A Large-Scale CNN Ensemble for Medication Safety Analysis

Revealing Adverse Drug Reactions (ADR) is an essential part of post-marketing drug surveillance, and data from health-related forums and medical communities can be of a great significance for estimating such effects. In this paper, we propose an end-to-end CNN-based method for predicting drug safety on user comments from healthcare discussion forums. We present an architecture that is based on a vast ensemble of CNNs with varied structural parameters, where the prediction is determined by the majority vote. To evaluate the performance of the proposed solution, we present a large-scale dataset collected from a medical website that consists of over 50 thousand reviews for more than 4000 drugs. The results demonstrate that our model significantly outperforms conventional approaches and predicts medicine safety with an accuracy of 87.17% for binary and 62.88% for multi-classification tasks

The Self-Organization of Interaction Networks for Nature-Inspired Optimization

Over the last decade, significant progress has been made in understanding complex biological systems, however there have been few attempts at incorporating this knowledge into nature inspired optimization algorithms. In this paper, we present a first attempt at incorporating some of the basic structural properties of complex biological systems which are believed to be necessary preconditions for system qualities such as robustness. In particular, we focus on two important conditions missing in Evolutionary Algorithm populations; a self-organized definition of locality and interaction epistasis. We demonstrate that these two features, when combined, provide algorithm behaviors not observed in the canonical Evolutionary Algorithm or in Evolutionary Algorithms with structured populations such as the Cellular Genetic Algorithm. The most noticeable change in algorithm behavior is an unprecedented capacity for sustainable coexistence of genetically distinct individuals within a single population. This capacity for sustained genetic diversity is not imposed on the population but instead emerges as a natural consequence of the dynamics of the system

Use of statistical outlier detection method in adaptive evolutionary algorithms

In this paper, the issue of adapting probabilities for Evolutionary Algorithm (EA) search operators is revisited. A framework is devised for distinguishing between measurements of performance and the interpretation of those measurements for purposes of adaptation. Several examples of measurements and statistical interpretations are provided. Probability value adaptation is tested using an EA with 10 search operators against 10 test problems with results indicating that both the type of measurement and its statistical interpretation play significant roles in EA performance. We also find that selecting operators based on the prevalence of outliers rather than on average performance is able to provide considerable improvements to adaptive methods and soundly outperforms the non-adaptive case

Numerical Modelling of Waves and Surge from Cyclone Mekunu (May 2018) in the Arabian Sea

Natural hazards like cyclones cause significant loss of life and damage to properties, ecosystems and marine structures and facilities. Numerical modelling of cyclones is carried out for deriving robust design conditions for coastal and marine structures and facilities. Cyclone modelling results are also used for emergency planning and decision-making to estimate potential loss of life, damage to properties and marine facilities and to develop rescue and mitigation measures and plan clean-up operations. Royal HaskoningDHV (RHDHV) has set up regional tidal hydrodynamic and wave transformation models covering the Arabian Sea to address the above issues. Cyclone Mekunu is relatively new (May 2018). A quick literature search by Royal HaskoningDHV has suggested that numerical modelling results of waves and surge on Cyclone Mekunu are hardly available in the public domain. Therefore, this paper has concentrated on this event to illustrate the use of numerical modelling to simulate waves and surge generated by cyclones. The MIKE21 model of DHI was used in the study. Sample results of waves and surge from the modelling study are presented in this paper for illustration purposes. Structural design considerations and cyclone risk reduction measures are also provided. The model could be used to simulate any cyclone generated anywhere within the Arabian Sea. The methodology described in this paper for modelling cyclone waves and surge in the Arabian Sea could also be applied to simulate cyclones at other sites around the world. The paper provides valuable information to the researchers and practitioners of the region on this relatively new event

Development of additively manufactured Titanium based (Ti6Al4V) implants with different inclination angle and its implications on bio-interface for orthopaedic applications

Musculoskeletal injuries and defects are considered globally as some of the most critical types of injury in orthopaedic field and it often requires surgical intervention to deal with these problems. These injuries may occur in different way such as tumor resection, traumatic bone injury, and osteitis. Bone trauma or defect can significantly deteriorate on the status of human's life. The design of tissue engineering materials for both orthopaedic and dental implants is a great challenge in terms of desirable mechanical properties, biocompatibility, and improved osseo-integration. Titanium has been an effective implant material due to its excellent strength to weight ratio, corrosion resistance, toughness, and bio-inert oxide surface. Due to the recent progress of additive manufacturing technique it is possible to make patient-specific implants. Therefore, additive manufacturing has the huge potentiality to disrupt traditional orthopaedic implants to met up the demand of increasing population. Selective laser melting (SLM) is an additive manufacturing process that fabricates constructs based on CAD design by scanning powdered materials using the thermal energy supplied by a focused and computer-controlled laser beam. SLM allows the generation of complex 3D parts by a layer-wise material addition technique that selectively melts successive layers of metal powder on top of each other. There have been several reports existed in the current literature which showed the relationship between different process parameters of additive manufacturing with its different surface properties, mechanical properties and microstructure. There have been also reported that there are several ways to improve the interface of additively manufactured by different surface treatments such as anodization, alkali treatment, surface modifications by coating, grafting and polishing. There has been only limited research has been carried out that how the build inclination angle can be used to improve the bio-interface of additively manufactured titanium implant surface for better osseo-integration without changing any process parameter of additive manufacturing. Therefore, understanding and investigating the relationship between as manufactured parts and its different surface profile properties (surface texture both 2D and 3D), surface roughness (Ra, Rq), surface morphology, and surface wettability are so essential prior to successful clinical application. At the initial stage, we have manufactured Ti6Al4V parts by selective laser melting process (SLM) with different inclination angle with respect to the build plane from 5 to 90 degrees with 5 degrees interval. The upward and downward faces of as-manufactured parts have been investigated profoundly using optical microscopy (OM), profilometer scanning electron microscopy (SEM). Herein, we demonstrated how the surface roughness, surface morphology, and surface wettability are changed with the alteration of inclination angle of SLM parts. There is much more percentage of correlation of arithmetic average of roughness (Ra) value for 5 average data points is found on lower surface on the linear, exponential and logarithmic regression line than the upper surface of SLM plates in the change of inclination angle. This study provides us a deep insight in terms of understanding how the surface properties are influenced by the design angle of additive manufacture when the processing parameters are constant. In the next stage, we have manufactured Ti6Al4V implants with three inclination angles (0 degree, 45 degrees and 90 degrees) and tried to establish a relationship between mammalian cell attachment with the surface properties of different inclination angle. It has been found that during the SLM process there is an increasing trend of partially melted particles with the increase of inclination angle which greatly influence the surface topography, surface chemistry and surface roughness. It has been found from the mammalian cell (CHO-GHP) attachment on different inclined surface that higher inclination angle induces the better cell attachment on implant surface with higher amount of spindle like shape with higher spindle dimension than lower inclination angle.  Implant associated infection is also a major concern among orthopaedic research community. Different coating, grafting, surface modification approaches have been carried out on metallic implant surface in order to prevent against biofilm formation. In this study, we have printed three different inclination angle 10, 45, and 90 degrees and Staphylococcus aureus (S.aureus) were grown on all these samples. After 48 hours of incubation, it has been found that lower inclination angle 10 degrees surface can inhibit biofilm formation due to its lower hydrophobicity, lower roughness, higher surface energy, and fewer partially melted metal particles than 45, and 90 degrees surface. In addition, the bulk chemistry was not altered in both lower and higher inclination angle and mammalian cell growth was not compromised in any of the inclination angle. This work demonstrates us a novel one step method at additive manufacturing that without using any surface modification approach we can develop additively manufactured surface which can shield against implant associated infection with superior surface functionality. In final stage, we have manufactured Ti6Al4V cylindrical single at three different inclination angles (30 degrees, 60 degrees and 90 degrees) with 0.2 mm, 0.6 mm, 1.0 mm diameter struts by selective laser melting process as a proof of concept of orthopaedic lattice implants. The surface properties (surface roughness) of individual cylindrical strut is dependent both with the inclination angle and diameter. In detailed porosity analysis of individual cylindrical strut has been conducted to understand how the pore size and pore orientation are changed with the inclination angle and strut diameter along the build height. The stress analysis and buckling behaviour have also been analysed for individual single strut. After that, rat primary osteoblast cells were grown on individual struts to understand how the bone cells are attached on strut surface after 3 & 7 days of incubation by scanning electron microscope. This work gives us the deep understanding of utilising SLM technology for the development of customized metallic implants for orthopaedic application specially where lattice geometry is required for healing the bone trauma

Credit Assignment in Adaptive Evolutionary Algorithms

In this paper, a new method for assigning credit to search\ud operators is presented. Starting with the principle of optimizing\ud search bias, search operators are selected based on an ability to\ud create solutions that are historically linked to future generations.\ud Using a novel framework for defining performance\ud measurements, distributing credit for performance, and the\ud statistical interpretation of this credit, a new adaptive method is\ud developed and shown to outperform a variety of adaptive and\ud non-adaptive competitors