Machine-learning assisted scheduling optimization and its application in quantum chemical calculations

Easy and effective usage of computational resources is crucial for scientific calculations, both from the perspectives of timeliness and economic efficiency. This work proposes a bi-level optimization framework to optimize the computational sequences. Machine-learning (ML) assisted static load-balancing, and different dynamic load-balancing algorithms can be integrated. Consequently, the computational and scheduling engine of the ParaEngine is developed to invoke optimized quantum chemical (QC) calculations. Illustrated benchmark calculations include high-throughput drug suit, solvent model, P38 protein, and SARS-CoV-2 systems. The results show that the usage rate of given computational resources for high throughput and large-scale fragmentation QC calculations can primarily profit, and faster accomplishing computational tasks can be expected when employing high-performance computing (HPC) clusters.

Comparison of Different Laboratory Methods for Clinical Detection of Brucella Infection

The rapidity, accuracy, and detection abilities of different laboratory methods (tube agglutination test (SAT), indirect ELISA, fluorescence polarization test (FPA), and blood culture methods) to detect Brucella in the laboratory. The study included 95 patients with documented and 42 patients with suspected brucellosis and 56 healthy control subjects. For the tests, the positive rates of Brucella infection detection in the confirmed group were significantly higher than in group with suspected infection (p<0.01) and in healthy controls (p<0.01). There was no significant difference between indirect ELISA and FPA in detecting antibodies to Brucella in acute (χ²=0.335), subacute (χ²=0.660), and chronic cases (χ²=5.332). Among the detection methods, indirect ELISA showed the highest sensitivity (98.9%), specificity (100%), and Youden index (0.989). The sensitivity and specificity of FPA were 96.8 and 96.4%, respectively. In order to easily and rapidly diagnose brucellosis in clinical practice, a combination of detection methods is recommended, in which Brucella antibodies are screened by FPA and then confirmed by indirect ELISA.