Spot the differences in traditional and social entrepreneurial intention : highlighting the role of human and social capital

There is general agreement in the scientific community that entrepreneurship plays a central role in the growth and development of an economy in rapidly changing environments (Acs & Virgill 2010). In particular, when business activities are regarded as a vehicle for sustainable growth at large, that goes beyond mere economic returns of singular entities, encompassing also social problems and heavily relying on collaborative actions, then we more precisely fall into the domain of ‘social entrepreneurship’(Robinson et al. 2009). In the entrepreneurship literature, prior studies demonstrated the role of intentionality as the best predictor of planned behavior (Ajzen 1991), and assumed that the intention to start a business derives from the perception of desirability and feasibility and from a propensity to act upon an opportunity (Fishbein & Ajzen 1975). Recognizing that starting a business is an intentional act (Krueger et al. 2000) and entrepreneurship is a planned behaviour (Katz & Gartner 1988), models of entrepreneurial intentions have substantial implications for intentionality research in entrepreneurship. The purpose of this paper is to explore the emerging practice of social entrepreneurship by comparing the determinants of entrepreneurial intention in general versus those leading to startups with a social mission. Social entrepreneurial intentions clearly merit to be investigated given that the opportunity identification process is an intentional process not only typical of for profit start-ups, and yet there is a lack of research examining opportunity recognition in social entrepreneurship (Haugh 2005). The key argument is that intentionality in both traditional and social entrepreneurs during the decision-making process of new venture creation is influenced by an individual's perceptions toward opportunities (Fishbein & Ajzen 1975). Besides opportunity recognition, at least two other aspects can substantially influence intentionality: human and social capital (Davidsson, 2003). This paper is set to establish if and to what extent the social intentions of potential entrepreneurs, at the cognitive level, are influenced by opportunities recognition, human capital, and social capital. By applying established theoretical constructs, the paper draws comparisons between ‘for-profit’ and ‘social’ intentionality using two samples of students enrolled in Economy and Business Administration at the University G. d’Annunzio in Pescara, Italy. A questionnaire was submitted to 310 potential entrepreneurs to test the robustness of the model. The collected data were used to measure the theoretical constructs of the paper. Reliability of the multi-item scale for each dimension was measured using Cronbach alpha, and for all the dimensions measures of reliability are above 0.70. We empirically tested the model using structural equation modeling with AMOS. The results allow us to empirically contribute to the argument regarding the influence of human and social cognitive capital on social and non-social entrepreneurial intentions. Moreover, we highlight the importance for further researchers to look deeper into the determinants of traditional and social entrepreneurial intention so that governments can one day define better polices and regulations that promote sustainable businesses with a social imprint, rather than inhibit their formation and growth.

Preface to special issue on digital human modelling for vehicle design and manufacturing

The automotive industry has been the focus of digital human modeling (DHM) research and application for many years. In the highly competitive marketplace for personal transportation, the desire to improve the customer’s experience has driven extensive research in both the physical and cognitive interaction between the vehicle and its occupants. Human models provide vehicle designers with tools to view and analyze product interactions before the first prototypes are built, potentially improving the design while reducing cost and development time. The focus of DHM research and applications began with prediction and representation of static postures for purposes of driver workstation layout, including assessments of seat adjustment ranges and exterior vision. Now DHMs are used for seat design and assessment of driver reach and ingress/egress. DHMs and related simulation tools are expanding into the cognitive domain, with computational models of perception and motion, and into the dynamic domain with models of physical responses to ride and vibration. Moreover, DHMs are now widely used to analyze the ergonomics of vehicle assembly tasks. In this case, the analysis aims to determine whether workers can be expected to complete the tasks safely and with good quality. This preface provides a review of the literature to provide context for the nine new papers presented in this special issue.

Negligible heat strain in armored vehicle officers wearing personal body armor

Objectives This study evaluated the heat strain experienced by armored vehicle officers (AVOs) wearing personal body armor (PBA) in a sub-tropical climate. Methods Twelve male AVOs, aged 35-58 years, undertook an eight hour shift while wearing PBA. Heart rate and core temperature were monitored continuously. Urine specific gravity (USG) was measured before and after, and with any urination during the shift. Results Heart rate indicated an intermittent and low-intensity nature of the work. USG revealed six AVOs were dehydrated from pre through post shift, and two others became dehydrated. Core temperature averaged 37.4 ± 0.3°C, with maximum's of 37.7 ± 0.2°C. Conclusions Despite increased age, body mass, and poor hydration practices, and Wet-Bulb Globe Temperatures in excess of 30°C; the intermittent nature and low intensity of the work prevented excessive heat strain from developing.

A particle-based micromechanics approach to simulate structural changes of plant cells during drying

This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

Optimal planning of electric-vehicle charging stations in distribution systems

With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile.

Structural characterisation of kaolinite : NaCl intercalate and its derivatives

Kaolinite:NaCl intercalates with basal layer dimensions of 0.95 and 1.25 nm have been prepared by direct reaction of saturated aqueous NaCl solution with well-crystallized source clay KGa-1. The intercalates and their thermal decomposition products have been studied by XRD, solid-state 23Na, 27Al, and 29Si MAS NMR, and FTIR. Intercalate yield is enhanced by dry grinding of kaolinite with NaCl prior to intercalation. The layered structure survives dehydroxylation of the kaolinite at 500°–600°C and persists to above 800°C with a resultant tetrahedral aluminosilicate framework. Excess NaCl can be readily removed by rinsing with water, producing an XRD ‘amorphous’ material. Upon heating at 900°C this material converts to a well-crystallized framework aluminosilicate closely related to low-camegieite, NaAlSiO4, some 350°C below its stability field. Reaction mechanisms are discussed and structural models proposed for each of these novel materials.

Protein monoubiquitination and polyubiquitination generate structural diversity to control distinct biological processes

Ubiquitination involves the attachment of ubiquitin (Ub) to lysine residues on substrate proteins or itself, which can result in protein monoubiquitination or polyubiquitination. Polyubiquitination through different lysines (seven) or the N-terminus of Ub can generate different protein-Ub structures. These include monoubiquitinated proteins, polyubiqutinated proteins with homotypic chains through a particular lysine on Ub or mixed polyubiquitin chains generated by polymerization through different Ub lysines. The ability of the ubiquitination pathway to generate different protein-Ub structures provides versatility of this pathway to target proteins to different fates. Protein ubiquitination is catalyzed by Ub-conjugating and Ub-ligase enzymes, with different combinations of these enzymes specifying the type of Ub modification on protein substrates. How Ub-conjugating and Ub-ligase enzymes generate this structural diversity is not clearly understood. In the current review, we discuss mechanisms utilized by the Ub-conjugating and Ub-ligase enzymes to generate structural diversity during protein ubiquitination, with a focus on recent mechanistic insights into protein monoubiquitination and polyubiquitination.

Contribution of DEAF1 structural domains to the interaction with the breast cancer oncogene LMO4

The proteins LMO4 and DEAF1 contribute to the proliferation of mammary epithelial cells. During breast cancer LMO4 is upregulated, affecting its interaction with other protein partners. This may set cells on a path to tumour formation. LMO4 and DEAF1 interact, but it is unknown how they cooperate to regulate cell proliferation. In this study, we identify a specific LMO4-binding domain in DEAF1. This domain contains an unstructured region that directly contacts LMO4, and a coiled coil that contains the DEAF1 nuclear export signal (NES). The coiled coil region can form tetramers and has the typical properties of a coiled coil domain. Using a simple cell-based assay, we show that LMO4 modulates the activity of the DEAF NES, causing nuclear accumulation of a construct containing the LMO4-interaction region of DEAF1.

The assessment of students with disabilities : the Australian law as to reasonable adjustment and academic integrity

This paper explains the legislation which underpins the right to reasonable adjustment in education for students with disabilities in Australian schools. It gives examples of the kinds of adjustment which may be made to promote equality of opportunity in the area of assessment. It also considers how the law has constructed the border between reasonable adjustment and academic integrity.

A psychosocial model of young adult passengers’ intervening in unsafe driving of their friends

Young adults are over-represented in motor vehicle crashes and the carrying of same passengers puts them at greater risk of crashing. The current study examined characteristics of the passengers who might play a positive role in reducing friends’ crashes by actively engaging in strategies to protect such friends. A psychosocial theoretical model of prosocial behavior including self-process and contextual cues explained intervening behavior among primarily novice driver college students (n=242) with the exception of the self-process, perspective taking. The results of this study provide support for countermeasure development that accounts for the positive role of peers to increase road safety, and reduce the incidence of crashes, among young adults.

Atmospheric deposition as a source of heavy metals in urban stormwater

Atmospheric deposition is one of the most important pathways of urban stormwater pollution. Atmospheric deposition which can be in the form of either wet or dry deposition have distinct characteristics in terms of associated particulate sizes, pollutant types and influential parameters. This paper discusses the outcomes of a comprehensive research study undertaken to identify important traffic characteristics and climate factors such as antecedent dry period and rainfall characteristics which influences the characteristics of wet and dry deposition of solids and heavy metals. The outcomes confirmed that Zinc (Zn) is correlated with traffic volume whereas Lead (Pb), Cadmium (Cd), Nickel (Ni), and Copper (Cu) are correlated with traffic congestion. Consequently, reducing traffic congestion will be more effective than reducing traffic volume for improving air quality particularly in relation to Pb, Cd, Ni, and Cu. Zn was found to have the highest atmospheric deposition rate compared to other heavy metals. Zn in dry deposition is associated with relatively larger particle size fractions (>10 µm), whereas Pb, Cd, Ni and Cu are associated with relatively smaller particle size fractions (<10 µm). The analysis further revealed that bulk (wet plus dry) deposition which is correlated with rainfall depth and contains a relatively higher percentage of smaller particles compared to dry deposition which is correlated with the antecedent dry period. As particles subjected to wet deposition are smaller, they disperse over a larger area from the source of origin compared to particles subjected to dry deposition as buoyancy forces become dominant for smaller particles compared to the influence of gravity. Furthermore, exhaust emission particles were found to be primarily associated with bulk deposition compared to dry deposition particles which mainly originate from vehicle component wear.

Socio-structural influences on the work participation of refugees : an exploratory systematic mixed studies review

This systematic mixed studies review aimed at synthesizing evidence from studies related to the influences on the work participation of people with refugee status (PWRS). The review focused on the role of proximal socio-structural barriers on work participation by PWRS while foregrounding related distal, intermediate, proximal, and meta-systemic influences. For the systematic search of the literature, we focused on databases that addressed work, well-being, and social policy in refugee populations, including, Medline, CINAHL, PsycInfo, Web of Science, Scopus, and Sociological Abstracts. Of the studies reviewed, 16 of 39 met the inclusion criteria and were retained for the final analysis. We performed a narrative synthesis of the evidence on barriers to work participation by PWRS, interlinking clusters of barriers potent to their effects on work participation. Findings from the narrative synthesis suggest that proximal factors, those at point of entry to the labor market, influence work participation more directly than distal or intermediate factors. Distal and intermediate factors achieve their effects on work participation by PWRS primarily through meta-systemic interlinkages, including host-country documentation and refugee administration provisions.

Numerical study of impact forces on railway sleepers under wheel flat

Wheel-rail interaction is one of the most important research topics in railway engineering. It includes track vibration, track impact response and safety of the track. Track structure failures caused by impact forces can lead to significant economic loss for track owners through damage to rails and to the sleepers beneath. The wheel-rail impact forces occur because of imperfections on the wheels or rails such as wheel flats, irregular wheel profile, rail corrugation and differences in the height of rails connected at a welded joint. The vehicle speed and static wheel load are important factors of the track design, because they are related to the impact forces under wheel-rail defects. In this paper, a 3-Dimensional finite element model for the study of wheel flat impact is developed by use of the FEA software package ANSYS. The effects of the wheel flat to impact force on sleepers with various speeds and static wheel loads under a critical wheel flat size are investigated. It has found that both wheel-rail impact force and impact force on sleeper induced by wheel flat are varying nonlinearly by increasing the vehicle speed; both impact forces are nonlinearly and monotonically increasing by increasing the static wheel load. The relationships between both of impact forces induced by wheel flat and vehicles speed or static load are important to the track engineers to improve the design and maintenance methods in railway industry.

On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations

Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

Systematic variation of the severity of motor vehicle accident-related traumatic brain injury vignettes produces different post-concussion symptom reports

This study investigated the specificity of the post-concussion syndrome (PCS) expectation-as-etiology hypothesis. Undergraduate students (n = 551) were randomly allocated to one of three vignette conditions. Vignettes depicted either a very mild (VMI), mild (MI), or moderate-to-severe (MSI) motor vehicle-related traumatic brain injury (TBI). Participants reported the PCS and PTSD symptoms that they imagined the depicted injury would produce. Secondary outcomes (knowledge of mild TBI, and the perceived undesirability of TBI) were also assessed. After data screening, the distribution of participants by condition was: VMI (n = 100), MI (n = 96), and MSI (n = 71). There was a significant effect of condition on PCS symptomatology, F(2, 264) = 16.55, p < .001. Significantly greater PCS symptomatology was expected in the MSI condition compared to the other conditions (MSI > VMI; medium effect, r = .33; MSI > MI; small-to-medium effect, r = .22). The same pattern of group differences was found for PTSD symptoms, F(2, 264) = 17.12, p < .001. Knowledge of mild TBI was not related to differences in expected PCS symptoms by condition; and the perceived undesirability of TBI was only associated with reported PCS symptomatology in the MSI condition. Systematic variation in the severity of a depicted TBI produces different PCS and PTSD symptom expectations. Even a very mild TBI vignette can elicit expectations of PCS symptoms.