Faktor yang Berhubungan dengan Berhubungan dengan Kejadian Sindrom Photokeratitis pada Pekerja Las Listrik di Kelurahan Romang Polong Kecamatan Somba Opu Kabupaten Gowa

Photokeratitis merupakan injury mata yang sering mengakibatkan hilangnya kemampuan melihat, setidaknya setengah dari semua kejadian kecelakaan dan kesakitan yang pernah terjadi (Mcguire C, 2011). Berdasarkan potensi terjadinya sindrom photokeratitis, perlu dilakukan uji hubungan untuk melihat faktor apa saja yang berhubungan dengan sindrom photokeratitis. Hasil penelitian dengan uji analisis bivariat, diperoleh faktor umur tidak berhubungan dengan kejadian sindrom photokeratitis, namun faktor lama pajanan, radiasi sinar UV, jarak pengelasan dan penggunaan APD berhubungan dengan dengan kejadian sindrom photokeratitis. Hubungan umur dengan kejadian sindrom photokeratitis p=0.71, hubungan lama pajanan dengan kejadian sindrom photokeratitis p=0.00, hubungan radiasi sinar UV dengan kejadian sindrom photokeratitis p=0.00, hubungan jarak pengelasan dengan kejadian sindrom photokeratitis p=0.00, dan hubungan penggunaan APD dengan kejadian sindrom photokeratitis p=0,00. Adapun saran yang menjadi rekomendasi pada pihak industri yakni memberikan pengetahuan tentang cara mengelas yang aman, penerapan SOP yang jelas untuk area bengkel pengelasan, dan melakukan pengawasan pada pekerja yang tidak menggunakan alat pelindung diri serta memperhatikan jarak pengelasan sesuai standar yag ditetapkan

Does land use and landscape contribute to self-harm? A sustainability cities framework

Self-harm has become one of the leading causes of mortality in developed countries. The overall rate for suicide in Canada is 11.3 per 100,000 according to Statistics Canada in 2015. Between 2000 and 2007 the lowest rates of suicide in Canada were in Ontario, one of the most urbanized regions in Canada. However, the interaction between land use, landscape and self-harm has not been significantly studied for urban cores. It is thus of relevance to understand the impacts of land-use and landscape on suicidal behavior. This paper takes a spatial analytical approach to assess the occurrence of self-harm along one of the densest urban cores in the country: Toronto. Individual self-harm data was gathered by the National Ambulatory Care System (NACRS) and geocoded into census tract divisions. Toronto’s urban landscape is quantified at spatial level through the calculation of its land use at di erent levels: (i) land use type, (ii) sprawl metrics relating to (a) dispersion and (b) sprawl/mix incidence; (iii) fragmentation metrics of (a) urban fragmentation and (b) density and (iv) demographics of (a) income and (b) age. A stepwise regression is built to understand the most influential factors leading to self-harm from this selection generating an explanatory model.This research was supported by the Canadian Institutes of Health Research Strategic Team Grant in Applied Injury Research # TIR-103946 and the Ontario Neurotrauma Foundation grantinfo:eu-repo/semantics/publishedVersio

Stimulating implementation of sustainable development goals and conservation action:Predicting future land use/cover change in Virunga national park, Congo

The United Nations 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDG’s) presents a roadmap and a concerted platform of action towards achieving sustainable and inclusive development, leaving no one behind, while preventing environmental degradation and loss of natural resources. However, population growth, increased urbanisation, deforestation, and rapid economic development has decidedly modified the surface of the earth, resulting in dramatic land cover changes, which continue to cause significant degradation of environmental attributes. In order to reshape policies and management frameworks conforming to the objectives of the SDG’s, it is paramount to understand the driving mechanisms of land use changes and determine future patterns of change. This study aims to assess and quantify future land cover changes in Virunga National Park in the Democratic Republic of the Congo by simulating a future landscape for the SDG target year of 2030 in order to provide evidence to support data-driven decision-making processes conforming to the requirements of the SDG’s. The study follows six sequential steps: (a) creation of three land cover maps from 2010, 2015 and 2019 derived from satellite images; (b) land change analysis by cross-tabulation of land cover maps; (c) submodel creation and identification of explanatory variables and dataset creation for each variable; (d) calculation of transition potentials of major transitions within the case study area using machine learning algorithms; (e) change quantification and prediction using Markov chain analysis; and (f) prediction of a 2030 land cover. The model was successfully able to simulate future land cover and land use changes and the dynamics conclude that agricultural expansion and urban development is expected to significantly reduce Virunga’s forest and open land areas in the next 11 years. Accessibility in terms of landscape topography and proximity to existing human activities are concluded to be primary drivers of these changes. Drawing on these conclusions, the discussion provides recommendations and reflections on how the predicted future land cover changes can be used to support and underpin policy frameworks towards achieving the SDG’s and the 2030 Agenda for Sustainable Development

Deep Learning for Detecting and Classifying Ocean Objects:Application of YoloV3 for Iceberg–Ship Discrimination

Synthetic aperture radar (SAR) plays a remarkable role in ocean surveillance, with capabilities of detecting oil spills, icebergs, and marine traffic both at daytime and at night, regardless of clouds and extreme weather conditions. The detection of ocean objects using SAR relies on well-established methods, mostly adaptive thresholding algorithms. In most waters, the dominant ocean objects are ships, whereas in arctic waters the vast majority of objects are icebergs drifting in the ocean and can be mistaken for ships in terms of navigation and ocean surveillance. Since these objects can look very much alike in SAR images, the determination of what objects actually are still relies on manual detection and human interpretation. With the increasing interest in the arctic regions for marine transportation, it is crucial to develop novel approaches for automatic monitoring of the traffic in these waters with satellite data. Hence, this study aims at proposing a deep learning model based on YoloV3 for discriminating icebergs and ships, which could be used for mapping ocean objects ahead of a journey. Using dual-polarization Sentinel-1 data, we pilot-tested our approach on a case study in Greenland. Our findings reveal that our approach is capable of training a deep learning model with reliable detection accuracy. Our methodical approach along with the choice of data and classifiers can be of great importance to climate change researchers, shipping industries and biodiversity analysts. The main difficulties were faced in the creation of training data in the Arctic waters and we concluded that future work must focus on issues regarding training data

The Law-in-Action of the International Criminal Court

As the International Criminal Court (ICC) moves from an exhilarating idea to a carefully negotiated document and finally to an operational institution, the cogency of its conception will be tested by the manifold realities of international politics, not the least of which will be the practical and financial limits those realities may place upon investigation and prosecution. The drafters of the Rome Statute benefited from important previous experiments-the Nuremberg Tribunal and the International Criminal Tribunals for the Former Yugoslavia and for Rwanda. But once the Court is launched, the predecessors and prototypes that were so helpful in the drafting stages will be of less and less assistance. The ICC must operate in a substantially different context than the earlier efforts, and the problems it will encounter (and already is encountering) will be different from and may prove more formidable than those facing its prototypes

Tunable True-Time Delay Operation in A Dispersion-Engineered Few-Mode Fiber

[EN] We present a simple few-mode fiber design as a promising platform to implement tunable sampled true-time delay lines for radiofrequency signal processing. To the best of our knowledge, this is the first few-mode fiber ever reported featuring evenly spaced incremental dispersion values, which is an essential characteristic required for tunable operation of microwave photonics applications. The performance of the designed five-sample true-time delay line is theoretically validated in the context of microwave signal filtering, demonstrating free spectral range continuous tunability from 12.4 up to 57 GHz.This work is supported by the European Research Council (ERC) under Consolidator Grant Project 724663, and Ramon y Cajal fellowship RYC-2014-16247 for I. Gasulla.Nazemosadat-Arsanjani, SB.; Gasulla Mestre, I. (2020). Tunable True-Time Delay Operation in A Dispersion-Engineered Few-Mode Fiber. IEEE. 203-206. https://doi.org/10.23919/MWP48676.2020.9314392S20320

Mode-division multiplexing for microwave signal processing

[EN] We present an overview of different mode-division multiplexing fiber technologies engineered to provide tunable microwave signal processing, including signal filtering and optical beamforming for phased-array antennas. The exploitation of both the space and wavelength dimensions brings advantages in terms of increased compactness, flexibility and versatility.This research was supported by the ERC Consolidator Grant ERC-COG-2016 InnoSpace 724663 and the Spanish MINECO fellowship RYC-2014- 16247 for I. Gasulla.Nazemosadat-Arsanjani, SB.; Gasulla Mestre, I. (2021). Mode-division multiplexing for microwave signal processing. IEEE. 1-2. https://doi.org/10.1109/SUM48717.2021.95058021

Crowdsourced-based mapping of historical west-to-east routes from the textual accounts of European Travelers

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Through the centuries, numerous travellers and orientalists visited Persia (Iran) and described the country and its inhabitants in their travel writings. These travel accounts comprise valuable historical information about the people and their traditions. A literature on travel writings indicate that surprisingly, despite the importance of these recordings, the studies related to the different aspects of these travels, such as the travel routes and the varieties of the possible application of them on the modern time are relatively scarce. The current research deals with the travel routes of nine the most famous early modern European explorers. Accordingly, in addition to digitalizing and mapping the taken routes, the dynamics of their itineraries are analysed

Technical Guidelines to Extract and Analyze VGI from Different Platforms

An increasing number of Volunteered Geographic Information (VGI) and social media platforms have been continuously growing in size, which have provided massive georeferenced data in many forms including textual information, photographs, and geoinformation. These georeferenced data have either been actively contributed (e.g., adding data to OpenStreetMap (OSM) or Mapillary) or collected in a more passive fashion by enabling geolocation whilst using an online platform (e.g., Twitter, Instagram, or Flickr). The benefit of scraping and streaming these data in stand-alone applications is evident, however, it is difficult for many users to script and scrape the diverse types of these data. On 14 June 2016, a pre-conference workshop at the AGILE 2016 conference in Helsinki, Finland was held. The workshop was called “LINK-VGI: LINKing and analyzing VGI across different platforms”. The workshop provided an opportunity for interested researchers to share ideas and findings on cross-platform data contributions. One portion of the workshop was dedicated to a hands-on session. In this session, the basics of spatial data access through selected Application Programming Interfaces (APIs) and the extraction of summary statistics of the results were illustrated. This paper presents the content of the hands-on session including the scripts and guidelines for extracting VGI data. Researchers, planners, and interested end-users can benefit from this paper for developing their own application for any region of the world

Dispersion-tailored few-mode fiber design for tunable microwave photonic signal processing

[EN] We present a novel double-clad step-index few-mode fiber that operates as a five-sampled tunable true-time delay line. The unique feature of this design lies in its particular modal chromatic dispersion behavior, which varies in constant incremental steps among adjacent groups of modes. This property, which to the best of our knowledge has not been reported in any other few-mode fiber to date, is the key to tunable operation of radiofrequency signal processing functionalities implemented in few-mode fibers. The performance of the designed true-time delay line is theoretically evaluated for two different microwave photonics applications, namely tunable signal filtering and optical beamforming networks for phased array antennas. In the 35-nm optical wavelength tuning range of the C-band, the free spectral range of the microwave filter and the beam-pointing angle in the phased array antenna can be continuously tuned from 12.4 up to 57 GHz and 12.6 degrees up to 90 degrees, respectively.European Research Council (Consolidator Grant Project 724663); Ministerio de Ciencia, Innovacion y Universidades (Ramon y Cajal fellowship RYC-2014-16247).Nazemosadat-Arsanjani, SB.; Gasulla Mestre, I. (2020). Dispersion-tailored few-mode fiber design for tunable microwave photonic signal processing. Optics Express. 28(24):37015-37025. https://doi.org/10.1364/OE.412830S3701537025282