Hasil untuk "Gynecology and obstetrics"

Alberto Raiola, Emanuele Locatelli, Davide Marenduzzo et al.

Magnetic polymers are examples of composite soft materials in which the competition between the large configurational entropy of the soft substrate (polymer) and the magnetic interaction may give rise to rich equilibrium phase diagrams as well as non-standard critical phenomena. Here, we study a self-avoiding walk model decorated by Ising spins of value $0$ and $\pm 1$ that interact according to a Blume-Emery-Griffith-like Hamiltonian. By using mean-field approximations and Monte Carlo simulations, we report the existence of three distinct equilibrium phases: swollen disordered, compact ordered, and compact disordered. Notably, these phases are separated by phase boundaries that meet at multicritical points, whose nature and location are tunable and depend on the strength of the interactions. In our conclusion, we discuss the relevance of the phase diagrams we have obtained to the physics of magnetic polymers and their application to chromatin biophysics.

Felix Biertümpfel, Jungbae Chun, and Peter Seiler

This paper presents a novel approach for ensuring safe operation of systems subject to input nonlinearities and time-varying safety constraints. We extend the time-varying barrier function framework to address time-varying safety constraints and explicitly account for control-dependent nonlinearities at the plant input. Guaranteed bounds on the input-output behavior of these nonlinearities are provided through pointwise-in-time quadratic constraints. The result is a class of robust time-varying control barrier functions that define a safety filter. This filter ensures robust safety for all admissible nonlinearities while minimally modifying the command generated by a baseline controller. We derive a second-order cone program (SOCP) to compute this safety filter online and provide feasibility conditions for ball-constrained inputs. The proposed approach is demonstrated on a spacecraft docking maneuver.

Zachary L. Crang, Rich D. Johnston, Katie L. Mills et al.

This study aimed to: (1) understand whether commercially available computer-vision and artificial intelligence (AI) player tracking software can accurately measure player position, speed and distance using broadcast footage and (2) determine the impact of camera feed and resolution on accuracy. Data were obtained from one match at the 2022 Qatar Federation Internationale de Football Association (FIFA) World Cup. Tactical, programme and camera 1 feeds were used. Three commercial tracking providers that use computer-vision and AI participated. Providers analysed instantaneous position (x, y coordinates) and speed (m\,s^{-1}) of each player. Their data were compared with a high-definition multi-camera tracking system (TRACAB Gen 5). Root mean square error (RMSE) and mean bias were calculated. Position RMSE ranged from 1.68 to 16.39 m, while speed RMSE ranged from 0.34 to 2.38 m\,s^{-1}. Total match distance mean bias ranged from -1745 m (-21.8%) to 1945 m (24.3%) across providers. Computer-vision and AI player tracking software offer the ability to track players with fair precision when players are detected by the software. Providers should use a tactical feed when tracking position and speed, which will maximise player detection, improving accuracy. Both 720p and 1080p resolutions are suitable, assuming appropriate computer-vision and AI models are implemented.

Maggie Barker, Daniel Guo, Justin Palmeri et al.

In the paper, a program strength model was proposed to evaluate the performance of countries across different Olympic events. The model assessed how strong a country's program was in each event and also factored in the influence of past Olympic performances. The final medal counts from the Paris 2024 Olympic Games were used to validate the model and to determine the optimal set of constants using Monte Carlo simulation. Based on this model, a prediction of the final medal counts for the 2028 Olympic Games is also provides for reference.

Dimitrios Rafail Kalaitzopoulos, Ioannis Maris, Konstantinos Chatzistergiou et al.

Background: Cervical cerclage is used to prevent preterm delivery caused by cervical insufficiency, thereby reducing neonatal morbidity and mortality rates. Transabdominal cerclage is usually performed in women who previously underwent transvaginal cerclage that failed to prevent pregnancy loss, or in those with a short cervix where transvaginal cerclage was not feasible. Objectives: To estimate the efficacy of pre-conceptional laparoscopic cerclage in facilitating term delivery and live birth. Methods: A systematic review was conducted according to the PRISMA 2020 guidelines. This study was registered in PROSPERO (CRD42024545316). A search was conducted up to the 15th of April 2024, in the PubMed and Cochrane databases, using a combination of terms “laparoscopy“, “transabdominal” and “cerclage”. Original studies investigating the role of pre-conceptional laparoscopic cerclage on pregnancy outcomes after follow-up were eligible for inclusion in this review. Main Outcomes Measures: Prevalence of deliveries after 37 weeks of gestation and live birth rates. Results: Ten studies involving 1060 patients were included. The pooled prevalence of deliveries after 37 weeks of pregnancy was 70% [95% confidence interval (CI) 60%-79%, 7 studies, 515 pregnancies, I2: 85%] and the pooled prevalence of live birth was 92% (95% CI 86%-95%, 10 studies, 713 pregnancies, I2: 69%). Significantly higher rates of delivery after 37 weeks of pregnancy were associated with the use of mersilene tape compared to conventional sutures [odds ratio (OR): 2.98, 95% 1.95-4.56] and the use of an anterior knot compared to a posterior knot (OR: 2.26, 95% CI: 1.50-3.40). Conclusions: Pre-conceptional laparoscopic cerclage achieved high rates of live birth after 37 weeks in women considered at high risk of preterm delivery. Comparative research is needed to better understand the efficacy of pre-conceptional laparoscopic cerclage as well as refine the indications for this procedure, optimise surgical techniques, and determine the best timing for cerclage placement. What is New? Pre-conceptional laparoscopic cerclage may prevent future preterm births and second-trimester pregnancy losses.

Na Wang, Bingqi Han, Sumiao Hong et al.

Abstract Background Preterm birth is a leading cause of health problems and death in infants. This study aims to investigate the association between maternal plasma glucose levels during pregnancy and risk of preterm birth. Methods This population-based retrospective study of 6,842 pregnant women used data from a tertiary hospital in China from January 2016 to December 2022. Plasma glucose levels were measured at fasting, 1 h, and 2 h after a 75-g OGTT between 24 and 28 weeks of gestation. The primary outcome of interest was preterm birth. Analysis was performed using restricted cubic splines and logistic regression models. Results The proportion of gestational diabetes mellitus (GDM) and preterm birth in this study were 7.92% and 5.86%, respectively. The levels of fasting plasma glucose (aOR: 1.26; 95% CI: 1.08, 1.47; P = 0.003; P for nonlinear = 0.264), 1-hour plasma glucose (aOR: 1.10; 95% CI: 1.03, 1.17; P = 0.003; P for nonlinear = 0.535), and 2-hour plasma glucose (aOR: 1.10; 95% CI: 1.02, 1.19; P = 0.012; P for nonlinear = 0.368) showed statistically significant linear associations with an increased risk of preterm birth. Conclusion Elevated plasma glucose levels during pregnancy statistically significantly increase the risk of preterm birth. Given that hyperglycemia during pregnancy can be prevented and managed, it is crucial to enhance health education and glucose monitoring for pregnant women. Timely interventions should be implemented to control plasma glucose levels, thereby reducing the incidence of preterm birth.

Zecheng Yin, Chonghao Cheng, and Yao Guo et al.

Navigating towards fully open language goals and exploring open scenes in an intelligent way have always raised significant challenges. Recently, Vision Language Models (VLMs) have demonstrated remarkable capabilities to reason with both language and visual data. Although many works have focused on leveraging VLMs for navigation in open scenes, they often require high computational cost, rely on object-centric approaches, or depend on environmental priors in detailed human instructions. We introduce Navigation with VLM (NavVLM), a training-free framework that harnesses open-source VLMs to enable robots to navigate effectively, even for human-friendly language goal such as abstract places, actions, or specific objects in open scenes. NavVLM leverages the VLM as its cognitive core to perceive environmental information and constantly provides exploration guidance achieving intelligent navigation with only a neat target rather than a detailed instruction with environment prior. We evaluated and validated NavVLM in both simulation and real-world experiments. In simulation, our framework achieves state-of-the-art performance in Success weighted by Path Length (SPL) on object-specifc tasks in richly detailed environments from Matterport 3D (MP3D), Habitat Matterport 3D (HM3D) and Gibson. With navigation episode reported, NavVLM demonstrates the capabilities to navigate towards any open-set languages. In real-world validation, we validated our framework's effectiveness in real-world robot at indoor scene.

Silas Otero Reis Salum, Eduardo Batista Candido, Maria Aparecida Custódio Domingues et al.

Abstract Objective Endometrial cancer (EC) is a heterogeneous disease with recurrence rates ranging from 15 to 20%. The discrimination of cases with a worse prognosis aims, in part, to reduce the length of surgical staging in cases with a better prognosis. This study aimed to evaluate the association between Insulin-like growth factor II mRNA-binding protein 3 (IMP3) expression and prognostic and morphological factors in EC. Methods This retrospective, cross-sectional, analytical study included 79 EC patients - 70 endometrioid carcinoma (EEC) and 9 serous carcinoma (SC) - and 74 benign endometrium controls. IMP3 expression was evaluated by immunohistochemistry-based TMA (Tissue Microarray), and the results were associated with morphological and prognostic factors, including claudins 3 and 4, estrogen and progesterone receptors, TP53, and KI67. Results IMP3 expression was significantly higher in SC compared to EEC in both extent (p<0.001) and intensity (p=0.044). It was also significantly associated with worse prognostic factors, including degree of differentiation (p=0.024, p<0.001), staging (p<0.001; p<0.001) and metastasis (p=0.002; p<0.001). IMP3 expression was also significant in extent (p=0.002) in endometrial tumors compared with controls. In addition, protein TP53 and KI67 showed significant associations in extent and intensity, respectively. Conclusion IMP3 expression was associated with worse prognostic factors studied. These findings suggest that IMP3 may be a potential biomarker for EC poorer prognosis.

Meiying Cao, Ying Kang, Jimin Li et al.

Abstract Purpose The relationship between exposure doses of 2.5-micrometer Particulate Matter (PM2.5), Inhalable particles (PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2) and Ozone (O3) in the first trimester and spontaneous abortion of pregnant women was evaluated by global average method and nearest monitoring station method, respectively. Method Retrospective analysis of the clinical data of pregnant women with spontaneous abortion and full-term pregnant women in the Department of Obstetrics and Gynecology of two third-class hospitals in a valley city in Northwest China. According to the age factor, the eligible pregnant women were matched at a ratio of 1 : 4. The global average method and the nearest monitoring station method were used to evaluate the exposure of pollutants. The rank-sum test and conditional logistic regression were used to analyze the correlation between air pollutants and spontaneous abortion. Results Although the global average method and the nearest monitoring station method are slightly different in the assessment of exposure dose, they do not affect the correlation evaluation with spontaneous abortion. The exposure of pregnant women to PM2.5(OR1 = 1.156, OR2 = 1.036), SO2 (OR1 = 1.432, OR2 = 1.429) and NO2 (OR1 = 1.121, OR2 = 1.159) in the first trimester is related to the occurrence of spontaneous abortion.(OR1: the global average method, OR2: the nearest monitoring station method) Conclusion The exposure of PM2.5, SO2 and NO2 in the first trimester in valley cities is associated with the occurrence of spontaneous abortion in pregnant women.

Sally K. Stauder, Shalmali R. Borkar, Anna Najor et al.

Background: Decreasing primary care access and increasing emergency department (ED) usage is a potential contributor to declining cancer screening prevalences in those facing barriers to health care access. The ED is a non-traditional yet potentially high-yield setting for implementation of interventions to monitor and increase cancer screening. Methods: An ED-administered survey in July 2022 gathered data on breast, cervical, and colorectal cancer screening, as well as human papillomavirus (HPV) vaccination status of females presenting to the ED for care. This was compared with electronic health record (EHR) data extraction of all ED patients during the same timeframe. Primary outcome was proportion of cancer screening and HPV vaccination not up to date in each group. Results: ED survey was administered to 101 individuals; EHR data was extracted on 2934 patients. Survey versus EHR, respectively, found cervical cancer screening was not up to date in 6.2% vs. 77.6%, breast cancer screening in 14.3% vs. 73.4%, colorectal cancer screening in 22.9% vs. 56.5%, and HPV vaccination in 33.3% vs. 57.8%. p value was < 0.001 for all screening category comparisons between survey and EHR. Discussion: Our data indicate significant discrepancies between self-reported screening history and EHR data. ED survey results were more in line with the observed screening rates in various surveillance systems and published in the literature. This suggests that point-of-care ED survey administration may be more effective in identifying those needing preventative cancer screening, especially in individuals with less access to routine health care.

Samira Zare, Alex Spaeth, Sandya Suresh et al.

Origami structures have been widely explored in robotics due to their many potential advantages. Origami robots can be very compact, as well as cheap and efficient to produce. In particular, they can be constructed in a flat format using modern manufacturing techniques. Rotational motion is essential for robotics, and a variety of origami rotational joints have been proposed in the literature. However, few of these are even approximately flat-foldable. One potential enabler of flat origami rotational joints is the inclusion of lightweight pneumatic pouches which actuate the origami's folds; however, pouch actuators only enable a relatively small amount of rotational displacement. The previously proposed Four-Vertex Origami is a flat-foldable structure which provides an angular multiplier for a pouch actuator, but suffers from a degenerate state. This paper presents a novel rigid origami, the Self-Lock Origami, which eliminates this degeneracy by slightly relaxing the assumption of flat-foldability. This joint is analysed in terms of a trade-off between the angular multiplier and the mechanical advantage. Furthermore, the Self-Lock Origami is a modular joint which can be connected to similar or different joints to produce complex movements for various applications; three different manipulator designs are introduced as a proof of concept.

Luyi Qiu, Xiaofeng Zhang, ChaoChen Gu et al.

Remote sensing change detection between bi-temporal images receives growing concentration from researchers. However, comparing two bi-temporal images for detecting changes is challenging, as they demonstrate different appearances. In this paper, we propose a dual attentive generative adversarial network for achieving very high-resolution remote sensing image change detection tasks, which regards the detection model as a generator and attains the optimal weights of the detection model without increasing the parameters of the detection model through generative-adversarial strategy, boosting the spatial contiguity of predictions. Moreover, We design a multi-level feature extractor for effectively fusing multi-level features, which adopts the pre-trained model to extract multi-level features from bi-temporal images and introduces aggregate connections to fuse them. To strengthen the identification of multi-scale objects, we propose a multi-scale adaptive fusion module to adaptively fuse multi-scale features through various receptive fields and design a context refinement module to explore contextual dependencies. Moreover, the DAGAN framework utilizes the 4-layer convolution network as a discriminator to identify whether the synthetic image is fake or real. Extensive experiments represent that the DAGAN framework has better performance with 85.01% mean IoU and 91.48% mean F1 score than advanced methods on the LEVIR dataset.

Shuyu Miao, Lin Zheng, Jingjing Liu et al.

The label-free model evaluation aims to predict the model performance on various test sets without relying on ground truths. The main challenge of this task is the absence of labels in the test data, unlike in classical supervised model evaluation. This paper presents our solutions for the 1st DataCV Challenge of the Visual Dataset Understanding workshop at CVPR 2023. Firstly, we propose a novel method called K-means Clustering Based Feature Consistency Alignment (KCFCA), which is tailored to handle the distribution shifts of various datasets. KCFCA utilizes the K-means algorithm to cluster labeled training sets and unlabeled test sets, and then aligns the cluster centers with feature consistency. Secondly, we develop a dynamic regression model to capture the relationship between the shifts in distribution and model accuracy. Thirdly, we design an algorithm to discover the outlier model factors, eliminate the outlier models, and combine the strengths of multiple autoeval models. On the DataCV Challenge leaderboard, our approach secured 2nd place with an RMSE of 6.8526. Our method significantly improved over the best baseline method by 36\% (6.8526 vs. 10.7378). Furthermore, our method achieves a relatively more robust and optimal single model performance on the validation dataset.

Ying Qin, Canliang Wen, Huijiao Wu

Objective Premature ovarian failure (POF) is a disease with high clinical heterogeneity. Subsequently, its diagnosis is challenging. CXCL10 which is a small signaling protein involved in immune response and inflammation may have diagnostic potential in detection of premature ovarian insufficiency. Therefore, this study aimed to investigate CXCL10 based diagnostic biomarkers for POF. Methods Transcriptome data for POF was obtained from the Gene Expression Omnibus (GEO) database (GSE39501). Principal component analysis (PCA) assessed CXCL10 expression in patients with POF. The receiver operating characteristic (ROC) curve, analyzed using PlotROC, demonstrated the diagnostic potential of CXCL10 and CXCL10-based models for POF. Differentially expressed genes (DEGs) in the control group of POF were identified using DEbylimma. PlotVenn was used to determine the overlap between the POF-control group and the high-/low-expression CXCL10 groups. QuadrantPlot was employed to detect CXCL10-dysregulated genes in POF. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were conducted on DEGs using RunMulti Group cluster Profiler. A POF model was induced with cisplatin (DDP) using KGN cells. RT-qPCR and Western blot were used to measure the expression of CXCL10, apoptosis-related proteins, and peroxisome proliferator–activated receptor (PPAR) signaling pathway-related proteins in this model, following siRNA-mediated silencing of CXCL10. Flow cytometry was employed to assess the apoptosis of KGN cells after CXCL10 downregulation. Results The expression of CXCL10 is dysregulated in POF, and it shows promising diagnostic potential for POF, as evidenced by an area under the curve value of 1. In POF, we found 3,362 up-regulated and 3,969 down-regulated DEGs compared to healthy controls, while the high- and low-expression groups of POF (comprising samples above and below the median CXCL10 expression) exhibited 1,304 up-regulated and 1,315 down-regulated DEGs. Among these, 786 DEGs consistently displayed dysregulation in POF due to CXCL10 influence. Enrichment analysis indicated that the PPAR signaling pathway was activated by CXCL10 in POF. The CXCL10-based model (including CXCL10, Itga2, and Raf1) holds potential as a diagnostic biomarker for POF. Additionally, in the DDP-induced KGN cell model, interfering with CXCL10 expression promoted the secretion of estradiol, and reduced apoptosis. Furthermore, CXCL10 silencing led to decreased expression levels of PPARβ and long-chain acyl-CoA synthetase 1 compared to the Si-NC group. These results suggest that CXCL10 influences the progression of POF through the PPAR signaling pathway. Conclusion The CXCL10-based model, demonstrating perfect diagnostic accuracy for POF and comprising CXCL10, Itga2, and Raf1, holds potential as a valuable diagnostic biomarker. Thus, the expression levels of these genes may collectively provide valuable diagnostic information for POF.

Éric Herbert, and Gael Giraud, Aurélie Louis-Napoléon et al.

This paper presents a conceptual model describing the medium and long-term co-evolution of natural and socio-economic subsystems of Earth. An economy is viewed as an out-of-equilibrium dissipative structure that can only be maintained with a flow of energy and matter. The distinctive approach emphasized here consists in capturing the economic impact of natural ecosystems being depleted and destroyed by human activities via a pinch of thermodynamic potentials. This viewpoint allows: (i) the full-blown integration of a limited quantity of primary resources into a non-linear macrodynamics that is stock-flow consistent both in terms of matter-energy as well as economic transactions; (ii) the inclusion of natural and forced recycling; (iii) the inclusion of a friction term which reflects the impossibility of producing goods and services in high metabolising intensity without exuding energy and matter wastes; (iv) the computation of the anthropically produced entropy as a function of intensity and friction. Analysis and numerical computations confirm the role played by intensity and friction as key factors for sustainability. Our approach is flexible enough to allow for various economic models to be embedded into our thermodynamic framework.

Sławomir Januszek, Natalia Siwiec, Rafał Januszek et al.

There are many arguments for the safety and efficacy of COVID-19 vaccines in pregnancy. The aim of this study is to describe the level of vaccination acceptance, to find the factors that most influence the decision to vaccinate, and to describe the scale of changes in vaccination acceptance influenced by medical information on the safety, efficacy, and benefits of vaccination among pregnant women. A total of 300 patients completed the questionnaire, including 150 in Poland and 150 in the Ukraine. The level of vaccination acceptance was assessed before and after medical consultation. There were 53 (35.3%) patients with the intention to get vaccinated in Poland and 25 (16.7%) in the Ukraine. After consultation with a physician, this increased to 109 (72.6%) in Poland and 69 (46%) in the Ukraine. The main factors influencing the acceptance of vaccinations were the fear of harming the foetus (OR-0.119, CI-0.039–0.324 <i>p</i> < 0.001), complications in pregnancy (OR-0.073 CI-0.023–0.197 <i>p</i> < 0.001), and limitations in the vaccination programme (OR-0.026 CI-0.001–0.207 <i>p</i> < 0.001). Medical information about the safety, effectiveness and benefits of vaccinations among pregnant women, provided during a medical visit, may increase the acceptance of vaccinations by 105.6%, as among Polish patients, and by 176%, as among pregnant women from the Ukraine.

Gilang Adi Firmansyah, Dyah Fauziah, Brahmana Askandar Tjokroprawiro

Highlights: 1. The major risk factors for type I endometrial cancer, namely age and obesity, play a major role in the increase in this case and are thought to be related to the grade in these cancer patients. 2. Type I endometrial cancer patients at Dr. Soetomo General Academic Hospital 2019-2020 are dominated by patients diagnosed at the age of 56-65 years, having an overweight body mass index (23-24.9 kg/m2). 3. The patient's age and body mass index did not correlate with endometrial cancer type I grade. Abstract Background: The increase in obesity and life expectancy has contributed to type I endometrial cancer cases worldwide. Increased risk factors play a role in the increase of these cases. Objectives: To determine the relationship between age and BMI with the cancer grade. Material and Method: This research was a cross-sectional study. The data were obtained from the patient’s medical records. The sampling technique was total sampling. The analysis used was Spearman Rho correlation test for the relationship between age and BMI with cancer grade. Results: This study recorded 54 patients with type I endometrial cancer in Dr. Soetomo General Academic Hospital, Surabaya, Indonesia, from 2019 to 2020. The patients were from the age group 56-65 years 25 patients (46.30%), 46-55 years 17 patients (31.48%), 36-45 years 8 patients (14.81%), 26-35 years 2 patients (3.7%), and >65 years 2 patients (3.7%). For BMI, the patients were overweight (23-24.9 kg/m2) 21 patients (38.89%), normal (18.5-22.9 kg/m2) 14 patients (25.93%), obesity (25-29.9 kg/m2) 12 patients (22.22%), and obesity II (≥30 kg/m2) 7 patients (12.96%). For grade, grade III were 22 patients (40.75%), grade II  20 patients (37.04%), and grade I 12 patients (22.22%). There was a weak, insignificant positive correlation between age with grade (ρ=0.116, 0.405>α=0.05) and a weak, insignificant negative correlation between BMI with grade (ρ=-0.206, 0.135>α=0.05). Conclusion: A total of 54 patients with type I endometrial cancer at Dr. Soetomo General Academic Hospital, Surabaya, Indonesia, from 2019-2020 aged 56-65 years and overweight (23-24.9 kg/m2) with grade III cancer. The patient's age and BMI did not correlate with the patient's grade.

Nuhamin Tesfa Tsega, Daniel Gashaneh Belay, Fantu Mamo Aragaw et al.

Abstract Background The period of youth is important for the foundation of healthy and stable relationships, women’s health and well-being. Youth women face a higher risk of experiencing violence than older women. Intimate partner violence (IPV) against youth women is a significant public health concern. Despite paramount negative health consequences of IPV for the survivor, as per our knowledge, research study on IPV and associated factors among youth women in Ethiopia is scarce. Therefore, this study aimed to assess the magnitude and associated factors of IPV among youth women in Ethiopia. Methods The data was accessed from 2016 Ethiopia demographic and health survey (EDHS) which was a cross sectional population based household survey. It was also conducted using a multi-stage stratified random cluster sampling approach. The data were cleaned, weighted, and analyzed using STATA Version 14 software. The total weighted sample of 1077 youth women were used in this study. Multilevel logistic regression modeling was used to determine factors associated with IPV among youth women. Adjusted odds ratio (AOR) with 95% confidence interval (CI) and p value < 0.05 were used to declare the significant variables. Results Among the total participants, 30.27% (95% CI 27.59, 33.09) of youth women experienced IPV. Individual level variables such as: Being widowed/divorced/separated (AOR = 2.28; 95% CI 1.33, 3.91), having a partner who drinks alcohol (AOR = 5.76; 95% CI 3.42, 9.69), witnessing inter-parental violence during childhood (AOR = 3.45; 95% CI 2.21, 5.37), being afraid of partners (AOR = 7.09; 95% CI 4.30, 11.68), and from community level variables, youth women residing in communities with a low proportion of educated youth women (AOR = 0.31; 95% CI 0.13, 0.78) were significantly associated with having experience of IPV. Conclusion The magnitude of intimate partner violence among youth women in Ethiopia was relatively high as compared to the global estimate of IPV. Individual and community level variables such as currently widowed/divorced/separated women, having a partner who drinks alcohol, witnessing inter-parental violence, being afraid of partner, and women from a low proportion of community level youth women's education were significantly associated with intimate partner violence. To decrease this public health problem, it is better to strengthen legislation on the purchase and sale of alcohol, provide legal protection for separated/divorced women, establish effective legal response services for IPV, promote gender equality, and provide psychological support for those who witnessed inter-parental violence during childhood to reduce IPV.

Юрий Алексеевич Семенов, Анна Валерьевна Чижовская, Валентина Федоровна Долгушина et al.

The problem of premature birth (PB) has been one of the most relevant and priority issues in obstetrics for many years. Due to the fact that their frequency has no downward trend. According to WHO, every year about 11 per cent (15 million) of children are born prematurely, more than 1 million of them die in their first year of life, and 25 to 50 per cent of survivors have some form of systemic deficiency. Two-thirds of the PB comes spontaneously, the rest of it was induced by medical intervention to help the mother or fetus in life-threatening conditions. The aim of the research – analyze the dynamics of the frequency of spontaneous premature births in Chelyabinsk and Chelyabinsk Region from 2012 to 2020. To make a forecast of this indicator for the next 5 years. Assess the impact of spontaneous premature births on perinatal mortality. Materials and methods. The analysis of the data of frequency of spontaneous PB, indicators of stillbirth rate, the dynamics of early neonatal mortality and perinatal mortality for 2012-2020 in Chelyabinsk and Chelyabinsk Region. Results.  Spontaneous PB in Chelyabinsk for 2012-2020 has increased until 2018 (7.6 %) with a subsequent reduction to 7.1 %, as in the Chelyabinsk region: 5.6 % in 2012, 6.5 % in 2018 and 6.3 % in 2020. While the frequency of spontaneous ultra-early RB declined gradually until 2015 (6.3 %) with further growth to 8.3 % in 2016. Due to improved routing and specialized care for pregnant women, this indicator reduced to 5.2 % by 2019. The reinvigoration of extremely early PB to 8.6 % in 2020 is likely due to a pandemic of a new coronavirus infection. The rate of early neonatal mortality declined steadily until 2016 (7.3 ‰), with further growth in 2017-2018, which is certainly due to an increase the level of PB in the same year. The stillbirth rate, like perinatal mortality, has a wave-like pattern of change, but remains approximately the same – 88 ‰. The level of these indicators varies directly according to the number of cases of PB and does not currently have a decreasing trend. Conclusion. Thus, the analysis of the frequency of spontaneous PB in Chelyabinsk for 2012-2020 showed an increase of cases of PB until 2018 with a subsequent reduction after that, a wave-like change in the frequency of spontaneous ultra-early PB without a downward trend. The rate of spontaneous PB in the Chelyabinsk region is going to increase for the next 5 years to 7.2 %. In this regard, it is necessary to carry out a further search for reliable predictors of the development of spontaneous PB, the definition of a «window of therapeutic possibilities», when the treatment would have avoided extremely early PB.

Hafez Farazi, Jan Nogga, and Sven Behnke

The ultimate goal of video prediction is not forecasting future pixel-values given some previous frames. Rather, the end goal of video prediction is to discover valuable internal representations from the vast amount of available unlabeled video data in a self-supervised fashion for downstream tasks. One of the primary downstream tasks is interpreting the scene's semantic composition and using it for decision-making. For example, by predicting human movements, an observer can anticipate human activities and collaborate in a shared workspace. There are two main ways to achieve the same outcome, given a pre-trained video prediction and pre-trained semantic extraction model; one can first apply predictions and then extract semantics or first extract semantics and then predict. We investigate these configurations using the Local Frequency Domain Transformer Network (LFDTN) as the video prediction model and U-Net as the semantic extraction model on synthetic and real datasets.