A study of women's participation in fish food security and poverty alleviation in Lagos and Ogun States

Women, all over the world have contributed in various ways to the social, political and economic development of the Society. In fact, the World Resource Institute recognizes that "women have profound and preserve effect onn the well-being of their families, communities and local ecosystems" (Gamble and Well 1997:211). Women constitute more than 50 percent of the Agricultural (Fisheries being a sub sector), labour force. A study on Women in Fisheries showed that they participate in all aspects of the sector (capture, culture, processing, marketing research, training and Extension services). This paper reports the result of the study on women's contributions in the development of the Fisheries Industry particularly their roles in Fish Food Security, Poverty Alleviation and high rates of women's adoption of Fisheries technologies. The Case-study research methodology is used to study the "How" and "Why" Women's Contribution in Fish Food Security and Poverty Alleviation is at the index level recorded for the gender. The study made use of "Case Study" Research Instrument; documents, interview, artefacts, direct observation and archival records. The sampling techniques were purposive for research audiences and simple random for fisher-folks in the chosen locations. Analysed data showed among others that in Fisheries Research women occupy very important positions as Heads of Division/Section, Fisheries Liasion/Extension Officers and Fisheries Laboratory Chiefs etc. The paper also gave results of women production, processing, marketing and other services statistics; it also discusses the "whys" of women's low capacity in fisheries development of the nation and finally suggested ways in improving women's optimal capacity utilization in fisheries development

Computational modeling and psychophysics in low- and mid-level vision

This thesis addresses a series of topics related to the question of how people find the foreground objects from complex scenes. With both computer vision modeling, as well as psychophysical analyses, we explore the computational principles for low- and mid-level vision.

We first explore the computational methods of generating saliency maps from images and image sequences. We propose an extremely fast algorithm called Image Signature that detects the locations in the image that attract human eye gazes. With a series of experimental validations based on human behavioral data collected from various psychophysical experiments, we conclude that the Image Signature and its spatial-temporal extension, the Phase Discrepancy, are among the most accurate algorithms for saliency detection under various conditions.

In the second part, we bridge the gap between fixation prediction and salient object segmentation with two efforts. First, we propose a new dataset that contains both fixation and object segmentation information. By simultaneously presenting the two types of human data in the same dataset, we are able to analyze their intrinsic connection, as well as understanding the drawbacks of today’s “standard” but inappropriately labeled salient object segmentation dataset. Second, we also propose an algorithm of salient object segmentation. Based on our novel discoveries on the connections of fixation data and salient object segmentation data, our model significantly outperforms all existing models on all 3 datasets with large margins.

In the third part of the thesis, we discuss topics around the human factors of boundary analysis. Closely related to salient object segmentation, boundary analysis focuses on delimiting the local contours of an object. We identify the potential pitfalls of algorithm evaluation for the problem of boundary detection. Our analysis indicates that today’s popular boundary detection datasets contain significant level of noise, which may severely influence the benchmarking results. To give further insights on the labeling process, we propose a model to characterize the principles of the human factors during the labeling process.

The analyses reported in this thesis offer new perspectives to a series of interrelating issues in low- and mid-level vision. It gives warning signs to some of today’s “standard” procedures, while proposing new directions to encourage future research.

Sustainable IT and IT for sustainability

Energy and sustainability have become one of the most critical issues of our generation. While the abundant potential of renewable energy such as solar and wind provides a real opportunity for sustainability, their intermittency and uncertainty present a daunting operating challenge. This thesis aims to develop analytical models, deployable algorithms, and real systems to enable efficient integration of renewable energy into complex distributed systems with limited information.

The first thrust of the thesis is to make IT systems more sustainable by facilitating the integration of renewable energy into these systems. IT represents the fastest growing sectors in energy usage and greenhouse gas pollution. Over the last decade there are dramatic improvements in the energy efficiency of IT systems, but the efficiency improvements do not necessarily lead to reduction in energy consumption because more servers are demanded. Further, little effort has been put in making IT more sustainable, and most of the improvements are from improved "engineering" rather than improved "algorithms". In contrast, my work focuses on developing algorithms with rigorous theoretical analysis that improve the sustainability of IT. In particular, this thesis seeks to exploit the flexibilities of cloud workloads both (i) in time by scheduling delay-tolerant workloads and (ii) in space by routing requests to geographically diverse data centers. These opportunities allow data centers to adaptively respond to renewable availability, varying cooling efficiency, and fluctuating energy prices, while still meeting performance requirements. The design of the enabling algorithms is however very challenging because of limited information, non-smooth objective functions and the need for distributed control. Novel distributed algorithms are developed with theoretically provable guarantees to enable the "follow the renewables" routing. Moving from theory to practice, I helped HP design and implement industry's first Net-zero Energy Data Center.

The second thrust of this thesis is to use IT systems to improve the sustainability and efficiency of our energy infrastructure through data center demand response. The main challenges as we integrate more renewable sources to the existing power grid come from the fluctuation and unpredictability of renewable generation. Although energy storage and reserves can potentially solve the issues, they are very costly. One promising alternative is to make the cloud data centers demand responsive. The potential of such an approach is huge.

To realize this potential, we need adaptive and distributed control of cloud data centers and new electricity market designs for distributed electricity resources. My work is progressing in both directions. In particular, I have designed online algorithms with theoretically guaranteed performance for data center operators to deal with uncertainties under popular demand response programs. Based on local control rules of customers, I have further designed new pricing schemes for demand response to align the interests of customers, utility companies, and the society to improve social welfare.

Rhythms of division of some algae in situ and in laboratory culture. [Translation from: Studii Cerc.Biol.(Bot.) 21, 61-65, 1969. ]

The rhythm of division of 9 species belonging to different groups of algae were analysed in situ and in the laboratory. The research which developed in different environmental conditions attempted to establish the capacity for multiplication and assimilation of chlorophyll on the part of the algae under study with a view to placing them in a culture. The results obtained showed that the green multicellular algae (eg. Ulothrix) and the blue algae (eg. Lyngbya, Oscillatoria) are able to produce an appreciable quantity of dry matter, just as the unicellular algae. At the same time it arises that amongst the numerous factors of the environment, temperature plays one of the most important roles in the process of multiplication.

Real-World Social Cognition: Context Effects in Face and Threat Processing

As borne out by everyday social experience, social cognition is highly dependent on context, modulated by a host of factors that arise from the social environment in which we live. While streamlined laboratory research provides excellent experimental control, it can be limited to telling us about the capabilities of the brain under artificial conditions, rather than elucidating the processes that come into play in the real world. Consideration of the impact of ecologically valid contextual cues on social cognition will improve the generalizability of social neuroscience findings also to pathology, e.g., to psychiatric illnesses. To help bridge between laboratory research and social cognition as we experience it in the real world, this thesis investigates three themes: (1) increasing the naturalness of stimuli with richer contextual cues, (2) the potentially special contextual case of social cognition when two people interact directly, and (3) a third theme of experimental believability, which runs in parallel to the first two themes. Focusing on the first two themes, in work with two patient populations, we explore neural contributions to two topics in social cognition. First, we document a basic approach bias in rare patients with bilateral lesions of the amygdala. This finding is then related to the contextual factor of ambiguity, and further investigated together with other contextual cues in a sample of healthy individuals tested over the internet, finally yielding a hierarchical decision tree for social threat evaluation. Second, we demonstrate that neural processing of eye gaze in brain structures related to face, gaze, and social processing is differently modulated by the direct presence of another live person. This question is investigated using fMRI in people with autism and controls. Across a range of topics, we demonstrate that two themes of ecological validity — integration of naturalistic contextual cues, and social interaction — influence social cognition, that particular brain structures mediate this processing, and that it will be crucial to study interaction in order to understand disorders of social interaction such as autism.

The ecology of phytoplankton in Shropshire and Cheshire meres

This review summarizes the findings of 5 years' research (June 1970-June 1975) on the meres of the Shropshire-Cheshire Plain. A mere is a small, shallow lake; supplied principally by ground water, whose chemical composition is infkuenced by the glacial frift through which it is percolating. The seasonal periodicity of the phytoplankton in the meres involved work mainly in the Grose Mere. Here diatoms were typically dominant in Feb & March, green algae in April & May, blue-green algae in early summer and dinoflagellates in late summer. This pattern is broadly similar from year to year, and has been suggested to be representative of a 'regional type'; it is also similar to that described for many of the world's mildly eutrophic temperate lakes. Vertical distribution of phytoplankton is influenced by their buoyancy (or lack of it) of by their ability to swim. A stylized depth-time distribution of 4 major phytoplankton components in Crose Mere is given diagrammatically.

A Continuum Model for Slip-Twinning Interactions in Magnesium and Magnesium Alloys

Due to their high specific strength and low density, magnesium and magnesium-based alloys have gained great technological importance in recent years. However, their underlying hexagonal crystal structure furnishes Mg and its alloys with a complex mechanical behavior because of their comparably smaller number of energetically favorable slip systems. Besides the commonly studied slip mechanism, another way to accomplish general deformation is through the additional mechanism of deformation-induced twinning. The main aim of this thesis research is to develop an efficient continuum model to understand and ultimately predict the material response resulting from the interaction between these two mechanisms.

The constitutive model we present is based on variational constitutive updates of plastic slips and twin volume fractions and accounts for the related lattice reorientation mechanisms. The model is applied to single- and polycrystalline pure magnesium. We outline the finite-deformation plasticity model combining basal, pyramidal, and prismatic dislocation activity as well as a convexification based approach for deformation twinning. A comparison with experimental data from single-crystal tension-compression experiments validates the model and serves for parameter identification. The extension to polycrystals via both Taylor-type modeling and finite element simulations shows a characteristic stress-strain response that agrees well with experimental observations for polycrystalline magnesium. The presented continuum model does not aim to represent the full details of individual twin-dislocation interactions, yet it is sufficiently efficient to allow for finite element simulations while qualitatively capturing the underlying microstructural deformation mechanisms.

Brca1 is expressed in human microglia and is dysregulated in human and animal model of ALS

Background: There is growing evidence that microglia are key players in the pathological process of amyotrophic lateral sclerosis (ALS). It is suggested that microglia have a dual role in motoneurone degeneration through the release of both neuroprotective and neurotoxic factors. Results: To identify candidate genes that may be involved in ALS pathology we have analysed at early symptomatic age (P90), the molecular signature of microglia from the lumbar region of the spinal cord of hSOD1(G93A) mice, the most widely used animal model of ALS. We first identified unique hSOD1(G93A) microglia transcriptomic profile that, in addition to more classical processes such as chemotaxis and immune response, pointed toward the potential involvement of the tumour suppressor gene breast cancer susceptibility gene 1 (Brca1). Secondly, comparison with our previous data on hSOD1(G93A) motoneurone gene profile substantiated the putative contribution of Brca1 in ALS. Finally, we established that Brca1 protein is specifically expressed in human spinal microglia and is up-regulated in ALS patients. Conclusions: Overall, our data provide new insights into the pathogenic concept of a non-cell-autonomous disease and the involvement of microglia in ALS. Importantly, the identification of Brca1 as a novel microglial marker and as possible contributor in both human and animal model of ALS may represent a valid therapeutic target. Moreover, our data points toward novel research strategies such as investigating the role of oncogenic proteins in neurodegenerative diseases.

Parity-dependent State Engineering and Tomography in the ultrastrong coupling regime

Reaching the strong coupling regime of light-matter interaction has led to an impressive development in fundamental quantum physics and applications to quantum information processing. Latests advances in different quantum technologies, like superconducting circuits or semiconductor quantum wells, show that the ultrastrong coupling regime (USC) can also be achieved, where novel physical phenomena and potential computational benefits have been predicted. Nevertheless, the lack of effective decoupling mechanism in this regime has so far hindered control and measurement processes. Here, we propose a method based on parity symmetry conservation that allows for the generation and reconstruction of arbitrary states in the ultrastrong coupling regime of light-matter interactions. Our protocol requires minimal external resources by making use of the coupling between the USC system and an ancillary two-level quantum system.

Assessment of the impact of aquatic resources research by ICLARM: scope and methodologies

The importance of quantifying the economic returns to investments in aquatic resources research together with the social, environmental and institutional impacts of such investments is widely recognized among ICLARM's donors, trustees and beneficiaries. As with other Consultative Group on International Agricultural Research (CGIAR) centers, ICLARM is being asked to provide specific accounts of the outputs of its research and their impact on farms and on fisheries, including their socioeconomic impact. Such impact information has become a necessary, though not sufficient, basis for setting priorities and allocating resources for research for the CGIAR centers. This paper discusses the types and methods of impact assessment relevant to ICLARM's work. A three-pronged assessment approach is envisaged to capture the full range of impacts: 1) ex ante assessment for research priority setting; 2) assessment prior to dissemination or adoption along with monitoring and evaluation; and 3) ex post impact assessment. It also discusses the objectives and scope for operational impact assessment of ICLARM's research.