We propose a generative framework for simultaneous machine translation. Conventional approaches use a fixed number of source words to translate or learn dynamic policies for the number of source words by reinforcement learning. Here we formulate simu
ltaneous translation as a structural sequence-to-sequence learning problem. A latent variable is introduced to model read or translate actions at every time step, which is then integrated out to consider all the possible translation policies. A re-parameterised Poisson prior is used to regularise the policies which allows the model to explicitly balance translation quality and latency. The experiments demonstrate the effectiveness and robustness of the generative framework, which achieves the best BLEU scores given different average translation latencies on benchmark datasets.
Most existing simultaneous machine translation (SiMT) systems are trained and evaluated on offline translation corpora. We argue that SiMT systems should be trained and tested on real interpretation data. To illustrate this argument, we propose an in
terpretation test set and conduct a realistic evaluation of SiMT trained on offline translations. Our results, on our test set along with 3 existing smaller scale language pairs, highlight the difference of up-to 13.83 BLEU score when SiMT models are evaluated on translation vs interpretation data. In the absence of interpretation training data, we propose a translation-to-interpretation (T2I) style transfer method which allows converting existing offline translations into interpretation-style data, leading to up-to 2.8 BLEU improvement. However, the evaluation gap remains notable, calling for constructing large-scale interpretation corpora better suited for evaluating and developing SiMT systems.
Knowledge Grounded Conversation Models are usually based on a selection/retrieval module and a generation module, trained separately or simultaneously, with or without having access to a gold' knowledge option. With the introduction of large pre-trai
ned generative models, the selection and generation part have become more and more entangled, shifting the focus towards enhancing knowledge incorporation (from multiple sources) instead of trying to pick the best knowledge option. These approaches however depend on knowledge labels and/or a separate dense retriever for their best performance. In this work we study the unsupervised selection abilities of pre-trained generative models (e.g. BART) and show that by adding a score-and-aggregate module between encoder and decoder, they are capable of learning to pick the proper knowledge through minimising the language modelling loss (i.e. without having access to knowledge labels). Trained as such, our model - K-Mine - shows competitive selection and generation performance against models that benefit from knowledge labels and/or separate dense retriever.
The aim of this study is to evaluate Jordanian Women's opinions, beliefs, and practices towards using different medicinal plants for postpartum health problems care.
Method: A cross-sectional observational study was conducted on 300 mothers aged 18
years and above. A structured valid and reliable questionnaire was used for collecting personal, medical and nutritional related data including: gestational weight gain characteristics, the effect of delivery and breast feeding on postpartum weight gain and herbal tea consumption for the management of different postpartum health problems such as postpartum colic, flatulence, spasm, maternal bleeding, lactation and weight gain. The above data where collected through a personal interview by the trained investigators.
Results: Around 45% of participants were overweight or obese with average post-pregnancy BMI of 25.1±4.94 kg/m2. Majority of participants (84%) used one or more medicinal plants after delivery to control their postpartum health problems. The participants may seek herbal help mainly for maternal purposes such as decreasing post-delivery colic, flatulence and spasm (52.9%), treating maternal postpartum bleeding (41.7%) and lactation enhancement (41.0%). Conversely, only 9.0% of participants used herbals for weight control. The most commonly used herbals were cinnamon (49.0%), sage (42.0%), and anise (38.0%).
Conclusions: The potential risk of medicinal plant self-medication is high for managing postpartum complications that need a professional evidence-based practice recommendation
Predicting the next utterance in dialogue is contingent on encoding of users' input text to generate appropriate and relevant response in data-driven approaches. Although the semantic and syntactic quality of the language generated is evaluated, more
often than not, the encoded representation of input is not evaluated. As the representation of the encoder is essential for predicting the appropriate response, evaluation of encoder representation is a challenging yet important problem. In this work, we showcase evaluating the text generated through human or automatic metrics is not sufficient to appropriately evaluate soundness of the language understanding of dialogue models and, to that end, propose a set of probe tasks to evaluate encoder representation of different language encoders commonly used in dialogue models. From experiments, we observe that some of the probe tasks are easier and some are harder for even sophisticated model architectures to learn. And, through experiments we observe that RNN based architectures have lower performance on automatic metrics on text generation than transformer model but perform better than the transformer model on the probe tasks indicating that RNNs might preserve task information better than the Transformers.
Neural generative dialogue agents have shown an increasing ability to hold short chitchat conversations, when evaluated by crowdworkers in controlled settings. However, their performance in real-life deployment -- talking to intrinsically-motivated u
sers in noisy environments -- is less well-explored. In this paper, we perform a detailed case study of a neural generative model deployed as part of Chirpy Cardinal, an Alexa Prize socialbot. We find that unclear user utterances are a major source of generative errors such as ignoring, hallucination, unclearness and repetition. However, even in unambiguous contexts the model frequently makes reasoning errors. Though users express dissatisfaction in correlation with these errors, certain dissatisfaction types (such as offensiveness and privacy objections) depend on additional factors -- such as the user's personal attitudes, and prior unaddressed dissatisfaction in the conversation. Finally, we show that dissatisfied user utterances can be used as a semi-supervised learning signal to improve the dialogue system. We train a model to predict next-turn dissatisfaction, and show through human evaluation that as a ranking function, it selects higher-quality neural-generated utterances.
Cesarean delivery rates have risen in Syria, as well all globally, in recent years. In our country, their prevalence is 16-27%. Surgical complications were compared between patients with three or less prior cesarean deliveries and four or more prior
cesarean deliveries. Records of 120 patients who had undergone cesarean sections in our Department of Obstetrics and Gynecology, between August and November 2019, were retrospectively studied. Cases were reviewed on the basis of age, type of operation, type of anesthesia, number of cesarean sections, time of hospitalization, and intra-operative and postoperative complications. Cesarean sections had been performed on 62 (51.7%) patients whose cesarean number was three or less, while 58 (48.3%) patients had multiple cesarean sections four or more. There is no greater risk of maternal complications in patients with four or more prior cesareans, excepting intra-abdominal adhesions.
Conflicting data exist concerning the implications of isolated oligohydramnios on pregnancy outcome at term. Aim: To assess the association between isolated oligohydramnios at term and pregnancy outcome in low-risk pregnancies. Materials and Methods:
This was a retrospective cohort study of term pregnancies with sonographic finding of isolated Oligohydramnios (amniotic fluid index (AFI) <5 cm) between 2017 and 2019, conducted at Obstetrics and Gynecology Department, Tishreen University Hospital, Lattakia, Syria, during the period between January 2019 – January 2020. Outcome was compared to a control group of pregnancies with normal AFI (5–25 cm). Pregnancies complicated by hypertension, diabetes, deviant fetal growth or chromosomal/ structural abnormalities were excluded. Composite adverse outcome included cesarean section delivery, low Apgar score, neonatal intensive care admission, meconium aspiration syndrome, or intubation. Results: Overall, 190 pregnancies complicated by isolated oligohydramnios were compared to 200 low-risk pregnancies with normal AFI. Isolated oligohydramnios was associated with a higher rate of induction of labor (29.8 % vs. 4 %, p < 0.05), cesarean section delivery (21.6 vs. 13 %, p < 0.05) and composite adverse outcome (13.2 % vs. 7 %, p < 0.05). However, after adjusting for potential confounders as induction of labor and nulliparity using multivariable logistic regression analysis, isolated oligohydramnios was not found to be independently associated with increased risk for composite adverse outcome (OR 1.07, 95 % CI 0.9–1.31, p = 0.87). Conclusion: Isolated oligohydramnios at term by itself is not associated with increased obstetrical morbidity.
Pregnancy and childbirth are two instinctive actions that a woman's reproductive system performs in order to produce a new organism that completes the continuity of life, and childbirth is the outcome of pregnancy for several months, and it is suppos
ed to be as calm and safe as possible for both mother and child, and birth pains differ from mother to mother and even from birth To another, it is very special and depends on several factors, including: the mother's ability to withstand pain, the size and position of the fetus, and the strength of uterine contractions during childbirth. Since ancient history, various ideas and methods have appeared to overcome the pain of childbirth in which there was a lot of sorcery and a little logic, but With the development of science and deepening into the depths of the human psyche, the idea of childbirth without pain began to develop, and it became based on scientific foundations, especially after the rapid development in the field of obstetric anesthesia and the numerous studies in the field of local anesthesia and epidural anesthesia, where this method changed all the parameters of childbirth without pain to become a realistic reality Women touch it daily in maternity homes scattered all over the world while maintaining complete alertness without fear, anxiety or pain, and actively participating in full vigilance and vigilance in the status of their newborn while he is fully active and effective and without little discouragement, and Peridural analgesia is considered one of the best types of analgesia and anesthesia used to accomplish childbirth and cesarean section, and it has received many international studies.
Skin-to-skin contact (SSC) between the mother and her infant immediately post-delivery is an important procedure that must be included in the care given to mother and her infant many health benefits. The mother's desire and reaction towards (SSC) is
the decisive factor in the success of this procedure, where personal factors in the mother's life play a role in agreeing to this way of care. Therefore, the present study aims to identifying the mother's initial Reaction to (SSC) with her infant after childbirth, and identifying the factors affecting this and finding a scientific solutions to it.
This descriptive study was conducted to investigate the initial reaction of 200 women towards (SSC) immediately after their vaginal delivery were randomly selected from labor section of the obstetric hospital and national children in Lattakia, the data were collected using a developed questionnaire for this purpose.
The results showed that nearly three-quarters of mothers agreed to have contact with their children in (SSC) and nearly three-quarters of approvals preferred to be covered. The highest rate of response to approvals for contact with their children immediately after birth was the expression of joy in child and then hugging and kissing him. While the highest response of non-approvals for contact with their children immediately Post-Delivery refused to touch the child because they were suffering of pain, There was also a significant difference between the consent of women to their child's carry and non- carry according to the variables of the cultural level, the economic situation, the number of births and the current state of birth.
The study recommended that every mother in the labor room should be investigated for carrying her naked child or swaddled with a blanket immediately after birth, not forcing them to immediately postpartum (SSC), and to conduct continuing education and training courses to provide all midwives and nurses working in labor rooms as well as mothers in their care settings With information and skills on the implementation of SSC between mother and newborn immediately after birth, and further research on nurse and midwife information on the importance of prompt (SSC) immediately Post-Delivery.
