bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-snapshot machine learning for super-resolution of turbulence
Authors: Fukami Kai , Taira Kunihiko
Published: December 2024

Modern machine-learning techniques are generally considered data-hungry. However, this may not be the case for turbulence as each of its snapshots can hold more information than a single data file in general machine-learning settings. This study asks the question of whether nonlinear machine-learning techniques can effectively extract physical insights even from as little as a single snapshot of turbulent flow. As an example, we consider machine-learning-based super-resolution analysis that reconstructs a high-resolution field from low-resolution data for two examples of two-dimensional isotropic turbulence and three-dimensional turbulent channel flow. First, we reveal that a carefully designed machine-learning model trained with flow tiles sampled from only a single snapshot can reconstruct vortical structures across a range of Reynolds numbers for two-dimensional decaying turbulence. Successful flow reconstruction indicates that nonlinear machine-learning techniques can leverage scale-invariance properties to learn turbulent flows. We also show that training data of turbulent flows can be cleverly collected from a single snapshot by considering characteristics of rotation and shear tensors. Second, we perform the single-snapshot super-resolution analysis for turbulent channel flow, showing that it is possible to extract physical insights from a single flow snapshot even with inhomogeneity. The present findings suggest that embedding prior knowledge in designing a model and collecting data is important for a range of data-driven analyses for turbulent flows. More broadly, this work hopes to stop machine-learning practitioners from being wasteful with turbulent flow data.
Rediscovering Bernard and Cannon: Restoring the Broader Vision of Homeostasis Eclipsed by the Cyberneticists
Authors: Bechtel William , Bich Leonardo
Published: December 2024

Since Cannon, inspired by Bernard’s discussion of the conditions required for free and independent life, introduced the term homeostasis, many have embraced it as the main theoretical principle guiding physiology and medicine. Nonetheless, critics have argued that homeostasis is too limiting and have advanced a variety of alternative concepts such as heterostasis, rheostasis, and allostasis. We argue that the critics target a much narrower understanding of homeostasis put forward by the cyberneticists and that Bernard and Cannon embraced a far broader understanding that can accommodate the alternatives advanced by the critics and provide an integrated theoretical framework for physiology.
Growth analysis of cassava genotypes planted under irrigation management practices during the early growth phase
Authors: Ruangyos Chanissara , Banterng Poramate , Vorasoot Nimitr , Jogloy Sanun , Theerakulpisut Piyada , Vongcharoen Kochaphan , Hoogenboom Gerrit
Published: December 2024

New information on the growth analysis for different cassava genotypes grown under different irrigation managements during the early growth phase could support decision-making to improve crop productivity. This study aimed to determine the performance of 20 cassava genotypes grown under different irrigation management practices during the early growth phase. A strip-plot design with four replications was used during two growing seasons (2019/2020 and 2020/2021). Three levels of irrigation from 30 to 180 days after planting (DAP) were assigned as factor A (W1 = 100%, W2 = 60% and W3 = 20% of the crop water requirement), whereas 20 cassava genotypes were assigned as factor B. Crop data were recorded on SPAD chlorophyll meter reading (SCMR), specific leaf area (SLA) and leaf area index (LAI) at 180 and 330 DAP, relative growth rate (RGR) from 180 to 330 DAP and harvest index (HI) at 330 DAP. The genotypes CMR36-31-381 and Huay Bong 90 had high values of HI, indicating a good partitioning of photosynthate to the storage root. These two genotypes also showed superior performances in terms of SCMR, SLA and RGR inW2 and W3 treatments when compared to the other genotypes. They also had LAI values within the optimum range during the period of maximum canopy size. Therefore, the genotypes CMR36-31-381 and Huay Bong 90 could be used as genetic resources to improve cassava productivity under different irrigation levels.
Phylogenetic study of the Cladonia cervicornis group (Cladoniaceae, Lecanorales) discloses a new species, Cladonia teuvoana
Authors: Pino-Bodas Raquel , Herrero Alberto , Aptroot André , Søchting Ulrik , McMullin Richard Troy , Burgaz Ana Rosa
Published: December 2024

The Cladonia cervicornis group comprises lichen-forming fungi characterized by having scyphi with central proliferations. It includes c. 20 species globally. The taxonomy of this group is poorly resolved, with many species not thoroughly disentangled. The focus of this study is the European species in the C. cervicornis group. In order to estimate the phylogenetic relationships of these species, six loci were used: ITS rDNA, IGS rDNA, RPB1, RPB2, ef1α and cox1. Species delimitation methods (ASAP, PTP and GMYC) were used to infer the species boundaries based on four loci, ITS rDNA, IGS rDNA, cox1 and RPB2. A morphological analysis based on multivariate methods was performed to assess the importance of phenotypic differences among the lineages. The phylogenetic reconstructions placed the species of this group in the subclade Cladonia. Five lineages were recovered, corresponding to C. cervicornis, C. macrophyllodes, C. pulvinata, C. verticillata and a new lineage that we describe here, C. teuvoana. Our analyses revealed that Cladonia cineracea, C. stricta and C. trassii are polyphyletic.
Contributions to the knowledge of lichenicolous fungi growing on Rhizoplaca s. lat., including five new taxa and an identification key
Authors: Zhurbenko Mikhail P.
Published: December 2024

Sixteen species and two varieties of lichenicolous fungi are reported from Rhizoplaca s. lat. Four species and one variety are described as new to science: Caeruleoconidia ahtii Zhurb. (on Rhizoplaca s. str.), with hyaline to pale greyish turquoise, comparatively large conidia; Cercidospora mongolica Zhurb. & Cl. Roux (on Rhizoplaca s. str.), with a reddish brown (above) to pale brownish grey to colourless (below) exciple, mostly 4-spored asci, and (0‒)1(‒2)-septate ascospores, mostly 23‒28.5 μm long; C. tyanshanica Zhurb. & Cl. Roux (on Protoparmeliopsis and Rhizoplaca s. str.), with a uniformly grey exciple, mostly 4-spored asci, and (0‒)1(‒2)-septate ascospores, mostly 25.5‒31.5 μm long; Stigmidium pseudosquamariae Zhurb. (on Protoparmeliopsis), inducing brown cerebriform galls, with consistently immersed ascomata and well-developed pseudoparaphyses of type b sensu Roux & Triebel (1994); and Arthonia clemens var. peltatae Zhurb. (on Protoparmeliopsis), with a brown epihymenium without grey shade. An unidentified species of Leptosphaeria growing on Protoparmeliopsis peltata, and Lichenostigma cf. chlaroterae growing on P. peltata and Rhizoplaca chrysoleuca are briefly characterized. Arthonia clemens is newly reported for Kazakhstan, Kyrgyzstan and the Republic of Sakha (Yakutia) in Russia; Cercidospora melanophthalmae is new to Kazakhstan, Kyrgyzstan and Mongolia; Didymocyrtis rhizoplacae is new to Russia; Lichenoconium lecanorae and Muellerella erratica are new to Kyrgyzstan; Stigmidium squamariae s. lat. is new to Kazakhstan, Kyrgyzstan and Turkmenistan. Didymocyrtis rhizoplacae is documented for the first time on Rhizoplaca subdiscrepans, and Pyrenidium actinellum s. lat. on Protoparmeliopsis. A key to 36 species of lichenicolous fungi and lichens known to occur on Rhizoplaca s. lat. is provided.
Genome-wide assessment of putative endemism and phylogeography of Cladonia sandstedei (Ascomycota: Cladoniaceae) in the Caribbean
Authors: Mercado-Díaz Joel A. , Grewe Felix , Lücking Robert , Moncada Bibiana , Rivera-Queralta Yoira , Motito-Marín Ángel , Lumbsch H. Thorsten
Published: December 2024

Cladonia sandstedei forms cushion-shaped lichens that colonize open environments and is distributed throughout the Caribbean and the south-eastern United States. It co-occurs in parts of its range with C. subtenuis, a morphologically similar taxon that is distinguished from the former by the presence of usnic acid. Preliminary phylogenetic analysis with the RPB2 and TEF-1α loci revealed that these taxa were closely related, but relationships were inconsistent among markers. Here, we combined phylogenetic and population genomic analyses based on RADseq data to clarify the evolutionary relationships and phylogeography of these taxa. Both approaches indicate that the taxa cannot be separated based on secondary metabolites, as previously proposed, but instead form a complex composed of several lineages, largely unrelated to chemistry but with a strong geographical structure in their genetic variation. Continental populations formerly separated under the names C. sandstedei and C. subtenuis were closely related to each other. A similar pattern was observed in the Jamaican counterparts of these taxa, suggesting homoplasy of secondary chemistry. Discriminant Analysis of Principal Components (DAPC) hinted at potential conspecificity between populations in Cuba and Puerto Rico on one hand, and between Jamaica and the continental US on the other; however, phylogenetic analysis and other population-level analyses (PCA and fineRADstructure) suggested that both insular and continental populations were more likely to be reproductively isolated from each other. Based on this, we propose to recognize only one species for the entire complex, under the older name C. sandstedei, with the four spatially structured clades as subspecies: C. sandstedei subsp. sandstedei (restricted to Jamaica) and C. sandstedei subsp. subtenuis comb. nov. (restricted to continental North America) exhibit several chemosyndromes variably containing usnic acid and/or atranorin. The two additional subspecies described here as new, C. sandstedei subsp. cubana and C. sandstedei subsp. landroniana, exhibit the atranorin chemosyndrome and are restricted to Cuba and Puerto Rico, respectively. Our work reaffirms the power of combining RADseq-based phylogenetics and population genetics to disentangle taxonomic and evolutionary histories in poorly understood, closely related and phenotypically similar lichen-forming fungal species.
Biodiversity and distribution of sea anemones (Cnidaria, Anthozoa, Actiniaria) in Peru
Authors: Durand Allison , Valdivia-Chávez Deysi , Aramayo Víctor
Published: December 2024

Sea anemones represent a highly abundant and diverse group within marine ecosystems, yet biodiversity analyses in Peru remain comparatively scarce. To enhance the inventory of biodiversity and its distribution, a comprehensive review of the available literature on species from Peruvian waters was performed. Only seven well-documented species (i.e. verified records) were found representing 31.8% of the total species reported in Peru (22 spp.) These seven species are Anthothoe chilensis, Phymactis papillosa (formerly reported as P. clematis), Phymanthea pluvia, Oulactis concinnata, Antholoba achates, Anemonia alicemartinae and Oulactis coliumensis. Overall, specimens were identified in 68 localities, the Actiniidae family exhibited the highest diversity with five species (71.4% of the total), whereas Actinostolidae and Sagartiidae each contributed one species (14.3%). The highest number of scientific publications (18) corresponds to the Lima region, with over twice as many studies as other regions, it is followed by Ica (8), Áncash (7), La Libertad (6), Tumbes (5), Piura (4), Arequipa (3), Tacna (2), Moquegua (1) and Lambayeque (1). However, the studied localities are unevenly distributed across regions. Rocky substrata (~55% of records) are the most reported habitat for sea anemones in Peru, including exposed vertical walls and sheltered crevices, caves and areas under rocks. Despite wide spatial distribution, our results indicate several under-researched regions. The growing interest in these benthic invertebrates over recent decades has revealed over 50% of reported biodiversity, yet many doubts about species described long ago remain. Potential biases in existing data require identification along with further analysis of environmental information.
Linguistic complexity in second language writing: Insight from studies on task planning
Authors: Johnson Mark D. , Abdi Tabari Mahmoud
Published: December 2024

Task planning and its effect on the complexity of second language (L2) written production have been studied extensively. However, the results of these studies are inconclusive, and at times contradictory, potentially as a result of variation in metrics of linguistic complexity. This study is an extension of earlier research syntheses and quantitative meta-analyses on the effects of planning on oral and written L2 production. It examines the identification and selection of linguistic complexity metrics in previous research on planning and its subsequent effects on the linguistic complexity of written L2 production. This research-focused synthesis of studies surveys construct definitions and operational definitions of linguistic complexity in the research domain and provides an overview of rationales for metric selection in the included studies. Methodological implications for future research are discussed in light of the findings.
A review of methods for mapping 3D rotations to one-dimensional planar rotations: analysis, comparison, and a novel efficient Quaternion-based approach
Authors: Ghiassi Mehdi , Kecskeméthy Andrés
Published: December 2024

In numerous applications, extracting a single rotation component (termed “planar rotation”) from a 3D rotation is of significant interest. In biomechanics, for example, the analysis of joint angles within anatomical planes offers better clinical interpretability than spatial rotations. Moreover, in parallel kinematics robotic machines, unwished rotations about an axis – termed “parasitic motions” – need to be excluded. However, due to the non-Abelian nature of spatial rotations, these components cannot be extracted by simple projections as in a vector space. Despite extensive discussion in the literature about the non-uniqueness and distortion of the results due to the nonlinearity of the SO(3) group, they continue to be used due to the absence of alternatives. This paper reviews the existing methods for planar-rotation extraction from 3D rotations, showing their similarities and differences as well as inconsistencies by mathematical analysis as well as two application cases, one of them from biomechanics (flexural knee angle in the sagittal plane). Moreover, a novel, simple, and efficient method based on a pseudo-projection of the Quaternion rotation vector is introduced, which circumvents the ambiguity and distortion problems of existing approaches. In this respect, a novel method for determining the orientation of a box from camera recordings based on a two-plane projection is also proposed, which yields more precise results than the existing Perspective 3-Point Problem from the literature. This paper focuses exclusively on the case of finite rotations, as infinitesimal rotations within a single plane are non-holonomic and, through integration, produce rotation components orthogonal to the plane.
Advancing cooperation in Health Technology Assessment in Europe: insights from the EUnetHTA 21 project amidst the evolving legal landscape of European HTA
Authors: Urbina Irene , Adams Roisin , Fernandez Judith , Willemsen Anne , Hedberg Niklas , Rüther Alric
Published: December 2024

Health Technology Assessment (HTA) in Europe has undergone significant evolution, culminating in the adoption of Regulation (EU) 2021/2282 on HTA (HTAR) aimed at fostering sustainable collaboration in HTA at the European Union (EU) level. The EUnetHTA 21 project, a 2-year initiative, was commissioned to address key methodological issues and prepare for the implementation of the HTAR. This commentary documents the outcomes of the EUnetHTA 21 project, focusing on Joint Clinical Assessments (JCAs), while analyzing challenges encountered and lessons learned for future collaboration under the HTAR. The EUnetHTA 21 consortium, comprising thirteen European HTA bodies, developed twenty guidance documents and thirteen templates, refining methods and procedures for joint work in HTA at EU level. Pilot JCAs and Joint Scientific Consultations were conducted to test these materials. Lessons learned from this experience emphasize the importance of inclusive consensus building, effective time and resource management, capacity building, and continuous quality improvement. The project’s realization underscores a collective commitment among HTA bodies to continue to collaborate, now under a legal framework. Recommendations from the project, along with experiences gained from previous European Network for HTA (EUnetHTA) Joint Actions, provide a foundation for developing guidance for EU-HTA under the HTAR. Further proactive efforts at national and central levels are essential to coordinate and ensure a sustainable cooperation. The EUnetHTA 21 experience provides valuable insights for advancing cooperation in HTA under the HTAR, aiming to improve the quality of HTA, avoid duplication, and ultimately enhance patient access to safe and effective health technologies in the EU.
Remote collection of language samples from three-year-olds
Authors: Jo Jinyoung , Sundara Megha
Published: December 2024

We characterised language samples collected remotely from typically developing three-year-olds by comparing them against independent language samples collected in person from age-matched peers with and without language delays. Forty-eight typically developing, English-learning three-year-olds were administered a picture description task via Zoom. The in-person comparison groups were two sets of independent language samples from age-matched typically developing as well as language-delayed children available on the Child Language Data Exchange System. The findings show that although language samples collected remotely from three-year-olds yield numerically dissimilar lexical and grammatical measures compared to samples collected in person, they still consistently distinguish toddlers with and without language delays.
Living with impunity versus living in fear: Universal jurisdiction defendants, due process, and the use of democracies by autocracies to prosecute their opponents
Authors: Bryce Natalie M. , Johns Leslie , Langer Máximo
Published: December 2024

This article introduces a new analytical category to provide a more accurate, comprehensive, and nuanced account of universal jurisdiction defendants: defendants living in fear. In contrast to defendants living with impunity, defendants living in fear are defendants whose home state is very much willing and able to prosecute and punish them. Using an original database, this article shows that there is a substantial number of universal jurisdiction defendants who live in fear, and that their percentage has increased since the early 2000s. The article also shows that defendants living in fear are more than ten times more likely to be arrested and more than 30 times more likely to be tried than defendants living with impunity.

In addition, this article argues that the function and justification of universal jurisdiction for defendants living in fear is not (only) the traditional justification of avoiding impunity, but (also) providing a fair trial that prevents wrongful convictions, and then assigning proportionate punishment if the defendant is found guilty.

Finally, this article discusses what democracies should do with living-in-fear cases to avoid being instruments of autocratic regimes that often prompt or encourage universal jurisdiction cases in other states against their military and political opponents.
Environmental constraints on the origin of life based on membrane formation: the role of salinity
Authors: Ginter Taren , Dujardin Alix , Roumans Sanne , Rothschild Lynn J. , Rheinstädter Maikel C.
Published: December 2024

The environmental conditions for the origin of life are still not well-constrained, but membrane-bound structures must have been key to the origin of life. Membranes composed of fatty acids are promising candidates due to their simplicity and plausible prevalence in prebiotic environments. To assess the stability of membranes composed of fatty acids with tail lengths ranging from 12 to 16 carbons at different temperatures and sodium chloride concentrations that may have existed on the early Earth, we conducted all-atom molecular dynamics (MD) simulations. In the absence of salt (freshwater), none of the fatty acids exhibited bilayer formation, whether below or above their chain melting temperature. However, elevating the salt concentration from 0.15 M (saline solution), 0.5 M (seawater), 1 M (seawater tide pools), 3 M (salty tide pools) and 5 M (Dead Sea) resulted in the formation of stable bilayers. The 16-carbon fatty acid required lower salt concentration, while shorter, 12-carbon chain necessitated higher salt levels. Increasing the salt concentration led to three main effects: (1) increased bilayer thickness, (2) reduced area per fatty acid and (3) elevated deuterium order parameter of the chains, resulting in more robust membranes. Our simulations indicated that the salt cations aggregated on the bilayer surfaces, effectively mitigating repulsive interactions among hydrophilic fatty acid head groups. These findings suggest that fatty acid bilayers are more likely present in ancient waters connected to saltwater reservoirs, or seawater tide pools with elevated salt concentrations.
The Analysis and the Impact of Surface Temperature Anomalies on the Health of Residents in the River Niger Basin Development Authority Area, West Africa
Authors: Akinnubi R. T. , Adegbo K. J. , Ojo M. O. , Ajakaiye M. P. , Sabejeje A. J. , Aramide J. O. , Akinnubi T. D.
Published: December 2024

This study investigates the impact of surface temperature anomalies on the health of residents within the River Niger Basin Development Authority (RIBDA) enclave, which covers Nigeria, Niger, and Mali in West Africa, with a focus on the regional implications for public health. Historical climate data from 1985 to 2014, sourced from the Climatic Research Unit Time‐Series, Version 3.22 (CRU TS 3.22), was analyzed to comprehend past climate patterns and establish a baseline for future comparisons. Predictions for future climate conditions (2015–2044) were derived by adjusting the CRU data using temperature projections from the Community Climate System Model 4 under the Representative Concentration Pathway 8.5 scenario. To assess the potential impacts of these climate changes, particularly during the boreal summer season of July‐August‐September (JAS), the study utilized the Hydrology, Entomology, and Malaria Transmission Simulator (HYDREMATS). Findings indicate that surface temperature can intricately influence disease transmission, with varied effects on parameters such as Ro, EIR, prevalence, and immunity index. Observations revealed fluctuations in temperature anomalies over the years, with negative anomalies in 1991–1995 and positive anomalies in subsequent years. Although precise predictions for 2016–2044 are challenging based solely on data trends from 1985 to 2015, continued temperature rises could potentially lead to increased disease prevalence and decreased immunity index. Moreover, the analysis identified a notable temporal increase in mean annual temperature and mean annual maximum temperature from 1999 to 2020, suggesting a faster warming trend in maximum temperatures compared to minimum temperatures. This increase in temperature variability may alter the onset and cessation dates of the rainy season, affecting water availability, accessibility, and consumption, consequently fostering conditions conducive to health‐related diseases. By incorporating predicted long‐term temperature changes due to greenhouse gas emissions while maintaining current inter‐annual climate patterns, this approach allows researchers to anticipate potential future health implications in the studied regions.
Summertime Continental Shallow Cumulus Cloud Detection Using GOES‐16 Satellite and Ground‐Based Ceilometer at North Alabama
Authors: Tian Jingjing , Zhang Yunyan , Knupp Kevin , Pangle Preston , Comstock Jennifer
Published: December 2024

Accurate simulations of boundary layer cloud processes remain challenging in Earth system modeling. Observations are essential to evaluate and improve models of such processes. This study introduces a comprehensive validation framework for a satellite‐based detection algorithm of continental shallow cumulus (ShCu) clouds during the daytime, which was initially developed using ground‐based observations of stereo cameras at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site (J. Tian et al., 2021, https://doi.org/10.3390/rs13122309, 2022, https://doi.org/10.1029/2021gl097070). To validate this algorithm, the framework employs ground‐based ceilometer measurements from North Alabama (NA) where ShCu populations are prevalent. This study first generates clear‐sky surface reflectance maps at NA and identifies ShCu pixels with a detection threshold using Geostationary Operational Environmental Satellite (GOES) reflectance data. The obtained cloud fractions (CFs) are then compared against CFs from a ground‐based ceilometer, considering factors such as observed area differences, satellite parallax issue, and systematic biases. We found that with a detection threshold (∆R) of 0.05, the ShCu detection algorithm is effective for NA, enabling the reproduction of hourly ShCu CFs using GOES. Our framework is straightforward and easily repeatable to evaluate the effectiveness of a ∆R threshold for detecting ShCu clouds in various geographic regions where ceilometers are deployed. This satellite detection of ShCu provides a crucial regional context for ground‐based measurements, facilitating the tracking of convection initiation and its coupling with land surface conditions. Integrating localized ground‐based and regional satellite data will enhance our ability to conduct thorough studies of cloud morphology and land‐atmosphere interactions in North Alabama.
Cyclin-dependent kinase inhibitor p18 regulates lineage transitions of excitatory neurons, astrocytes, and interneurons in the mouse cortex
Authors: Lee Wonyoung , Kang Byunghee , Kim Hyo-Min , Ishida Tsuyoshi , Shin Minkyung , Iwashita Misato , Nitta Masahiro , Shiraishi Aki , Kiyonari Hiroshi , Shimoya Koichiro , Masamoto Kazuto , Roh Tae-Young , Kosodo Yoichi
Published: December 2024

Neural stem cells (NSCs) can give rise to both neurons and glia, but the regulatory mechanisms governing their differentiation transitions remain incompletely understood. Here, we address the role of cyclin-dependent kinase inhibitors (CDKIs) in the later stages of dorsal cortical development. We find that the CDKIs p18 and p27 are upregulated at the onset of astrocyte generation. Acute manipulation of p18 and p27 levels shows that CDKIs modulate lineage switching between upper-layer neurons and astrocytes at the transitional stage. We generate a conditional knock-in mouse model to induce p18 in NSCs. The transcriptomic deconvolution of microdissected tissue reveals that increased levels of p18 promote glial cell development and activate Delta-Notch signaling. Furthermore, we show that p18 upregulates the homeobox transcription factor Dlx2 to subsequently induce the differentiation of olfactory bulb interneurons while reducing the numbers of upper-layer neurons and astrocytes at the perinatal stage. Clonal analysis using transposon-based reporters reveals that the transition from the astrocyte to the interneuron lineage is potentiated by p18 at the single-cell level. In sum, our study reports a function of p18 in determining the developmental boundaries among different cellular lineages arising sequentially from NSCs in the dorsal cortex.
Transposable element activity captures human pluripotent cell states
Authors: Levin-Ferreyra Florencia , Kodali Srikanth , Cui Yingzhi , Pashos Alison R S , Pessina Patrizia , Brumbaugh Justin , Di Stefano Bruno
Published: December 2024

Human pluripotent stem cells (hPSCs) exist in multiple, transcriptionally distinct states and serve as powerful models for studying human development. Despite their significance, the molecular determinants and pathways governing these pluripotent states remain incompletely understood. Here, we demonstrate that transposable elements act as sensitive indicators of distinct pluripotent cell states. We engineered hPSCs with fluorescent reporters to capture the temporal expression dynamics of two state-specific transposable elements, LTR5_Hs, and MER51B. This dual reporter system enables real-time monitoring and isolation of stem cells transitioning from naïve to primed pluripotency and further towards differentiation, serving as a more accurate readout of pluripotency states compared to conventional systems. Unexpectedly, we identified a rare, metastable cell population within primed hPSCs, marked by transcripts related to preimplantation embryo development and which is associated with a DNA damage response. Moreover, our system establishes the chromatin factor NSD1 and the RNA-binding protein FUS as potent molecular safeguards of primed pluripotency. Our study introduces a novel system for investigating cellular potency and provides key insights into the regulation of embryonic development.
The systems and interactions underpinning complex cell wall patterning
Authors: Deinum Eva E.
Published: December 2024

Cell walls can confer amazing properties to plant cells, particularly if they have complex patterns. Complex cell wall patterns in the primary cell wall often lead to complex cell shapes, whereas in the secondary cell wall they lead to advanced material properties that prepare cells for mechanically demanding tasks. Not surprisingly, many of these structures are found in water transporting tissues. In this review, I compare the mechanisms controlling primary and secondary cell wall patterns, with emphasis on water transporting tissues and insights derived from modeling studies. Much of what we know about this is based on complex cell shapes and primary xylem patterns, leading to an emphasis on the Rho-of-plants — cortical microtubule — cellulose microfibril system for secondary cell wall patterning. There is a striking diversity of secondary cell wall patterns with important functional benefits, however, about which we know much less and that may develop in substantially different ways.
A study on Pursuit of Artificial Intelligence in Human Resource Management: A Narrative view
Authors: Ganagi Mahesh C. , Rotti Arun A.
Published: December 2024

This study harnesses the power of narrative to explore how artificial intelligence (AI) transforms Human Resource Management (HRM). The findings illustrate the broad changes that are taking place in key HR activities like recruitment, performance management processes, employee engagement and learning & development as organizations adopt more AI powered tools to enable workforce outcomes. Synthesising current insights and case studies, the paper identifies AI use-cases that help improve processes while supporting data-driven decision-making. But it tackles moral questions too — biases in algorithms, privacy issues around handling data and the iffy territory of how workers might take to using A.I. The methodology makes use of a secondary data analysis, employing thematic analysis to investigate the consequences that AI can mean for HRM. The results bring home the vast possibilities and difficulties associated with utilizing AI, underscoring why HR workers must quickly come to grips with rapid change in tech. Conclusion This study facilitates important contributions to the current debate on AI and future work, providing a comprehensive narrative perspective on what it means for HR professionals and organizations.
Analysing Employees’ Perception of AI-Enhanced Work from Home Approach in Karnataka
Authors: Bhajantri Vani Dilipkumar , Kudachimatht Basavaraj S. , Inamdar Rajendra M. , Daddikar Prasad
Published: December 2024

The shift to working from home became a standard response across industries during the COVID19 pandemic to sustain the economy. This shift accelerated the global transition to remote work, altering traditional workplace dynamics. This analytical study investigates employees’ perceptions of AI-enhanced work from home (WFH) models in Karnataka. Using a survey of 183 participants through a convenience sampling method, the study examines key variables influencing WFH experiences, including job satisfaction, work-life balance, productivity, and challenges related to technology and AI integration. Our findings reveal that most employees working from home report higher job satisfaction and improved worklife balance, however, significant challenges persist, such as inadequate technology infrastructure, unclear work-life boundaries, and issues related to AI integration. Demographic factors like age, gender, and job role also influenced attitudes and adaptability to AI-driven remote work. The insights from this study can help employers and policymakers refine remote work policies and AI support systems, ensuring a productive and balanced remote workplace. Future research should focus on the long-term effects of AI-enhanced WFH and strategies to overcome its challenges.
The Impact of Artificial Intelligence in Reshaping Education: An Analysis Based on Learning Theories
Authors: Krishna S Lekshmi , Prasad C Jayasankar , S Anjali
Published: December 2024

A change in behavior that results from experience and is relatively permanent in nature can be defined as Learning. Behaviorism, a dominant theory used to explain learning, sought to measure only observable behaviors. In AI training, supervised and reinforcement learning methods can help machines learn from feedback and improve their performance and this process influences or biases the learner when he adopts AI as a tool for learning and when it is in their zone of understanding. Exposure to AI technologies in higher education prepares students for future careers, as they gain experience with tools and skills that are increasingly relevant in the workforce. To identify the implications of AI interaction in learning we have taken the experiences of 38 students and 15 educators from different fields. We have identified different levels of AI interactions in scaffolding, individualization, challenges, and stress. The design and implementation of different learning platforms aligned with the Zone of Proximal Development (ZPD) in higher education can also be associated with several learning theories. therefore, the features of such a platform also correspond to different learning theories.
Chatbots of Indian banks – utility for prospective customers – a perceptive study
Authors: B V Ramana Rao , Kulkarni Savitha
Published: December 2024

Introduction of Chatbots by banks has changed the face of interaction between customers and banks. The cost-effectiveness and the lead generation advantage of Chatbots will drive Indian banks for enhanced functionality of Chatbots. However, the availability of Chatbot on the website of bank alone will be of use for a prospective customer for a bank. This fact is not yet fully recognized by the Indian Banks. This research paper attempted to analyse the level of functionality of Chatbots placed on the websites of banks considered for study, based on primary data collected from 17 banks in India. The uniqueness of this research work is the exclusive focus on the utility of Chatbots provided by Indian banks for the prospective customers of banks rather than for the existing customers. The study indicated that an amount of improvement is required in the functionality of Chatbots in the two-way interaction through posing a query by the user. In the context of application of AI in the arena of digital financial inclusion, making available the Chatbots in Indian languages may seem to be imperative for the banks in our country in the years to come.
Evaluating Mutual Funds for Retirement: Insights from Primary Data Analysis on Investor Preferences and Performance
Authors: Metilda Jayaraj Mary , B Abhishek
Published: December 2024

This study evaluates the effectiveness of mutual funds in a retirement planning context by analyzing primary data collected from 204 participants, including investors and financial advisors. The survey focused on four important variables, diversification of funds, long term performance of the chosen fund, impact on retirement savings and the risk return relationship. A descriptive analysis and simple statistical tests like correlation to study the strength of relationship between the variables and regression to understand the predictive ability of the variables, demonstrates positive relationships in all the factors. The correlation analysis demonstrates positive relationships in all the factors. . Long-term performance is highly correlated with diversification, and also strongly related to impact on retirement savings and risk. This interconnectedness indicates that respondents who value one aspect of investment are likely to value others as well. The findings also suggest a positive impact of diversification on mutual fund long term performance and also a significant effect of long-term performance on ‘impact on retirement saving’.
Loan Borrower’s Perception and Awareness on CIBIL Credit Scoring Model
Authors: Jayaraj Mary Metilda , Togal Amrut
Published: December 2024

This study examines the effectiveness of various credit scoring models employed by financial institutions particularly in predicting loan default rates. The growing reliance on these models to decide on lending loans , understanding the factors that influence credit score such as payment history, the length of credit history, the diversity of credit portfolios and the total amount owed has become crucial. This research seeks to assess the awareness levels among borrowers regarding these factors and how their understanding impacts their financial decisions. By employing structured questionnaires and surveys the study gathers data from loan borrowers to understand borrower behaviour and knowledge on credit scores. ANOVA and correlation analysis is used to examine the differences in awareness across demographics variables and CIBIL factors. The findings indicate that demographic factors like gender, age and education levels impact their understanding of the CIBIL credit score factors.
Exploring User Experience and Perception of Online Digital Payment Systems
Authors: Jayaraj Mary Metilda , Bhat Adarsh Umesh
Published: December 2024

Growing internet accessibility, the rise of Internet electronic devices and government initiatives and commitment to transform India into a digital society has rapidly transformed the payment mechanism into a cashless one. This paper explores the user experience and perception of the digital payment system across different demographic profiles. The study seeks to understand the influence of demographic variables on preference for online payments, usage experience, satisfaction levels, security concerns and purchase experience. Gender, education, age and employment status are associated. There is a moderate correlation between the preference for online payments and user experience, security concerns, satisfaction levels and purchase experience. Findings show a broad agreement that online payment systems are generally seen as accessible and easy to use, supporting their widespread adoption. It is also found that there is a strong sense of security among most users, highlighting the effectiveness of online payment systems in safeguarding personal data, reflecting widespread confidence in their security features despite some concerns.
Insights into Rural Consumers’ Perceptions on Digital Payment Systems
Authors: Jayaraj Mary Metilda , Sarkar Bibek
Published: December 2024

This study uses structured questionnaires to determine the factors that affect rural Indian consumers’ adoption of bank-launched electronic payments products. The paper aims to identify certain demographic characteristics that influence digital payment and to uncover dimensions of factors that influence digital payments in the rural set up. Data was collected form 200 respondents from the rural districts of Assam and Nagaland. Descriptive statistics was used to analyze the demographic variables. To uncover factors influencing the digital payment system, a factor analysis of variables identified was used and three factors literacy, technology and reliability and perception and concerns were identified and tested for reliability of the items to be measured. We propose future research in the identified variables using the tested measurement scales.
A comprehensive study on comparison of Long short-term memory, Support Vector Machine, and their hybrid model performance using erratic cryptocurrency data
Authors: Hegde Bhumika Prakash , U Roopa
Published: December 2024

Prediction of relatively accurate cryptocurrency prices remains a big challenge due to the high volatility inherently associated with it and the absence of appropriate valuation metrics. This research explores the performance of Long Short-Term Memory (LSTM), Support Vector Machine (SVM), and the hybrid model of these two algorithms for this complex task. LSTM has demonstrated significant potential in capturing short-term price fluctuations. At the same time, the hybrid model aims to combine the strengths of temporal dependencies of LSTM, and nonlinear data pattern recognition of SVM considering the generalization ability of the models, robustness, computational efficiency, and interpretability. To evaluate the models’ performance, a comprehensive evaluation framework was used. Historical daily price data for five leading cryptocurrencies had been used. This data had been used to test the performance of algorithms used in this study, by using metrics such as R-Square value and P value, Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). This research aims to provide comparative analysis of machine learning and deep learning models for the cryptocurrency price forecasting. The insights/outcomes gained by this study holds value for both forecasters and researchers. Upcoming studies can focus to explore more advanced hybrid architectures by adding additional data sources and checking how varying market conditions affects model performance.
Gamification empowered with AI tools to enhance student learning engagement and involvement for personalized effective learning experiences
Authors: Surve Bhisaji C. , Ghatule Arjun P.
Published: December 2024

A prevalent mindset in modern society that can transcend the educational process should be “Game Thinking”; because there is a strong connection between game-like environments andworkplace settings. The application of game-inspired thinking in non-gaming contexts, particularly through technological tools, is referred to as “Gamification.”

Technology-savvy Millennials, the current dominant workforce, represent the future of business leadership. Therefore, gamification is highly effective in engaging this generation in meaningful ways. The intersection of the Gamification of education and AI presents numerous opportunities for enhancing learning experiences. Continuous research in these areas can lead to innovative solutions that empower students enabling them to achieve their educational goals more effectively as a benefit. Secondly, gamified outcome-based educational approaches can produce industry-ready skilled manpower.

AI tools based on Large Language Models (LLM) enhance their capabilities in multimodal means to handle not only text but audio-video-graphics too; hence these tools can bring new excitement to education paedology. The first part of the paper provides a psychological framework for gamification, while the second segment explores how to develop and constructa technological framework to implement AI-based gamification.
“An Empirical study on Enhancing Employee Engagement and Job Performance through Self-Determination Theory: The Role of Artificial Intelligence in Karnataka’s Banking Sector”
Authors: Arokiyaswamy C Milagrin Mary , Rathod Pralhad , Aishwaryalaxmi N.S. , Kagawade Shivanand
Published: December 2024

The The integration of Self-Determination Theory and Artificial Intelligence in facilitating employee engagement in job performance within the banking sector in Karnataka was explored. SDT states that three innate psychological needs are at the center of developing intrinsic motivation and job satisfaction, which is stated as autonomy, competence, and relatedness. When AI tools are designed to meet these needs, organizations can create a more supportive and motivating work environment. Examples are personalized experiences provided by AI in task management systems that better help employees manage their work, real-time feedback to develop employee skills, and collaboration platforms that enhance connections among team members. The outcome can be increased employee engagement and job satisfaction to enhance overall performance. It offers some practical insights into how AI can be used to respond to the recent challenges that emerge with regard to employee engagement within an increasingly fast-moving banking environment and further opines that there is a need to balance technology approaches with human-centered approaches. This will be quite useful for the HR manager and the organizational leader in driving motivation, productivity, and job satisfaction through AI.
Artificial Intelligence (AI) as a Moderating Variable in the Relationship Between Financial Inclusion, Digital Adoption, and Financial Literacy in Developing Economies
Authors: Aishwaryalaxmi N.S. , Rathod Pralhad , Arokiyswamy C Milagrin Mary
Published: December 2024

This Research study has explored in an analytical how Artificial Intelligence (AI)acts as a mediating variable in the connection between digital literacy, digital adoption, and financial inclusion in developing economies. Building on prior research, which highlights the crucial part of digital financial literacy in making progress financial inclusion, this study introduces AI-driven Fintech tools as a key enabler. The findings suggest that AI enhances financial decision-making for underserved populations by simplifying complex financial tasks and bridging financial literacy gaps. This, in turn, promotes wider adoption of digital financial services, mainly in between people who has less financial knowledge. Using a sample size of 350 participants from developing economies, the study provides evidence that AI strengthens the effect of internet financial in a positive way and digital adoption on financial inclusion. The study contributes to a deeper theoretical understanding of digital adoption, highlighting AI’s capacity to mitigate the adverse effects of low financial literacy. For both Fintech companies and policy-makers it gives a broader picture of how Artificial intelligence and the tools connected with it are increasing access of all financial services to the more distanced population who aren’t able to connect. The study shows the Artificial intelligence connection with financial inclusion and how it transforms the extended potential in helping the increase in digital adoption which helps in developing economies and how it empowers the underserved population through the connection internet banking through the help of AI.