Experiencing Transformative Learning during Participatory Needs Assessment of a Public School: Journeys and Arrivals to Relational Ontology(ies)

This paper discusses experiences from school-based needs assessment within a Participatory Action Research (PAR) project aimed at facilitating quality education in public schools of rural Nepal. Being often a first stage in the process of research-action, Participatory Needs Assessment (PNA) offers space for community members’ perceptions and attitudes toward their collective needs. In this light, this paper takes evidence from the first and the second authors’ Ph.D. experiences, under the supervision of the third and the fourth authors to initiate PNA of a school. Also, incorporating the reflections from the fifth author as a critical friend, it observes the political, epistemological, ethical, and methodological challenges of doing such assessments; the challenges of involving all the stakeholders in identifying problems, and the transformative possibilities the approach inherently brings within it. On the whole, the paper reflects how, despite manifold conflicting interests of the multi-group stakeholders, relational ontology(ies) emerged in the cyclical and spiral process

Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam.

The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years

Selective area epitaxy of ultra-high density InGaN quantum dots by diblock copolymer lithography

Highly uniform InGaN-based quantum dots (QDs) grown on a nanopatterned dielectric layer defined by self-assembled diblock copolymer were performed by metal-organic chemical vapor deposition. The cylindrical-shaped nanopatterns were created on SiNx layers deposited on a GaN template, which provided the nanopatterning for the epitaxy of ultra-high density QD with uniform size and distribution. Scanning electron microscopy and atomic force microscopy measurements were conducted to investigate the QDs morphology. The InGaN/GaN QDs with density up to 8 × 1010 cm-2 are realized, which represents ultra-high dot density for highly uniform and well-controlled, nitride-based QDs, with QD diameter of approximately 22-25 nm. The photoluminescence (PL) studies indicated the importance of NH3 annealing and GaN spacer layer growth for improving the PL intensity of the SiNx-treated GaN surface, to achieve high optical-quality QDs applicable for photonics devices

A hybrid MBE-based growth method for large-area synthesis of stacked hexagonal boron nitride/graphene heterostructures

Van der Waals heterostructures combining hexagonal boron nitride (h-BN) and graphene offer many potential advantages, but remain difficult to produce as continuous films over large areas. In particular, the growth of h-BN on graphene has proven to be challenging due to the inertness of the graphene surface. Here we exploit a scalable molecular beam epitaxy based method to allow both the h-BN and graphene to form in a stacked heterostructure in the favorable growth environment provided by a Ni(111) substrate. This involves first saturating a Ni film on MgO(111) with C, growing h-BN on the exposed metal surface, and precipitating the C back to the h-BN/Ni interface to form graphene. The resulting laterally continuous heterostructure is composed of a top layer of few-layer thick h-BN on an intermediate few-layer thick graphene, lying on top of Ni/MgO(111). Examinations by synchrotron-based grazing incidence diffraction, X-ray photoemission spectroscopy, and UV-Raman spectroscopy reveal that while the h-BN is relaxed, the lattice constant of graphene is significantly reduced, likely due to nitrogen doping. These results illustrate a different pathway for the production of h-BN/graphene heterostructures, and open a new perspective for the large-area preparation of heterosystems combining graphene and other 2D or 3D materials

Testing a global standard for quantifying species recovery and assessing conservation impact

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Prevalence and risk factors of post-traumatic stress disorders among the survivors of 2015 Nepal earthquake, in Dhading, Nepal

Background: Nepal is considered to be the 11th most earthquake prone country in the world. On Saturday, 25 April2015 an earthquake of magnitude 7.9 on Richter scale struck in Barpak of central Nepal. It results over 8,790 casualties and 22,300 injuries. Mental health disturbances, especially post-traumatic stress disorders are major public health issues arising in the aftermath of such natural disasters of higher intensity. Aim of this study was to investigate the prevalence of posttraumatic stress disorders (PTSD) and perceived social support, their risk factors and relationship of PTSD to perceived social support among survivors of the Barpak earthquake in Dhading District, Nepal. Methods: Cross sectional study was conducted among the five hundred and thirty-five survivors from the rural Dhading District. A conjoint study tool had been administered for evaluating Post traumatic stress disorders and perceived social support by using the PTSD Checklist-Civilian Version (PCL-C) questionnaire and Oslo Social Support Scale. Univariate analysis was done for the description of sample characteristics. Chi-square test was done to establish the association between predictors and outcome variable of interest. Further, binary regression model was used to adjust the confounders. Results: The prevalence of PTSD among survivors was 18.5%. Significant risk factors of PTSD included gender (females 26.31%, males 11.80%), age (18–35 years 10.85%, 36–59 years 23.89%, ≥60 years 45.09), lost their job or income generating activities of the family(60%). Approximately 62 percent of PTSD was attributable for low social support. Multivariate logistic regression showed that females, older people, lost of job, difficulty in communication were significantly more likely to develop PTSD. Prevalence of the low social support was found to be 25.2%. Conclusions: Posttraumatic stress symptoms remained relatively common among survivors nine month after Barpak earthquake. It is important to provide psychological aid and social support for survivors to decrease health burden from PTSD, especially for females, old age survivors and those who lost their job and income generation activities

PD CONTROLLER BASED UNMANNED SHIP NAVIGATION

For the improvement of the performance of track keeping of unmanned water vehicle numerous ship models, wave disturbances models and distinct control algorithms has been proposed. Researchers are using variants of PID controllers, Adaptive controllers and Predictive controllers for accurate trajectory control. Being simpler in nature still PID controller are popular in control domain. In this paper we have implemented PD based controller for trajectory control of unmanned vehicle considering all standard models of sea disturbances. Analysis of result obtained using PD control proved that path tracking is more accurate than open loop controller in terms of computation time, complexity and fuel consumptio

Assessment of ‘hen and chicken’ disorder for marketable yield estimates of table grape using the ‘Berry Analysis Tool’

Walsh, KB ORCiD: 0000-0002-3033-8622Bunch and berry size are important quality criteria for table grapes, and bunch weight is used in estimation of vine yield. The Berry Analysis Tool (BAT), a machine vision technique, was trialled for use in estimation of berry count, diameter and weight, to support estimates of ‘hen and chicken’ disorder and vineyard yield. Berries were spread on a plate for imaging. BAT estimates achieved a r2 = 0.99 on berry number per bunch, r2 = 0.98 on average berry minor axis and r2 = 0.99 on bunch weight. Based on an allometric relationship between lineal dimensions and weight, these attributes were used to estimate the proportion of under-size (‘chicken’) berries per bunch, and bunch weight. The estimated bunch weight multiplied by a number bunches per vine provides an estimation of vine yield. Use of the BAT as a decision support tool in table grape farm management is described.Associated Grant:Australia Awar