A toolbox for animal call recognition

Monitoring the natural environment is increasingly important as habit degradation and climate change reduce theworld’s biodiversity.We have developed software tools and applications to assist ecologists with the collection and analysis of acoustic data at large spatial and temporal scales.One of our key objectives is automated animal call recognition, and our approach has three novel attributes. First, we work with raw environmental audio, contaminated by noise and artefacts and containing calls that vary greatly in volume depending on the animal’s proximity to the microphone. Second, initial experimentation suggested that no single recognizer could dealwith the enormous variety of calls. Therefore, we developed a toolbox of generic recognizers to extract invariant features for each call type. Third, many species are cryptic and offer little data with which to train a recognizer. Many popular machine learning methods require large volumes of training and validation data and considerable time and expertise to prepare. Consequently we adopt bootstrap techniques that can be initiated with little data and refined subsequently. In this paper, we describe our recognition tools and present results for real ecological problems.

Efficient safety information retrieval on construction sites: a preliminary methodology

IT-supported field data management benefits on-site construction management by improving accessibility to the information and promoting efficient communication between project team members. However, most of on-site safety inspections still heavily rely on subjective judgment and manual reporting processes and thus observers’ experiences often determine the quality of risk identification and control. This study aims to develop a methodology to efficiently retrieve safety-related information so that the safety inspectors can easily access to the relevant site safety information for safer decision making. The proposed methodology consists of three stages: (1) development of a comprehensive safety database which contains information of risk factors, accident types, impact of accidents and safety regulations; (2) identification of relationships among different risk factors based on statistical analysis methods; and (3) user-specified information retrieval using data mining techniques for safety management. This paper presents an overall methodology and preliminary results of the first stage research conducted with 101 accident investigation reports.

A tissue engineering solution for segmental defect regeneration in load-bearing long bones

The reconstruction of large defects (>10 mm) in humans usually relies on bone graft transplantation. Limiting factors include availability of graft material, comorbidity, and insufficient integration into the damaged bone. We compare the gold standard autograft with biodegradable composite scaffolds consisting of medical-grade polycaprolactone and tricalcium phosphate combined with autologous bone marrow-derived mesenchymal stem cells (MSCs) or recombinant human bone morphogenetic protein 7 (rhBMP-7). Critical-sized defects in sheep - a model closely resembling human bone formation and structure - were treated with autograft, rhBMP-7, or MSCs. Bridging was observed within 3 months for both the autograft and the rhBMP-7 treatment. After 12 months, biomechanical analysis and microcomputed tomography imaging showed significantly greater bone formation and superior strength for the biomaterial scaffolds loaded with rhBMP-7 compared to the autograft. Axial bone distribution was greater at the interfaces. With rhBMP-7, at 3 months, the radial bone distribution within the scaffolds was homogeneous. At 12 months, however, significantly more bone was found in the scaffold architecture, indicating bone remodeling. Scaffolds alone or with MSC inclusion did not induce levels of bone formation comparable to those of the autograft and rhBMP-7 groups. Applied clinically, this approach using rhBMP-7 could overcome autograft-associated limitations.

Bone tissue engineering : reconstruction of critical sized segmental bone defects in the ovine tibia

Well-established therapies for bone defects are restricted to bone grafts which face significant disadvantages (limited availability, donor site morbidity, insufficient integration). Therefore, the objective was to develop an alternative approach investigating the regenerative potential of medical grade polycaprolactone-tricalcium phosphate (mPCL-TCP) and silk-hydroxyapatite (silk-HA) scaffolds. Critical sized ovine tibial defects were created and stabilized. Defects were left untreated, reconstructed with autologous bone grafts (ABG) and mPCL-TCP or silk-HA scaffolds. Animals were observed for 12 weeks. X-ray analysis, torsion testing and quantitative computed tomography (CT) analyses were performed. Radiological analysis confirmed the critical nature of the defects. Full defect bridging occurred in the autograft and partial bridging in the mPCL-TCP group. Only little bone formation was observed with silk-HA scaffolds. Biomechanical testing revealed a higher torsional moment/stiffness (p < 0.05) and CT analysis a significantly higher amount of bone formation for the ABG group when compared to the silk-HA group. No significant difference was determined between the ABG and mPCL-TCP groups. The results of this study suggest that mPCL-TCP scaffolds combined can serve as an alternative to autologous bone grafting in long bone defect regeneration. The combination of mPCL-TCP with osteogenic cells or growth factors represents an attractive means to further enhance bone formation.