Challenges of a Developmental Idea towards Sustainability

This paper attempts to situate and deconstruct the meanings associated with the term development in the context of the developing world. The arguments made highlights the deeply contested and fragmented terrain of development. The paper provides a historical overview of the changing nature of discourses on development, how the imageries of development have shifted since the postwar period. It deploys diverse meanings associated with development as a concept and as a theory. Thus development without dignity means little for those living in the margins of the society. At the same time the language of development has undergone revolutions and convulsions and the role of buzzwords and catch phrases have only helped to prolong misery in a neoliberal world. Development has become a 'one size fits all' concept shorn of cultural and regional specificities. It has been decontextualised and dehumanised to relate to targets
resulting in greater dissonance than resolution of aim and outcomes. The way forward is a better appreciation of the cultural capacity of the social groups for whom development is critical for survival. The conclusion highlights the endemic contradictions inherent in the meaning and delivery of development as a goal, especially when we seek to achieve resilient and sustainable development.

Keywords: Development, Neoliberalism, growth, participation, empowerment,
efficiency, market, state, societies, entitlements and capabilities, stakeholder, rights, structural adjustments, globalisation, self-help, doing development, freedom and
unfreedom.

FKBPL Is a Critical Antiangiogenic Regulator of Developmental and Pathological Angiogenesis

OBJECTIVE: The antitumor effects of FK506-binding protein like (FKBPL) and its extracellular role in angiogenesis are well characterized; however, its role in physiological/developmental angiogenesis and the effect of FKBPL ablation has not been evaluated. This is important as effects of some angiogenic proteins are dosage dependent. Here we evaluate the regulation of FKBPL secretion under angiogenic stimuli, as well as the effect of FKBPL ablation in angiogenesis using mouse and zebrafish models.

APPROACH AND RESULTS: FKBPL is secreted maximally by human microvascular endothelial cells and fibroblasts, and this was specifically downregulated by proangiogenic hypoxic signals, but not by the angiogenic cytokines, VEGF or IL8. FKBPL's critical role in angiogenesis was supported by our inability to generate an Fkbpl knockout mouse, with embryonic lethality occurring before E8.5. However, whilst Fkbpl heterozygotic embryos showed some vasculature irregularities, the mice developed normally. In murine angiogenesis models, including the ex vivo aortic ring assay, in vivo sponge assay, and tumor growth assay, Fkbpl(+/-) mice exhibited increased sprouting, enhanced vessel recruitment, and faster tumor growth, respectively, supporting the antiangiogenic function of FKBPL. In zebrafish, knockdown of zFkbpl using morpholinos disrupted the vasculature, and the phenotype was rescued with hFKBPL. Interestingly, this vessel disruption was ineffective when zcd44 was knocked-down, supporting the dependency of zFkbpl on zCd44 in zebrafish.

CONCLUSIONS: FKBPL is an important regulator of angiogenesis, having an essential role in murine and zebrafish blood vessel development. Mouse models of angiogenesis demonstrated a proangiogenic phenotype in Fkbpl heterozygotes.

Algorithms for Hidden Markov Models With Imprecisely Specified Parameters

Hidden Markov models (HMMs) are widely used models for sequential data. As with other probabilistic graphical models, they require the specification of precise probability values, which can be too restrictive for some domains, especially when data are scarce or costly to acquire. We present a generalized version of HMMs, whose quantification can be done by sets of, instead of single, probability distributions. Our models have the ability to suspend judgment when there is not enough statistical evidence, and can serve as a sensitivity analysis tool for standard non-stationary HMMs. Efficient inference algorithms are developed to address standard HMM usage such as the computation of likelihoods and most probable explanations. Experiments with real data show that the use of imprecise probabilities leads to more reliable inferences without compromising efficiency.

Absolute magnitudes and slope parameters of Pan-STARRS PS1 asteroids -preliminary results

We present the study of absolute magnitude (H) and slope parameter (G) of 170,000 asteroids observed by the Pan-STARRS1 telescope during the period of 15 months within its 3-year all-sky survey mission. The exquisite photometry with photometric errors below 0.04 mag and well-defined filter and photometric system allowed to derive H and G with statistical and systematic errors. Our new approach lies in the Monte Carlo technique simulating rotation periods, amplitudes, and colors, and deriving most-likely H, G and their systematic errors. Comparison of H_M by Muinonen's phase function (Muinonen et al., 2010) with the Minor Planet Center database revealed a negative offset of 0.22±0.29 meaning that Pan-STARRS1 asteroids are fainter. We showed that the absolute magnitude derived by Muinonen's function is systematically larger on average by 0.14±0.29 and by 0.30±0.16 when assuming fixed slope parameter (G=0.15, G_{12}=0.53) than Bowell's absolute magnitude (Bowell et al., 1989). We also derived slope parameters of asteroids of known spectral types and showed a good agreement with the previous studies within the derived uncertainties. However, our systematic errors on G and G_{12} are significantly larger than in previous work, which is caused by poor temporal and phase coverage of vast majority of the detected asteroids. This disadvantage will vanish when full survey data will be available and ongoing extended and enhanced mission will provide new data.

Molecular pedigree reconstruction and estimation of evolutionary parameters in a wild Atlantic salmon river system with incomplete sampling: a power analysis

Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.

Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.

Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.

Early childhood neurodevelopment after intrauterine growth restriction: a systematic review

BACKGROUND AND OBJECTIVE: Children who experienced intrauterine growth restriction (IUGR) may be at increased risk for adverse developmental outcomes in early childhood. The objective of this study was to carry out a systematic review of neurodevelopmental outcomes from 6 months to 3 years after IUGR.

METHODS: PubMed, Embase, PsycINFO, Maternity and Infant Care, and CINAHL databases were searched by using the search terms intrauterine, fetal, growth restriction, child development, neurodevelopment, early childhood, cognitive, motor, speech, language. Studies were eligible for inclusion if participants met specified criteria for growth restriction, follow-up was conducted within 6 months to 3 years, methods were adequately described, non-IUGR comparison groups were included, and full English text of the article was available. A specifically designed data extraction form was used. The methodological quality of included studies was assessed using well-documented quality-appraisal guidelines.

RESULTS: Of 731 studies reviewed, 16 were included. Poorer neurodevelopmental outcomes after IUGR were described in 11. Ten found motor, 8 cognitive, and 7 language delays. Other delays included social development, attention, and adaptive behavior. Only 8 included abnormal Doppler parameters in their definitions of IUGR.

CONCLUSIONS: Evidence suggests that children are at risk for poorer neurodevelopmental outcomes following IUGR from 6 months to 3 years of age. The heterogeneity of primary outcomes, assessment measures, adjustment for confounding variables, and definitions of IUGR limits synthesis and interpretation. Sample sizes in most studies were small, and some examined preterm IUGR children without including term IUGR or AGA comparison groups, limiting the value of extant studies.

Absolute magnitudes and slope parameters for 250,000 asteroids observed by Pan-STARRS PS1 - preliminary results

We present the results of a Monte Carlo technique to calculate the absolute magnitudes (H) and slope parameters (G) of about 240,000 asteroids observed by the Pan-STARRS1 telescope during the first 15 months of its 3-year all-sky survey mission. The system's exquisite photometry with photometric errors asteroids rotation period, amplitude and color to derive the most-likely H and G, but its major advantage is in estimating realistic statistical+systematic uncertainties and errors on each parameter. The method was confirmed by comparison with the well-established and accurate results for about 500 asteroids provided by Pravec et al. (2012) and then applied to determining H and G for the Pan-STARRS1 asteroids using both the Muinonen et al. (2010) and Bowell et al. (1989) phase functions. Our results confirm the bias in MPC photometry discovered by ( Jurić et al., 2002).

An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.