Predicting house damage class using artificial intelligence method

The unsatisfactory performance of light structures founded on expansive soils subject to seasonal movements is frequently reported since the early 1950\u27s in Australia. Excessive movements have caused damage to numerous structures that have not been adequately designed to accommodate soil volume changes. However, the sole presence of expansive soil is not necessarily the main cause of damage. Other factors such as vegetation, climate factors, types of construction materials and geology type may also contribute. This paper presents a model which predicts the damage class by analyzing combinations of the contributing factors using artificial intelligence methods. This model can help to identify if any serious and urgent repairs are necessary and immediate actions could be initiated without delay

The geometric order of stripes and Luttinger liquids

It is argued that the electron stripes as found in correlated oxides have to do with an unrecognized form of order. The manifestation of this order is the robust property that the charge stripes are at the same time anti-phase boundaries in the spin system. We demonstrate that the quantity which is ordering is sublattice parity, referring to the geometric property of a bipartite lattice that it can be subdivided in two sublattices in two different ways. Re-interpreting standard results of one dimensional physics, we demonstrate that the same order is responsible for the phenomenon of spin-charge separation in strongly interacting one dimensional electron systems. In fact, the stripe phases can be seen from this perspective as the precise generalization of the Luttinger liquid to higher dimensions. Most of this paper is devoted to a detailed exposition of the mean-field theory of sublattice parity order in 2+1 dimensions. Although the quantum-dynamics of the spin- and charge degrees of freedom is fully taken into account, a perfect sublattice parity order is imposed. Due to novel order-out-of-disorder physics, the sublattice parity order gives rise to full stripe order at long wavelength. This adds further credibility to the notion that stripes find their origin in the microscopic quantum fluctuations and it suggests a novel viewpoint on the relationship between stripes and high Tc superconductivity.Comment: 29 pages, 14 figures, 1 tabl

The ranking of factors influencing the behaviour of light structures on expansive soils in Victoria, Australia

In this paper a Neural Network Model was used to develop a ranking of the potential damage influences for light structures on expansive soils in Victoria. These influences include geology, Thornthwaite moisture index, vegetation covers, construction foundation type, construction wall type, geographical region and age of building when first inspected. Approximately 400 cases of damage to light structures in Victoria, Australia were considered in this study. Feedforward Backpropagation was adopted to train the data. The ranking of importance was estimated using connection weight approach and then compared to results calculated from sensitivity analysis. From the analysis, the ranking of importance for potential damage factor was noted.<br /

The Socio-demography and Clinical Profile of Vitiligo in Sudan.

Introduction: Vitiligo is a chronic skin disease that causes loss of pigment, resulting in irregular pale patches of skin. The precise cause of vitiligo is complex and not fully understood. There is some evidence suggesting it is caused by a combination of auto-immune, genetic, and environmental factors. The population incidence worldwide is considered to be between 0.1% and 2%. The disease has different clinical types but generally, it consists of areas of macular depigmentation, commonly on extensor aspects of extremities, on the face or neck, and in skin folds. Age of onset is often in young adulthood and the condition tends to progress gradually with lesions enlarging and extending until a quiescent state is reached. Objective: To define the socio-demography and clinical profile of vitiligo in Sudan. Study design: This study is a cross-sectional, clinico-epidemiological and hospital-based study, done in Khartoum Dermatologic Hospital (KDH). The data were collected between June 2007 and November 2007. Results: The total number of patients with vitiligo in the study was 113. Male patients were 47 (42%). Children were 13 (11%), adults were 90 (80%) and elderlies were 10 (9%). The mean age of onset of the disease was found to be 11.5 yrs in 22.5% of the patients. Patients with acute (< 1 yr) disease were 6 (5.4 %), while those with chronic (b 1 yr) disease were 107 (94.6 %). The most commonly affected tribe was Algaa\'liyeen tribe (27 %). The commonest precipitating factor for vitiligo has been found to be emotional disturbances (in 27 % of patients). Commonest symptom of the disease was depigmented patch/es (64.8 %). Severe (b10 %) involvement of skin surface area was found in 59 % of patients, while mild

Latest Advances in Waste Plastic Pyrolytic Catalysis

With the increase in demand for plastic use, waste plastic (WP) management remains a challenge in the contemporary world due to the lack of sustainable efforts to tackle it. The increment in WPs is proportional to man’s demand and use of plastics, and these come along with environmental challenges. This increase in WPs, and the resulting environmental consequences are mainly due to the characteristic biodegradation properties of plastics. Landfilling, pollution, groundwater contamination, incineration, and blockage of drainages are common environmental challenges associated with WPs. The bulk of these WPs constitutes polyethene (PE), polyethene terephthalate (PET) and polystyrene (PS). Pyrolysis is an eco-friendly thermo-chemical waste plastic treatment solution for valuable product recovery, preferred over landfilling and incineration solutions. In this extensive review, a critical investigation on waste plastic catalytic pyrolysis (WPCP) is performed, including catalyst and non-catalyst applications to sustainably tackle WP management. Current catalysis techniques are revealed, and some comparisons are made where necessary. Common pyrolytic products and common shortcomings and errors related to WP catalysis were also identified. The benefits of catalysts and their applications to augment and optimise thermal pyrolysis are emphasised. With all these findings, and more, this paper provides reassurance on the significance of catalysis to industrial-scale applications and products and supports related WPCP research work concerning the environment and other beneficiaries

The psychological impact of vitiligo in adult Sudanese patients

Objective: Vitiligo is a chronic skin disease that causes loss of pigment, resulting in irregular pale patches of skin. The disease has profound psychological consequences. These effects range from mild embarrassment to a severe loss of self-confidence and social anxiety, especially for those who have lesions on exposed skin. The study sought to determine the psychological impact of vitiligo in Sudanese patients. Method: This study is a cross-sectional, clinical-epidemiological and hospital-based study, underatken in Khartoum Dermatologic Hospital (KDH). The data was collected between June 2007 and November 2007. 111 adult patients were enrolled sequentially during the study period and they were tested using the 12-item General Health Questionnaire (GHQ-12). Results: Psychological disturbances as a consequence of vitiligo were found in 36 (31 %) adult patients. Patients with mild psychological disturbances were found in 20 of these patients and severe disturbances in 16. Conclusion: Psychological consequences are common in patients with vitiligo.Key words: Vitiligo; Stress; Psychological; Suda

Recent Advances on Waste Plastic Thermal Pyrolysis: A Critical Overview

Post-consumer plastic management, otherwise termed waste plastic (WP) management, is a great challenge in today’s world, mainly because of its characteristic biodegradation properties. The quantity of waste plastics correspondingly increases with the increase in demand for plastic use. Research has shown that this demand increases yearly. Most of these waste plastics include high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyethylene terephthalate (PET) and polystyrene (PS). Potentially, these wastes are a wealth, and studies have explored that pyrolysis is a reputable mechanism to accomplish this. In this critical review, an extensive investigation on waste plastics thermal pyrolysis (WPTP) is carried out. The factors that affect the product’s yield and selectivity are discussed, and a comparative quality guarantee of WPTP is examined. This paper presents an assurance into the current findings of WPTP and reveals some common gaps and misconceptions surrounding this field, which are recommendable towards the support of further research work. The significant role of co-pyrolysis of plastics with biomass in this field is also emphasised, and a glimpse into the influence of mixed waste plastics in pyrolysis is presented

Comparison of Artificial Neural Networks and Autoregressive Model to Forecast Inflows to Roseires Reservoir for better Prediction of Irrigation Water Supply in the Sudan

The Blue Nile River is utilized in Sudan as the main source of irrigation water. However, the river has a long, dry, low-flow season (October–May), which necessitates the use of regulations and rules to manage its water use during this period. This depends on the use of accurate lead time forecasts of inflows to the reservoirs built along the river. Thus a reliable and tested forecasting tool is needed to provide inflow forecast, with sufficient lead time. In the present study, artificial neural network (ANN) is used to model the recession curve of the flow hydrograph at El-Deim gauging station, which subsequently is used as inflows to the Roseires Reservoir on the Blue Nile River. Different scenarios of ANN have been tested to forecast 23 10-day mean discharges during the recession period and their performances were assessed. Results from the optimal ANN model were compared to those simulated with an autoregressive (AR1) model to check their accuracy. Modelling results showed that the ANN model developed is capable of accurately forecasting the inflows to the Roseires Reservoir and outperforms the AR1 model. It has then proposed for use in operation of the reservoir for purposes of predicting irrigation water supply