A giant right atrial myxoma with pulmonary arterial hypertension

Here we report a case of a right atrial mass that morphology mimicking myxoma, in a young patient with no past medical history. The mass was pathologically confirmed to be symptomatic and surgical removal was successfully done

Botanical and Genetic Identification Followed by Investigation of Chemical Composition and Biological Activities on the Scabiosa atropurpurea L. Stem from Tunisian Flora

Scarce information about the phenolic composition of Scabiosa atropurpurea L. is available, and no carotenoid compounds have been reported thus far. In this study the phenolic and carotenoid composition of this plant was both investigated and associated bioactivities were evaluated. Aiming to obtain extracts and volatile fractions of known medicinal plants to valorize them in the pharmaceutical or food industries, two techniques of extraction and five solvents were used to determine the biologically active compounds. Gas chromatography coupled to flame ionization and mass spectrometry and liquid chromatography coupled to photodiode array and atmospheric pressure chemical ionization/electrospray ionization mass spectrometry highlighted the presence of 15 volatiles, 19 phenolic, and 24 natural pigments in Scabiosa atropurpurea L. stem samples; among them, the most abundant were 1,8-cineole, chlorogenic acid, cynaroside, and lutein. Bioactivity was assessed by a set of in vitro tests checking for antioxidant, antibacterial, antifungal, and allelopathic (against Brassica oleracea L. and Lens culinaris Medik) effects. Scabiosa atropurpurea L. stem extracts presented a considerable antioxidant, antibacterial, and allelopathic potential, with less antifungal effectiveness. These results indicate that the volatile fractions and extracts from S. atropurpurea L. stem could be considered as a good source of bioactive agents, with possible applications in food-related, agriculture, and pharmaceutical fields. Genetic investigations showed 97% of similarity with Scabiosa tschiliensis, also called Japanese Scabiosa

An Item Response Curves Analysis of the Force Concept Inventory

Several years ago, we introduced the idea of item response curves (IRC), a simplistic form of item response theory (IRT), to the physics education research community as a way to examine item performance on diagnostic instruments such as the Force Concept Inventory (FCI). We noted that a full-blown analysis using IRT would be a next logical step, which several authors have since taken. In this paper, we show that our simple approach not only yields similar conclusions in the analysis of the performance of items on the FCI to the more sophisticated and complex IRT analyses but also permits additional insights by characterizing both the correct and incorrect answer choices. Our IRC approach can be applied to a variety of multiple-choice assessments but, as applied to a carefully designed instrument such as the FCI, allows us to probe student understanding as a function of ability level through an examination of each answer choice. We imagine that physics teachers could use IRC analysis to identify prominent misconceptions and tailor their instruction to combat those misconceptions, fulfilling the FCI authors\u27 original intentions for its use. Furthermore, the IRC analysis can assist test designers to improve their assessments by identifying nonfunctioning distractors that can be replaced with distractors attractive to students at various ability levels

A Hybrid Neuro-Fuzzy Approach for Heterogeneous Patch Encoding in ViTs Using Contrastive Embeddings & Deep Knowledge Dispersion

Vision Transformers (ViT) are commonly utilized in image recognition and related applications. It delivers impressive results when it is pre-trained using massive volumes of data and then employed in mid-sized or small-scale image recognition evaluations such as ImageNet and CIFAR-100. Basically, it converts images into patches, and then the patch encoding is used to produce latent embeddings (linear projection and positional embedding). In this work, the patch encoding module is modified to produce heterogeneous embedding by using new types of weighted encoding. A traditional transformer uses two embeddings including linear projection and positional embedding. The proposed model replaces this with weighted combination of linear projection embedding, positional embedding and three additional embeddings called Spatial Gated, Fourier Token Mixing and Multi-layer perceptron Mixture embedding. Secondly, a Divergent Knowledge Dispersion (DKD) mechanism is proposed to propagate the previous latent information far in the transformer network. It ensures the latent knowledge to be used in multi headed attention for efficient patch encoding. Four benchmark datasets (MNIST, Fashion-MNIST, CIFAR-10 and CIFAR-100) are used for comparative performance evaluation. The proposed model is named as SWEKP-based ViT, where the term SWEKP stands for Stochastic Weighted Composition of Contrastive Embeddings & Divergent Knowledge Dispersion (DKD) for Heterogeneous Patch Encoding. The experimental results show that adding extra embeddings in transformer and integrating DKD mechanism increases performance for benchmark datasets. The ViT has been trained separately with combination of these embeddings for encoding. Conclusively, the spatial gated embedding with default embeddings outperforms Fourier Token Mixing and MLP-Mixture embeddings

Socioeconomic determinants of organic cotton adoption in Benin, West Africa

Organic cotton relies on ecological processes and the use of natural resources to sustain the production system, unlike conventional cotton, mainly characterized by massive utilization of synthesis chemicals. In West Africa, where rural livelihoods are particularly vulnerable, organic cotton is expected to contribute not only to poverty reduction but also to strengthen households’ resilience. The objective of this study was to assess institutional and socioeconomic factors determining farmers’ decisions to adopt organic cotton. For this purpose, we applied a probit model on empirical data collected from producers of the Centre and the Northern parts of Benin. Overall, we found that organic cotton adoption is mainly determined by farmers’ socioeconomic characteristics, the physical distance between farm and house, and contact with extension and advisory services. Organic farming is more attractive to women compared to conventional farming. This because such type of cotton farming enables women to hold a separate cotton farm and thus increase their economic independence, whereas with the conventional system they depend mainly on the farm of the (male) head of the household. Older, less educated and low-income farmers who express environmental concern are more likely to adopt organic cotton. Subsequently, organic cotton should be considered as a prospective policy option to reach the poor and strengthen their livelihoods conditions while contributing to preserve the environment and natural resources. Furthermore, farmers who have their farm near home are more likely to adopt organic farming than those who have the farm far from their home. It also came out that organic farmers have more contacts with advisory and extension services. Finally, the study noted that there is still a need to enhance the extension system by: (1) exploring, designing, and upgrading innovative pedagogic tools such as videos and mobile phone technology to foster learning; and (2) strengthening organic farmer’s organizations and the linkage with agricultural research organizations for technology development