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HighlightsThe poly(1,3-dioxolane) (PDOL) electrolyte demonstrates promising potential for practical application due to its advantages in in-situ polymerization process, high ionic conductivity, and long cycle life.This review focuses on the polymerization mechanism, composite innovation, and application of PDOL electrolytes.This review provides a comprehensive summary of the challenges associated with the PDOL electrolyte and makes forward-looking recommendations.Polymer solid-state lithium batteries (SSLB) are regarded as a promising energy storage technology to meet growing demand due to their high energy density and safety. Ion conductivity, interface stability and battery assembly process are still the main challenges to hurdle the commercialization of SSLB. As the main component of SSLB, poly(1,3-dioxolane) (PDOL)-based solid polymer electrolytes polymerized in-situ are becoming a promising candidate solid electrolyte, for their high ion conductivity at room temperature, good battery electrochemical performances, and simple assembly process. This review analyzes opportunities and challenges of PDOL electrolytes toward practical application for polymer SSLB. The focuses include exploring the polymerization mechanism of DOL, the performance of PDOL composite electrolytes, and the application of PDOL. Furthermore, we provide a perspective on future research directions that need to be emphasized for commercialization of PDOL-based electrolytes in SSLB. The exploration of these schemes facilitates a comprehensive and profound understanding of PDOL-based polymer electrolyte and provides new research ideas to boost them toward practical application in solid-state batteries.

In the context of area coverage tasks in three-dimensional space, unmanned aerial vehicle (UAV) clusters face challenges such as uneven task assignment, low task efficiency, and high energy consumption. This paper proposes an efficient mission planning strategy for UAV clusters in area coverage tasks. First, the area coverage search task is analyzed, and the coverage scheme of the task area is determined. Based on this, the cluster task area is divided into subareas. Then, for the UAV cluster task allocation problem, a step-by-step solution is proposed. Afterward, an improved fuzzy C-clustering algorithm is used to determine the UAV task area. Furthermore, an optimized particle swarm hybrid ant colony (PSOHAC) algorithm is proposed to plan the UAV cluster task path. Finally, the feasibility and superiority of the proposed scheme and improved algorithm are verified by simulation experiments. The simulation results show that the proposed method achieves full coverage of the task area and efficiently completes the task allocation of the UAV cluster. Compared with related comparison algorithms, the method proposed in this paper can achieve a maximum improvement of 21.9% in balanced energy consumption efficiency for UAV cluster task search planning, and the energy efficiency of the UAV cluster can be improved by up to 7.9%.

The photonic spin Hall effect (SHE) provides an effective way to manipulate the spin-polarized photons. However, the spin-dependent splitting is very tiny due to the weak spin-orbit coupling, and previous investigations for enhancing this phenomenon have some serious limitations (e.g. inconvenient to tune, inadequate attention in terahertz region). Therefore, controlling and enhancing the photonic SHE in a flexible way is highly desirable, especially for terahertz region. In this contribution, we propose a method to manipulate the photonic SHE by taking advantage of tunable optical properties of graphene via weak optical pumping. We find that photonic SHE of graphene-dielectric structure in terahertz region is quite sensitive to the pumping power. The spin shift for H polarized incident beam can reach its upper limitation under the optimal pumping power, which is related to the zero value of the real part of graphene conductivity. These findings may provide a new degree of freedom for the design of tunable spin-based photonic devices in the future.

Height is an important factor affecting crop architecture, apical dominance, biomass, resistance to lodging, tolerance to crowding and mechanical harvesting. The impressive increase in wheat and rice yield during the ‘green revolution’ benefited from a combination of breeding for high-yielding dwarf varieties together with advances in agricultural mechanization, irrigation and agrochemical/fertilizer use. To maximize yield under irrigation and high fertilizer use, semi-dwarfing is optimal, whereas extreme dwarfing leads to decreased yield. Rice plant height is controlled by genes that lie in a complex regulatory network, mainly involved in the biosynthesis or signal transduction of phytohormones such as gibberellins, brassinosteroids and strigolactones. Additional dwarfing genes have been discovered that are involved in other pathways, some of which are uncharacterized. This review discusses our current understanding of the regulation of plant height using rice as a well-characterized model and highlights some of the most promising research that could lead to the development of new, high-yielding varieties. This knowledge underpins future work towards the genetic improvement of plant height in rice and other crops.

This paper considers the problem of communication protocols between leaders and its followers for motion planning in an initially partially known environment. In this setting, the leader observes the environment information to satisfy its own local objective and and the follower completes its own local objective by estimating the states of the leader and communicating with the leader to update its knowledge about the environment when it is necessary, where the local objectives can be expressed in temporal logic. A verifier construction is built first to contain all possible communication protocols between the leaders and the followers. Then, a two‐step synthesis procedure is proposed to capture all feasible communication protocol that satisfy the local objectives for the leader and follower, respectively. In the first step, a sub‐verifier is synthesized to satisfy the objective of the follower. In the second step, based on the obtained sub‐verifier, an iterative algorithm is proposed to extract communication protocols such that the objectives of the leader and follower are satisfied, respectively. A running example is provided to illustrate the proposed procedures.

While liquid crystal elastomers (LCEs) show promise for diverse soft actuators due to their strong stimulus responsiveness, limited investigation into their light perception and processing restricts their wider use in intelligent systems. This study employs a hollow double-layer structure to design light-controlled logic soft switches based on LCEs. The design realizes digital logic circuits including AND gates, OR gates, and NOT gates, as well as an optical switch array capable of converting light signals into visualized digital signals. These light-controlled soft switches exhibit strong photothermal responsiveness (~12 s), high programmability, and excellent cyclic stability (>500 times). This research provides a new perspective on light-controlled logic soft switches and their applications in logic circuits.

Unmanned aerial vehicle (UAV) swarm intelligence technology has shown unique advantages in agricultural and forestry disaster detection, early warning, and prevention with its efficient and precise cooperative operation capability. In this paper, a systematic application strategy of UAV swarms in forest fire detection is proposed, including fire point detection, fire assessment, and control measures, based on the fusion of particle swarm optimization (PSO) and the artificial bee colony (ABC) algorithm. The UAV swarm application strategy provides optimized paths to quickly locate multiple mountain forest fire points in 3D forest modeling environments and control measures based on the analysis of the fire situation. This work lays a research foundation for studying the precise application of UAV swarm technology in real-world forest fire detection and prevention.

This work presents a new method to effectively improve the optical temperature behavior of Er 3+ doped Y 2 O 3 microtubes by co-doping of Tm 3+ or Ho 3+ ion and controlling excitation power. The influence of Tm 3+ or Ho 3+ ion on optical temperature behavior of Y 2 O 3 :Er 3+ microtubes is investigated by analyzing the temperature and excitation power dependent emission spectra, thermal quenching ratios, fluorescence intensity ratios, and sensitivity. It is found that the thermal quenching of Y 2 O 3 :Er 3+ microtubes is inhibited by co-doping with Tm 3+ or Ho 3+ ion, moreover the maximum sensitivity value based on the thermal coupled 4 S 3/2 / 2 H 11/2 levels is enhanced greatly and shifts to the high temperature range, while the maximum sensitivity based on 4 F 9/2(1) / 4 F 9/2(2) levels shifts to the low temperature range and greatly increases. The sensitivity values are dependent on the excitation power, and reach two maximum values of 0.0529/K at 24 K and 0.0057/K at 457 K for the Y 2 O 3 :1%Er 3+ , 0.5%Ho 3+ at 121 mW/mm 2 excitation power, which makes optical temperature measurement in wide temperature range possible. The mechanism of changing the sensitivity upon different excitation densities is discussed.

Purpose The impact of body mass index (BMI) on in vitro fertilization (IVF) has been well acknowledged; however, the reported conclusions are still incongruent. This study aimed to investigate the effect of BMI on IVF embryos and fresh transfer clinical outcomes. Methods This retrospective cohort analysis included patients who underwent IVF/ICSI treatment and fresh embryo transfer from 2014 to March 2022. Patients were divided into the underweight group: BMI < 18.5 kg/m 2 ; normal group: 18.5 ≤ BMI < 24 kg/m 2 ; overweight group: 24 ≤ BMI < 28 kg/m 2 ; and obesity group: BMI ≥ 28 kg/m 2 . A generalized linear model was used to analyze the impact of BMI on each IVF outcome used as a continuous variable. Results A total of 3465 IVF/ICSI cycles in the embryo part; and 1698 fresh embryo transplanted cycles from the clinical part were included. Available embryos rate (61.59% vs. 57.32%, p  = 0.007) and blastocyst development rates (77.98% vs. 66.27%, p  < 0.001) were higher in the obesity group compared to the normal BMI group. Also, the fertilization rate of IVF cycles in the obesity group was significantly decreased vs. normal BMI group (normal: 62.95% vs. 66.63% p  = 0.006; abnormal: 5.43% vs. 7.04%, p  = 0.037), while there was no difference in ICSI cycles. The clinical outcomes of overweight and obesity groups were comparable to the normal group. The gestational age of the obesity group was lower compared to the normal group (38.08 ± 1.95 vs. 38.95 ± 1.55, p  = 0.011). The adjusted OR (AOR) of BMI for the preterm birth rate of singletons was 1.134 [(95% CI 1.037–1.240), p  = 0.006]. BMI was significantly associated with live birth rate after excluded the PCOS patients [AOR: 1.042 (95% CI 1.007–1.078), p  = 0.018]. In young age (≤ 35 years), clinical pregnancy rate and live birth rate were positively correlated with BMI, AOR was 1.038 [95% CI (1.001–1.076), p  = 0.045] and 1.037 [95% CI (1.002–1.074) p  = 0.038] respectively. Conclusion Being overweight and obese was not associated with poor IVF outcomes but could affect blastocyst formation. ICSI could help to avoid low fertilization in obese patients. Also, obesity was associated with increased rates of premature singleton births.

Background Polycystic ovary syndrome (PCOS) pathogenesis involves dysregulated granulosa cell function, but molecular mechanisms remain unclear. Methods High-throughput RNA sequencing was performed on ovarian granulosa cells from 6 PCOS patients and 3 controls to identify differentially expressed mRNAs. Bioinformatics analyses including ceRNA network construction predicted the KRTAP5-AS1/miR-199b-5p/CYP19A1 regulatory axis, which was experimentally validated through dual-luciferase reporter assays. qRT-PCR confirmed the expression patterns of these molecules in expanded clinical cohorts (38 PCOS vs. 30 controls), with Pearson correlation analysis examining relationships between gene expression and clinical parameters. Using the KGN granulosa cell line, functional studies included: (1) ELISA quantification of estradiol production; (2) proliferation assessment via CCK-8 and colony formation assays; and (3) apoptosis evaluation by flow cytometry and Bax/Bcl-2 protein analysis. These experiments were performed following both gain-of-function (overexpression) and loss-of-function (shRNA knockdown) manipulations of KRTAP5-AS1 and miR-199b-5p. Results Through RNA sequencing of ovarian granulosa cells from 6 PCOS patients and 3 controls, we identified CYP19A1 as significantly upregulated in PCOS. Expanded validation in 38 PCOS vs. 30 controls confirmed elevated CYP19A1 and reduced miR-199b-5p in PCOS, with KRTAP5-AS1 showing negative correlation to miR-199b-5p and positive to CYP19A1. Clinically, CYP19A1 upregulation correlated with poor embryo quality, elevated testosterone, AMH, BMI, and infertility duration, while miR-199b-5p levels associated positively with embryo quality. In KGN granulosa cells, miR-199b-5p overexpression suppressed CYP19A1 expression and estradiol synthesis, whereas KRTAP5-AS1 overexpression alleviated this suppression via competitive miR-199b-5p binding. Functional studies demonstrated that miR-199b-5p overexpression combined with KRTAP5-AS1 knockdown inhibited proliferation, promoted apoptosis, and reduced estradiol production, while opposite manipulations reversed these effects. Conclusions Our findings reveal that KRTAP5-AS1 modulates granulosa cell dysfunction in PCOS through the miR-199b-5p/CYP19A1 axis, highlighting miR-199b-5p as a potential therapeutic target for PCOS-related ovarian dysfunction and endocrine abnormalities. Clinical trial number Not applicable.