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BackgroundAdverse drug reactions (ADRs), which are the phenotypic manifestations of clinical drug toxicity in humans, are a major concern in precision clinical medicine. A comprehensive evaluation of ADRs is helpful for unbiased supervision of marketed drugs and for discovering new drugs with high success rates. ObjectiveIn current practice, drug safety evaluation is often oversimplified to the occurrence or nonoccurrence of ADRs. Given the limitations of current qualitative methods, there is an urgent need for a quantitative evaluation model to improve pharmacovigilance and the accurate assessment of drug safety. MethodsIn this study, we developed a mathematical model, namely the Adverse Drug Reaction Classification System (ADReCS) severity-grading model, for the quantitative characterization of ADR severity, a crucial feature for evaluating the impact of ADRs on human health. The model was constructed by mining millions of real-world historical adverse drug event reports. A new parameter called Severity_score was introduced to measure the severity of ADRs, and upper and lower score boundaries were determined for 5 severity grades. ResultsThe ADReCS severity-grading model exhibited excellent consistency (99.22%) with the expert-grading system, the Common Terminology Criteria for Adverse Events. Hence, we graded the severity of 6277 standard ADRs for 129,407 drug-ADR pairs. Moreover, we calculated the occurrence rates of 6272 distinct ADRs for 127,763 drug-ADR pairs in large patient populations by mining real-world medication prescriptions. With the quantitative features, we demonstrated example applications in systematically elucidating ADR mechanisms and thereby discovered a list of drugs with improper dosages. ConclusionsIn summary, this study represents the first comprehensive determination of both ADR severity grades and ADR frequencies. This endeavor establishes a strong foundation for future artificial intelligence applications in discovering new drugs with high efficacy and low toxicity. It also heralds a paradigm shift in clinical toxicity research, moving from qualitative description to quantitative evaluation.

ObjectiveTo investigate the use of contraceptive methods， and to evaluate maternal healthcare services utilization among women within 2 years in Pudong New Area of Shanghai.MethodsA cross-sectional survey was conducted using a questionnaire for women at different postpartum periods who visited a community health clinic with their children from June to November 2021. Data were analyzed using χ2 test and binary logistic regression.ResultsAmong the 1 946 postpartum women surveyed， 1 934 were either married or cohabiting， and 1 430 had resumed their sexual life. Among women at 4， 6， 12， 18 and 24 months postpartum， the contraceptive prevalence rates （CPR） were 92.34% （193/209）， 92.16% （235/255）， 87.31% （282/323）， 91.95% （297/323） and 90.00% （288/320）， respectively. The modern contraceptive prevalence rates （mCPR） were 87.08% （182/209）， 87.06% （222/255）， 82.04% （265/323）， 83.09% （271/323） and 85.31% （273/320）， respectively， while the unmet contraceptive needs （UMNs） were 7.66% （16/209）， 7.84% （20/255）， 11.46% （37/323）， 6.81% （22/323） and 10.00% （32/320）， respectively. The use rates of long-acting reversible contraceptive （LARC） methods among women at 6， 12， 18 and 24 months postpartum period were 0.39% （1/255）， 2.17% （7/323）， 0.31% （1/323）， and 2.81% （9/320）， respectively. Among all surveyed subjects， 32.17% （626/1 946） had received postpartum contraceptive services only once， while 27.85% （542/1 946） had not received any postpartum contraceptive services. Binary logistic regression analysis indicated that the use of contraceptive methods among postpartum women was associated with whether relevant educational services were received after childbirth and during postpartum home visits （all P

Bamboo is widely used in the construction industry due to its excellent mechanical properties, short production cycle, and environmental concerns. Reconstructing and processing bamboo into biomass-based composite materials that can replace wood alleviates the imbalance between wood supply and demand. This article uses cold press setting and hot press curing molding processes to prepare small samples of Hexagonal Recombinant Bamboo Material (glued HexBam). Through orthogonal analysis, the preparation process parameters, adhesive types, adhesive application amounts, and the relationship between the temperature and time of hot pressing solidification molding and the mechanical properties of glued HexBam were determined. A phenolic adhesive (PF) was used with a dosage of 200 g/m2, a heat setting and molding temperature of 130 °C, and a heat setting molding time of 10 minutes. Under these process conditions, the prepared glued HexBam had a longitudinal compressive strength of 73.8 MPa and a specific strength of 0.0535 N•m/kg, which is superior to ordinary steel.

Drought stress severely impairs common bean production. For facilitating drought-resistance breeding in common bean, molecular markers were identified in a genome-wide level marker–trait association study. A panel of 210 common bean accessions showed large variation in 11 agronomic traits at the adult stage (plant height, pod number per plant, seed number per pod, seed number per plant, seed yield per plant, pod length, harvest index, pod harvest index, days to maturity, hundred-seed weight, and seed yield) under two water conditions. The coefficient of variation ranged from 6.21% for pod harvest index to 51.00% for seed number per plant under well-watered conditions, and from 4.05% for days to maturity to 40.72% for seed number per plant under drought stress. In a genome-wide association study, 119 quantitative-trait loci were associated with drought resistance, including 41 adjacent to known loci. Among these loci, 12 were found to be associated with at least two traits. Three major loci were identified at Pv01 and Pv02. A set of candidate genes were found that encode MYBs, AREBs, WKRYs, and protein kinases. These results reveal promising alleles that control drought resistance, shedding light on the genetic basis of drought resistance and accelerating future efforts for drought resistance improvement in common bean.

Abstract Given the “carbon neutralization and carbon peak” policy, enhancing the low voltage ride-through (LVRT) capability of wind farms has become a current demand to ensure the safe and stable operation of power systems in the context of a possible severe threat of large-scale disconnection caused by wind farms. Currently, research on the LVRT of wind farms mainly focuses on suppressing rotor current and providing reactive current support, while the impact of active current output on LVRT performance has not been thoroughly discussed. This paper studies and reveals the relationship between the limit of reactive current output and the depth of voltage drop during LVRT for doubly-fed induction generator (DFIG) based wind farms. Specifically, the reactive current output limit of the grid-side converter is independent of the depth of voltage drop, and its limit is the maximum current allowed by the converter, while the reactive current output limit of the DFIG stator is a linear function of the depth of voltage drop. An optimized scheme for allocating reactive current among the STATCOM, DFIG stator, and grid-side converter is proposed. The scheme maximizes the output of active current while satisfying the standard requirements for reactive current output. Compared to traditional schemes, the proposed LVRT optimization strategy can output more active power during the LVRT period, effectively suppressing the rate of rotor speed increase, and improving the LVRT performance and fault recovery capability of wind farms. Simulation results verify the effectiveness of the proposed scheme.

Abstract The virtual synchronous generator (VSG) is a good solution for stabilizing the power system with high penetration of renewable energy. However, in case of serious unbalanced voltage disturbance/fault, the conventional VSG may lose voltage, inertia, and damping support characteristics to the grid and even can cause disconnection of renewable energy. This paper proposes an improved fault control strategy for VSG with the coordination of STATCOM. The proposed method can provide sufficient voltage support while keeping continuous system inertia and damping support under severe unbalanced fault. In the paper, an improved VSG and STATCOM control topology based on positive and negative sequence current control are first proposed so as to keep the damping and inertia support to grid during the grid fault. Secondly, the voltage support control method for the VSG with improved topology during unbalanced fault is introduced, which can achieve multiple control objectives, in terms of voltage support, current limitation, and active power output simultaneously. Then a coordination control scheme of improved VSG and STATCOM is developed so as to optimize the maximum control objectives in all possible scenarios, especially in the case of severe unbalanced fault. Finally, the effectiveness of the method is verified by using the MATLAB/SIMULINK simulation platform.