Development of a Framework for Local Governments to Enhance Adaptive Capacity to Climate Change

Climate change presents a fundamental challenge for Local Government functions, including land use and development, coastal management, community health and safety, waste disposal and recycling, and emergency management. Local Government Authorities (LGAs) have a vital role to play in identifying, planning and implementing effective and timely adaptation actions that can reduce the vulnerabilities of their systems and services. Many LGAs in Australia, with support from the Commonwealth Government, undertook climate change risk assessments and developed adaptation plans during 2008-2010. However, it appears that many of these plans have not been taken to the implementation stage. Studies suggest that this is predominantly because local governments face a range of barriers that prevent them from implementing adaptation responses. This research aimed to address some of these issues. There were four main aims: firstly to identify the barriers for local governments to implement Climate Change Adaptation (CCA) measures; secondly to examine the existing capacity of LGAs to implement CCA and identify the opportunities to improve their adaptive capacity; thirdly to understand the comparative advantages and disadvantages of responding to adaptation individually and in collaboration with other LGAs; and finally to identify and present the key elements of a framework that local governments can use to incorporate CCA into their mainstream planning and operations. The research was based on a qualitative study, which involved review of a large body of literature, to identify the best practices of local governments in relation to responding to the impacts of climate change; collection of information, through a questionnaire survey, from local governments in Australia, about status, challenges and opportunities to incorporate climate change adaptation in mainstream planning and operations; analysis of the responses using content analysis; stakeholder workshops to discuss and identify the key elements of the framework; and trialling the draft framework to validate the effectiveness and appropriateness of the framework in LGAs. Barriers that inhibit LGAs from implementing their adaptation plans have been identified. These include a lack of understanding of climate change risks and the need for adaptation; lack of capacity to develop and implement adaptation measures; limitations posed by the existing governance systems; and a lack of ability to determine the local impacts of climate change. The investigation of the existing capacity of local governments suggests that there is a need to implement well-structured and on-going awareness and capacity development programs for both council staff and the community, which should be specifically tailored for target groups to appropriately convey the messages. The research suggests that while there are both advantages and disadvantages in implementing adaptation measures individually and in partnerships, it is often more effective to work in collaboration, as it can provide economies-of-scale, benefit from an increased knowledge base, and present a stronger voice to influence policy development. Finally, the key elements of a framework have been presented to help LGAs improve their adaptive capacity to climate change. These include guidelines on six major areas of LGA activities – communications, governance, planning, networking, funding and implementation. The framework has been validated for its effectiveness and usability in a local government context and is expected to be suitable for use by LGAs in Australia as well as other countries with similar socio-political structures

Response of germination and seedling growth to soil particle size of three herbaceous perennials on alpine zone of Mt. Fuji

Polygonum cuspidatum, P. weyrichii and Artemisia pedunculosa are herbaceous perennials in the alpine zone on Mt. Fuji. The effect of soil particle size on seed germination and seedling growth of these species was investigated. In the experiment three different particle size soils (large particle size LPS, medium particle size MPS, and small particle size SPS) were used. The other experiment was designed under three different watering intervals (every day, every two days, and every four days). Soil particle size had a great impact on seed germination and seedling growth. The highest percentage of seeds germinated in SPS and lowest in LPS soil, irrespective of the species. In the case of A. pedunculosa there was no significant difference of seed germination between SPS and MPS soils. However, the other two species had significantly reduced percentages of seed germination with increasing soil particle size. The maximum root length of seedlings was significantly longer in LPS and MPS compared to the SPS soil group, for all species. The number of root tips was increased with decreasing soil particle size, irrespective of the species. Further, larger aboveground biomass was found in seedlings of SPS than those of LPS and MPS. A. pedunculosa showed a slightly different pattern of seed germination and seedling growth compared to the two Polygonum species. Seed germination of A. pedunculosa was comparatively independent of soil particle size, and it may have conservative water use strategy. On the other hand, seed germination of Polygonum species was highly affected by the soil particle size, and those species may adapt to the water deficit condition by taking up water from deeper soil

An efficient plasmonic photovoltaic structure using silicon strip-loaded geometry

We show that a silicon thin-film photovoltaic structure with silicon strips on the top and grooves on the silver back contact layer can absorb incident solar energy over a broad spectral range. The silicon strips on the top scatter the incident light and significantly help couple to the photonic modes in the smaller wavelength range. The grooves on the silver back contact layer both scatter the incident light and help couple to the photonic modes and resonant surface plasmon polaritons. We find an increase of ∼46% in total integrated solar absorption in the proposed strip-loaded structure compared to that in a planar thin film structure of same dimensions. The proposed structure offers simpler fabrication compared to similar plasmonic-inspired designs

Sulfur and nitrogen removal of model fuel using activated carbon derived from oil palm shell

This research was done to understand the suitability and effectiveness of oil palm shells (OPS) as low cost adsorbents via physically activation with carbon dioxide (CO2) as an adsorbent for desulphurization and denitrogenation of a model fuel under different concentration. Batch mode experiments were conducted to study the effects concentration of Benzothiophine, Quinoline and Indole. Activated carbon (AC) was prepared at three different activation temperatures (500°C, 600°C, and 700°C), which was characterized with Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (mR), and a mercury intrusion porosimeter. After adsorption, the solution was analysed with a Gas Chromatography (GC). Equilibrium adsorption isotherms and kinetics were investigated. The experimental data were analysed by the Langmuir and Freundlich models of adsorption. The adsorption isotherm data were fitted well to Langmuir isotherm and the most adsorption capacity on the best suited AC for Benzothiophene, Quinoline, and Indole were 3.64 mg/g, 4.19 mg/g and 2.98 mg/g respectively. The rates of adsorption were 0.19409 h-1, 0.08411 h-1, and 0.02883 h-1 for the adsorption of Benzothiophene, Quinoline, and Indole respectively. The kinetic data obtained at different concentrations have been analysed using a pseudo-first-order, pseudo-second-order equation and intraparticle diffusion equation. The pseudo-first­order model best described the sorption process and was employed in predicting the rate constant, equilibrium sorption capacity as well

A Deep Learning Study on Osteosarcoma Detection from Histological Images

In the U.S, 5-10\% of new pediatric cases of cancer are primary bone tumors. The most common type of primary malignant bone tumor is osteosarcoma. The intention of the present work is to improve the detection and diagnosis of osteosarcoma using computer-aided detection (CAD) and diagnosis (CADx). Such tools as convolutional neural networks (CNNs) can significantly decrease the surgeon's workload and make a better prognosis of patient conditions. CNNs need to be trained on a large amount of data in order to achieve a more trustworthy performance. In this study, transfer learning techniques, pre-trained CNNs, are adapted to a public dataset on osteosarcoma histological images to detect necrotic images from non-necrotic and healthy tissues. First, the dataset was preprocessed, and different classifications are applied. Then, Transfer learning models including VGG19 and Inception V3 are used and trained on Whole Slide Images (WSI) with no patches, to improve the accuracy of the outputs. Finally, the models are applied to different classification problems, including binary and multi-class classifiers. Experimental results show that the accuracy of the VGG19 has the highest, 96\%, performance amongst all binary classes and multiclass classification. Our fine-tuned model demonstrates state-of-the-art performance on detecting malignancy of Osteosarcoma based on histologic images

Planting time and mulching effect on onion development and seed production

A field experiment was conducted to evaluate effects of planting time and mulches on bulb growth and seed production of onion (Allium cepa L.) cv. Taherpuri. Planting time and mulches had significant influence on almost all parameters studied. Onion planted on 21 November had better agronomic traits contributing towards yield formation. Growth and seed production was accelerated by black polythene. Seed yield (460.81 kgha-1) was highest in the plots planted on 21 Nov. Seed yield was 529.06 kgha-1 where black polythene mulch was used

A Mobile App for Wound Localization using Deep Learning

We present an automated wound localizer from 2D wound and ulcer images by using deep neural network, as the first step towards building an automated and complete wound diagnostic system. The wound localizer has been developed by using YOLOv3 model, which is then turned into an iOS mobile application. The developed localizer can detect the wound and its surrounding tissues and isolate the localized wounded region from images, which would be very helpful for future processing such as wound segmentation and classification due to the removal of unnecessary regions from wound images. For Mobile App development with video processing, a lighter version of YOLOv3 named tiny-YOLOv3 has been used. The model is trained and tested on our own image dataset in collaboration with AZH Wound and Vascular Center, Milwaukee, Wisconsin. The YOLOv3 model is compared with SSD model, showing that YOLOv3 gives a mAP value of 93.9%, which is much better than the SSD model (86.4%). The robustness and reliability of these models are also tested on a publicly available dataset named Medetec and shows a very good performance as well.Comment: 8 pages, 5 figures, 1 tabl

Removal of chlorinated phenol from aqueous solution utilizing activated carbon derived from papaya (carica papaya) seeds

Activated carbons (ACs) were prepared from papaya seeds with different dry weight impregnation ratios of zinc chloride (ZnCl2) to papaya seeds by using a two-stage self-generated atmosphere method. The papaya seeds were first semi-carbonized in a muffle furnace at 300 oC for 1 h and then impregnated with ZnCl2 before activation at 500 oC for 2 h. Several physical and chemical characteristics such as moisture, ash, pH, functional groups, morphological structure and porosity of prepared ACs were studied and presented here. AC2, with the impregnation ration of 1 : 2 (papaya seeds: ZnCl2), yielded a product that had the highest adsorption capacity, 91.75%, achieved after 180min contact time. The maximum Brunauer, Emmett and Teller (BET) surface area of AC2 was 546m2/g. Adsorption studies indicated that AC2 complied well with the Langmuir isotherm (qm=39.683mg g-1) and the pseudo-second-order (qe=29.36mg g-1). This indicated that chemisorption was the primary adsorption method for AC2. The intraparticle diffusion model proved that the mechanism of adsorption was separated into two stages: the instantaneous stage and the gradual adsorption stage. Overall, this work demonstrated the suitability of using papaya seeds as a precursor to manufacture activated carbon

Recovery and characterization of used lubricating oil using acid with two different adsorbents

This study is a form of experimental analysis that utilizes used lubricating oil (ULO) in order to reclaim base oil by using a combination of acetic acid and two different adsorbents namely aluminum oxide (Al2O3) and river sand (RS). The two different adsorbents were used to compare for better quality of oil using the same method. The characterization of the recovered ULO samples was conducted by using Fourier-transform infrared spectroscopy (FTIR) and the viscosity was tested by using the viscometer. Based on the results obtained, the Al2O3 seems to be a better adsorbent than RS in several tests such as density, sludge removal and viscosity. For better viscosity and mass of sludge values, the Al2O3 adsorbent is more suitable compared to the RS. It was found that by using Al2O3, there is a 26% viscosity reduction for ULO samples. By using RS, 6.67% viscosity reduction was found for ULO samples. 24.9% and 25.7% of sludge removal was found in ULO samples by Al2O3 and RS, respectively. FTIR analysis showed that before treatment oxidative compounds such as alkens and helides were present in the ULO and UEO samples. However, after treatment by both of the adsorbents, the oxidative compounds were removed. The removal of the alkenes and alkyl halides has evidently indicated the treatment was able to remove the oxidative compounds in the oil

Possible ability of bovine follicular fluid to attract migrating bull spermatozoa

AimTo examine the potential of bovine follicular fluid (BFF) to attract bull spermatozoa. MethodsThe ability of the BFF to attract bull sperm was evaluated by observing changes in sperm migration after being placed in a cross-column chamber. The movement parameters of the heads and flagella of the sperm that were attracted to the BFF were analyzed by using the Computer Assisted Sperm Analysis system. ResultsIt was observed that 61.6% of the bull sperm migrated toward the BFF when the BFF was used at a concentration of 0.1%, but 67.2% of the sperm did not migrate toward the BFF at a concentration of 10%. Relatively larger numbers of both precapacitated and postcapacitated bull sperm migrated toward the BFF (0.1%). The ability of the 0.1% BFF to attract sperm probably affected both the normal artificial insemination (AI) fertility sperm and the poor AI fertility spermatozoa. The flagellar curvilinear ratio of the sperm winding to the 0.1% BFF was significantly higher than that of the prewinding sperm. ConclusionThese results could suggest that BFF potentially attracts bull sperm at a certain concentration, irrespective of the capacitation status of the sperm. Although the mechanism by which this attraction occurs remains unclear, these data imply that it could be related to BFF-dependent changes in the sperm flagellar curvilinear ratio.ArticleREPRODUCTIVE MEDICINE AND BIOLOGY.16(2):133-138(2017)journal articl