Verification of regional climates of GISS GCM. Part 1: Winter

Verification is made of the synoptic fields, sea level pressure, precipitation rate, 200 mb zonal wind and the surface resultant wind, generated by two versions of the GISS climate model. The models differ regarding the horizontal resolution of the computational grids and the specification of the sea surface temperatures. Maps of the regional distributions of seasonal variations of the model fields are shown alongside maps showing the observed distributions. Comparisons of the model results with observations are discussed, and also summarized in tables according to geographic regions

Reactive direction control for a mobile robot: A locust-like control of escape direction emerges when a bilateral pair of model locust visual neurons are integrated

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have been equipped with only a single, central artificial LGMD sensor, and this triggers a non-directional stop or rotation when a potentially colliding object is detected. Clearly, for a robot to behave autonomously, it must react differently to stimuli approaching from different directions. In this study, we implement a bilateral pair of LGMD models in Khepera robots equipped with normal and panoramic cameras. We integrate the responses of these LGMD models using methodologies inspired by research on escape direction control in cockroaches. Using ‘randomised winner-take-all’ or ‘steering wheel’ algorithms for LGMD model integration, the khepera robots could escape an approaching threat in real time and with a similar distribution of escape directions as real locusts. We also found that by optimising these algorithms, we could use them to integrate the left and right DCMD responses of real jumping locusts offline and reproduce the actual escape directions that the locusts took in a particular trial. Our results significantly advance the development of an artificial collision detection and evasion system based on the locust LGMD by allowing it reactive control over robot behaviour. The success of this approach may also indicate some important areas to be pursued in future biological research

Modeling user’s trust in M-commerce acceptance: A conceptual framework in context of Pakistan

With the emergence of Intern ate and world wide web traditional business got new opportunity to complete globally. Traditional bricks-and-mortar business became electronic business ( e-business) by utilizing information and communication technology (ICT) tools. A new term of Mobile Commerce (M-Commerce) has created tremendous spectrum of business opportunities for businesses. Although there has been large scale adoption of M-Commerce in developing economies, but little growth is observed in developing economies such as Pakistan. There are doubts that users of M-Commerce demonstrate a lack of enthusiasm, which may be due to lack of trustworthiness. Based on the well-known and widely used technology acceptance model (TAM), this research study provides the conceptual framework, underpinning the relationship of trust with adoption of M-Commerce in Pakistan. The aim of this paper is to study the role of trust and its relationship with the acceptance of M-Commerce in Pakistan

A framework for the analysis of determinants of social media acceptance in higher educational institute of Pakistan

Social media is being considered an important source in the perspective of academic learning in the educational sector.The scope of learning through social media encompasses broadening the information sharing through collaborative approach with the help of web-based social networking sites as the means to enhance the knowledge of coworkers, colleagues and other mates.Due to large scale penetration of social media among youngsters, it is being perceived to be one of the futuristic approaches for next generation knowledge sharing and academic learning.On one hand, learning through social media has attained an important value in developed economies but on the other hand, real benefits and future implications have not been interpreted and realized in developing economies like Pakistan.Educational institutes in Pakistan need to evaluate and understand the importance and the usage of social networking for the sake of its valued role in academia.Although research communities in the developing countries are paying attention towards the development of this sector in academia but Pakistan still has to go a long way in this regard.The aim of the study is to explore the significant factors which are affecting the delayed acceptance and usage of social media for academic learning purpose.This research proposes an integrated framework including some widely accepted technology models such as Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) to determine significant factors

Climatic effects of 1950-2050 changes in US anthropogenic aerosols - Part 2: Climate response

We investigate the climate response to changing US anthropogenic aerosol sources over the 1950–2050 period by using the NASA GISS general circulation model (GCM) and comparing to observed US temperature trends. Time-dependent aerosol distributions are generated from the GEOS-Chem chemical transport model applied to historical emission inventories and future projections. Radiative forcing from US anthropogenic aerosols peaked in 1970–1990 and has strongly declined since due to air quality regulations. We find that the regional radiative forcing from US anthropogenic aerosols elicits a strong regional climate response, cooling the central and eastern US by 0.5–1.0 °C on average during 1970–1990, with the strongest effects on maximum daytime temperatures in summer and autumn. Aerosol cooling reflects comparable contributions from direct and indirect (cloud-mediated) radiative effects. Absorbing aerosol (mainly black carbon) has negligible warming effect. Aerosol cooling reduces surface evaporation and thus decreases precipitation along the US east coast, but also increases the southerly flow of moisture from the Gulf of Mexico resulting in increased cloud cover and precipitation in the central US. Observations over the eastern US show a lack of warming in 1960–1980 followed by very rapid warming since, which we reproduce in the GCM and attribute to trends in US anthropogenic aerosol sources. Present US aerosol concentrations are sufficiently low that future air quality improvements are projected to cause little further warming in the US (0.1 °C over 2010–2050). We find that most of the warming from aerosol source controls in the US has already been realized over the 1980–2010 period

Regional Warming from Aerosol Removal over the United States: Results from a Transient 2010-2050 Climate Simulation

We use a general circulation model (NASA Goddard Institute for Space Studies GCM 3) to investigate the regional climate response to removal of aerosols over the United States. We perform a pair of transient 2010e2050 climate simulations following a scenario of increasing greenhouse gas concentrations, with and without aerosols over the United States and with present-day aerosols elsewhere. We find that removing U.S. aerosol significantly enhances the warming from greenhouse gases in a spatial pattern that strongly correlates with that of the aerosol. Warming is nearly negligible outside the United States, but annual mean surface temperatures increase by 0.4e0.6 K in the eastern United States. Temperatures during summer heat waves in the Northeast rise by as much as 1e2 K due to aerosol removal, driven in part by positive feedbacks involving soil moisture and low cloud cover. Reducing U.S. aerosol sources to achieve air quality objectives could thus have significant unintended regional warming consequences

Effect of low protein diet supplemented with or without amino acids on the production of broiler

Experiment was carried out to investigate the effect of low protein diet supplemented with or without amino acids on the performance of broiler. Hubbard 375 day-old broiler were purchased, initially weighed and randomly divided into five groups (75 broilers in each group). Group A was kept as control given commercial feed, group B further divided into two group B1 and B2 were fed low CP (15 and 16%) ratio supplemented with lysine (1.0%) and methionine (0.5%) , while group C also further divided into group C1 and C2 were fed with the same low CP(15 and 16%) ratio without lysine and methionine supplementation. The experimental ratios were start up from fourth week of the experiment. Feed intake of broiler in group A, B1, B2, C1 and C2 was 3.793, 3.781, 3.739, 3.837 and 3.852 kg/b,(P > 0.05) and water intake 11.113, 11.494, 11.850, 11.277 and 11.252 lit/b, (P > 0.05), respectively. Live body weight of broiler was higher in B1 (2.149), than A(2.091), B2(2.069), C1(1.952) and C2(1.929), kg/b (P < 0.05) and their FCR was better for B1(1.75) than B2(1.80), A(1.81), C1(1.85) and C2(1.99), respectively. Carcass weight of broiler for A (1.227), B1 (1.339), B2 (1.210), C1 (1.155) and C2 (1.200) kg/b, (P > 0.05) and their dressing percentage were A(60.46), B1 ( 62.41), B2(60.48), C1 (59.59) and C2(59.22) percent (P > 0.05), respectively. Mortality of broiler in group A (5.3), B1 (2.6), B2 (6.6), C1 (4.0) and C2 (1.3) percent (P > 0.05), respectively. The average weight of liver, heart, gizzard, spleen and intestine for various group of broiler were found non significant (P > 0.05). Net profit was better in group B1 (75.5), followed by B2 (68.3), A (62.5), C1 (51.8) and C2 (49.9) Rs/b, respectively. It was concluded that low protein diet supplemented with lysine plus methionine significantly improved live body weight of broiler.Key words: Protein, amino acid, supplemented, broiler

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging and so forth. A good number of motion detectors have been identified in the insects' visual pathways. Computational modelling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. These biological mechanisms through millions of years of evolutionary development will have formed solid modules for constructing dynamic vision systems for future intelligent machines. This article reviews the computational motion perception models originating from biological research of insects' visual systems in the literature. These motion perception models or neural networks comprise the looming sensitive neuronal models of lobula giant movement detectors (LGMDs) in locusts, the translation sensitive neural systems of direction selective neurons (DSNs) in fruit flies, bees and locusts, as well as the small target motion detectors (STMDs) in dragonflies and hover flies. We also review the applications of these models to robots and vehicles. Through these modelling studies, we summarise the methodologies that generate different direction and size selectivity in motion perception. At last, we discuss about multiple systems integration and hardware realisation of these bio-inspired motion perception models