Non-linear optimization for parameter estimation for flood forecasting

Floods are the response of a catchment area to severe rainfall events. Each catchment will have its unique response which is dependent on its own characteristics and the temporal and spatial distribution of the oncoming rainfall event. A non linear optimization technique has been applied to historical data for rainfall and river flows of the Kakanui catchment in North Otago, New Zealand, to estimate the parameters of a model based on the transfer function concept. The non linear optimization is based on Powell algorithm. Powell algorithm has been widely used in the literature, and it is more efficient and faster than the Simplex method (Press et al., 1989) Observed rainfall events at two locations in the Kakanui catchment, along with the corresponding observed flows of the river have been utilized to estimate the transfer function which represents the response of the Kakanui catchment to rainfall events. An adjusted form of Philip’s equation for infiltration was used to estimate the abstraction of the rainfall event and obtain the effective rainfall which will contribute to the river flow. Weighing factors were assigned to each of the rainfall sites to obtain the best fit between observed and forecasted flows. Nine flood events were used for the calibration process, while two events were utilized for the validation of the derived model. The model has 19 parameters for the transfer function, 2 parameters for the hydrologic abstractions model, and 2 parameters for the weighing factors of the rainfall sites. This results in a total of 23 parameters for the developed model. The ratio of observed cumulative rainfall at Clifton Falls to the corresponding rainfall at the Dasher for historical events is not consistent, and varies significantly from one event to another. This indicates the high variability of the spatial distribution of rainfall events over the Kakanui catchment. As these rainfall events were used in the model calibration, it was difficult to obtain the correct transfer function without proper accounting for the spatial distribution of rainfall over the whole watershed. However, the model, in general, performed satisfactory, given the difficulty in representing the spatial variability of the rainfall events. The model was capable of simulating the flood hydrographs of several events which were incorporated in its calibration, but did not perform well with others. The model was able to simulate well the flows of a flood event which was not included in its calibration. Moreover, in applying the derived model for a real case event which occurred most recently on 30 July 2007, the model was able to forecast very closely the peak flow, but the whole flow hydrograph was not forecasted as good

Analyzing Disproportionate Reaction via Comparative Multilingual Targeted Sentiment in Twitter

Global events such as terrorist attacks are commented upon in social media, such as Twitter, in different languages and from different parts of the world. Most prior studies have focused on monolingual sentiment analysis, and therefore excluded an extensive proportion of the Twitter userbase. In this paper, we perform a multilingual comparative sentiment analysis study on the terrorist attack in Paris, during November 2015. In particular, we look at targeted sentiment, investigating opinions on specific entities, not simply the general sentiment of each tweet. Given the potentially inflammatory and polarizing effect that these types of tweets may have on attitudes, we examine the sentiments expressed about different targets and explore whether disproportionate reaction was expressed about such targets across different languages. Specifically, we assess whether the sentiment for French speaking Twitter users during the Paris attack differs from English-speaking ones. We identify disproportionately negative attitudes in the English dataset over the French one towards some entities and, via a crowdsourcing experiment, illustrate that this also extends to forming an annotator bias

Two-stage repair of low anorectal malformations in girls: is it truly a setback?

Background/purpose Anorectal malformations (ARMs) affect 1 in 4000–5000 births. Low ARMs are nowadays treated in the first stage rather than at second or third stages. However, reports suggest problems with continence in these children because of wound dehiscence and infection; thus, protective colostomy may still be recommended. Colostomies do have complications, but the question is whether these disadvantages outweigh the protective effect on wound healing after anal reconstruction. The aim of this study was to define whether two-stage repair of low ARMs in girls is truly a setback or whether it is beneficial.Patients and methods During the period of June 2008–June 2012, 30 female patients suffering from low ARMs were admitted to Mansoura University Children Hospital. Their ages at the time of surgery ranged from 3 to 11 months (mean age 6.2) and they were divided into two equal groups. The fistula location was defined either anocutaneous or anovestibular according to the Pena classification. The choice of management was totally randomized; thus, patients of group A underwent a two-stage posterior sagittal anorectoplasty and group B patients underwent a one-stage posterior sagittal anorectoplasty operation. Data recorded included age, fistula location, associated anomalies, operation performed, operative time, length of hospital stay, approximate cost, and postoperative complications.Results A comparison of data showed that treatment of patients of group A involved more time and money and they had a longer duration of hospital stay than did patients of group B. Seven patients (47%) in group A and nine patients (60%) in group B showed postoperative complications. Wound infection occurred in three patients (20%) of group A and in eight patients (53%) of group B. More importantly, two (13%) wound disruptions occurred among the three cases with wound infection in group A, whereas six (40%) disruptions occurred among the eight patients (53%) with wound infections in group B. The incidence of redo operation in group B was found to be significantly higher than in group A. Mucosal prolapse occurred in only one patient (7%) of group B. Complications related to colostomy occurred in group A only; five patients (33%) suffered skin excoriation around the stoma and one patient (7%) showed a prolapsed distal stoma loop. Constipation was noted during follow-up in five patients (33%) of group A and in six patients (40%) of group B.Conclusion Two-stage repair of low ARM in girls is truly beneficial, as we could perform a successful operation and achieve continence in the child regardless of the complications of colostomy, which are temporary and tolerable.Keywords: anorectal malformations, colostomy, posterior sagittal anorectoplasty, two-stage repair of low anorectal malformatio

Evaluation of Post-operative Pain after Irrigation Using End-vented NaviTip Tips versus Vibringe Sonic Irrigating System in Teeth with Acute Pulpitis with Apical Periodontitis: A Randomized Clinical Trial

AIM: This clinical study was conducted to evaluate and compare the post-operative pain after the using of two different irrigating techniques: Vibringe sonic irrigating system with end-vented NaviTip and conventional needle with end-vented NaviTip immediate postoperatively and 4, 12, 24, 48, and 72 h and 7 days utilizing a numerical rating scale (NRS). METHODS: Thirty-eight patients with acute pulpitis with apical periodontitis were involved in this study. Root canals were prepared using NiTi ProTaper Universal rotary system then randomized into two equal groups according to the technique used for irrigation Group A, Vibringe sonic irrigating system with end-vented NaviTip and Group B, conventional syringe with end-vented NaviTip® irrigating tip. The needles of irrigation were penetrated 2 mm shorter than the working length. The trial design of this study is a parallel randomized controlled trial. RESULTS: All demographic data, clinical and radiographic findings, and modified NRS scores obtained from patients were statistically analyzed. Results showed that there was no statistically difference between the two groups regarding the demographic data, prevalence of pre-operative pain, after 4 h, 12 h, 24 h, and 48 h and 7 days, while in both groups, there was a statistically significant decrease in pain intensity preoperatively compared with all other time periods. CONCLUSION: There is no statistical significance difference between Vibringe sonic irrigating syringe with endvented needle and conventional syringe with end-vented NaviTip, while in both groups, there was a statistically significant decrease in pain intensity preoperatively compared with all other time periods

The impact of El Nino and La Nina weather patterns on Canterbury water resources

Water is an extremely important and increasingly contentious resource in the Canterbury region. An accurate assessment of the size and behaviour of the resource is fundamental to effective water management. This study attempts to calculate rainfall, runoff and evapotranspiration (ET) for Canterbury in order to ascertain a regional water balance as a means of quantifying a net excess or deficit of water in the hydrological budget. The effect of the El Nino Southern Oscillation (ENSO) on this water balance is investigated. Water balances are calculated for two ‘mega-catchments’; western or ‘Alpine’ Canterbury, from the Southern Alps to the foothills, and eastern or ‘Plains’ Canterbury. Long term averages (LTA) are compared with the two strongest years of positive and negative ENSO in the last thirty years, as measured by the Southern Oscillation Index (SOI). The water balance of the Alpine catchment proved problematic, with a significant deficit result. This is thought to be due to major underestimation of rainfall in the alpine region resulting from poor distribution of rainfall gauges. The rainfall figures were recalculated by addition of runoff and ET. The resulting rainfall figures show an increase in rain from LTA for El Nino years and an even greater increase for La Nina, although the high variability in rain means these differences are not statistically significant. This research indicates that there is an impact of strong ENSO events on the water budget components of Canterbury, New Zealand. La Nina conditions tend to produce increased rainfall and decreased evapotranspiration compared to El Nino conditions. The Plains catchment is where the pressure on the water resources is greatest. The LTA’s produce an annual excess of 94mm, while El Nino years with lower rainfall and higher ET, produced a deficit of 65mm. La Nina years have rainfall between the LTA and El Nino years, but a lower ET than either, and produces a deficit of 10mm. Due to data and modeling inaccuracies the La Nina deficit is not large enough to be considered certain. Availability of accurate measured data across the catchments proved to be a major issue for this study. As a result a mixture of measured and modeled data is used and results should be treated with caution. It is recommended that significant investment be made in increasing the capacity of the region to accurately quantify its water resources

Immobilization of halophilic Aspergillus awamori EM66 exochitinase on grafted k-carrageenan-alginate beads

A novel extreme halophilic exochitinase enzyme was produced by honey isolate Aspergillus awamori EM66. The enzyme was immobilized successfully on k-carrageenan-alginate gel carrier (CA) with 93 % immobilization yield. The immobilization process significantly improved the enzyme specific activity 2.6-fold compared to the free form. The significant factors influencing the immobilization process such as enzyme protein concentration and loading time were studied. Distinguishable characteristics of optimum pH and temperature, stability at different temperatures and NaCl tolerance for free and immobilized enzyme were studied. The immobilization process improved optimum temperature from 35 to 45 °C. The immobilized enzyme retained 76.70 % of its activity after 2 h at 75 °C compared to complete loss of activity for the free enzyme. The reusability test proved the durability of the CA gel beads for 28 cycles without losing its activity

Ecological Agro-ecosystem Sustainable Development in Relationship to Other Sectors in the Economic System, and Human Ecological Footprint and Imprint☆

Abstract Sustainable agriculture is the major economic sector (i.e. about 30% of Global economy) with the industrial and trading system in the world's economy. It is important to understand why the sustainable development is very important to the point of view of improving of human life and reducing the poverty. Additionally, we need to sustain our natural resources to be replenished and continue support our human population growth that is continued to increase in alarming rate rather than development, which is in a slow rate that does not meet the demands. This paper is to discuss the importance of global agro-ecosystems, to support humans' needs for feeding and continue their lives in a healthy and sustainable life and to function within the society. In addition, the paper will show the availability of the agriculture natural resources in terms of global ecological biological capacities in hectares and the trends in using these resources in terms of an ecological footprint in hectares. Additionally, we study the term of ecological human imprint in relation to the agro-ecosystem as suggested by Shakir Hanna et al., 2014 . Further the paper will address the impacts of agro-ecosystem on global economy and, further discuss the impacts of human technological advances on agro-ecosystems ecologically, economically, and social importance. Our results show that the global population will be 10.50 billion people in 2050 (i.e. 1.1% the current population growth). The available global cropped land is 2.36 billion global hectares in 2008.The question is the Earth able to provide food and other agricultural products to support the healthy living of all human beings in year 2050 at the current growth rate? The paper is discussing these concerns

EveTAR: Building a Large-Scale Multi-Task Test Collection over Arabic Tweets

This article introduces a new language-independent approach for creating a large-scale high-quality test collection of tweets that supports multiple information retrieval (IR) tasks without running a shared-task campaign. The adopted approach (demonstrated over Arabic tweets) designs the collection around significant (i.e., popular) events, which enables the development of topics that represent frequent information needs of Twitter users for which rich content exists. That inherently facilitates the support of multiple tasks that generally revolve around events, namely event detection, ad-hoc search, timeline generation, and real-time summarization. The key highlights of the approach include diversifying the judgment pool via interactive search and multiple manually-crafted queries per topic, collecting high-quality annotations via crowd-workers for relevancy and in-house annotators for novelty, filtering out low-agreement topics and inaccessible tweets, and providing multiple subsets of the collection for better availability. Applying our methodology on Arabic tweets resulted in EveTAR , the first freely-available tweet test collection for multiple IR tasks. EveTAR includes a crawl of 355M Arabic tweets and covers 50 significant events for which about 62K tweets were judged with substantial average inter-annotator agreement (Kappa value of 0.71). We demonstrate the usability of EveTAR by evaluating existing algorithms in the respective tasks. Results indicate that the new collection can support reliable ranking of IR systems that is comparable to similar TREC collections, while providing strong baseline results for future studies over Arabic tweets

A Semantic Graph-Based Approach for Radicalisation Detection on Social Media

From its start, the so-called Islamic State of Iraq and the Levant (ISIL/ISIS) has been successfully exploiting social media networks, most notoriously Twitter, to promote its propaganda and recruit new members, resulting in thousands of social media users adopting a pro-ISIS stance every year. Automatic identification of pro-ISIS users on social media has, thus, become the centre of interest for various governmental and research organisations. In this paper we propose a semantic graph-based approach for radicalisation detection on Twitter. Unlike previous works, which mainly rely on the lexical representation of the content published by Twitter users, our approach extracts and makes use of the underlying semantics of words exhibited by these users to identify their pro/anti-ISIS stances. Our results show that classifiers trained from semantic features outperform those trained from lexical, sentiment, topic and network features by 7.8% on average F1-measure