when they viewed smaller faces. Concurrent high-resolution eye tracking further provided mechanistic insights: subjects had more fixations onto the eyes when they viewed larger faces whereas they had a wider dispersion of fixations when they viewed smaller faces. The difference in eye movement was present across fixations in serial order but independent of morph level, ambiguity level, or behavioral judgment. Together, this study not only suggested a link between emotion judgment and eye movement, but also showed importance of equalizing stimulus sizes when comparing emotion judgments.
As an emerging research topic, online class imbalance learning often combines the challenges of both class imbalance and concept drift. It deals with data streams having very skewed class ...distributions, where concept drift may occur. It has recently received increased research attention; however, very little work addresses the combined problem where both class imbalance and concept drift coexist. As the first systematic study of handling concept drift in class-imbalanced data streams, this paper first provides a comprehensive review of current research progress in this field, including current research focuses and open challenges. Then, an in-depth experimental study is performed, with the goal of understanding how to best overcome concept drift in online learning with class imbalance.
To facilitate software testing, and save testing costs, a wide range of machine learning methods have been studied to predict defects in software modules. Unfortunately, the imbalanced nature of this ...type of data increases the learning difficulty of such a task. Class imbalance learning specializes in tackling classification problems with imbalanced distributions, which could be helpful for defect prediction, but has not been investigated in depth so far. In this paper, we study the issue of if and how class imbalance learning methods can benefit software defect prediction with the aim of finding better solutions. We investigate different types of class imbalance learning methods, including resampling techniques, threshold moving, and ensemble algorithms. Among those methods we studied, AdaBoost.NC shows the best overall performance in terms of the measures including balance, G-mean, and Area Under the Curve (AUC). To further improve the performance of the algorithm, and facilitate its use in software defect prediction, we propose a dynamic version of AdaBoost.NC, which adjusts its parameter automatically during training. Without the need to pre-define any parameters, it is shown to be more effective and efficient than the original AdaBoost.NC.
In this paper, a selective harmonic current mitigation pulsewidth modulation (SHCM-PWM) technique with low switching frequencies is proposed for grid-connected cascaded H-bridge multilevel rectifiers ...to fully meet harmonic requirements within extended harmonic spectrum. In the proposed technique, instead of using the voltage references to calculate switching angles for the rectifier as in conventional selective harmonic elimination-PWM (SHE-PWM) or selective harmonic mitigation-PWM (SHM-PWM), current references are used to compensate the current harmonics due to both grid voltage harmonics and rectifier input voltage harmonics so as to meet the current harmonic requirements and total demand distortion within the whole harmonic spectrum. Furthermore, the techniques to design the critical parameters including switching frequency, the highest harmonic order that can be mitigated using the proposed current-reference-based technique, and the coupling inductance that can attenuate the current harmonic orders above the highest order are investigated. With the same switching frequency, the proposed SHCM-PWM technique uses smaller coupling inductance to meet higher orders of current harmonic requirements than the conventional SHE-PWM technique. Finally, simulations and experiments were conducted to validate the proposed technique.
Starch Retrogradation: A Comprehensive Review Wang, Shujun; Li, Caili; Copeland, Les ...
Comprehensive reviews in food science and food safety,
September 2015, Letnik:
14, Številka:
5
Journal Article
Recenzirano
Starch retrogradation is a process in which disaggregated amylose and amylopectin chains in a gelatinized starch paste reassociate to form more ordered structures. Starch retrogradation has been the ...subject of intensive research over the last 50 years, mainly due to its detrimental effect on the sensory and storage qualities of many starchy foods. However, starch retrogadation is desirable for some starchy food products in terms of textural and nutritional properties. To better understand the effect of starch retrogradation on the quality of starchy foods, measurement methods of starch retrogradation and factors that influence starch retrogradation have been studied extensively. This article provides a comprehensive review of starch retrogradation including the definition of the process, molecular mechanisms of how it occurs, and measurement methods and factors that influence starch retrogradation. The review also discusses the effect of retrogradation on the in vitro enzyme digestibility of starch. Spectroscopic methods such as FTIR and Raman are considered to be very promising in characterizing starch retrogradation at a molecular level, although more studies are needed in the future.
Online class imbalance learning is a new learning problem that combines the challenges of both online learning and class imbalance learning. It deals with data streams having very skewed class ...distributions. This type of problems commonly exists in real-world applications, such as fault diagnosis of real-time control monitoring systems and intrusion detection in computer networks. In our earlier work, we defined class imbalance online, and proposed two learning algorithms OOB and UOB that build an ensemble model overcoming class imbalance in real time through resampling and time-decayed metrics. In this paper, we further improve the resampling strategy inside OOB and UOB, and look into their performance in both static and dynamic data streams. We give the first comprehensive analysis of class imbalance in data streams, in terms of data distributions, imbalance rates and changes in class imbalance status. We find that UOB is better at recognizing minority-class examples in static data streams, and OOB is more robust against dynamic changes in class imbalance status. The data distribution is a major factor affecting their performance. Based on the insight gained, we then propose two new ensemble methods that maintain both OOB and UOB with adaptive weights for final predictions, called WEOB1 and WEOB2. They are shown to possess the strength of OOB and UOB with good accuracy and robustness.
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