Miracle-dz/UniFAR-FTUs huggingface dataset:
Interventions to treat fear of childbirth in pregnancy: a systematic review and meta-analysis

Abstract Background Between 5% and 14% of women suffer from fear of childbirth (FOC) which is associated with difficulties during birth and in postnatal psychological adjustment. Therefore, effective interventions are needed to improve outcomes for women. A systematic review and meta-analysis was used to identify effective interventions for treating women with FOC. Methods Literature searches were undertaken on online databases. Hand searches of reference lists were also carried out. Studies were included in the review if they recruited women with FOC and aimed to reduce FOC and/or improve birth outcomes. Data were synthesised qualitatively and quantitatively using meta-analysis. The literature searches provided a total of 4474 citations. Results After removing duplicates and screening through abstracts, titles and full texts, 66 papers from 48 studies were identified for inclusion in the review. Methodological quality was mixed with 30 out of 48 studies having a medium risk of bias. Interventions were categorised into six broad groups: cognitive behavioural therapy, other talking therapies, antenatal education, enhanced midwifery care, alternative interventions and interventions during labour. Results from the meta-analysis showed that most interventions reduced FOC, regardless of the approach (mean effect size = −1.27; z = −4.53, p < 0.0001) and that other talking therapies may reduce caesarean section rates (OR 0.48, 95% CI 0.48–0.90). Conclusions Poor methodological quality of studies limits conclusions that can be drawn; however, evidence suggests that most interventions investigated reduce FOC. Future high-quality randomised controlled trials are needed so that clear conclusions can be made.
for Exploit Visual Dependency Relations for Semantic Segmentation

In this section, we describe more details of the proposed DependencyNet in Figure 1. The kernel sizes, operation types, and output channels are displayed in the boxes. The three dependency reasoning modules, i.e. intra-class, interclass, and global, are distinguished by different colors in the figure. The global reasoning (green) branch and the Lseg (gray) branch consist of only group convolutions. As a result, there is no information exchange among different groups. Moreover, the k group of features are only supervised by the ground truth of category k so that they are guided to encode the spatial and semantic representations of objects that belong to the k category. The intra-class dependence module (blue) updates the class-specific representations by two group convolutions. The inter-class dependency module (orange) conducts spatial and semantic reasoning among different classes via two group weighted convolutions (gwConv). The interactions among different categories are based on prior knowledge about the interclass dependency relations, which is extracted from training annotations. Finally, the representation of each category is further refined by multiplying it with the probability that objects of the corresponding category exist in the whole scene. For all group-based operations, i.e., group convolutions and group weighted convolutions, the number of groups equals the number of categories. For example, the number of groups is 20 for the Cityscapes dataset, which includes 19 foreground classes and a background class. As for the complexity of our design, given a batch size of 4, an input size of 768x768 and a Resnet-101 baseline, the model size increases from 47.9M to 52.6M and the GPU memory consumption increases from 21.1G to 22.3G. In testing, the computational complexity increases from 1497 GFLOPS to 1617 GFLOPS. In our ablation study, we built the baselines by replacing our modules with conventional convolutions to retain the network depth and model size and showed that the performance gain was not caused by an un-
Supplementary Materials

2 Proofs for Theorems in Section 3 of the Paper 1 2.1 Notations and Conventions . 1 2.2 Training Losses . 2 2.3 Proof of Theorem 1 from Paper . 2 2.3. 1 Main Lemmas . 3 2.3. 2 Auxilliary Lemmas . 5 2.4 Proof of Theorem 2 from Paper . 7 2.5 Nonlinear-Teacher-Network Results . 10
The costs (and benefits) of effortful listening on context processing: A simultaneous electrophysiology, pupillometry, and behavioral study

There is an apparent disparity between the fields of cognitive audiology and cognitive electrophysiology as to how linguistic context is used when listening to perceptually challenging speech. To gain a clearer picture of how listening effort impacts context use, we conducted a pre-registered study to simultaneously examine electrophysiological, pupillometric, and behavioral responses when listening to sentences varying in contextual constraint and acoustic challenge in the same sample. Participants (N = 44) listened to sentences that were highly constraining and completed with expected or unexpected sentence-final words ("The prisoners were planning their escape/party") or were low-constraint sentences with unexpected sentence-final words ("All day she thought about the party"). Sentences were presented either in quiet or with +3 dB SNR background noise. Pupillometry and EEG were simultaneously recorded and subsequent sentence recognition and word recall were measured. While the N400 expectancy effect was diminished by noise, suggesting impaired real-time context use, we simultaneously observed a beneficial effect of constraint on subsequent recognition memory for degraded speech. Importantly, analyses of trial-to-trial coupling between pupil dilation and N400 amplitude showed that when participants' showed increased listening effort (i.e., greater pupil dilation), there was a subsequent recovery of the N400 effect, but at the same time, higher effort was related to poorer subsequent sentence recognition and word recall. Collectively, these findings suggest divergent effects of acoustic challenge and listening effort on context use: while noise impairs the rapid use of context to facilitate lexical semantic processing in general, this negative effect is attenuated when listeners show increased effort in response to noise. However, this effort-induced reliance on context for online word processing comes at the cost of poorer subsequent memory.
Influence of thermal factor on chickpea (Cicer arietinum L.) development, yield and yield components

In Argentina, chickpea (Cicer arietinum L.) sowing date may take place any time between April and June, with crop yield ranging from 1200 to 3000 kg/ha. The distinct environmental scenarios that are set up by different sowing dates exert an important influence on the development of the phenological phases, the behavior of yield components, and yield. Temperature stands out as one of the main factors causing these variations, as its behavior changes over time and space. The impact of the thermal factor on the phenology, yield components, and yield of chickpea crops grown without water constraints was evaluated in a trial with a completely randomized design with 4 replications, where sowing dates were April 15, June 14, July 7, and August 5 (year 2016). Yield components and yield were assessed prior to harvest, and an index of adverse temperature events (IATE) was created to measure the severity and duration of such events. Significant differences were observed in the duration and occurrence of phenological phases, yield components, and yield, as well as in accumulated IATE values. Crops sown on April 15 presented higher seed weight and number, collected from more abundant branches with fewer pods, but with a higher number of large caliber seeds. Later sowing dates led to significant
Representation Learning and Adversarial Sample Generation for Strings

In malware behavioral analysis, the list of accessed and created ﬁles is very often a strong predictive feature for classiﬁcation whether the examined ﬁle is malicious or benign. However, malware authors are trying to avoid detection by generating random ﬁlenames, and/or modifying existing ﬁlenames with new versions of the malware. These changes represent real-world adversarial examples against the detection classiﬁer. The goal of this work is to learn latent representations of character sequences, generate realistic adversarial examples, and improve the classiﬁer’s robustness against adversarial attacks. To obtain ﬁxed-size vector representations of character sequences, we developed a recurrent autoencoder architecture that achieves high sample reconstruction accuracy. Using gradient-based adversarial attacks in the latent representation space, we were able to generate realistic adversarial examples in the input space, and use these adversarial examples to improve the classiﬁer’s robustness. Additionally, we showed that latent representations obtained using variational autoencoders improve adversarial robustness without the need for adversarial training.
AIFit: Automatic 3D Human-Interpretable Feedback Models for Fitness Training

I went to the gym today, but how well did I do? And where should I improve? Ah, my back hurts slightly. User engagement can be sustained and injuries avoided by being able to reconstruct 3d human pose and motion, relate it to good training practices, identify errors, and provide early, real-time feedback. In this paper we introduce the first automatic system, AIFit, that performs 3d human sensing for fitness training. The system can be used at home, outdoors, or at the gym. AIFit is able to reconstruct 3d human pose, shape, and motion, reliably segment exercise repetitions, and identify in real-time the deviations between standards learnt from trainers, and the execution of a trainee. As a result, localized, quantitative feedback for correct execution of exercises, reduced risk of injury, and continuous improvement is possible. To support research and evaluation, we introduce the first large scale dataset, Fit3D, containing over 3 million images and corresponding 3d human shape and motion capture ground truth configurations, with over 37 repeated exercises, covering all the major muscle groups, performed by instructors and trainees. Our statistical coach is governed by a global parameter that captures how critical it should be of a trainee’s performance. This is an important aspect that helps adapt to a student’s level of fitness (i.e. beginner vs. advanced vs. expert), or to the expected accuracy of a 3d pose reconstruction method. We show that, for different values of the global parameter, our feedback system based on 3d pose estimates achieves good accuracy compared to the one based on ground-truth motion capture. Our statistical coach offers feedback in natural language, and with spatio-temporal visual grounding.
TEP1, Encoded by a Candidate Tumor Suppressor Locus, Is a Novel Protein Tyrosine Phosphatase Regulated by Transforming Growth Factor 1@'

It has long been postulated that protein tyrosine phosphatases may act as tumor suppressors because of their ability to counteract the oncogenic actions of protein tyrosine kinases. Here we report the cloning and char acterization of a novel human protein tyrosine phosphatase, TEP1. TEP1 contains the protein tyrosine phosphatase signature motif, and we show that it possesses an intrinsic protein tyrosine phosphatase activity. TEP1 also shares extensive homology with tensm, a cytoskeletal protein localized to focal adhesions, and with auxilin, a protein involved in synaptic vesicle transport. Immunofluorescence studies show that TEP1 is a cytoplasmic protein. The abundance of TEP1 transcription is altered in many trans formed cells. In the transforming growth factor fl-sensitive cells, TEP1 expression is rapidly down-regulated by transforming growth factor @1,a cytokine shown to be involved in regulatingcell adhesion and cell motility. We have also mapped the gene encoding TEP1 to chromosome 10q23, a locus that is frequently deleted in a variety of human cancers. TEPI protein is identical to the protein encoded by the candidate tumor sup pressor gene PTEN/MMACJ.Our functional studies of the TEPI protein suggest that its tumor suppressor function may associate with Its intrinsic protein tyrosine phosphatase activity and its cytoplasmic localization. the during the formation of focal adhesions.
ARTP Mutagenesis to Improve Mycelial Polysaccharide Production of Grifola frondosa Using a Mixture of Wheat Bran and Rice Bran as Substrate

Mycelial polysaccharides from Grifola frondosa have shown potential for the prevention of chronic diseases. Atmospheric and room temperature plasma (ARTP) technology was used to enhance the ability of G. frondosa to efficiently utilize a mixture of rice bran and wheat bran in the production of mycelial polysaccharides. The ARTP-mutant G. frondosa GFA2 had an improved growth rate of 6.0 mm/d and polysaccharide yield of 2.65 g/L and showed stable genetic characteristics. Uniform design experiments showed that polysaccharide yield could be increased to 5.90 g/L using the optimized conditions of 10.0 g/L rice bran and 110.0 g/L wheat bran while omitting KH2PO4 and MgSO4·7H2O. Gas chromatography demonstrated that GFA2 polysaccharides were composed of the monosaccharides rhamnose, arabinose, fucose, xylose, mannose, glucose, and galactose. This study provides an effective strategy for improving polysaccharide production in edible fungi while proposing the added-value utilization of rice and wheat brans.
Operationalising positive tipping points towards global sustainability

Non-technical summary Transforming towards global sustainability requires a dramatic acceleration of social change. Hence, there is growing interest in finding ‘positive tipping points’ at which small interventions can trigger self-reinforcing feedbacks that accelerate systemic change. Examples have recently been seen in power generation and personal transport, but how can we identify positive tipping points that have yet to occur? We synthesise theory and examples to provide initial guidelines for creating enabling conditions, sensing when a system can be positively tipped, who can trigger it, and how they can trigger it. All of us can play a part in triggering positive tipping points. Technical summary Recent work on positive tipping points towards sustainability has focused on social-technological systems and the agency of policymakers to tip change, whilst earlier work identified social-ecological positive feedbacks triggered by diverse actors. We bring these together to consider positive tipping points across social-technological-ecological systems and the potential for multiple actors and interventions to trigger them. Established theory and examples provide several generic mechanisms for triggering tipping points. From these we identify specific enabling conditions, reinforcing feedbacks, actors and interventions that can contribute to triggering positive tipping points in the adoption of sustainable behaviours and technologies. Actions that can create enabling conditions for positive tipping include targeting smaller populations, altering social network structure, providing relevant information, reducing price, improving performance, desirability and accessibility, and coordinating complementary technologies. Actions that can trigger positive tipping include social, technological and ecological innovations, policy interventions, public investment, private investment, broadcasting public information, and behavioural nudges. Positive tipping points can help counter widespread feelings of disempowerment in the face of global challenges and help unlock ‘paralysis by complexity’. A key research agenda is to consider how different agents and interventions can most effectively work together to create system-wide positive tipping points whilst ensuring a just transformation. Social media summary We identify key actors and actions that can enable and trigger positive tipping points towards global sustainability.
Identification of new secondary metabolites in Persea americana Miller variety Drymifolia

Plants have developed various defense strategies under conditions of biotic and abiotic stress, among the main ones, highlights the synthesis of secondary metabolites that act as herbicides, larvicides, repellents, attractants, fungicides, bactericides, insecticides, etc. In the present investigation, the chemical characterization of 54 collections of P. americana Miller variety Drymifolia from the avocado producer fringe of the state of Michoacán and conserved in the germplasm bank of the Faculty of Agrobiology ‘Presidente Juárez’ was raised. The study is part of a comprehensive strategy to evaluate the potential of collections as rootstocks with attributes of resistance to pests and diseases. When analyzing the chemical profile, a total of 47 secondary metabolites were identified, 16 of them, have not been reported in Persea leaf tissue. Some compounds such as β-pinene, caryophyllene, estragole, hexadecanoic acid, heptacosane and αtocopherol were present in the 54 collections analyzed. Estragole with antifungal, larvicidal, insecticidal and genotoxic biological activity predominated with a concentration of 26.53%, with respect to the total. Additionally, significant statistical differences were determined for 12 secondary metabolites. In contrast, no relationship was found between the concentration of the metabolites and the origin of the collections.
Efficacy of Linaclotide in Reducing Abdominal Symptoms of Bloating, Discomfort, and Pain: A Phase 3B Trial Using a Novel Abdominal Scoring System

INTRODUCTION: Linaclotide improves abdominal pain and constipation in patients with constipation-predominant irritable bowel syndrome (IBS-C). Patients report additional bothersome abdominal symptoms of bloating and discomfort. The intention of this study was to evaluate linaclotide's efficacy in relieving IBS-C-related abdominal symptoms (bloating, discomfort, and pain) using a novel multi-item Abdominal Score (AS). METHODS: Patients with IBS-C with abdominal pain ≥3 (0–10 scale) were randomized to linaclotide 290 μg or placebo daily for 12 weeks. The AS, derived from the Diary for IBS Symptoms-Constipation, is the average of abdominal bloating, discomfort, and pain at their worst (0 = none, 10 = worst possible). The primary end point was overall change from baseline (CFB) in AS. Secondary end points included CFB in 12-week AS evaluated using cumulative distribution function and 6-week/12-week AS responder (AS improvement ≥2 points for ≥6-week/12-week). RESULTS: Overall, 614 patients (mean age 46.7 years; 81% female) were randomized. All prespecified end points showed significant benefit of linaclotide vs placebo. The mean overall CFB AS reduction for linaclotide was −1.9 vs −1.2 for placebo (P < 0.0001); the 6-week/12-week AS responder rate was 40.5% for linaclotide vs 23.4% for placebo (odds ratio = 2.2 [95% confidence interval, 1.55–3.12; P < 0.0001]). Diarrhea was the most common treatment-emergent adverse event (linaclotide = 4.6%, placebo = 1.6%). DISCUSSION: Linaclotide significantly reduced multiple abdominal symptoms important to patients with IBS-C (bloating, discomfort, and pain) compared with placebo, as measured by a novel multi-item AS. The AS, derived from the Diary for IBS Symptoms-Constipation, should be considered for use in future IBS-C clinical studies to measure clinically meaningful improvements beyond traditional end points.
Single-Trial EEG Classification via Common Spatial Patterns with Mixed Lp- and Lq-Norms

As a multichannel spatial filtering technique, common spatial patterns (CSP) have been successfully applied in brain-computer interfaces (BCI) community based on electroencephalogram (EEG). However, it is sensitive to outliers because of the employment of the L2-norm in its formulation. It is beneficial to perform robust modelling for CSP. In this paper, we propose a robust framework, called CSP-Lp/q, by formulating the variances of two EEG classes with Lp- and Lq-norms ( 0 < p and q < 2 ) separately. The method CSP-Lp/q with mixed Lp- and Lq-norms takes the class-wise difference into account in formulating the sample dispersion. We develop an iterative algorithm to optimize the objective function of CSP-Lp/q and show its monotonity theoretically. The superiority of the proposed CSP-Lp/q technique is experimentally demonstrated on three real EEG datasets of BCI competitions.
Use of disaccharides and activated carbon to preserve cellulolytic ruminal bacterial consortiums lyophilized

Objective. To determine in vitro fermentation of cellulolytic ruminal bacterial consortia (CBC) preserved by lyophilization using activated carbon, maltose and lactose as preservatives. Materials and methods. A CBC was isolated from the ruminal fluid of a female water buffalo in selective cellulolytic media. The CBC were lyophilized without preservative (SP), activated carbon (CA), lactose (LA) o maltose (MA) as preservatives. The experimental design was completely random to measure biogas at different time intervals; as well as completely random with 4x3 factorial arrangement, factors were preservative [SP, CA, LA and MA] and fermentation time (24, 48 and 72 h) for pH, ammoniacal nitrogen (NH3-N), dry matter degradation (DMD), neutral detergent fiber degradation (NDFD), enzymatic activity cellulases and total bacteria population. Results. LA produced higher accumulated biogas at 72 h and partial biogas after 12 h (p≤0.05). SP did not show differences (p>0.05) in cellulases, total bacteria population, DMD and NDFD in the fermentation times evaluated with the rest of the preservative. Conclusions. The production of partial and accumulated biogas, the increase in the degradation rate of 8.3 and 91.1% in the DMD and NDFD from 24 to 72 h (p≤0.05) in the LA preservative, show that lactose can be used as a preservative of ruminal cellulolytic bacteria.
UWS Academic Portal Spectroscopic studies of neutron-rich 129In and its -decay daughter, 129Sn, using the GRIFFIN spectrometer Garcia, F. H.; Andreoiu,

Citation for published version (APA): Garcia, F. H. , Andreoiu, C. , Ball, G. C. , Bernier, N. , Bidaman, H. , Bildstein, V. , Bowry, M. , Cross, D. S. , Dunlop, M. R. , Dunlop, R. , Garnsworthy, A. B. , Garrett, P. E. , Henderson, J., Measures, J., Olaizola, B. , Ortner, K. , Park, J., Petrache, C. M. , Pore, J. L. , . Zidar, T. (2021). Spectroscopic studies of neutron-rich 129 In and its -decay daughter, 129 Sn, using the GRIFFIN spectrometer. Physical Review C, 103(2), [024310]. https://doi.org/10.1103/PhysRevC.103. 024310
Pedestrian and Ego-vehicle Trajectory Prediction from Monocular Camera

Predicting future pedestrian trajectory is a crucial component of autonomous driving systems, as recognizing critical situations based only on current pedestrian position may come too late for any meaningful corrective action (e.g. breaking) to take place. In this paper, we propose a new method to predict future position of pedestrians, with respect to a predicted future position of the ego-vehicle, thus giving a assistive/autonomous driving system sufficient time to respond. The method explicitly disentangles actual movement of pedestrians in real world from the ego-motion of the vehicle, using a future pose prediction network trained in self-supervised fashion, which allows the method to observe and predict the intrinsic pedestrian motion in a normalised view, that captures the same real-world location across multiple frames.