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

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

The FruitShell French synthesis system at the Blizzard 2023 Challenge

This paper presents a French text-to-speech synthesis system for the Blizzard Challenge 2023. The challenge consists of two tasks: generating high-quality speech from female speakers and generating speech that closely resembles specific individuals. Regarding the competition data, we conducted a screening process to remove missing or erroneous text data. We organized all symbols except for phonemes and eliminated symbols that had no pronunciation or zero duration. Additionally, we added word boundary and start/end symbols to the text, which we have found to improve speech quality based on our previous experience. For the Spoke task, we performed data augmentation according to the competition rules. We used an open-source G2P model to transcribe the French texts into phonemes. As the G2P model uses the International Phonetic Alphabet (IPA), we applied the same transcription process to the provided competition data for standardization. However, due to compiler limitations in recognizing special symbols from the IPA chart, we followed the rules to convert all phonemes into the phonetic scheme used in the competition data. Finally, we resampled all competition audio to a uniform sampling rate of 16 kHz. We employed a VITS-based acoustic model with the hifigan vocoder. For the Spoke task, we trained a multi-speaker model and incorporated speaker information into the duration predictor, vocoder, and flow layers of the model. The evaluation results of our system showed a quality MOS score of 3.6 for the Hub task and 3.4 for the Spoke task, placing our system at an average level among all participating teams

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

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

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling

With the incorporation of the UNet architecture, diffusion probabilistic models have become a dominant force in image generation tasks. One key design in UNet is the skip connections between the encoder and decoder blocks. Although skip connections have been shown to improve training stability and model performance, we reveal that such shortcuts can be a limiting factor for the complexity of the transformation. As the sampling steps decrease, the generation process and the role of the UNet get closer to the push-forward transformations from Gaussian distribution to the target, posing a challenge for the network's complexity. To address this challenge, we propose Skip-Tuning, a simple yet surprisingly effective training-free tuning method on the skip connections. Our method can achieve 100% FID improvement for pretrained EDM on ImageNet 64 with only 19 NFEs (1.75), breaking the limit of ODE samplers regardless of sampling steps. Surprisingly, the improvement persists when we increase the number of sampling steps and can even surpass the best result from EDM-2 (1.58) with only 39 NFEs (1.57). Comprehensive exploratory experiments are conducted to shed light on the surprising effectiveness. We observe that while Skip-Tuning increases the score-matching losses in the pixel space, the losses in the feature space are reduced, particularly at intermediate noise levels, which coincide with the most effective range accounting for image quality improvement

Practical lessons for bringing policy-makers on board in sexual and reproductive health research

Abstract Background The need to translate research into policy, i.e. making research findings a driving force in agenda-setting and policy change, is increasingly acknowledged. However, little is known about translation mechanisms in the field of sexual and reproductive health (SRH) outside North American or European contexts. This paper seeks to give an overview of the existing knowledge on this topic as well as to document practical challenges and remedies from the perspectives of researchers involved in four SRH research consortium projects in Latin America, sub-Saharan Africa, China and India. Methods A literature review and relevant project documents were used to develop an interview guide through which researchers could reflect on their experiences in engaging with policy-makers, and particularly on the obstacles met and the strategies deployed by the four project consortia to circumvent them. Results Our findings confirm current recommendations on an early and steady involvement of policy-makers, however they also suggest that local barriers between researchers and policy-making spheres and individuals can represent major hindrances to the realization of translation objectives. Although many of the challenges might be common to different contexts, creating locally-adapted responses is deemed key to overcome them. Researchers’ experiences also indicate that - although inevitable - recognizing and addressing these challenges is a difficult, time- and energy-consuming process for all partners involved. Despite a lack of existing knowledge on translation efforts in SRH research outside North American or European contexts, and more particularly in low and middle-income countries, it is clear that existing pressure on health and policy systems in these settings further complicates them. Conclusions This article brings together literature findings and researchers’ own experiences in translating research results into policy and highlights the major challenges research conducted on sexual and reproductive health outside North American or European contexts can meet. Future SRH projects should be particularly attentive to these potential obstacles in order to tailor appropriate and consistent strategies within their existing resources

Direct isolation of small extracellular vesicles from human blood using viscoelastic microfluidics

Small extracellular vesicles (sEVs; <200 nm) that contain lipids, nucleic acids, and proteins are considered promising biomarkers for a wide variety of diseases. Conventional methods for sEV isolation from blood are incompatible with routine clinical workflows, significantly hampering the utilization of blood-derived sEVs in clinical settings. Here, we present a simple, viscoelastic-based microfluidic platform for label-free isolation of sEVs from human blood. The separation performance of the device is assessed by isolating fluorescent sEVs from whole blood, demonstrating purities and recovery rates of over 97 and 87%, respectively. Significantly, our viscoelastic-based microfluidic method also provides for a remarkable increase in sEV yield compared to gold-standard ultracentrifugation, with proteomic profiles of blood-derived sEVs purified by both methods showing similar protein compositions. To demonstrate the clinical utility of the approach, we isolate sEVs from blood samples of 20 patients with cancer and 20 healthy donors, demonstrating that elevated sEV concentrations can be observed in blood derived from patients with cancer

Multimodality of AI for Education: Towards Artificial General Intelligence

This paper presents a comprehensive examination of how multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intelligence (AGI) in educational contexts. It scrutinizes the evolution and integration of AI in educational systems, emphasizing the crucial role of multimodality, which encompasses auditory, visual, kinesthetic, and linguistic modes of learning. This research delves deeply into the key facets of AGI, including cognitive frameworks, advanced knowledge representation, adaptive learning mechanisms, strategic planning, sophisticated language processing, and the integration of diverse multimodal data sources. It critically assesses AGI's transformative potential in reshaping educational paradigms, focusing on enhancing teaching and learning effectiveness, filling gaps in existing methodologies, and addressing ethical considerations and responsible usage of AGI in educational settings. The paper also discusses the implications of multimodal AI's role in education, offering insights into future directions and challenges in AGI development. This exploration aims to provide a nuanced understanding of the intersection between AI, multimodality, and education, setting a foundation for future research and development in AGI