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Contradictory Stakeholder Pressures/Influences for the Oil and Gas Industry’s Environmental Performance-Implications for the Current Era
No full textDue to immense pressure from various stakeholders, for better environmental performance from the oil and gas sector, oil and gas companies have been (at least) projecting an image of better environmental performance. More recently, due to political developments, for example, in the United States, government pressure seems to be lessening; on the contrary there seems to be increased support for the oil and gas sector, in the second largest polluting country, globally. As a timely focus, this study examines the impact of multiple stakeholders’ related independent variables, specifically government influence, on the environmental performance of the oil and gas sector. A survey approach has been adopted for data collection, and structural equation modelling (SEM) has been used to undertake factor analysis. Stakeholder theory has been employed to discuss the survey results. Results demonstrate that governmental, customer, and employee pressures have a significant positive effect on environmental performance in the oil and gas sector. Relaxed government approach thus poses as a major risk against the environmental performance of oil and gas companies. Government support of the oil and gas sector has a negative impact on the influence of other key stakeholders, for example NGOs. Due to the more dominant influence of the government, NGO pressure becomes weaker, and insignificant, as highlighted by our study. In circumstances like these, NGO pressure and investor pressure may not have a significant direct effect on improved environmental performance of oil and gas companies, due to a high level of government support for the sector. Originality/value: This study offers empirical insights into stakeholder pressures on the oil and gas sector, contributing to stakeholder theory by highlighting the fluidity of significant stakeholder influence on environmental governance.</p
A Flow-oriented Genealogical Approach to Understand Digital Transformation: An illustrative Case Analysis
No full textWe position this paper as a provocation in the term’s positive sense as a challenge that is intended to prompt discussion and/or action. In our case the challenge is to overcome theoretical and research methodological orthodoxies in the information systems (IS) community. Inspired by the alternative research approach of problematization we utilize the unconventional theoretical framing of flow-orientation to understand digital transformation. Instead of a traditional understanding through analysing deliberate actions of specific actors, flow-orientation offers a complementary vocabulary of timing, attentionality, and undergoing, which supports a temporal understanding of digital transformation as the result of corresponding flows of action. We demonstrate the perspective’s value with an empirical case of an ongoing digital transformation. Our work also provides practitioners with an alternative approach to managing digital transformation, which supports them in cultivating the dynamics of favourable circumstances under which transformative possibilities can be created, sensed, and actualized at timely moments.</p
Ambidextrous IT Governance in bimodal IT Environments: A Systematic Literature Review and Conceptual Framework
No full textThis study addresses IT governance in bimodal IT environments where traditional IT and agile IT development coexist. Drawing upon the concept of ambidextrous IT governance, this paper presents a systematic literature review that examines how organizations govern their bimodal IT environments. Grounded on ambidexterity theory, we propose a conceptual model that explicates how IT governance mechanisms support organizational ambidexterity by resolving bimodal IT challenges. The paper concludes with an agenda for future research, emphasizing the need for empirical validation of the framework and empirically investigating the effectiveness of the proposed mechanisms.</p
In situ phosphorus-modified Mg2Ge/Zn-Cu composite with improved mechanical, degradation, biotribological properties, and in vitro and in vivo osteogenesis and osteointegration performance for biodegradable bone-implant applications
No full textZinc (Zn)-based composites are promising biodegradable bone-implant materials because of their good biocompatibility, processability, and biodegradability. Nevertheless, the low interfacial bonding strength, coordinated deformation capacity, and mechanical strength of current Zn-based composites hinder their clinical application. In this study, we developed a biodegradable in situ 4Mg2Ge/Zn-0.3Cu-0.05P composite (denoted ZMGCP) via phosphorus (P) modification and hot-rolling for bone-implant applications. The mechanical properties, corrosion behavior, biotribological performance, in vitro cytocompatibility and osteogenic differentiation, and in vivo osteogenesis and osteointegration of the as-cast (AC) and hot-rolled (HR) ZMGCP samples were systematically evaluated and compared to those of 4Mg2Ge/Zn-0.3Cu (denoted ZMGC). The primary and eutectic reinforcement Mg2Ge phases formed during solidification were refined after P modification and hot-rolling. The HR ZMGCP exhibited the best tensile properties among all the samples with an ultimate tensile strength of 288.9 MPa, a yield strength of 194.5 MPa, and an elongation of 17.7 %. The HR ZMGCP showed the lowest corrosion rate of 336 μm/a, 186 μm/a, and 61.7 μm/a as measured by potentiodynamic polarization, electrochemical impedance spectroscopy, and immersion testing, respectively, among all the samples in Hanks’ solution. The HR ZMGCP also showed higher biotribological resistance than its ZMGC counterpart. The HR ZMGCP exhibited the highest in vitro cytocompatibility, the best osteogenesis capability and angiogenesis property among the HR samples of pure Zn, ZMGC, and ZMGCP. Furthermore, the HR ZMGCP displayed complete in vivo biocompatibility, osteogenesis, osteointegration capability, and an appropriate degradation rate, showing significant potential for a biodegradable bone-implant material.</p
Plant Wearable Environmental Monitoring System
No full textThe emergence of plant‐wearable health monitoring systems represents a transformative advance in precision agriculture, enabling continuous, non-invasive monitoring of plant physiological responses under real environmental conditions. As immobile organisms, plants are highly sensitive to biotic and abiotic stresses, which often manifest through volatile organic compound (VOC) emissions, pigmentation changes, or variations in water content. Traditional laboratory-based spectroscopy and imaging methods, while accurate, are hindered by bulkiness, cost, and lack of real-time field applicability. To address these limitations, this thesis develops novel low-power sensing platforms focused on methanol (MeOH) VOC detection and plant wearable optical monitoring of leaf colour, thereby establishing a multifunctional framework for chemical and agricultural health monitoring.
In the first stage, pristine tin oxide (SnO2) thin films were fabricated and evaluated as resistive gas sensors for MeOH detection. Their response at various temperatures was evaluated. SnO2 exhibited excellent sensitivity at elevated temperatures (>200 °C). The sensor such conditions were incompatible with portable and low-power applications. This comparative study demonstrated pristine SnO2 as a promising alternative for MeOH where thermal excitation is available, advancing the applicability of metal-oxide-based sensors for energy-efficient platforms.
To overcome the limitation of external activation, the second stage focused on conducting polymers, specifically poly(3,4-ethylenedioxythiophene):tosylate (PEDOT:Tos). These thin films exhibited measurable conductivity shifts upon MeOH exposure at room temperature, eliminating the need for thermal or photo activation which is critical for wearable integration. However, pristine films showed moderate sensitivity, prompting surface modification using urea treatment. Morphological analyses via SEM and AFM confirmed increased porosity and roughness, which enhanced gas–surface interactions. This modification resulted in a substantial improvement in sensitivity, positioning urea-treated PEDOT:Tos films as highly promising candidates for low-power, room-temperature VOC sensing.
The third and most application-oriented component of the research extended the scope of sensing toward plant health monitoring by developing a flexible optical wearable sensor. A flexible, lightweight patch was designed using discrete LEDs and photodiodes on a polyimide substrate, ensuring conformal contact with leaf surfaces. Blue and red LEDs probed chlorophyll absorption bands to detect pigmentation changes during stress progression, while near-infrared LEDs at 1250 nm and 1450 nm targeted water absorption bands to monitor hydration levels. Integrated with amplifiers and a wireless Bluetooth module, the patch provided real-time, non-invasive insights into leaf colour transitions (green to yellow, red, or brown) and water status.
Collectively, this research advances both the fundamental understanding and practical application of multifunctional sensor technologies. The insights into pristine SnO2 based MeOH sensor, the successful demonstration of urea-functionalized PEDOT:Tos for room-temperature gas sensing, and the creation of a flexible optical patch form a coherent framework for next-generation agricultural and environmental monitoring. Beyond agriculture, these research works have broader implications for industrial safety and environmental VOC detection. By integrating advances in material science, sensor engineering, and flexible electronics, this work lays a foundation for future development of compact, energy-efficient, and multifunctional wearable systems capable of delivering real-time, actionable insights for both biological and environmental health monitoring.</p
Understanding the perspectives of a teacher educator and pre-service teachers toward an immersive STEM experience.
No full textThis study explored the nuanced perspectives of a teacher educator and primary pre‐service teachers regarding their participation in an immersive STEM experience. Employing a descriptive case study methodology augmented by storytelling techniques, our study aimed to unravel the complex dynamics inherent in such educational initiatives. Through the lens of figured‐world analysis, we uncovered the tensions and dualities that permeate this immersive learning environment. Our findings revealed a complex interplay of perspectives, highlighting the challenges and opportunities encountered by both educators and learners. By elucidating the nature of their experiences, this research contributes to a deeper understanding of immersive STEM education and offers insights into its effective implementation in initial teacher education programs.</p
Body Common: Writing Towards a Metabolic Framework
No full textAs physician and philosopher Georges Canguilhem wrote: ‘the idea of the continuity between the normal and the pathological is itself in continuity with the idea of the continuity between life and death, organic and inorganic matter’ (1991: 72). Being partially bounded yet constantly exchanging energy and matter is one of the conditions of living, whether at the level of the cell, a human body, or an ecosystem (Dahiya 2022). Both world and self are always in the making. In this creative practice research, I develop and use a metabolic conceptual framework in response to a physiological perturbance in my own eating. Physiological change is a matter of epistemology (Boyer 2019) and phenomenology (Carel 2014) – of knowing and being. As medical anthropologist Annemarie Mol asks: ‘what if our theoretical repertoires were to take inspiration not from thinking but from eating?’ (2021: 3) I am interested in thresholds and boundaries in multiple senses, as both division and traversable border between inside and outside, health and illness, self and other. I consider health and illness as expressions of a history of collective somatic relationships and systems, demonstrating that ‘health’ as it is experienced by the individual is an internalised expression of power in the body, flows of energy and matter irreducible to inside/outside; the individual is never discrete, nor self-sufficient. I use theoretical framings of living matter from Margulis, Sagan, and Dahiya, and Landecker’s work in waste studies. I outline enclosure and expropriation, their relationship to the subject, and writing in an Australian context. I develop and explore a conceptual and ontological metabolic framework and its effect on ideas of health, illness, self, land, the ‘normal’, and property. The metabolic framework leads me to a ‘body common’, imagining body and self as a kind of commons with overlapping rights and responsibilities.</p
Supersaturated Design-Based Statistical Methods for Variable Selection in Observational Studies
No full textWith technological advancements, datasets containing numerous predictors are increasingly common in observational study settings and encompass both low- and high-dimensional data formats. Model building is a fundamental step following data collection, in which variable selection plays a crucial role, particularly when the underlying true model is sparse. Identifying important predictors is vital for descriptive modeling and enhances the predictive power of the fitted models. Numerous variable selection methods have been proposed in the literature; however, they often yield different subsets of predictors and perform variably under distinct data conditions. Interestingly, some methods originally introduced for factor screening in experimental studies using supersaturated designs (SSDs) have been motivated by ideas from variable selection in observational studies. Inspired by this connection, this thesis proposes novel statistical methods for selecting important predictors in observational data, drawing on concepts used in the analysis of SSDs.Two novel methods, the SSD-based Confidence Interval (SSD-CI) method and the SSD-based Singular Value Decomposition (SSD-SVD) method, were developed by modifying two-level SSD techniques to handle continuous outcomes and accommodate three commonly encountered data structures in observational studies: (a) low-dimensional numeric data; (b) low-dimensional mixed data (including both numeric and categorical (binary) variables); and (c) high-dimensional continuous data. Rather than developing a single universal method, the proposed approaches were tailored to each of the data structures. Additionally, SSD-CI was adapted to support both inference- and prediction-oriented objectives by adjusting the parameter-estimation strategy.The proposed frameworks were applied to both simulated and real-world datasets, which spanned a range of experimental complexities, to assess their relative performance. Unlike prior studies that often compare new methods to only a few benchmarks, potentially overstating their performance, this thesis conducts an extensive comparative evaluation involving a broad suite of classical and modern variable selection methods. These include LASSO, ALASSO, SCAD, MCP, Elastic Net, and ISIS, along with Backward Elimination (BE) approaches in low-dimensional settings, GLASSO in low-dimensional mixed settings, and Stepwise regression with modified Bayesian information criterion (Stepwise(mBIC)) in high-dimensional context. The comparisons considered various conditions, including varying sample sizes, degrees of multicollinearity, true model sizes, and signal strengths.The results revealed that no single method performed the best across all scenarios. SSD-CI can be recommended as a competitive variable selection for both inference and prediction within high-dimensional setting and SSD-SVD as an effective screening tool. Within low-dimensional settings, penalized regression methods such as LASSO with λmin as the penalty (LASSO(λmin)) and Elastic Net could not differentiate true from false, making them less suitable for variable selection in low-dimensional settings, proposing the introduced SSD-based methods as better alternatives.SSD-CI demonstrated robust predictive performance under low-dimensional settings, noisy conditions, and small-sample conditions, and successfully identified unique variables that were often missed by other methods. In contrast, SSD-SVD exhibited a comparatively lower prediction performance but showed a better capability of eliminating false predictors.Overall, SSD-based methods provide a valuable alternative for variable selection in observational studies, particularly in scenarios with small sample sizes and noisy complex data. The results suggest that SSD-CI can serve as a complementary tool in hybrid selection strategies and emerge as a robust approach for capturing true predictors while maintaining predictive accuracy. In contrast, SSD-SVD is more suitable for descriptive modeling of low-dimensional numeric data under a strong model fit. These findings highlight the importance of tailoring variable selection approaches to the data structure, study objectives, and desired balance between predictor identification, inference validity, and predictive performance.</p
Fucoidan for Lung Cancer Therapy: A Review of Classification, Mechanisms, and Preclinical Studies
No full textLung cancer is one of the most common cancers, resulting in numerous deaths worldwide. It is classified into small-cell lung cancer and non-small cell lung cancer. The non-small cell lung cancer accounts for approximately 80% of all cases. Current chemotherapeutic treatments, often limited by severe side effects and toxicity to healthy tissues, underscore the need for more effective and better-tolerated therapies. Natural compounds, such as fucoidan, a sulfated polysaccharide extracted from brown algae, offer a promising avenue for developing such treatments due to their ability to eliminate tumor cells, delay tumor growth, and improve the effectiveness of chemotherapy drugs. Furthermore, fucoidan has received much attention in cancer therapy owing to its various advantages, including its abundance in natural sources, unique structural features of sulfate groups capable of interacting with receptors involved in cancer suppression, and its ability to modulate multiple cancer pathways. This review provides an overview of key factors contributing to lung cancer development, introduces the chemical structure and classification of fucoidans, and comprehensively examines their antilung cancer mechanisms, including apoptosis induction, proliferation inhibition, metastatic suppression, and immune modulation at the cellular level. Drug discovery and preclinical studies evaluating fucoidan in lung cancer therapy are summarized and discussed. Finally, current challenges and future research directions for fucoidan-based drug design are addressed, focusing on the steps necessary to translate promising preclinical findings into clinical applications.</p
Neuroinflammation associated with proviral DNA persists in the brain of virally suppressed people with HIV
No full textDespite viral suppression with antiretroviral therapy (ART), people with HIV (PWH) continue to exhibit brain pathology, and ~20% of individuals develop HIV-associated neurocognitive disorders. However, the state of cellular activation in the brain of virally suppressed (VS) PWH and the impact of local viral reservoirs on cellular activation are unclear. Using multiplex immunofluorescence imaging, here, we demonstrate that the frontal cortex brain tissue from both non-virally suppressed (nVS; n=17) and VS PWH (n=18) have higher frequencies of astrocytes and myeloid cells expressing interferon-inducible Mx-1 and proinflammatory TNFα relative to HIV-seronegative individuals (p</p