Factors that influence entrepreneurial intentions among undergraduates of South-south and Southeast Nigeria

Research shows intentions as the best predictor of behaviour or action, more so if the behaviour requires some unknown time lags to get it realised. This mixed methods research is conducted to explain what factors encourage or discourage entrepreneurship among undergraduates in South-south and Southeast Nigeria and to know whether the factors are the same across the two regions. It surveys 1,129 indigenous final-year undergraduates from 11 states, in 15 universities across 12 faculties and 68 departments in the two regions studied plus four focus groups of 42 participants. It uses a partial least squares structural equation modelling technique (PLS-SEM) to analyse the survey data. It finds the personal attitude construct as the strongest influence on the entrepreneurial intentions variable, followed by the perceived behavioural control construct. The next influence is the perceived barriers construct; it acts as a discouraging factor. The focus group interview results find that the undergraduates explained the factors that influence them as being transformational, affective, push, personal fulfilment motives and personality traits. Moreover, the results indicate that the undergraduates would more likely embrace entrepreneurship if courses were taught in a more practical or application-oriented approach than theory-oriented. Also, if relevant internships were introduced in their courses, entrepreneurship lecturers were experienced entrepreneurs, and universities had a strong collaboration with relevant industries too. The partial least squares multi-group analysis detected no significant differences in any of the 18 relationships hypothesised, based on the model paths. This result suggests that, conceptually or theoretically, the factors modelled as influencing the South-south and Southeast students toward entrepreneurship are fundamentally the same. Nevertheless, in practice as well as in the wider society, the pattern between the two regions might somewhat differ. The reason is that the participants in the focus group interviews consistently demonstrated that they observe and, therefore, perceive the people of Southeast Nigeria as exhibiting a more peculiar flair for entrepreneurial activities in practice. The participants offered various explanations for their position to include: apprenticeship, serial mentorship, crave for independence, early childhood introduction to business by family, and profit motives as the factors that they believe, are more likely to distinguish the Southeast people from their South-south counterparts in entrepreneurship pursuits. They believe, also, that graduates from the two regions would probably follow the same observed patterns of entrepreneurial behaviours. Thus, a major implication would be that in undertaking undergraduate entrepreneurship research, accommodating multi-logical approaches that also encourage views of the students could offer more useful solutions for policy on what students perceive would attract them toward entrepreneurship

Remarks on Topological SUSY in sixdimensional TQFTs

We establish the existence of the topological vector supersymmetry in the six dimensional topological field theory for two-form fields introduced by Baulieu and West. We investigate the relation of these symmetries to the twist operation for the (2,0) supersymmetry and comment on their resemblance to the analogous symmetries in topological Yang-Mills theory.Comment: 12 pages, to be published in JHEP 11(1999)03

Similarities of gauge and gravity amplitudes

We review recent progress in computations of amplitudes in gauge theory and gravity. We compare the perturbative expansion of amplitudes in N=4 super Yang-Mills and N=8 supergravity and discuss surprising similarities.Comment: Talk presented by Harald Ita at "Continuous Advances in QCD 2006", 7 page

Perturbative Gravity and Twistor Space

The recent progress in computing gauge theory amplitudes can be extended, in many cases, to theories incorporating gravity. This has improved our understanding of the perturbative expansion of N=8 supergravity supporting the ``no-triangle hypothesis'' that N=8 one-loop amplitudes may be expressed in terms of scalar box integral functions.Comment: Talk presented by N. E. J. Bjerrum-Bohr at Loop and Legs 2006, 5 page

High multiplicity W+jets predictions at NLO

In these proceedings we present results from a recent calculation for the production of a W boson in conjunction with five jets at next-to-leading order in perturbative QCD. We also use results at lower multiplicities to extrapolate the cross section to the same process with six jets.Comment: 5 pages, Proceedings for the DIS2013 conferenc

The BlackHat Library for One-Loop Amplitudes

We present recent next-to-leading order (NLO) results in perturbative QCD obtained using the BlackHat software library. We discuss the use of n-tuples to separate the lengthy matrix-element computations from the analysis process. The use of n-tuples allows many analyses to be carried out on the same phase-space samples, and also allows experimenters to conduct their own analyses using the original NLO computation.Comment: Talk given at ACAT 2013, Beijing, China, May 16--21, 2013; 6 pages, 2 figures; added reference

Universality in W+Multijet Production

We study $W$-boson production accompanied by multiple jets at 7 TeV at the LHC. We study the jet-production ratio, of total cross sections for $W$+$n$- to $W$+($n-1$)-jet production, and the ratio of distributions in the total transverse hadronic jet energy $H_{\rm T}^{\rm jets}$. We use the ratios to extrapolate the total cross section, and the differential distribution in $H_{\rm T}^{\rm jets}$, to $W$+6-jet production. We use the BlackHat software library in conjunction with SHERPA to perform the computations.Comment: Merge of Moriond 2014 and Loops & Legs 2014 proceedings, 6 pages, 2 figure

Observations of Stellar Maser Sources with no IRAS Counterpart

We investigated stellar maser sources with no IRAS counterpart at the radio, middle-infrared, and near-infrared wavelengths. A 43 GHz SiO maser search for 120 2MASS/MSX objects, and 10 OH 1612 MHz sources with no or a very faint MSX counterpart, resulted in 43 SiO detections: one OH 1612 MHz source, 2 near-infrared stars, and 40 MSX sources. Additional near-infrared J-, H-, and K-band observations of the OH 1612 MHz sources detected 5 near-infrared counterparts. Furthermore, middle-infrared imaging observations at 8.8, 9.7, 12.4, and 24.5 micron with the Subaru 8.2-m telescope found counterparts for 2 near-infrared stars with SiO masers, and counterparts for 6 OH 1612 MHz sources. However, 4 OH 1612 MHz sources were not detected in the sensitive near- and middle-infrared searches; three of these are relatively strong OH maser sources for which the positions were known accurately. We conclude that one of these (OH 028.286-01.801) must be a young object in a star-forming region.Comment: PASJ 57, No.6 issue in press (1 color figure), full high res. figures available at ftp://ftp.nro.nao.ac.jp/nroreport/no629.pdf.gz. PASJ 57 No. 6 (Dec 25, 2005 issue) in pres

GROWTH PROFILE ANALYSIS OF OIL PALM BY USING SPOT 6 THE CASE OF NORTH SUMATRA

Oil Palm (Elaeis guineensis Jack.) is one of the world’s most important tropical tree crops. Its expansion has been reported to cause widespread environment impacts. SPOT 6 data is one of high resolution satellite data that can give information more detail about vegetation and the age of oil palm plantation. The objective of this study was to analyze the growth profile of oil palm and to estimate the productivity age of oil palm. The study area is PTP N 3 in Tebing Tinggi North Sumatera Indonesia.  The method that used is NDVI analysis and regression analysis for getting the model of oil palm growth profile. Data from the field were collected as the secondary data to build that model. The data that collected were age of oil palm and diameters of canopy for every age.   Results indicate that oil palm growth can be explained by variation of NDVI with formula y = -0.0004x2 + 0.0107x + 0.3912, where x is oil palm age and  Y is NDVI of SPOT, with R² = 0.657. This equation can be used to predict the age of oil palm for range 4 to 11 years with R2 around 0.89