PROBABILISTIC MODELING OF RAINFALL INDUCED LANDSLIDE HAZARD ASSESSMENT IN SAN JUAN LA LAGUNA, SOLOLÁ, GUATEMALA

The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.

Social Networks Analysis

This morning Dr. Risser will introduce you to the basic ideas of social network analysis. You will learn some history behind the study of social networks. Dr. Risser will introduce you to mathematical measures of social networks including centrality measures and measures of spread and cohesion. You will also learn how to use a computer program to analyze social network data

Graft coronary vasculopathy in cardiac transplantation--evaluation of risk factors by multivariate analysis

The development of coronary vasculopathy is the main determinant of long-term survival in cardiac transplantation. The identification of risk factors, therefore, seems necessary in order to identify possible treatment strategies. Ninety-five out of 397 patients, undergoing orthotopic cardiac transplantation from 10/1985 to 10/1992 were evaluated retrospectively on the basis of perioperative and postoperative variables including age, sex, diagnosis, previous operations, renal function, cholesterol levels, dosage of immunosuppressive drugs (cyclosporin A, azathioprine, steroids), incidence of rejection, treatment with calcium channel blockers at 3, 6, 12, and 18 months postoperatively. Coronary vasculopathy was assessed by annual angiography at 1 and 2 years postoperatively. After univariate analysis, data were evaluated by stepwise multiple logistic regression analysis. Coronary vasculopathy was assessed in 15 patients at 1 (16%), and in 23 patients (24%) at 2, years. On multivariate analysis, previous operations and the incidence of rejections were identified as significant risk factors (P < 0.05), whereas the underlying diagnosis had borderline significance (P = 0.058) for the development of graft coronary vasculopathy. In contrast, all other variables were not significant in our subset of patients investigated. We therefore conclude that the development of coronary vasculopathy in cardiac transplant patients mainly depends on the rejection process itself, aside from patient-dependent factors. Therapeutic measures, such as the administration of calcium channel blockers and regulation of lipid disorders, may therefore only reduce the progress of native atherosclerotic disease in the posttransplant setting.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Chinese Internet language: A sociolinguistic analysis of adaptations of the Chinese writing system

This paper examines the adaptations of the writing system in Internet language in mainland China from a sociolinguistic perspective. A comparison is also made of the adaptations in mainland China with those that Su (2003) found in Taiwan. In Computer-Mediated Communication (CMC), writing systems are often adapted to compensate for their inherent inadequacies (such as difficulty in input). Su (2003) investigates the creative uses of the writing system on the electronic bulletin boards (BBS) of two college student organizations in Taipei, Taiwan, and identifies four popular and creative uses of the Chinese writing system: stylized English, stylized Taiwanese-accented Mandarin, stylized Taiwanese, and the recycling of a transliteration alphabet used in elementary education. According to Coupland (2001; cited in Su 2003), stylization is “the knowing deployment of culturally familiar styles and identities that are marked as deviating from those predictably associated with the current speaking context”. Within this framework and drawing on the data in previous publications on Internet language and online sources, this study identifies five types of adaptations in mainland China’s Internet language: stylized Mandarin (e.g., 漂漂 piāopiāo for 漂亮 ‘beautiful’), stylized dialect-accented Mandarin (e.g., 灰常 huīcháng for 非常 ‘very much’), stylized English (e.g., 伊妹儿 yīmèier for ‘email’), stylized initials (e.g., bt 变态 biàntài for ‘abnormal’; pk, short form for ‘player kill’), and stylized numbers (e.g., 9494 jiùshi jiùshi 就是就是 ‘that is it’). The Internet community is composed of highly mobile individuals and thus forms a weak-tie social network. According to Milroy and Milroy (1992), a social network with weak ties is often where language innovation takes place. Adaptations of the Chinese writing system in Internet language provide interesting evidence for the innovations within a weak-tie social network. Our comparison of adaptations in mainland China and Taiwan shows that, in maximizing the effectiveness and functionality of their communication, participants of Internet communication are confronted with different language resources and situations, including differences in Romanization systems, English proficiency level, and attitudes towards English usage. As argued by Milroy and Milroy (1992), a weak-tie social network model can bridge the social class and social network. In the Internet community, the degree of diversity of the stylized linguistic varieties indexes the virtual and/or social status of its participants: the more diversified one’s Internet language is, the higher is his/her virtual and/or social status.

Antiplatelets versus Anticoagulants for the Treatment of Cervical Artery Dissection: Bayesian Meta-Analysis

OBJECTIVE To compare the effects of antiplatelets and anticoagulants on stroke and death in patients with acute cervical artery dissection. DESIGN Systematic review with Bayesian meta-analysis. DATA SOURCES The reviewers searched MEDLINE and EMBASE from inception to November 2012, checked reference lists, and contacted authors. STUDY SELECTION Studies were eligible if they were randomised, quasi-randomised or observational comparisons of antiplatelets and anticoagulants in patients with cervical artery dissection. DATA EXTRACTION Data were extracted by one reviewer and checked by another. Bayesian techniques were used to appropriately account for studies with scarce event data and imbalances in the size of comparison groups. DATA SYNTHESIS Thirty-seven studies (1991 patients) were included. We found no randomised trial. The primary analysis revealed a large treatment effect in favour of antiplatelets for preventing the primary composite outcome of ischaemic stroke, intracranial haemorrhage or death within the first 3 months after treatment initiation (relative risk 0.32, 95% credibility interval 0.12 to 0.63), while the degree of between-study heterogeneity was moderate (τ(2) = 0.18). In an analysis restricted to studies of higher methodological quality, the possible advantage of antiplatelets over anticoagulants was less obvious than in the main analysis (relative risk 0.73, 95% credibility interval 0.17 to 2.30). CONCLUSION In view of these results and the safety advantages, easier usage and lower cost of antiplatelets, we conclude that antiplatelets should be given precedence over anticoagulants as a first line treatment in patients with cervical artery dissection unless results of an adequately powered randomised trial suggest the opposite.

3G network traffic sources measurement and analysis

In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows. Copyright © 2013 John Wiley & Sons, Ltd.

Sparse computation for large-scale binary classification

Well-known data mining algorithms rely on inputs in the form of pairwise similarities between objects. For large datasets it is computationally impossible to perform all pairwise comparisons. We therefore propose a novel approach that uses approximate Principal Component Analysis to efficiently identify groups of similar objects. The effectiveness of the approach is demonstrated in the context of binary classification using the supervised normalized cut as a classifier. For large datasets from the UCI repository, the approach significantly improves run times with minimal loss in accuracy.

Choosing and using diversity indices: insights for ecological applications from the German Biodiversity Exploratories

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D-1), Simpson's dominance (D-2), Simpson's evenness (E), and Berger-Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P.lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.

“Facebook Style”: The Use of Emoticons and Graphic Signs by Users in the Cape Flats

Over the last few years Facebook has become a widespread and continuously expanding medium of communication in Africa and worldwide. Being a new medium of social interaction, Facebook produces its own communication style. It is a style conditioned by the medium and the community of users. My focus of analysis is how Facebook users from the city of Cape Town create this style by means of emoticons and other graphic signs in order to reflect the reality of living in Cape Town’s underprivileged areas. This study is based on a theoretical framework which combines sociolinguistics with Computer-Mediated-Communication to study the emergence of a style peculiar of the online social networks. In a corpus of Coloured Facebook users from the Cape Flats, I have analysed the emergence of emoticons and other graphic signs related to Capetonian gang culture and then tracked the spread of these features to the extensive use by users not related to gangs. It can be deduced that in this process the analysed features amplify their meaning and are employed in a much broader context as their original use. Due to the development and spread of these features we can consider the peculiar electronic communication of Facebook as a style constrained by the electronic medium and its users. It is a style which serves the users to create social meaning and to express their linguistic identities.

Facebook style: The use of non-standard features in virtual speech conditioned by the medium Facebook

Over the last few years Facebook has become a widespread and continuously expanding medium of communication. Being a new medium of social interaction, Facebook produces its own communication style. My focus of analysis is how Facebook users from the city of Malaga create this style by means of phonic features typical of the Andalusian variety and how the users reflect on the use of these phonic features. This project is based on a theoretical framework which combines variationist sociolinguistics with CMC to study the emergence of a style peculiar of the online social networks. In a corpus of Facebook users from three zones of Malaga, I have analysed the use of non-standard phonic features and then compared them with the same features in a reference corpus collected on three beaches of Malaga. From this comparison it can be deduced that the analysed social and linguistic factors work differently in real and virtual speech. Due to these different uses we can consider the peculiar electronic communication of Facebook as a style constrained by the electronic medium. It is a style which serves the users to create social meaning and to express their linguistic identities.

Sustainability principles put into practice: case studies of network analysis in Swiss climate change adaptation

Climate adaptation policies increasingly incorporate sustainability principles into their design and implementation. Since successful adaptation by means of adaptive capacity is recognized as being dependent upon progress toward sustainable development, policy design is increasingly characterized by the inclusion of state and non-state actors (horizontal actor integration), cross-sectoral collaboration, and inter-generational planning perspectives. Comparing four case studies in Swiss mountain regions, three located in the Upper Rhone region and one case from western Switzerland, we investigate how sustainability is put into practice. We argue that collaboration networks and sustainability perceptions matter when assessing the implementation of sustainability in local climate change adaptation. In other words, we suggest that adaptation is successful where sustainability perceptions translate into cross-sectoral integration and collaboration on the ground. Data about perceptions and network relations are assessed through surveys and treated via cluster and social network analysis.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Efficacy, Acceptability, and Tolerability of Antipsychotics in Treatment-Resistant Schizophrenia: A Network Meta-analysis.

Importance In treatment-resistant schizophrenia, clozapine is considered the standard treatment. However, clozapine use has restrictions owing to its many adverse effects. Moreover, an increasing number of randomized clinical trials (RCTs) of other antipsychotics have been published. Objective To integrate all the randomized evidence from the available antipsychotics used for treatment-resistant schizophrenia by performing a network meta-analysis. Data Sources MEDLINE, EMBASE, Biosis, PsycINFO, PubMed, Cochrane Central Register of Controlled Trials, World Health Organization International Trial Registry, and clinicaltrials.gov were searched up to June 30, 2014. Study Selection At least 2 independent reviewers selected published and unpublished single- and double-blind RCTs in treatment-resistant schizophrenia (any study-defined criterion) that compared any antipsychotic (at any dose and in any form of administration) with another antipsychotic or placebo. Data Extraction and Synthesis At least 2 independent reviewers extracted all data into standard forms and assessed the quality of all included trials with the Cochrane Collaboration's risk-of-bias tool. Data were pooled using a random-effects model in a Bayesian setting. Main Outcomes and Measures The primary outcome was efficacy as measured by overall change in symptoms of schizophrenia. Secondary outcomes included change in positive and negative symptoms of schizophrenia, categorical response to treatment, dropouts for any reason and for inefficacy of treatment, and important adverse events. Results Forty blinded RCTs with 5172 unique participants (71.5% men; mean [SD] age, 38.8 [3.7] years) were included in the analysis. Few significant differences were found in all outcomes. In the primary outcome (reported as standardized mean difference; 95% credible interval), olanzapine was more effective than quetiapine (-0.29; -0.56 to -0.02), haloperidol (-0. 29; -0.44 to -0.13), and sertindole (-0.46; -0.80 to -0.06); clozapine was more effective than haloperidol (-0.22; -0.38 to -0.07) and sertindole (-0.40; -0.74 to -0.04); and risperidone was more effective than sertindole (-0.32; -0.63 to -0.01). A pattern of superiority for olanzapine, clozapine, and risperidone was seen in other efficacy outcomes, but results were not consistent and effect sizes were usually small. In addition, relatively few RCTs were available for antipsychotics other than clozapine, haloperidol, olanzapine, and risperidone. The most surprising finding was that clozapine was not significantly better than most other drugs. Conclusions and Relevance Insufficient evidence exists on which antipsychotic is more efficacious for patients with treatment-resistant schizophrenia, and blinded RCTs-in contrast to unblinded, randomized effectiveness studies-provide little evidence of the superiority of clozapine compared with other second-generation antipsychotics. Future clozapine studies with high doses and patients with extremely treatment-refractory schizophrenia might be most promising to change the current evidence.