Browsing by Author "van Heerden A"

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    Gender-perceived workplace stressors by New Zealand construction professionals
    (Taylor and Francis Group, 2024-02-19) van Heerden A; Boulic M; McDonald BW; Chawynski G
    The construction workplace is male-dominated and stressful, but little is known about gender-based differences in its stressors. This research examined the effect of gender and personal attributes on stressors in the New Zealand construction industry at four major levels: (1) individual, (2) group, (3) organizational, and (4) extra-organizational. Target respondents were professional construction members from Site Safe New Zealand, with 317 completed questionnaires and statistical analysis using the two-sample t-test, Kruskal-Wallis test, and Levene’s test. The findings show that females have higher qualifications than males, but males have about ten years more experience and more completed projects than their female counterparts. Males reported significantly higher technical skills than females and there was no significant difference between genders regarding sector involvement. At the individual level, females were most affected by role conflict stress and the perception of different treatment because of gender. Males felt significantly higher stress over the variable 'on/off-site office/administration building conditions’. At the group level, there were no significant gender differences, but sexual harassment warranted further investigation. Within the organizational and extra-organizational levels, no variables differed significantly between genders. The construction workforce has a strong gender imbalance and efforts are needed to address this through better work-life balance.
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    Six type-I PKS classes and highly conserved melanin and elsinochrome gene clusters found in diverse Elsinoë species.
    (BioMed Central Ltd, 2024-10-22) van Heerden A; Pham NQ; Wingfield BD; Wingfield MJ; Wilken PM
    Elsinoë species are phytopathogenic fungi that cause serious scab diseases on economically important plants. The disease symptoms arise from the effects of a group of phytotoxins known as elsinochromes, produced via a type-I polyketide synthase (PKS) biosynthetic pathway. The elsinochrome gene cluster was first annotated in Elsinoë fawcettii where the main type-I PKS gene was characterized as EfPKS1. A later study showed that this gene and the associated cluster had not been correctly annotated, and that EfPKS1 was actually the anchor gene of the melanin biosynthetic pathway. A new type-I PKS gene EfETB1 associated with elsinochrome production was also identified. The aim of this study was to identify all type-I PKS genes in the genomes of seven Elsinoë species with the goal of independently verifying the PKS containing clusters for both melanin and elsinochrome production. A total of six type-I PKS classes were identified, although there was variation between the species in the number and type of classes present. Genes similar to the E. fawcettii EfPKS1 and EfETB1 type-I PKS genes were associated with melanin and elsinochrome production respectively in all species. The complete melanin and elsinochrome PKS containing clusters were subsequently annotated in all the species with high levels of synteny across Elsinoë species. This study provides a genus-level overview of type-I PKS distribution in Elsinoë species, including an additional line of support for the annotation of the melanin and elsinochrome PKS containing clusters in these important plant pathogens.
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    Using trickle ventilators coupled to fan extractor to achieve a suitable airflow rate in an Australian apartment: A nodal network approach connected to a CFD approach
    (Elsevier B.V., 2023-12-26) Boulic M; Bombardier P; Zaidi Z; Russell A; Waters D; van Heerden A
    The level of airtightness is increasing in newly built Australian apartments. Due to the COVID-19 pandemic, restrictions have forced many people to work from home. An appropriate ventilation rate is needed to decrease virus transmission and provide occupants with a healthy environment. As occupants tend not to open windows, they need to be informed about the potential benefit of using trickle ventilators, in connection with exhaust systems, to ventilate their apartments. In 2022, a provision for lower rates of continuous ventilation (10 L.s−1 for the bathroom exhaust system and 12 L.s−1 for the kitchen exhaust system) was considered for inclusion in the National Construction Code of Australia. This provision was not adopted; however, this is still a valid reference for good practice. Based on this provision for continuous ventilation, our study aims to investigate the airflow velocity and the ventilation efficiency to remove the carbon dioxide (CO2) generated across winter and summer seasons in a Melbourne apartment occupied by two adults and a child over four hours. The study's objectives are 1) to connect two modelling approaches (Computational Fluid Dynamics and nodal networks), and 2) to investigate the potential benefits of using trickle ventilators across winter and summer seasons. The results show that wind conditions have limited effects (4% decrease in the extracted air flow rate) if the extraction network output is protected from the wind. Comparing winter and summer conditions, we found that indoor airflows differed, highly influenced by the temperature difference between outside and inside. We observed that the airflow patterns were more inclined to create “CO2 pockets” during winter, which could increase virus transmission due to ineffective ventilation in this area. However, in winter, ventilation performed better in reducing the CO2 concentration in the kitchen/living room area and the whole apartment than it did during summer.
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    Utilizing passive sensing data to provide personalized psychological care in low-resource settings.
    (F1000 Research Ltd, 2020) Byanjankar P; Poudyal A; Kohrt BA; Maharjan SM; Hagaman A; van Heerden A
    Background: With the growing ubiquity of smartphones and wearable devices, there is an increased potential of collecting passive sensing data in mobile health. Passive data such as physical activity, Global Positioning System (GPS), interpersonal proximity, and audio recordings can provide valuable insight into the lives of individuals. In mental health, these insights can illuminate behavioral patterns, creating exciting opportunities for mental health service providers and their clients to support pattern recognition and problem identification outside of formal sessions. In the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) project, our aim was to build an mHealth application to facilitate the delivery of psychological treatments by lay counselors caring for adolescent mothers with depression in Nepal. Methods: This paper describes the development of the StandStrong platform comprising the StandStrong Counselor application, and a cloud-based processing system, which can incorporate any tool that generates passive sensing data. We developed the StandStrong Counselor application that visualized passively collected GPS, proximity, and activity data. In the app, GPS data displays as heat maps, proximity data as charts showing the mother and child together or apart, and mothers’ activities as activity charts. Lay counselors can use the StandStrong application during counseling sessions to discuss mothers’ behavioral patterns and clinical progress over the course of a five-week counseling intervention. Achievement Awards based on collected data can also be automatically generated and sent to mothers. Additionally, messages can be sent from counselors to mother’s personal phones through the StandStrong platform. Discussion: The StandStrong platform has the potential to improve the quality and effectiveness of psychological services delivered by non-specialists in diverse global settings.
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    What Does Social Support Sound Like? Challenges and Opportunities for Using Passive Episodic Audio Collection to Assess the Social Environment.
    (Frontiers Media S.A., 2021-03-29) Poudyal A; van Heerden A; Hagaman A; Islam C; Thapa A; Maharjan SM; Byanjankar P; Kohrt BA; Kyriakopoulos M
    Background: The social environment, comprised of social support, social burden, and quality of interactions, influences a range of health outcomes, including mental health. Passive audio data collection on mobile phones (e.g., episodic recording of the auditory environment without requiring any active input from the phone user) enables new opportunities to understand the social environment. We evaluated the use of passive audio collection on mobile phones as a window into the social environment while conducting a study of mental health among adolescent and young mothers in Nepal. Methods: We enrolled 23 adolescent and young mothers who first participated in qualitative interviews to describe their social support and identify sounds potentially associated with that support. Then, episodic recordings were collected for 2 weeks from the mothers using an app to record 30 s of audio every 15 min from 4 A.M. to 9 P.M. Audio data were processed and classified using a pretrained model. Each classification category was accompanied by an estimated accuracy score. Manual validation of the machine-predicted speech and non-speech categories was done for accuracy. Results: In qualitative interviews, mothers described a range of positive and negative social interactions and the sounds that accompanied these. Potential positive sounds included adult speech and laughter, infant babbling and laughter, and sounds from baby toys. Sounds characterizing negative stimuli included yelling, crying, screaming by adults and crying by infants. Sounds associated with social isolation included silence and TV or radio noises. Speech comprised 43% of all passively recorded audio clips (n = 7,725). Manual validation showed a 23% false positive rate and 62% false-negative rate for speech, demonstrating potential underestimation of speech exposure. Other common sounds were music and vehicular noises. Conclusions: Passively capturing audio has the potential to improve understanding of the social environment. However, a pre-trained model had the limited accuracy for identifying speech and lacked categories allowing distinction between positive and negative social interactions. To improve the contribution of passive audio collection to understanding the social environment, future work should improve the accuracy of audio categorization, code for constellations of sounds, and combine audio with other smartphone data collection such as location and activity.