bluuebunny/crossref_metadata_2025 huggingface dataset:
Food safety knowledge and changes in practices and concerns of Indian families during the COVID-19 pandemic
Authors: Thakur Sunaina , Mathur Pulkit
Published: May 2022

Purpose

Unsafe food can lead to various foodborne diseases and even death, especially among children. This paper aims to assess food safety knowledge and changes in practices and concerns among adults ≥ 18 years during the coronavirus disease 2019 (COVID-19) pandemic.

Design/methodology/approach

A cross-sectional, web-based survey was conducted among 325 adults living in Northern India. Demographic data and information regarding their knowledge, practices and concerns about various food safety issues were collected to see if there were any changes due to the COVID-19 pandemic.

Findings

The results showed that the participants had slightly higher than average knowledge and good food safety practices with mean scores of 9.75 ± 2.23 and 24.87 ± 2.28, respectively. Contracting COVID-19 from food and food packaging materials was of high concern for more than 70% of the participants. Majority (> 80%) of them reported an increase in the frequency of handwashing. About 16% of the participants used chemical disinfectants for washing fruits and vegetables. An increase (57.5%) in the frequency of food label reading was also noted during the pandemic. Freshness and the general quality of food items (49.5%), safety of food (30.8%) and cost (18.2%) were the top drivers that influenced the purchase decision.

Originality/value

This study highlighted the need to send out clear messages on safe food handling practices and keeping the tempo up for sustaining good hygienic practices. This will help in reducing the risk of foodborne diseases.
The effects of concession timing, perceived fairness and aggressiveness on tax negotiation offers
Authors: Voon Yuen Hoong , Che Azmi Anna , Jayasingam Sharmila
Published: May 2022

Purpose

This study aims to examine the consequences of tax authorities’ use of concession-timing negotiation strategies on tax practitioners and their final proposed offers.

Design/methodology/approach

This is an experimental study conducted on tax practitioners using a design of 2 × 1, varying the tax authorities’ negotiation strategy (i.e. concession-gradual and concession-end strategies) across two levels.

Findings

The concessionary negotiation strategies adopted by tax authorities influence tax practitioners’ final proposed offers, their perceptions of fairness (i.e. distributive justice and procedural justice) and their aggressiveness of stance in tax audit negotiations.

Originality/value

This experimental study contributes to existing research on tax authority-tax practitioner negotiation models used during tax audits by providing the first evidence that concession timing matters. The study extends the negotiation model to include tax aggressiveness as a new variable and examines the indirect roles of fairness and offers in tax audit negotiations.
Personnel Review at age 50: a retrospective using bibliometric analysis
Authors: Varma Arup , Kumar Satish , Lim Weng Marc , Pandey Nitesh
Published: May 2022

Purpose

Personnel Review (PR) is a leading human resource management journal. The article endeavors to provide a retrospective of the journal to commemorate the journal's 50th anniversary.

Design/methodology/approach

The article employs a variety of bibliometric analysis techniques such as performance analysis, co-authorship analysis, bibliographic coupling, and negative binomial regression to provide a retrospective of PR.

Findings

The performance analysis suggests that PR has grown steadily in PR's publications and citations. Though most of PR's contributions originate from Europe, a geographical shift toward global contributions has been witnessed in recent years. Besides that, a culture of collaboration among PR authors has manifested and proliferated over time. Though a third of European studies are qualitative and more than 90% of Asian studies are quantitative, PR studies, as a whole, are moving away from conceptual and qualitative to empirical and quantitative research. Next, the bibliographic coupling of the PR corpus indicates five major themes—namely, human resource management policies and practices; personnel competency, experience, and well-being; career management and employee engagement; strategic human resource management; and organizational culture and workplace environment. Finally, the negative binomial regression reveals that article age, abstract and article length and number of keywords and references significantly drive PR citations.

Originality/value

The article represents the inaugural retrospective of PR.
Extended contextual validation of stakeholder approach to firm technology adoption: moderating and mediating relationships in an innovation eco-system
Authors: Doe Joshua Kofi , Van de Wetering Rogier , Honyenuga Ben , Versendaal Johan
Published: May 2022

Purpose

The need for context-specific adoption models led to the development of the firm technology adoption model (F-TAM) model. Among small to medium-scale enterprises (SMEs); however, firm-level factors were rather insignificant in engendering SME level adoption of technological innovation. This study aims to examine the effect of firm size and other moderating and mediating factors on the relationships between personal, firm, societal and technological factors proposed in the stakeholder-oriented F-TAM among SMEs.

Design/methodology/approach

A research instrument was developed, reviewed by experts, and pilot tested with a sample of 25 respondents. Data were purposively collected from four hundred (400) SMEs and analyzed with partial least squares structural equation modeling (PLS-SEM).

Findings

The study discovered that employees, societal and technological factors moderate the relationship between firm factors of adoption and firm adoption. Without these moderating effects, firm factors of adoption would have been insignificant at the SMEs’ level of organizational technology adoption. The study further discovered that firm size, as well as risk propensity, also affect the relationships proposed in the model.

Research limitations/implications

Data was collected on voluntary adoption from the most cosmopolitan area of a developing country. It, therefore, needs further contextual validation across the country and different countries.

Practical implications

The engagement of innovations in firms must be planned with employees and society as major stakeholders.

Originality/value

The significance of this finding is the study’s emphasis on an eco-system approach for examining the phenomenon of innovation adoption. To the best of the authors’ knowledge, this study is the first to examine the effect of firm characteristics on is proposed eco-system of stakeholders.
Below‐ground ecosystem engineers enhance biodiversity and function in a polluted ecosystem
Authors: Bugnot Ana B. , Gribben Paul E. , O'Connor Wayne A. , Erickson Katherine , Coleman Ross A. , Dafforn Katherine A.
Published: May 2022

Many important ecosystem functions are underpinned by below‐ground biodiversity and processes. Marine sediments, one of the most abundant habitats on earth, are essential to the mineralisation of organic matter. However, they are increasingly polluted by urban activities leading to the loss of biodiversity and the functions they provide. While traditional sediment remediation strategies are focussed on microbial and engineering solutions, we propose that the reintroduction of below‐ground ecosystem engineers (bioturbators) is important to rehabilitate polluted sediments and drive recovery of their functions in urban coastal ecosystems.

We tested this notion by introducing bioturbators to nutrient polluted sediments to assess their survival, as well as their capacity to drive biodiversity and oxygenation and their potential to remediate nutrient pollution. Polychaete wormsDiopatra aciculataand clamsKatelysiasp. were added to mesocosms (ex‐situ), and the worms also added to experimental plots in‐situ. Potential for remediation was assessed with measures of nutrient content.

All animals survived when introduced to polluted sediments and showed no evidence of sub‐lethal effects. Worms oxygenated sediments and reduced organic matter content by up to 50% in‐situ. The worms also drove shifts in the receiving communities at all locations and increased the number of taxa at one location. On the other hand, the effects of clams were variable, showing opposite effects in organic matter content at different sites and levels of pollution.

Synthesis and applications. Global seafloor habitats are becoming increasingly degraded and novel strategies that combine biodiversity restoration with remediation are urgently needed to return function. Tube‐building bioturbators can stimulate nutrient processing in sediments proving multiple functional outcomes, but these effects are dependent on the receiving environment. In areas with medium levels of pollution, they can kick‐start recovery in a feedback loop whereby bioturbation increases oxygenation and nutrient remediation, shifting sediment biodiversity and contributing to further recovery. This can drive long‐term changes in sediment communities, particularly in urban areas where unvegetated sediments are conspicuous.
Recent insights into oceanic dimethylsulfoniopropionate biosynthesis and catabolism
Authors: Shaw Deepak Kumar , Sekar Jegan , Ramalingam Prabavathy Vaiyapuri
Published: May 2022

Dimethylsulfoniopropionate (DMSP), a globally important organosulfur compound is produced in prodigious amounts (2.0 Pg sulfur) annually in the marine environment by phytoplankton, macroalgae, heterotrophic bacteria, some corals and certain higher plants. It is an important marine osmolyte and a major precursor molecule for the production of climate‐active volatile gas dimethyl sulfide (DMS). DMSP synthesis take place via three pathways: a transamination ‘pathway‐’ in some marine bacteria and algae, a Met‐methylation ‘pathway‐’ in angiosperms and bacteria and a decarboxylation ‘pathway‐’ in the dinoflagellate, Crypthecodinium. The enzymes DSYB and TpMMT are involved in the DMSP biosynthesis in eukaryotes while marine heterotrophic bacteria engage key enzymes such as DsyB and MmtN. Several marine bacterial communities import DMSP and degrade it via cleavage or demethylation pathways or oxidation pathway, thereby generating DMS, methanethiol, and dimethylsulfoxonium propionate, respectively. DMSP is cleaved through diverse DMSP lyase enzymes in bacteria and via Alma1 enzyme in phytoplankton. The demethylation pathway involves four different enzymes, namely DmdA, DmdB, DmdC and DmdD/AcuH. However, enzymes involved in the oxidation pathway have not been yet identified. We reviewed the recent advances on the synthesis and catabolism of DMSP and enzymes that are involved in these processes.
College Entrance Exams: A Modern “Shibboleth”?
Authors: Robinson Daniel , Wainer Howard
Published: May 2022

The Covid-19 pandemic led many US colleges to drop requirements for admissions tests. Daniel Robinson and Howard Wainer consider what the consequences of this decision might be – for students and universities
Did “Trumpists” Perform Worse in US Senate Election Polls?
Authors: Chen Sina , Körtner John
Published: May 2022

Support for Donald Trump was underestimated by pre-election polls in 2016 and 2020. In a new analysis, Sina Chen and John Körtner examine Senate pre-election polls and results for the years 2018 and 2020 to see how Trump-endorsed candidates fared compared to other Republican candidates
Governing extension and extending governance for Pacific organic farming
Authors: Carter Jennifer , Hollinsworth David
Published: May 2022

Organic farming in the Pacific region could provide higher‐than‐average premiums to small‐scale farmers. Thus, many farmers seek specific information on market access and internationally recognised global standards and third‐party certification. Agricultural extension work has changed in terms of formal and informal understanding and expression. Concomitantly, pluralist extension networks and innovation have replaced singular, publicly‐delivered extension services because of an increase in private commercial interests under prevailing neoliberal logics. Nevertheless, there are socio‐spatial barriers to farmers accessing extension and establishing relations with certifying bodies and some extension partners. Thus, agricultural extension experts will need to create new governance arrangements with local farmer groups as nodes within pluralist public–private–producer networks and regional information flows to support these groups and their accountability and trust with local constituents. In this article, we argue that geographically disparate local farmer groups should be supported by flatter governance of agricultural extension to better link local farmer nodes in comparable growing regions with other transnational local nodes, and with regional certification bodies. Aided by powerful supporting partners in such a plural extension network, this type of flat governance would build trans‐local connections that better situate small‐scale farming and food security as responsive to future uncertainties.
AntiV‐SGN: a universal antiviral strategy to combat both RNA and DNA viruses by destroying their nucleic acids without sequence limitation
Authors: Tian Kun , Qi Zhen , Chi Ying , Qiang Huanran , Wang Pei , Liu Yu , Zhou Guohua , Zhu Fengcai , Guo Qinglong , Xu Shu
Published: May 2022

Numerous viral outbreaks have threatened us throughout history. Here, we demonstrated a nucleic acid‐based antiviral strategy named AntiV‐SGN. Unlike those CRISPR‐mediated methods, AntiV‐SGN has advantages of no targets' sequence limitation, such as protospacer adjacent motif (PAM) or protospacer flanking sequence (PFS), being universal for both DNA and RNA viruses. AntiV‐SGN was composed of a FEN1 protein and specific hpDNAs targeting viruses' nucleic acid. Its antiviral ability was tested on SARS‐CoV‐2 and HBV respectively. Reporter assays in human cells first illustrated the feasibility of AntiV‐SGN. Then, it was verified that AntiV‐SGN destroyed about 50% of live RNAs of SARS‐CoV‐2 in Vero cells and 90% cccDNA of HBV in HepG2.2.15 cells. It was also able to remove viral DNA integrated into the host's genome. In the mouse model, AntiV‐SGN can be used to significantly reduce HBV expression at a level of 90%. Actually, in some cases, when viruses mutate to eliminate PAM/PFS or hosts were infected by both DNA and RNA viruses, AntiV‐SGN could be a choice. Collectively, this study provided a proof‐of‐concept antiviral strategy of AntiV‐SGN, which has potential clinical value for targeting a wide variety of human pathogens, both known and newly identified.
Toward a Robust Land Suitability Framework for Manure Management: Modeling Impacts and Evaluating Biophysical Characteristics
Authors: Saha Gourab K. , Cibin Raj , Elliott Herschel A. , Preisendanz Heather E.
Published: May 2022

Manure application at the right place, time, and rate is critical for sustainable manure management. A land suitability framework (LSF) was previously developed for identifying suitable areas for manure utilization considering landscape vulnerability. This study aimed to evaluate the developed LSF and provide insights to build a new robust LSF for manure utilization. The study (1) evaluates the potential environmental impacts of manure application compared to inorganic fertilization, (2) evaluates the robustness of the previously developed LSF, and (3) identifies landscape biophysical attributes driving manure nutrient loss. The fertilization scenarios were evaluated using the Soil and Water Assessment Tool (SWAT) in a case study watershed located in Pennsylvania, USA. SWAT‐simulated results showed 80% higher organic nitrogen loss and 44% lower nitrate loss with manure fertilization compared to inorganic fertilization scenarios. The previously developed LSF was a useful screening tool for identifying vulnerable areas for manure application. However, the simulation results indicated limitations in the LSF in representing the combined effect of multiple landscape biophysical attributes. The decision tree model using the landscape biophysical characteristics and nutrient loading simulations implied the LSF can be improved by considering soil biophysical characteristics. The study results provide critical insights toward developing a robust LSF for sustainable manure utilization.
Assessing the predictive power of step selection functions: How social and environmental interactions affect animal space use
Authors: Potts Jonathan R. , Börger Luca , Strickland Bronson K. , Street Garrett M.
Published: May 2022

The ability to predict animal space use patterns is a fundamental concern in changing environments. Such predictions require a detailed understanding of the movement mechanisms from which spatial distributions emerge. However, these are typically complex, multifaceted, and therefore difficult to uncover.

Here, we provide a methodological framework for uncovering the movement mechanisms necessary for building predictive models of animal space use. Our procedure begins by parametrising a movement model of each individual in a population using step selection analysis, from which we build an individual‐based model (IBM) of interacting individuals, derive predicted broad‐scale space use patterns from the IBM and then compare the predicted and empirical patterns. Importantly, discrepancies between these predicted and empirical patterns are used to formulate new hypotheses about the drivers of animal movement decisions and thus iteratively improve the model's predictive power. We demonstrate our method on a population of feral pigs in Mississippi, USA.

Our technique incorporates both social interactions between individuals and environmental drivers of movement. At each iteration of model construction, we were able to identify missing features to improve model prediction by analysing the IBM output. These include overuse‐avoidance effects of self‐attractive mechanisms (i.e. attraction to previously visited sites becomes repulsion if there have been multiple visits in quick succession), which were vital for ensuring predicted occurrence distributions do not become vanishingly small.

Overall, we have provided a general method for iteratively improving the predictive power of step selection models. This will enable future researchers to maximise the information obtained from step selection analyses and to highlight potentially missing data for uncovering the drivers of movement decisions and emergent space use patterns. Ultimately, this provides a fundamental step towards the general aim of constructing predictive models of animal space use.
Pre‐ and posttransfer computed tomography imaging in Canadian trauma centers: A multicenter retrospective cohort study
Authors: Abiala Godwill , Bérubé Mélanie , Mercier Éric , Yanchar Natalie , Stelfox H. Thomas , Archambault Patrick , Bourgeois Gilles , Belcaid Amina , Neveu Xavier , Isaac Chartelin J. , Clément Julien , Lamontagne François , Moore Lynne
Published: May 2022

Background

Multiple clinical practice guidelines recommend minimizing radiation in trauma patients but there is a knowledge gap on the importance of this problem for trauma transfers. We aimed to estimate the incidence of pretransfer and repeat posttransfer computed tomography (CT) overall and in patients with an indication for immediate transfer, to assess interhospital practice variation, to identify predictors, and to quantify the influence of pretransfer CT on time to transfer.

Methods

We conducted a retrospective multicenter cohort study on patients transferred to major trauma centers from 2013 to 2019. Multilevel generalized linear regression was used to generate intraclass correlation coefficients (ICCs) to assess interhospital variation, multilevel logistic regression to generate odds ratios for each predictor, and geometric mean ratios to quantify the influence of CT on time to transfer.

Results

Of 18,244 patients included, 8501 (47%) had a pretransfer CT and one‐quarter (26%) had a repeat posttransfer CT. Interhospital variation was moderate for pretransfer CT (5%–66%, ICC 12.5%) and for repeat posttransfer CT (7%–44%, ICC 14.7%). Pretransfer imaging was more frequent in elders and in males and repeat posttransfer imaging decreased over the study period but was more frequent in patients transferred in from Level III/IV centers than nondesignated hospitals. Time to transfer was doubled in patients who had a pretransfer CT.

Conclusions

Results suggest that pretransfer CT and repeat posttransfer CT are frequent and are subject to significant practice variation. In addition, pretransfer CT is associated with increased times to transfer though additional studies are needed to demonstrate causation. These results highlight potential opportunities to reduce low‐value imaging for trauma transfers.
Synthetic antigenic determinants of clavulanic acid induce dendritic cell maturation and specific T cell proliferation in patients with immediate hypersensitivity reactions
Authors: Fernandez‐Santamaria Ruben , Bogas Gador , Montañez Maria Isabel , Ariza Adriana , Salas Maria , Cespedes Jose Antonio , Labella Marina , Paris Juan Luis , Perez‐Sanchez Natalia , Perez‐Inestrosa Ezequiel , Vida Yolanda , Fernandez Tahia D. , Mayorga Cristobalina , Torres Maria Jose
Published: May 2022

Background

Immediate drug hypersensitivity reactions (IDHRs) to clavulanic acid (CLV) have increased in the last decades due to a higher consumption alongside amoxicillin (AX). Due to its chemical instability, diagnostic procedures to evaluate IDHRs to CLV are difficult, and current in vitro assays do not have an optimal sensitivity. The inclusion of the specific metabolites after CLV degradation, which are efficiently recognised by the immune system, could help to improve sensitivity of in vitro tests.

Methods

Recognition by dendritic cells (DCs) of CLV and the synthetic analogues of two of its hypothesised antigenic determinants (ADs) was evaluated by flow cytometry in 27 allergic patients (AP) and healthy controls (HC). Their ability to trigger the proliferation of T cells was also analysed by flow cytometry.

Results

The inclusion of synthetic analogues of CLV ADs, significantly increased the expression of maturation markers on DCs from AP compared to HC. A different recognition pattern could be observed with each AD, and, therefore, the inclusion of both ADs achieves an improved sensitivity. The addition of synthetic ADs analogues increased the proliferative response of CD4+Th2 compared to the addition of native CLV. The combination of results from both ADs increased the sensitivity of proliferative assays from 19% to 65% with a specificity higher than 90%.

Conclusions

Synthetic ADs from CLV are efficiently recognised by DCs with ability to activate CD4+Th2 cells from AP. The combination of analogues from both ADs, significantly increased the sensitivity of DC maturation and T‐cell proliferation compared to native CLV.
Right‐sided Mahaim‐mediated tachycardia combined with atypical atrioventricular nodal reentrant tachycardia and left free wall accessory pathway: A case report
Authors: Chen Mingxian , Li Xuping , Wu Zhihong , Liu Zhenjiang , Hu Lin , Liu Qiming , Zhou Shenghua
Published: May 2022

A 37‐year‐old man was admitted to our hospital with paroxysmal palpitation for half year. A previous electrogram showed a narrow complex tachycardia. Electrophysiologic study (EPS) found a concealed left‐sided free wall pathway accessory. In addition, a transseptal approach was used for radiofrequency ablation. After successful ablation, EPS induced a wide complex tachycardia and a narrow complex tachycardia. The wide complex tachycardia was diagnosed as a right‐sided Mahaim fiber atriofascicular accessory pathway, and the narrow complex tachycardia was diagnosed as atypical atrioventricular nodal reentrant tachycardia (AVNRT). Then, the right‐sided Mahaim fiber atriofascicular accessory pathway and atypical AVNRT were successfully ablated. Herein, we report a rare case of a concealed left‐sided accessory pathway combined with a right atriofascicular Mahaim fiber and atypical AVNRT.
Morphological characteristics of the optic nerve head and impacts on longitudinal change in macular choroidal thickness during myopia progression
Authors: Hu Guangyi , Xie Jiamin , Shi Ya , Li Menghan , Ye Luyao , Chen Qiuying , Lv Hanyi , Yin Yao , Zou Haidong , He Jiangnan , Zhu Jianfeng , Fan Ying , Xu Xun
Published: May 2022

Purpose

The aim of this study was to investigate the association between morphological characteristics of Bruch’s membrane opening distance (BMOD), border length (BL), border tissue angle (BTA), peripapillary atrophy (PPA) as well as axial length (AL) and incident decreased macular choroidal thickness (mChT) in young healthy myopic eyes.

Methods

A total of 323 participants aged 17–30 years were included in the current 2‐year longitudinal study. Each participant underwent detailed ocular examinations at baseline and follow‐up. Data of AL, refraction error, PPA area, BMOD, BL, BTA and mChT were measured individually. Incident decreased mChT was defined as follow‐up mChT of participants decreased into the lowest quartile of baseline mChT.

Results

Subjects with longer AL, longer BMOD were more likely to have incident decreased mChT (odds ratio [OR], 1.56; 2.09, respectively, per 1 Z‐score increment), whereas larger BTA was less likely to develop decreased mChT (odds ratio [OR], 0.51, per 1 Z‐score increment). The area under the receiver operating curve (AUROC) of basic risk model for incident decreased mChT was 0.6284. After adding BMOD, BTA and AL separately to the basic risk model, the AUROC of the combination could reach 0.6967, 0.6944 and 0.7383, respectively. After combining BMOD, BTA and AL to the basic model, the AUROC of the combination showed the highest AUROC of 0.7608.

Conclusions

Bruch’s membrane opening distance and AL are significant risk factors for incident decreased mChT, whereas BTA played protective role in the deterioration of mChT. In addition, a combination of BMOD, BTA and AL could serve as earlier predictors of the attenuation of mChT in myopia progression.
Neither market nor hierarchy—coordination costs in the allocation of track capacity in the Swedish railway network
Authors: Alexandersson Gunnar , Andersson Matts , Bondemark Anders , Hultén Staffan
Published: May 2022

Transaction costs have been an issue since the advent of the deregulation of the European railway markets in the 1990s. Transaction cost economics received renewed attention in research on the deregulated railway markets in the EU after the publications of two influential reports in the early 2010s.

In this article, we develop a model that enables classification and measurement of transaction costs and other coordination costs in deregulated markets. This model is then used to analyze the costs of path allocation in the Swedish railway sector and to compare the results with findings in previous research. We also discuss the economic rationale of the distribution of coordination costs among the involved parties.

Our key empirical findings are that the total coordination costs in the Swedish market‐mimicking path allocation process are as low as or lower than the most cost‐efficient market coordination processes studied in railway markets, and that the state administrations take on nearly all the coordination costs in order to minimize the effects of opportunism, rent‐seeking and information impactedness. Another finding is that the size of the coordination costs found by different studies seems to be dependent on whether a bottom‐up or a top‐down approach is used.
Editorial: estimating the costs of care in irritable bowel syndrome—a necessary step to enhance value‐based care for a high‐prevalence, low‐cost condition. Authors' reply
Authors: Goodoory Vivek C. , Ng Cho Ee , Black Christopher J. , Ford Alexander C.
Published: May 2022

LINKED CONTENT

This article is linked to Goodoory et al papers. To view these articles, visit https://doi.org/10.1111/apt.16939 and https://doi.org/10.1111/apt.16956
Extracellular vesicles expressing CEACAM proteins in the urine of bladder cancer patients
Authors: Igami Ko , Uchiumi Takeshi , Shiota Masaki , Ueda Saori , Tsukahara Shigehiro , Akimoto Masaru , Eto Masatoshi , Kang Dongchon
Published: May 2022

Early detection and long‐term monitoring are important for urothelial carcinoma of the bladder (UCB). Urine cytology and existing markers have insufficient diagnostic performance. Here, we examined medium‐sized extracellular vesicles (EVs) in urine to identify specific markers for UCB and evaluated their usefulness as diagnostic material. To identify specific markers in urinary EVs derived from UCB, we undertook shotgun proteomics using urine from four UCB patients and four healthy subjects. Next, 29 healthy specimens, 18 noncancer specimens, and 33 UCB specimens, all from men, were analyzed for urinary EVs by flow cytometry to evaluate the diagnostic performance of UCB‐specific EVs. Nanoparticle‐tracking analysis indicated that the size of EVs extracted from urine was mostly <400 nm. By shotgun proteomics, we detected several proteins characteristic of UCB and found that carcinoembryonic antigen‐related adhesion molecule (CEACAM) proteins were increased in patients. Flow cytometric analysis revealed that the degree of expression of CEACAM1, CEACAM5, and CEACAM6 proteins on the surface of EVs varied among patients. Extracellular vesicles expressing CEACAM proteins also expressed mucin 1, suggesting that they were derived from tumorigenic uroepithelial cells. The number of EVs expressing CEACAM1, 5, and 6 proteins was significantly increased in UCB (mean ± SD, 8.6 ± 13%) compared to non‐UCB (0.69 ± 0.46) and healthy (0.46 ± 0.34) by flow cytometry. The results of receiver operating characteristic (ROC) analysis showed a good score of area under the ROC curve of 0.907. We identified EVs that specifically express CEACAM proteins in urine and have potential for diagnostic applications. These EVs are potential targets in a new liquid biopsy test for UCB patients.
Real‐time Virtual‐Try‐On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers
Authors: Kips R. , Jiang R. , Ba S. , Duke B. , Perrot M. , Gori P. , Bloch I.
Published: May 2022

Augmented reality applications have rapidly spread across online retail platforms and social media, allowing consumers to virtually try‐on a large variety of products, such as makeup, hair dying, or shoes. However, parametrizing a renderer to synthesize realistic images of a given product remains a challenging task that requires expert knowledge. While recent work has introduced neural rendering methods for virtual try‐on from example images, current approaches are based on large generative models that cannot be used in real‐time on mobile devices. This calls for a hybrid method that combines the advantages of computer graphics and neural rendering approaches. In this paper, we propose a novel framework based on deep learning to build a real‐time inverse graphics encoder that learns to map a single example image into the parameter space of a given augmented reality rendering engine. Our method leverages self‐supervised learning and does not require labeled training data, which makes it extendable to many virtual try‐on applications. Furthermore, most augmented reality renderers are not differentiable in practice due to algorithmic choices or implementation constraints to reach real‐time on portable devices. To relax the need for a graphics‐based differentiable renderer in inverse graphics problems, we introduce a trainable imitator module. Our imitator is a generative network that learns to accurately reproduce the behavior of a given non‐differentiable renderer. We propose a novel rendering sensitivity loss to train the imitator, which ensures that the network learns an accurate and continuous representation for each rendering parameter. Automatically learning a differentiable renderer, as proposed here, could be beneficial for various inverse graphics tasks. Our framework enables novel applications where consumers can virtually try‐on a novel unknown product from an inspirational reference image on social media. It can also be used by computer graphics artists to automatically create realistic rendering from a reference product image.
Learning a self‐supervised tone mapping operator via feature contrast masking loss
Authors: Wang C. , Chen B. , Seidel HP. , Myszkowski K. , Serrano A.
Published: May 2022

High Dynamic Range (HDR) content is becoming ubiquitous due to the rapid development of capture technologies. Nevertheless, the dynamic range of common display devices is still limited, therefore tone mapping (TM) remains a key challenge for image visualization. Recent work has demonstrated that neural networks can achieve remarkable performance in this task when compared to traditional methods, however, the quality of the results of these learning‐based methods is limited by the training data. Most existing works use as training set a curated selection of best‐performing results from existing traditional tone mapping operators (often guided by a quality metric), therefore, the quality of newly generated results is fundamentally limited by the performance of such operators. This quality might be even further limited by the pool of HDR content that is used for training. In this work we propose a learning‐based self‐supervised tone mapping operator that is trained at test time specifically for each HDR image and does not need any data labeling. The key novelty of our approach is a carefully designed loss function built upon fundamental knowledge on contrast perception that allows for directly comparing the content in the HDR and tone mapped images. We achieve this goal by reformulating classic VGG feature maps into feature contrast maps that normalize local feature differences by their average magnitude in a local neighborhood, allowing our loss to account for contrast masking effects. We perform extensive ablation studies and exploration of parameters and demonstrate that our solution outperforms existing approaches with a single set of fixed parameters, as confirmed by both objective and subjective metrics.
Compact Facial Landmark Layouts for Performance Capture
Authors: Zell E. , McDonnell R.
Published: May 2022

An abundance of older, as well as recent work exists at the intersection of computer vision and computer graphics on accurate estimation of dynamic facial landmarks with applications in facial animation, emotion recognition, and beyond. However, only a few publications exist that optimize the actual layout of facial landmarks to ensure an optimal trade‐off between compact layouts and detailed capturing. At the same time, we observe that applications like social games prefer simplicity and performance over detail to reduce the computational budget especially on mobile devices. Other common attributes of such applications are predefined low‐dimensional models to animate and a large, diverse user‐base. In contrast to existing methods that focus on creating person‐specific facial landmarks, we suggest to derive application‐specific facial landmarks. We formulate our optimization method on the widely adopted blendshape model. First, a score is defined suitable to compute a characteristic landmark for each blendshape. In a following step, we optimize a global function, which mimics merging of similar landmarks to one. The optimization is solved in less than a second using integer linear programming and guarantees a globally optimal solution to an NP‐hard problem. Our application‐specific approach is faster and fundamentally different to previous, actor‐specific methods. Resulting layouts are more similar to empirical layouts. Compared to empirical landmarks, our layouts require only a fraction of landmarks to achieve the same numerical error when reconstructing the animation from landmarks. The method is compared against previous work and tested on various blendshape models, representing a wide spectrum of applications.
Shape Transformers: Topology‐Independent 3D Shape Models Using Transformers
Authors: Chandran Prashanth , Zoss Gaspard , Gross Markus , Gotardo Paulo , Bradley Derek
Published: May 2022

Parametric 3D shape models are heavily utilized in computer graphics and vision applications to provide priors on the observed variability of an object's geometry (e.g., for faces). Original models were linear and operated on the entire shape at once. They were later enhanced to provide localized control on different shape parts separately. In deep shape models, nonlinearity was introduced via a sequence of fully‐connected layers and activation functions, and locality was introduced in recent models that use mesh convolution networks. As common limitations, these models often dictate, in one way or another, the allowed extent of spatial correlations and also require that a fixed mesh topology be specified ahead of time. To overcome these limitations, we present Shape Transformers, a new nonlinear parametric 3D shape model based on transformer architectures. A key benefit of this new model comes from using the transformer's self‐attention mechanism to automatically learn nonlinear spatial correlations for a class of 3D shapes. This is in contrast to global models that correlate everything and local models that dictate the correlation extent. Our transformer 3D shape autoencoder is a better alternative to mesh convolution models, which require specially‐crafted convolution, and down/up‐sampling operators that can be difficult to design. Our model is also topologically independent: it can be trained once and then evaluated on any mesh topology, unlike most previous methods. We demonstrate the application of our model to different datasets, including 3D faces, 3D hand shapes and full human bodies. Our experiments demonstrate the strong potential of our Shape Transformer model in several applications in computer graphics and vision.
Automatic Differentiable Procedural Modeling
Authors: Gaillard Mathieu , Krs Vojtěch , Gori Giorgio , Měch Radomír , Benes Bedrich
Published: May 2022

Procedural modeling allows for an automatic generation of large amounts of similar assets, but there is limited control over the generated output. We address this problem by introducing Automatic Differentiable Procedural Modeling (ADPM). The forward procedural model generates a final editable model. The user modifies the output interactively, and the modifications are transferred back to the procedural model as its parameters by solving an inverse procedural modeling problem. We present an auto‐differentiable representation of the procedural model that significantly accelerates optimization. In ADPM the procedural model is always available, all changes are non‐destructive, and the user can interactively model the 3D object while keeping the procedural representation. ADPM provides the user with precise control over the resulting model comparable to non‐procedural interactive modeling. ADPM is node‐based, and it generates hierarchical 3D scene geometry converted to a differentiable computational graph. Our formulation focuses on the differentiability of high‐level primitives and bounding volumes of components of the procedural model rather than the detailed mesh geometry. Although this high‐level formulation limits the expressiveness of user edits, it allows for efficient derivative computation and enables interactivity. We designed a new optimizer to solve for inverse procedural modeling. It can detect that an edit is under‐determined and has degrees of freedom. Leveraging cheap derivative evaluation, it can explore the region of optimality of edits and suggest various configurations, all of which achieve the requested edit differently. We show our system's efficiency on several examples, and we validate it by a user study.
Neural Precomputed Radiance Transfer
Authors: Rainer Gilles , Bousseau Adrien , Ritschel Tobias , Drettakis George
Published: May 2022

Recent advances in neural rendering indicate immense promise for architectures that learn light transport, allowing efficient rendering of global illumination effects once such methods are trained. The training phase of these methods can be seen as a form of pre‐computation, which has a long standing history in Computer Graphics. In particular, Pre‐computed Radiance Transfer (PRT) achieves real‐time rendering by freezing some variables of the scene (geometry, materials) and encoding the distribution of others, allowing interactive rendering at runtime. We adopt the same configuration as PRT – global illumination of static scenes under dynamic environment lighting – and investigate different neural network architectures, inspired by the design principles and theoretical analysis of PRT. We introduce four different architectures, and show that those based on knowledge of light transport models and PRT‐inspired principles improve the quality of global illumination predictions at equal training time and network size, without the need for high‐end ray‐tracing hardware.
Computational Design of Self‐Actuated Surfaces by Printing Plastic Ribbons on Stretched Fabric
Authors: Jourdan David , Skouras Mélina , Vouga Etienne , Bousseau Adrien
Published: May 2022

We introduce a new mechanism for self‐actuating deployable structures, based on printing a dense pattern of closely‐spaced plastic ribbons on sheets of pre‐stretched elastic fabric. We leverage two shape‐changing effects that occur when such an assembly is printed and allowed to relax: first, the incompressible plastic ribbons frustrate the contraction of the fabric back to its rest state, forcing residual strain in the fabric and creating intrinsic curvature. Second, the differential compression at the interface between the plastic and fabric layers yields abilayer effectin the direction of the ribbons, making each ribbon buckle into an arc at equilibrium state and creating extrinsic curvature. We describe an inverse design tool to fabricate low‐cost, lightweight prototypes of freeform surfaces using the controllable directional distortion and curvature offered by this mechanism. The core of our method is a parameterization algorithm that bounds surface distortions along and across principal curvature directions, along with a pattern synthesis algorithm that covers a surface with ribbons to match the target distortions and curvature given by the aforementioned parameterization. We demonstrate the flexibility and accuracy of our method by fabricating and measuring a variety of surfaces, including nearly‐developable surfaces as well as surfaces with positive and negative mean curvature, which we achieve thanks to a simple hardware setup that allows printing on both sides of the fabric.
Neural Fields in Visual Computing and Beyond
Authors: Xie Yiheng , Takikawa Towaki , Saito Shunsuke , Litany Or , Yan Shiqin , Khan Numair , Tombari Federico , Tompkin James , sitzmann Vincent , Sridhar Srinath
Published: May 2022

Recent advances in machine learning have led to increased interest in solving visual computing problems using methods that employ coordinate‐based neural networks. These methods, which we callneural fields, parameterize physical properties of scenes or objects across space and time. They have seen widespread success in problems such as 3D shape and image synthesis, animation of human bodies, 3D reconstruction, and pose estimation. Rapid progress has led to numerous papers, but a consolidation of the discovered knowledge has not yet emerged. We provide context, mathematical grounding, and a review of over 250 papers in the literature on neural fields. InPart I, we focus on neural field techniques by identifying common components of neural field methods, including different conditioning, representation, forward map, architecture, and manipulation methods. InPart II, we focus on applications of neural fields to different problems in visual computing, and beyond (e.g., robotics, audio). Our review shows the breadth of topics already covered in visual computing, both historically and in current incarnations, and highlights the improved quality, flexibility, and capability brought by neural field methods. Finally, we present a companion website that acts as a living database that can be continually updated by the community.
Authoring Virtual Crowds: A Survey
Authors: Lemonari Marilena , Blanco Rafael , Charalambous Panayiotis , Pelechano Nuria , Avraamides Marios , Pettré Julien , Chrysanthou Yiorgos
Published: May 2022

Recent advancements in crowd simulation unravel a wide range of functionalities for virtual agents, delivering highly‐realistic, natural virtual crowds. Such systems are of particular importance to a variety of applications in fields such as: entertainment (e.g., movies, computer games); architectural and urban planning; and simulations for sports and training. However, providing their capabilities to untrained users necessitates the development of authoring frameworks. Authoring virtual crowds is a complex and multi‐level task, varying from assuming control and assisting users to realise their creative intents, to delivering intuitive and easy to use interfaces, facilitating such control. In this paper, we present a categorisation of the authorable crowd simulation components, ranging from high‐level behaviours and path‐planning to local movements, as well as animation and visualisation. We provide a review of the most relevant methods in each area, emphasising the amount and nature of influence that the users have over the final result. Moreover, we discuss the currently available authoring tools (e.g., graphical user interfaces, drag‐and‐drop), identifying the trends of early and recent work. Finally, we suggest promising directions for future research that mainly stem from the rise of learning‐based methods, and the need for a unified authoring framework.
A Survey on SPH Methods in Computer Graphics
Authors: Koschier Dan , Bender Jan , Solenthaler Barbara , Teschner Matthias
Published: May 2022

Throughout the past decades, the graphics community has spent major resources on the research and development of physics simulators on the mission to computer‐generate behaviors achieving outstanding visual effects or to make the virtual world indistinguishable from reality. The variety and impact of recent research based on Smoothed Particle Hydrodynamics (SPH) demonstrates the concept's importance as one of the most versatile tools for the simulation of fluids and solids. With this survey, we offer an overview of the developments and still‐active research on physics simulation methodologies based on SPH that has not been addressed in previous SPH surveys. Following an introduction about typical SPH discretization techniques, we provide an overview over the most used incompressibility solvers and present novel insights regarding their relation and conditional equivalence. The survey further covers recent advances in implicit and particle‐based boundary handling and sampling techniques. While SPH is best known in the context of fluid simulation we discuss modern concepts to augment the range of simulatable physical characteristics including turbulence, highly viscous matter, deformable solids, as well as rigid body contact handling. Besides the purely numerical approaches, simulation techniques aided by machine learning are on the rise. Thus, the survey discusses recent data‐driven approaches and the impact of differentiable solvers on artist control. Finally, we provide context for discussion by outlining existing problems and opportunities to open up new research directions.