bluuebunny/crossref_metadata_2025 huggingface dataset:
Angiotensin‐Converting Enzyme 2 (SARS‐CoV‐2 receptor) expression in human skeletal muscle
Authors: Perez‐Valera Mario , Martinez‐Canton Miriam , Gallego‐Selles Angel , Galván‐Alvarez Victor , Gelabert‐Rebato Miriam , Morales‐Alamo David , Santana Alfredo , Martin‐Rodriguez Saul , Ponce‐Gonzalez Jesus Gustavo , Larsen Steen , Losa‐Reyna Jose , Perez‐Suarez Ismael , Dorado Cecilia , Curtelin David , Gonzalez‐Henriquez Juan Jose , Boushel Robert , Hallen Jostein , de Pablos Velasco Pedro , Freixinet‐Gilart Jorge , Holmberg Hans‐Christer , Helge Jorn W. , Martin‐Rincon Marcos , Calbet Jose A.L.
Published: September 2021

The study aimed to determine the levels of skeletal muscle angiotensin‐converting enzyme 2 (ACE2, the SARS‐CoV‐2 receptor) protein expression in men and women and assess whether ACE2 expression in skeletal muscle is associated with cardiorespiratory fitness and adiposity. The level of ACE2 in vastus lateralis muscle biopsies collected in previous studies from 170 men (age: 19–65 years, weight: 56–137 kg, BMI: 23–44) and 69 women (age: 18–55 years, weight: 41–126 kg, BMI: 22–39) was analyzed in duplicate by western blot. VO2max was determined by ergospirometry and body composition by DXA. ACE2 protein expression was 1.8‐fold higher in women than men (p = 0.001, n = 239). This sex difference disappeared after accounting for the percentage of body fat (fat %), VO2max per kg of legs lean mass (VO2max‐LLM) and age (p = 0.47). Multiple regression analysis showed that the fat % (β = 0.47) is the main predictor of the variability in ACE2 protein expression in skeletal muscle, explaining 5.2% of the variance. VO2max‐LLM had also predictive value (β = 0.09). There was a significant fat % by VO2max‐LLM interaction, such that for subjects with low fat %, VO2max‐LLM was positively associated with ACE2 expression while as fat % increased the slope of the positive association between VO2max‐LLM and ACE2 was reduced. In conclusion, women express higher amounts of ACE2 in their skeletal muscles than men. This sexual dimorphism is mainly explained by sex differences in fat % and cardiorespiratory fitness. The percentage of body fat is the main predictor of the variability in ACE2 protein expression in human skeletal muscle.
Culture, Cognition, and Internalization
Authors: Lizardo Omar
Published: September 2021

In this paper, I address the history and systematics of the concept of internalization in cultural theory, noting that while use of the concept declined after its heyday in mid‐20th‐century functionalism, it is as indispensable now as it was then. I build an account of internalization consistent with recent conceptual distinctions offered in the culture and cognition literature. Taking the (relatively easy) case of the internalization of belief first, I problematize a popular conception of how declarative forms of personal culture are internalized via linguistic communication but flag a potentially promising solution. In this alternative story, the same “dialectical” model linking personal and public culture accounts for the internalization of both declarative and nondeclarative culture, allowing us to tell the same general story for the internalization of “knowledge‐that” and “knowledge‐how.” I then discuss conceptual personal culture as a third general type of personal culture (“knowledge‐what”), standing between the purely declarative and nondeclarative. I show how the model of internalization developed in the case of beliefs and skills also applies to it with minor modifications. I close by outlining some implications of the theory developed here for clarifying such problems as theorizing degrees of internalization and the relative fragmentation of culture in persons.
Severe autoimmune hemolytic anemia following receipt of SARS‐CoV‐2 mRNA vaccine
Authors: Gadi Sanjay R. V. , Brunker Patricia A. R. , Al‐Samkari Hanny , Sykes David B. , Saff Rebecca R. , Lo Janet , Bendapudi Pavan , Leaf David E. , Leaf Rebecca Karp
Published: September 2021

Background

Large clinical trials have demonstrated the overall safety of vaccines for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). However, reports have emerged of autoimmune phenomena, including vaccine‐associated myocarditis, immune thrombocytopenia, and immune thrombotic thrombocytopenia.

Case Presentation

Here we present a novel case of a young woman who developed life‐threatening autoimmune hemolytic anemia (AIHA) after her first dose of a SARS‐CoV‐2 mRNA vaccine. Notably, initial direct antiglobulin testing was negative using standard anti‐IgG reagents, which are “blind” to certain immunoglobulin (IgG) isotypes. Further testing using an antiglobulin reagent that detects all IgG isotypes was strongly positive and confirmed the diagnosis of AIHA. The patient required transfusion with 13 units of red blood cells, as well as treatment with corticosteroids, rituximab, mycophenolate mofetil, and immune globulin.

Conclusion

As efforts to administer SARS‐CoV‐2 vaccines continue globally, clinicians must be aware of potential autoimmune sequelae of these therapies.
How can cover crops contribute to weed management? A modelling approach illustrated with rye (Secale cereale) and Amaranthus tuberculatus
Authors: Liebman Matt , Basche Andrea D. , Nguyen Huong T. X. , Weisberger David A.
Published: September 2021

Cover cropping has been proposed as an important component of integrated weed management strategies due to its potential effects on multiple demographic processes, including weed seedling emergence from soil, plant survival, seed production, and seed predation. In this article, we report the results of modelling analyses that investigated how a cover crop could affect the population dynamics of Amaranthus tuberculatus (Moq.) J.D. Sauer (waterhemp), an annual dicotyledonous species that is a major problem in maize and soyabean fields in the central USA. We constructed difference equation models for maize–soyabean rotations with and without a rye cover crop and parameterised the models with values drawn from published scientific literature. Results of the analyses indicate that the use of a winter cover crop would have minimal effects on the level of herbicide efficacy required to prevent increases in A. tuberculatus population density in maize and soyabean. However, if a high level of herbicide efficacy was imposed, cover crop‐derived reductions in A. tuberculatus seedling population density, delays in seedling emergence, and increases in seed predation would diminish A. tuberculatus seed population density in soil up to 96% over a 10‐year period. Thus, while cover crops did not replace the need for other control strategies for A. tuberculatus, they could complement them. Relative to cover crops, greater benefits for A. tuberculatus management might be gained using diverse sequences of cash crops. Possible synergies between cover crops and diversified crop rotations should be explored in both field experiments and modelling analyses.
Broken pencils and moving rulers: After an unpublished book by Mitchell Feigenbaum
Authors: Eckmann Jean-Pierre
Published: September 2021

Mitchell Feigenbaum discovered an intriguing property of viewing images through cylindrical mirrors or looking into water. Because the eye is a lens with an opening of about 5 mm, many different rays of reflected images reach the eye and need to be interpreted by the visual system. This has the surprising effect that what one perceives depends on the orientation of the head, whether it is tilted or not. I explain and illustrate this phenomenon on the example of a human eye looking at a ruler immersed in water.
Menthol-Based Topical Analgesic Induces Similar Upper and Lower Body Pain Pressure Threshold Values: A Randomized Trial
Authors: Behm David G. , Herat Nehara , Power Gerard M.J. , Brosky Joseph A. , Page Phil , Alizadeh Shahab
Published: September 2021

Context: Both health professionals and consumers use menthol-based topical analgesics extensively for the temporary relief of pain from musculoskeletal ailments or injury. However, there are no reports of differences in the pain pressure threshold (PPT) or the relative effectiveness of topical analgesics to reduce pain in the upper and lower body muscles and tendons. The objective of this study was to investigate whether differences existed in PPT and relative pain attenuation associated with a menthol-based topical analgesic over a variety of upper and lower body muscles and tendons. Design: Randomized allocation, controlled, intervention study. Methods: Sixteen participants (10 females and 6 males) were tested on their dominant or nondominant side. The order of specific muscle/tendon testing was also randomized, which included upper body (middle deltoid, biceps brachii, and lateral epicondylar tendon) and lower body locations (quadriceps, hamstrings, gastrocnemius, lumbosacral erector spinae muscles, and patellar and Achilles tendons). The PPT was monitored before and 15 minutes following the application of a menthol-based topical analgesic. Results: A menthol-based topical analgesic increased PPT (decreased pain sensitivity) overall (P = .05; 11.6% [2.4%]; d = 1.05) and PPT was higher (P < .0001; 31.5%–44.2%; d = 1.03–1.8) for lower versus upper body locations. Conclusions: Health professionals and the public can be assured of similar reductions in pain sensitivity independent of the location of application of a menthol-based topical analgesic.
Altruistic bet-hedging and the evolution of cooperation in a Kalahari bird
Authors: Capilla-Lasheras Pablo , Harrison Xavier , Wood Emma M. , Wilson Alastair J. , Young Andrew J.
Published: September 2021

Striking effects of cooperation on the reproductive variance of relatives help to explain the global biogeography of altruism.
High-throughput single-cell quantification of hundreds of proteins using conventional flow cytometry and machine learning
Authors: Becht Etienne , Tolstrup Daniel , Dutertre Charles-Antoine , Morawski Peter A. , Campbell Daniel J. , Ginhoux Florent , Newell Evan W. , Gottardo Raphael , Headley Mark B.
Published: September 2021

This study presents a novel method for low-cost cell surface proteomics using flow cytometry and machine learning.
Facile full-color printing with a single transparent ink
Authors: Li Kaixuan , Li Tongyu , Zhang Tailong , Li Huizeng , Li An , Li Zheng , Lai Xintao , Hou Xiaoyu , Wang Yu , Shi Lei , Li Mingzhu , Song Yanlin
Published: September 2021

A facile full structural-color inkjet printing strategy is developed.
Subarctic climate for the earliestHomo sapiensin Europe
Authors: Pederzani Sarah , Britton Kate , Aldeias Vera , Bourgon Nicolas , Fewlass Helen , Lauer Tobias , McPherron Shannon P. , Rezek Zeljko , Sirakov Nikolay , Smith Geoff M. , Spasov Rosen , Tran N.-Han , Tsanova Tsenka , Hublin Jean-Jacques
Published: September 2021

Subarctic climate at an earlyH. sapienssite in Europe shows that expansion of our species was not predicated on warm climates.
Predictive simulations of running gait reveal a critical dynamic role for the tail in bipedal dinosaur locomotion
Authors: Bishop Peter J. , Falisse Antoine , De Groote Friedl , Hutchinson John R.
Published: September 2021

Computer simulations reveal a previously unrecognized, but critical, role of the tail in dinosaur locomotion.
Programmable assembly of particles on a Chladni plate
Authors: Kopitca Artur , Latifi Kourosh , Zhou Quan
Published: September 2021

Nature-inspired algorithm iteratively assembles particles into complex user-specified shapes on a vibrating plate.
The relevance of signal timing in human-robot collaborative manipulation
Authors: Cini F. , Banfi T. , Ciuti G. , Craighero L. , Controzzi M.
Published: September 2021

A robot should communicate its intention to collaborate shortly after a human has picked an object to avoid interferences.
Toll-like receptor 4–mediated enteric glia loss is critical for the development of necrotizing enterocolitis
Authors: Kovler Mark L. , Gonzalez Salazar Andres J. , Fulton William B. , Lu Peng , Yamaguchi Yukihiro , Zhou Qinjie , Sampah Maame , Ishiyama Asuka , Prindle Thomas , Wang Sanxia , Jia Hongpeng , Wipf Peter , Sodhi Chhinder P. , Hackam David J.
Published: September 2021

TLR4-induced enteric glia loss leads to experimental NEC through BDNF loss, which can be treated with by compound J11.
Super-enhancer landscape reveals leukemia stem cell reliance on X-box binding protein 1 as a therapeutic vulnerability
Authors: Zhou Jingfeng , Wang Shubo , Nie Danian , Lai Peilong , Li Yiqing , Li Yangqiu , Jin Yanli , Pan Jingxuan
Published: September 2021

Leukemia stem cells are dependent on the super-enhancer–associated oncogene XBP1, suggesting a potential targeting strategy in relapsed CML.
Engineering the Outer Membrane Could Facilitate Better Bacterial Performance and Effectively Enhance Poly-3-Hydroxybutyrate Accumulation
Authors: Wang Jianli , Ma Wenjian , Fang Yu , Zhang Hailing , Liang Hao , Liu Haili , Wang Tingwei , Chen Shangwei , Ji Jian , Wang Xiaoyuan
Published: September 2021

Understanding the detailed influence of the OM on the cell envelope and cellular metabolism is important for optimizing the
E. coli
cell factory and many other microorganisms. This study revealed the applicability of remodeling the OM to enhance PHB accumulation as representative inclusion bodies.
Overview of Changes to the Clinical and Laboratory Standards Institute
Performance Standards for Antimicrobial Susceptibility Testing,
M100, 31st Edition
Authors: Humphries Romney , Bobenchik April M. , Hindler Janet A. , Schuetz Audrey N.
Published: September 2021

The Clinical and Laboratory Standards Institute (CLSI) Subcommittee on Antimicrobial Susceptibility Testing (AST) develops and publishes standards and guidelines for AST methods and results interpretation in an annual update to the
Performance Standards for Antimicrobial Susceptibility Testing
(M100). This minireview will discuss changes to M100 for the 31st edition, including new and revised breakpoints and testing recommendations.
The Impact of Borderline Quantiferon-TB Gold Plus Results for Latent Tuberculosis Screening under Routine Conditions in a Low-Endemicity Setting
Authors: Wikell A. , Jonsson J. , Dyrdak R. , Henningsson A. J. , Eringfält A. , Kjerstadius T. , Hålldin E. , Baqir H. , Kholod V. , Sturegård E. , Bruchfeld J. , Schön T.
Published: September 2021

Quantiferon-TB Gold Plus (QFT-Plus) is an interferon gamma release assay used to diagnose latent tuberculosis (LTB). A borderline range (0.20 to 0.99 IU/ml) around the cutoff (0.35 IU/ml) has been suggested for the earlier QFT version.
Chikungunya Virus Exposure Partially Cross-Protects against Mayaro Virus Infection in Mice
Authors: Fumagalli Marcilio Jorge , de Souza William Marciel , de Castro-Jorge Luiza Antunes , de Carvalho Renan Villanova Homem , Castro Ítalo de Araújo , de Almeida Luiz Gustavo Nogueira , Consonni Silvio Roberto , Zamboni Dario Simões , Figueiredo Luiz Tadeu Moraes
Published: September 2021

Mosquito-borne viruses have a worldwide impact, especially in tropical climates. Chikungunya virus has been present mostly in developing countries, causing millions of infections, while Mayaro virus, a close relative, has been limited to the Caribbean and tropical regions of Latin America.
Structural Study of Aavrh.10 Receptor and Antibody Interactions
Authors: Mietzsch Mario , Yu Jennifer C. , Hsi Jane , Chipman Paul , Broecker Felix , Fuming Zhang , Linhardt Robert J. , Seeberger Peter H. , Heilbronn Regine , McKenna Robert , Agbandje-McKenna Mavis
Published: September 2021

Gene therapy vectors based on adeno-associated virus rhesus isolate 10 (AAVrh.10) have been used in several clinical trials to treat monogenetic diseases. However, compared to other AAV serotypes little is known about receptor binding and antigenicity of the AAVrh.10 capsid.
The Vancomycin Resistance-Associated Regulatory System VraSR Modulates Biofilm Formation of Staphylococcus epidermidis in an
ica
-Dependent Manner
Authors: Wu Youcong , Meng Yuanyuan , Qian Lian , Ding Baixing , Han Haiyan , Chen Hongling , Bai Li , Qu Di , Wu Yang
Published: September 2021

S. epidermidis
is a leading cause of hospital-acquired catheter-related infections, and its pathogenicity depends mostly on its ability to form biofilms on implants. The biofilm formation is a complex procedure that involves multiple regulating factors. Here, we show that a vancomycin resistance-associated two-component regulatory system, VraSR, plays an important role in modulating
S. epidermidis
biofilm formation and tolerance to stress.
Role of Glucose-6-Phosphate in Metabolic Adaptation of Staphylococcus aureus in Diabetes
Authors: Seo Keun Seok , Park Nogi , Rutter Jaime K. , Park Youngkyung , Baker Carol L. , Thornton Justin A. , Park Joo Youn
Published: September 2021

Sugars are essential nutrients for
S. aureus
to survive and proliferate within the host. Because elevated serum glucose levels are a hallmark of diabetes, most studies have focused on the effect of glucose metabolism, and very little is known regarding the effects of metabolism of other sugars on the pathogenesis of
S. aureus
in diabetes.
Supplemental Material: Geologic map of central Panamint Range, California
Authors: Andrew J.E.
Published: September 2021

Digital map data files in ArcGIS shapefile format for data collection points, geologic contacts, and geologic unit polygons.
Implementation of an adapted Sepsis Risk Calculator algorithm to reduce antibiotic usage in the management of early onset neonatal sepsis: a multicentre initiative in Wales, UK
Authors: Goel Nitin , Cannell Stephanie , Davies Gemma , Natti Murali Sridhar , Kirupaalar Vickness , Abelian Artur , Saeed Shakir , Smith Rhian , Manikonda Ravi , Pitchaikani Prem Kumar , Davies Dawn , Morris Rachel May , Edwards Lynsey , Govindaraju Roopashree , Creese Kate , Jones Jane , Choudhary Jalil , Rowley Sarah , Sethuraman Chidambaram , Muxworthy Helen , Curtis Felicity , Donnelly Patricia , Joishy Manohar , Barnard Ian , Kenny Celyn , Pal Rajarshi , Jones Karen , Banerjee Sujoy
Published: September 2021

Objective

Assess the impact of introducing a consensus guideline incorporating an adapted Sepsis Risk Calculator (SRC) algorithm, in the management of early onset neonatal sepsis (EONS), on antibiotic usage and patient safety.

Design

Multicentre prospective study

Setting

Ten perinatal hospitals in Wales, UK.

Patients

All live births ≥34 weeks’ gestation over a 12-month period (April 2019–March 2020) compared with infants in the preceding 15-month period (January 2018–March 2019) as a baseline.

Methods

The consensus guideline was introduced in clinical practice on 1 April 2019. It incorporated a modified SRC algorithm, enhanced in-hospital surveillance, ongoing quality assurance, standardised staff training and parent education. The main outcome measure was antibiotic usage/1000 live births, balancing this with analysis of harm from delayed diagnosis and treatment, disease severity and readmissions from true sepsis. Outcome measures were analysed using statistical process control charts.

Main outcome measures

Proportion of antibiotic use in infants ≥34 weeks’ gestation.

Results

4304 (14.3%) of the 30 105 live-born infants received antibiotics in the baseline period compared with 1917 (7.7%) of 24 749 infants in the intervention period (45.5% mean reduction). All 19 infants with culture-positive sepsis in the postimplementation phase were identified and treated appropriately. There were no increases in sepsis-related neonatal unit admissions, disease morbidity and late readmissions.

Conclusions

This multicentre study provides evidence that a judicious adaptation of the SRC incorporating enhanced surveillance can be safely introduced in the National Health Service and is effective in reducing antibiotic use for EONS without increasing morbidity and mortality.
Maternal vitamin B12, folate during pregnancy and neurocognitive outcomes in young adults of the Pune Maternal Nutrition Study (PMNS) prospective birth cohort: study protocol
Authors: Behere Rishikesh V , Deshpande Gopikrishna , Bandyopadhyay Souvik Kumar , Yajnik Chittaranjan
Published: September 2021

Introduction

The Developmental Origins of Health and Disease (DOHaD) hypothesis proposes that intrauterine and early life exposures significantly influence fetal development and risk for disease in later life. Evidence from prospective birth cohorts suggests a role for maternal B12and folate in influencing neurocognitive outcomes in the offspring. In the Indian setting, B12deficiency is common during the pregnancy while rates of folate deficiency are lower. The long-term influences of maternal nutrition during the pregnancy on adult neurocognitive outcomes have not been examined. The Pune Maternal Nutrition Study (PMNS) is a preconceptional birth cohort into its 24th year and is considered a unique resource to study the DOHaD hypothesis. We found an association between maternal B12status in pregnancy and child’s neurocognitive status at 9 years of age. We now plan to assess neurocognitive function and MRI measurements of brain structural–functional connectivity at young adult age to study its association with maternal nutritional exposures during the pregnancy.

Methods and analysis

As part of ongoing prospective follow-up in young adults of the PMNS at the Diabetes Unit, KEM Hospital Research Center, Pune India, the following measurements will be done: neurocognitive performance (Standardised Tests of Intelligence, Verbal and Visual Memory, Attention and Executive Functions), temperament (Adult Temperament Questionnaire), psychopathology (Brief Symptom Inventory and Clinical Interview on Mini Neuropsychiatric Interview 7.0). Brain MRI for structural T1, resting-state functional connectivity and diffusion tensor imaging will be performed on a subset of the cohort (selected based on exposure to a lower or higher maternal B12status at 18 weeks of pregnancy).

Ethics and dissemination

The study is approved by Institutional ethics committee of KEM Hospital Research Center, Pune. The results will be shared at national and international scientific conferences and published in peer-reviewed scientific journals.

Trial registration number

NCT03096028
Influence of COVID-19 on the preventive health behaviours of Indigenous Peoples of Australia residing in New South Wales: a mixed-method study protocol
Authors: Usher Kim , Bhullar Navjot , Sibbritt David , Anubha Amarasena Suruchi Sue , Peng Wenbo , Durkin Joanne , Smallwood Reakeeta , Power Tamara , Porter Cheryl , McGowen Debbie , Jackson Debra
Published: September 2021

Introduction

Chronic conditions impact Indigenous Peoples of Australia at a much higher rate than non-Indigenous Australians. Attendance at the Medicare Benefits Scheme (MBS) supported Indigenous health checks are crucial to improve prevention and management of chronic health conditions. However, in conjunction with lifestyle and environmental factors, attendance rates at primary healthcare services for screening and treatment have fallen in Australia during the COVID-19 pandemic. This study aims to explore the influence of the COVID-19 pandemic on preventive health behaviours of Indigenous Australians and the associated barriers to, and enablers of, engagement with health services to formulate a targeted intervention strategy.

Methods and analysis

A concurrent mixed-methods study (comprising quantitative and qualitative data collection methods) will be employed. Descriptive analysis of MBS data about the characteristics of Indigenous Peoples of Australia claiming health assessment services will be performed. Generalised estimating equation regression models will be used to examine the use of health assessment services over time. Qualitative interviews informed by Indigenous research methods will be conducted. Interviews will investigate barriers to, and enablers of, engagement with health services. Thematic approach guided by the principles of indigenist praxis, storytelling and collaborative research will be used to analyse the interview data. The project commenced in July 2020 and will be completed by July 2022.

Ethics and dissemination

The project received ethics approval from the Aboriginal Health and Medical Research Council of New South Wales and the University of New England Human Research Ethics Committee. Findings will be disseminated via peer-reviewed journal articles, conferences, government and relevant stakeholder reports, and infographics.
A long and winding road: non-traditional routes into medical leadership
Authors: Gulati Steve , Shrimpton Christiane
Published: September 2021

Introduction

Clinicians enter the medical profession through a variety of routes. This paper explores how non-traditional routes into the medical profession can follow through into subsequent medical leadership practice, influencing issues of confidence, self-image and assumptions about leadership as a concept.

Method

The first-person reflections of a doctor who entered the profession and the National Health Service from the German system and with a non-standard background are considered. We then discuss how those involved in leadership education can use diversity as a developmental tool. The article starts and ends with personal reflections and observations from a Consultant Opthalmologist, interposed with insights from the pedagogy of leadership development by a University academic.

Conclusions

We conclude that medical leadership development can be enriched through recognising the value that non-traditional routes in clinical leadership can bring, and that educators can use the leverage of difference and diversity to create positive loops of development activity.
Radial artery access for neuroendovascular procedures: safety review and complications
Authors: Narsinh Kazim H , Mirza Mohammed H , Caton Jr M Travis , Baker Amanda , Winkler Ethan , Higashida Randall T , Halbach Van V , Amans Matthew R , Cooke Daniel L , Hetts Steven W , Abla Adib A , Dowd Christopher F
Published: September 2021

Although enthusiasm for transradial access for neurointerventional procedures has grown, a unique set of considerations bear emphasis to preserve safety and minimize complications. In the first part of this review series, we reviewed anatomical considerations for safe and easy neuroendovascular procedures from a transradial approach. In this second part of the review series, we aim to (1) summarize evidence for safety of the transradial approach, and (2) explain complications and their management.
Trajectories of opioid consumption from day of surgery to 28 days postoperatively: a prospective cohort study in patients undergoing abdominal, joint, or spine surgery
Authors: McCarthy Robert J , Adams Ashley Meng , Sremac Amanda C , Kreider Wendy Jo , Pelletier Pete L , Buvanendran Asokumar
Published: September 2021

Introduction

Descriptions of opioid use trajectories and their association with postsurgical pain and opioid consumption are limited. We hypothesized that trajectories of opioid consumption in the first 28 days following surgery would be associated with unique patterns of pain and duration of opioid use.

Methods

A prospective longitudinal cohort of patients undergoing elective inpatient abdominal, joint, or spine surgery between June 2016 and June 2019 was studied. At hospital discharge and every 7 days for 28 days, patients were assessed for pain, analgesic use, pain interference, satisfaction, and side effects. Duration of opioid use was determined for 6 months. The primary analysis used latent class group modeling to identify trajectories of opioid use.

Results

Decreasing, high, and persistent opioid trajectories were identified following joint and spine surgery and a decreasing and persistent trajectory following abdominal surgery. Reported pain was greater in the high and persistent trajectories compared with the decreasing use trajectories. Compared with the decreasing opioid trajectory, the median duration of opioid use was increased by 4.5 (95% CI 1 to 22, p<0.01) weeks in persistent opioid use abdominal and by 6 (95% CI 0 to 6, p<0.01) weeks in the high or persistent use joint and spine groups. The odds (95% CI) of opioid use at 6 months in the high or persistent opioid use trajectory was 24.3 (2.9 to 203.4) for abdominal and 3.7 (1.9 to 7.0) for joint or spine surgery compared with the decreasing use trajectory. Morphine milliequivalent per 24 hours of hospitalization was the primary independent predictor of opioid use trajectories.

Conclusions

We observed distinct opioid use trajectories following abdominal and joint or spine surgery that were associated with different patterns of pain and duration of opioid use postoperatively. Prediction of postoperative opioid use trajectory groups may be clinically important for identifying risk of prolonged opioid use.
Critical insights in laboratory shear wave velocity correlations of clays
Authors: Elbeggo Dania , Ethier Yannic , Dubé Jean-Sébastien , Karray Mourad
Published: September 2021

Shear wave velocity, Vs, is an important mechanical–dynamic parameter allowing the characterization of a soil in the elastic range (γ < 10–3%). Thirty-five existing Gmax or Vs laboratory correlations were examined in this study and are grouped into different general forms based on their geotechnical properties. A database of 11 eastern Canadian clay deposits was selected and used for the critical insights. The effect of the coefficient of earth pressure at rest, K0, was also examined. A range of variation for each general form of correlation was determined to take the plasticity index and void ratio values of investigated sites into account. The analysis shows a significant scatter in Vs1 values predicted by existing correlations and raises questions on the applicability of these correlations, especially for eastern Canadian clays. New correlations are proposed for Champlain clays based on laboratory measurement of Vs using the piezoelectric ring-actuator technique, P-RAT, incorporated in consolidation cells. An analysis of P-RAT results reveals the sample disturbance effect and suggests an approach to correct the effect of disturbance on laboratory Vs measurements. The applicability of the proposed correlations, including the disturbance correction, is validated by comparison with in situ measurements using multi-modal analysis of surface waves (MMASW).
Soft Group Action From Classical View Point
Authors: Goldar Sujay
Published: September 2021

Soft set theory, proposed by Molodtsov, Soft set theory — First results, Computers and Mathematics with Applications 37(4/5) (1999) 19–31, has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, we introduce the notion of the soft group action as a general group action and study their properties. Some interesting results and relation between soft group action and ordinary group action are studied. Also, Soft Stabilizer, Soft Centralizer and Soft Normalizer have been depicted.
Human detection of machine-manipulated media
Authors: Groh Matthew , Epstein Ziv , Obradovich Nick , Cebrian Manuel , Rahwan Iyad
Published: September 2021

Technologies for manipulating and faking online media may outpace people's ability to tell the difference.
Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems Using Multi-objective Reinforcement Learning
Authors: Chen Jianguo , Li Kenli , Li Keqin , Yu Philip S. , Zeng Zeng
Published: September 2021

As a new generation of Public Bicycle-sharing Systems (PBS), the Dockless PBS (DL-PBS) is an important application of cyber-physical systems and intelligent transportation. How to use artificial intelligence to provide efficient bicycle dispatching solutions based on dynamic bicycle rental demand is an essential issue for DL-PBS. In this article, we propose MORL-BD, a dynamic bicycle dispatching algorithm based on multi-objective reinforcement learning to provide the optimal bicycle dispatching solution for DL-PBS. We model the DL-PBS system from the perspective of cyber-physical systems and use deep learning to predict the layout of bicycle parking spots and the dynamic demand of bicycle dispatching. We define the multi-route bicycle dispatching problem as a multi-objective optimization problem by considering the optimization objectives of dispatching costs, dispatch truck's initial load, workload balance among the trucks, and the dynamic balance of bicycle supply and demand. On this basis, the collaborative multi-route bicycle dispatching problem among multiple dispatch trucks is modeled as a multi-agent and multi-objective reinforcement learning model. All dispatch paths between parking spots are defined as state spaces, and the reciprocal of dispatching costs is defined as a reward. Each dispatch truck is equipped with an agent to learn the optimal dispatch path in the dynamic DL-PBS network. We create an elite list to store the Pareto optimal solutions of bicycle dispatch paths found in each action, and finally get the Pareto frontier. Experimental results on the actual DL-PBS show that compared with existing methods, MORL-BD can find a higher quality Pareto frontier with less execution time.
Software development in disruptive times
Authors: Varajão João
Published: September 2021

Creating a software solution with fast decision capability, agile project management, and extreme low-code technology.
QuickLoc: Adaptive Deep-Learning for Fast Indoor Localization with Mobile Devices
Authors: Tiku Saideep , Kale Prathmesh , Pasricha Sudeep
Published: September 2021

Indoor localization services are a crucial aspect for the realization of smart cyber-physical systems within cities of the future. Such services are poised to reinvent the process of navigation and tracking of people and assets in a variety of indoor and subterranean environments. The growing ownership of computationally capable smartphones has laid the foundations of portable fingerprinting-based indoor localization through deep learning. However, as the demand for accurate localization increases, the computational complexity of the associated deep learning models increases as well. We present an approach for reducing the computational requirements of a deep learning-based indoor localization framework while maintaining localization accuracy targets. Our proposed methodology is deployed and validated across multiple smartphones and is shown to deliver up to 42% reduction in prediction latency and 45% reduction in prediction energy as compared to the best-known baseline deep learning-based indoor localization model.
Meta-Learning to Improve Unsupervised Intrusion Detection in Cyber-Physical Systems
Authors: Zoppi Tommaso , Gharib Mohamad , Atif Muhammad , Bondavalli Andrea
Published: September 2021

Artificial Intelligence (AI)-
based classifiers rely on
Machine Learning (ML)
algorithms to provide functionalities that system architects are often willing to integrate into critical
Cyber-Physical Systems (CPSs)
. However, such algorithms may misclassify observations, with potential detrimental effects on the system itself or on the health of people and of the environment. In addition, CPSs may be subject to threats that were not previously known, motivating the need for building
Intrusion Detectors (IDs)
that can effectively deal with zero-day attacks. Different studies were directed to compare misclassifications of various algorithms to identify the most suitable one for a given system. Unfortunately, even the most suitable algorithm may still show an unsatisfactory number of misclassifications when system requirements are strict. A possible solution may rely on the adoption of meta-learners, which build ensembles of base-learners to reduce misclassifications and that are widely used for supervised learning. Meta-learners have the potential to reduce misclassifications with respect to non-meta learners: however, misleading base-learners may let the meta-learner leaning towards misclassifications and therefore their behavior needs to be carefully assessed through empirical evaluation. To such extent, in this paper we investigate, expand, empirically evaluate, and discuss meta-learning approaches that rely on ensembles of unsupervised algorithms to detect (zero-day) intrusions in CPSs. Our experimental comparison is conducted by means of public datasets belonging to network intrusion detection and biometric authentication systems, which are common IDSs for CPSs. Overall, we selected 21 datasets, 15 unsupervised algorithms and 9 different meta-learning approaches. Results allow discussing the applicability and suitability of meta-learning for unsupervised anomaly detection, comparing metric scores achieved by base algorithms and meta-learners. Analyses and discussion end up showing how the adoption of meta-learners significantly reduces misclassifications when detecting (zero-day) intrusions in CPSs.
Deep Learning to Predict the Feasibility of Priority-Based Ethernet Network Configurations
Authors: Mai Tieu Long , Navet Nicolas
Published: September 2021

Machine learning has been recently applied in real-time systems to predict whether Ethernet network configurations are feasible in terms of meeting deadline constraints without executing conventional schedulability analysis. However, the existing prediction techniques require domain expertise to choose the relevant input features and do not perform consistently when topologies or traffic patterns differ significantly from the ones in the training data. To overcome these problems, we propose a Graph Neural Network (GNN) prediction model that synthesizes relevant features directly from the raw data. This deep learning model possesses the ability to exploit relations among flows, links, and queues in switched Ethernet networks and generalizes to unseen topologies and traffic patterns. We also explore the use of ensembles of GNNs and show that it enhances the robustness of the predictions. An evaluation on heterogeneous testing sets comprising realistic automotive networks shows that ensembles of 32 GNN models feature a prediction accuracy ranging from 79.3% to 90% for Ethernet networks using priorities as the Quality-of-Service mechanism. The use of ensemble models provides a speedup factor ranging from 77 to 1,715 compared to schedulability analysis, which allows a far more extensive design space exploration.
Tolerating Defects in Low-Power Neural Network Accelerators Via Retraining-Free Weight Approximation
Authors: Hosseini Fateme S. , Meng Fanruo , Yang Chengmo , Wen Wujie , Cammarota Rosario
Published: September 2021

Hardware accelerators are essential to the accommodation of ever-increasing Deep Neural Network (DNN) workloads on the resource-constrained embedded devices. While accelerators facilitate fast and energy-efficient DNN operations, their accuracy is threatened by faults in their on-chip and off-chip memories, where millions of DNN weights are held. The use of emerging Non-Volatile Memories (NVM) further exposes DNN accelerators to a non-negligible rate of permanent defects due to immature fabrication, limited endurance, and aging. To tolerate defects in NVM-based DNN accelerators, previous work either requires extra redundancy in hardware or performs defect-aware retraining, imposing significant overhead. In comparison, this paper proposes a set of algorithms that exploit the flexibility in setting the fault-free bits in weight memory to effectively approximate weight values, so as to mitigate defect-induced accuracy drop. These algorithms can be applied as a one-step solution when loading the weights to embedded devices. They only require trivial hardware support and impose negligible run-time overhead. Experiments on popular DNN models show that the proposed techniques successfully boost inference accuracy even in the face of elevated defect rates in the weight memory.
Schedulability Analysis for Timed Automata With Tasks
Authors: Sun Jinghao , Guan Nan , Shi Rongxiao , Tan Guozhen , Yi Wang
Published: September 2021

Research on modeling and analysis of real-time computing systems has been done in two areas, model checking and real-time scheduling theory. In model checking, an expressive modeling formalism such as timed automata (TA) is used to model complex systems, but the analysis is typically very expensive due to state-space explosion. In real-time scheduling theory, the analysis techniques are highly efficient, but the models are often restrictive. In this paper, we aim to exploit the possibility of applying efficient analysis techniques rooted in real-time scheduling theory to analysis of real-time task systems modeled by timed automata with tasks (TAT). More specifically, we develop efficient techniques to analyze the feasibility of TAT-based task models (i.e., whether all tasks can meet their deadlines on single-processor) using demand bound functions (DBF), a widely used workload abstraction in real-time scheduling theory. Our proposed analysis method has a pseudo-polynomial time complexity if the number of clocks used to model each task is bounded by a constant, which is much lower than the exponential complexity of the traditional model-checking based analysis approach (also assuming the number of clocks is bounded by a constant). We apply dynamic programming techniques to implement the DBF-based analysis framework, and propose state space pruning techniques to accelerate the analysis process. Experimental results show that our DBF-based method can analyze a TAT system with 50 tasks within a few minutes, which significantly outperforms the state-of-the-art TAT-based schedulability analysis tool TIMES.
Guaranteeing Timely Response to Changes of Monitored Objects by Assigning Deadlines and Periods to Tasks
Authors: Zhou Quan , Li Guohui , Chen Qi , Li Jianjun
Published: September 2021

Timely response to changes of monitored objects is the key to ensuring the safety and reliability of cyber-physical systems (CPSs). There are two kinds of tasks in CPSs: update tasks and control tasks. Update tasks are responsible for updating the data in the system based on the state of the objects they monitor. Control tasks are responsible for making decisions based on the data in the system. The response time of the system to the change of a monitored object consists of two parts: the time taken by update tasks to reflect the change to the system, and the time taken by control tasks to make decisions according to the data in the system. Deadlines and periods of update tasks and control tasks directly affect the response time. Reasonable deadline and period assignment is the key to ensuring timely response to the changes of monitored objects. In this paper, we study the deadline and period assignment in CPSs. To the best of our knowledge, all existing work only focuses on the deadline and period assignment for update tasks with the goal of ensuring the freshness of the data in CPSs, and this is the first study focusing on the deadline and period assignment for both update tasks and control tasks with the goal of ensuring timely response to the changes of monitored objects. A new problem about response time control and system workload control is defined in this paper. Two deadline and period assignment methods are proposed to solve the defined problem. All the proposed methods can be used in the CPSs adopting the earliest deadline first (EDF) scheduling method. Experiments with randomly generated tasks are conducted to evaluate the performance of the proposed methods in terms of acceptance ratio and execution efficiency.
Cross-Layer Adaptation with Safety-Assured Proactive Task Job Skipping
Authors: Wang Zhilu , Huang Chao , Kim Hyoseung , Li Wenchao , Zhu Qi
Published: September 2021

During the operation of many real-time safety-critical systems, there are often strong needs for adapting to a dynamic environment or evolving mission objectives, e.g., increasing sampling and control frequencies of some functions to improve their performance under certain situations. However, a system's ability to adapt is often limited by tight resource constraints and rigid periodic execution requirements. In this work, we present a cross-layer approach to improve system adaptability by allowing
proactive skipping
of task executions, so that the resources can be either saved directly or re-allocated to other tasks for their performance improvement. Our approach includes three novel elements: (1) formal methods for deriving the feasible skipping choices of control tasks with safety guarantees at the functional layer, (2) a schedulability analysis method for assessing system feasibility at the architectural layer under allowed task job skippings, and (3) a runtime adaptation algorithm that efficiently explores job skipping choices and task priorities for meeting system adaptation requirements while ensuring system safety and timing correctness. Experiments demonstrate the effectiveness of our approach in meeting system adaptation needs.
Declarative Power Sequencing
Authors: Schult Jasmin , Schwyn Daniel , Giardino Michael , Cock David , Achermann Reto , Roscoe Timothy
Published: September 2021

Modern computer server systems are increasingly managed at a low level by baseboard management controllers (BMCs). BMCs are processors with access to the most critical parts of the platform, below the level of OS or hypervisor, including control over power delivery to every system component. Buggy or poorly designed BMC software not only poses a security threat to a machine, it can permanently render the hardware inoperative. Despite this, there is little published work on how to rigorously engineer the power management functionality of BMCs so as to prevent this happening.

This article takes a first step toward putting BMC software on a sound footing by specifying the hardware environment and the constraints necessary for safe and correct operation. This is best accomplished through automation: correct-by-construction power control sequences can be efficiently generated from a simple, trustworthy model of the platform’s power tree that incorporates the sequencing requirements and safe voltage ranges of all components.

We present both a modeling language for complex power-delivery networks and a tool to automatically generate safe, efficient power sequences for complex modern platforms. This not only increases the trustworthiness of a hitherto opaque yet critical element of platform firmware: regulator and chip power models are significantly simpler to produce than hand-written power sequences. This, combined with model reuse for common components, reduces both time and cost associated with platform bring-up for new hardware.

We evaluate our tool using a new high-performance 2-socket server platform with >100W per socket TDP, tight voltage limits and 25 distinct power regulators needing configuration, showing both fast (<10s) tool runtime, and correct power sequencing of a live system.
Liquid testing with your smartphone
Authors: Yue Shichao , Katabi Dina
Published: September 2021

Surface tension is an important property of liquids. It has diverse uses such as testing water contamination, measuring alcohol concentration in drinks, and identifying the presence of protein in urine to detect the onset of kidney failure. Today, measurements of surface tension are done in a lab environment using costly instruments, making it hard to leverage this property in ubiquitous applications. In contrast, we show how to measure surface tension using only a smartphone. We introduce a new algorithm that uses the small waves on the liquid surface as a series of lenses that focus light and generate a characteristic pattern. We then use the phone camera to capture this pattern and measure the surface tension. Our approach is simple, accurate, and available to anyone with a smartphone. Empirical evaluations show that our mobile app can detect water contamination and measure alcohol concentration. Furthermore, it can track protein concentration in the urine, providing an initial at-home test for proteinuria, a dangerous complication that can lead to kidney failure.
Remaining connected throughout design
Authors: Thinyane Hannah
Published: September 2021

Applying the unique experiences of designing technologies for vulnerable communities.