Managing housing needs in post conflict housing reconstruction in Sri Lanka: gaps versus recommendations

Addressing housing needs in post conflict housing reconstruction leads to successful housing reconstruction. As part of a study of investigating how the housing needs can be effectively addressed in post conflict housing reconstruction, this paper identifies the gaps in managing housing needs in post conflict housing reconstruction within the context of Sri Lanka and presents the recommendations to minimise such gaps. Data was collected through un-structured interviews conducted with 37 participants, comprising policy makers, practitioners, academics and beneficiaries who engaged in post conflict housing reconstruction in Sri Lanka. Gaps were mainly found in conflict sensitivity, measures related to physical housing, performance of implementing agencies, policy and practice issues. On the job training, application of ‘do no harm’ principles, enhanced beneficiary participation, enhanced accountability, effective monitoring, enhanced knowledge sharing, adequate drinking water facilities, irrigation development and initiatives for material manufacturing were suggested as recommendations to minimise these gaps. Identification of gaps in managing housing needs in post conflict housing reconstruction and recommendations to minimise them inform policy makers to address the housing needs effectively through incorporating these aspects into the related policies. This in turn enhances the sustainability in housing development after conflicts

Beta defensin-2 is reduced in central but not in distal airways of smoker COPD patients

Background: Altered pulmonary defenses in chronic obstructive pulmonary disease (COPD) may promote distal airways bacterial colonization. The expression/activation of Toll Like receptors (TLR) and beta 2 defensin (HBD2) release by epithelial cells crucially affect pulmonary defence mechanisms. Methods: The epithelial expression of TLR4 and of HBD2 was assessed in surgical specimens from current smokers COPD (s-COPD; n = 17), ex-smokers COPD (ex-s-COPD; n = 8), smokers without COPD (S; n = 12), and from non-smoker non-COPD subjects (C; n = 13). Results: In distal airways, s-COPD highly expressed TLR4 and HBD2. In central airways, S and s-COPD showed increased TLR4 expression. Lower HBD2 expression was observed in central airways of s-COPD when compared to S and to ex-s-COPD. s-COPD had a reduced HBD2 gene expression as demonstrated by real-time PCR on micro-dissected bronchial epithelial cells. Furthermore, HBD2 expression positively correlated with FEV1/FVC ratio and inversely correlated with the cigarette smoke exposure. In a bronchial epithelial cell line (16 HBE) IL-1β significantly induced the HBD2 mRNA expression and cigarette smoke extracts significantly counteracted this IL-1 mediated effect reducing both the activation of NFkB pathway and the interaction between NFkB and HBD2 promoter. Conclusions: This study provides new insights on the possible mechanisms involved in the alteration of innate immunity mechanisms in COPD. © 2012 Pace et al

Pathological and ecological host consequences of infection by an introduced fish parasite

The infection consequences of the introduced cestode fish parasite Bothriocephalus acheilognathi were studied in a cohort of wild, young-of-the-year common carp Cyprinus carpio that lacked co-evolution with the parasite. Within the cohort, parasite prevalence was 42% and parasite burdens were up to 12% body weight. Pathological changes within the intestinal tract of parasitized carp included distension of the gut wall, epithelial compression and degeneration, pressure necrosis and varied inflammatory changes. These were most pronounced in regions containing the largest proportion of mature proglottids. Although the body lengths of parasitized and non-parasitized fish were not significantly different, parasitized fish were of lower body condition and reduced weight compared to non-parasitized conspecifics. Stable isotope analysis (δ15N and δ13C) revealed trophic impacts associated with infection, particularly for δ15N where values for parasitized fish were significantly reduced as their parasite burden increased. In a controlled aquarium environment where the fish were fed ad libitum on an identical food source, there was no significant difference in values of δ15N and δ13C between parasitized and non-parasitized fish. The growth consequences remained, however, with parasitized fish growing significantly slower than non-parasitized fish, with their feeding rate (items s−1) also significantly lower. Thus, infection by an introduced parasite had multiple pathological, ecological and trophic impacts on a host with no experience of the parasite

Leaf segmentation in plant phenotyping: a collation study

Image-based plant phenotyping is a growing application area of computer vision in agriculture. A key task is the segmentation of all individual leaves in images. Here we focus on the most common rosette model plants, Arabidopsis and young tobacco. Although leaves do share appearance and shape characteristics, the presence of occlusions and variability in leaf shape and pose, as well as imaging conditions, render this problem challenging. The aim of this paper is to compare several leaf segmentation solutions on a unique and first-of-its-kind dataset containing images from typical phenotyping experiments. In particular, we report and discuss methods and findings of a collection of submissions for the first Leaf Segmentation Challenge of the Computer Vision Problems in Plant Phenotyping workshop in 2014. Four methods are presented: three segment leaves by processing the distance transform in an unsupervised fashion, and the other via optimal template selection and Chamfer matching. Overall, we find that although separating plant from background can be accomplished with satisfactory accuracy (>>90 % Dice score), individual leaf segmentation and counting remain challenging when leaves overlap. Additionally, accuracy is lower for younger leaves. We find also that variability in datasets does affect outcomes. Our findings motivate further investigations and development of specialized algorithms for this particular application, and that challenges of this form are ideally suited for advancing the state of the art. Data are publicly available (online at http://​www.​plant-phenotyping.​org/​datasets) to support future challenges beyond segmentation within this application domain

A method for automatic segmentation and splitting of hyperspectral images of raspberry plants collected in field conditions

Abstract Hyperspectral imaging is a technology that can be used to monitor plant responses to stress. Hyperspectral images have a full spectrum for each pixel in the image, 400–2500 nm in this case, giving detailed information about the spectral reflectance of the plant. Although this technology has been used in laboratory-based controlled lighting conditions for early detection of plant disease, the transfer of such technology to imaging plants in field conditions presents a number of challenges. These include problems caused by varying light levels and difficulties of separating the target plant from its background. Here we present an automated method that has been developed to segment raspberry plants from the background using a selected spectral ratio combined with edge detection. Graph theory was used to minimise a cost function to detect the continuous boundary between uninteresting plants and the area of interest. The method includes automatic detection of a known reflectance tile which was kept constantly within the field of view for all image scans. A method to split images containing rows of multiple raspberry plants into individual plants was also developed. Validation was carried out by comparison of plant height and density measurements with manually scored values. A reasonable correlation was found between these manual scores and measurements taken from the images (r2 = 0.75 for plant height). These preliminary steps are an essential requirement before detailed spectral analysis of the plants can be achieved

Sull’attuazione degli obblighi internazionali di risposta e ripresa a fronte della pandemia di Covid-19: una prospettiva italiana

This work aims at offering a critical analysis of how Italy, as one of the most early-affected countries, has responded to and is currently recovering from the Covid-19 pandemic, in the framework of international and European obligations applicable to CBRN events at large. To this end, this article will first examine the main obligations concerning «response» to and «recovery» from a pandemic event, as stemming from relevant international and European law instruments. Then, it will look at how these obligations have been implemented by Italian central and local authorities vis-à-vis the Covid-19 pandemic, while also offering some conclusive remarks on the legal meaning of the «disaster management cycle»

Stereotype and skew: Quantifying gender bias in pre-trained and fine-tuned language models

This paper proposes two intuitive metrics, skew and stereotype, that quantify and analyse the gender bias present in contextual language models when tackling the WinoBias pronoun resolution task. We find evidence that gender stereotype correlates approximately negatively with gender skew in out-of-the-box models, suggesting that there is a trade-off between these two forms of bias. We investigate two methods to mitigate bias. The first approach is an online method which is effective at removing skew at the expense of stereotype. The second, inspired by previous work on ELMo, involves the fine-tuning of BERT using an augmented gender-balanced dataset. We show that this reduces both skew and stereotype relative to its unaugmented fine-tuned counterpart. However, we find that existing gender bias benchmarks do not fully probe professional bias as pronoun resolution may be obfuscated by cross-correlations from other manifestations of gender prejudice. Our code is available online

Impact of uniaxial strain and doping on oxygen diffusion in CeO2

Doped ceria is an important electrolyte for solid oxide fuel cell applications. Molecular dynamics simulations have been used to investigate the impact of uniaxial strain along the directions and rare-earth doping (Yb, Er, Ho, Dy, Gd, Sm, Nd, and La) on oxygen diffusion. We introduce a new potential model that is able to describe the thermal expansion and elastic properties of ceria to give excellent agreement with experimental data. We calculate the activation energy of oxygen migration in the temperature range 900-1900K for both unstrained and rare-earth doped ceria systems under tensile strain. Uniaxial strain has a considerable effect in lowering the activation energies of oxygen migration. A more pronounced increase in oxygen diffusivities is predicted at the lower end of the temperature range for all the dopants considered