S-D614G Mutation Reveals the Euro-America and East-Asia Origin SARS-CoV-2 Virus Spread in Indonesia

COVID-19 is a pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The first case was found in the city of Wuhan, Hubei province, China. The first case in Indonesia was reported in March 2020 and currently there are 0.5 million cases with a death rate of 3.1%. This rapid increase in cases is thought to due to presence of the mutant strain S-D614G, which causes a faster rate of infection and spread. The purpose of this study was to determine the presence of S-D614G mutations in Indonesian samples in order to find the origin of COVID-19 which was spread in Indonesia based on the Spike gene sequences and the RdRp genes from 25 countries, and one control sequence China/Wuhan-Hu-1 obtained from the NCBI and GISAID databases. Mutation analysis was carried out through multiple alignments using BioEdit software. Phylogenetic tree reconstruction using MEGA6 software with the Neighbor Joining method. This study found mutation of S-D614G in one Indonesian sample, namely the Indonesian/SBY9 sample along with 23 samples from Europe, America, and Africa. The phylogenetic tree reconstruction confirmed these findings; the mutated samples were closely related to samples from these continents, while the non-mutated Indonesian samples were closely related to sample from East Asia. These findings indicate that the origin of the SARS-CoV-2 virus in Indonesia possibly came from the East Asia cluster and the European-American cluster.

Petroleum Reservoir Control Optimization with the Use of the Auto-Adaptive Decision Trees

The global increase in energy demand and the decreasing number of newly discovered hydrocarbon reservoirs caused by the relatively low oil price means that it is crucial to exploit existing reservoirs as efficiently as possible. Optimization of the reservoir control may increase the technical and economic efficiency of the production. In this paper, a novel algorithm that automatically determines the intelligent control maximizing the NPV of a given production process was developed. The idea is to build an auto-adaptive parameterized decision tree that replaces the arbitrarily selected limit values for the selected attributes of the decision tree with parameters. To select the optimal values of the decision tree parameters, an AI-based optimization tool called SMAC (Sequential Model-based Algorithm Configuration) was used. In each iteration, the generated control sequence is introduced into the reservoir simulator to compute the NVP, which is then utilized by the SMAC tool to vary the limit values to generate a better control sequence, which leads to an improved NPV. A new tool connecting the parameterized decision tree with the reservoir simulator and the optimization tool was developed. Its application on a simulation model of a real reservoir for which the CCS-EOR process was considered allowed oil production to be increased by 3.5% during the CO2-EOR phase, reducing the amount of carbon dioxide injected at that time by 16%. Hence, the created tool allowed revenue to be increased by 49%.

Efficiency improvement of dual three-phase permanent magnet synchronous motor using modified switching table DTC for electric ship propulsion

A direct torque control using a classical switching- table ST-DTC can be used to control the torque and thus the speed of Dual Three-Phase Permanent Magnet Synchronous Motor (DTP-PMSM). The principle is based on direct application of control sequence by using two hysteresis regulators and a switching table. A large stator current containing low order harmonics is produced during the application of the classic ST-DTC technique, this leads to higher losses affecting the efficiency of the machine. To allow a reduction of these harmonics a modified switching-table approach based DTC technique is examined. Indeed, an improved ST-DTC strategy, which consist of replacing the vectors of the classical table with synthetic vectors, is discussed. The simulation results confirm the validity of the selected strategy.

Dynamic Programming in Data Driven Model Predictive Control

In this short note, one data driven model predictive control is studied to design the optimal control sequence. The idea of data driven means the actual output value in cost function for model predictive control is identi_ed through input-output observed data in case of unknown but bounded noise and martingale di_erence sequence. After substituting the identi_ed actual output in cost function, the total cost function in model predictive control is reformulated as the other standard form, so that dynamic programming can be applied directly. As dynamic programming is only used in optimization theory, so to extend its advantage in control theory, dynamic programming algorithm is proposed to construct the optimal control sequence. Furthermore, stability analysis for data drive model predictive control is also given based on dynamic programming strategy. Generally, the goal of this short note is to bridge the dynamic programming, system identi_cation and model predictive control. Finally, one simulation example is used to prove the e_ciency of our proposed theory

GmNF-YC4-2 Increases Protein, Exhibits Broad Disease Resistance and Expedites Maturity in Soybean

The NF-Y gene family is a highly conserved set of transcription factors. The functional transcription factor complex is made up of a trimer between NF-YA, NF-YB, and NF-YC proteins. While mammals typically have one gene for each subunit, plants often have multigene families for each subunit which contributes to a wide variety of combinations and functions. Soybean plants with an overexpression of a particular NF-YC isoform GmNF-YC4-2 (Glyma.04g196200) in soybean cultivar Williams 82, had a lower amount of starch in its leaves, a higher amount of protein in its seeds, and increased broad disease resistance for bacterial, viral, and fungal infections in the field, similar to the effects of overexpression of its isoform GmNF-YC4-1 (Glyma.06g169600). Interestingly, GmNF-YC4-2-OE (overexpression) plants also filled pods and senesced earlier, a novel trait not found in GmNF-YC4-1-OE plants. No yield difference was observed in GmNF-YC4-2-OE compared with the wild-type control. Sequence alignment of GmNF-YC4-2, GmNF-YC4-1 and AtNF-YC1 indicated that faster maturation may be a result of minor sequence differences in the terminal ends of the protein compared to the closely related isoforms.

Averaged No-Regret Control for an Electromagnetic Wave Equation Depending upon a Parameter with Incomplete Initial Conditions

This chapter concerns the optimal control problem for an electromagnetic wave equation with a potential term depending on a real parameter and with missing initial conditions. By using both the average control notion introduced recently by E. Zuazua to control parameter depending systems and the no-regret method introduced for the optimal control of systems with missing data. The relaxation of averaged no-regret control by the averaged low-regret control sequence transforms the problem into a standard optimal control problem. We prove that the problem of average optimal control admits a unique averaged no-regret control that we characterize by means of optimality systems.

Human Rev1 relies on insert-2 to promote selective binding and accurate replication of stabilized G-quadruplex motifs

We previously reported that human Rev1 (hRev1) bound to a parallel-stranded G-quadruplex (G4) from the c-MYC promoter with high affinity. We have extended those results to include other G4 motifs, finding that hRev1 exhibited stronger affinity for parallel-stranded G4 than either anti-parallel or hybrid folds. Amino acids in the αE helix of insert-2 were identified as being important for G4 binding. Mutating E466 and Y470 to alanine selectively perturbed G4 binding affinity. The E466K mutant restored wild-type G4 binding properties. Using a forward mutagenesis assay, we discovered that loss of hRev1 increased G4 mutation frequency >200-fold compared to the control sequence. Base substitutions and deletions occurred around and within the G4 motif. Pyridostatin (PDS) exacerbated this effect, as the mutation frequency increased >700-fold over control and deletions upstream of the G4 site more than doubled. Mutagenic replication of G4 DNA (±PDS) was partially rescued by wild-type and E466K hRev1. The E466A or Y470A mutants failed to suppress the PDS-induced increase in G4 mutation frequency. These findings have implications for the role of insert-2, a motif conserved in vertebrates but not yeast or plants, in Rev1-mediated suppression of mutagenesis during G4 replication.

Analysis and Countermeasures of Abnormal Operation of Unloading Circuit

Taking the two position two way valve unloading circuit, accumulator unloading circuit, double pump unloading circuit, liquid control sequence valve unloading circuit as examples, the paper analyses the reason of abnormal operation of several hydraulic unloading circuit, puts forward concrete measures, which provides basis for design and operation of hydraulic system.