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Effect of elevation on soil quality under bamboo (Bambusa teres Buch.-Ham. ex Munro) stands outside forest areas in Eastern Nepal
No full textBamboo dynamics in non-forest areas remain relatively underexplored, despite over 50 % of the global bamboo population being found in degraded, marginal or agricultural lands outside forests. To address this, we investigated soil quality dynamics under isolated bamboo stands (Bambusa teres) across three elevation regions: lower (0–400 m), middle (400–800 m), and higher (800–1200 m) in Katari, Udayapur, Nepal. Stratified sampling, followed by purposive sampling, was used to account for elevation variation and bamboo's scattered distribution. A total of thirty 100 m2 circular plots (10 per elevation stratum) were sampled at two soil depths (0–15 cm and 15–30 cm) to assess soil quality, using various indicators based on published literature from Nepal. At middle elevation, organic carbon, nitrogen and potassium were significantly higher at 0–15 cm, while phosphorus and pH were higher at 15–30 cm (p ≤ 0.05). A fair soil quality rating (SQI: 0.48 –0.57) was observed in the study area. Elevation significantly (p ≤ 0.05) affected SQI at 0 –15 cm depth, with higher SQI at middle elevation (0.57) and lower SQI at lower elevation (0.48). For effective bamboo management and land-use planning, it is important to consider elevation-specific zoning. Middle and higher elevations should be prioritized for bamboo plantations, incorporating management activities and agroforestry integration to enhance soil productivity. Further studies with larger samples and broader geographic coverage, incorporating additional soil indicators and environmental variables is recommended
Catching the wisps: Stellar mass-loss limits from low-frequency radio observations
No full textThe winds of low-mass stars carry away angular momentum and impact the atmospheres of surrounding planets. Determining the properties of these winds is necessary to understand the mass-loss history of the star and the evolution of exoplanetary atmospheres. Due to their tenuous nature, the winds of low-mass main-sequence stars are difficult to detect. The few existing techniques for measuring these winds are indirect, with the most common inference method for winds of low-mass stars being astrospheric Lyman-α absorption combined with complex hydrodynamical modelling of the interaction between the stellar wind and the interstellar medium. Here, we employ a more direct method to place upper limits on the mass-loss rates of low-mass stars by combining observations of low-frequency coherent radio emission, the lack of free-free absorption, and a simple stellar wind model. We determine upper limits on the mass-loss rate for a sample of 19 M dwarf stars detected with the LOFAR telescope at 120−168 MHz, reaching a sensitivity within an order of magnitude of the solar mass-loss rate for cold stars with a surface magnetic field strength of ∼100 G. The sensitivity of our method does not depend on distance or spectral type, allowing us to find mass-loss rate constraints for stars up to spectral type M6 and out to a distance of 50 pc, later and farther than previous measurements. With upcoming low-frequency surveys with both LOFAR and the Square Kilometre Array, the number of stars with mass-loss rate upper limits determined with this method could reach ∼1000
Enhancing Food Security Through Home Gardening: A Case Study in Phoukhoud District, Lao PDR
Full text linkFood insecurity is a global challenge, particularly affecting developing nations. This study evaluated the role of home gardens in addressing food security in rural upland regions of Laos among three different types of vulnerable households. To address this objective, household survey data of project baseline 2019 (n = 504), midterm in 2021 (n = 425), and final 2022 (n = 435) were analyzed and tested. Additionally, focus group discussion (n = 3) and key informant interviews (n = 42) were carried out to gain deeper insights and triangulate and supplement household survey findings. The study found a 21% drop in food insecurity from 2019 to 2022, mainly due to a 12% increase in the number of home gardens, boosting crop production and harvests. We also found that dietary habits significantly improved between 2019 and 2022, with minimum diet diversity rising to 41% for three types of vulnerable households: 62% for female-headed households, 41% for households with disabilities, and 67% for other households. While there has been an improvement among different types of vulnerable households, about 15% of them still faced severe food shortages as of 2022. However, food insecurity among the three predetermined categories reveals significant disparities. Female-headed households experienced the most severe food insecurity and showed the least progress between 2019 and 2022. Additionally, we compared crop and diet diversity and various food insecurity coping methods across different time periods among these three vulnerable households. We provide several recommendations for targeted interventions and policies to address the remaining food security challenges in rural upland areas, ultimately contributing towards reducing global food insecurity
Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications
Full text linkSolid-state quantum emitters, molecular-sized complexes releasing a single photon at a time, have garnered much attention owing to their use as a key building block in various quantum technologies. Among these, quantum emitters in hexagonal boron nitride (hBN) have emerged as front runners with superior attributes compared to other competing platforms. These attributes are attainable thanks to the robust, two-dimensional (2D) lattice of the material formed by the extremely strong B─N bonds. This review discusses the fundamental properties of quantum emitters in hBN and highlights recent progress in the field. The focus is on the fabrication and engineering of these quantum emitters facilitated by state-of-the-art equipment. Strategies to integrate the quantum emitters with dielectric and plasmonic cavities to enhance their optical properties are summarized. The latest developments in new classes of spin-active defects, their predicted structural configurations, and the proposed suitable quantum applications are examined. Despite the current challenges, quantum emitters in hBN have steadily become a promising platform for applications in quantum information science
Designing an information technology-enabled framework in the retail service ecosystem
Full text linkDespite the significant importance of service innovation in a value-centered retail environment, less is explored regarding its conceptualization through firms' information technology (IT) based strategic capabilities to promote the value formation process in a retail service ecosystem. To address this gap, this study aims to develop an integrated framework based on the concepts of service-dominant logic and resource advantage theory. By conducting 24 in-depth interviews (12 with employees and 12 with customers) across various non-fuel retail stores commonly referred to as tuck shops, this study highlights the significant role of firms' strategic IT-enabled capabilities in enhancing service process innovation and customer service. These IT capabilities, combined with service process innovation and customer service, not only create opportunities for value co-creation through resource exchange (value-in-exchange) but also enable customers to create value through individual service consumption (value-in-use). The findings further suggest co-creation experience within the retail ecosystem is shaped by customers' emotional involvement, role projection, and escapism, which collectively determine their value-in-experience. Finally, the proposed framework offers valuable implications for practitioners, emphasizing the need to design more integrative IT-enabled platforms to achieve improved customer value outcomes
A novel uncertainty-aware liquid neural network for noise-resilient time series forecasting and classification
No full textWhile Liquid Neural Networks (LNN) are promising for modeling dynamic systems, there is no internal mechanism that quantifies the uncertainty of a prediction. This can produce overly confident outputs, especially when operating in noisy or uncertain environments. One potential issue that might be highlighted with LNNs is that their highly flexible connectivity leads to overfitting on the training data. This is targeted by the present work, which introduces the uncertainty-aware LNN framework, the UA-LNN, by considering Monte Carlo dropout for quantifying the uncertainty of LNNs. The proposed UA-LNN enhances the stochasticity of both training and inference, hence allowing for more reliable predictions by modeling output uncertainty. We applied the UA-LNN in the two tasks of time series forecasting and multi-class classification, where we showed its performance on a wide range of datasets and under different noise conditions. The proposed UA-LNN has shown the best results, outperforming the benchmarks of standard LNN, Long Short-Term Memory (LSTM) and Multilayer Perceptron (MLP) models in terms of R2, RMSE, and MAE consistently. Additionally, for performance metrics such as accuracy, precision, recall, and F1 score, the results showed improvement over LSTM and MLP models in multi-classification tasks. More importantly, under heavy noise, the UA-LNN maintained superior performance, while demonstrating enhanced classification capabilities across many datasets with challenging tasks, such as arrhythmia detection and cancer classification
Unravelling the Antibiotic Resistance: Molecular Insights and Combating Therapies
No full textAntibiotics, the full-stop of invasive bacteria, have been used in clinical setups from unthreatening fever to massive challenging therapies. Constant dependency on medication upsurges the evasion of microbes from antibiotics contemporarily along with ecological footprint. Thus, the infested pathogen became resilient to antibiotics, disguised as multidrug-resistant bacteria (MDR), pandrug-resistant bacteria (PDR), and extensively drug-resistant bacteria (XDR). The etymology of genetic modifications and horizontal gene transfer played an external influence on the arising resurgence. Also, intrinsic parameters, such as antibiotic efflux pumps and the formation of biofilms, encouraged intense resistance to antibiotic drugs. This aggravated resistance in microbes builds up resistome in the environment due to selective pressure; thereby drastic devastation of people suffering from disastrous diseases is mournful. Since novelite approaches for broad-spectrum antibiotics against drug resistance microbes are grueling challenges in these crucial times. This scientific study has come up with neoteric methodologies to elude immediate consequences and health hazards. Inculcating ancestral treatment towards pharmacognosy as adjuvants to the prevailing hi-fi nanotechnology, phage and algal therapy, genome mining, and bioinformatics databases are the optimizing inventions for actual and prospective living
A Crisis of Identity: A Collage of Emerging Scholars in the Crucible of Academe
Full text linkThis collaborative autoethnography (CAE) is presented in the form of a collage, rendered as an assemblage of co-constructed autoethnographic reflections, juxtaposed with poems, illustrations, and multivocal analyses that draw on Butlerian performativity, queer temporalities, and interpretive disability studies. Identifying as ‘differently abled’, we explore how our respective cognitive impairments and shared situatedness as mature-aged, ex-professional, non-economically productive ‘students’ have informed our identity development within the neoliberal academe. Responding to Amy Kilgard’s call for further theorisation of the embodied activity of collage-making, we invite readers to engage in shared meaning-making as we explore the methodological intersection of disability, queer temporality, and identity precariousness
The perceptions parents of dyslexic children have on barriers to meaningful parent–school partnerships in Australia
Full text linkThe relationship between schools and parents has evolved over recent years and is now recognized as a valuable and bi-directional partnership in the educative process. This partnership is of particular significance for parents with a dyslexic child, playing a vital role in ensuring success within the school and beyond. Using a unique conceptual lens of parental allyship, this paper reports on an investigation that employed semi-structured interviews to investigate the experiences of ten Australian parents of dyslexic children and the actions they undertook to meet their child’s needs within the school. Using qualitative content analysis, we explored the nature and impact of these experiences on both the parents and the parent–school partnership. Findings indicate that parents develop a level of expertise in their allyship to their child and this expertise is not always welcomed by the school. In addition, parents perceived interpersonal and systemic barriers that hindered both the parent–school partnership and the support provided to their dyslexic child. The paper contributes unique insights into the perspectives of parents on how parent–school policy is enacted at a school level, and raises consideration for a greater focus on parent–school partnerships for the future educational success of dyslexic children