Faithful Representation Research Articles

Sodium-Glucose Cotransporter-2 Inhibition Normalizes Metabolic Derangements in the Ischemic Myocardium

IntroductionSodium-glucose cotransporter-2 inhibitors (SGLT2i) have shown efficacy in the context of heart failure but have not been well-studied in ischemic heart disease. We employed a large animal model of chronic coronary artery disease and metabolic syndrome (MS) to investigate the hemodynamic and metabolic consequences of SGLT2i administration. MethodsThirty-eight Yorkshire swine were divided into two groups, with half (n = 21) receiving a high fat diet to induce MS, and the other half fed a standard diet (n = 17). All animals underwent thoracotomy for ameroid constrictor placement over the left circumflex coronary artery. Treatment with SGLT2i was then initiated, generating four groups: regular diet placebo (CON, n = 9), regular diet canagliflozin (n = 8), high-fat control (n = 11), and high-fat canagliflozin (n = 10). After 5 wks, all animals underwent terminal myocardial harvest with pressure-volume loop acquisition, perfusion studies, and tissue resection for molecular analysis. ResultsSGLT2i improved multiple measures of myocardial performance, including a nearly 1.5-fold increase in both cardiac output and ejection fraction; these changes were associated with augmented capillary density and a twofold increase perfusion to the ischemic myocardium. These augmentations were blunted; however, in the presence of MS, and associated with modulated myocardial expression of multiple major metabolic enzymes. ConclusionsSGLT2i significantly improved cardiac function in our large animal model of coronary artery disease, with metabolic modulation of the myocardial tissue serving as a candidate account of these changes. The blunting seen with MS underscores the dependence of clinical translatability on faithful representation of the biochemical environment of human disease.

SpaInGNN: Enhanced clustering and integration of spatial transcriptomics based on refined graph neural networks

Recent developments in spatial transcriptomics (ST) technology have markedly enhanced the proposed capacity to comprehensively characterize gene expression patterns within tissue microenvironments while crucially preserving spatial context. However, the identification of spatial domains at the single-cell level remains a significant challenge in elucidating biological processes. To address this, SpaInGNN was developed, a sophisticated graph neural network (GNN) framework that accurately delineates spatial domains by integrating spatial location data, histological information, and gene expression profiles into low-dimensional latent embeddings. Additionally, to fully leverage spatial coordinate data, spatial integration using graph neural network (SpaInGNN) refines the graph constructed for spatial locations by incorporating both tissue image distance and Euclidean distance, following a pre-clustering of gene expression profiles. This refined graph is then embedded using a self-supervised GNN, which minimizes self-reconfiguration loss. By applying SpaInGNN to refined graphs across multiple consecutive tissue slices, this study mitigates the impact of batch effects in data analysis. The proposed method demonstrates substantial improvements in the accuracy of spatial domain recognition, providing a more faithful representation of the tissue organization in both mouse olfactory bulb and human lateral prefrontal cortex samples

Advanced waveform analysis of the electrocardiogram signals using complementary signal processing techniques to investigate the response to a QTc prolonging drug vs control

Abstract Background Thorough QTc (TQT) studies using Electrocardiogram (ECG) data, are a well-established method for testing the pro-arrhythmic propensity of drugs performed during safety studies as part of drug development. ECG analysis is currently reduced to simplified biomarkers, such as rate, intervals and amplitudes. However, ECG waveforms are complex and generally sampled with high fidelity (125-1000 Hz). Our novel mathematical method, Symmetric Projection Attractor Reconstruction (SPAR) analyses the morphology and variability of such waveforms, using every data point to generate a new, faithful 2D waveform representation termed an ‘attractor’. Moxifloxacin is a reversible blocker of the rapid component of the delayed rectifier, potassium current of the cardiac IKr potassium channel and has been shown to cause a mean increase of the QTc interval of 10–14 ms after an oral single dose of 400 mg. Separately, studies have shown that meals can alter QT interval as well as altering the pharmacokinetic profile of moxifloxacin itself with gender and ethnicity impacting individual responses. In-depth knowledge of these physiological factors could support safer medicines development and clinical use. Purpose This project investigated the feasibility of SPAR analysis of ECG signals to detect drug induced changes which a higher degree of sensitivity, to support safety evaluation during medicines development. Methods High resolution triplicate 12 lead ECG time-series data from a Phase one study of healthy human volunteers cross over of placebo, moxifloxacin or moxifloxacin + food was retrospectively analysed using SPAR. Using a bespoke software tool was used to perform SPAR analyses to transform ECG time-series into corresponding attractors. Corresponding single point measurements were previously obtained as part of the original Phase one study. Results Initial evaluation of attractors revealed high inter-individual variation, consistent with previous SPAR ECG analysis. Nevertheless, we identified changes in subjects receiving Moxifloxacin (six hour time point) when compared to those receiving placebo control. These changes were not as evident in previously obtained QT intervals. Conclusion This pilot study illustrates that SPAR is highlighting changes on the ECG that are less obvious from QT data alone. Further evaluation of the whole dataset to identify generalisable SPAR features, and their comparison with existing markers is now necessary. The individualised nature of ECGs and corresponding attractors indicates the method may have highest utility in personalised medicine, evaluating each individual’s change and hence individual risk to drug induced arrhythmia.Visualisations of SPAR analysis of ECGs

CryoVesNet: A dedicated framework for synaptic vesicle segmentation in cryo-electron tomograms.

Cryo-electron tomography (cryo-ET) has the potential to reveal cell structure down to atomic resolution. Nevertheless, cellular cryo-ET data is highly complex, requiring image segmentation for visualization and quantification of subcellular structures. Due to noise and anisotropic resolution in cryo-ET data, automatic segmentation based on classical computer vision approaches usually does not perform satisfactorily. Communication between neurons relies on neurotransmitter-filled synaptic vesicle (SV) exocytosis. Cryo-ET study of the spatial organization of SVs and their interconnections allows a better understanding of the mechanisms of exocytosis regulation. Accurate SV segmentation is a prerequisite to obtaining a faithful connectivity representation. Hundreds of SVs are present in a synapse, and their manual segmentation is a bottleneck. We addressed this by designing a workflow consisting of a convolutional network followed by post-processing steps. Alongside, we provide an interactive tool for accurately segmenting spherical vesicles. Our pipeline can in principle segment spherical vesicles in any cell type as well as extracellular and in vitro spherical vesicles.

The Visibility of Climate‐Related Disclosures by Large Australian Companies

Mobilising the work of Brighenti (2007), we assess the visibility of climate‐related disclosures across different reporting venues and sectors for the 2022 reporting period. We do so by analysing the content of the corporate reports of 28 ASX50 companies. This is supplemented by articles published in the Australian media and on prominent activist investor websites. We find that physical climate risks are often under‐reported or superficially addressed in company reports, whereas transition opportunities related to a low‐carbon economy are more frequently disclosed. This discrepancy suggests a pattern of selective disclosure emphasising more favourable outcomes and potentially obscuring the full spectrum of climate‐related risks and opportunities. In contrast, transition risks are supra‐visible because of the attention from media and activist investors—particularly in the energy and materials sectors. Our results reflect concerns raised by regulators with regard to greenhushing (the withholding of information) of physical and transition risks and greenwashing (exaggerated claims) of transition opportunities. We also find inconsistencies in reporting practice, with implications for comparability and the faithful representation of climate‐related information.

Developing illustrative examples for revenue recognition in credit card rewards programmes

Orientation: The literature does not provide illustrative examples of specific credit card rewards programme (CCRP) transactions.Research purpose: The objective of the research was to develop and confirm illustrative examples for co-brand CCRPs, complex CCRPs and CCRPs offering cash rewards after the effective date of International Financial Reporting Standard (IFRS) 15.Motivation for the study: Credit card rewards programme management in practice acknowledged the need for illustrative examples of accounting for CCRP transactions.Research approach/design and method: This qualitative study used document analysis to develop the illustrative examples; and to confirm the examples, the Delphi technique was applied.Main findings: Illustrative examples were developed (based on existing literature, including IFRS) that show the differences in accounting treatment based on the type of CCRP. The initial recognition of the award credits liability, the proportionate derecognition of the liability when award credits are redeemed, and a change in the expected redemption rate are included in the examples. The study also clearly indicates the differences in the structure and functioning of each type of CCRP that support the different accounting treatments suggested.Practical/managerial implications: This study contributes to practice by providing CCRPs with illustrative examples that could reduce uncertainty and inconsistencies in practice. The illustrative examples developed make the theory – specifically principle-based IFRS – more practical and could improve faithful representation, as well as make transactions easier to verify (audit).Contribution/value-add: This study underscores the need for educators to train students in applying principle-based standards like IFRS 15 to complex transactions, fostering critical thinking and workplace readiness.

Updating a Code for Teaching Ethical Visualizations

The prevalent paradigm for understanding what constitutes a ‘good’ data visualization, and what we are likely teaching business students, relates to a conventional wisdom of efficiency, clarity, transparency, and faithful representation of truth. Teaching about the ethics of visualizations seems to be largely absent from business school curricula. This paper suggests that business students who make and use visualizations should be taught to use a code of ethics for visualizations based not only on conventional wisdom, but also on ideas from the Machine Learning/AI and ‘ethical visualizations’ communities. Elaborating on Sheppard’s code, the code suggested here incorporates ideas about bias, transparency, user agency, and privacy. Ethical awareness and practice become even more important as more data collection, processing, and visualization is shifted to Machine Learning and Generative AI. A threshold model is adapted to understand when visualization decisions require more scrutiny. Ideas from the code and the threshold model are used to analyze choices made by the CDC’s COVID-19 Rapid Response Team for an early pandemic visualization that circulated widely beyond the initial report in which it appeared. This and other examples underscore the need for business professionals to consider their visualizations from the perspective of the code.

The Myth of the Classless Society: Henry Carey and the Anti-Labor Origins of U.S. Political Economy (1820s–1830s)

Abstract The essay argues that the idea of the United States as a classless society was never a faithful representation of the U.S. socioeconomic reality, but constituted a myth elaborated since the 1830s by the first generation of U.S. economists to oppose the insubordination of Northern white workers, their mobilization through strikes, their politicization of class, and their critique of wage labor. It was precisely to counter the workers’ discourse, the essay maintains, that the first U.S. economists, most importantly Henry Charles Carey (1793–1879), developed an ideological representation of U.S. society as a classless structure devoid of fixed boundaries, in which industrious individuals could improve their condition through labor and in which social positions reflected a scale of talents and merits. By studying the early writings of Carey, but also of Theodore Sedgwick (1780–1839), Francis Wayland (1796–1865), Henry Vethake (1791–1866), Alonzo Potter (1800–1865), and Francis Lieber (1800–1872), the essay shows how economists used the myth of the classless society to scientifically legitimize the coming of capitalism to the United States, as well as to delegitimize class conflict. This anti-labor reaction, the essay argues, marked the very emergence of political economy in the United States as a science aimed at justifying the order of society through a mystified representation of its power relations, while the myth of the classless society would persist as a fundamental ideological pillar in the legitimation and naturalization of American capitalism.

The influence of substantial intragranular orientation gradients on the micromechanical response of heavily-worked material

In this study, we employ high-energy X-ray characterization to examine the role of relatively large amounts of intragranular lattice misorientation – present after many thermomechanical processes – on the micromechanical response of Al-7085 with a modified T7452 temper. We utilize near-field high energy X-ray diffraction microscopy (HEDM) to measure three-dimensional (3D) spatial orientation fields, facilitated by a novel method that utilizes grain orientation envelopes measured using far-field HEDM to enable reconstruction of grains with intragranular orientation spreads greater than 20°. We then assess the consequences of consideration of intragranular orientation fields on the predicted deformation response of the sample through 3D micromechanical simulations of the forged Al-7085. We construct two virtual polycrystalline specimens for use in simulations: the first a faithful representation of the HEDM reconstruction, the second a microstructure with no intragranular misorientation (i.e., grain-averaged orientations). We find significant differences in the predicted deformation mechanism activation, distribution of stress, and distribution of plastic strain between simulations containing intragranular misorientation and those with grain-averaged orientations, indicating the necessity for consideration of intragranular orientation fields for accurate predictions. Further, the influence of elastic anisotropy is discussed, along with the effects of intragranular misorientation on fatigue life through the calculation and analysis of fatigue indicator parameters.

A physics-constraint neural network for CO2 storage in deep saline aquifers during injection and post-injection periods

CO2 capture and storage is a viable solution in the effort to mitigate global climate change. Deep saline aquifers, in particular, have emerged as promising storage options, owing to their vast capacity and widespread distribution. However, the task of proficiently monitoring and simulating CO2 behavior within these formations poses significant challenges. To address this, we introduce the physics-constraint neural network for CO2 storage (CO2PCNet), a model specifically designed for simulating and monitoring CO2 storage in deep saline aquifers during injection and post-injection periods. Recognizing the significant challenges in accurately modeling the distribution and movement of CO2 under varying permeability conditions, the CO2PCNet integrates the principles of physics with the robustness of deep learning, serving as a powerful surrogate model. The architecture of CO2PCNet starts with an encoder that adeptly processes spatial features from overall mole fraction (zCO2) and pressure fields (Pl), capturing the complex dynamics of a CO2 trajectory. By incorporating permeability information through a conditioning step, the network ensures a faithful representation of the influences on CO2 behavior in subsurface conditions. A ConvLSTM module subsequently discerns temporal evolutions, reflecting the real-world progression of CO2 plumes within the reservoir. Lastly, the decoder precisely reconstructs the predictive spatial profile of CO2 distribution. CO2PCNet, with its integration of convolutional layers, recurrent mechanisms, and physics-informed constraints, offers a refined approach to CO2 storage simulation. This model offers the potential of utilizing advanced computational methods in advancing CCS practices.

An evaluation of financial statement quality in pre-versus post-IFRS-7 implementation: the case of Iraqi banking industry

This study compares Iraqi banking financial statements before and after IFRS-7 financial instruments disclosure. “Nijmegen Centre for Economics (NiCE)” qualitative content analysis was used to assess financial statement quality, which was measured using NiCE disclosure index. This study analysed data using a paired sample test to meet its goals. After IFRS-7, financial reporting quality is represented by 2016–2018. Before IFRS-7, it was represented by 2013–2015. In addition, the OLS regression analysis was implemented to assess hypotheses, incorporating data from 24 Iraqi institutions. The univariate analysis (t-test) and OLS regression showed that IFRS-7 improves financial statement “relevance, faithful representation, comparability, and timeliness”. No correlation was found for “understandability”. This study is the first to use Iraqi data and the most recent disclosure index to test the relationship between financial figure quality before and after applying the IFRS-7 financial instruments disclosure standard in developing countries. The results help regulators and policymakers regulate IFRS in Iraq and suggest policy changes to ensure compliance. The findings have major implications for business and policy that executives, lawmakers, and stockholders should consider. This study is applicable to ME countries that share comparable institutional, cultural, and accounting framework characteristics.

Research on the English Translation of Culture-Bound Terms in Yi Dialect Oral Literature from the Perspective of Four-life Maxim

The accurate translation of culture-bound terms is vital for ensuring the faithful representation of ethnic minority oral literature. Analyzing the English translation of these terms can significantly promote minority cultures, offer a comprehensive view of China to the world, and enhance the narrative of Chinese stories. China’s Eco-Translatology, rooted in Eastern ecological wisdom, provides a framework for translation in the new era, emphasizing Four-life Maxim. Guided by this theory, this paper examines the English translation of culture-bound terms in the Yi oral literature Meige, providing a reference for translating China’s minority literature.

Virtual Investment Analysis (Metaverse) in Developing An IAS 38 as a Part of Future Accounting

Objectives: Rapid technological developments need to be responded to immediately by companies in order to achieve competitive advantage and businesses’ sustainability. The company may consider investing in technology (especially in the metaverse), and this has been applied by various large companies. The development of technology has implications for whether current accounting standards could accommodate all accounting treatments for virtual investments (the metaverse). IAS 38 regarding intangible assets is one part of the IFRS accounting standards that best accommodates Metaverse for transactions with a purpose for the long term and not to trade as main business activities, but not the whole accounting treatment. Hence, the aim of this study is to analyze the metaverse for accountants and propose developing an IAS 38 to accommodate that investment from recognition, measurement, presentation, and disclosure. Theoretical Framework: This study applies normative theory, syntactic theory and information quality theory in developing IAS 38 to reflect metaverse phenomena within the scope of the research. Method: This study applies deep interviews with six categories of accountants (public accountants, preparers, academicians, standards setters, regulators, and consultants) in Indonesia with a total of 14 informants and literature studies. Results and Discussion: The result showed that Metaverse is very useful for accountants, and IAS 38 still needs development to accommodate Metaverse with long-term investment and not trading as the main business activities. Research Implications: Six categories of accountants in this research could consider the benefit of metaverse to theirs operational and mitigate the risk of used of metaverse. In addition, Standards setters and stakeholders need to consider updating IAS 38 in order to achieve information quality about metaverse phenomenon. Originality/Value: The novelty of this research is that it proposes developing an IAS 38 regarding recognition, measurement, presentation, and disclosure to accommodate the metaverse in order to achieve faithful representation’s information quality in the metaverse.

From de Sitter to de Sitter: A Thermal Approach to Running Vacuum Cosmology and the Non-Canonical Scalar Field Description

The entire classical cosmological history between two extreme de Sitter vacuum solutions is discussed based on Einstein’s equations and non-equilibrium thermodynamics. The initial non-singular de Sitter state is characterised by a very high energy scale, which is equal or smaller than the reduced Planck mass. It is structurally unstable, and all of the continuous created matter, energy, and entropy of the material component comes from the irreversible flow powered by the primeval vacuum energy density. The analytical expression describing the running vacuum is obtained from the thermal approach. It opens a new perspective to solve the old puzzles and current observational challenges plaguing the cosmic concordance model driven by a rigid vacuum. Such a scenario is also modelled through a non-canonical scalar field. It is demonstrated that the resulting scalar field model is shown to be a step-by-step a faithful analytical representation of the thermal running vacuum cosmology.

When the barbarians came by sea: hunting and alienism in entangled Sino-Japanese visual cultures, 1550–1750

This article places a hunting screen, now in the Rijksmuseum Amsterdam, in the longue durée of intricate intra-Asian visual entanglements to elaborate on a ‘pathos formula’ that migrated across vast stretches of time and space. It proposes that a wide array of Chinese and Japanese paintings, screens, and porcelain objects produced between 1550 and 1750 followed established formulas of picturing foreign tropes that stereotypically viewed the non-Han and non-Japanese peoples as ‘barbarians.’ Historically, the northern nomadic peoples were depicted as powerful yet savage horse riders skilled in hunting and equestrian sports. To illuminate the afterlives of this shared East Asian visual legacy, key discussions include imitations of Southern Song paintings on hunting and the tragic fate of Wenji (a Chinese woman who returned to the Han empire after being captive for twelve years in the steppe), the Japanese Tartar screens, the gold-painted hunt screens produced in Macau for the galleon trade, and the carved lacquer screens manufactured along China’s southeast coast. Behind the pan-East Asian resurgence of this ‘pathos formula’, as this article suggests, three territorial and geopolitical shifts emerged as stimuli: Japan’s pursuit of overseas conquest, the rise of the Jurchens (and later, the Manchus), and the arrival of the maritime centuries in which the Europeans were predominantly engaged. The article concludes that the Amsterdam hunting screen was much more than a faithful representation of any specific event or collective, and followed a stereotypical view of the ‘Red-haired Barbarians’ (Dutch traders) who approached China by sea as nomads.

Reconstruction of ionospheric VTEC using empirical orthogonal function and its performance during extreme geomagnetic storm

This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis. These basis functions were derived using the Singular Value Decomposition of a matrix composed of pragmatic vertical Total Electron Content (VTEC) values collected across varied ionospheric conditions and measured over the region of interest. The reconstruction was achieved by linearly combining the appropriately chosen significant bases with corresponding weight factors. The reconstruction accuracy of the algorithm was found to be better than 4 TECU (TECU = 1016 electrons/m2) for more than 99.9 % of the time when tested over the complete year of 2016 with only eight basis vectors. The containment factor, defined here, indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high, aiding in improved algorithm performance. The performance, however, was found to be sensitive to the seasons and geomagnetic conditions. Deteriorated performance was observed when tested for the St. Patrick's Day storm data. The deterioration was attributed to the structural alteration of the ionospheric plasma density and the presence of atypical modes during the storm. The results ascertain the prospect of a faithful representation of the spatial distribution of the ionospheric VTEC using limited parametric variables, which may find utility in navigation, radar, and various other applications.

The Escape Velocity Profile of the Milky Way from Gaia DR3

The escape velocity profile of the Milky Way offers a crucial and independent measurement of its underlying mass distribution and dark matter (DM) properties. Using a sample of stars from the third data release of Gaia with 6D kinematics and strict quality cuts, we obtain an escape velocity profile of the Milky Way from 4 to 11 kpc in Galactocentric radius. To infer the escape velocity in radial bins, we model the tail of the stellar speed distribution with both traditional power-law models and a new functional form that we introduce. While power-law models tend to rely on extrapolation to high speeds, we find our new functional form gives the most faithful representation of the observed distribution. Using this for the escape velocity profile, we constrain the properties of the Milky Way’s DM halo modeled as a Navarro–Frenck–White profile. Combined with constraints from the circular velocity at the solar position, we obtain a concentration and mass of c200cDM=13.9−4.3+6.2 and M200cDM=0.55−0.14+0.15×1012M⊙ . This corresponds to a total Milky Way mass of M200c=0.64−0.14+0.15×1012M⊙ , which is on the low end of the historic range of the galaxy’s mass, but in line with other recent estimates.

Towards an ecologically valid naturalistic cognitive neuroscience of memory and event cognition

The landscape of human memory and event cognition research has witnessed a transformative journey toward the use of naturalistic contexts and tasks. In this review, we track this progression from abrupt, artificial stimuli used in extensively controlled laboratory experiments to more naturalistic tasks and stimuli that present a more faithful representation of the real world. We argue that in order to improve ecological validity, naturalistic study designs must consider the complexity of the cognitive phenomenon being studied. Then, we review the current state of “naturalistic” event segmentation studies and critically assess frequently employed movie stimuli. We evaluate recently developed tools like lifelogging and other extended reality technologies to help address the challenges we identified with existing naturalistic approaches. We conclude by offering some guidelines that can be used to design ecologically valid cognitive neuroscience studies of memory and event cognition.

Abstract Mo043: Advanced waveform analysis of the electrocardiogram signals using complementary signal processing techniques to investigate the response to a QTc prolonging drug vs control including food effect.

Background: Thorough QT studies using Electrocardiogram data, are a well-established method for testing the pro-arrhythmic propensity of drugs performed during drug development. ECG analysis is currently reduced to simplified biomarkers, such as rate, intervals and amplitudes. However, ECG waveforms are complex and generally sampled with high fidelity 125-1000 Hz. Our novel mathematical method, Symmetric Projection Attractor Reconstruction analyses the morphology and variability of such waveforms, using every data point to generate a new, faithful 2D waveform representation termed an attractor. Moxifloxacin know QT prolonging medicine and has been shown to cause a mean increase of the QTc interval of 10–14 mS after a single dose of 400 mg. Separately, studies have shown that meals can alter QT interval as well as altering the pharmacokinetic profile of moxifloxacin itself with gender and ethnicity impacting individual responses. In-depth knowledge of these physiological factors could support safer medicines development and clinical use. Purpose: This project investigated the feasibility of SPAR analysis of ECG signals to detect drug induced changes which a higher degree of sensitivity, to support safety evaluation during medicines development Methods: High resolution triplicate 12 lead ECG time-series data from a Phase one study of healthy human volunteers cross over of placebo, moxifloxacin or moxifloxacin + food was retrospectively analysed using SPAR at 0,1 and 6 hours. MATLAB bespoke software tool was used to perform SPAR analyses to transform ECG time-series into corresponding attractors. Corresponding single point measurements were previously obtained as part of the original Phase one study. Results: Initial evaluation of attractors revealed high inter-individual variation, consistent with previous SPAR ECG analysis. Nevertheless, we identified changes in subjects receiving Moxifloxacin +/- food vs placebo control. These changes were not as evident in previously obtained QT intervals. Conclusion: This pilot study illustrates that SPAR is highlighting changes on the ECG in fasted and fed states that are less obvious from QT data alone. Further evaluation of the whole dataset to identify generalisable SPAR features, and their comparison with existing markers is now necessary. The individualised nature of ECGs and corresponding attractors indicates the method may have highest utility in personalised medicine.

On the relation of character codegrees and the minimal faithful quasi-permutation representation degree of p-groups

For a finite group G, we denote by c ( G ) , the minimal degree of a faithful representation of G by quasi-permutation matrices over C . For an irreducible character χ of G, the codegree of χ is defined as cod ( χ ) = | G / ker ( χ ) | / χ ( 1 ) . In this article, we establish equality between c ( G ) and a Q ≥ 0 -sum of codegrees of some irreducible characters of a non-abelian p-group G of odd order. We also study the relation between c ( G ) and irreducible character codegrees for various classes of non-abelian p-groups, such as, p-groups with cyclic center, maximal class p-groups, GVZ p-groups, and others.