A factor-analytic study exploring the factors of co-worker cohesion

Despite the applied importance of cohesion within organisational settings, researchers have yet to reach consensus about the dimensionality of group cohesion, and therefore appropriate tools for its measurement. The way that cohesion has generally been conceptualised has changed over time, but the measures appear not to reflect the underlying theory. This deficiency has impeded attempts to explore the relationship between co-worker cohesion and group performance (Beal et al., 2003; Mullen & Copper, 1994). Given inconsistent findings from previous factor analyses of cohesion, the present study employed exploratory means to help clarify the factor structure of cohesion within the workplace. Potential participants were recruited via the researchers' social networks. This snowballing technique led to 236 participants completing the online questionnaire. Exploratory factor analysis revealed four first-order factors of team commitment, friendliness, interpersonal conflict and communication that collectively accounted for 55.17% of the variance shared among the 75 cohesion items. Subsequently, a single higher-order factor was extracted which accounted for over half of the co-variation among the first order factors. This higher-order factor seems to reflect a general cohesion factor, as it was loaded by a diffuse collection of items, including those from the four lower-order factors as well as items that failed to load onto these lower-order factors. While there were similarities between these results and those of previous studies, the present factor structure did not map perfectly onto any of the existing conceptual models of cohesion. This finding highlights the need to incorporate some alternate factors that have previously been given little consideration.

Effect of noise factors in energy management of series plug-in hybrid electric vehicles

It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

Effect of speculative prefetching on network load in distributed systems

Previous studies in speculative prefetching focus on building and evaluating access models for the purpose of access prediction. This paper on the other hand investigates the performance of speculative prefetching. When prefetching is performed speculatively, there is bound to be an increase in the network load. Furthermore, the prefetched items must compete for space with existing cache occupants. These two factors-increased load and eviction of potentially useful cache entries-are considered in the analysis. We obtain the following conclusion: to maximise the improvement in access time, prefetch exclusively all items with access probabilities exceeding a certain threshold.

Improving load forecasting accuracy through combination of best forecasts

Neural network (NN) models have been widely used in the literature for short-term load forecasting. Their popularity is mainly due to their excellent learning and approximation capability. However, their forecasting performance significantly depends on several factors including initializing parameters, training algorithm, and NN structure. To minimize negative effects of these factors, this paper proposes a practically simple, yet effective and an efficient method to combine forecasts generated by NN models. The proposed method includes three main phases: (i) training NNs with different structures, (ii) selecting best NN models based on their forecasting performance for a validation set, and (iii) combination of forecasts for selected best NNs. Forecast combination is performed through calculating the mean of forecasts generated by best NN models. The performance of the proposed method is examined using real world data set. Comparative studies demonstrate that the accuracy of combined forecasts is significantly superior to those obtained from individual NN models.

Factors to drive clinical practice improvement in a Malaysian intensive care unit : assessment of organisational readiness using a mixed method approach

This study assessed organisational readiness and factors to drive clinical practice improvement for VAP, CRBSI and PU in a Malaysian intensive care unit (ICU). A mixed method study approach was undertaken in a 16-bed ICU in regional Malaysia using an environmental scan, key informant interviews, staff surveys, and patient audit to elucidate factors contributing to planning for clinical practice improvement. Measurements of sustainability of practice and regard for the practice environment were assessed using validated measures. An environmental scan demonstrated high patient occupancy and case load. Nineteen percent of ICU patients developed complications according to validated measures. Survey results indicated that the majority of nurses had a good knowledge of strategies to prevent ICU complications and a positive attitude toward change processes. Engaging executive leadership was identified as crucial in priming the clinical site for practice change. Providing nurses with tools to monitor their clinical practice and empowering them to change practices are important in improving clinical outcomes.

Biomechanics of the sclera in myopia: Extracellular and cellular factors

Excessive axial elongation of the eye is the principal structural cause of myopia. The increase in eye size results from active remodelling of the sclera, producing a weakened scleral matrix. The present study will detail the biomechanics of the sclera and highlight the matrix and cellular factors important in the control of eye size. Scleral elasticity (load vs. tissue extension) and creep rate (tissue extension vs. time) have been measured postmortem in human eyes. Animal models of myopia have allowed the direct relevance of scleral biomechanics to be investigated during myopia development. Recently, data on tissue matrices incorporating scleral fibroblasts have highlighted the role of cellular contraction in scleral biomechanics. Scleral elasticity is increased in eyes developing myopia, with a reduction in the failure load of the tissue. Scleral creep rate is increased in the sclera from eyes developing myopia, and reduced in eyes recovering from myopia. These changes in biomechanical properties of the sclera occur early in the development of myopia (within 24 h). Alterations in scleral biomechanics during myopia development have been attributed to changes in matrix constituents, principally reduced collagen content. Although the biochemical structure of the sclera plays a critical role in defining the mechanical properties, recent studies investigating the cellular mechanics of the sclera, implicate myofibroblasts in scleral biomechanics. Scleral myofibroblasts have the capacity to contract the matrix and are regulated by tissue stress and growth factors such as transforming growth factor-ß. Changes in these regulatory factors have been observed during myopia development, implicating cellular factors in the resultant weakened sclera. Changes in the biomechanical properties of the sclera are important in facilitating the increase in axial length that results in myopia. Understanding the matrix and cellular factors contributing to the weakened sclera may aid in the development of a clinically appropriate treatment for myopia.

Evaluation of FRP concrete compression member under repeated load and harsh environment

Strengthening and rehabilitation have been increasingly applied in many structures to improve their capacity and serviceability. Fiber Reinforced Polymer (FRP) materials are universally known for their ability to improve the load capacity of damaged structural elements because of their high linear-elastic behavior. However, enhancing the capacity of structural elements that are exposed to repeated load coupled with harsh environment is an area that requires further investigation. This research focused on experimental analysis of the behavior and response of confined and unconfined concrete compression members (300mm x 150mm) under repeated load while exposed to 1440 cycles of seawater splash zone in United Arab Emirates (UAE). Confining concrete compression members with Carbon Fiber Reinforced Polymer (CFRP) and Glass Fiber Reinforced Polymer (GFRP) sheets have increased the load capacity compared to the control sample at room temperature by 110% and 84%, respectively. Results showed that the average value of compressive strength for the confined concrete exposed to sea water splash zone conditions for CFRP and GFRP specimens has decreased by 33% and 23%, respectively, compared to the confined concrete in the room temperature. However, GFRP specimens showed higher performance in compressive strength under sea water splash zone than those of the CFRP specimens. Different mode of failures such as delamination, de-bonding and combination of such modes were observed and related to various exposure factors and mechanical properties.

Load compensation in four-wire electrical power systems

This work describes a methodology for power factor control and correction of the unbalanced currents in four-wire electric circuits. The methodology is based on the insertion of two compensation networks, one wye-grounded neutral and another in delta, in parallel to the load. The mathematical development has been proposed in previous work [3]. In this paper, however, the methodology was adapted to accept different power factors for the system to be compensated. on the other hand, the determination of the compensation susceptances is based on the instantaneous values of the load currents. The results are obtained using the MatLab - Simulink environment.

Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spontaneous Periodontitis Development in Diabetic Rats Involves an Unrestricted Expression of Inflammatory Cytokines and Tissue Destructive Factors in the Absence of Major Changes in Commensal Oral Microbiota

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Determination of the probable ontogenic time of action of lethal factors on the second chromosome of Drosophila melanogaster derived from a natural population

From the study of the genetic load of second chromosome factors in a natural population of Drosophila melanogaster, 15 lethal-bearing strains were recovered and maintained in the laboratory balanced against Ins (2L + 2R), Cy, L-4. For each lethal factor, the probable time of action during development was determined by the appearance of a sharp reduction, at any given stage, in the frequency of individuals compared to that expected in the absence of the lethal factor. Carried out in this way, the analysis suggested that seven were embryonic lethals, two larval lethals and three pupal lethals. Additionally, three gave no evidence of affecting any of the above-mentioned stages; these are interpreted as gametic lethals.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

Application of Conservative Power Theory to load and line characterization and revenue metering

This paper proposes a set of performance factors for load characterization and revenue metering. They are based on the Conservative Power Theory, and each of them relates to a specific load non-ideality (unbalance, reactivity, distortion). The performance factors are capable to characterize the load under different operating conditions, considering also the effect of non-negligible line impedances and supply voltage deterioration. © 2012 IEEE.

HLA-Bw4-B*57 and Cw*18 alleles are associated with plasma viral load modulation in HIV-1 infected individuals in Salvador, Brazil

Host genetic factors play an important role in mediating resistance to HIV-1 infection and may modify the course of infection. HLA-B alleles (Bw4 epitope; B*27 and B*57) as well as killer cell immunoglobulin-like receptors have been associated with slow progression of HIV-1 infection. OBJECTIVE: To evaluate the association between serological epitopes HLA-Bw4 and HLA-Bw6 and prognostic markers in AIDS. METHODS: 147 HIV-infected individuals in Bahia, Northeast Brazil, were genotyped for HLA class I locus. HLA class I genotyping was performed by hybridization with sequence-specific oligonucleotide probes following amplification of the corresponding HLA-A, HLA-B and HLA-C genes. Statistical analysis was performed using Fisher's exact and ANOVA tests for categorical and continuous variables, respectively. RESULTS: We detected a significant association (χ2 = 4.856; p = 0.018) between the presence of HLA-Bw4 and low levels of viremia. Eighteen out of the 147 HIV-infected individuals presented viremia <1,800 copies/mL and 129 presented viremia > 2,000 copies/mL. Ninety and four percent (17/18) of all individuals with viremia < 1,800 copies/mL carried HLA-Bw4, compared to 67.4% (87/129) of individuals with viremia > 2,000 copies/mL. Additionally, we found a significantly higher frequency of B*57 (OR = 13.94; 95% CI = 4.19-46.38; p < 0.0001) and Cw*18 (OR = 16.15; 95% CI = 3.46-75.43; p < 0.0001) alleles, favoring the group with lower viremia levels, in comparison with those with higher viral load. CONCLUSION: HLA-Bw4-B*57 and Cw*18 alleles are associated with lower level of viral load in HIV-infected Brazilian patients. These findings may help us in understanding the determinants of HIV evolution in Brazilian patients, as well as in providing important information on immune response correlates of protection for such population.

Load analyser using conservative power theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)