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Displacing problems: a constructivist grounded theory of problematic pornography use
Full text linkIntroduction: Research indicates that pornography is not inherently harmful for the individual, however, many users consider their use to be problematic. The majority of research concerning problematic pornography use (PPU), often referred to as pornography addiction, discusses nomenclature rather than having an applied focus. Given the lack of theoretical development in this area, a constructivist grounded theory was undertaken with the aim of creating an understanding of the development and maintenance of PPU. Methods: Participants were required to have self-reported PPU and were recruited from online sources. Two main sources of data collection were used: journals of last pornography use, and semi structured interviews. 258 journals of pornography use, and 21 semi-structured interviews were completed. Results: Five interlinked categories were constructed from the data. All participants were seen by the author and constructed as having underlying distinct problems prior to their self-reported PPU; histories of loneliness and isolation, trauma and mental health, they were struggling with their sexual orientation, or sexual dysfunction. Their pornography use had changed function over time, from enjoyment to habitual and instrumental use, mostly being used as a form of emotional regulation. The participants pornography use impacted upon their functioning, their ability to work, study, and socialise. The participant’s discovery and identification of ‘having PPU’ was constructed as occurring by proxy, through an external means - the commonest source was online forums; when participants reached out for information, they were met with an addiction narrative and consequently saw themselves as addicted to pornography. Once this narrative was internalised it appeared to displace the distinct problems as a causative framework. The participants now saw their main problem as pornography addiction, rather than related to other pre-existing distinct problems. This process of displacement was conceptualised as the core category in this grounded theory in that it led participants to committing to a mission, attempting to conquer their addiction. Once they had embarked upon their mission, the underlying distinct problems became secondary to the participants, and often seen as resulting from their pornography use. Discussion: The constructivist grounded theory was situated alongside current theory and research. Some aspects of the grounded theory were judged as having similarities to existing theories, but when taken as a whole it was proposed that the grounded theory is original, having clear implications for future research and clinical practice
Potential of treated wastewater as an energy source for district heating: incorporating social elements into a multi-factorial comparative assessment for cities.
Full text linkRecovering waste heat from urban infrastructures is gaining greater importance in the context of decarbonisation. However, evaluating the feasibility of waste heat recovery projects requires a holistic analysis of potential impacts, which includes social elements that are often overlooked. This paper introduces a novel methodology for assessing the competitiveness of waste heat integration into district heating, based on a multi-factorial decision support tool that incorporates energy poverty as a key performance indicator, in addition to energy, environmental and economic factors. The comparative assessment is based on the implementation of large-scale heat pumps recovering wastewater heat, a resource of great potential that is still underutilised in Europe. The methodology is tested in the cities of London and Riga, which are in countries with significantly different stages of DH development. In London, an emerging market with high growth potential, and in Riga, where there is a well-established DH system. The study has shown that waste heat can significantly reduce consumers' bills for heating, which was observed in all analysed scenarios. The social benefit decreases when the replaced technology involves biomass heat-only boilers or combined heat and power. The methodology presented is generic and can be applied to other locations and heat sources
Computational and theoretical investigation of acoustical and vibrational properties of rigid thin material
Full text linkComputational and theoretical investigation of acoustical and vibrational properties of rigid thin fiberglass material was carried out for different boundary conditions. Fiberglass materials could be utilised for applications ranging from aerospace industry and automotive industry to building and construction industry. The theory of the plate vibration and acoustic radiation were applied to predict the deflection of the thin fibreglass material and sound radiation efficiency at different locations on its surface while study-controlled equation of motion known as Kirchhoff thin plate theory was applied for COMSOL simulation of thin material to determine the deflection of the plate and to obtain stress distribution, velocity contour, displacement, and acoustic pressure at first resonance of the material. The results of this paper show that thin fiberglass material could be applied to sandwich building structures to form panels in order to attenuate airborne sound and to lower noise transmission of structural borne sound, to cover noise barrier to make them more sustainable and weather resistant, to dampen the vibration of machines, and to reduce the structural vibration of buildings
Nanomaterial integration in micro LED technology: Enhancing efficiency and applications
Full text linkThe micro-light emitting diode (µLED) technology is poised to revolutionise display applications through the introduction of nanomaterials and Group III-nitride nanostructures. This review charts state-of-the-art in this important area of micro-LEDs by highlighting their key roles, progress and concerns. The review encompasses details from various types of nanomaterials to the complexity of gallium nitride (GaN) and III nitride nanostructures. The necessity to integrate nanomaterials with III-nitride structures to create effective displays that could disrupt industries was emphasised in this review. Commercialisation challenges and the economic enhancement of micro-LED integration into display applications using monolithic integrated devices have also been discussed. Furthermore, different approaches in micro-LED development are discussed from top-down and bottom-up approaches. The last part of the review focuses on nanomaterials employed in the production of micro-LED displays. It also highlights the combination of III-V LEDs with silicon LCDs and perovskite-based micro-LED displays. There is evidence that efficiency and performance have improved significantly since the inception of the use of nanomaterials in manufacturing these
Gender classification based on gait analysis using ultrawide band radar augmented with artificial intelligence
Full text linkThe identification of individuals based on their walking patterns, also known as gait recognition, has garnered considerable interest as a biometric trait. The use of gait patterns for gender classification has emerged as a significant research domain with diverse applications across multiple fields. The present investigation centers on the classification of gender based on gait utilizing data from Ultra-wide band radar. A total of 181 participants were included in the study, and data was gathered using Ultra-wide band radar technology. This study investigates various preprocessing techniques, feature extraction methods, and dimensionality reduction approaches to efficiently process Ultra-wide band radar data. The data quality is improved through the utilization of a two-pulse canceller and discrete wavelet transform. The hybrid feature dataset is generated through the creation of gray-level co-occurrence matrices and subsequent extraction of statistical features. Principal Component Analysis is utilized for dimensionality reduction, and prediction probabilities are incorporated as features for classification optimization. The present study employs k-fold cross-validation to train and assess machine learning classifiers, Decision Tree, Random Forest, Support Vector Machine, Logistic Regression, Multi-Layer Perceptron, K-Nearest Neighbors, and Extra Tree Classifier. The Multilayer Perceptron exhibits superior performance, achieving an accuracy of 0.936. The Support Vector Machine and k-Nearest Neighbors classifiers closely trail behind, both achieving an accuracy of 0.934. This research is of the utmost importance due to its capacity to offer solutions to crucial problems in multiple domains. The findings indicate that the utilization of UWB radar data for gait-based gender classification holds promise in diverse domains, including biometrics, surveillance, and healthcare. The present study makes a valuable contribution to the progress of gender classification systems that rely on gait patterns
An Interpretive Phenomenological Analysis of the Experiences of Autistic Psychiatrists: “If We Can't Recognize Ourselves, How Can We Diagnose Autistic Patients Accurately?”
Full text linkEvaluating the Impact of COVID-19 Mitigation Measures on Quality Assurance of Cross-border Construction Logistics and Supply Chain
No full textPurpose: While COVID-19 mitigation measures (CMMs) aided in steady recovery during the pandemic, they also impeded movement across economies/borders, affecting quality assurance (QA) of Cross-border Construction Logistics and Supply Chain (Cb-CLSC). However, prior studies on the pandemic in the construction project industry have not revealed how CMMs have impacted QA. Thus, this study aims to evaluate the impact of the CMMs on the QA of Cb-CLSC.
Methodology: This is achieved by adopting an embedded mixed-method approach involving a desk literature review and engaging 150 experts from different economies across the globe using expert surveys, and results verified via semi-structured expert interviews. Structural equation modelling-based multiple regression analysis (SEM-MRA) was integrated to examine the impact of the CMMs on the QA, along with descriptive and content analysis.
Findings: The study confirmed that CMMs have not only impacted the QA negatively but also influenced the positioning of the QA for the post-pandemic era and probably to survive the risks of future pandemics. Among all the identified CMMs, the top three critical measures include “lockdown (CMM2)”, “use of personal protective equipment, such as nose masks, disinfects, etc. (CMM5)”, and “electronic/virtual meetings (CMM7)”. However, CMM5 possesses the highest contributory power to form CMM in impacting the QA, and this can be regarded as largely positive by strengthening health and safety management systems. Its negative impact lies with the project cost increment and the inconveniences of using nose and face masks.
Practical Implication: This study provides a better understanding to construction practitioners and policy makers on how the pandemic policies, i.e., CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics.
Originality: The study contributes to knowledge in that it provides a better understanding of how the pandemic policies, such as CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics. This area of study has been given limited attention among prior studies during the pandemic
Cumulative incidence and risk factors for cutaneous squamous-cell carcinoma metastases in organ transplant recipients: the SCOPE-ITSCC metastases study, a prospective multi-center study.
Full text linkSolid organ transplant recipients (SOTRs) are believed to have an increased risk of metastatic cutaneous squamous-cell carcinoma (cSCC), but reliable data are lacking regarding the precise incidence and associated risk factors. In a prospective cohort study, including 19 specialist dermatology outpatient clinics in 15 countries, patient and tumor characteristics were collected using standardized questionnaires when SOTRs presented with a new cSCC. After a minimum of 2 years of follow-up, relevant data for all SOTRs were collected. Cumulative incidence of metastases was calculated by the Aalen-Johansen estimator. Fine and Gray models were used to assess multiple risk factors for metastases. Of 514 SOTRs who presented with 623 primary cSCCs, 37 developed metastases with a 2-year patient-based cumulative incidence of 6.2%. Risk factors for metastases included location in the head and neck area, local recurrence, size >2cm, clinical ulceration, poor differentiation grade, perineural invasion and deep invasion. A high-stage tumor that is also ulcerated showed the highest risk of metastasis, with a 2-year cumulative incidence of 46.2% (31.9% - 68.4%). SOTRs have a high risk of cSCC metastases and well-established clinical and histological risk factors have been confirmed. High-stage, ulcerated cSCCs have the highest risk of metastasis. [Abstract copyright: Copyright © 2024. Published by Elsevier Inc.
A wearable sensor and framework for accurate remote monitoring of human motion
Full text linkRemote monitoring and evaluation of human motion during daily life require accurate extraction of kinematic quantities of body segments. Current approaches use inertial sensors that require numerical time differentiation to access the angular acceleration vector, a mathematical operation that greatly increases noise in the acceleration value. Here we introduce a wearable sensor that utilises a spatially defined cluster of inertial measurement units on a rigid base for directly measuring the angular acceleration vector. For this reason, we used computational modelling and experimental data to demonstrate that our new sensor configuration improves the accuracy of tracking angular acceleration vectors. We confirmed the feasibility of tracking human movement by automatic assessment of experimental fall initiation and balance recovery responses. The sensor therefore presents an opportunity to pioneer reliable assessment of human movement and balance in daily life
Photothermal Radiometry Data Analysis by Using Machine Learning
Full text linkPhotothermal techniques are infrared remote sensing techniques that have been used for biomedical applications, as well as industrial non-destructive testing (NDT). Machine learning is a branch of artificial intelligence, which includes a set of algorithms for learning from past data and analyzing new data, without being explicitly programmed to do so. In this paper, we first review the latest development of machine learning and its applications in photothermal techniques. Next, we present our latest work on machine learning for data analysis in opto-thermal transient emission radiometry (OTTER), which is a type of photothermal technique that has been extensively used in skin hydration, skin hydration depth profiles, skin pigments, as well as topically applied substances and skin penetration measurements. We have investigated different algorithms, such as random forest regression, gradient boosting regression, support vector machine (SVM) regression, and partial least squares regression, as well as deep learning neural network regression. We first introduce the theoretical background, then illustrate its applications with experimental results