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Nonthermal Pressures:Key to Energy Balance and Structure Formation near Sgr A* in the Milky Way
Full text linkThe circumnuclear region of the Galactic center offers a unique laboratory to study energy balance and structure formation around Sgr A⋆. This work investigates thermal and nonthermal processes within a 7 pc distance from Sgr A⋆. Using MeerKAT 1.3 GHz radio continuum data and Atacama Large Millimeter/submillimeter Array H40α radio recombination line emission from the ACES survey, we separate free–free and synchrotron components at ∼0.2 pc resolution. With a thermal fraction of ≃13%, the 1.3 GHz emission shows tight correlations with the Herschel PACS IR data. The correlation between the equipartition magnetic field and molecular gas traced by JCMT 12CO (J = 3 → 2) observations reveals a balance between the magnetic field, cosmic rays, and molecular gas pressures south of the circumnuclear disk on ∼0.7 pc scales. Unlike the magnetic field and ionized gas, the molecular gas density declines in the cavity (R ≤ 2 pc) toward the center, likely due to feedback from Sgr A⋆. We find that nonthermal pressure from turbulent gas nearly balances magnetic and cosmic-ray pressures and exceeds the thermal pressure by 2 orders of magnitude. The medium surrounding Sgr A⋆ is filled by a low-β (thermal-to-magnetic energy ratio), supersonic plasma, with an Alfvén Mach number ≃ 4 (assuming equipartition). Analysis of the mass-to-magnetic flux ratio suggests that the circumnuclear region is mostly subcritical and, therefore, the magnetic field can help stabilize gas clouds against gravitational collapse
An investigative study into the suitability of the Bradford assay for rapid protein determination in whey
No full textThe gold-standard method to calculate protein content is to determine nitrogen levels, through Kjeldahl or Dumas, and subsequently convert this to protein using a conversion factor. However, this is slow, expensive and requires specialist equipment. This has led to the widespread use of colorimetric assays, principally the Bradford assay, as a rapid protein determination method. Limited research exists quantifying the accuracy of these methods for whey protein, using bovine serum albumin (BSA) as a quantifiable standard. To this end, standardised solutions were made of whey protein and BSA and protein content confirmed using Dumas. When tested with Bradford reagent, it was shown that standard solutions of whey protein were significantly less reactive than equivalent concentrations of BSA: thus, the use of BSA substantially underestimated the amount of protein present within a whey protein sample. This highlights that different proteins vary in their affinity for the reagent, indicating the need for researchers to create a sample-specific standard curve. Bradford data was shown to vary significantly from the reported protein concentration for a range of commercial whey proteins. Dumas was accurate only within a limited range, with higher margins of error being seen than commonly reported. The authors suggest against the use of BSA standard curves in the determination of protein within whey due to the varying protein-reagent affinities and recommend the use of any colorimetric assays with caution for heterogenous mixtures. It is hoped that highlighting these limitations will assist the development of more accurate protein determination methodologies, improving scientific quality.</p
Changes in biopsychosocial factors based on transportation independence among older adults:A one-year study post-COVID-19 movement restrictions
No full textIntroduction: The global COVID-19 pandemic prompted widespread lockdown measures, impacting transportation systems and specifically affecting the mobility of older adults, which could result in changes to their biophysical, psychological and social health, or better known as biopsychosocial health. However, limited information exists regarding the alterations in the biopsychosocial aspects of older adults during and after the COVID-19 movement restrictions, as well as their association. The objective of this study is to investigate the biopsychosocial dynamics associated with navigating transportation during and after the recovery phase of COVID-19 pandemic. Additionally, it aims to determine the association between transportation independence status and various biopsychosocial factors. Methods: A sub-sample of 100 individuals aged 60 years and above (mean age ± SD: 68.4 ± 5.3), from earlier cross-sectional study were recruited in a one year follow up study. Face-to-face interviews were conducted by the same researcher from baseline to obtain older adults’ sociodemographic health status, anthropometric measurements, functional status, depressive symptoms, nutritional status, cognitive status, visual assessment, physical activity and physical performance and transportation independence. Bivariate logistic regression was performed to examine the association. Results: While there were no significant changes in transportation independence among older adults during and after the COVID-19 movement restriction, there were noticeable increases in outdoor mobility and certain changes in biopsychosocial factors. Results revealed higher fat mass (Adj OR = 1.20, 95% CI: 1.03–1.41, p < 0.05), poorer performance in Timed up and Go (TUG) (Adj OR = 1.40, 95% CI: 1.03–1.88, p < 0.05) test, poorer Hand Grip Strength (HGS) (Adj OR = .85, 95% CI: .74–.98, p < 0.05) and changes in Instrumental Activities of Daily Living (IADL) (p < 0.05) are associated with restricted transportation in older adults. Conclusion: The findings of this study highlight the importance of biopsychosocial health factors, such as body composition, physical performance, and function, which may be influenced by transportation independence among older adults.</p
Long-tailed recognition via key attribute learning
No full textDeep learning models often struggle with datasets exhibiting long-tailed distributions, where the majority of data is concentrated in a few categories, leaving many with very few samples. This imbalance results in models favouring well-represented categories, leading to poorer performance for those with fewer instances. Existing methodologies focus on addressing class-wise imbalance but disregard the attribute-wise disparities. By assigning equal weight to each instance within a class, these approaches overlook the long-tailed distribution of attributes, thus underrepresenting information from infrequent attributes. The reduction in feature diversity consequently diminishes model performance. To address this challenge, we introduce an innovative methodology, namely Key Attribute Learning (KAL). It emphasises the importance of less common attributes by utilising the Instance Diversity Index (IDI) to assess and prioritise attribute diversity for each instance. KAL effectively expands feature margins among categories and addresses the overfitting problem. Our results demonstrate that KAL is non-invasive in both single-model and Mixture of Experts (MoE) settings. Implementing our method on BalPoE, we attained state-of-the-art (SOTA) performance on CIFAR-100-im100, ImageNet-LT, and iNaturalist datasets, showcasing its broad applicability and significant improvements across both balanced and diverse test distributions.</p
A 'New' Old Welsh Personal Name
No full textThis paper gives a new reading of an Old Welsh personal name from the Book of St Chad, arguing that the same name might occur in Gerald of Wales's list of bishops and archbishops of St Davids. Possible etymologies are discussed, and the relationship of these Welsh names with an early medieval Breton personal name is considered. This entails a clarification of the development of intervocal /b m/ in the Brittonic languages
"Pepita Jiménez" and the British critics (1882-1892):The Soul of Spain
No full textDespite the impact of Juan Valera's Pepita Jiménez on literature since its publication in 1874, it was not universally appreciated by critics in the nineteenth century. The exegesis of the novel diverged, viewing in it a possible mysticism or what could plausibly be considered a mystical satire. While bearing in mind such common criticisms in the context of Spain, this article focuses on the novel's reception by British critics between 1882 and 1892 who saw in the novel the quintessence of mystical-religious form and content, with a praise-worthy moral framework. These opinions differed from the critical views espoused by the Spanish neo-Catholic press. The critical judgments of Wentworth Webster, Edmund Gosse, Arthur Symons, and especially Coventry Patmore, among others, as well as the endorsements by William Howells and James Russell Lowell in the United States, would catapult Anglo-American interest in and recognition of the novel, to such an extent that its defects were buried for the sake of its defense of morality and religion. It would thus be judged as one of the best works of fiction published in Europe since the middle of the nineteenth century, thereby predicting the work's inclusion in the Spanish literary canon (JMGP).</p
Quantum Time Travel Revisited:Noncommutative Möbius Transformations and Time Loops
No full textWe extend the theory of quantum time loops introduced by Greenberger and Svozil [1] from the scalar situation (where paths have just an associated complex amplitude) to the general situation where the time traveling system has multidimensional underlying Hilbert space. The main mathematical tool that emerges is the noncommutative Möbius Transformation and this affords a formalism similar to the modular structure well known to feedback control problems. The self-consistency issues that plague other approaches do not arise here, as we do not consider completely closed time loops. We argue that a sum-over-all-paths approach may be carried out in the scalar case but quickly becomes unwieldy in the general case. It is natural to replace the beam splitters of [1] with more general components having their own quantum structure, in which case the theory starts to resemble the quantum feedback network theory for open quantum optical models and indeed we exploit this to look at more realistic physical models of time loops. We analyze some Grandfather paradoxes in the new setting
Tin, secret societies, and the slow development of the Chinese mining community in a Siam-Burma border village of Maliwun, 1840s–1890s
No full textThis article reconstructs the mining practices and social activities of Chinese migrants in Maliwun, a tin-rich Burmese village on the Siam-Burma border between the 1840s and 1890s. Despite its natural resources and repeated mining attempts by various stakeholders, Maliwun could not materialise its potential and was slow in tin production and community development throughout this period. By focusing on the internal dynamics among its Chinese miners, especially around the rivalling Chinese “secret societies,” this article situates the frontier mining settlement within a larger regional network of the Southeast Asian Chinese and traces its Chinese community’s evolving relationships with fellow countrymen along the southern Siamese and northern Malayan coastlines. It argues that grassroots organisations played a crucial role in the early formation of this frontier Chinese migrant community, which was sitting at the intersection of political, labour, resource, gender, and ethnic frontiers and exhibited key features of fluid boundaries and transnational networks. Yet, these impacts should not be overstated, individually or collectively. The slow development of Maliwun calls for a careful reassessment of the limitation of roles played by porous borders, hybrid interactions, and transnational networks at a historic frontier.</p
Partial unified learning for dynamic change detection in hyperspectral images
No full textHyperspectral image change detection (HSI-CD) aims to identify changes in bi-temporal hyperspectral images (HSIs) captured at different times in the same location. Existing algorithms often overlook the inherent class imbalance in HSI-CD, leading to poor generalization in detecting changes while introducing redundant computation in unchanged regions. This paper introduces a novel mechanism based on Partial Unified Learning for Dynamic Change Detection (PUL-DCD) to address these limitations. Particularly, a novel partial unified learning network is proposed, whose backbone is trained using multiple datasets, whilst the task-specific networks are trained independently with each individual dataset. In so doing, the network can maintain outstanding performance on specific datasets while having strong generalization ability. Furthermore, an innovative dynamic architecture is introduced that distinguishes between easy and hard regions for change detection, thereby optimizing parameter configuration and enhancing detection performance in challenging areas, while mitigating redundancy regarding unchanged information. Experimental results on three datasets show that PUL-DCD is competitive in both accuracy and efficiency.</p