Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Feasibility of an Early Childhood Intervention Using Mobile Phones Among Low-Income Mothers of Newborns: Qualitative Interview Study

Background Many children aged younger than 5 years living in low- and middle-income countries are at risk for poor development. Early child development (ECD) programs are cost-effective strategies to reduce poverty, crime, school dropouts, and socioeconomic inequality. With the spread of low-cost mobile phones and internet access in low- and middle-income countries, new service delivery models such as mobile phone–aided interventions have a great potential to improve early childhood development. Objective This study aimed to identify the beliefs on importance of ECD, feasibility of a proposed intervention using mobile phones and factors that may affect the usability of the intervention among mothers of newborns in a poverty-stricken area in southwestern China. Methods We conducted an in-depth, semistructured interview study of 25 low-income mothers of newborns recruited from two county hospitals in Yunnan Province. We applied the health belief model and cultural competence theories to identify the facilitators, barriers, and preferences among the target population for parenting knowledge. Results The results showed that the participants had low health literacy and high perceived needs for learning ECD knowledge. At the same time, they experienced several barriers to learning parenting information and following evidence-based instructions including having limited time, limited financial resources, and different opinions on childcare among family members. Many participants preferred to receive personalized messages tailored to their specific needs and preferred videos or graphics to text only in the messages. Many favored a separate module to support postpartum mental health. Conclusions The study assessed the acceptability of an early childhood intervention using mobile phones to meet the needs of the target population based on their beliefs, traits, and preferences and provided suggestions to refine the intervention to improve its usability.
Peanut Response to Prohexadione Calcium, a New Plant Growth Regulator

Abstract Experiments in 1992, 1993, and 1994 evaluated prohexadione calcium (calcium salt of 3,5-dioxo-4-propionylcyclohexanecarboxylic acid) as a growth regulator for peanut (Arachis hypogaea L.).
Partial Genomic Sequence of Buffalo (Bubalus bubalis) ITGB2 Gene

Abstract Niranjan, S.K. , Deb, S.M. , Mitra, A. , Sharma, D. , Sharma, A and Sharma A. 2005. Partial genomic sequence of buffalo (Bubalus bubalis) ITGB2 gene. J. Appl. Anim. Res., 28: 41–43. A fragment of 367 bp corresponding to parts of fifth and sixth exons flanking intron five of ITGB2 was amplified in river buffaloes (Bubalus bubalis). The Taq I-RFLP analysis showed the absence of BLAD (D128G) allele in the buffalo population studied. The sequence data of the amplicon, first report on buffalo ITGB2, was submitted to Genbank. Single nucleotide changes at seven places in fifth exon of buffalo ITGB2 led to substitution of Val140 and Asp159 and creation of one Msp I site.
Hepatocyte KLF6 expression affects FXR signalling and the clinical course of primary sclerosing cholangitis

Primary sclerosing cholangitis (PSC) is characterized by chronic cholestasis and inflammation, which promotes cirrhosis and an increased risk of cholangiocellular carcinoma (CCA). The transcription factor Krueppel‐like‐factor‐6 (KLF6) is a mediator of liver regeneration, steatosis, and hepatocellular carcinoma (HCC), but no data are yet available on its potential role in cholestasis. Here, we aimed to identify the impact of hepatic KLF6 expression on cholestatic liver injury and PSC and identify potential effects on farnesoid‐X‐receptor (FXR) signalling.
Risk Factors Influencing the Incidence of Ankle Sprain Among Elite Football and Basketball Players: A Prospective Study

Introduction. The objective of the present study was to investigate whether certain intrinsic factors (foot hyperpronation, generalized joint laxity) and clinical tests (anterior drawer and talar tilt tests, single-leg balance test and star excursion balance test, ankle and first metatarsophalangeal range of motion) could predict the incidence of lateral ankle sprains among elite football and basketball players during a full year. Method. In a prospective cohort study, 106 elite basketball and football players were recruited. During the preseason period, players underwent baseline measurements. Team physicians in following year reported occurrence of new ankle sprains. Results. Ankle sprain was more frequent among basketball players (P = .01). The history of recurrent (P = .001) and acute ankle sprain (P = .01) and each 5-year increase in age (P = .039) were predictive factors for ankle sprain. No evidence for relationship between other risk factors and occurrence of ankle sprain were achieved. Conclusion. In our study, the history of recurrent and acute ankle sprain was the strongest predictor for ankle injuries. Considering the limitations of this study, it seems mandatory to conduct more prospective studies with a larger sample size and longer follow-up period. Levels of Evidence: Level II: Prognostic
Sugar-sweetened beverage consumption and association with weight status in Irish children: a cross-sectional study prior to the introduction of a government tax on sugar-sweetened beverages

Abstract Objective: To provide baseline evidence of sugar-sweetened beverage (SSB) consumption in a sample of Irish children prior to the introduction of the SSB tax; to identify the energy contribution of SSB to daily energy intake; and to explore the association between SSB consumption and overweight/obesity. Design: Cross-sectional study. Setting: Primary schools in Cork, Ireland in 2012. Participants: 1075 boys and girls aged 8–11 years. SSB consumption was assessed from 3-d food diaries. BMI was used to define obesity (International Obesity Taskforce definitions). Plausible energy reporters (n 724, 68 % of total sample) were classified using Schofield equation. Results: Eighty-two per cent of children with plausible energy intake consumed SSB. Mean energy intake from SSB was 485 kJ (6 % of total kJ). Mean kilojoules from SSB increased with weight status from 443 kJ for normal-weight children to 648 kJ for children with overweight/obesity (5·8 and 7·6 % of total kJ, respectively). Mean SSB intake was significantly higher in children with overweight/obesity than normal-weight children (383 and 315 ml/d). In adjusted analyses, children consuming >200 ml/d had an 80 % increased odds of overweight/obesity compared to those consuming <200 ml/d (OR 1·8, 95 % CI 1·0, 3·5). Family socioeconomic status and lifestyle determinants, including frequency of takeaway consumption and TV viewing, were also significantly associated with SSB consumption. Conclusions: SSB account for a substantial proportion of daily energy intake and are significantly associated with child overweight/obesity. This study provides baseline data from a sample of children from which the impact of the SSB tax can be benchmarked.
Psychosocial Factors Influence Sexual Satisfaction among Women with Vulvodynia

Abstract Vulvodynia affects about 8% of women, many of whom report a negative impact on their ability to have sexually satisfying relationships. In this study, we examined predictors of sexual satisfaction in 207 women with clinically confirmed vulvodynia. We adapted a model examining resilience in chronic pain patients originally developed by Sturgeon and Zautra to include resilience factors (communication with partner about sexual health and coping strategies) and vulnerable factors (abuse history, pain intensity, rumination). These variables were regressed onto sexual satisfaction. In the full model, only emotion-based rumination was predictive of sexual satisfaction. Thus, focusing on emotion-based rumination in clinical intervention may improve sexual satisfaction.
Quantitative analysis of Y-Chromosome gene expression across 36 human tissues

Little is known about how human Y-Chromosome gene expression directly contributes to differences between XX (female) and XY (male) individuals in nonreproductive tissues. Here, we analyzed quantitative profiles of Y-Chromosome gene expression across 36 human tissues from hundreds of individuals. Although it is often said that Y-Chromosome genes are lowly expressed outside the testis, we report many instances of elevated Y-Chromosome gene expression in a nonreproductive tissue. A notable example is EIF1AY, which encodes eukaryotic translation initiation factor 1A Y-linked, together with its X-linked homolog EIF1AX. Evolutionary loss of a Y-linked microRNA target site enabled up-regulation of EIF1AY, but not of EIF1AX, in the heart. Consequently, this essential translation initiation factor is nearly twice as abundant in male as in female heart tissue at the protein level. Divergence between the X and Y Chromosomes in regulatory sequence can therefore lead to tissue-specific Y-Chromosome-driven sex biases in expression of critical, dosage-sensitive regulatory genes.
Homology modeling of human GABA-AT and devise some novel and potent inhibitors via computer-aided drug design techniques

Abstract γ-aminobutyric acid aminotransferase (GABA-AT) is a pyridoxal 5′-phosphate (PLP)-dependent enzyme which degrades γ-aminobutyric (GABA) in the brain. GABA is an important inhibitory neurotransmitter that plays important neurological roles in the brain. Therefore, GABA-AT is an important drug target which regulates the GABA level. Novel and potent drug development to inhibit GABA-AT is still very challenging task. In this study, we aimed to devise novel and potent inhibitors against GABA-AT using computer-aided drug design (CADD) tools. However, the human GABA-AT crystal structure is not available yet, and we built the 3D structure of human GABA-AT based on the crystal structure of pig’s liver (Sus Scrofa) enzyme as a template. The generated model was validated with numerous tools such as ProSA and PROCHECK. A set of selected well-known inhibitors have been tested against the modeled GABA-AT. Molecular docking studies have been accomplished via application of Genetic Optimization for Ligand Docking (GOLD), Vina and Autodock 4.2 software to search for potent inhibitors. The best two candidate inhibitors have been computationally examined for absorption, distribution, metabolism, elimination and toxicity descriptors (ADMET) and Lipinski’s rule of 5. Lastly, molecular dynamics (MD) simulations were carried out to inspect the ligands’ binding mode and stability of the active site of human GABA-AT over time. The top ranked ligands exhibited reliable stability throughout the MD simulation. The selected compounds are promising candidates and might be tested experimentally for the inhibition of human GABA-AT enzyme. Communicated by Ramaswamy H. Sarma
Anaphylaxis in pregnancy: a population‐based multinational European study

Anaphylaxis in pregnancy is a rare but severe complication for both mother and infant. Population‐based data on anaphylaxis in pregnancy are lacking from mainland European countries. This multinational study presents the incidence, causative agents, management and maternal and infant outcomes of anaphylaxis in pregnancy. This descriptive multinational study used a combination of retrospective (Finnish medical registries) and prospective population‐based studies (UK, France, Belgium and the Netherlands) to identify cases of anaphylaxis. Sixty‐five cases were identified among 4,446,120 maternities (1.5 per 100,000 maternities; 95%CI 1.1–1.9). The incidence did not vary between countries. Approximately three‐quarters of reactions occurred at the time of delivery. The most common causes were antibiotics in 27 women (43%), and anaesthetic agents in 11 women (17%; including neuromuscular blocking drugs, 7), which varied between countries. Anaphylaxis had very poor outcomes for one in seven mothers and one in seven babies; the maternal case fatality rate was 3.2% (95%CI 0.4–11.0) and the neonatal encephalopathy rate was 14.3% (95%CI 4.8–30.3). Across Europe, anaphylaxis related to pregnancy is rare despite having a multitude of causative agents and different antibiotic prophylaxis protocols.
FINANCIAL MARKET RETURNS

Hani El-Chaarani. 2015. Volatility spillover between Lebanese political shocks and financial market returns. Lebanese Science Journal, 16(2): 95-111. This paper examines the impact of Lebanese political news announcements on Beirut Stock Exchange (BSE) returns and volatility from 2005 to 2014. Using a sample of (294) Lebanese political news, the results from GARCH, EGARCH and ARCH models reveal significant impacts of favorable and unfavorable political news on BSE returns. Favorable political news has a positive impact while unfavorable political news has a negative impact. This research also confirms that both favorable and unfavorable political news announcements increase BSE volatility. Additional analysis shows that unfavorable political news has greater impacts on BSE volatility and returns than favorable political news. It seems that BSE investors are more sensitive to unfavorable political news which leads them to avoid the regret feeling by following the market tendency. The findings of this study show that the Lebanese banking sector plays a positive role by mitigating the negative impact of bad political news.
Neural Text-to-Speech Synthesis for an Under-Resourced Language in a Diglossic Environment: the Case of Gascon Occitan

Occitan is a minority language spoken in Southern France, some Alpine Valleys of Italy, and the Val d’Aran in Spain, which only very recently started developing language and speech technologies. This paper describes the first project for designing a Text-to-Speech synthesis system for one of its main regional varieties, namely Gascon. We used a state-of-the-art deep neural network approach, the Tacotron2-WaveGlow system. However, we faced two additional difficulties or challenges: on the one hand, we wanted to test if it was possible to obtain good quality results with fewer recording hours than is usually reported for such systems; on the other hand, we needed to achieve a standard, non-Occitan pronunciation of French proper names, therefore we needed to record French words and test phoneme-based approaches. The evaluation carried out over the various developed systems and approaches shows promising results with near production-ready quality. It has also allowed us to detect the phenomena for which some flaws or fall of quality occur, pointing at the direction of future work to improve the quality of the actual system and for new systems for other language varieties and voices.
TRopBank: Turkish PropBank V2.0

In this paper, we present and explain TRopBank “Turkish PropBank v2.0”. PropBank is a hand-annotated corpus of propositions which is used to obtain the predicate-argument information of a language. Predicate-argument information of a language can help understand semantic roles of arguments. “Turkish PropBank v2.0”, unlike PropBank v1.0, has a much more extensive list of Turkish verbs, with 17.673 verbs in total.
A Dataset of Mycenaean Linear B Sequences

We present our work towards a dataset of Mycenaean Linear B sequences gathered from the Mycenaean inscriptions written in the 13th and 14th century B.C. (c. 1400-1200 B.C.). The dataset contains sequences of Mycenaean words and ideograms according to the rules of the Mycenaean Greek language in the Late Bronze Age. Our ultimate goal is to contribute to the study, reading and understanding of ancient scripts and languages. Focusing on sequences, we seek to exploit the structure of the entire language, not just the Mycenaean vocabulary, to analyse sequential patterns. We use the dataset to experiment on estimating the missing symbols in damaged inscriptions.
A Platform for Event Extraction in Hindi

Event Extraction is an important task in the widespread field of Natural Language Processing (NLP). Though this task is adequately addressed in English with sufficient resources, we are unaware of any benchmark setup in Indian languages. Hindi is one of the most widely spoken languages in the world. In this paper, we present an Event Extraction framework for Hindi language by creating an annotated resource for benchmarking, and then developing deep learning based models to set as the baselines. We crawl more than seventeen hundred disaster related Hindi news articles from the various news sources. We also develop deep learning based models for Event Trigger Detection and Classification, Argument Detection and Classification and Event-Argument Linking.
Emotional Speech Corpus for Persuasive Dialogue System

Expressing emotion is known as an efficient way to persuade one’s dialogue partner to accept one’s claim or proposal. Emotional expression in speech can express the speaker’s emotion more directly than using only emotion expression in the text, which will lead to a more persuasive dialogue. In this paper, we built a speech dialogue corpus in a persuasive scenario that uses emotional expressions to build a persuasive dialogue system with emotional expressions. We extended an existing text dialogue corpus by adding variations of emotional responses to cover different combinations of broad dialogue context and a variety of emotional states by crowd-sourcing. Then, we recorded emotional speech consisting of of collected emotional expressions spoken by a voice actor. The experimental results indicate that the collected emotional expressions with their speeches have higher emotional expressiveness for expressing the system’s emotion to users.
PATE: A Corpus of Temporal Expressions for the In-car Voice Assistant Domain

The recognition and automatic annotation of temporal expressions (e.g. “Add an event for tomorrow evening at eight to my calendar”) is a key module for AI voice assistants, in order to allow them to interact with apps (for example, a calendar app). However, in the NLP literature, research on temporal expressions has focused mostly on data from the news, from the clinical domain, and from social media. The voice assistant domain is very different than the typical domains that have been the focus of work on temporal expression identification, thus requiring a dedicated data collection. We present a crowdsourcing method for eliciting natural-language commands containing temporal expressions for an AI voice assistant, by using pictures and scenario descriptions. We annotated the elicited commands (480) as well as the commands in the Snips dataset following the TimeML/TIMEX3 annotation guidelines, reaching a total of 1188 annotated commands. The commands can be later used to train the NLU components of an AI voice assistant.
Joint Learning of Syntactic Features Helps Discourse Segmentation

This paper describes an accurate framework for carrying out multi-lingual discourse segmentation with BERT (Devlin et al., 2019). The model is trained to identify segments by casting the problem as a token classification problem and jointly learning syntactic features like part-of-speech tags and dependency relations. This leads to significant improvements in performance. Experiments are performed in different languages, such as English, Dutch, German, Portuguese Brazilian and Basque to highlight the cross-lingual effectiveness of the segmenter. In particular, the model achieves a state-of-the-art F-score of 96.7 for the RST-DT corpus (Carlson et al., 2003) improving on the previous best model by 7.2%. Additionally, a qualitative explanation is provided for how proposed changes contribute to model performance by analyzing errors made on the test data.
English Recipe Flow Graph Corpus

We present an annotated corpus of English cooking recipe procedures, and describe and evaluate computational methods for learning these annotations. The corpus consists of 300 recipes written by members of the public, which we have annotated with domain-specific linguistic and semantic structure. Each recipe is annotated with (1) ‘recipe named entities’ (r-NEs) specific to the recipe domain, and (2) a flow graph representing in detail the sequencing of steps, and interactions between cooking tools, food ingredients and the products of intermediate steps. For these two kinds of annotations, inter-annotator agreement ranges from 82.3 to 90.5 F1, indicating that our annotation scheme is appropriate and consistent. We experiment with producing these annotations automatically. For r-NE tagging we train a deep neural network NER tool; to compute flow graphs we train a dependency-style parsing procedure which we apply to the entire sequence of r-NEs in a recipe.In evaluations, our systems achieve 71.1 to 87.5 F1, demonstrating that our annotation scheme is learnable.
Differential Expression and Association of Calcium Channel α1B and β Subunits during Rat Brain Ontogeny*

Calcium functions as an essential second messenger during neuronal development and synapse acquisition. Voltage-dependent calcium channels (VDCC), which are critical to these processes, are heteromultimeric complexes composed of α1, α2/δ, and β subunits. β subunits function to direct the VDCC complex to the plasma membrane as well as regulate its channel properties. The importance of β to neuronal functioning was recently underscored by the identification of a truncated β4 isoform in the epileptic mouse lethargic (lh) (Burgess, D. L., Jones, J. M., Meisler, M. H., and Noebels, J. L. (1997) Cell 88, 385–392). The goal of our study was to investigate the role of individual β isoforms (β1b, β2, β3, and β4) in the assembly of N-type VDCC during rat brain development. By using quantitative Western blot analysis with anti-α1B-directed antibodies and [125I-Tyr22]ω-conotoxin GVIA (125I-CTX) radioligand binding assays, we observed that only a small fraction of the total α1B protein present in embryonic and early postnatal brain expressed high affinity125I-CTX-binding sites. These results suggested that subsequent maturation of α1B or its assembly with auxiliary subunits was required to exhibit high affinity125I-CTX binding. The temporal pattern of expression of β subunits and their assembly with α1B indicated a developmental pattern of expression of β isoforms: β1b increased 3-fold from P0 to adult, β4 increased 10-fold, and both β2 and β3 expression remained unchanged. As the β component of N-type VDCC changed during postnatal development, we were able to identify both immature and mature forms of N-type VDCC. At P2, the relative contribution of β is β1b > β3 ≫ β2, whereas at P14 and adult the distribution is β3 > β1b = β4. Although we observed no β4 associated with the α1B at P2, β4 accounted for 14 and 25% of total α1B/β subunit complexes in P14 and adult, respectively. Thus, of the β isoforms analyzed, only the β4 was assembled with the rat α1B to form N-type VDCC with a time course that paralleled its level of expression during rat brain development. These results suggest a role for the β4 isoform in the assembly and maturation of the N-type VDCC.
TopicNet: Making Additive Regularisation for Topic Modelling Accessible

This paper introduces TopicNet, a new Python module for topic modeling. This package, distributed under the MIT license, focuses on bringing additive regularization topic modelling (ARTM) to non-specialists using a general-purpose high-level language. The module features include powerful model visualization techniques, various training strategies, semi-automated model selection, support for user-defined goal metrics, and a modular approach to topic model training. Source code and documentation are available at https://github.com/machine-intelligence-laboratory/TopicNet