bluuebunny/crossref_metadata_2025 huggingface dataset:
Looking to the past, considering the present and preparing for the future: digital technologies and the business model canvas
Authors: Matricano Diego , Liguori Eric W.
Published: October 2024

Purpose

This paper aims to propose a reconfiguration of the business model canvas (BMC) to highlight the relevant, and often critical, role of digital technologies (DTs).

Design/methodology/approach

The authors review the business model literature to further clarify its dynamic nature (expressed by innovation, adaptation and experimentation) and the factors that may affect it. Ultimately, to better capture the role of DTs, the authors posit a new iteration of the BMC (namely, the digital business model canvas [DiBMC]).

Findings

Historically, DTs were not clearly represented in the BMC, often resulting in them being disparately woven into other boxes or not clearly captured at all. By reconfiguring the nine original building blocks, and adding two new ones related to DTs, the DiBMC supports a more complete visualization of how value is created and the role of DTs.

Originality/value

DTs are too relevant in today’s business environment to not more formally model them on BMCs. The proposed reconfiguration of the BMC into the DiBMC improves the utility of the tool for practitioners, scholars and students alike.
Creditor rights and investment sensitivity: evidence from an emerging market
Authors: Tripathi Pranshu , Sharma Anil K.
Published: October 2024

Purpose

Creditor rights reduce or increase agency problems in corporations, affecting financial decisions. This study examines the impact of India’s Insolvency and Bankruptcy Code of 2016 (hereinafter referred to as the Code) on firms’ investment and investment sensitivity based on their health, considering this Code as more creditor-friendly than pre-existing bankruptcy laws.

Design/methodology/approach

This study uses a quasi-natural experiment that employs the difference-in-differences (DID) and propensity score matching difference-in-differences (PSM DiD) approach by considering the Code as treatment and categorizing the firms into distressed (treated group) and healthy (control group) firms. For the purpose of analysis, a fixed-effect regression model is used.

Findings

This study finds that distressed firms reduce their investment after the Code, but healthy firms do not observe any change. It shows that the reduction in investment of the distressed group is significantly greater than that of the healthy group due to agency conflict and the liquidation bias hypothesis. However, the reduction in investment is not followed by the change in investment sensitivity.

Originality/value

This study adds to the existing studies on the impact of the Insolvency and Bankruptcy Code, 2016 on investment. No study explores the relationship between this Code and investment based on the financial health of the firms. Also, none of the studies explores the impact of the Code on investment sensitivity. The results show that this Code has provided stronger protection to the creditors, which hurts the internal stakeholders’ interests. The study has implications for policymakers and academicians.
Comparable yet distinct: a systematic review of social and small and medium-sized enterprises growth trajectories
Authors: Figueroa Herrera María Fernanda , Murcia María José
Published: October 2024

Purpose

This study aims to expand the concept of business growth by incorporating sustainability demands, particularly in the context of the Anthropocene era. It explores the growth trajectories of social enterprises (SEs) and small and medium-sized enterprises (SMEs), examining how SEs integrate social and environmental objectives into their growth process. Through a systematic literature review (SLR), this study compares these approaches with traditional SME growth paradigms, highlighting the need for a holistic understanding of business growth that addresses contemporary socioenvironmental challenges.

Design/methodology/approach

A qualitative SLR was conducted, using a structured search algorithm to identify and evaluate research on growth and scaling in SMEs and SEs. The search of the Web of Science database with specific growth-related keywords yielded 5,362 articles, which were narrowed to 194 after filtering by journal relevance. Content analysis, guided by an inductively developed codebook, examined growth definitions, operationalizations, and methodologies. This paper focused on key growth dimensions (economic, social and environmental) and identified whether growth was addressed as an outcome or process, along with its enablers and barriers.

Findings

While there are areas of intersection between the literatures, the findings reveal that traditional SME growth frameworks do not entirely align with SEs growth conception and management. Furthermore, SE’s growth barriers and facilitators, as well as growth trajectories more broadly, emerge as distinct from those of traditional SMEs. The results distill insights from SE growth paths that can be valuable for traditional SME managers, particularly in terms of managing stakeholders and the institutional environment. Social entrepreneurs commonly use strategies for reshaping business norms, influencing consumer culture and raising social issues awareness, leveraging the values of stakeholders to secure essential support.

Originality/value

As SMEs confront escalating pressure to align with the sustainable development agenda, the findings underscore the critical significance of drawing insights from the burgeoning SE growth literature. This suggests that traditional SME growth literature stands to gain invaluable insights from recent SE research, fostering a more nuanced comprehension of sustainability-centric SME growth trajectories.
Large invasive herbaceous plants decrease the taxonomic, functional and phylogenetic diversity of birds via their reproductive traits
Authors: Grzędzicka Emilia , Reif Jiří , Hanzelka Jan
Published: October 2024

Birds are among the organisms most impacted by plant invasions, the effects of which are particularly conspicuous during the breeding season. Birds can incorrectly assess the suitability of large, invasive hogweeds Heracleum sp. in south‐eastern Poland when selecting nesting sites early in spring when the developing invaders do not yet differ substantially in form from the rest of the vegetation.

One would expect lower bird breeding success in areas with invasive hogweeds. Furthermore, this may shift bird community composition towards species with filtered traits, which may then be reflected in various measures of diversity. To assess these expectations, we conducted bird surveys at 74 sites, arranged as 37 pairs (with invasive Heracleum vs. control).

The presence of Heracleum was associated with lower bird taxonomic and phylogenetic diversity. Functional richness (calculated based on species' reproductive traits) was also lower at sites with these invaders. The species detected at Heracleum sites were characterised by traits associated with rapid breeding, for example, small clutches, short incubation periods and short fledging periods.

We show that the bird community at sites with hogweeds became less diverse and composed of random species sharing similar reproductive traits. Bird communities with low diversity at Heracleum sites tended to exhibit a common trait syndrome. These patterns provide insights into the mechanisms of how invasive plants may lead to the loss of some traits and species in bird communities.

Read the free Plain Language Summary for this article on the Journal blog.
The role of indirect interspecific effects in the stochastic dynamics of a simple trophic system
Authors: Bartra‐Cabré Laura , Hansen Brage B. , Lee Aline M. , Layton‐Matthews Kate , Loonen Maarten J. J. E. , Fuglei Eva , Loe Leif E. , Grøtan Vidar
Published: October 2024

Indirect interspecific effects (IIEs) occur when one species affects another through a third intermediary species. Understanding the role of IIEs in population dynamics is key for predicting community‐level impacts of environmental change. Yet, empirically teasing apart IIEs from other interactions and population drivers has proven challenging and data‐demanding, particularly in species‐rich communities.

We used stochastic population models parameterized with long‐term time series of individual data to simulate population trajectories and examine IIEs in a simple high‐arctic vertebrate food chain consisting of the wild Svalbard reindeer, its scavenger (the Arctic fox) and the barnacle goose, a migratory prey of the fox.

We used the simulated population trajectories to explore co‐fluctuations between the species within the food chain. Additionally, we adjusted the model in two ways: first, to isolate the impact of fluctuations in the abundance of a species by keeping its abundance constant; and second, to isolate the impact of a trophic interaction on the dynamics of other species by setting the abundance of the influencing species to zero.

We found that fluctuations in reindeer carcasses shaped fox abundance fluctuations, which subsequently affected goose population dynamics. Reindeer and goose population growth rates were nevertheless only weakly correlated, probably in part due to demographic and environmental stochasticity, density dependence and lagged dynamics in the geese. However, removing the fluctuations in reindeer abundance or setting reindeer abundance to zero indeed demonstrated strong underlying IIEs on goose population dynamics and extinction probability.

This study thus highlights the importance of species interactions, including IIEs, on species coexistence and communities in the long‐term, that is beyond immediate effects and covariation in short‐term fluctuations.
Impacts of wild herbivores on soil seed banks are explained by precipitation conditions in protected areas across semi‐arid to arid regions
Authors: Xu Tongtong , Cornwell Will , Wang Ling , Wijas Baptiste , Liu Chen , Yuan Zuoqiang , Letnic Mike
Published: October 2024

Protected areas form the backbone of global conservation efforts. Vegetation is the primary foundation for achieving conservation goals, and soil seed banks is a cryptic biodiversity reservoir for recruiting species that may not be represented in above‐ground vegetation. Unfortunately, unmanaged grazing by wild herbivores has led to vegetation degradation in semi‐arid to arid regions. However, experimental evidence on the long‐term impacts of wild herbivores on soil seed banks is largely lacking.

Here, with the aim of examining how wild herbivores impact soil seed banks, we investigated the composition of the germinable seed banks in three protected areas (Yathong, Mungo and Boolcoomatta) along a semi‐arid to arid precipitation gradient in south‐eastern Australia.

The density and species richness of the soil seed banks increased with increasing aridity, which indicated that the soil seed banks in arid regions is an important biodiversity reservoir. The effects of wild herbivores on soil seed density were strongly dependent on precipitation. Wild herbivores disrupted the soil seed banks at the most arid site but promoted the accumulation of seeds in the soil at the least arid site. Grazing was linked to an increase in the frequency of the seeds of introduced species and decrease in the frequency of the seeds of perennials.

Synthesis and applications: Disruption of the soil seed banks by the grazing of wild herbivores could lead to the failure of post‐rain pulses of vegetation growth and hamper efforts to restore vegetation in protected areas. Therefore, suppressing wild herbivore numbers is a strategy that could enhance soil seed bank reserves and revegetation efforts in arid protected areas.
Prevalence of clinical deterioration in the pre‐hospital setting
Authors: Bourke‐Matas Emma , Doan Tan , Bowles Kelly‐Ann , Bosley Emma
Published: October 2024

Objective

Improved understanding of the deteriorating patient in the pre‐hospital setting may result in earlier recognition and response. Considering the effects of undetected deterioration are profound, it is fundamental to report the prevalence of pre‐hospital clinical deterioration to advance our understanding. The present study investigated the prevalence of pre‐hospital clinical deterioration and adverse events (AEs) within 3 days of the pre‐hospital episode of care.

Methods

This retrospective cohort study was based on pre‐hospital incidents involving adult patients attended by Queensland Ambulance Service between 1 January 2018 and 31 December 2020. Due to lacking a standardised definition of pre‐hospital clinical deterioration, established early warning scores (NEWS, MEWS and Q‐ADDS) were calculated from pre‐hospital vital signs to identify clinical deterioration. Linked hospital data were used to identify the occurrence of an AE.

Results

Some degree of physiological derangement was initially observed in over half of the patients, and pre‐hospital clinical deterioration was seen in 2.7%–4% of patients. The prevalence of AEs was 3.2%. Patients that experienced an AE were more likely to be male, elderly, suffering from a medical (non‐trauma) condition, and had a greater burden of disease. Concerningly, almost 50% of patients that suffered an AE did not meet escalation thresholds of NEWS, MEWS or Q‐ADDS.

Conclusions

The present study found the prevalence of pre‐hospital clinical deterioration and AEs subsequent to pre‐hospital episodes of care to be low. Future research should prioritise using standardised criteria to define pre‐hospital clinical deterioration and evaluate the performance of early warning scores.
From ‘cooking wife’ to ‘cooking mother’: Exploring generational shifts in perceptions regarding domestic cooking practices
Authors: Mazzonetto Ana Claudia , Melo Jackeline Nass Machado , Dean Moira , Fiates Giovanna Medeiros Rataichesck
Published: October 2024

Aims

Utilising the life course perspective as the theoretical framework, we investigate how women from different generations perceive their cooking experiences and articulate their feelings regarding this activity.

Method

Following a review of the literature and four exploratory focus groups, an interview guide was developed and piloted. Interviews were conducted with 22 Brazilian women spanning three distinct generations. Participants were prompted to recall their life stories, spanning from childhood to the present day and focused on cooking‐related situations. Interviews were transcripted and analysed using reflexive thematic analysis.

Results

There were three major themes developed. The first theme outlines variations in the food context across generations. The second theme encompasses perceptions of the responsibility for cooking as being linked to the female gender, indicating a generational shift from the role of the ‘cooking wife’ to that of the ‘cooking mother’. The third theme explores thoughts and reflections on feelings of obligation, oppression, and liberation in cooking, tied to changes in the social and temporal context in which these women operate.

Conclusion

Strategies promoting cooking should consider the meanings attributed to it, contribute to the deconstruction of gender‐specific family dynamics, and encourage the pursuit for pleasure, satisfaction and autonomy in this practice. This study contributes novel insights into cooking, including reflections on obligation or oppression versus liberation and the evolving social roles of women as primary cooks.
Potential mechanisms of metabolic reprogramming induced by ischemia–reperfusion injury in diabetic myocardium
Authors: Ma Haiping , Zhao Jiyao , Zheng Yan , Wang Junjie , Anwar Yultuz , He Yuxuan , Wang Jiang
Published: October 2024

Objective

This study aimed to explore metabolic reprogramming in diabetic myocardium subjected to ischemia–reperfusion injury (I/RI) and potential mechanisms.

Background

Increased vulnerability after I/RI in diabetic myocardium is a major cause of the high prevalence of perioperative adverse cardiac events, and the specific alterations in energy metabolism after I/RI in diabetic myocardium and the impact on increased vulnerability are not fully understood.

Methods

Metabolomic methods were used to explore the differences and characteristics of metabolites in the heart tissues of four groups, and then, single‐cell RNA sequencing (ScRNA‐seq) was used to explore the potential mechanism of metabolic reprogramming.

Results

It was found that the fatty acid metabolism of db/db mouse I/RI (DMI) showed a significant upward trend, especially the metabolites of ultra‐long and medium‐long‐chain fatty acids; the metabolic flow analysis found that the U‐13C glucose M + 6 was significantly higher in the C57BL mouse sham operation (NM) group than in the db/db mouse sham operation (DM) group, and in the C57BL mouse I/RI (NMI) than in the DMI group. Compared with the NMI group, the intermediate metabolites of glycolysis and tricarboxylic acid (TCA) cycle were significantly reduced in the DMI group; all comparisons were statistically significant (p < 0.05), indicating that the glucose uptake of diabetic myocardetis, the ability of glucose glycolysis after I/RI, and the contribution of glucose to TCA were significantly reduced. The results of ScRNA‐seq revealed that the number of Cluster 0 myocardial isoforms was significantly increased in diabetic myocardium, and the differential genes were mainly enriched in fatty acid metabolism, and the PPARA signaling pathway was found to be over‐activated and involved in the regulation of metabolic reprogramming of diabetic myocardial I/RI.

Conclusion

Metabolic reprogramming of diabetic myocardial I/RI may be the main cause of increased myocardial vulnerability. The number of myocardial subtype Cluster 0 increased significantly, and PPARA PPARA is a ligand‐activated receptor of the nuclear hormone receptor family that plays a central regulatory role in lipid metabolism. signaling pathway activation may be a potential mechanism for reprogramming metabolism in diabetic myocardium.

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A comparison of joint species distribution models for percent cover data
Authors: Korhonen Pekka , Hui Francis K. C. , Niku Jenni , Taskinen Sara , van der Veen Bert
Published: October 2024

Joint species distribution models (JSDMs) have gained considerable traction among ecologists over the past decade, due to their capacity to answer a wide range of questions at both the species‐ and the community‐level. The family of generalised linear latent variable models in particular has proven popular for building JSDMs, being able to handle many response types including presence‐absence data, biomass, overdispersed and/or zero‐inflated counts.

We extend latent variable models to handle percent cover response variables, with vegetation, sessile invertebrate and macroalgal cover data representing the prime examples of such data arising in community ecology.

Sparsity is a commonly encountered challenge with percent cover data. Responses are typically recorded as percentages covered per plot, though some species may be completely absent or present, that is, have 0% or 100% cover, respectively, rendering the use of beta distribution inadequate.

We propose two JSDMs suitable for percent cover data, namely a hurdle beta model and an ordered beta model. We compare the two proposed approaches to a beta distribution for shifted responses, transformed presence‐absence data and an ordinal model for percent cover classes. Results demonstrate the hurdle beta JSDM was generally the most accurate at retrieving the latent variables and predicting ecological percent cover data.
Improving racial/ethnic health equity and naloxone access among people at risk for opioid overdose: A simulation modeling analysis of community‐based naloxone distribution strategies in Massachusetts, United States
Authors: Zang Xiao , Skinner Alexandra , Li Zongbo , Shaw Leah C. , Behrends Czarina N. , Chatterjee Avik , Jalali Ali , Jordan Ashly E. , Morgan Jake R. , Nolen Shayla , Schackman Bruce R. , Marshall Brandon D. L. , Walley Alexander Y.
Published: October 2024

Background and Aims

During the COVID‐19 pandemic, there was a surge in opioid overdose deaths (OODs) in Massachusetts, USA, particularly among Black and Hispanic/Latinx populations. Despite the increasing racial and ethnic disparities in OODs, there was no compensatory increase in naloxone distributed to these groups. We aimed to evaluate two community‐based naloxone expansion strategies, with the objective of identifying approaches that could mitigate mortality and racial and ethnic disparities in OODs.

Design

Individual‐based simulation model. We measured naloxone availability using naloxone kits per OOD and evaluated scenarios of achieving higher benchmarks for naloxone availability (i.e. 40, 60 and 80 kits per OOD) from 2022 levels (overall: 26.0, White: 28.8, Black: 17.3, Hispanic/Latinx: 18.9). We compared two naloxone distribution strategies: (1) proportional distribution: achieving the benchmark ratio at the overall population level while distributing additional kits proportional to the 2022 level for each racial/ethnic group (at 40 kits per OOD benchmark: overall: 40, White: 44.3, Black: 26.6, Hispanic/Latinx: 29.1), and (2) equity‐focused distribution: achieving the benchmark ratio among each racial/ethnic group (at 40 kits per OOD benchmark: 40 for all groups).

Setting

Massachusetts, United States.

Participants

People at risk of OOD.

Measurements

Annual number and rate of OODs, total healthcare costs of increasing naloxone availability.

Findings

Both naloxone distribution strategies yielded comparable predicted reductions in total OODs in 2025 and incurred similar incremental costs. However, the relative reduction in the rate of OODs differed across groups. For achieving an 80 kits per OOD benchmark, proportional distribution resulted in a projected 6.7%, 6.5% and 7.1% reduction in annual OODs in 2025 among White, Black and Hispanic/Latinx populations, respectively. In contrast, equity‐focused distribution achieved a reduction of 5.7%, 11.3% and 10.2% in the respective groups. In all scenarios, the cost per OOD averted was lower than the generally accepted thresholds for cost per life saved.

Conclusions

An equity‐focused naloxone distribution strategy designed to reduce racial and ethnic disparities in naloxone availability could improve health equity among racial and ethnic groups while potentially improving overall population health at lower healthcare costs per opioid overdose death averted than a proportional distribution strategy.
Predicting Spontaneous Termination of Atrial Fibrillation Based on Analysis of Standard Electrocardiograms: A Systematic Review
Authors: Wadforth Brandon , Goh Jing Soong , Tiver Kathryn , Shahrbabaki Sobhan Salari , Tonchev Ivaylo , Dharmaprani Dhani , Ganesan Anand N.
Published: October 2024

Background

Forward prediction of atrial fibrillation (AF) termination is a challenging technical problem of increasing significance due to rising AF presentations to emergency departments worldwide. The ability to non‐invasively predict which AF episodes will terminate has important implications in terms of clinical decision‐making surrounding treatment and admission, with subsequent impacts on hospital capacity and the economic cost of AF hospitalizations.

Methods and Results

MEDLINE, EMCare, CINAHL, CENTRAL, and SCOPUS were searched on 29 July 2023 for articles where an attempt to predict AF termination was made using standard surface ECG recordings. The final review included 35 articles. Signal processing techniques fit into three broad categories including machine learning (n = 14), entropy analysis (n = 12), and time–frequency/frequency analysis (n = 9). Retrospectively processed ECG data was used in all studies with no prospective validation studies. Most studies (n = 33) utilized the same ECG database, which included recordings that either terminated within 1 min or continued for over 1 h. There was no significant difference in accuracy between groups (H(2) = 0.058, p‐value = 0.971). Only one study assessed recordings earlier than several minutes preceding termination, achieving 92% accuracy using the central 10 s of paroxysmal episodes lasting up to 174.

Conclusions

No studies attempted to forward predict AF termination in real‐time, representing an opportunity for novel prospective validation studies. Multiple signal processing techniques have proven accurate in predicting AF termination utilizing ECG recordings sourced from a database retrospectively.
Evaluation of five different methods for diagnosis of Helicobacter pylori from fecal samples
Authors: Horsma‐Heikkinen Jenni , Pätäri‐Sampo Anu , Holma Tanja , Nevalainen Annika , Friberg Nathalie , Jarva Hanna , Loginov Raisa , Antikainen Jenni
Published: October 2024

Accurate detection of Helicobacter pylori and its antimicrobial resistance is essential for eradication of the infections. The aim of this study was to compare five different CE‐IVD marked assays in detection of H. pylori from 268 clinical stool samples. Samples were considered positive for H. pylori when at least three of the five tests were positive. Amplified IDEIA Hp StAR (Oxoid) and Premier Platinum HpSA PLUS (Meridian Bioscience Inc.) assays showed sensitivity of 100% [95% CI (confidence interval): 87–100] and LIAISON® Meridian H. pylori SA (DiaSorin) of 83.3% (95% CI: 66–93). Specificities of the assays were 94.5% (95% CI: 91–97), 95.4%; (95% CI: 92–97), and 97.1% (95% CI: 94–99) respectively. Amplidiag® H. pylori + ClariR (Mobidiag) assay showed 93.3% (95% CI: 78–99) and Allplex™ H. pylori & ClariR Assay (Seegene Inc.) 36.7% (95% CI: 22–55) sensitivity, while specificity of both was 97.9% (95% CI: 95–99). The Amplidiag® and Allplex™ assays concordantly detected clarithromycin resistance in positive for H. pylori samples. The Amplidiag® assay showed the highest accuracy, namely 97.4% (95% CI: 95–99). These data provide helpful information for planning laboratory diagnostics of H. pylori and detection of clarithromycin resistance from stool samples.
CoupNeRF: Property‐aware Neural Radiance Fields for Multi‐Material Coupled Scenario Reconstruction
Authors: Li Jin , Gao Yang , Song Wenfeng , Li Yacong , Li Shuai , Hao Aimin , Qin Hong
Published: October 2024

Neural Radiance Fields (NeRFs) have achieved significant recognition for their proficiency in scene reconstruction and rendering by utilizing neural networks to depict intricate volumetric environments. Despite considerable research dedicated to reconstructing physical scenes, rare works succeed in challenging scenarios involving dynamic, multi‐material objects. To alleviate, we introduce CoupNeRF, an efficient neural network architecture that is aware of multiple material properties. This architecture combines physically grounded continuum mechanics with NeRF, facilitating the identification of motion systems across a wide range of physical coupling scenarios. We first reconstruct specific‐material of objects within 3D physical fields to learn material parameters. Then, we develop a method to model the neighbouring particles, enhancing the learning process specifically in regions where material transitions occur. The effectiveness of CoupNeRF is demonstrated through extensive experiments, showcasing its proficiency in accurately coupling and identifying the behavior of complex physical scenes that span multiple physics domains.
Gaussian in the Dark: Real‐Time View Synthesis From Inconsistent Dark Images Using Gaussian Splatting
Authors: Ye Sheng , Dong Zhen‐Hui , Hu Yubin , Wen Yu‐Hui , Liu Yong‐Jin
Published: October 2024

3D Gaussian Splatting has recently emerged as a powerful representation that can synthesize remarkable novel views using consistent multi‐view images as input. However, we notice that images captured in dark environments where the scenes are not fully illuminated can exhibit considerable brightness variations and multi‐view inconsistency, which poses great challenges to 3D Gaussian Splatting and severely degrades its performance. To tackle this problem, we propose Gaussian‐DK. Observing that inconsistencies are mainly caused by camera imaging, we represent a consistent radiance field of the physical world using a set of anisotropic 3D Gaussians, and design a camera response module to compensate for multi‐view inconsistencies. We also introduce a step‐based gradient scaling strategy to constrain Gaussians near the camera, which turn out to be floaters, from splitting and cloning. Experiments on our proposed benchmark dataset demonstrate that Gaussian‐DK produces high‐quality renderings without ghosting and floater artifacts and significantly outperforms existing methods. Furthermore, we can also synthesize light‐up images by controlling exposure levels that clearly show details in shadow areas.
DSGI‐Net: Density‐based Selective Grouping Point Cloud Learning Network for Indoor Scene
Authors: Wen Xin , Duan Yao , Xu Kai , Zhu Chenyang
Published: October 2024

Indoor scene point clouds exhibit diverse distributions and varying levels of sparsity, characterized by more intricate geometry and occlusion compared to outdoor scenes or individual objects. Despite recent advancements in 3D point cloud analysis introducing various network architectures, there remains a lack of frameworks tailored to the unique attributes of indoor scenarios. To address this, we propose DSGI‐Net, a novel indoor scene point cloud learning network that can be integrated into existing models. The key innovation of this work is selectively grouping more informative neighbor points in sparse regions and promoting semantic consistency of the local area where different instances are in proximity but belong to distinct categories. Furthermore, our method encodes both semantic and spatial relationships between points in local regions to reduce the loss of local geometric details. Extensive experiments on the ScanNetv2, SUN RGB‐D, and S3DIS indoor scene benchmarks demonstrate that our method is straightforward yet effective.
Density‐Aware Diffusion Model for Efficient Image Dehazing
Authors: Zhang Ling , Bai Wenxu , Xiao Chunxia
Published: October 2024

Existing image dehazing methods have made remarkable progress. However, they generally perform poorly on images with dense haze, and often suffer from unsatisfactory results with detail degradation or color distortion. In this paper, we propose a density‐aware diffusion model (DADM) for image dehazing. Guided by the haze density, our DADM can handle images with dense haze and complex environments. Specifically, we introduce a density‐aware dehazing network (DADNet) in the reverse diffusion process, which can help DADM gradually recover a clear haze‐free image from a haze image. To improve the performance of the network, we design a cross‐feature density extraction module (CDEModule) to extract the haze density for the image and a density‐guided feature fusion block (DFFBlock) to learn the effective contextual features. Furthermore, we introduce an indirect sampling strategy in the test sampling process, which not only suppresses the accumulation of errors but also ensures the stability of the results. Extensive experiments on popular benchmarks validate the superior performance of the proposed method. The code is released in https://github.com/benchacha/DADM.
CrystalNet: Texture‐Aware Neural Refraction Baking for Global Illumination
Authors: Zhang Z. , Simo‐Serra E.
Published: October 2024

Neural rendering bakes global illumination and other computationally costly effects into the weights of a neural network, allowing to efficiently synthesize photorealistic images without relying on path tracing. In neural rendering approaches, G‐buffers obtained from rasterization through direct rendering provide information regarding the scene such as position, normal, and textures to the neural network, achieving accurate and stable rendering quality in real‐time. However, due to the use of G‐buffers, existing methods struggle to accurately render transparency and refraction effects, as G‐buffers do not capture any ray information from multiple light ray bounces. This limitation results in blurriness, distortions, and loss of detail in rendered images that contain transparency and refraction, and is particularly notable in scenes with refracted objects that have high‐frequency textures. In this work, we propose a neural network architecture to encode critical rendering information, including texture coordinates from refracted rays, and enable reconstruction of high‐frequency textures in areas with refraction. Our approach is able to achieve accurate refraction rendering in challenging scenes with a diversity of overlapping transparent objects. Experimental results demonstrate that our method can interactively render high quality refraction effects with global illumination, unlike existing neural rendering approaches. Our code can be found at https://github.com/ziyangz5/CrystalNet
Spatially and Temporally Optimized Audio‐Driven Talking Face Generation
Authors: Dong Biao , Ma Bo‐Yao , Zhang Lei
Published: October 2024

Audio‐driven talking face generation is essentially a cross‐modal mapping from audio to video frames. The main challenge lies in the intricate one‐to‐many mapping, which affects lip sync accuracy. And the loss of facial details during image reconstruction often results in visual artifacts in the generated video. To overcome these challenges, this paper proposes to enhance the quality of generated talking faces with a new spatio‐temporal consistency. Specifically, the temporal consistency is achieved through consecutive frames of the each phoneme, which form temporal modules that exhibit similar lip appearance changes. This allows for adaptive adjustment in the lip movement for accurate sync. The spatial consistency pertains to the uniform distribution of textures within local regions, which form spatial modules and regulate the texture distribution in the generator. This yields fine details in the reconstructed facial images. Extensive experiments show that our method can generate more natural talking faces than previous state‐of‐the‐art methods in both accurate lip sync and realistic facial details.
Curved Image Triangulation Based on Differentiable Rendering
Authors: Wang Wanyi , Chen Zhonggui , Fang Lincong , Cao Juan
Published: October 2024

Image triangulation methods, which decompose an image into a series of triangles, are fundamental in artistic creation and image processing. This paper introduces a novel framework that integrates cubic Bézier curves into image triangulation, enabling the precise reconstruction of curved image features. Our developed framework constructs a well‐structured curved triangle mesh, effectively preventing overlaps between curves. A refined energy function, grounded in differentiable rendering, establishes a direct link between mesh geometry and rendering effects and is instrumental in guiding the curved mesh generation. Additionally, we derive an explicit gradient formula with respect to mesh parameters, facilitating the adaptive and efficient optimization of these parameters to fully leverage the capabilities of cubic Bézier curves. Through experimental and comparative analyses with state‐of‐the‐art methods, our approach demonstrates a significant enhancement in both numerical accuracy and visual quality.
GLTScene: Global‐to‐Local Transformers for Indoor Scene Synthesis with General Room Boundaries
Authors: Li Yijie , Xu Pengfei , Ren Junquan , Shao Zefan , Huang Hui
Published: October 2024

We present GLTScene, a novel data‐driven method for high‐quality furniture layout synthesis with general room boundaries as conditions. This task is challenging since the existing indoor scene datasets do not cover the variety of general room boundaries. We incorporate the interior design principles with learning techniques and adopt a global‐to‐local strategy for this task. Globally, we learn the placement of furniture objects from the datasets without considering their alignment. Locally, we learn the alignment of furniture objects relative to their nearest walls, according to the alignment principle in interior design. The global placement and local alignment of furniture objects are achieved by two transformers respectively. We compare our method with several baselines in the task of furniture layout synthesis with general room boundaries as conditions. Our method outperforms these baselines both quantitatively and qualitatively. We also demonstrate that our method can achieve other conditional layout synthesis tasks, including object‐level conditional generation and attribute‐level conditional generation. The code is publicly available at https://github.com/WWalter-Lee/GLTScene.
Controllable Anime Image Editing via Probability of Attribute Tags
Authors: Song Zhenghao , Mo Haoran , Gao Chengying
Published: October 2024

Editing anime images via probabilities of attribute tags allows controlling the degree of the manipulation in an intuitive and convenient manner. Existing methods fall short in the progressive modification and preservation of unintended regions in the input image. We propose a controllable anime image editing framework based on adjusting the tag probabilities, in which a probability encoding network (PEN) is developed to encode the probabilities into features that capture continuous characteristic of the probabilities. Thus, the encoded features are able to direct the generative process of a pre‐trained diffusion model and facilitate the linear manipulation. We also introduce a local editing module that automatically identifies the intended regions and constrains the edits to be applied to those regions only, which preserves the others unchanged. Comprehensive comparisons with existing methods indicate the effectiveness of our framework in both one‐shot and linear editing modes. Results in additional applications further demonstrate the generalization ability of our approach.
Adversarial Unsupervised Domain Adaptation for 3D Semantic Segmentation with 2D Image Fusion of Dense Depth
Authors: Zhang Xindan , Li Ying , Sheng Huankun , Zhang Xinnian
Published: October 2024

Unsupervised domain adaptation (UDA) is increasingly used for 3D point cloud semantic segmentation tasks due to its ability to address the issue of missing labels for new domains. However, most existing unsupervised domain adaptation methods focus only on uni‐modal data and are rarely applied to multi‐modal data. Therefore, we propose a cross‐modal UDA on multi‐modal datasets that contain 3D point clouds and 2D images for 3D Semantic Segmentation. Specifically, we first propose a Dual discriminator‐based Domain Adaptation (Dd‐bDA) module to enhance the adaptability of different domains. Second, given that the robustness of depth information to domain shifts can provide more details for semantic segmentation, we further employ a Dense depth Feature Fusion (DdFF) module to extract image features with rich depth cues. We evaluate our model in four unsupervised domain adaptation scenarios, i.e., dataset‐to‐dataset (A2D2 → SemanticKITTI), Day‐to‐Night, country‐to‐country (USA → Singapore), and synthetic‐to‐real (VirtualKITTI → SemanticKITTI). In all settings, the experimental results achieve significant improvements and surpass state‐of‐the‐art models.
Acceptability and quality of the ‘Grog Survey App’ brief intervention: Helping Aboriginal Australians reflect on their drinking using a digital health tool
Authors: Lee KS Kylie , Conigrave James H. , Dale Elizabeth , Conigrave Katherine M. , Dzidowska Monika , Reynolds Taleah , Wilson Scott , Perry Jimmy , Manton Danielle , Lee Alex , Hayman Noel , Zheng Catherine , Fitts Michelle , Wilson Dan , Dawson Angela
Published: October 2024

Introduction

The Grog Survey App is a validated, visual and interactive self‐administered application for tablet computers that is designed to help Aboriginal Australians describe their alcohol consumption. Each person who completes the App also receives a brief intervention with feedback tailored to their survey responses. We aimed to qualitatively assess the acceptability and perceived quality of the Grog App's brief intervention, among higher risk consumers and health providers at an Aboriginal residential rehabilitation centre.

Methods

This descriptive qualitative study analysed feedback from clients (n = 20) and staff (n = 10) of a drug and alcohol residential rehabilitation service on the brief intervention element of the Grog App. Data were collected face‐to‐face via semi‐structured interviews over four consecutive weeks between May and June 2021. A content analysis was conducted, which was informed by the Mobile App Rating Scale (MARS).

Results

Client and staff feedback is summarised using four themes from the MARS framework: (i) aesthetics; (ii) engagement; (iii) functionality; and (iv) information. Most clients and staff felt like health messages on the brief intervention were written by ‘someone who understands’. Overall, clients and staff described the brief intervention as visually appealing, engaging and likely able to elicit ‘lightbulb moments’.

Discussion and Conclusion

The brief intervention on the Grog App is unique in its provision of tailored advice based on survey responses to all individuals (i.e., those who do not drink through to those with likely dependence). Further research is needed to assess effectiveness of this brief intervention.
Carcinoembryonic antigen‐related cell adhesion molecule 1 in cancer: Blessing or curse?
Authors: Götz Lisa , Rueckschloss Uwe , Najjar Sonia M. , Ergün Süleyman , Kleefeldt Florian
Published: October 2024

The Carcinoembryonic antigen‐related cell adhesion molecule 1 (CEACAM1, also CD66a), a transmembrane glycoprotein of the immunoglobulin superfamily, is a pivotal mediator of various physiological and pathological processes, including oncologic disorders. However, its precise role in tumorigenicity is contradictory discussed by several clinical studies. This review aims to elucidate the clinical significance of CEACAM1 in different cancer entities focusing on tumour formation, progression and metastasis as well as on CEACAM1‐mediated treatment resistance. Furthermore, we discuss the contribution of CEACAM1 to cancer immunity and modulation of the inflammatory microenvironment and finally provide a comprehensive review of treatment regimens targeting this molecule.
Study on changes of bioactive substances and flavour characteristics during fermentation of jujube vinegar
Authors: Zhao Shimin , Tang Fengxian , Zhang Yao , Cai Wenchao , Zhang Qin , Zhao Xinxin , Shan Chunhui
Published: October 2024

Jujubes are an excellent source of sugar and nutrients, making them well‐suited for fermentation. Previous research on jujubes has primarily focused on their use in fermented beverages and fruit wines, but their potential for vinegar production has not been sufficiently explored. Therefore, this study produced jujube vinegar from jujube as raw material using microbial fermentation technology, and the changes in bioactive substances and volatile components during different fermentation stages were monitored. Results revealed that the primary organic acids in jujube vinegar were acetic acid, malic acid and lactic acid. The levels of phenolic compounds, such as epicatechin and ferulic acid, increased significantly by 3.5‐fold and 3.2‐fold, respectively, after acetic fermentation, resulting in an improvement in antioxidant activity. In addition, a total of seventy‐three volatile substances were detected in jujube vinegar, with acids accounting for 72.13% of the overall content. Isoamyl alcohol, ethyl phenylacetate, benzaldehyde and 3‐hydroxy‐2‐butanone were also the principal flavour compounds of jujube vinegar, which are the main source of its intense flavour. This study reveals the dynamic law of nutrients and flavour compounds during the fermentation process of jujube vinegar. The findings provide a theoretical reference and practical basis for the production of jujube vinegar.
Prevalence and influencing factors of cognitive frailty among Chinese older adults: A systematic review and meta‐analysis
Authors: Lin Xie , Nian Zhong , Yang Liu , Qing Zhang , Zhenjun Niu , Yanlin Heng
Published: October 2024

Aims

Cognitive frailty refers to the coexistence of physical frailty and cognitive impairment in older adults, without a concurrent diagnosis of Alzheimer's disease or other dementias. This review aims to evaluate the prevalence of CF subtypes and identify influencing factors among Chinese older adults.

Methods

The following databases were searched: PubMed/Medline, Embase, Cochrane Library, WOS, PsycINFO and CNKI et al (1 January 2001 to 20 October 2022). The risk of bias was assessed using the Agency for Healthcare Research and Quality Evidence‐based Practice Center Methods Guide. Stata 17.0 software was used to pool the prevalence of cognitive frailty, and the pooled odds ratio and 95% CI of the influencing factors were calculated.

Results

The meta‐analysis (56 studies and 80,320 participants) revealed the following prevalence rates: CF (18.9%), reversible CF (19.5%), potentially reversible CF (17.5%), CF in community‐dwelling older adults (14.3%), CF in nursing homes (22.7%) and CF in older inpatients (25.2%). Influential factors identified included age, gender, education, nutrition, depression, exercise, sleep and comorbidity.

Conclusions

The prevalence of CF among Chinese older adults is notably high, and it probably underestimates the prevalence of reversible cognitive frailty. It is crucial to encourage adherence to healthy behaviours, as it can effectively reduce and delay the onset of cognitive frailty.
Is seated voiding associated with lower urinary tract symptoms, health conditions, or marital status? Findings by age group from the 2023 Japan Community Health Survey
Authors: Sekido Noritoshi , Haga Nobuhiro , Omae Kenji , Kubota Yasue , Mitsui Takahiko , Masumori Naoya , Saito Motoaki , Sakakibara Ryuji , Yoshida Mikako , Takahashi Satoru
Published: October 2024

Objectives

Seated voiding may be an attempt to obviate voiding dysfunction, improve physical stability during voiding, and prevent messy bathroom contamination. Therefore, we hypothesized that seated voiders had a higher prevalence of lower urinary tract symptoms (LUTS), deteriorating health conditions, and a higher marriage rate than standing voiders.

Methods

Of the participants from the 2023 Japan Community Health Survey conducted by the Japanese Continence Society, 2936 men (mean age: 53.6 years old) were divided into sitting and standing groups based on their posture when voiding at home. Characteristics of the two groups were compared, and factors associated with seated voiding stratified by age were investigated using multivariable logistic regression analysis.

Results

One‐thousand six‐hundred and sixty men (57%) voided in the sitting position at home, and the proportion of seated voiding decreased with age. On multivariable analysis, comorbidities other than benign prostatic hyperplasia were associated with the standing group aged 40–59, and storage symptoms were associated with the seated group aged 60 and older. Being married was significantly and consistently associated with seated voiding across all ages.

Conclusions

Approximately 60% of Japanese men void in the sitting position at home. There are certain differences in the associations of LUTS and health conditions with voiding position by age, while seated voiding is consistently associated with marital status throughout all ages, which implies that sanitation matters.
Disruptive Timetables and Frameworks Within the Gamification of Critique and Peer Review
Authors: Makemson Justin B.
Published: October 2024

Researchers define gamification as the phenomenon of creating “gameful experiences” and the use of “game mechanics” in non‐gaming contexts (Deterding et al. 2011; Hamari et al. 2014). Gamification within education is the translation of design elements historically associated with gaming, e.g., embodiment, restructured timetables, probability, risk and reward, into the design of pedagogical approaches towards the goal of increasing student motivation, responsiveness and self‐determination. The following article examines the gamification of critiques and peer‐reviews as an evidence‐based best practice and disruptive innovation before outlining examples of critique games. The critique games in this article disrupt instinctive response frameworks and timetables and provide alternatives to more conventional critique and peer‐review practices.