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Climate Driven Trends in Historical Extreme Low Streamflows on Four Continents
Get PDFUnderstanding temporal trends in low streamflows is important for water management and ecosystems. This work focuses on trends in the occurrence rate of extreme low‐flow events (5‐ to 100‐yearreturn periods) for pooled groups of stations. We use data from 1,184 minimally altered catchments in Europe,North and South America, and Australia to discern historical climate‐driven trends in extreme low flows (1976–2015 and 1946–2015). The understanding of low streamflows is complicated by different hydrological regimes in cold, transitional, and warm regions. We use a novel classification to define low‐flow regimes using air temperature and monthly low‐flow frequency. Trends in the annual occurrence rate of extreme low‐flow events(proportion of pooled stations each year) were assessed for each regime. Most regimes on multiple continents did not have significant (p < 0.05) trends in the occurrence rate of extreme low streamflows from 1976 to 2015;however, occurrence rates for the cold‐season low‐flow regime in North America were found to be significantly decreasing for low return‐period events. In contrast, there were statistically significant increases for this period in warm regions of NA which were associated with the variation in the Pacific Decadal Oscillation. Significant decreases in extreme low‐flow occurrence rates were dominant from 1946 to 2015 in Europe and NA for both cold‐ and warm‐season low‐flow regimes; there were also some non‐significant trends. The difference in the results between the shorter (40‐year) and longer (70‐year) records and between low‐flow regimes highlights the complexities of low‐flow response to changing climatic condition
Cognitive engagement with AI‐enabled technologies and value creation in healthcare
Get PDFDespite the potential for artificial intelligence (AI)-enabled technologies in healthcare, their benefits are limited owing to the numerous challenges of cognitive engagement. This research paper explores the factors of “cognitive engagement with AI-enabled technologies” and its impact on the customers' benefits and value creation. A mixed-method study was utilized in the Indian health-care setup where AI-based technology is developing. The qualitative findings shed light on the factors of cognitive engagement with AI-enabled technologies. Grounded on the theories of customer benefit, an integrative framework of customer-perceived financial, experiential, psychological, and functional benefits, alongside perceived instrumental and terminal values, was developed. The quantitative findings of PLS-SEM explain the dynamics of the patients' cognitive engagement with AI-enabled technologies. The results enrich a more nuanced understanding of how the patient benefits of AI applications have different impacts on perceived value. The study concludes with theoretical and practical implications
Draft genome sequence of the fungal biocontrol agent, Bacillus velezensis Kos
Get PDFHere, we report the draft genome sequence of Bacillus velezensis strain Kos,isolated from casing soil used during Agaricus bisporus cultivation in Dublin, Ireland. B.velezensis Kos exhibits a suppressive ability toward Cladobotryum mycophilum, Trichoderma aggressivum, and Lecanicillium fungicola, which are common threats to A. bisporusproduction, cultivation, and quality
Learning from innovative staff practices that led to virtual disability services using the lens of Complex Adaptive Systems
Get PDFthis paper draws on a complex adaptive systems lens to develop an understanding of the staff practices that sup-ported the development of Virtual Disability services in ireland amid the cOViD-19 pandemic. the study involved twelve interviews with service providers, which were anal-ysed using Reflexive thematic analysis, leading to two over-arching themes. the first theme focuses on the logistics of constructing the response. this includes dynamic adaptive-ness, technological readiness, a positive attitude towards technology, resource availability, digital skills, and the level of take-up. the second theme centres on the enacted response, which encompasses sensemaking, developing technological expertise, managing upward, fostering creative innovation, cultivating a systems sensibility, and creating conditions for psychological safety and authentic engagement. We conclude that staff practices are key for creating conditions conducive to safe spaces, sustaining well-being, and reshaping power dynamics and emphasise the impor-=tance of embracing technology as a tool for innovation within complex operating environments
SynchroLINNce: Toolbox for Neural Synchronization and Desynchronization Assessment in Epilepsy Animal Models
Get PDFEpilepsy is a worldwide public health issue, given its biological, social, and economic impacts. Considering several open questions about synchronization and desynchronization mechanisms underlying epileptic phenomena, the development of algorithms and computational toolboxes for such analysis is highly relevant to their research. Moreover, given the recent developments of neurotechnology for epilepsy, it is essential to understand that proposals like computational tools may provide consistent data for closed-loop control systems, necessary in neuromodulation treatment alternatives, and for real-time monitoring systems to predict the occurrence of epileptic seizures. In the present work, SynchroLINNce, a freely distributable MATLAB toolbox designed to be used by epilepsy neuroscientists, including software-untrained), is proposed. Among its features, several functionalities such as recording visualization, digital filtering, and correlation analysis, as well as more specific methodologies, such as mechanisms for the automatic detection of epileptiform spikes, morphology analysis of these spikes, and their coincidence between channels are presented
Guest Editorial. Interdisciplinary Approaches for Human Cognition: Expanding Perspectives on the Mind
Get PDFThe abstract is included in the text
Investigating the Impact of Encoder Architectures and Batch Size on Depth Estimation through Semantic Consistency
Get PDFTraditional methods for depth estimation rely on supervised learning with resource-intensive LiDAR data. Virtual synthetic datasets provide a cost-effective alternative, but bridging the domain gap between synthetic and real-world data remains a significant challenge. In existing work, this gap is addressed through domain adaptation techniques, aligning the feature distributions of synthetic (source) and real-world (target) domains. Our study explores the efficacy of different encoder architectures (ResNet variants with 35, 50, 101, 101-with-attention, and 152 convolution layers) and two batch sizes (2 and 4) for the depth estimation task. Our experiments show that ResNet101 without and with attention mechanisms provide the best performance across 2 and 4 batch sizes, respectively, compared to the other models. Conversely, the deeper architecture considered, ResNet152, shows the lowest performance, indicating that increasing the network depth does not necessarily lead to improved results for depth estimation tasks. This study's findings provide valuable insights for developing more effective depth estimation algorithms, and it suggests future directions in hyperparameter optimization and semantic consistency modeling
Temperature-Induced Conversion of 2D Vanadium-Doped MoSe 2 Nanosheets to 1D V 2 MoO 8 Rods: Enhanced Performance in Electrochemical Antibiotic Detection in Biological and Environmental Samples
Get PDFIn this work, new strategies were developed to
prepare 1D-V2MoO8 (VMO) rods from 2D V-doped MoSe2
nanosheets (VMoSe2) with good control over morphology and
crystallinity by a facile hydrothermal and calcination process. The
morphological changes from 2D to 1D rods were controlled by
changing the calcination temperature from 300 to 600 °C. The
elimination of Se and the incorporation of O into the V−Mo
structure were evaluated by TGA, p-XRD, Raman, FE-SEM, EDAX,
FE-TEM, and XPS analyses. These results prove that the
optimization of the physical parameters leads to changes in the
crystal phase and textural properties of the prepared material. The
VMoSe2 and its calcined products were investigated as electrochemical sensors for the detection of the antibacterial drug
nitrofurantoin (NFT). At a calcination temperature of 500 °C, the modified screen-printed carbon electrodes (SPCE) proved to
be an excellent electrochemical sensor for the detection of NFT in neutral media. Under the optimized conditions, VMO-500 °C/
SPCE exhibits low detection limit (LOD) (0.015 μM), wide linear ranges (0.1−31, 47−1802 μM), good sensitivity, and selectivity.
The proposed sensor was successfully used for the analysis of NFT in real samples with good recovery results. Moreover, the
reduction potential of NFT agreed well with the theoretical analysis using quantum chemical calculations, with the B3LYP with 6-
31G(d,p) basis set predicting an E0 value of −0.45 V. The interaction between the electrode surface and NFT via the LUMO
diagram and the electrostatic potential surface is also discusse
A Tutorial-Cum-Survey on Percolation Theory With Applications in Large-Scale Wireless Networks
Get PDFConnectivity is an important key performance indicator and a focal point of research in large-scale wireless
networks. Due to path-loss attenuation of electromagnetic waves,
direct wireless connectivity is limited to proximate devices.
Nevertheless, connectivity among distant devices can still be
attained through a sequence of consecutive multi-hop communication links, which enables routing and disseminating
legitimate information across wireless ad hoc networks. Multihop connectivity is also foundational for data aggregation in the
Internet of things (IoT) and cyberphysical systems (CPS). On the
downside, multi-hop wireless transmissions increase susceptibility
to eavesdropping and enable malicious network attacks. Hence,
security-aware network connectivity is required to maintain
communication privacy, detect and isolate malicious devices,
and thwart the spreading of illegitimate traffic (e.g., viruses,
worms, falsified data, illegitimate control, etc.). In 5G and beyond
networks, an intricate balance between connectivity, privacy, and
security is a necessity due to the proliferating IoT and CPS, which
are featured with massive number of wireless devices that can
directly communicate together (e.g., device-to-device, machine-tomachine, and vehicle-to-vehicle communication). In this regards,
graph theory represents a foundational mathematical tool to
model the network physical topology. In particular, random geometric graphs (RGGs) capture the inherently random locations
and wireless interconnections among the spatially distributed
devices. Percolation theory is then utilized to characterize
and control distant multi-hop connectivity on network graphs.
Recently, percolation theory over RGGs has been widely utilized
to study connectivity, privacy, and security of several types of
wireless networks. The impact and utilization of percolation
theory are expected to further increase in the IoT/CPS era, which
motivates this tutorial. Towards this end, we first introduce the
preliminaries of graph and percolation theories in the context
of wireless networks. Next, we overview and explain their
application to various types of wireless networks
Relational Perspective in Breastfeeding Research
Get PDFIn a recent Lactations Newsmakers interview with Professor Fiona Dykes, we talked about the importance of the relational perspective in breastfeeding research, the underlying subject of most of both of our ethnographic research on breastfeeding (Cassidy & Dykes, 2019; Cassidy & El Tom, 2014; Dykes, 2006). This commentary offers a detailed perspective on the topic of relational perspective in breastfeeding research, particularly from the lens of the social and cultural sciences, through the use of ethnographic methods, which has long been argued to be the study of relations (Murdock, 1941). As this commentary will detail, the so-called “relational turn” in the social sciences engages some of the most prominent minds (Simmel, 1908), and has great potential for the future of breastfeeding research (Säilävaara, 2023). We begin by discussing some of the meanings associated with relational ethnographic perspective, and then turn our discussion to how the relational perspective can help to study the complex social and cultural issues underlying breastfeeding