Effects of post-abortion family planning services on contraceptive practices in China : protocol for a clustered randomized controlled trial

Study objectives: To determine whether integrating post-abortion services in hospital settings in China will increase the contraceptive use and decrease repeat abortion rates. Study design: Three-arms cluster randomised controlled trial in which the unit of randomisation is hospital. Participants: Women seeking induced abortion within 12 weeks of gestation age. Sites: Ninety hospitals from 30 provinces in China will be randomised to the three arms of the study stratified by province. In each province, eligible hospitals will be matched on the characteristics of abortion departments, especially the volume of abortions in the 2 months in the situation survey. Length of follow up: Six months. Intervention: Multiple interventions that aim to increase the use of more effective contraceptive methods, improve user adherence to reduce the unintended pregnancies and repeat induced abortions. Data collection: Data will be collected at four time points, one at baseline(month 0 at the time of enrolment) and twice during intervention (1st 3rd and 6th month after enrolment, respectively). Primary outcome: Unintended pregnancies or repeated induced abortions; immediate contraceptive uptake and the use of modern effective contraceptive methods

Approximate SU(4) spin models on triangular and honeycomb lattices in twisted AB-Stacked WSe2_2 homo-bilayer

In this paper, we derive lattice models for the narrow moir\'e bands of the AB-stacked twisted WSe$_2$ homobilayer through continuum model and Wannier orbital construction. Previous work has shown that an approximate SU(4) Hubbard model may be realized by combining spin and layer because inter-layer tunneling is suppressed due to spin $S_z$ conservation. However, Rashba spin-orbit coupling (SOC) was ignored in the previous analysis. Here, we show that a Rashba SOC of reasonable magnitude can induce a finite but very small inter-layer hopping in the final lattice Hubbard model. At total filling $n=1$, we derive a spin-layer model on a triangular lattice in the large-U limit where the inter-layer tunneling contributes as a sublattice-dependent transverse Ising field for the layer pseudospin. We then show that the $n=2$ Mott insulator is also captured by an approximate SU(4) spin model, but now on honeycomb lattice. We comment on the possibility of a Dirac spin liquid (DSL) and competing phases due to SU(4) anisotropy terms

Research on Multi-Dimensional Dynamic Clustering Method of Big Data Alliance Users

In order to improve the clustering accuracy of big data alliance users, this paper studies users\u27 dynamic clustering based on their multi-dimensional attributes. First of all, the user profile of big data alliance is constructed from five dimensions of user basic attribute, domain attribute, preference attribute, social attribute and value attribute. And the K-means algorithm is used to cluster user profiles to complete the initial clustering. Then, based on the group user profile, combined with the user\u27s recent dynamic behavior data, the FCM algorithm is used to achieve secondary clustering. Finally, the proposed user clustering method is tested by recommending data resources to the clustered user groups. The experimental results show that the user clustering method proposed in this paper has higher accuracy and lower error rate

L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion Priors

Language-based colorization produces plausible and visually pleasing colors under the guidance of user-friendly natural language descriptions. Previous methods implicitly assume that users provide comprehensive color descriptions for most of the objects in the image, which leads to suboptimal performance. In this paper, we propose a unified model to perform language-based colorization with any-level descriptions. We leverage the pretrained cross-modality generative model for its robust language understanding and rich color priors to handle the inherent ambiguity of any-level descriptions. We further design modules to align with input conditions to preserve local spatial structures and prevent the ghosting effect. With the proposed novel sampling strategy, our model achieves instance-aware colorization in diverse and complex scenarios. Extensive experimental results demonstrate our advantages of effectively handling any-level descriptions and outperforming both language-based and automatic colorization methods. The code and pretrained models are available at: https://github.com/changzheng123/L-CAD

Quantum algorithm for ground state energy estimation using circuit depth with exponentially improved dependence on precision

A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods. The current understanding is that achieving quantum advantage in this area will require some degree of fault-tolerance. While hardware is improving towards this milestone, optimizing quantum algorithms also brings it closer to the present. Existing methods for ground state energy estimation are costly in that they require a number of gates per circuit that grows exponentially with the desired number of bits in precision. We reduce this cost exponentially, by developing a ground state energy estimation algorithm for which this cost grows linearly in the number of bits of precision. Relative to recent resource estimates of ground state energy estimation for the industrially-relevant molecules of ethylene-carbonate and PF$_6^-$, the estimated gate count and circuit depth is reduced by a factor of 43 and 78, respectively. Furthermore, the algorithm can use additional circuit depth to reduce the total runtime. These features make our algorithm a promising candidate for realizing quantum advantage in the era of early fault-tolerant quantum computing.Comment: Fixed typos and streamlined presentation, 8 pages of main text + 16 pages of method

Induced abortion in 30 Chinese provinces in 2013: a cross-sectional survey

Background: Galloping economic growth and reform in China in the past 30 years has led to dramatic social changes. Attitudes towards sex and sexual behaviour have changed, and premarital sex has become more acceptable. The methods of contraception have changed, and the use of highly effective or long-acting contraceptive methods tends to be decreasing, especially in urban areas. Abortion is commonly used to end unintended pregnancy. The aim of this study was to survey the current situation of induced abortions in selected hospitals in 30 provinces in China. Methods: This cross-sectional study was conducted in 295 randomly selected hospitals in 30 Chinese provinces between April and August, 2013. We collected data using a questionnaire filled by the abortion service providers for all women seeking abortion within 12 weeks of pregnancy during a period of two months. The information included self-reported demographic and economic characteristics, history of induced abortion, and use of contraception. The characteristics of women were summarised with counts (percentages) for categorical variables; mean (SD) and range for age of women. All participants signed a written informed consent of which they received a copy. Ethics approvals were obtained from both ethics committees of the National Research Institution for Family Planning (NRIFP), China, and of the Ghent University, Belgium. Findings: 79 174 women participated in the study (mean age 28∙9 years (SD 1∙7; range 13–58), of whom 27 134 (35%) were undergoing a first induced abortion, 28 637 (37%) a second abortion, and 22 682 (29%) a third or subsequent abortion. About a third of participants (31%) were not married and more than half (61%) were not local residents. The primary reasons for the unintended pregnancy were contraception failure (50%) and non-use of contraception (44%). Interpretation: This is the first nationwide large-scale study in 30 provinces to show that repeated induced abortion is high in China. A family planning programme for young and unmarried people is urgently needed to improve their access to information, advice, and services about contraception and to reduce unintended pregnancies and repeated induced abortion. Funding: The European Commission (EC) under the Seventh Framework Programme (FP7), project number 282490

Numerical simulation method study of rock fracture based on strain energy density theory

Many numerical methods are carried out to study the nonlinear failure behaviors of the rock; however, the numerical simulation methods for the failed rock are still in the research stage. This paper establishes the damage constitutive equation by combining the bilinear strain softening constitutive model with energy dissipation principles, as well as the energy failure criterion of mesoscopic elements based on the strain energy density theory. When the strain energy stored by an element exceeds a fixed value, the element enters the damage state and the damage degree increases with increasing energy dissipation. Simultaneously, the material properties of the damaged element change until it becomes an element with certain residual strength. As the load increases, the damage degree of an element increases. When the strain energy stored by an element exceeds the established value of the energy criterion, the element is defined to be failed. As the number of failed elements constantly increases, failed elements interconnect and form macrocracks. The rock fracture calculation program on the basis of the preceding algorithm is successfully applied to the fracture simulation process in Brazilian splitting, tensile tests with build-in crack and tunnel excavation

Study on the effect of new type liquid accelerator on the performance of shotcrete

Shotcrete is an essential preliminary support means in New Austrian Tunneling Method (NATM) construction and plays a very important role in controlling the stability of surrounding rock. The accelerator is a necessary admixture in shotcrete and its quality can greatly affect shotcrete performance. This paper proposes a new liquid accelerator characterized by short initial and final setting time, small dosage, and good adaptability to cement. Laboratory tests and field tests are conducted to verify the influence of this liquid accelerator on performance of shotcrete. Numerical simulation is carried out to study the strength growth of shotcrete with time and interaction between the strength and stress release of surrounding rock. The results show that the initial and final setting time of this liquid accelerator is 2 minutes and 4 minutes respectively. Its dosage is just 1.5% to 4% of the cement quantity. Adding this liquid accelerator can effectively improve the early strength and reduce the later strength loss of shotcrete, and therefore enhance the supporting effects of shotcrete on surrounding rock. In the field application, it is an ideal liquid accelerator for shotcrete, characterized by little resilience, no slurry shedding, and low dust

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models

Diffusion Probabilistic Models (DPMs) have achieved considerable success in generation tasks. As sampling from DPMs is equivalent to solving diffusion SDE or ODE which is time-consuming, numerous fast sampling methods built upon improved differential equation solvers are proposed. The majority of such techniques consider solving the diffusion ODE due to its superior efficiency. However, stochastic sampling could offer additional advantages in generating diverse and high-quality data. In this work, we engage in a comprehensive analysis of stochastic sampling from two aspects: variance-controlled diffusion SDE and linear multi-step SDE solver. Based on our analysis, we propose SA-Solver, which is an improved efficient stochastic Adams method for solving diffusion SDE to generate data with high quality. Our experiments show that SA-Solver achieves: 1) improved or comparable performance compared with the existing state-of-the-art sampling methods for few-step sampling; 2) SOTA FID scores on substantial benchmark datasets under a suitable number of function evaluations (NFEs)