Social networks, migration, and care in Tanzania

This paper explores the impacts of the HIV/AIDS epidemic on children and families in northern Tanzania using the concept of social resilience.1 The study is based on the findings of childfocused research with street children and children and families from HIV/AIDS-affected households. The paper illustrates the coping strategies that children and young people, and parents and caregivers adopt at the household level. In particular, it examines how the burden of care affects different generations of women and highlights their resilience, together with the importance of social networks and the fluidity of movement between rural and urban areas. The research suggests that migrating to urban areas to seek a living in the informal sector represents a survival strategy adopted by some children and young people orphaned by AIDS when their families and communities are unable or unwilling to support them. The paper concludes by exploring parents’, caregivers’, children’s, and young people’s views on the forms of social support that would promote their resilience and thereby help to mitigate the impacts of the epidemic at the household level.

The system identification and control of Hammerstein system using non-uniform rational B-spline neural network and particle swarm optimization

In this paper a new system identification algorithm is introduced for Hammerstein systems based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a non-uniform rational B-spline (NURB) neural network. The proposed system identification algorithm for this NURB network based Hammerstein system consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples including a model based controller are utilized to demonstrate the efficacy of the proposed approach. The controller consists of computing the inverse of the nonlinear static function approximated by NURB network, followed by a linear pole assignment controller.

Evolving social networks, attitudes and beliefs and counter terrorism

'The Princeton Companion to Applied Mathematics' is an introduction to applied mathematics for students, teachers, and professionals. This article is for the "Application Areas" part of the book, which comprises articles on connections between applied mathematics and other disciplines.

Digital predistorter design using B-Spline neural network and inverse of De Boor algorithm

This contribution introduces a new digital predistorter to compensate serious distortions caused by memory high power amplifiers (HPAs) which exhibit output saturation characteristics. The proposed design is based on direct learning using a data-driven B-spline Wiener system modeling approach. The nonlinear HPA with memory is first identified based on the B-spline neural network model using the Gauss-Newton algorithm, which incorporates the efficient De Boor algorithm with both B-spline curve and first derivative recursions. The estimated Wiener HPA model is then used to design the Hammerstein predistorter. In particular, the inverse of the amplitude distortion of the HPA's static nonlinearity can be calculated effectively using the Newton-Raphson formula based on the inverse of De Boor algorithm. A major advantage of this approach is that both the Wiener HPA identification and the Hammerstein predistorter inverse can be achieved very efficiently and accurately. Simulation results obtained are presented to demonstrate the effectiveness of this novel digital predistorter design.

Corporate social responsibility, mining and sustainable development in Namibia: critical reflections through a relational lens

For its advocates, corporate social responsibility (CSR) represents a powerful tool through which business and particularly multinationals can play a more direct role in global sustainable development. For its critics, however, CSR rarely goes beyond business as usual, and is often a cover for business practices with negative implications for communities and the environment. This paper explores the relationship between CSR and sustainable development in the context of mining in Namibia. Drawing upon extant literatures on the geographies of responsibility, and referencing in-country empirical case-study research, a critical relational lens is applied to consider their interaction both historically and in the present.

Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder

Literatures have shown that Internet gaming disorder (IGD) subjects show impaired executive control and enhanced reward sensitivities than healthy controls. However, how these two networks jointly affect the valuation process and drive IGD subjects' online-game-seeking behaviors remains unknown. Thirty-five IGD and 36 healthy controls underwent a resting-states scan in the MRI scanner. Functional connectivity (FC) was examined within control and reward network seeds regions, respectively. Nucleus accumbens (NAcc) was selected as the node to find the interactions between these two networks. IGD subjects show decreased FC in the executive control network and increased FC in the reward network when comparing with the healthy controls. When examining the correlations between the NAcc and the executive control/reward networks, the link between the NAcc - executive control network is negatively related with the link between NAcc - reward network. The changes (decrease/increase) in IGD subjects' brain synchrony in control/reward networks suggest the inefficient/overly processing within neural circuitry underlying these processes. The inverse proportion between control network and reward network in IGD suggest that impairments in executive control lead to inefficient inhibition of enhanced cravings to excessive online game playing. This might shed light on the mechanistic understanding of IGD.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

Employment Protection Legislation and Firm Growth : Evidence from a Natural Experiment

A natural experiment is used to identify the causal relationship between employment protection legislation and fi…rm growth. The natural experiment occurred in Sweden in 2001, when an exemption made it possible for fi…rms with less than eleven employees to exclude two workers from the last-in-fi…rst-out principle when dismissing personnel. The estimated average treatment effect of the reform show that the number of employees increased with 0.135 percent in fi…rms with 5-9 employees relative to fi…rms with 10-15 employees, which corresponds to over 5,000 additional jobs per year created by the reform. Firms with ten employees, just below the size threshold, became 3.4 percent less likely to increase their workforce to a level surpassing the threshold, indicating that the last-in-…first-out rule prevented these …firms from growing. Thus, employment protection legislation seems to act as a growth barrier for small fi…rms.

Social Media, Privacy, and the Academic Classroom

We live in a world full of social media and portable technology that allows for the effortless access to, and sharing of, information. While this constant connection can be viewed as a benefit by some, there have been recent, sometimes embarrassing, instances throughout the world that show just how quickly any expectation of privacy can be destroyed. From pictures of poorly dressed shoppers at a grocery store to customers recording interactions with their servers at restaurants, the internet is full of media (all with the potential to go viral) created and posted without consent of all parties captured. This risk to privacy is not just limited to retail and restaurants, as being in any situation amongst people puts you at risk, including being in an academic classroom. Anyone providing in-class instruction, be they professor or librarian, can be at risk for this type of violation of privacy. In addition, the students in the class are also at risk for being unwittingly captured by their classmates. To combat this, colleges and universities are providing recommendations to faculty regarding this issue, such as including suggested syllabus statements about classroom recording by students. In some instances, colleges and universities have instituted formal policies with strict penalties for violators. An overview of current privacy law as it relates to an academic setting is discussed as well as recent, newsworthy instances of student recording in the classroom and the resulting controversies. Additionally, there is a discussion highlighting various recommendations and formal policies that have been issued and adopted by colleges and universities around the country. Finally, advice is offered about what librarians can do to educate students, faculty, and staff about the privacy rights of others and the potential harm that could come from posting to social media and the open web images and video of others without their consent.