Complex Morphology Research Articles

Advancements in Natural Language Understanding- Driven Machine Translation: Focus on English and the Low Resource Dialectal Lusoga

This review explores recent advancements in Natural Language Understanding-driven Machine Translation (NLU-MT) with a focus on English and the low-resource dialectal Lusoga. A Low-resource language, such as Lusoga, faces significant challenges in Machine Translation (MT) due to the scarcity of high-quality parallel corpora, the complex morphology inherent in Bantu languages, and the dialectal variations within Lusoga itself, particularly between Lutenga and Lupakoyo. This paper examines the role of NLU-based MT systems in overcoming these challenges by shifting from word-for-word mapping to meaning-based translations, enabling better handling of these dialectal differences. We highlight the success of leveraging linguistic similarities between Lusoga and related languages, such as Luganda, to improve translation performance through multilingual transfer learning techniques. Key advancements include the use of transformer-based architectures such as Multilingual Bidirectional and Auto-Regressive Transformer (mBART) and Multilingual Text-To-Text Transfer Transformer (mT5), specifically selected for their effectiveness in NLU-driven contexts, which have shown promise in enhancing translation accuracy for African low-resource languages. However, the review also identifies ongoing obstacles, including historical low demand and the lack of well-developed corpora, which hinder scalability. The paper concludes by emphasizing the potential of hybrid approaches that combine community-driven corpus-building initiatives with improved model architectures to drive further progress in low-resource MT. Ultimately, NLU-MT is positioned as a crucial tool not only for bridging communication gaps but also for preserving linguistic diversity and cultural heritage.

Complexity and accuracy of verbal morphology in written L2 Italian

Abstract The present study aims to verify previous findings on the role of proficiency in the degree of complexity and accuracy of verbal morphemes in written essays from intermediate and advanced L2 Italian learners. In addition, by taking the perspective of usage-based theories on the distributional properties in the input, it investigates the extent to which contingency affects morphological complexity and accuracy by the emergence of cue-outcome associations. Hypotheses on the effects of contingency and proficiency on complexity and accuracy, and on their mutual relationships, are verified by adopting a confirmatory approach and by using Structural equation modeling. Results support the claims for non-universal mechanisms in the acquisition of verbal morphology: proficiency does not affect the morphological complexity of learner texts in the same way in inflectionally rich and poor languages, and the cue-outcome mechanisms of associative learning work to different extents depending on the inflectional systems of the target languages.

Imprints of interaction processes in the globular cluster system of NGC 3640

We present a wide-field study of the globular cluster systems (GCS) of the elliptical galaxy NGC 3640 and its companion NGC 3641, based on observations from Gemini Multi-Object Spectrograph/Gemini using g’r’i’ filters. NGC 3640 is a shell galaxy which presents a complex morphology, which previous studies have indicated as the sign of a recent ‘dry’ merger, although whether its nearest neighbour could have influenced these substructures remains an open question. In this work, we trace the spatial distribution of the globular clusters (GCs) as well as their colour distribution, finding a potential bridge of red (metal-rich) GCs that connects NGC 3640 to its less massive companion, and signs that the blue (metal-poor) GCs were spatially disturbed by the event that created the shells. While NGC 3640 presents a typical bimodal colour distribution, the GCS attributed to NGC 3641 appears unimodal, with most GCs presenting an intermediate colour in comparison to those closer to its companion.

ACU-TransNet: Attention and convolution-augmented UNet-transformer network for polyp segmentation.

UNet has achieved great success in medical image segmentation. However, due to the inherent locality of convolution operations, UNet is deficient in capturing global features and long-range dependencies of polyps, resulting in less accurate polyp recognition for complex morphologies and backgrounds. Transformers, with their sequential operations, are better at perceiving global features but lack low-level details, leading to limited localization ability. If the advantages of both architectures can be effectively combined, the accuracy of polyp segmentation can be further improved. In this paper, we propose an attention and convolution-augmented UNet-Transformer Network (ACU-TransNet) for polyp segmentation. This network is composed of the comprehensive attention UNet and the Transformer head, sequentially connected by the bridge layer. On the one hand, the comprehensive attention UNet enhances specific feature extraction through deformable convolution and channel attention in the first layer of the encoder and achieves more accurate shape extraction through spatial attention and channel attention in the decoder. On the other hand, the Transformer head supplements fine-grained information through convolutional attention and acquires hierarchical global characteristics from the feature maps. mcU-TransNet could comprehensively learn dataset features and enhance colonoscopy interpretability for polyp detection. Experimental results on the CVC-ClinicDB and Kvasir-SEG datasets demonstrate that mcU-TransNet outperforms existing state-of-the-art methods, showcasing its robustness.

Technique and early results of endovenous laser ablation in morphologically complex varicose vein recurrence after small saphenous vein surgery.

Recurrences after varicose vein treatment occur frequently and represent a significant health and economic problem. In contrast to primary treatments of superficial truncal venous insufficiency, their management is often more difficult. Here we assessed the technical feasibility and early results of endovenous laser ablation (EVLA) for recurrences with stumps or subfascial meandering varices after small saphenous vein (SSV) surgery. This single-center retrospective study included 45 consecutive EVLA procedures from July 2019 to December 2021 in 40 patients (19 male, 21 female, mean age 62.8 ± 12.7 years). Patients had clinically relevant recurrent varicose veins after SSV surgery, with clinical, etiologic, anatomic and pathophysiologic (CEAP) classification stage of C2S or higher. We categorized the recurrences morphologically according to duplex sonographic criteria. Ablations were done with a 1470 nanometers laser and dual ring radial fibers and aimed at thermal closure as proximal as possible to the upper inflow. Analyses were performed by descriptive statistics and the Kaplan-Meier method. The primary outcome analyzed was the technical success, defined by thermal occlusion not requiring re-intervention during the observation period. The secondary outcome was the occurrence of postoperative complications. A complex morphology with residual stumps or tortuous venous connections to the popliteal vein was present in 35 cases (77.8%). Immediate technical success at the first postoperative visit after a median of 11 days (interquartile range 8-13 days) was 97.8%. During the follow-up period (median 77 days, interquartile range 13-256 days), 6 limbs (13.3%) required redo EVLA due to symptomatic persistent or newly presenting reflux. The median freedom from re-recurrence was 791 days. Otherwise, no medical or surgical complications requiring specific treatment were observed, particularly no endothermal heat-induced thrombosis (EHIT) or other thrombotic complications, and no nerve damage. According to our pilot data, EVLA is technically feasible for complex popliteal variceal recurrence, although the success rate appears substantially lower than for primary treatment of truncal venous insufficiency.

Cross-Linguistic Differences in Morphological Processing: Evidence from English and Italian

ABSTRACT Purpose The present study examined cross-linguistic differences in orthographic transparency and morphological complexity during complex word recognition in English and Italian. If morphological processing is more important in orthographically transparent and morphemically rich languages, larger morpheme-effects should be evident in Italian. However, if morphological processing is more pronounced in orthographically opaque and morphemically sparser languages, morpheme-effects should be larger in English. Method 60 Italian (M age = 25.33, 34 females, Caucasian) and 60 English (M age = 26.35, 34 females, mostly Caucasian) native-speakers completed an online lexical decision task, while reaction times and accuracy were measured. To tease apart the independent role of stems and suffixes, we employed four types of nonwords: Stem+Suffix: night+ness, Stem+NonSuffix: night-lude, NonStem+Suffix: nisht+ness, NonStem+NonSuffix: nisht-lude). Results The results revealed a significant morpheme interference effect in both languages: nonwords with stems were read slower and less accurately than those without stems and nonwords with suffixes slower and less accurately than those without suffixes. Crucially, this observed pattern was larger in English than Italian. Also, a significant Stem by Suffix interaction suggested that Stem+Suffix nonwords were harder to reject than all others. Conclusion The current findings suggest that morphological processing is more pronounced in opaque orthographies like English, possibly because the activation of morphemic chunks can be used to compensate for grapheme-to-phoneme inconsistencies.

MOF-on-MOF Growth: Inducing Naturally Nonpreferred MOFs and Atypical MOF Growth.

ConspectusOverflowing metal-organic frameworks (MOFs) have been synthesized from a wide range of metal and organic components for specific purposes and intellectual curiosity. Each MOF has unique chemical and structural characteristics directed by the incorporated components, metal ions (or clusters), organic linkers, and their intrinsic coordination interactions. These incorporated components and structural characteristics are two pivotal factors influencing MOFs' fundamental properties and subsequent applications. Therefore, selecting the appropriate metal and organic components, considering their innate chemical and structural properties, is crucial to endow the final MOFs with the desired properties. Ultimately, producing MOFs with a desired structure using ideal components is the best approach to achieving the best MOFs tailored for specific purposes with desired properties. However, achieving MOFs with the intended structure from chosen components remains underdeveloped. In many cases, the resulting MOF structure is governed by the thermodynamically and/or kinetically preferred configuration (refers to a naturally preferred structure) of the chosen components and given reaction conditions. Additionally, producing hybrid MOFs with complex components, structures, and morphologies presents a great opportunity to obtain special MOFs with advanced properties and functions. In this Account, we outline our group's efforts over the past few years to develop naturally nonpreferred MOFs through the induced MOF-on-MOF growth process and atypical hybrid MOFs via nonstandard MOF-on-MOF growth. First, we highlight the prime strategy for producing naturally nonpreferred MOFs based on template-induced MOF-on-MOF growth. In this section, we discuss the two basic growth behaviors, isotropic and anisotropic growth of naturally nonpreferred MOFs, determined by the degree of matching between the cell lattices of the two MOFs. Second, we introduce the MOF farming concept for the productive cultivation and effective harvesting of naturally nonpreferred MOFs made by MOF-on-MOF growth. Here we discuss the importance of selecting the ideal MOF template for productive growth and developing an efficient method for harvesting cultivated MOFs. Next, we describe atypical anisotropic MOF-on-MOF growths between two MOFs with mismatched cell lattices. In this section, we introduce tip-to-middle MOF-on-MOF growth involving self-structural adjustment of the secondary MOF, logical inference of unidentified MOF structures based on MOF-on-MOF growth behavior and morphological features, and MOF-on-MOF growth accompanied by etching and transformation of the template. Finally, we discuss the perspectives and challenges of MOF-on-MOF growth and the synthesis of naturally nonpreferred MOFs. We hope that this Account offers valuable insights into the rational design and development of MOFs with desired structural and compositional characteristics, leading to the creation of ideal MOFs.

The twisted jets and magnetic fields of the extendedradio galaxy 4C70.19

The appearance of the jets and lobes of some radio galaxies makes it difficult to assign them to a known class of objects. This is often due to the activity of the central engine and/or interactions with the environment, as well as projection effects. We analyse the radio data for an apparently asymmetric radio source 4C\,70.19, which is associated with the giant elliptical galaxy NGC\,6048. The source shows distorted radio jets and lobes, one of which bends by 180degr . The aim of our study is to explain the nature of the observed distortions. We used LOFAR, Effelsberg, and VLA radio data in a wide range of frequencies. At high frequencies, we also used radio polarimetry to study the properties of the magnetic fields. Additionally, we made use of optical, infra-red, and X-ray data. Polarisation data suggest shearing of the magnetic fields at points where the jets bend. The low-frequency LOFAR map at 145\,MHz, as well as the sensitive single-dish Effelsberg map at 8.35\,GHz, reveal previously undetected diffuse emission around the source. The rotation measure (RM) derived from the polarimetric data allowed us to estimate the density of the medium surrounding the source, which agrees with typical densities of the intergalactic medium or the outer parts of insterstellar halos. We propose that the southern jet is bent in the same manner as the northern one, but that it is inclined to the sky plane. Both these bends are likely caused by the orbital motion within the galaxy group, as well as interactions with the intergalactic medium. Our analyses suggest that, despite its complex morphology, 4C\,70.19 seems to be intrinsically symmetric with a physical extent of up to 600\,kpc, and that the diffuse emission detected in our high-sensitivity maps is related to radio plumes that are expanding behind the source.

One-step nanoscale expansion microscopy reveals individual protein shapes.

The attainable resolution of fluorescence microscopy has reached the subnanometer range, but this technique still fails to image the morphology of single proteins or small molecular complexes. Here, we expand the specimens at least tenfold, label them with conventional fluorophores and image them with conventional light microscopes, acquiring videos in which we analyze fluorescence fluctuations. One-step nanoscale expansion (ONE) microscopy enables the visualization of the shapes of individual membrane and soluble proteins, achieving around 1-nm resolution. We show that conformational changes are readily observable, such as those undergone by the ~17-kDa protein calmodulin upon Ca2+ binding. ONE is also applied to clinical samples, analyzing the morphology of protein aggregates in cerebrospinal fluid from persons with Parkinson disease, potentially aiding disease diagnosis. This technology bridges the gap between high-resolution structural biology techniques and light microscopy, providing new avenues for discoveries in biology and medicine.

On the Utilization of Emoji Encoding and Data Preprocessing with a Combined CNN-LSTM Framework for Arabic Sentiment Analysis

Social media users often express their emotions through text in posts and tweets, and these can be used for sentiment analysis, identifying text as positive or negative. Sentiment analysis is critical for different fields such as politics, tourism, e-commerce, education, and health. However, sentiment analysis approaches that perform well on English text encounter challenges with Arabic text due to its morphological complexity. Effective data preprocessing and machine learning techniques are essential to overcome these challenges and provide insightful sentiment predictions for Arabic text. This paper evaluates a combined CNN-LSTM framework with emoji encoding for Arabic Sentiment Analysis, using the Arabic Sentiment Twitter Corpus (ASTC) dataset. Three experiments were conducted with eight-parameter fusion approaches to evaluate the effect of data preprocessing, namely the effect of emoji encoding on their real and emotional meaning. Emoji meanings were collected from four websites specialized in finding the meaning of emojis in social media. Furthermore, the Keras tuner optimized the CNN-LSTM parameters during the 5-fold cross-validation process. The highest accuracy rate (91.85%) was achieved by keeping non-Arabic words and removing punctuation, using the Snowball stemmer after encoding emojis into Arabic text, and applying Keras embedding. This approach is competitive with other state-of-the-art approaches, showing that emoji encoding enriches text by accurately reflecting emotions, and enabling investigation of the effect of data preprocessing, allowing the hybrid model to achieve comparable results to the study using the same ASTC dataset, thereby improving sentiment analysis accuracy.

Band alignment of CoO(100)-water and CoO(111)-water interfaces accelerated by machine learning potentials.

Cobalt monoxide (CoO) nanomaterials have drawn attention for their remarkable photocatalytic water splitting without an externally applied potential or co-catalyst. The success of overall water splitting is due to the appropriate band edge positions of the catalyst, which span the redox potentials of water splitting. Typically, CoO nanomaterials possess complex morphologies, which consist of multiple active surfaces. As a result, the precise roles of the surfaces in the overall water-splitting process remain to be elucidated. In this work, we have undertaken a thorough investigation into the band alignments at the CoO(100)-water and CoO(111)-water interfaces using abinitio molecular dynamics and machine learning accelerated molecular dynamics simulations. The results of band alignment reveal that CoO(100) supports both the Hydrogen Evolution Reaction (HER) and the oxygen evolution reaction, whereas CoO(111) only facilitates the HER. Moreover, the variance in band positions between CoO(100) and CoO(111) results in an intrinsic potential difference, facilitating the migration of electrons toward CoO(100), while holes accumulate on CoO(111). The separation of photoexcited carriers effectively promotes water splitting in CoO.

Stereologic consequences of iatrogenic collapse: The morphology of adenocarcinoma in situ overlaps with invasive patterns. Proposal for a necessary modified classification of pulmonary adenocarcinomas

Recognizing non-invasive growth patterns is necessary for correct diagnosis, invasive size determination and pT-stage in resected non-small cell lung carcinoma. Due to iatrogenic collapse after resection, the distinction between adenocarcinoma in-situ (AIS) and invasive adenocarcinoma may be difficult. The aim of this study is to investigate the complex morphology of non-mucinous non-invasive patterns of AIS in resection specimen with iatrogenic collapse, and to relate this to follow-up.The effects of iatrogenic collapse on the morphology of collapsed AIS were simulated in a mathematical model. Three dimensional related criteria applied in a modified classification, using also cytokeratin 7 and elastin as additional stains, in two independent retrospective cohorts of primary pulmonary adenocarcinomas ≤3 cm resection specimen with available follow-up information.The model demonstrated that infolding of alveolar walls occurs during iatrogenic collapse and lead to a significant increase in tumor cell heights in maximal collapse areas, compared to less collapsed areas. The morphology of infolded AIS overlaps with patterns described as papillary and acinar adenocarcinoma according to the WHO classification, necessitating an adaptation.The modified classification incorporates recognition of iatrogenic and biologic collapse, tangential cutting effect true invasion and surrogate markers of invasion i.e. grey zone, covering a multilayering falling short of micropapillary, cribriform and solid alveolar filling growth. The use of elastin and CK7 staining aids in the morphologic recognition of iatrogenic collapsed AIS and the distinction from invasive adenocarcinoma. Out of a total of 70 resection specimens 1 case was originally classified as AIS and 9 were reclassified as iatrogenic collapsed AIS. Patients with collapsed AIS showed a 100 % recurrence-free survival after a mean follow-up time of 69.5 months.With the current WHO classification, AIS is overdiagnosed as invasive adenocarcinoma due to infolding. The modified classification facilitates the diagnosis of AIS.

BioSAM: Generating SAM Prompts From Superpixel Graph for Biological Instance Segmentation.

Proposal-free instance segmentation methods have significantly advanced the field of biological image analysis. Recently, the Segment Anything Model (SAM) has shown an extraordinary ability to handle challenging instance boundaries. However, directly applying SAM to biological images that contain instances with complex morphologies and dense distributions fails to yield satisfactory results. In this work, we propose BioSAM, a new biological instance segmentation framework generating SAM prompts from a superpixel graph. Specifically, to avoid over-merging, we first generate sufficient superpixels as graph nodes and construct an initialized graph. We then generate initial prompts from each superpixel and aggregate them through a graph neural network (GNN) by predicting the relationship of superpixels to avoid over-segmentation. We employ the SAM encoder embeddings and the SAM-assisted superpixel similarity as new features for the graph to enhance its discrimination capability. With the graph-based prompt aggregation, we utilize the aggregated prompts in SAM to refine the segmentation and generate more accurate instance boundaries. Comprehensive experiments on four representative biological datasets demonstrate that our proposed method outperforms state-of-the-art methods.

Recording morphogen signals reveals mechanisms underlying gastruloid symmetry breaking.

Aggregates of stem cells can break symmetry and self-organize into embryo-like structures with complex morphologies and gene expression patterns. Mechanisms including reaction-diffusion Turing patterns and cell sorting have been proposed to explain symmetry breaking but distinguishing between these candidate mechanisms of self-organization requires identifying which early asymmetries evolve into subsequent tissue patterns and cell fates. Here we use synthetic 'signal-recording' gene circuits to trace the evolution of signalling patterns in gastruloids, three-dimensional stem cell aggregates that form an anterior-posterior axis and structures resembling the mammalian primitive streak and tailbud. We find that cell sorting rearranges patchy domains of Wnt activity into a single pole that defines the gastruloid anterior-posterior axis. We also trace the emergence of Wnt domains to earlier heterogeneity in Nodal activity even before Wnt activity is detectable. Our study defines a mechanism through which aggregates of stem cells can form a patterning axis even in the absence of external spatial cues.

Development of a Children’s Educational Dictionary for a Low-Resource Language Using AI Tools

Today, various interactive tools or partially available artificial intelligence applications are actively used in educational processes to solve multiple problems for resource-rich languages, such as English, Spanish, French, etc. Unfortunately, the situation is different and more complex for low-resource languages, like Kazakh, Uzbek, Mongolian, and others, due to the lack of qualitative and accessible resources, morphological complexity, and the semantics of agglutinative languages. This article presents research on early childhood learning resources for the low-resource Kazakh language. Generally, a dictionary for children differs from classical educational dictionaries. The difference between dictionaries for children and adults lies in their purpose and methods of presenting information. A themed dictionary will make learning and remembering new words easier for children because they will be presented in a specific context. This article discusses developing an approach to creating a thematic children’s dictionary of the low-resource Kazakh language using artificial intelligence. The proposed approach is based on several important stages: the initial formation of a list of English words with the use of ChatGPT; identification of their semantic weights; generation of phrases and sentences with the use of the list of semantically related words; translation of obtained phrases and sentences from English to Kazakh, dividing them into bigrams and trigrams; and processing with Kazakh language POS pattern tag templates to adapt them for children. When the dictionary was formed, the semantic proximity of words and phrases to the given theme and age restrictions for children were taken into account. The formed dictionary phrases were evaluated using the cosine similarity, Euclidean similarity, and Manhattan distance metrics. Moreover, the dictionary was extended with video and audio data by implementing models like DALL-E 3, Midjourney, and Stable Diffusion to illustrate the dictionary data and TTS (Text to Speech) technology for the Kazakh language for voice synthesis. The developed thematic dictionary approach was tested, and a SUS (System Usability Scale) assessment of the application was conducted. The experimental results demonstrate the proposed approach’s high efficiency and its potential for wide use in educational purposes.

Radiolarians from Cambrian Series 2 Niujiaohe Formation in southern Jiangxi, South China

The origin and early evolution of radiolarian fossils have always provoked great interest among paleontologists. Yet, little is known about the earliest morphological and evolutionary characteristics of radiolarians largely due to the lack of documentation of early Cambrian radiolarian fossils. Herein, we conduct a thorough examination of the basinal Niujiaohe Formation in Chongyi County of southern Jiangxi and report two types of radiolarians: a large number of spherical radiolarians and a minor occurrence of ellipsoidal radiolarian fossils with bipolar rodded spines. The lengths of the spines on ellipsoid radiolarian fossils vary, and typically, the main spines are slightly offset from the polar axis, resulting in an asymmetrical appearance in some specimens. Through systematic taxonomic examination, this radiolarian fossil form is tentatively identified as Beothuka sp. of the spherical polycystine group. The genus Beothuka is commonly found in the Early Ordovician and has not yet been reported in the early Cambrian. Combined with previous reports, four species of radiolarians in three genera are identified from the Niujiaohe Formation in South China, including Paraantygopora porosa, Paraantygopora sp., spherical radiolarian, and Beothuka sp. Overall, the radiolarian fossils in the Niujiaohe Formation are characterized by low diversity and small size, in contrast to the relatively more diverse fauna found in the contemporary shallow-water Shuijingtuo Formation. Therefore, we speculate that radiolarians may have initially originated in shallow water areas and gradually expanded to deep water. This study further enriches the fossil record of the Cambrian Series 2 radiolarians. Combined with relevant data from South China, the radiolarian fauna began to exhibit diversity and complex morphology, indicating the presence of various, advanced spherical-skeletons in early radiolarians, and radiolarians from the early Cambrian appeared to display multiple evolutionary trends.

Morphologies of Bright Complex Fast Radio Bursts with CHIME/FRB Voltage Data

We present the discovery of 12 apparently nonrepeating fast radio burst (FRB) sources, detected by the Canadian Hydrogen Intensity Mapping Experiment (CHIME) telescope. These sources, only one of which has been presented previously in the first CHIME/FRB catalog, were selected from a database comprising O(103) CHIME/FRB full-array raw voltage data recordings, based on their large signal-to-noise ratios and complex morphologies. Our study examines the time-frequency characteristics of these bursts, including drifting, microstructure, and periodicities. The events in this sample display a variety of unique drifting phenomenologies that deviate from the linear negative drifting phenomenon seen in many repeating FRBs, and motivate a possible new framework for classifying drifting archetypes. Additionally, we detect microstructure features of duration ≲50 μs in seven events, with some as narrow as ≃7 μs. We find no evidence of significant periodicities between subburst components. Furthermore, we report the polarization characteristics of seven events, including their polarization fractions and Faraday rotation measures (RMs). The observed ∣RM∣ values span a wide range of 17.24(2)–328.06(2) rad m−2, with apparent linear polarization fractions between 0.340(1) and 0.946(3). The morphological properties of the bursts in our sample appear broadly consistent with predictions from both relativistic shock and magnetospheric models of FRB emission, as well as propagation through discrete ionized plasma structures. We address these models and discuss how they can be tested using our improved understanding of morphological archetypes.

The Evolution of Photospheric Current Density During an X9.3-Class Solar Flare

This paper deduced the temporal evolution of the magnetic field through a series of high-resolution vector magnetograms and calculated the fine distribution map of current density during an X9.3-class flare eruptions using Ampère’s law. The results show that a pair of conjugate current ribbons exist on both sides of the magnetic neutral line in this active region, and these conjugate current ribbons persist before, during, and after the flare. It was observed that the X9.3-class flare brightened in the form of a bright core and evolved into a double-ribbon flare over time. Importantly, the position of the double-ribbon flare matches the position of the current ribbons with high accuracy, and their morphologies are very similar. By investigating the complexity of current density and flare morphology, we discovered a potential connection between the eruption of major flares and the characteristics of current density.

Confinement induced alteration in interfacial energy in aqueous surfactant systems

When a liquid is confined between two parallel plates, the pressure field at its bulk alters, because of the concave meniscus at the air-water interface. For an aqueous surfactant solution in contact with an oil, like an oil-in-water emulsion, this effect can alter the surfactant concentration at the interface of the two phases thereby changing the interfacial energy. Alteration of interfacial energy is expected to affect morphology of a complex system consisting of three immiscible phases. To verify this hypothesis a drop of crosslinkable silicone liquid was placed on a glass slide and was immobilized by partial crosslinking. An aqueous solution of surfactant, with SiO2 microspheres dispersed in it, was dispensed on this drop to create a liquid pool. It was then confined between two parallel plates to create a meniscus. Consequently, the particles got embedded at the oil-water interface to different extent, depending on the degree of confinement. Force balance along tangents to different interfaces showed that the interfacial energy of silicone-water (aqCTAB 0.3 mM) interface increases from 33.3 ± 0.5 mJ/m2 for an unconfined system to 45.4 ± 2.2 mJ/m2 for the confined one. This effect then elucidates how confinement alters complex emulsion morphologies in multiphase systems.

Genome-resolved metagenomics revealed novel microbial taxa with ancient metabolism from macroscopic microbial mat structures inhabiting anoxic deep reefs of a Maldivian Blue Hole.

Blue holes are vertical water-filled openings in carbonate rock that exhibit complex morphology, ecology, and water chemistry. In this study, macroscopic microbial mat structures found in complete anoxic conditions in the Faanu Mudugau Blue Hole (Maldives) were studied by metagenomic methods. Such communities have likely been evolutionary isolated from the surrounding marine environment for more than 10,000 years since the Blue Hole formation during the last Ice Age. A total of 48 high-quality metagenome-assembled genomes (MAGs) were recovered, predominantly composed of the phyla Chloroflexota, Proteobacteria and Desulfobacterota. None of these MAGs have been classified to species level (<95% ANI), suggesting the discovery of several new microbial taxa. In particular, MAGs belonging to novel bacterial genera within the order Dehalococcoidales accounted for 20% of the macroscopic mat community. Genome-resolved metabolic analysis of this dominant microbial fraction revealed a mixotrophic lifestyle based on energy conservation via fermentation, hydrogen metabolism and anaerobic CO2 fixation through the Wood-Ljungdahl pathway. Interestingly, these bacteria showed a high proportion of ancestral genes in their genomes providing intriguing perspectives on mechanisms driving microbial evolution in this peculiar environment. Overall, our results provide new knowledge for understanding microbial life under extreme conditions in blue hole environments.