In this multi-centre study, the mid- to long-term efficacy and safety of the Amplatzer Piccolo Occluder in patent ductus arteriosus closure in premature and term infants as well as children were discussed. Methods. Between 2016 and 2021, 645 patients, 152 of whom were less than 1 month old, underwent ductus closure with the Piccolo device from five different centres in Turkey. The median age of the patients was 2.2 years, and the mean narrowest point of duct diameter was 1.8 mm. Sixty-two patients weighed ≤ 1.5 kg, 90 patients 1.5–3 kg, and the mean follow-up was 20.4 months. In 396, the duct was closed by the retrograde route. Ductal anatomy was Type A in 285, C in 72, E in 171, and F in 64 patients. Fluoroscopy duration was 6.2 min. The procedure success rate was 99.1%. Device embolisation occurred in 13 patients (2%), and 11 were retrieved with a snare. Cardiac perforation and death developed in one premature baby. The left pulmonary artery and the descending aorta stenosis were observed in 3 (0.4%) and in 5 patients (0.5%). Results. Piccolo device is safe and effective in closing ductus in all age groups. It has low profile for use in premature and newborn babies, a small embolisation risk, and a low residual shunt rate after closure. Conclusion. The Piccolo device can be considered as close an ideal occluder. The lower profile, smaller delivery catheter size, and symmetry of this device allow for a venous or arterial approach.

Magmatic activity in the Sakarya Zone, an important segment of the Alpine orogenic belt, continues intermittently from the middle Carboniferous to Miocene. In this study, we provide geochronological and geochemical data from the Dağdibi Pluton in the eastern Sakarya Zone to present some inferences on the source region and petrogenesis of the middle Eocene magmatism. U–Pb zircon geochronology from two granodiorite samples gives middle Eocene ages of 44.75 ± 0.92 and 45.01 ± 0.59 Ma. The pluton is mainly composed of K-feldspar, plagioclase, quartz, Mg-hornblende/actinolite, Fe–Ti oxides and small amounts of biotite, and secondary chlorite and epidote. Parental magma of the intrusive rocks has a high-K calc-alkaline affinity with metaluminous character. The oxygen fugacity values vary between −18 and −17. The rocks show slightly radiogenic 87Sr/86Sr(i) (0.704845–0.705726) ratios and ϵNdi values between −0.96 and +0.52. Pb–Pb isotope ratios are typical for those of the lower continental crust. ϵHf(i) values of the zircons range from 0.14 to 10.26. The geochemical and isotopic features of the pluton point to a parental magma derived from a depleted mantle that was metasomatized by fluids during previous subduction events. The volumetric abundances of the rock types are decreased as the silica content increase, implying that the fractional crystallization is the most important process during the formation of the present compositional range of the pluton. Amphibole, plagioclase and Fe–Ti oxides are the fractionated phases while K-feldspar is largely accumulated. In the light of the data presented above, slab breakoff is regarded as the geodynamic process responsible for the formation of the Dağdibi Pluton in the middle Eocene.

Named entity recognition (NER) aims to identify mentions of named entities in an unstructured text and classify them into predefined named entity classes. While deep learning-based pre-trained language models help to achieve good predictive performances in NER, many domain-specific NER applications still call for a substantial amount of labeled data. Active learning (AL), a general framework for the label acquisition problem, has been used for NER tasks to minimize the annotation cost without sacrificing model performance. However, the heavily imbalanced class distribution of tokens introduces challenges in designing effective AL querying methods for NER. We propose several AL sentence query evaluation functions that pay more attention to potential positive tokens and evaluate these proposed functions with both sentence-based and token-based cost evaluation strategies. We also propose a better data-driven normalization approach to penalize sentences that are too long or too short. Our experiments on three datasets from different domains reveal that the proposed approach reduces the number of annotated tokens while achieving better or comparable prediction performance with conventional methods.

A system of interacting multi-class finite-state jump processes is analyzed. The model under consideration consists of a block-structured network with dynamically changing multi-color nodes. The interactions are local and described through local empirical measures. Two levels of heterogeneity are considered: between and within the blocks where the nodes are labeled into two types. The central nodes are those connected only to nodes from the same block, whereas the peripheral nodes are connected to both nodes from the same block and nodes from other blocks. Limits of such systems as the number of nodes tends to infinity are investigated. In particular, under specific regularity conditions, propagation of chaos and the law of large numbers are established in a multi-population setting. Moreover, it is shown that, as the number of nodes goes to infinity, the behavior of the system can be represented by the solution of a McKean–Vlasov system. Then, we prove large deviations principles for the vectors of empirical measures and the empirical processes, which extends the classical results of Dawson and Gärtner (Stochastics 20, 1987) and Léonard (Ann. Inst. H. Poincaré Prob. Statist. 31, 1995).

Collective decision-making by a swarm of robots is of paramount importance. In particular, the problem of collective perception wherein a swarm of robots aims to achieve consensus on the prevalent feature in the environment. Recently, this problem has been formulated as a discrete collective estimation scenario to estimate their proportion rather than deciding about the prevalent one. Nevertheless, the performance of the existing strategies to resolve this scenario is either poor or depends on higher communication bandwidth. In this work, we propose a novel decision-making strategy based on maximum likelihood estimate sharing (MLES) to resolve the discrete collective estimation scenario. Experimentally, we compare the tradeoff speed versus accuracy of MLES with state-of-the-art methods in the literature, such as direct comparison (DC) and distributed Bayesian belief sharing (DBBS). Interestingly, MLES achieves an accurate consensus nearly 20% faster than DBBS, its communication bandwidth requirement is the same as DC but six times less than DBBS, and its computational complexity is $O(1)$ . Furthermore, we investigate how noisy sensors affect the effectiveness of the strategies under consideration, with MLES showing better sustainability.

This article strives to open a window on ‘eco-humour’, an umbrella term for diverse forms of humour targeting ecological and environmental issues. It encourages readers to consider eco-humour as a valuable, pedagogical toolkit for environmental education and communication. To this aim, eco-humour is, first, put into perspective of humour scholarship. In particular, I discuss the critical and corrective potential of humour to address and possibly redress environmental issues. Pedagogical benefits of humour are, then, touched upon to pave the way for a discussion of ‘humour-integrated environmental education’. The paper also addresses UNESCO’s 2030 roadmap of education for sustainable development and the ‘sustainability’ component of Australian Curriculum to further justify and contextualise the use of eco-humour. Moreover, several university-based initiatives to integrate echo-humour into environmental education are considered. Likewise, I briefly address ‘humour-integrated language learning’ as an emerging approach in language education that may offer valuable insights into eco-humour curriculum integration. Finally, the article points out several practical considerations and future directions in humour-integrated environmental education.

Automatic paraphrase detection is the task of measuring the semantic overlap between two given texts. A major hurdle in the development and evaluation of paraphrase detection approaches, particularly for South Asian languages like Urdu, is the inadequacy of standard evaluation resources. The very few available paraphrased corpora for these languages are manually created. As a result, they are constrained to smaller sizes and are not very feasible to evaluate mainstream data-driven and deep neural networks (DNNs)-based approaches. Consequently, there is a need to develop semi- or fully automated corpus generation approaches for the resource-scarce languages. There is currently no semi- or fully automatically generated sentence-level Urdu paraphrase corpus. Moreover, no study is available to localize and compare approaches for Urdu paraphrase detection that focus on various mainstream deep neural architectures and pretrained language models.

This research study addresses this problem by presenting a semi-automatic pipeline for generating paraphrased corpora for Urdu. It also presents a corpus that is generated using the proposed approach. This corpus contains 3147 semi-automatically extracted Urdu sentence pairs that are manually tagged as paraphrased (854) and non-paraphrased (2293). Finally, this paper proposes two novel approaches based on DNNs for the task of paraphrase detection in Urdu text. These are Word Embeddings n-gram Overlap (henceforth called WENGO), and a modified approach, Deep Text Reuse and Paraphrase Plagiarism Detection (henceforth called D-TRAPPD). Both of these approaches have been evaluated on two related tasks: (i) paraphrase detection, and (ii) text reuse and plagiarism detection. The results from these evaluations revealed that D-TRAPPD ( $F_1 = 96.80$ for paraphrase detection and $F_1 = 88.90$ for text reuse and plagiarism detection) outperformed WENGO ( $F_1 = 81.64$ for paraphrase detection and $F_1 = 61.19$ for text reuse and plagiarism detection) as well as other state-of-the-art approaches for these two tasks. The corpus, models, and our implementations have been made available as free to download for the research community.

Buckwheat (Fagopyrum spp.) is an important crop in the high-altitude regions of the Northwest Indian Himalayas. The agro-climatic heterogeneity of this region offers a great deal of diversity in the agro-morphology of buckwheat species. In this study, a total of 61 accessions of Fagopyrum esculentum and Fagopyrum tataricum were characterized for 17 morphological (8 qualitative and 9 quantitative) traits. Significant differences (P < 0.0001) among all the traits were revealed by one-way analysis of variance. Further, significant phenotypic variability in both qualitative as well as quantitative traits was also observed. Both positive and negative correlations were observed between the traits of agronomic relevance. The principal component analysis (PCA) reveals about 69% variability among the first six components. The accessions were divided into two key clusters with numerous subclusters by considering the unweighted pair group method with arithmetic mean dendrogram. A cluster of 19 accessions was formed utilizing a PCA scatter plot indicating accessions with maximum values for important quality traits like plant height, leaf blade width, stem colour (red), primary branches, inflorescence length, flower colour (greenish-yellow), seed anthocyanin colour (green), seed shape (ovate) and seed weight. These accessions can be of vital significance for future buckwheat breeding programmes. The findings from the current study will form a favourable base for genetic resource management, improved cultivation and applications of buckwheat at the commercial level in the northwestern Himalayas of India.

Ventriculoarterial connection is one of the important points of the segmental approach to congenital cardiac malformations. Double outlet of both ventricles is a rare form where both great arterial roots override the interventricular septum. In this article, we aimed to draw attention to this very rare form of ventriculoarterial connection by presenting an infant case diagnosed using echocardiography, CT angiography, and 3-dimensional modelling.

The characterisation of traditional barley varieties from North Africa is promising with respect to detect traits linked with resilience to drought. Nine Algerian barley varieties comprising the economically relevant local landraces Saïda183 and Tichedrett were genotyped by random amplifying polymorphic DNA (RAPD) and by Simple Sequence Repeat (SSR) markers to get insight into their phylogenetic relationship and to compare the efficiency of the two approaches. The SSR markers were chosen such that all chromosomes of barley were represented by at least one marker. In addition, a principal component analysis (PCA) of morpho-agronomical traits was conducted. We found that the phylogeny based on the RAPD markers reflected the geographical distribution of the tested varieties, while the phylogeny based on the SSR markers reflected the pedigree. Among the RAPD markers, the maximal polymorphism information content was obtained for BY14 with a value of 0.82, for the SSR markers, Bmg13 was most informative with a value of 0.60. The similarity matrix used to the construct the phylogenetic tree, inferred a close relationship (Jaccard Index 0.8 based on RAPD markers) between the accessions Fouara and Oued-Athmania occurring in close vicinity. The SSR markers group the autochthonous varieties Saïda183 and Tichedrett together with a Jaccard Index of 0.8. The close phylogenetic relationship between Saïda183 and Tichedrett is also supported by the PCA of morphological and agronomic traits. Our data underpin the diversity of Algerian barley varieties and lend support to the autochthonous origin of these two Algerian landraces.

The Kaya forests in Southern Kenya are valuable habitats for rare animal and plant species and provide various ecosystem services. The Kaya forests are also centres of cultural life and are of great relevance to rites, traditions, and the social order of the community of people. During the past decades, these forest remnants become under extreme pressure due to land use and resource exploitation and are in danger of disappearing completely during the next years. This negative trend is progressing with the increasing population density. In addition, the relevance of the former cultural rites is increasingly being forgotten, and with it the relevance of these places. In order to preserve these forest remnants in the long term, it is important to make the population aware of the numerous and valuable ecosystem services, as well as to bring the former cultural life back into the centre of society. A general prerequisite to efficiently conserve Kayas might be the improvement of communication among generations, such as between the elders of Kayas and the youth, as well as among elders from different Kayas to harmonize conservation strategies and the sustainable use of these forest remnants. In addition, strengthening the communication between state institutions and the elders of the individual Kayas might help to find a common strategy to conserve Kaya forests.

Mixed total anomalous pulmonary venous connection is a rare CHD with a wide variation in pulmonary venous anatomy and drainage. We present a ten-day-old newborn with a rare bizarre subtype of mixed total anomalous pulmonary venous connection.