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Due to phase angle measured by phase locked loop has phase difference with grid positive sequence fundamental voltage of traditional id-iq harmonic detection method in grid voltage asymmetry and distortion phase, at the same time, low pass filter performance used in traditional id-iq harmonic detection method will influence accuracy and real-time performance, an improved id-iq harmonic detection algorithm was proposed, namely using of fundamental positive sequence current with good symmetry to instead of instantaneous voltage to lock phase, so as to eliminate measured phase difference of phase angle of power grid, and using of average value theory to replace function of the low pass filter，in order to reduce time delay and improve real-time performance and detection accuracy of the algorithm. The Matlab/Simulink simulation result proves that the algorithm is correctness.

Background and Objectives: Safety aspects regarding free asparagine concentration in wheat arise because of its acrylamide formation potential in baked wheat products. Free asparagine concentration in wheat is affected by environment, genotype, and nitrogen and sulfur fertilization, which also affect wheat protein content and composition. Changing protein content and composition affects gluten strength, altering product quality. This study investigated how gluten strength was affected by environment, genotype, and fertilization treatments grown under commercially relevant conditions. Findings: Environment predominated in affecting dough extensibility and genotype primarily affected resistance to extension, with minimal effects from fertilization treatments. Differences in extensigraph parameters at two resting times segregated genotypes according to gluten strength. Conclusions: Factors affecting free asparagine accumulation in wheat also affect gluten strength. Genotype and environment require primary attention since they play an important role in both wheat safety and quality. Significance and Novelty: The lack of studies investigating the impact of factors affecting free asparagine concentration on the gluten strength of wheat has implications for the global wheat market. From a novel perspective on dough extensibility and resistance to extension, the effects of environment, genotype, and fertilization on the gluten strength of commercially important wheat varieties are considered in a food safety context. [ABSTRACT FROM AUTHOR]

Background and objectives: The presence of acrylamide, a probable carcinogen, is a global concern for the baking industry. The reduction of free asparagine in wheat is an effective strategy to mitigate acrylamide formation. However, field‐based strategies for this purpose also affect gluten strength and bread quality. Therefore, we investigated the relationship between wheat free asparagine concentration, gluten strength and whole wheat bread quality for an extensive set of hard red spring wheat samples. Findings: Gluten strength parameters negatively correlated to wheat free asparagine concentration and showed strong inverse correlations to wheat free asparagine concentration per unit mass of protein. Reducing free asparagine concentration in the wheat did not affect the quality of the bread. Conclusions: In efforts to deliver wheat grains with a low acrylamide‐formation potential, wheat producers can apply strategies, for example, variety selection, that will reduce free asparagine without worries that gluten strength and bread quality will be impaired. Significance and novelty: Safety concerns regarding free asparagine in wheat have elicited much attention from cereal scientists and the breadmaking industry. However, the effects of reducing free asparagine on gluten strength have not been systematically studied in the literature. This comprehensive study shows that there is an inverse relationship between gluten strength and wheat free asparagine concentration. [ABSTRACT FROM AUTHOR]

In silico toxicity prediction plays an important role in the regulatory decision making and selection of leads in drug design as in vitro/vivo methods are often limited by ethics, time, budget, and other resources. Many computational methods have been employed in predicting the toxicity profile of chemicals. This review provides a detailed end-to-end overview of the application of machine learning algorithms to Structure-Activity Relationship (SAR)-based predictive toxicology. From raw data to model validation, the importance of data quality is stressed as it greatly affects the predictive power of derived models. Commonly overlooked challenges such as data imbalance, activity cliff, model evaluation, and definition of applicability domain are highlighted, and plausible solutions for alleviating these challenges are discussed. [ABSTRACT FROM AUTHOR]

Highlights: [•] The Bi2O3 hollow microspheres were synthesized via template-free solvothermal method. [•] The β- and α-Bi2O3 were obtained by calcination at 270°C and 350°C, respectively. [•] The formation mechanism of α- and β-Bi2O3 hollow sphere structure was proposed. [•] The β-Bi2O3 hollow microspheres showed superior photocatalytic activity than α-Bi2O3. [ABSTRACT FROM AUTHOR]