bluuebunny/crossref_metadata_2025 huggingface dataset:
The ethics of partiality
Authors: Lange Benjamin
Published: July 2022

Partiality is the special concern that we display for ourselves and other people with whom we stand in some special personal relationship. It is a central theme in moral philosophy, both ancient and modern. Questions about the justification of partiality arise in the context of enquiry into several moral topics, including the good life and the role in it of our personal commitments; the demands of impartial morality, equality, and other moral ideals; and commonsense ideas about supererogation. This paper provides an overview of the debate on the ethics of partiality through the lens of the domains of permissible and required partiality. After outlining the conceptual space, I first discuss agent‐centred moral options that concern permissions not to do what would be impartially optimal. I then focus on required partiality, which concerns associative duties that go beyond our general duties to others and require us to give special priority to people who are close to us. I discuss some notable features of associative duties and the two main objections that have been raised against them: the Voluntarist and the Distributive objections. I then turn to the justification of partiality, focusing on underivative approaches and reasons‐based frameworks. I discuss the reductionism and non‐reductionism debate: the question whether partiality is derivative or fundamental. I survey arguments for ‘the big three’, according to which partiality is justified by appeal to the special value of either projects, personal relationships, or individuals. I conclude by discussing four newly emerging areas in the debate: normative transitions of various personal relationships, relationships with AI, epistemic partiality, and negative partiality, which concerns the negative analogue of our positive personal relationships.
The impact of macroprudential policies on the transmission of shocks across financially integrated countries
Authors: Intungane Doriane
Published: July 2022

We study the implications of macroprudential policies across countries on the transmission of shocks when international investment activities are allowed. In a two‐country dynamic stochastic general equilibrium (DSGE) model in which international investors are borrowing constrained and pledge international assets, we introduce a time‐varying loan‐to‐value (LTV) ratio that adjusts to the variation of three different financial vulnerability indicators. We examine the effect of these policies on negative productivity and borrowing capacity shocks. Although time‐varying LTV ratios reduce the international propagation of the productivity shock, their response to the shock depends on the financial vulnerability indicator with which the LTV ratio changes. With a productivity shock, the adjustment of the LTV ratio to the deviation of credit or asset price helps to reverse the negative impact of the shock. With a financial shock, LTV ratios varying with a deviation of credit‐to‐GDP ratio or aggregate credit can mitigate the impact of a negative financial shock. Adjustment of the LTV ratios reduces the fluctuation of international investors' balance sheets, investment, and productivity. We find that countries improve their welfare when time‐varying LTV ratios are in place. The magnitude of the welfare gain differs with both the financial vulnerability indicator and the shock.
Season‐ and facial site‐specific skin changes due to long‐term mask wearing during the COVID‐19 pandemic
Authors: Nakamura Tomomi , Yoshida Hiroyuki , Haneoka Mai , Nakamura Shun , Takahashi Yoshito
Published: July 2022

Background

As people have regularly worn facial masks due to the coronavirus disease 2019 (COVID‐19) pandemic, mask‐wear‐related adverse effects on the skin have been recognized. The aim of this study was to explore skin changes, their seasonal variations in the general population caused by commonly used masks and a possible mechanism underlying negative effects of mask‐wearing.

Materials and methods

Eighteen Japanese females participated in the study during summer and winter in Japan. Skin characteristics were measured in the non‐mask‐wearing preauricular area and the mask‐wearing cheek and perioral areas.

Results

Trans‐epidermal water loss (TEWL) on the cheek area tended to be increased in winter, which was positively correlated with skin scaliness on the same area. Ceramide (CER) content and composition in the mask‐covered stratum corneum (SC) were slightly changed between summer and winter, and CER [NP]/[NS] ratio was negatively correlated with the TEWL on the perioral skin in winter. Skin hydration and sebum secretion were higher on the cheek compared to the perioral area in summer. Skin redness was particularly high on the cheek in winter.

Conclusion

Mask‐wear‐related skin changes were season‐ and facial site‐specific, and alterations in SC CER may play a role in barrier‐related skin problems caused by mask use.
Understanding urban wealth perception using a hybrid dataset and ranking‐scoring framework
Authors: Liu Wuping , Guo Wei , Wu Ruijie
Published: July 2022

Research on urban perception using street view images has developed rapidly. Global urban perception datasets commonly used in local urban perception research may be inaccurate because of the differences in the characteristics across cities. Building a new local urban perception dataset requires a practical and efficient solution to construct high‐availability datasets and a corresponding urban perception framework. In this study, we developed a simple and effective ranking‐scoring framework containing two stages. First, we constructed a hybrid dataset in a 1:1 ratio, based on the global and local datasets. Next, we built a ranking‐scoring network that uses deep learning models to obtain the features of images and a learning‐to‐rank approach to determine perceptual scores. To validate the effectiveness of our method, we examined the perception of urban wealth in Wuhan, China. Our framework showed high accuracy when the hybrid dataset was used. Furthermore, we analyzed the differences between the spatial distribution of the perception results of the hybrid model and the global model in the study area. In addition, we analyzed driving factors for wealth perception, such as visual elements and road types. The results verified that the hybrid dataset is more suitable for local urban perception. Our framework could assist researchers in conducting fast and accurate urban perception of local cities, using a hybrid dataset and ranking‐scoring, thus enabling urban planners to provide more consideration to users' perceptions during the planning process without dwelling upon additional burdens.
Necessitation and the Changing Past
Authors: Schipper Arthur
Published: July 2022

A central tenet of truthmaker theory is that necessitation is necessary for truthmaking (nec). This paper defendsnecin a novel, piecemeal way, namely by responding to a potential counterexample involving a changing past. If Carter won a race att1but is later disqualified att2, then Carter no longer won att1. A wholly past event seems to have changed in the future. The event makes ‘Carter won the race att1’ (race) true betweent1‐2but fails to make it true att2. So, we have a potential counterexample to necessitation: a truthmaker ofracefails in another context to make the same truthbearerracetrue. I argue that the best solution to this challenge is not that there are different truthbearers att1‐2andt2(the semantic response), or thatracewas never true because of the future disqualification or will always be true despite the future disqualification. The best solution is to accept that the past can change: past events can change based on what happens in the future (e.g., via their effects). This paper's novel defence of necessitation will illustrate the importance of utilising explicitly ontological and commonsensical tools in accounting for truth.
MRI of the live fish brain at 3 Tesla: Feasibility, technique and interspecies anatomic variations
Authors: Clark Jennifer R. , Camus Alvin C. , Comolli Jessica , Divers Stephen J. , Gendron Karine P.
Published: July 2022

Advances in aquatic animal medicine and continued growth of the fish hobbyist and aquaculture communities have led to a developing interest in antemortem diagnostic imaging of aquatic species. The aims of this prospective, pilot study were to determine whether advanced neuroimaging can be safely achieved in live fish using clinically available equipment, to optimize imaging parameters, and to develop a comparative MRI atlas of a few fish species of economic or research value. Two each of channel catfish (Ictalurus punctatus), koi (Cyprinus rubrofuscus), and grass carp (Ctenopharyngodon idella) of at least 30 cm in length were individually anesthetized for 3 Tesla (3T) magnetic resonance imaging (MRI) of the brain. All fish achieved an adequate anesthetic level for prolonged immobilization during imaging. Diagnostic quality images were obtained for all subjects; however, the spatial resolution was maximized with larger fish. Imaging protocols were optimized for standard neuroimaging sequences. Additionally, inversion times for fluid‐attenuation inversion recovery (FLAIR) sequences were adapted to the naturally high protein content of fish pericerebral fluid. Following imaging, the fish successfully recovered from anesthesia, were humanely euthanized, and were immediately processed to assess brain histopathology. Necropsy confirmed the sex and health status of each fish. A limited comparative MRI atlas was created of the brains of these species for clinical reference. Findings from the current study supported the use of 3T MRI as an adjunct diagnostic test for fish with suspected neurologic disease and provided a limited anatomic atlas of the teleost brain for use as a reference.
Bayesian Inference With Gaussian Process Surrogates to Characterize Anisotropic Mechanical Properties of Skin From Suction Tests
Authors: Song Gyohyeon , An Jaehee , Tepole Adrian Buganza , Lee Taeksang
Published: July 2022

One of the intrinsic features of skin and other biological tissues is the high variation in the mechanical properties across individuals and different demographics. Mechanical characterization of skin is still a challenge because the need for subject-specific in vivo parameters prevents us from utilizing traditional methods, e.g., uniaxial tensile test. Suction devices have been suggested as the best candidate to acquire mechanical properties of skin noninvasively, but capturing anisotropic properties using a circular probe opening—which is the conventional suction device—is not possible. On the other hand, noncircular probe openings can drive different deformations with respect to fiber orientation and therefore could be used to characterize the anisotropic mechanics of skin noninvasively. We propose the use of elliptical probe openings and a methodology to solve the inverse problem of finding mechanical properties from suction measurements. The proposed probe is tested virtually by solving the forward problem of skin deformation by a finite element (FE) model. The forward problem is a function of the material parameters. In order to solve the inverse problem of determining skin properties from suction data, we use a Bayesian framework. The FE model is an expensive forward function, and is thus substituted with a Gaussian process metamodel to enable the Bayesian inference problem.
Determinant Physical Factors of Tennis Serve Velocity: A Brief Review
Authors: Colomar Joshua , Corbi Francisco , Brich Quim , Baiget Ernest
Published: July 2022

Purpose: To review the main physical aspects that could positively or negatively influence serve velocity (SV). Methods: An examination of existing literature including studies analyzing positive (biomechanical aspects, anthropometrics, range of motion, strength, and power) and negative (competition-induced fatigue) associations to SV are summarized in this review. Results: Aspects such as lower-leg drive, hip and trunk rotations, upper-arm extension, and internal rotation seem to be the major contributors to racquet and ball speed. Favorable anthropometric characteristics, such as body height, arm length, and a greater lean body mass, seem to positively influence SV. Also, strength indicators such as maximal isometric strength and rate of force development in specific joint positions involved in the kinetic chain alongside upper-body power seem to be related to faster serves. On the other hand, the effects of prolonged or repetitive match play may impair the aforementioned factors and negatively influence SV. Conclusions: Following specific serving models that seem to enhance velocity production and efficient motion is highly recommended. Moreover, achieving a higher impact point, alongside shifting body composition toward a greater lean body mass, will most likely aid toward faster serves. Programs aiming at improving maximal isometric strength and rate of force development in specific positions involved in the kinetic chain including stretch-shortening cycle predominance and the mimicking of the serve motion seem of great interest to potentially increase SV. Effective recovery and monitoring of these variables appear to be essential to avoid impairments produced by continued or repetitive competition loads.
Measures of Lower Body Strength Associated With Injuries in Australian Special Forces Selection Candidates
Authors: Doyle Tim L.A. , Fain AuraLea C. , Wills Jodie A. , Cooper Daniel , Toonen Kevin , Kamphius Benjamin
Published: July 2022

The diverse and grueling nature of activities undertaken during Special Forces selection makes it difficult to develop physical training to improve performance and reduce injury risk. It is generally accepted that increased strength is protective against injury, but it is unclear if this is evident in a Special Forces selection environment. This study investigated the effect of the rigors of a Special Forces selection course has on performance of the isometric mid-thigh pull, countermovement jump, squat jump, drop landing, elastic utilization ratio (EUR), and injury occurrence. Throughout the course, 26% of participants sustained a preventable lower limb injury, with 65% of these occurring at the knee. The uninjured had higher values of absolute strength as measured by isometric mid-thigh pull peak absolute force (3399 [371] N, 3146 [307] N; P = .022) and lower EUR (0.94 [0.08], 1.01 [0.09]; P = .025) compared to the injured. Preventable knee injury was significantly correlated with isometric mid-thigh pull (r = −.245, P = .031) and EUR (r = .227, P = .044). The selection course altered EUR for uninjured individuals only (P = .004). Findings indicate that individuals with higher strength levels may be at a lower risk of injury than their weaker counterparts.
Adolescents’ Physical Activity and Psychological Adjustment Across the First Year of the COVID-19 Pandemic
Authors: Ellis Wendy E. , Talebi Sarah , Dumas Tara M. , Forbes Lindsey
Published: July 2022

The outbreak of the COVID-19 virus dramatically changed daily life and created many obstacles for adolescents to engage in physical activity (PA). This study tracked rates of self-reported PA and examined its impact on adjustment among adolescents during the first 14 months of the pandemic. Canadian adolescents (N = 1068, 14–18 y, meanage = 16.95 y) reported on their frequency of PA, context of activity, and adjustment across 4 time points (April 2020 to June 2021). In line with our hypothesis, higher average levels of vigorous PA across the pandemic predicted less anxiety and depression and higher self-esteem at our study’s end. Vigorous PA also buffered the relationships COVID-19 stress had with anxiety and self-esteem. The results further support recommendations for PA throughout the pandemic and while dealing with lockdown situations.
Making Sense of Science Teacher Retention: Teacher Embeddedness and Its Implications for New Teacher Support
Authors: Larkin Douglas B. , Carletta Liz , Poole Patzelt Suzanne , Ahmed Khadija
Published: July 2022

This chapter reports initial findings from IMPREST, a 5-year research project that aims to investigate novice science teacher retention in the United States, with a focus on the underlying factors influencing retention for the teachers who stay. The goal of this project is to describe efforts to support novice science teachers across a wide range of school and community environments in places where the retention rate of novice science teachers is demonstrably well above average. In such districts, there are stakeholders who know and have learned a great deal about how to support novice science teachers and create conditions for their success, including district administrators, science supervisors, teachers, and community members, and a core aim of this project is to spread their hard-won practical wisdom to a wider audience. In this chapter, we report the design of the project, introduce the theory of teacher embeddedness used in this research, and share preliminary findings from case studies in six school districts. This study found that retained teachers placed a high value on collaborative environments, adequate resources and salary, and the relationships they developed both within the school organization and the community. In many of the case study districts, the collective mentoring efforts of the science department as a whole was viewed by teachers as more important for retention than individually assigned mentors. In these districts, the human resources process of “onboarding” into the job was distinct from induction efforts to provide longitudinal new teacher supports. One clear implication from this study is the value of adequate common planning time, shared spaces, and engagement in informal relationship-building efforts because doing so helps teachers develop the links necessary to sustain themselves professionally over time.
How Early-Career Science Teachers Negotiate Their Beliefs and Practices During an Online Induction Program
Authors: Ellis Joshua A. , Carro Natalie , Marichal Andrew , Titu Preethi , Roehrig Gillian H.
Published: July 2022

Prior research has reported that, in the absence of high-quality, science-specific induction support, science teachers’ beliefs and classroom practices are consolidated into teacher-centered, didactic practices as they are socialized into the classroom (Luft et al., 2003; Simmons et al., 1999). This study presents findings from A Study on Promoting Reflective and Equitable Practice Through Science Induction (PREPScI), an NSF Noyce Track 4 project focused on developing a strong empirical understanding of effective induction support for early-career secondary science teachers working in high-need schools. A primary goal of this project is to explore how participating teachers’ reform-based beliefs and practices change through their first year in an induction program. An explanatory sequential mixed-methods design (Creswell, 2014) was used to assess how 16 beginning science teachers who participated in our online induction program understood and enacted reform-based strategies within their K–12 classrooms. Quantitative analysis of changes in teacher responses to the Beliefs About Reformed Science Teaching and Learning instrument (BARSTL; Sampson, Enderle, & Grooms, 2013) over the span of one academic year revealed statistically significant changes in beliefs related to Lesson Design and Implementation and The Nature of the Science Curriculum. Similar analysis of observational data from the Reformed Teaching Observation Protocol (RTOP; Sawada et al., 2002) over the same span of time revealed no statistically significant changes over the academic year but suggested some evidence for an increase in reformed practices related to Student/Teacher Relationships. Qualitative analysis of Teacher Beliefs Interviews (TBIs; Luft & Roehrig, 2007) conducted with these teachers served to contextualize and explain findings from the BARSTL and RTOP. The three themes resulting from this analysis are making learning meaningful, agency in planning, and listening to student conversations. These findings illustrate how our early-career science teachers negotiated between the reform-based theories presented in their preservice licensure program and the realities of the classroom.
Uptake of Phytoplankton-Derived Carbon and Cobalamins by Novel
Acidobacteria
Genera in
Microcystis
Blooms Inferred from Metagenomic and Metatranscriptomic Evidence
Authors: Smith Derek J. , Kharbush Jenan J. , Kersten Roland D. , Dick Gregory J.
Published: July 2022

Interactions between heterotrophic bacteria and phytoplankton influence competition and successions between phytoplankton taxa, thereby influencing ecosystem-wide processes such as carbon cycling and algal bloom development. The cyanobacterium
Microcystis
forms harmful blooms in freshwaters worldwide and grows in buoyant colonies that harbor other bacteria in their phycospheres.
Heterotrophic Bacteria Dominate Catalase Expression during
Microcystis
Blooms
Authors: Smith Derek J. , Berry Michelle A. , Cory Rose M. , Johengen Thomas H. , Kling George W. , Davis Timothy W. , Dick Gregory J.
Published: July 2022

Cyanobacterial harmful algal blooms (CHABs) threaten freshwater ecosystems globally through the production of toxins. Toxin production by cyanobacterial species and strains during CHABs varies widely over time and space, but the ecological drivers of the succession of toxin-producing species remain unclear.
Oral Administration with Live Attenuated Citrobacter rodentium Protects Immunocompromised Mice from Lethal Infection
Authors: Wang Shuyu , Xia Xue , Liu Yue , Wan Fengyi
Published: July 2022

Enteropathogenic
Escherichia coli
(EPEC) and enterohemorrhagic
E. coli
(EHEC) are important causative agents for foodborne diseases worldwide. Besides antibiotic treatment, vaccination has been deemed as the most effective strategy for preventing EPEC- and EHEC-caused foodborne illnesses. Despite substantial progress made in identifying promising antigens and efficacious vaccines, no vaccines against EPEC or EHEC have yet been licensed.
Genome Sequence of Feline Papillomavirus Strain P20 Assembled from Metagenomic Data from the Skin of a House Cat Owner
Authors: Graham Ema H. , Adamowicz Michael S. , Angeletti Peter C. , Clarke Jennifer L. , Fernando Samodha C. , Herr Joshua R.
Published: July 2022

A feline papillomavirus genome was assembled from metagenomic sequencing data collected from the skin of a house cat owner. The circular genome of strain P20 is 8,069 bp in length, has a GC content of 54.38%, and displays genome organization typical of feline papillomaviruses. The genome exhibits approximately 75% sequence similarity to other feline papillomavirus genomes.
Contrasting Responses of Rhizosphere Fungi of
Scutellaria tsinyunensis
, an Endangered Plant in Southwestern China
Authors: Zuo You-wei , Yu Feng-qiong , Zhang Jia-hui , Xia Chang-ying , Zhang Huan , Deng Hong-ping
Published: July 2022

Our study highlighted the importance of rhizosphere fungal communities in an endangered plant,
S. tsinyunensis
. Comparative analysis of soil samples in nearly all extant
S. tsinyunensis
populations identified that soil properties, especially soil water content, might play essential roles in the survival and expansion of
S. tsinyunensis
.
Effects of a social participation-focused virtual reality intervention for community-dwelling stroke survivors with physical disabilities: a randomised controlled trial protocol
Authors: Chau Janita Pak Chun , Lo Suzanne Hoi Shan , Lau Alexander Yuk Lun , Lee Vivian Wing Yan , Choi Kai Chow , Kwok Eddie Chi Fai , Thompson David R
Published: July 2022

Introduction

Studies show that stroke survivors encounter physical and psychological limitations that restrict their participation in social and community activities. Systematic reviews have yielded inconclusive evidence regarding the effectiveness of different interventions intended to support stroke survivors’ social participation. Recent advances in virtual reality technology may offer promising solutions, although the optimal approach to enhance social participation among stroke survivors is yet to be determined. This trial aims to develop and evaluate the effectiveness of a social participation-focused virtual reality (SP-VR) intervention on the physical, psychological and social outcomes of community-dwelling stroke survivors with physical disabilities.

Methods and analysis

A two-arm randomised, controlled, assessor-blind clinical trial will be conducted with 250 stroke survivor–caregiver dyads recruited from three acute and one rehabilitation hospitals, and three stroke nurse-led clinics. Participants will be survivors of a first or recurrent stroke within 6 months of stroke onset and able to remain in a sitting position without support, and their primary caregivers. Eligible participants will be randomly allocated to receive the SP-VR intervention or usual care which includes conventional physical therapy services. The intervention group will receive a newly developed 6-week novel custom-made SP-VR application comprising two sessions weekly. Three SP-VR modules will cover key aspects of survivors’ social health needs, namely functional rehabilitation, social participation, and social interaction and recreation. The primary outcome for stroke survivors is social participation, and secondary outcomes include depressive symptoms, participation self-efficacy, physical function, functional mobility and social support. User satisfaction will be evaluated among both survivors and caregivers. Data will be collected in person at baseline, immediately after, and 3 months postintervention.

Ethics and dissemination

Ethical approval has been obtained from the Joint Chinese University of Hong Kong-New Territories East Cluster Research Ethics Committee (Ref. No.: 2019.676). Study results will be disseminated through peer-reviewed journals and conference presentations.

Trial registration number

ChiCTR2100050850.
Human-centric robotic manipulation in construction: generative adversarial networks based physiological computing mechanism to enable robots to perceive workers’ cognitive load
Authors: Liu Yizhi , Ojha Amit , Shayesteh Shayan , Jebelli Houtan , Lee SangHyun
Published: July 2022

With the recent advancements in sensing technologies, mechatronics, and artificial intelligence, collaborative robots are deployed on construction sites to assist workers in performing physically demanding tasks. However, the human–robot collaboration (HRC) can bring several occupational challenges to workers, ranging from physical collisions to adverse psychological impacts. To date, most of the literature on HRC has focused on addressing physical safety challenges, while very few have considered the psychological safety of the workers. To bridge this gap, by integrating generative adversarial network, autoencoder, machine learning, and robot adaptation techniques, this study proposes a novel physiological computing system that enables the collaborative robot to efficiently perceive workers’ psychological states and regulate its performance seamlessly. The results showed that the proposed system allowed the robot to adjust its performance as per workers’ cognitive load level with 89.6% accuracy. The findings revealed the potential of the proposed system in facilitating safe HRC in construction.
CHAOTIC BEHAVIOR IN FRACTIONAL HELMHOLTZ AND KELVIN–HELMHOLTZ INSTABILITY PROBLEMS WITH RIESZ OPERATOR
Authors: OWOLABI KOLADE M. , GÓMEZ-AGUILAR J. F. , KARACA YELIZ , LI YONG-MIN , SALEH BAHAA , ALY AYMAN A.
Published: July 2022

This paper introduces some important dissipative problems that are recent and still of intermittent interest. The classical dynamics of Helmholtz and Kelvin–Helmholtz instability equations are modeled with the Riesz operator which incorporates the left- and right-sided of the Riemann–Liouville non-integer order operators to mimic naturally the physical patterns of these models arising in hydrodynamics and geophysical fluids. The Laplace and Fourier transform techniques are used to approximate the Riesz fractional operator in a spatial direction. The behaviors of the Helmholtz and Kelvin–Helmholtz equations are observed for some values of fractional power in the regimes, [Formula: see text] and [Formula: see text], using different boundary conditions on a square domain in 1D, 2D and 3D (spatial-dimensions). Numerical results reveal some astonishing and very impressive phenomena which arise due to the variations in the initial and source function, as well as fractional parameter [Formula: see text], for subdiffusive and superdiffusive scenarios.
A NEW FRACTAL FRACTIONAL MODELING OF THE COMPUTER VIRUSES SYSTEM
Authors: PARTOHAGHIGHI MOHAMMAD , YUSUF ABDULLAHI , KARACA YELIZ , LI YONG-MIN , IBRAHIM TAREK F. , YOUNIS B. A. , SALEH BAHAA , ALY AYMAN A.
Published: July 2022

In this study, we model the fractal-fractional system of the Computer virus problem using the Atangana–Baleanu operator. Moreover, we have presented the existence and the uniqueness of the results under applying the Schauder fixed point and Banach fixed theorems. We have used the Atangana–Toufik technique to obtain the approximate solutions by choosing various values of orders. Different values of fractal-fractional orders along with different amounts of initial conditions are selected to examine the performance of the suggested numerical method on the new fractal-fractional system. Also, graphs in different dimensions are presented to exhibit the solutions, clearly.
Vibration-Based Structural Damage Detection Using the Interactive Autodidactic School Optimization Algorithm Based on an Energy-Dissipation Method
Authors: Jahangiri Milad , Hadianfard Mohammad Ali , Najafgholipour Mohammad Amir , Jahangiri Mehdi
Published: July 2022

The conventional modal strain energy (MSE), as a practical objective function, suffers from the lack of access to the damaged stiffness matrix and uses the intact stiffness matrix of the structure instead. To overcome the aforementioned deficiency of the MSE, this study proposes a reformed elastic strain energy-dissipation criterion called the “augmented modal strain energy” (AMSE) which is composed of relative differences of natural frequency and mode shape. In the AMSE not only the effects of the energy-dissipation criterion as a function of natural frequency but also the equilibria of the elastic strain energy as a function of mode shape are considered. Hereupon, the AMSE is implemented along with the interactive autodidactic school (IAS) optimization algorithm to investigate the effectiveness of the proposed identification method. In this regard, the AMSE is verified by assessing three benchmark truss and frame structures. The obtained results confirm the reliable performance of AMSE in both terms of intensification and diversification. Furthermore, it is observed that despite using noise-polluted modal data, the proposed AMSE not only identifies the damage location accurately, but also anticipates the extent of damage precisely. Consequently, the proposed energy-dissipation-based objective function (AMSE) is suggested, along with the IAS optimization algorithm, as a robust technique for the damage detection of structures.
Deep Learning Models for Time-History Prediction of Vehicle-Induced Bridge Responses: A Comparative Study
Authors: Li Huile , Wang Tianyu , Yang Judy P. , Wu Gang
Published: July 2022

Time-history responses of the bridge induced by the moving vehicle provide crucial information for bridge design, operation, maintenance, etc. As inspired by this, this work attempts to provide a new paradigm for vehicle–bridge interaction (VBI) by highlighting the comparison of different deep learning algorithms applied to the prediction of time-history responses of the bridge under vehicular loads. Particularly, three deep learning architectures with few and measurable input features developed by using fully-connected feedforward neural network, long short-term memory (LSTM) network, and convolutional neural network (CNN) are proposed on the basis of the governing equation of bridge vibrations. Three VBI systems with various vehicle models are developed and further validated to produce reliable training data. To examine the accuracy of the predictive models, two advanced metrics are exploited for time-history estimate. Moreover, the proposed deep learning models are comprehensively investigated through a parametric study on the influential factors associated with the VBI system and network architecture. The results show that deep feedforward neural network (DFNN), LSTM network, and CNN can be applied in VBI analysis to estimate the bridge time-history response. The three neural networks have comparable prediction accuracies. When considering the irregularity excitation, CNN is found to be the most efficient predictive model, while DFNN needs the least training time under perfect bridge surface condition.
Dynamic Amplification Factors of Partial-Interaction Composite Beams Acted Upon by the Moving Load
Authors: Sun Qikai , Zhang Nan , Liu Xiao , Cheng Zenong
Published: July 2022

This paper focuses on the dynamic response, mainly dynamic amplification factors (DAFs), of partial-interaction composite beams (PICBs) based on the Timoshenko beam theory (TBT). By assuming that each sub-beam behaves as an independent Timoshenko beam, the governing differential equations of motion of the PICBs are derived under the action of dynamic load. The natural frequencies and modal shapes for simply supported PICBs are also extracted. For decoupling the governing differential equations of motion, the orthogonality property of two distinct vibration modes is checked and applied for further analysis. The modal superposition method is then utilized to derive the analytical expressions of transverse deflection, interfacial shear slip, and normal stresses of the PICBs subjected to the moving load. Finally, two test beams are organized to validate the proposed methodology. For this purpose, the results which are calculated by ANSYS and obtained from available methods are appropriately compared. The effects of shear connector stiffness and speed of the moving load on the DAFs of the PICB acted upon by the moving constant load are discussed.
Image Interpolation Based on 2D-DWT with Novel Regularity-Preserving Algorithm Using RLS Adaptive Filters
Authors: Sadaghiani Abdol Vahab Khalili , Sheikhaei Samad , Forouzandeh Behjat
Published: July 2022

This paper proposes a novel method for the image interpolation problem based on two-dimensional discrete wavelet transform (DWT) with the edge preserving approach. The purpose of this method is to consider two contrasting issues of over-smoothing and creation of spurious edges at the same time, and offer a novel solution based on statistical dependencies of image sub-bands, and noise behavior. The offered method has a multi-faceted approach for the problem; by sub-band coding, it handles each 2D-DWT image sub-band with a different solution. For LH and HL sub-bands, two algorithms work together in order to preserve regularity. Area_Check algorithm is a four-phase edge-preserving algorithm that aims to recognize and interpolate separating lines of environments and edgy regions in the best possible way. On the other hand, RLS_AVG algorithm interpolates smooth surfaces of the image by keeping the regularity of the image without over-smoothing. In this regard, the offered algorithm has a great power to counter jaggies and annoying artifacts. In the end, in order to demonstrate the capability, and performance of the proposed method, the final results in various metrics are compared with the results of the most famous and the newest image interpolation methods.
Experimental Demonstration of STT-MRAM-based Nonvolatile Instantly On/Off System for IoT Applications: Case Studies
Authors: Li Yueting , Kang Wang , Zhou Kunyu , Qiu Keni , Zhao Weisheng
Published: July 2022

Energy consumption has been a big challenge for electronic devices, particularly for battery-powered Internet of Things (IoT) equipment. To address such a challenge, on the one hand, low-power electronic design methodologies and novel power management techniques have been proposed, such as nonvolatile memories and instantly on/off systems; on the other hand, the energy harvesting technology by collecting signals from human activity or the environment has attracted widespread attention in the IoT area. However, the system with self-powered energy harvesting may suffer frequent energy failures or fluctuating energy conditions, which degrade system reliability and user experience. Therefore, how to make the system under unreliable power inputs operate correctly and efficiently is one of the most critical issues for energy harvesting technology. In this article, we built an instantly on/off system based on nonvolatile STT-MRAM for IoT applications, which can instantly power on/off under different conditions of the harvested energy. The system powers on and operates normally when the harvested energy is enough (over the preset threshold); otherwise, the system powers off and stores the operational data back to the nonvolatile STT-MRAM. We described implementations of the hardware/software co-designed architecture (with image acquisition as an example) based on the commercialized 32 MB STT-MRAM, and we experimentally demonstrated the system functionality and efficiency under five typical energy harvesting scenarios, including radio frequency, thermal, solar, piezoelectric, and WIFI. Our experimental results show that the power consumption and data restore time were reduced by 15.1% and 714 times, respectively, in comparison with the DRAM-based counterpart.
Author Reflections on Creating Accessible Academic Papers
Authors: Menzies Rachel , Tigwell Garreth W. , Crabb Michael
Published: July 2022

Academic papers demonstrate inaccessibility despite accessible writing resources made available by SIGACCESS and others. The move from accessibility guidance to accessibility implementation is challenging for authors. Our work focuses on understanding what challenges authors of academic papers face in creating content elements (e.g., tables, charts, images) to better understand how to improve accessibility. We classified 3,866 content elements from 330 papers covering a 10-year sample of academic work from ASSETS to understand the variety used. We also reflected on the design choices that make the content elements inaccessible. We then conducted interviews with 13 academic authors from PhD student through to Professor Emeritus that publish within top-tier accessibility and HCI venues to understand the challenges faced in creating accessible content. We found critical issues in how academics understand and implement accessibility while also balancing the visual design of the paper. We provide recommendations for improving accessibility in the academic paper-writing process and focus on steps that can be taken by authors, publishers, researchers, and universities.
Flow Computation Pioneer Irmgard Flügge-Lotz (1903–1974)
Authors: Freund Jonathan B.
Published: July 2022

Volumes of this journal typically include one or two historical articles, many of which celebrate the life and impact in fluid mechanics of a recently deceased contributor to the field. The Editorial Committee recently stepped beyond this model to examine whom might have been missed over the years. Naturally, even when a candidate is identified, the passing of time makes it hard to find authors with living memory of the subject. Fortunately, in the case of Professor Dr. Irmgard Flügge-Lotz there is a rare opportunity: An appropriate article appeared in the collection Women in Mathematics, coauthored by her first PhD student John Spreiter and her husband Wilhelm Flügge, both her colleagues at Stanford University. We republish this article to share her remarkable story and contributions in fluid mechanics, as she worked with Prandtl, led a research group at ONERA ( Office national d'études et de recherches aérospatiales), and eventually became the first woman professor of engineering at Stanford.
Epinephrine evokes shortening of human airway smooth muscle cells following β2adrenergic receptor desensitization
Authors: Deeney Brian T. , Cao Gaoyuan , Orfanos Sarah , Lee Jordan , Kan Mengyuan , Himes Blanca E. , Parikh Vishal , Koziol-White Cynthia J. , An Steven S. , Panettieri Reynold A.
Published: July 2022

Epinephrine (EPI), an endogenous catecholamine involved in the body’s fight-or-flight responses to stress, activates α1-adrenergic receptors (α1ARs) expressed on various organs to evoke a wide range of physiological functions, including vasoconstriction. In the smooth muscle of human bronchi, however, the functional role of EPI on α1ARs remains controversial. Classically, evidence suggests that EPI promotes bronchodilation by stimulating β2-adrenergic receptors (β2ARs). Conventionally, the selective β2AR agonism of EPI was thought to be, in part, due to a predominance of β2ARs and/or a sparse, or lack of α1AR activity in human airway smooth muscle (HASM) cells. Surprisingly, we find that HASM cells express a high abundance of ADRA1B (the α1AR subtype B) and identify a spontaneous “switch-like” activation of α1ARs that evokes intracellular calcium, myosin light chain phosphorylation, and HASM cell shortening. The switch-like responses, and related EPI-induced biochemical and mechanical signals, emerged upon pharmacological inhibition of β2ARs and/or under experimental conditions that induce β2AR tachyphylaxis. EPI-induced procontractile effects were abrogated by an α1AR antagonist, doxazosin mesylate (DM). These data collectively uncover a previously unrecognized feed-forward mechanism driving bronchospasm via two distinct classes of G protein-coupled receptors (GPCRs) and provide a basis for reexamining α1AR inhibition for the management of stress/exercise-induced asthma and/or β2-agonist insensitivity in patients with difficult-to-control, disease subtypes.
Critical Decision-Making Issues in Disaster Relief Supply Management: A Review
Authors: Ma Ke , Yan Hong , Ye Yusen , Zhou Dao , Ma Dongce
Published: July 2022

This paper comprehensively reviews the literature related to disaster relief supply management in recent years by taking the perspectives of three critical decision-making issues, i.e., coordination issues, facility location decisions, and inventory decisions. For each decision-making issue discussed, we clarify the barriers of current research papers and identify the major challenges and critical factors that should be considered. In the following, we present the perspectives on the road of coordination between multiple relief actors, characterize the location decisions of relief facilities with a variety of optimization objectives, and emphasize the importance of relief supply varieties and critical factors in the decisions of disaster relief inventories. Future research directions are recommended for further discussions.
Construction of Music Intelligent Creation Model Based on Convolutional Neural Network
Authors: Chen Jing
Published: July 2022

The application of machine learning technology to intelligent music creation has become a very important field in music creation. The main current research on music intelligent creation methods uses fixed coding steps in audio data, which lead to weak feature expression ability. Based on convolutional neural network theory, this paper proposes a deep music intelligent creation method. The model uses a convolutional recurrent neural network to generate an effective hash code, first preprocesses the music signal to obtain a Mel spectrogram, and then inputs it into a pretrained CNN to extract from its convolutional layers. The network space details and the semantic information of musical symbols are used to construct the feature map sequence using selection strategy for the feature map of each convolutional layer, so as to solve the problem of high data feature dimension and poor recognition performance. In the simulation process, the Mel cepstral coefficient method (MFCC) was used to extract the features of four different music signals, and the features that could represent each signal were extracted through the convolutional neural network, and the continuous signals were discretized and reduced. The experimental results show that the high-dimensional music data are dimensionally reduced at the data level. After the data are compressed, the correct rate of intelligent creation is as high as 98%, and the characteristic signal distortion rate is reduced to 5% below, effectively improving the algorithm performance and the ability to create music intelligently.
Investigation of the Mechanism of Periploca forrestii against Rheumatoid Arthritis with Network Pharmacology-Based Analysis
Authors: Wang Qiuyi , Yao Xueming , Ling Yi , Huang Ying , Chen Changming , Hou Lei , Yang Yutao , Wu Hongyan , Ma Wukai
Published: July 2022

Periploca forrestii Schltr (P. forrestii) is an edible medicinal herb with various health benefits such as treating antirheumatoid arthritis (RA), reducing inflammation, and preventing tumor growth. The active ingredients in P. forrestii responsible for its protective effect against RA, however, remain unknown. In this study, the active ingredient of P. forrestii and its potential mechanism of action against RA were investigated by network pharmacology and enrichment analysis. The methods included predicting target genes of P. forrestii, constructing a protein interaction network, and performing gene-ontology (GO) and Kyoto-encyclopedia of genes and genomes (KEGG) enrichment analysis. We discovered targets of RA through retrieval of OMIM and GeneCards public databases. Cardiac glycosides (CGs) are considered the primarily active ingredients of P. forrestii, and the target genes of GCs were discovered to be overlapped with relevant targets of RA using the Venn diagram. After that, prediction of relevant targets of P. forrestii was accomplished with a network pharmacology-based approach. Through the Venn diagram, we discovered 99 genes shared in the target genes of P. forrestii and RA. Gene enrichment analysis showed that the mechanisms of CGs against RA are associated with 55 signaling pathways, including endocrine resistance, Epstein-Barr virus infection, bladder cancer, prostate cancer, and coronavirus disease (COVID-19) signaling pathways. Coexpression analysis indicated ADSL, ATIC, AR, CCND1, MDM2, and HSP90AA1 as the hub genes between putative targets of P. forrestii-derived CGs and known therapeutic targets of RA. In conclusion, we clarified the mechanism of action of P. forrestii against RA, which would provide a basis for further understanding the clinical application of P. forrestii.
Construction of a Novel MYC-Associated ceRNA Regulatory Network to Identify Prognostic Biomarkers in Colon Adenocarcinoma
Authors: Xin Rui , Tang Xiao-Mei , Jiang Ying-Jie , Yu Fei , Li Sha , Jia Cheng-You , Wang Gao-Ren , Fu Da , Liu Ji-Bin , Ma Yu-Shui
Published: July 2022

Colorectal cancer (CRC) includes colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ). Competitive endogenous RNA (ceRNA) is crucial for cancer pathogenesis. Abnormal expression of MYC is generally associated with a poor colon adenocarcinoma prognosis. The present study aimed to identify a novel MYC-associated ceRNA regulatory network and identify potential prognostic markers associated with COAD. We obtained the transcriptome sequencing profiles of 462 COAD cases from the TCGA database and analyzed differentially expressed genes (DEGs) in MYC high expression (MYChigh) and MYC low expression (Myclow) tumors. We identified an important lncRNA, LINC00114, which effectively predicts overall survival and plays a protective role in COAD. Moreover, the LINC00114/miR-216a-5p axis was identified as a clinical prognostic model. The predicted target genes of the LINC00114/miR-216a-5p axis include uromodulin Like 1 (UMODL1) and oncoprotein induced transcript 3 (OIT3), which are closely related to the survival and prognosis of COAD patients. In summary, we constructed a novel ceRNA regulatory network and identified potential biomarkers for the targeted therapy and prognosis of COAD.