Abstract Endocrine disruption during pregnancy has gained increasing interest as epidemiological studies report associations of exposures and adverse effects on fetal growth, followed by effects on the growing child and ultimately in the adult. When studying endocrine disruption during pregnancy the placental steroidogenesis is difficult to model, as the human placenta is unique in the pathway of cellular uptake of cholesterol, the high levels of progesterone production, and the expression of aromatase. Models to test for endocrine disruption should respect species differences with preference to human models for human risk assessment. Here, we present existing research of placental steroidogenesis and other placental hormones using human placental models: Placental perfusion, placental explants, microsomes and vesicles, primary cell culture, stem cells, Placenta-on-a-chip, and choriocarcinoma cell cultures: BeWo, HTR8/SVneo, Jar, JEG-3 and ACH-3P. We conclude that there is a lack of research focused on placental steroidogenesis and the effects of EDC. Advantages and limitations of existing models are discussed and future directions suggested.

Introduction: Radiofrequency Pulmonary Vein Isolation (RF-PVI) is an established treatment for Atrial Fibrillation (AF). Patients are administered Conscious Sedation (CS) or General Anaesthesia (GA) to minimise discomfort and patient movement during RF-PVI. There is a paucity of data on patient experiences of different modes of anaesthesia used during RF-PVI. The purpose of this study was to compare patient experiences of CS versus GA during RF-PVI Methods: A retrospective, observational, single-centre, single-operator study was performed, comparing patient experiences of RF-PVI performed under GA versus CS. A Likert scale questionnaire was used to compare modes of anaesthesia. The domains analysed were: (1) pain/discomfort during the procedure, (2) anxiety/depression post-procedure, (3) satisfaction with recovery time post-procedure, (4) Likelihood To Recommend (LTR) the procedure, (5) LTR mode of anaesthesia, (6) overall satisfaction with the ablation experience. Results: 41 patients were included - 20 in CS group, and 21 in GA group. Groups were well-matched. Patients in the GA group experienced lower levels of pain/discomfort (p<0.001) and were more likely to recommend the mode of anaesthesia (p<0.001), compared with those in CS group. Conclusion: Patients who had GA for RF-PVI experienced less peri-procedural pain than patients who had CS and were more likely to recommend GA as a mode of anaesthesia. This information has important implications for planning service delivery in centres performing AF ablation.

Confirming a genetic diagnosis of cystic fibrosis (CF) for clinically affected individuals should be more accessible today, with more laboratories offering testing and improved technologies at lower costs. Instead, diagnostic testing for CF has become more complex due to the variety of genetic testing options available for the one known causative gene ( CFTR). This article provides an overview of genetic tests currently available for CF in six laboratories in South Africa (SA). Also, it demonstrates the evolution of CF tests used at one private laboratory in the country via a ten-year retrospective audit. The findings of this study may serve as a guide for healthcare providers (HCPs) in selecting appropriate testing for CF diagnostic genetic confirmation. The choice of genetic test and methodology depends on individualised factors such as the ethnic origin of the patient, test availability, advantages and limitations, and cost. The ethnic diversity of SA’s populations and probable under-reporting of CF in the country makes the diagnosis of this relatively common genetic condition complex. The actual burden of CF in SA is unknown, and comprehensive genetic testing, with an ongoing compilation of patient data in the SA CF registry, should assist in addressing the genetic diversity of CF-causing variants.

The use of biodegradable mulch films in agriculture has gained considerable attention for their potential to reduce plastic pollution and mitigate the carbon footprint of crop production. This study evaluated the impact of biodegradable mulch film on soil microbial community structure, greenhouse gas emissions, and physicochemical properties in maize production. The results show that while current biodegradable mulch films, primarily composed of petroleum-based PBAT, have a higher carbon footprint compared to conventional PE films, their application leads to significant reductions in N₂O emissions. Furthermore, biodegradable mulch films induce shifts in soil microbial communities, particularly affecting the abundance of genes involved in carbon and nitrogen cycling. The metagenomic analysis reveals that these shifts favor microbial species and metabolic pathways linked to carbon sequestration and stabilization, resulting in lower CO₂ emissions relative to no-mulch conditions. These findings underscore the importance of optimizing biodegradable mulch film composition to enhance environmental benefits, offering valuable insights for the development of sustainable agricultural practices and contributing to climate change mitigation through improved mulching alternatives.

We present a novel methodology for analyzing electroencephalographic (EEG) event-related potentials (ERP) using massive univariate statistical methods combined with Bayesian inference. This data-driven approach automatically identifies clusters of electrodes and time windows showing potential effects, improving traditional methods that rely on a priori selection of regions of interest and null hypothesis significance testing (NHST). Our methodology addresses key limitations of NHST, including increased risk of type II errors and restrictive experimental design requirements. Through Bayesian inference, we evaluate and quantify the significance of the identified effects, providing a more flexible and interpretable framework for hypothesis testing. We applied this method to EEG data collected from ex-combatants, victims, and civilians involved in the Colombian armed conflict during a modified Implicit Association Test designed to measure implicit bias. Our approach demonstrated increased sensitivity compared to conventional NHST-based ERP analyses, with Bayesian inference offering robust evidence for group differences. This methodology enhances exploratory ERP research by mitigating issues related to multiple comparisons and integrating prior knowledge. It could also be applicable in experimental psychology and neuroscience studies where pre-selecting regions of interest is still challenging.

Water management in Chennai holds significance for urban sustainability, with sources such as Chembarambakkam Lake and Poondi Reservoir playing a major role in supplying water for the city. This indicates that drainage connectivity and its analysis are inadequate and lead to substantial flooding; thus, more segmentation and management of drainage pathways are needed to control water flow and intensity of flooding. This study examines Chennai as a case study using a 30m-resolution Digital Elevation Model derived from Shuttle Radar Topography Mission data to capture the region’s elevations. This research processes the Digital Elevation Model data through flow direction and accumulation analysis, generating a Topographic Wetness Index image. The Topographic Wetness Index image assists in improving the elevation data by reducing the elevation of the water bodies while increasing the land height surrounding the water bodies, which assists in defining the drainage network boundaries. To segment the drainage patterns in detail, the article utilizes a Vision Transformer that uses enhanced Topographic Wetness Index images for training and testing. The architecture of the Vision Transformer is such that the recognition of complex patterns is made possible, thereby making way for accurate segmentation and mapping of drainage networks. The model’s performance was successfully delineating and analyzing the drainage networks identified in Chennai, with a 98.64% accuracy for training and 98.94% for testing using Digital Elevation Model data. This thus shows the potent ability of the Vision Transformer as a tool for the hydrological studies of urban environments.

Hydrological niche specialization influences plant survival in hyperarid deserts by allowing species to access different water sources over spatial and temporal gradients. We examined the isotopic hydrological niches of Eriosyce cacti distributed across the arid to hyperarid regions of Atacama Desert. By analyzing stable isotopes (δ²H, δ¹⁸O) in root water, we identified primary water sources and assessed how geographic and morphological factors shape these plants’ strategies to persist under extreme conditions. We characterized the isotopic niche of 323 individuals from 62 populations of 39 Eriosyce species. Our results showed a wide isotopic range. Deuterium excess (D-excess), which indicates evaporation-related enrichment. Species with fibrous roots generally exhibited more negative D-excess, whereas those with tuberous or taproots were associated with more positive values. Coastal and central valley taxa tended showed higher D-excess, reflecting reliance on isotopically enriched fog, while Andean species had more negative values, indicating greater use of rainfall and snow sources. Among the studied taxa, E. aurata var. aurata displayed the broadest isotopic niche, indicating flexibility in exploiting multiple water sources across varying elevations and distances from the coast. In contrast, species such as E. limariensis and E. elquiensis were more narrowly restricted, relying predominantly on a single water source. Bayesian mixing models confirmed that fog dominated as the main water supply for most coastal and central valley species, whereas Andean populations received more substantial contributions from rainfall and snow. Geographic variables—longitude, altitude, and distance from the coast—significantly influenced D-excess, while latitude, aridity index, mean annual precipitation (rainfall), and root dimensions had less impact. These findings demonstrate that Eriosyce cacti employ diverse water-use strategies tailored to local environmental gradients, thereby enabling them to occupy hyperarid desert.

Sesuvium portulacastrum has the remarkable ability to substitute Na for K in its growing leaves, enabling osmotic functions without adverse effects. When subjected to high salt stress, the plant absorbs Na + through its roots and transports it to the leaf parenchyma cells, where it is compartmentalized and stored in vacuoles. Additionally, salt ions crystallize to preserve cell turgor. S. portulacastrum adapts to high salinity environments by accumulating substantial amounts of glycine betaine, which helps maintain the normal synthetic metabolic processes of its cells. Several plants that overexpress the BADH gene exhibit significant improvements in salt tolerance. The 3D structure of the SpBADH reveals that VTLELGGKSP and Cys are crucial for its catalytic activity, while Tyr-163, Trp-170, Trp-288, and Trp-459 contribute to structural stability. Tyr-163 and Trp-459 are also involved in substrate recognition and specific binding. Overexpression of SpBADH in yeast AXT3K and Escherichia coli enhances salt tolerance. Further research has shown that overexpressing SpBADH in Arabidopsis leads to increased GB accumulation, which promotes Na + efflux, enhances K + recruitment, and thereby reduces Na + toxicity to the roots. GB also protects chloroplast structure, boosts the activity of ROS scavenging enzymes, alleviates photoinhibition of PS I and PS II, and improves Arabidopsis’ adaptation to salt environments by regulating ion balance. Intriguingly, we have found that GB plays a regulatory role akin to plant hormones, regulating cell damage repair and growth and development in Arabidopsis. Consequently, introducing the GB biosynthesis pathway into plants or applying exogenous GB could be an effective strategy to enhance plant salt tolerance.

Teosintes, the wild relatives of maize, exhibit a wide ecogeographic distribution across Mexico and Central America, spanning starkly varying precipitation and temperatures. Understanding the genetic basis of teosinte’s adaptation to such conditions is crucial for its in situ conservation. We present findings from a study of 3,455 individuals across 276 teosinte populations, encompassing all known taxa except Zea vespertillio. Environmental and morphological data, along with genotype data comprising 33,929 SNPs, were analysed to elucidate the genetic population structure, ecological adaptation, and candidate genes associated with various climatic factors and phenotypic traits. Our results revealed distinct genetic and phenotypic adaptations within teosinte populations, shaped by the climate conditions of their habitats. Genome-wide association studies (GWAS) identified significant SNPs associated with morphological traits and environmental factors, elucidating adaptive mechanisms in teosinte evolution. Comparative analysis with maize literature on GWAS on SNPs found to be associated with agronomically important maize phenotypes highlighted both shared and unique genetic variants between teosinte and maize. Furthermore, protein function annotated to marker loci regions revealed the multifaceted nature of adaptive strategies in teosinte, indicating different potentially adaptive loci, even between populations growing in similar environmental conditions. Recognizing this diversity is important for teosinte conservation, as pointed out by new international frameworks, and for its management considering teosinte’s gene flow with maize, potential transgenic flow and the risk of new weeds emergence. Our research underscores the importance of studying the genetic diversity of crop wild relatives at the population level within centers of origin.

The vast global freshwater biodiversity hotspot Lake Baikal is located in a region with extremely cold winters and warm summers. Although conditions in winter with low water temperatures and relative scarcity of food may seem unfavorable for reproduction, Baikal is inhabited by a major endemic winter-reproducing amphipod species complex. We analyzed sex-specific seasonal proteome dynamics in a common representative species of this complex, Eulimnogammarus verrucosus, sampled in the field in fall, winter, and summer 2019/20. Especially female proteomes were dominated by sampling time point-specific hallmarks of reproduction-related processes and events, particularly related to formation of the eggs and embryo development. Proteome characteristics indicated that processes requiring the supply of external resources tend to take place at times of higher food availability before and after the winter: Thus, formation of the eggs in female E. verrucosus starts already in summer and juveniles hatch from eggs in spring; in winter, processes supplied by stored resources take place, such as embryo development in the egg fueled by the egg yolk. Adjustments of the amphipods of both sexes to environmental winter conditions were reflected by abundance changes of enzymes of the digestive system, indicating a response to seasonal diet changes, and of enzymes involved in RNA biosynthesis and protein folding, possibly related to decreasing water temperatures. The here analyzed proteomes reveal a strategy of a cold-adapted amphipod to deal with the unique and extreme environmental conditions of Baikal, directed to pace and timing of the resource depending, reproduction-related processes in relation to environmental parameters.

Ecosystem carbon sink play a crucial role in mitigating global climate change. Over the past two decades, the Yangtze River Delta (YRD) region has experienced rapid urbanization, significantly impacting its ecosystem carbon sink function. Using the Carnegie-Ames-Stanford Approach (CASA) model and soil respiration model, this study quantitatively assessed the total ecosystem carbon sink in the YRD region from 2000 to 2020, employing global Moran’s I, hotspot analysis, standard deviational ellipse, and Structural Equation Modeling (SEM) to analyze its spatiotemporal evolution and driving factors. The results revealed three key findings: (1) The total carbon sink in the YRD region increased from 70 million tons to 104 million tons between 2000 and 2020, with high-value areas primarily distributed in the mountainous and hilly regions of the southern and southwestern parts, while low-value areas concentrated in the eastern region, centered around Shanghai and its surrounding cities. (2) During this period, 68.45% of the region experienced enhanced carbon sink function, while 15.67% showed weakening, with the center of gravity shifting 24.4 km northwest. (3) The SEM model effectively explained the complex mechanisms influencing carbon sink function, identifying the normalized difference vegetation index (NDVI), proportion of forest land (PF), and proportion of built-up land (PBL) as key mediating variables. This study reveals the spatiotemporal evolution characteristics and complex influencing mechanisms of ecosystem carbon sink function in rapidly urbanizing areas, emphasizing the importance of strengthening ecological restoration and management. The findings provide valuable reference for balancing ecological conservation and economic development in the YRD region and other rapidly urbanizing areas globally.

REAL-LIFE INSIGHTS AND CLINICAL CHARACTERISTICS OF HEREDITARY ALPHA TRYPTASEMIA IN ANAPHYLACTIC PATIENTSAuthors: Loli-Ausejo D1,2,4*, Gonzalez-Matamala MF1,2*, Martí D3, Ruano-Zaragoza M1,2,4, Mir-Ihara P1,2,4, Solis-Ynga K1,2, Lara R3, Bartra J1,2,4, Pascal M2,3,4**, Muñoz-Cano R 1,2,4**1. Department of Allergy, Hospital Clinic Barcelona, Universitat de Barcelona (UB), Barcelona, Spain.2. Clinical and Experimental Respiratory Immunoallergy (IRCE), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.3. Department of Immunology, Hospital Clínic Barcelona, Universitat de Barcelona (UB), Barcelona, Spain.4. Redes de Investigación Cooperativa Orientadas a Resultados en Salud (RICORS), Red de Enfermedades Inflamatorias (REI), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.* Loli-Ausejo D and Gonzalez-Matamala MF contributed equally to this work** Pascal M and Muñoz-Cano R contributed equally to this workCorrespondance : rmunoz@clinic.cat

Background: Treatment of atrial fibrillation (AF) in horses is challenged by high recurrence rates, potentially driven by underlying myocardial changes or remodelling caused by AF itself. Understanding the molecular mechanisms behind these changes is crucial for developing new targeted therapies and improving treatment outcomes. Objectives: To characterize the cardiac transcriptome of healthy horses and explore the transcriptional changes associated with persistent AF. Study design: Case-control study. Methods: RNA-sequencing was performed on samples from all four heart chambers collected from six horses with naturally occurring persistent AF (lasting 2–12 weeks) and six healthy controls. Differential gene expression and pathway enrichment analyses were conducted to identify chamber specific differences and molecular pathways associated with AF. Findings were integrated with proteomic data and compared to transcriptional changes observed in tachypacing-induced AF. Atrial metabolic remodelling was further investigated by evaluating AMP-activated protein kinase (AMPK) activity and local glycogen content. Results: The transcriptomes of the four heart chambers had distinct molecular identities. Expression of ion channels and genes encoding calcium handling proteins were largely similar to humans, despite important differences in the ventricular expression of repolarizing potassium channels. Persistent AF was associated with minimal ion channel changes but significant upregulation of metabolic, fibrotic, and myofibrillar pathways. Metabolic remodelling included transcriptional upregulation of glycolytic pathways, increased glycogen content in the left atrium, and preserved AMPK activity in the right atrium. The transcriptomic profiles of persistent AF correlated well with those of tachypacing-induced AF. Main limitations: The study cannot distinguish changes predisposing to AF from those caused by it. Functional validation of ion channel currents was not performed. Conclusion: Persistent AF was associated with changes in metabolic and fibrotic pathways in the atria, with minimal ion channel remodelling. Targeting these pathways, rather than focusing solely on the electrical disturbance, may improve treatment outcomes in equine AF.

Obstructive sleep apnea (OSA) is a sleep condition characterized by the partial or full interruption of breathing while a person is asleep. Several techniques have been suggested for the automated recognition of OSA events. However, there has been little research on the prediction of these events using prior data, which is valuable for the advancement of medical devices that observe respiration while sleeping. In this research, we have proposed four techniques for forecasting OSA events by using a fusion of time-frequency representation (TFR) of electrocardiogram (ECG) signals and deep neural networks (Gabor-CNN, Wavelet-CNN, Wigner-CNN, and STFT-CNN). Overall, these techniques are called Predict-OSA. These techniques use raw single-lead ECG data collected at a sampling rate of 100 Hz without the inclusion of any manually extracted features. By analyzing the preceding 120 seconds of data, we can predict the occurrences of OSA (apnea) and regular breathing episodes in a lead time of 60 seconds. The findings obtained from analyzing a dataset consisting of more than 34270 60-second segments from 70 ECG recordings indicate that all four models had a high level of accuracy, surpassing 83%. The Wigner-CNN model demonstrated superior performance, achieving accuracy, specificity, and sensitivity of 89.75%, 91.89%, and 86.25%, respectively. The findings indicate that OSA occurrences may be reliably anticipated by analyzing single-lead ECG signals, which creates possibilities for designing devices that can prevent the incidence of OSA events from occurring during sleep. Our algorithms may be implemented in devices with limited storage space due to their ability to handle low sampling rates. This makes them well-suited for use in at-home environments.

The space-ground integrated network has the characteristics of open communication link, narrow bandwidth and limited satellite computing resources. Aiming at the problem that the existing authentication and key agreement (AKA) protocol can not meet the communication scenario of the space-ground integrated network, this paper analyzes the security performance requirements of the space-ground integrated network, and proposes a networking AKA protocol, including two stages of adjacent node networking AKA and cross-node networking AKA. In the phase of adjacent node networking AKA, the networking AKA are performed based on the ground AAS to generate inter-satellite authentication credentials. In the cross-node networking AKA stage, based on the authentication credentials generated by adjacent satellite authentication, the Chebyshev chaotic mapping technology is used to realize cross-node inter-satellite mutual authentication. Security and performance analysis show that our protocol has certain advantages in security, and improves the computation and communication efficiency to meet the lightweight requirements of the space-ground integrated network.

In natural environments, competition between species is a crucial factor for the survival or demise of populations. Therefore, understanding the mechanisms that promote species coexistence is crucial in community and evolutionary ecology. The Phylogenetic Limiting to Similarity Hypothesis (PLSH) posits that closely related species should experience greater competition due to niche conservatism, leading to higher overlap in resource use. However, studies have shown mixed results regarding the influence of phylogenetic distance and other abiotic and biotic factors on interspecific competition. This study explores the role of phylogenetic relatedness, body mass differences, and environmental factors such as primary productivity, in shaping trophic niche overlap among mesocarnivores across ten global biomes. Our extensive bibliographic review of more than 200 sources over nearly five decades suggests that while phylogenetic distance and body mass differences are significant predictors of niche overlap, environmental factors like primary productivity also play a crucial role. The findings highlight the complexity of species interactions, emphasizing that niche overlap is influenced by a combination of intrinsic and extrinsic factors. This study contributes to a deeper understanding of the dynamics governing species coexistence and the assembly of ecological communities.

Several studies have explored the linkages among biodiversity, ecosystem functions, and services; however, how biodiversity affects bundles of ecosystem services through collaboration and antagonism remains unknown, especially in ecologically fragile drylands. In this study, species-specific plant traits were extended to ecosystem services at the community level through transect sampling of shrublands in Northwest China using a trait-based approach. It revealed biodiversity-ecosystem service (ES) relationships in drylands and how environmental pressures (sites with high aridity, precipitation seasonality, and soil total salt) and human activities affect them. We found synergistic relationships among ESs at both the species and community levels, and environmental pressures and anthropogenic activities such as cotton cultivation and grazing are important drivers of ES decline at community level. However, environmental pressure did not reduce the alpha diversity such as species richness, Simpson, Shannon-Wiener, Margalef, and Pielou index of the shrublands, and the species richness of shrublands was decoupled from the ESs. Our findings highlight the vulnerability and sensitivity of drylands and show that rational human production activities are important for maintaining ESs in drylands.

Understanding how natural disturbance regimes drive biodiversity patterns is a major research challenge. Disturbances disrupt local communities by increasing population mortality and alter dispersal between communities. Yet, how species’ ecological strategies and disturbance regimes intertwine to shape the structure of metacommunities across space and time remains poorly understood. Drying river networks (DRNs) exemplify ecosystems structured by natural disturbances: drying events disrupt both local habitat within reaches and connectivity among flowing sections. Drying-wetting cycles thus alter two major mechanisms shaping metacommunity diversity: ecological drift and dispersal dynamics. In this study, we present a mechanistic metacommunity model that simulates species’ ability to withstand drying in place (resistance strategy) and to recolonize communities after rewetting (resilience strategy). Coupling this model with realistic hydrological models, we simulated community dynamics in four European DRNs encompassing variable flow intermittence regimes. Our aim was to investigate the relative importance of flow intermittence, network connectivity and species’ ecological strategies in shaping spatio-temporal biodiversity patterns. We show that higher connectivity increases reach-level α-diversity and decreases reach-level temporal β-diversity, whereas flow intermittence has the opposite effects. At the metacommunity scale, more intermittent DRNs exhibited low mean α-diversity and high spatial β-diversity, while DRNs with downstream drying exhibited high temporal β-diversity. Finally, we show that high levels of species drying resistance and dispersal counteract the effect of flow intermittence, leading to high mean α-diversity and low spatial and temporal β-diversities at the metacommunity scale. In contrast, maximal dispersal distance had complex, non-linear effects on spatial and temporal β-diversities, because dispersal amplifies both community stochasticity and biotic homogenisation. Altogether, our work emphasises how stochastic recolonisation of disturbed communities and biotic homogenisation interact with species resilience and resistance strategies to shape the spatio-temporal structure of biodiversity.

Mycorrhizal symbiont type is an important trait that differentiates tree species’ responses to their neighbours. In temperate forests, tree species associated with arbuscular mycorrhizae (AM) fungi tend to show reduced performance in conspecific relative to heterospecific neighbourhoods, while species associated with ectomycorrhizal (EcM) fungi do not suffer such negative effects from conspecific neighbours. However, our understanding of such mycorrhizae-mediated neighbourhood effects in tropical forests is limited. We address this knowledge gap through a shade house plant-soil feedback experiment and an observational field study of seedling dynamics within mixed dipterocarp (EcM host trees of family Dipterocarpaceae) forests of Sri Lanka. In the shade house, we transplanted 478 seedlings of three EcM host and two AM host species into conspecific- and heterospecific-trained soils and monitored their growth and survival over ~1.5 years. In the field, we tagged, identified, and measured seedlings in 576 seedling plots established within known adult neighbourhoods, and monitored growth and survival over two years beneath conspecific and heterospecific tree crowns. We found that the response of seedling growth and survival to neighbourhood (conspecific or heterospecific) depended on mycorrhizal symbiont type (AM or EcM) in the field, but not in the shade house, suggesting that above-ground enemies or input from leaf litter drive neighbourhood effects. AM host seedlings had lower growth and survival in conspecific vs. heterospecific neighbourhoods in the field, but the opposite pattern was observed for growth in the shade house. In contrast, growth and survival of EcM host seedlings did not vary with neighbourhood type in the field or shade house. These results support mycorrhizae-mediated neighbourhood effects in tropical mixed dipterocarp forests. The ability of EcM-host dipterocarp species to tolerate conspecific neighbours likely contributes to their dominance, whereas negative effects of conspecific neighbours may allow AM host seedlings to persist in enemy-free space beneath heterospecific adults.

As research advances, the number of study articles and researchers in diverse disciplines increases, emphasizing the importance of understanding their relationships. So the number of researchers is growing in the research community, and not only that research domain is also rising in a vast area. So our aim is to establish the nature of the researcher's connection. This article focuses on established relationship between Ph.D. advisors and advisees, which can be used to construct Academic Genealogy Trees and address future research challenges. The machine learning techniques will resolve the advisoradvisee relationship. In this article, five ML techniques, i.e., Decision Tree, SVM, Naive Bayes, Logistic Regression, and Random Forest for both cases advisor findings and advisee findings. In the experiment for advisor findings, Random Forest performs better than the other four models i.e. 95.4%., and advisee findings Logistic Regression performs better than the other four models i.e. 80.2%. Finally, compare our proposed model to the baseline, which is 11% better.

A document by Bibek Shrestha. Click on the document to view its contents.

Research has become increasingly reliant on software, serving as the driving force behind bioinformatics, high performance computing, physics, machine learning and artificial intelligence, to name a few. While progress has been made in advocating for the research software engineer, little attention has been placed on the workforce behind research infrastructure and innovation, namely compilers and compatibility tool development, orchestration and scheduling infrastructure, developer environments, container technologies, and workflow managers. As economic incentives are moving toward different models of cloud computing and innovation is required, the need for such a role is essential for the continued success of science. While scattered staff in non-traditional roles have found time to work on some facets of this space, the lack of a larger workforce and incentive to support it has led to the scientific community falling behind. In this article highlight the importance of this missing layer, providing examples of how a missing role of infrastructure engineer has led to inefficiencies in the interoperability, portability, and reproducibility of science. We suggest that an inability to allocate, provide resources for, and sustain individuals to work on these technologies could lead to possible futures that are sub-optimal for the continued success of our scientific communities.

Climate warming and anthropogenic activities have led to an increase in the prevalence of non-native plants in mountainous regions that previously exhibited limited occurrences. This phenomenon has resulted in detrimental effects on endemic plants and ecosystem functions. Yet, how traits of non-native plants that successfully spread to high elevation vary along the elevation gradient, as well as the underlying drivers of these changes, remain sparsely understood. In this study, we use Erigeron annuus, a cosmopolitan non-native plant that has invaded to high elevation, as our model to explore its individual biomass pattern along a 1900 m elevation gradient. We also contrast this pattern with the native Artemisia lavandulifolia, which has the same distribution range as E. annuus. We found that the biomass of E. annuus displayed a hump-shape pattern along elevation, while the biomass of native A. lavandulifolia gradually decreased with elevation. By evaluating the effect of climate variables, soil properties, rhizosphere fungal communities and its spatial mid-domain effect (i.e. geographic limitation) on plant biomass, we found that the biomass of E. annuus was primarily influenced by the spatial mid-domain effect, while the biomass of A. lavandulifolia resulted from a complex interplay of climatic variables and rhizosphere microbial communities. Our findings emphasize the importance of a spatial mid-domain effect on the growth of non-native E. annuus along elevation, indicating the impact of E. annuus probable be greatest at mid-elevations and thus, where management priority should be set. Further investigations considering more non-native plant species and species’ traits will allow to scrutinize this vision.

 IOT FOR KIDS