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Massey Research Online
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Love what you do (and it'll become increasingly difficult to agitate for workplace rights): Sex, work, and rejecting the empowerment discourse
(Taylor and Francis Group on behalf of Routledge, 2022-09-02) Easterbrook-Smith G; Rees E
Taking as its point of inquiry movements in sex work activism which frame sex work as work, this chapter considers the implications of a resistance to discourses of ‘empowerment’. An ‘empowerment’ discourse gained prominence through the late 1990s and 2000s as a means to justify sex work as legitimate and deserving of respect. However, this discourse has been weaponised against sex workers who experience exploitation, or other poor working conditions. Resisting the insistence that sex work must be pleasurable in order to be real work is implicitly a resistance to neoliberal and particularly postfeminist pressures to display an appropriate affective engagement in one’s work. Rather than a politics which aims for incremental acceptance for those already closest to inclusion, it demands that the work be taken seriously regardless of how, where, and by whom it is carried out. Speaking to the interplay of themes about the personal and political, this chapter argues that in this context a refusal to engage with discussions of pleasure may, counterintuitively, sometimes be subversive.
CSMSA: Cross-Space Multiscale Adaptive Link Prediction for ceRNA-Mediated Multimolecular Disease Regulatory Networks
(Association for Computing Machinery, 2025-12-10) Long J; Li J; Qu G; Liu K; Liu B
Regulatory interactions associated with diseases are pivotal for elucidating the molecular mechanisms that drive disease progression and promoting precision medicine. Nevertheless, existing research algorithms often overlook the potential dynamic synergistic-competitive mechanisms between different ceRNA regulatory networks and lack cross-space learning capabilities across multiple heterogeneous graph structures, making it difficult to comprehensively capture the multidimensional molecular regulatory biological mechanisms in disease data with different structural densities. Therefore, we propose the cross-space multiscale adaptive learning framework (CSMSA) that integrates a heterogeneous five-layer ceRNA regulatory network and introduces an adaptive cross-space learning mechanism to dynamically capture complementary and specific interactions and effectively learn the intrinsic biological regulatory mechanisms. Moreover, the CSMSA framework employs a multi-scale feature fusion strategy that hierarchically learns node embeddings by integrating local structural information and global topological features from heterogeneous graphs to enhance predictive performance and robustness across complex datasets of varying sizes. Comprehensive evaluations on three independent datasets show that CSMSA surpasses existing methods in the multimolecular disease prediction task (Max AUC = 0.9880, Max AUPR = 0.9829), thereby providing a reliable new paradigm for probing disease regulatory links.
Smart Glasses for CVI: Co-Designing Extended Reality Solutions to Support Environmental Perception by People with Cerebral Visual Impairment
(Association for Computing Machinery, 2025-10-22) Gamage B; Mcdowell N; Kovacic D; Holloway L; Do TT; Lowery AJ; Price N; Marriott K; Kane S; Shinohara K
Cerebral Visual Impairment (CVI) is the set to be the leading cause of vision impairment, yet remains underrepresented in assistive technology research. Unlike ocular conditions, CVI affects higher-order visual processing - impacting object recognition, facial perception, and attention in complex environments. This paper presents a co-design study with two adults with CVI investigating how smart glasses, i.e. head-mounted extended reality displays, can support understanding and interaction with the immediate environment. Guided by the Double Diamond design framework, we conducted a two-week diary study, two ideation workshops, and ten iterative development sessions using the Apple Vision Pro. Our findings demonstrate that smart glasses can meaningfully address key challenges in locating objects, reading text, recognising people, engaging in conversations, and managing sensory stress. With the rapid advancement of smart glasses and increasing recognition of CVI as a distinct form of vision impairment, this research addresses a timely and under-explored intersection of technology and need.
Vulnerability of marine megafauna to global at-sea anthropogenic threats
(Wiley Periodicals LLC on behalf of Society for Conservation Biology, 2025-11-14) VanCompernolle M; Morris J; Calich HJ; Rodríguez JP; Marley SA; Pearce JR; Abrahms B; Abrantes K; Afonso AS; Aguilar A; Agyekumhene A; Akamatsu T; Åkesson S; Alawa NG; Alfaro-Shigueto J; Anderson RC; Anker-Nilssen T; Arata JA; Araujo G; Arostegui MC; Arrizabalaga H; Arrowsmith LM; Auger-Méthé M; Avila IC; Bailleul F; Barker J; Barlow DR; Barnett A; Barrios-Garrido H; Baylis AMM; Bearzi G; Bejder L; Belda EJ; Benson SR; Berumen ML; Bestley S; Bezerra NPA; Blaison AV; Boehme L; Bograd SJ; Abimbola BD; Bond ME; Borrell A; Bouchet PJ; Boveng P; Braulik G; Braun CD; Brodie S; Bugoni L; Bustamante C; Campana SE; Cárdenas-Alayza S; Carmichael RH; Carroll G; Carter MID; Ceia FR; Cerchio S; Ferreira LC; Chambault P; Chapple TK; Charvet P; Chavez EJ; Chevallier D; Chiaradia A; Chilvers BL; Cimino MA; Clark BL; Clarke CR; Clay TA; Cloyed CS; Cochran JEM; Collins T; Cortes E; Cuevas E; Curnick DJ; Dann P; de Bruyn PJN; de Vos A; Derville S; Dias MP; Diaz-Lopez B; Dodge KL; Dove ADM; Doyle TK; Drymon JM; Dudgeon CL; Dutton PH; Ellenberg U; Elwen SH; Emmerson L; Eniang EA; Espinoza M; Esteban N; Mul E; Fadely BS; Fayet AL; Feare C; Ferguson SH; Feyrer LJ; Finucci B; Florko KRN; Fontes J; Fortuna CM; Fossette S; Fouda L; Frere E; Fuentes MMPB; Gallagher AJ; Borboroglu PG; Garrigue C; Gauffier P; Gennari E; Genov T; Germanov ES; Giménez J; Godfrey MH; Godley BJ; Goldsworthy SD; Gollock M; González Carman V; Gownaris NJ; Grecian WJ; Guzman HM; Hamann M; Hammerschlag N; Hansen ES; Harris MP; Hastie G; Haulsee DE; Hazen EL; Heide-Jørgensen MP; Hieb EE; Higdon JW; Hindell MA; Hinke JT; Hoenner X; Hofmeyr GJG; Holmes BJ; Hoyt E; Huckstadt LA; Hussey NE; Huveneers C; Irvine LG; Jabado RW; Jacoby DMP; Jaeger A; Jagielski PM; Jessopp M; Jewell OJD; Jiménez Alvarado D; Jordan LKB; Jorgensen SJ; Kahn B; Karamanlidis AA; Kato A; Keith-Diagne LW; Kiani MS; Kiszka JJ; Kock AA; Kopf RK; Kuhn C; Kyne PM; Laidre KL; Lana FO; Lander ME; Le Corre M; Lee OA; Leeney RH; Levengood AL; Levenson JJ; Libertelli M; Liu K-M; Lopez Mendilaharsu M; Loveridge A; Lowe CG; Lynch HJ; Macena BCL; Mackay AI
Marine megafauna species are affected by a wide range of anthropogenic threats. To evaluate the risk of such threats, species’ vulnerability to each threat must first be determined. We build on the existing threats classification scheme and ranking system of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species by assessing the vulnerability of 256 marine megafauna species to 23 at-sea threats. The threats we considered included individual fishing gear types, climate-change-related subthreats not previously assessed, and threats associated with coastal impacts and maritime disturbances. Our ratings resulted in 70 species having high vulnerability (v > 0.778 out of 1) to at least 1 threat, primarily drifting longlines, temperature extremes, or fixed gear. These 3 threats were also considered to have the most severe effects (i.e., steepest population declines). Overall, temperature extremes and plastics and other solid waste were rated as affecting the largest proportion of populations. Penguins, pinnipeds, and polar bears had the highest vulnerability to temperature extremes. Bony fishes had the highest vulnerability to drifting longlines and plastics and other solid waste; pelagic cetaceans to 4 maritime disturbance threats; elasmobranchs to 5 fishing threats; and flying birds to drifting longlines and 2 maritime disturbance threats. Sirenians and turtles had the highest vulnerability to at least one threat from all 4 categories. Despite not necessarily having severe effects for most taxonomic groups, temperature extremes were rated among the top threats for all taxa except bony fishes. The vulnerability scores we provide are an important first step in estimating the risk of threats to marine megafauna. Importantly, they help differentiate scope from severity, which is key to identifying threats that should be prioritized for mitigation.
MIC: Medical Image Classification Using Chest X-ray (COVID-19 & Pneumonia) Dataset with the Help of CNN and Customized CNN
(Association for Computing Machinery, 2025-06-06) Fahad N; Ahmed R; Jahan F; Jamal Sadib R; Morol MK; Jubair MAA
The COVID-19 pandemic has had a detrimental impact on the health and welfare of the world's population. An important strategy in the fight against COVID-19 is the effective screening of infected patients, with one of the primary screening methods involving radiological imaging with the use of chest X-rays. Which is why this study introduces a customized convolutional neural network (CCNN) for medical image classification. This study used a dataset of 6432 images named Chest X-ray (COVID-19 & Pneumonia), and images were preprocessed using techniques, including resizing, normalizing, and augmentation, to improve model training and performance. The proposed CCNN was compared with a convolutional neural network (CNN) and other models that used the same dataset. This research found that the Convolutional Neural Network (CCNN) achieved 95.62% validation accuracy and 0.1270 validation loss. This outperformed earlier models and studies using the same dataset. This result indicates that our models learn effectively from training data and adapt efficiently to new, unseen data. In essence, the current CCNN model achieves better medical image classification performance, which is why this CCNN model efficiently classifies medical images. Future research may extend the model's application to other medical imaging datasets and develop real-time offline medical image classification websites or apps.