bluuebunny/crossref_metadata_2025 huggingface dataset:
Ontogenetic Variation in Blade Toughness May Contribute to the Spread of Turbinaria ornata Across the South Pacific
Authors: Betancourt Austin M. , Fenwick Ileana F. , Howard Hunter B. , Long Alexys E. , Fong Peggy , Barber Paul H. , Fong Caitlin R.
Published: October 2022

Coral reefs are shifting from coral to algal‐dominated ecosystems worldwide. Recently, Turbinaria ornata, a marine alga native to coral reefs of the South Pacific, has spread in both range and habitat usage. Given dense stands of T. ornata can function as an alternative stable state on coral reefs, it is imperative to understand the factors that underlie its success. We tested the hypothesis that T. ornata demonstrates ontogenetic variation in allocation to anti‐herbivore defense, specifically that blade toughness varied nonlinearly with thallus size. We quantified the relationship between T. ornata blade toughness and thallus size for individual thalli within algal stands (N = 345) on seven fringing reefs along the north shore of Moorea, French Polynesia. We found that blade toughness was greatest at intermediate sizes that typically form canopies, with overall reduced toughness in both smaller individuals that refuge within the understory and older reproductive individuals that ultimately detach and form floating rafts. We posit this variation in blade toughness reduces herbivory on the thalli that are most exposed to herbivores and may facilitate reproduction in dispersing stages, both of which may aid the proliferation of T. ornata.
The Influence of Host Specificity and Temperature on Bacterial Communities Associated with Sargassum (Phaeophyceae) Species
Authors: Li Huan , Li Jing‐Jing , Gao Tian‐Heng , Bi Yuan‐Xin , Liu Zheng‐Yi
Published: October 2022

Host‐related microbiota are critically important for the adaptation/acclimation of hosts to changing environments, but how environmental factors and host characteristics shape the microbial communities remains largely unknown. We investigated the effects of temperature on habitat‐forming macroalgae and their associated bacterial communities. Three Sargassum species (S. horneri, S. fusiforme, and S. thunbergii) and seawater samples were sampled in Gouqi Island, China, and these macroalgal samples were incubated at different temperatures (10, 20, and 27°C) for 7 d. Bacterial communities were identified from the 16S rRNA gene V3–V4 regions. The algae‐associated bacterial communities of the field samples were significantly different from seawater, implying host specificity. During laboratory incubation, decreased physiological status (photosynthetic rate and oxidative stress response) was detected for all the species at 10°C, especially with regard to S. horneri and S. fusiforme. For each host, associated bacterial communities at 20 and 27°C clustered closely, and these were separated from samples at 10°C based on constrained PCoA analyses. Permutational multivariate analysis of variance revealed that algae‐associated bacterial communities were more affected by host species (23.3%) than by temperature (2.48%) during laboratory incubation. The changes in bacterial community composition may be influenced by algae metabolites, which should be tested in a future study. These results further contribute to our understanding of algal microbiome changes in response to environmental changes.
A self‐supervised monocular depth estimation model with scale recovery and transfer learning for construction scene analysis
Authors: Shen Jie , Yan Wenjie , Qin Shengxian , Zheng Xiaoyu
Published: October 2022

Estimating the depth of a construction scene from a single red‐green‐blue image is a crucial prerequisite for various applications, including work zone safety, localization, productivity analysis, activity recognition, and scene understanding. Recently, self‐supervised representation learning methods have made significant progress and demonstrated state‐of‐the‐art performance on monocular depth estimation. However, the two leading open challenges are the ambiguity of estimated depth up to an unknown scale and representation transferability for a downstream task, which severely hinders the practical deployment of self‐supervised methods. We propose a prior information‐based method, not depending on additional sensors, to recover the unknown scale in monocular vision and predict per‐pixel absolute depth. Moreover, a new learning paradigm for a self‐supervised monocular depth estimation model is constructed to transfer the pre‐trained self‐supervised model to other downstream construction scene analysis tasks. Meanwhile, we also propose a novel depth loss to enforce depth consistency when transferring to a new downstream task and two new metrics to measure transfer performance. Finally, we verify the effectiveness of scale recovery and representation transferability in isolation. The new learning paradigm with our new metrics and depth loss is expected to estimate the monocular depth of a construction scene without depth ground truth like light detection and ranging. Our models will serve as a good foundation for further construction scene analysis tasks.
Divine and Human Love in the Philosophy of Miklos Vetö (1936‐2020)
Authors: Tóth Beáta
Published: October 2022

During recent decades there has been an upsurge of studies exploring the nature and conditions of human love. This article examines an original and consciously Christian approach by the Hungarian‐French philosopher, Miklós Vetö, who builds his innovative account of love on trinitarian foundations (Court traité sur l'amour, L'Harmattan, 2020). His ‘expanded’ metaphysics lays bare the theological content of philosophical assumptions, and it also rethinks traditional theological themes in a novel conceptual way. Our survey proceeds in three consecutive steps. First, it reflects on the overall shape of Vetö's project and on his distinctive view of the relationship between the philosophical and the theological enterprise. Second, it investigates some key concepts of Vetö's (uncompleted) philosophy of God and central elements of his conception of divine love. Third, it examines Vetö's phenomenological analyses of various forms of human love in order to outline the pivotal building blocks of his novel approach, which, however, provokes further questions and invites one to revitalise both the theological and the philosophical quest for a better understanding of this ceaselessly intriguing topic.
Epistemic bootstrapping as a failure to use an independent source
Authors: Fernández‐Vargas Miguel Ángel
Published: October 2022

The problem of epistemic bootstrapping requires explaining, in a principled manner, why a subject who engages in bootstrapping fails to know the conclusion of her reasoning. Existing proposed solutions to the problem provide unsatisfactory explanations regarding the bootstrapper's ignorance. This paper puts forward a novel solution and argues that it satisfactorily explains the ignorance of the bootstrapper, while avoiding the difficulties that other proposals face. Section 1 explains what epistemic bootstrapping is, defines the problem it poses for a theory of knowledge, and outlines the basic desiderata demanded of any acceptable solution to the problem. Section 2 explicates the proposal I defend throughout the rest of the paper. Here, I contend that the wrong−making feature of bootstrapping which ultimately explains the bootstrapper's ignorance is a failure to use an independent source in checking the accuracy of the reports of a given source. I call this explanation the “Independence proposal.” Section 2 also argues that the phenomenon of bootstrapping is broader than is usually assumed; there are cases of bootstrapping that do not fit the superficial structure of the prototypical cases discussed in the literature, and any good proposal should apply to these as well. Section 3 argues that the independence proposal does better than other current proposals in fulfilling the desiderata identified in Section 1. Section 4 sums up the central contributions of the paper.
Insights into the Ultrafast Photodissociation Dynamics of Isoprene‐Derived Criegee Intermediates
Authors: Antwi Ernest , Packer Niamh A. , Ratliff Jordyn M. , Marchetti Barbara , Karsili Tolga N. V.
Published: October 2022

Isoprene is the most abundant nonmethane volatile organic compound emitted into the troposphere by terrestrial vegetation. Reaction with ozone represents an important isoprene removal process from the troposphere and is a well‐known source of Criegee intermediates (CIs), which are reactive carbonyl oxides. Three CIs, formaldehyde oxide (CH2OO), methyl vinyl ketone oxide (MVK‐oxide) and methacrolein oxide (MACR‐oxide) are formed during isoprene ozonolysis. All three CIs contain strongly absorbing ππ* states, electronic excitation, which leads to dissociation to form aldehyde/ketone + oxygen products. Here, we compare the excited state chemistry of CH2OO, MVK‐oxide and MACR‐oxide in order to ascertain how increasing molecular complexity affects their photodynamics. In CH2OO, vertical excitation to the S2 state leads to prompt O‐O bond fission with a unity quantum yield. Branching into both the O (1D) + H2CO (S0) and O (3P) + H2CO (T1) product channels is predicted, with 80% of trajectories dissociating to form the former product pair. Analogous vertical excitation of the lowest energy conformers of MVK‐oxide and MACR‐oxide also undergoes O‐O bond fission to form O + MVK/MACR products—albeit with a nonunity quantum yield. In the latter case, ca. 10% and 25% of trajectories remain as the parent MVK‐oxide and MACR‐oxide molecules, respectively. Additionally, at most only 5% of the dissociating trajectories form O (3P) + MVK/MACR (T1) products, with a greater fraction forming O (1D) + MVK/MACR (S0) products (cf. CH2OO). This latter observation coupled with the greater fraction of undissociated trajectories aligns with the bathochromic shift in the electronic absorption of the MACR‐oxide and MVK‐oxide (cf. CH2OO). We discuss the implications of the results in a broader context, including those that are relevant to the atmosphere.
Life cycle environmental impacts of consumer packaging products in Japan
Authors: Pragati Pooja , Maeda Yasunobu
Published: October 2022

Several Japanese companies and the government are recently promoting a plastic ban and imposing a tax levy to curb litter and reduce greenhouse gas emissions. This has led to a rapid rise of nonplastic packaging alternatives. While plastics and litter are pressing concerns, it is paramount to examine environmental risks of other alternatives before wide application and legislative action, to not further the risk of environmental damage. This study aims to quantify and compare plastic products such as polyethylene‐terephthalate (PET) bottles and high‐density polyethylene (HDPE) bags with widely available alternatives in Japan like glass bottles, aluminum bottles, paper bags, and textile bags, to find a product with the least environmental impact. A life cycle assessment is conducted from a cradle‐to‐grave environmental impact approach that includes raw material extraction, production, transportation, end‐of‐life treatment, and disposal. Sixteen impact categories including climate change, acidification, aquatic‐toxicity, so forth, and weighing is assessed using the MiLCA software. The functional unit is one piece of each packaging product, and impacts of product‐filling, storage, recycling, and reuse are excluded for a consistent comparison. HDPE bags performed better than paper and textile bags in 15 of the 16 analyzed impact categories. Similarly, PET bottles outperformed aluminum and glass bottles in 12 out of the 16 impact categories analyzed. Weighted results also highlight the heightened negative environmental impacts of replacing plastic packaging with widely available alternatives.
Exploring acceptable risk in engineering and operations research and management science by bibliometric analysis
Authors: Zhang Yanni , Duan Zhengxiao , Shu Pan , Deng Jun
Published: October 2022

As the decision‐making basis for “safety” in risk management and risk assessment activities, acceptable risk has always been an important topic of risk‐related research. Based on the records in the Science Citation Index Expanded database and Social Sciences Citation Index database via the Web of Science Core Collection, 1124 articles or reviews related to acceptable risk in engineering and operations research and management science were retrieved. These documents, published between 1961 and 2021, covered 3056 authors, 75 countries/territories, 1296 institutions, and 323 journals. In this study, bibliometric data such as annual growth trends were analyzed by using descriptive statistics. Through the co‐occurrence maps created by CiteSpace and Gephi, the most productive and influential countries/territories, institutions, and authors as well as their cooperation networks were identified. Further analysis was conducted to determine the core publications and publication sources in this field through co‐citation analysis. Insights into focus areas and research topics over time were obtained through keyword co‐occurrence analysis. This study provides a macroscopic overview of acceptable risk research and may help researchers better understand this research field and predict its dynamic directions.
Geographic location or experience: Using PRISM to understand how people seek flood risk information
Authors: Stephens Keri K. , Tich Kendall P. , Carlson Nancy H. , Doucet Cassidy S.
Published: October 2022

Flooding is increasing worldwide, and with climate change, people need help understanding these changing conditions and that their flood risk may also change. This study extends the planned risk information seeking model (PRISM) into the flood risk domain and examines the antecedents that explain flood risk information seeking behavior. Using a survey reflective of the population in the state of Texas (N = 1079), this study includes an operationalization of risk perception specific to the complexity of floods and explores two key moderators in the PRISM model. Findings suggest that using PRISM to elaborate flood risk information seeking behaviors explains 48% of the variance in information seeking intent and 37% of the variance in affective risk perception. Using multigroup modeling, the findings also reveal that simply living in an area at high risk for floods does not significantly impact any relationships in the model. However, having experience with flooding increases the strength of risk perception paths—in particular, perceived probability of flood risk—and better explains flood risk information seeking. Suggestions for how to use communication to influence risk perceptions and information seeking, as well as future directions for research, are also discussed.
From doing to leading: PGY‐1 to PGY‐2 transition
Authors: Blair Rachel A. , Eldam Alla M. , Ramani Subha
Published: October 2022

Background

Clinical trainees experience several professional transitions throughout their career, which can be exciting, anxiety‐provoking or both. The first to second post‐graduate year (PGY) transition for residents (junior doctors) in North America involves assuming new roles such as team leader, clinical supervisor, and teacher, often with minimal preparation. We explored resident experiences and emotions during this transition, and obtained their strategies for navigating this transition, through the lens of Bridges' transition model. This model has three stages: (1) ending, losing and letting go, (2) the neutral zone and (3) the new beginning.

Methods

We conducted one in‐person focus group and subsequent one‐on‐one virtual semistructured interviews (due to COVID‐19) of PGY‐2 and PGY‐3 residents who had previously undergone the transition. These sessions were recorded and transcribed, and thematic analysis was performed.

Findings

Four residents participated in the focus group, and 14 participated in one‐on‐one interviews. We identified five key themes: (1) not just a cog in the wheel, (2) contributing to growth of near‐peers, (3) being flexible and adaptive, (4) emulating resident role models and (5) relationships with attendings. Residents suggested a transitions‐focused retreat, simulation training to lead clinical emergencies, supervised opportunities for PGY‐1s to act as PGY‐2s coached by senior residents, and pairing PGY‐1s with senior residents to help prepare for the transition.

Conclusion

Professional transitions are both anxiety‐provoking and exciting. Clinical trainees need preparation to successfully navigate multiple transitions. The Bridges' transition model could be useful in conceptualising transitions and planning curricula.
An accurate genetic assay to identify human neutrophil antigen 2 deficiency
Authors: Li Yunfang , Schuller Randy M. , Wu Jianming
Published: October 2022

Objective

We aimed to develop accurate and user‐friendly genetic assays to identify the inherited neutrophil antigen‐2 (HNA‐2) deficiency in humans.

Background

HNA‐2 is one of the most important neutrophil antigens implicated in a number of human disorders. HNA‐2 deficiency or HNA‐2 null is a common phenotype observed in 3%–5% Americans. HNA‐2 null individuals are at risk to produce isoantibodies (or alloantibodies) that play important roles in transfusion‐related acute lung injury, immune neutropenia, and bone marrow graft failure. We previously demonstrated that the CD177 coding SNP 787A > T (c.787A > T) is the most important genetic determinant for HNA‐2 deficiency. However, reliable genetic assays are not available for routine clinical laboratory application up to now.

Study Design and Methods

A novel polymerase chain reaction (PCR) strategy was used to determine genotypes of the CD177 SNP c.787A > T. In the simplified PCR assay, all allele specific primers and internal control primers were included in the same reaction, which ensures reliability of the assay. In addition, a novel high‐throughput nested TaqMan assay was developed to determine genotypes of c.787A > T for large population genetic analysis of HNA‐2 deficiency.

Results

CD177 SNP c787A > T genotypes of 396 subjects were 100% concordant among the single PCR reaction method, the nested TaqMan assay, and Sanger Sequencing analysis. Out of 396 subjects, all 18 donors with the CD177 STP homozygous genotype were HNA‐2 null.

Conclusion

The novel PCR‐based genotyping assay is accurate to identify HNA‐2 deficient individuals and is suitable for clinical laboratories. In addition, the innovative high‐throughput nested TaqMan assay will be useful for large‐scale population screens and genetic studies of HNA‐2 deficiency.
Magnetic dipole moments as a strong signature for $$\alpha $$-clustering in even-even self-conjugate nuclei
Authors: Stellin Gianluca , Speidel Karl-Heinz , Meißner Ulf-G.
Published: October 2022

We investigate the magnetic dipole moments in even-even self-conjugate nuclei from$$^{12}$$12C to$$^{48}$$48Cr. For these nuclei, the measured gyromagnetic factors of excited states turn out to assume the same value of$$g \approx + 0.5$$g≈+0.5within statistical errors. This peculiar feature can be interpreted on the basis of collective excitations of$$\alpha $$α-clusters. Analogously, the behaviour of the same observable is studied for all isotopes obtained by adding one or two neutrons to the considered self-conjugate nuclei. It is found that for the$$N = Z + 1$$N=Z+1isotopes the$$\alpha $$α-cluster structure hardly contributes to the observed negative g- factor value, corroborating molecular$$\alpha $$α-cluster models. The addition of a further neutron, however, restores the original$$\alpha $$α-cluster g-factors, except for the semi-magic isotopes, in which the deviations from$$g \approx + 0.5$$g≈+0.5can be associated with the relevant shell closures. Secondly, we analyze the same observable in the framework of a macroscopic$$\alpha $$α-cluster model on a finite lattice of side lengthL. We focus on the discretization effects induced in the magnetic dipole moments of the$$2_1^+$$21+and the$$3_1^-$$31-states of$$^{12}$$12C at different values of the lattice spacinga.
Early time behavior of spatial and momentum anisotropies in kinetic theory across different Knudsen numbers
Authors: Borghini Nicolas , Borrell Marc , Roch Hendrik
Published: October 2022

We investigate the early time development of the anisotropic transverse flow and spatial eccentricities of a fireball with various particle-based transport approaches using a fixed initial condition. In numerical simulations ranging from the quasi-collisionless case to the hydrodynamic regime, we find that the onset of $$v_n$$

v
n

and of related measures of anisotropic flow can be described with a simple power-law ansatz, with an exponent that depends on the amount of rescatterings in the system. In the few-rescatterings regime we perform semi-analytical calculations, based on a systematic expansion in powers of time and the cross section, which can reproduce the numerical findings.
New physics in $$\text {b} \rightarrow \text {s}$$ transitions in the MF331 model
Authors: Duy N. T. , Thu P. N. , Huong D. T.
Published: October 2022

There are two sources that help to explain the $$\text {R}_\text {K}$$

R
K

, $$\text {R}_{\text {K}^*}$$

R

K
∗

anomalies in the MF331 model. The first is non-LFUV couplings of the new neutral gauge boson $$\text {Z}^{\prime }$$

Z
′

with leptons, $$\text {g}^{\text {Z}^\prime }(e)\ne \text {g}^{\text {Z}^\prime }(\mu ,\tau )$$

g

Z
′

(
e
)

≠

g

Z
′

(
μ
,
τ
)

, which causes the $$\text {R}_\text {K}$$

R
K

, $$\text {R}_{\text {K}^*}$$

R

K
∗

anomalies via $$\text {Z}^\prime $$

Z
′

-penguin diagrams involving newly charged gauge bosons $$\text {X}^{\pm }_{\mu }$$

X
μ
±

, and exotic U-quarks. The second is the contribution from the box diagram only for the first generation of leptons. We show that the penguin diagrams can not explain $$\text {R}_\text {K}$$

R
K

, $$\text {R}_{\text {K}^*}$$

R

K
∗

anomalies, and that the box diagram is required. The experimental constraints for $$\text {R}_\text {K}$$

R
K

and $$\text {R}_{\text {K}^*}$$

R

K
∗

result in new particle mass degeneracy. The contributions of NP to the branching ratios $$\text {Br}(\text {B}_{\text {s}}\rightarrow \mu ^+ \mu ^-), \text {Br}(\text {b}\rightarrow s \gamma )$$

Br

(

B
s

→

μ
+

μ
-

)

,
Br

(
b
→
s
γ
)

predict results that agree with the experimental limits in the allowed region of the NP scale.
Late-time-accelerated expansion esteemed from minisuperspace deformation
Authors: Tajahmad Behzad
Published: October 2022

The effects of minisuperspace deformation on Einstein–Hilbert action along with ordinary and phantom scalar fields as the matter contents are investigated. It is demonstrated that late-time-accelerated expansion and phase transition (from decelerated to accelerated) are obtained as a consequence of minisuperspace deformation. Finally, a mathematical theorem for distinguishing valid descriptions of the noncommutative frames is suggested.
The possibility of X(4014) as a $$D^*{\bar{D}}^*$$ molecular state
Authors: Duan Man-Yu , Chen Dian-Yong , Wang En
Published: October 2022

Within the framework of the local hidden gauge approach, we have studied the near-threshold $$D^* {\bar{D}}^*$$

D
∗

D

¯

∗

interaction with quantum numbers $$I(J^{PC}) = 0(0^{++})$$

I

(

J

PC

)

=
0

(

0

+
+

)

, $$0(2^{++})$$

0
(

2

+
+

)

, $$1(0^{++})$$

1
(

0

+
+

)

, and $$1(2^{++})$$

1
(

2

+
+

)

, respectively. The contact term and vector meson exchange term in coupled channels are taken into account in this work. One pole, which is found in the case of the quantum numbers $$I(J^{PC}) = 0(0^{++})$$

I

(

J

PC

)

=
0

(

0

+
+

)

, could be associated to the X(4014) recently observed by the Belle Collaboration. Thus, we suggest that the X(4014) may be an $$D^* {\bar{D}}^*$$

D
∗

D

¯

∗

molecular state with $$I(J^{PC}) = 0(0^{++})$$

I

(

J

PC

)

=
0

(

0

+
+

)

, and more precise information about X(4014), such as resonance parameters and decay properties, could be useful to shed light on its structure.
On Enhanced Second-Order Explicit Integration Methods with Controllable Algorithmic Dissipation and Adjustable Sub-Step Size for Hyperbolic Problems
Authors: Li Jinze , Li Hua , Lian Yiwei , Yu Kaiping , Zhao Rui
Published: October 2022

This paper constructs and analyzes a generalized composite two-sub-step explicit method to solve various dynamical problems effectively. Via the accuracy and dissipation analysis, the constructed explicit method is further developed into two novel members that achieve identical second-order accuracy, controllable algorithmic dissipation, and desired stability. Unlike all existing explicit schemes, the novel members employ two independent integration parameters ([Formula: see text] and [Formula: see text]) to control numerical features. The parameter [Formula: see text], denoting the splitting ratio of sub-step size, can determine the instant at which external loads are calculated, whereas another parameter [Formula: see text], denoting the spectral radius at the bifurcation point, can control numerical dissipation imposed. Independently adjusting the sub-step size is one significant advantage for solving dynamical problems triggered by discontinuous loads. This paper also provides two novel explicit members’ single-parameter versions for inexperienced users. Besides, the novel explicit members achieve a smaller local truncation error in acceleration, thus enhancing the solution accuracy in displacement and velocity. Numerical examples are solved to validate the significant superiority of the novel members in the solution accuracy.
How Should We Regulate Cryptocurrencies via Consensus?: A Strategic Framework for Optimal Legal Transaction Throughput
Authors: Ahuja Aditya , Ribeiro Vinay , Pal Ranjan
Published: October 2022

Permissionless blockchain consensus protocols have been leveraged for defining decentralized economies for the (commercial or private) trade of virtual and physical assets, using cryptocurrencies. In most instances, the assets being traded are
regulated
, which mandates that the legal right to their trade and their trade value are determined by the governmental regulator of the jurisdiction in which the trade occurs. Unfortunately, existing blockchains do not formalize proposal of legal cryptocurrency transactions, as part of the execution of their respective consensus protocols, resulting in illegal activities in the associated crypto-economies. In this contribution, unlike existing non-consensus solutions, which are prone to be more compute-time and audit-time intensive, we present a novel regulatory framework for blockchain protocols, for ensuring legal transaction confirmation as part of the blockchain consensus. As per our regulatory framework, we derive, through a stochastic game analysis, block proposal strategies under which legal transaction throughput supersedes throughput of traditional transactions, which are, in the worst case, an indifferentiable mix of legal and illegal transactions. Finally, we show that when a majority of the consensus protocol participants are licensed by the regulator to propose legal transactions, there exists a fair consensus execution policy to maximize the legal transaction throughput in the blockchain network.
Introduction to the Special Issue on Understanding the Spread of COVID-19, Part 2
Authors: Züfle Andreas , Gao Song , Anderson Taylor
Published: October 2022

Infectious diseases are transmitted between human hosts when in close contact over space and time. Recently, an unprecedented amount of spatial and spatiotemporal data have been made available that can be used to improve our understanding of the spread of COVID-19 and other infectious diseases. This understanding will be paramount to prepare for future pandemics through spatial algorithms and systems to collect, capture, curate and analyze complex, multi-scale human movement data to solve problems such as infectious diseases prediction, contact tracing, and risk assessment. In exploring and deepening the conversation around this topic, the five articles included in the second volume of this special issue employ diverse theoretical perspectives, methodologies, and frameworks, including but not limited to close contact modeling, infectious diseases spread prediction, mobility analysis, effective testing and intervention strategies. Rather than focusing on a narrow set of problems, these articles provide a glimpse into the diverse possibilities of leveraging spatial and spatiotemporal data for pandemic preparedness.
A Personalized Interaction Mechanism Framework for Micro-moment Recommender Systems
Authors: Lin Yi-Ling , Lee Shao-Wei
Published: October 2022

The emergence of the micro-moment concept highlights the influence of context; recommender system design should reflect this trend. In response to different contexts, a micro-moment recommender system (MMRS) requires an effective interaction mechanism that allows users to easily interact with the system in a way that supports autonomy and promotes the creation and expression of self. We study four types of interaction mechanisms to understand which personalization approach is the most suitable design for MMRSs. We assume that designs that support micro-moment needs well are those that give users more control over the system and constitute a lighter user burden. We test our hypothesis via a two-week between-subject field study in which participants used our system and provided feedback. User-initiated and mix-initiated intention mechanisms show higher perceived active control, and the additional controls do not add to user burdens. Therefore, these two designs suit the MMRS interaction mechanism.
Managing Delays in Human-Robot Interaction
Authors: Pelikan Hannah , Hofstetter Emily
Published: October 2022

Delays in the completion of joint actions are sometimes unavoidable. How should a robot communicate that it cannot immediately act or respond in a collaborative task? Drawing on video recordings of a face-scanning activity in family homes, we investigate how humans make sense of a Cozmo robot’s delays on a moment-by-moment basis. Cozmo’s sounds and embodied actions are recognized as indicators of delay but encourage human participants to act in ways that undermine the scanning process. In comparing the robot’s delay management strategies with human-human vocal and embodied practices, we demonstrate key differences in the sequences that impact how the robot is understood. The study demonstrates how delay events are accomplished as embodied displays that are distributed across co-participants. We present a framework for making delay transparent through situated explanations, particularly in the form of non-lexical sounds and bodily actions.
Lightweight Feature De-redundancy and Self-calibration Network for Efficient Image Super-resolution
Authors: Wang Zhengxue , Gao Guangwei , Li Juncheng , Yan Hui , Zheng Hao , Lu Huimin
Published: October 2022

In recent years, thanks to the inherent powerful feature representation and learning abilities of the convolutional neural network (CNN), deep CNN-steered single image super-resolution approaches have achieved remarkable performance improvements. However, these methods are often accompanied by large consumption of computing and memory resources, which is difficult to be adopted in real-world application scenes. To handle this issue, we design an efficient Feature De-redundancy and Self-calibration Super-resolution network (FDSCSR). In particular, a Feature De-redundancy and Self-calibration Block (FDSCB) is proposed to reduce the repetitive feature information extracted by the model and further enhance the efficiency of the model. Then, based on FDSCB, a Local Feature Fusion Module is presented to elaborately utilize and fuse the feature information extracted by each FDSCB. Abundant experiments on benchmarks have demonstrated that our FDSCSR achieves superior performance with relatively less computational consumption and storage resource than other state-of-the-art approaches. The code is available at
https://github.com/IVIPLab/FDSCSR
.
What Is the Intended Usage Context of This Model? An Exploratory Study of Pre-Trained Models on Various Model Repositories
Authors: Gong Lina , Zhang Jingxuan , Wei Mingqiang , Zhang Haoxiang , Huang Zhiqiu
Published: October 2022

There is a trend of researchers and practitioners to directly apply pre-trained models to solve their specific tasks. For example, researchers in software engineering (SE) have successfully exploited the pre-trained language models to automatically generate the source code and comments. However, there are domain gaps in different benchmark datasets. These data-driven (or machine learning based) models trained on one benchmark dataset may not operate smoothly on other benchmarks. Thus, the reuse of pre-trained models introduces large costs and additional problems of checking whether arbitrary pre-trained models are suitable for the task-specific reuse or not. To our knowledge, software engineers can leverage code contracts to maximize the reuse of existing software components or software services. Similar to the software reuse in the SE field, reuse SE could be extended to the area of pre-trained model reuse. Therefore, according to the model card’s and FactSheet’s guidance for suppliers of pre-trained models on what information they should be published, we propose
model contracts
including the pre- and post-conditions of pre-trained models to enable better model reuse. Furthermore, many non-trivial yet challenging issues have not been fully investigated, although many pre-trained models are readily available on the model repositories. Based on our model contract, we conduct an exploratory study of 1908 pre-trained models on six mainstream model repositories (i.e., the TensorFlow Hub, PyTorch Hub, Model Zoo, Wolfram Neural Net Repository, Nvidia, and Hugging Face) to investigate the gap between necessary pre- and post-condition information and actual specifications. Our results clearly show that (1) the model repositories tend to provide confusing information of the pre-trained models, especially the information about the task’s type, model, training set, and (2) the model repositories cannot provide all of our proposed pre/post-condition information, especially the intended use, limitation, performance, and quantitative analysis. On the basis of our new findings, we suggest that (1) the developers of model repositories shall provide some necessary options (e.g., the training dataset, model algorithm, and performance measures) for each of pre/post-conditions of pre-trained models in each task type, (2) future researchers and practitioners provide more efficient metrics to recommend suitable pre-trained model, and (3) the suppliers of pre-trained models should report their pre-trained models in strict accordance with our proposed pre/post-condition and report their models according to the characteristics of each condition that has been reported in the model repositories.
Simulator-based Explanation and Debugging of Hazard-triggering Events in DNN-based Safety-critical Systems
Authors: Fahmy Hazem , Pastore Fabrizio , Briand Lionel , Stifter Thomas
Published: October 2022

When Deep Neural Networks (DNNs) are used in safety-critical systems, engineers should determine the safety risks associated with failures (i.e., erroneous outputs) observed during testing. For DNNs processing images, engineers visually inspect all failure-inducing images to determine common characteristics among them. Such characteristics correspond to hazard-triggering events (e.g., low illumination) that are essential inputs for safety analysis. Though informative, such activity is expensive and error prone.

To support such safety analysis practices, we propose Simulator-based Explanations for DNN failurEs (SEDE), a technique that generates readable descriptions for commonalities in failure-inducing, real-world images and improves the DNN through effective retraining. SEDE leverages the availability of simulators, which are commonly used for cyber-physical systems. It relies on genetic algorithms to drive simulators toward the generation of images that are similar to failure-inducing, real-world images in the test set; it then employs rule learning algorithms to derive expressions that capture commonalities in terms of simulator parameter values. The derived expressions are then used to generate additional images to retrain and improve the DNN.

With DNNs performing in-car sensing tasks, SEDE successfully characterized hazard-triggering events leading to a DNN accuracy drop. Also, SEDE enabled retraining leading to significant improvements in DNN accuracy, up to 18 percentage points.
The Opportunity in Difficulty: A Dynamic Privacy Budget Allocation Mechanism for Privacy-Preserving Multi-dimensional Data Collection
Authors: Chen Xue , Wang Cheng , Yang Qing , Hu Teng , Jiang Changjun
Published: October 2022

Data collection underlocal differential privacy (LDP)has been gradually on the stage. Compared with the implementation of LDP on the single attribute data collection, that on multi-dimensional data faces great challenges as follows: (1)Communication cost. Multivariate data collection needs to retain the correlations between attributes, which means that more complex privatization mechanisms will result in more communication costs. (2)Noise scale. More attributes have to share the privacy budget limited by data utility and privacy-preserving level, which means that less privacy budget can be allocated to each of them, resulting in more noise added to the data. In this work, we innovatively reverse the complex multi-dimensional attributes, i.e., the majornegativefactor that leads to the above difficulties, to act as abeneficialfactor to improve the efficiency of privacy budget allocation, so as to realize a multi-dimensional data collection under LDP with high comprehensive performance. Specifically, we first present aMultivariatek-ary Randomized Response (kRR)mechanism, calledMulti-kRR. It applies the RR directly to each attribute to reduce the communication cost. To deal with the impact of a large amount of noise, we propose a Markov-based dynamic privacy budget allocation mechanism Markov-kRR, which determines the present privacy budget (flipping probability) of an attribute related to the state of the previous attributes. Then, we fix the threshold of flipping times in Markov-kRR and propose an improved mechanism called MarkFixed-kRR, which can obtain more optimized utility by choosing the suitable threshold. Finally, extensive experiments demonstrate the efficiency and effectiveness of our proposed methods.
Minimum Cut and Minimum
k
-Cut in Hypergraphs via Branching Contractions
Authors: Fox Kyle , Panigrahi Debmalya , Zhang Fred
Published: October 2022

On hypergraphs with
m
hyperedges and
n
vertices, where
p
denotes the total size of the hyperedges, we provide the following results:

We give an algorithm that runs in

\(\widetilde{O}(mn^{2k-2})\)

time for finding a minimum
k
-cut in hypergraphs of arbitrary rank. This algorithm betters the previous best running time for the minimum
k
-cut problem, for
k
> 2.

We give an algorithm that runs in

\(\widetilde{O}(n^{\max \lbrace r,2k-2\rbrace })\)

time for finding a minimum
k
-cut in hypergraphs of constant rank
r
. This algorithm betters the previous best running times for both the minimum cut and minimum
k
-cut problems for dense hypergraphs.

Both of our algorithms are Monte Carlo, i.e., they return a minimum
k
-cut (or minimum cut) with high probability. These algorithms are obtained as instantiations of a generic
branching randomized contraction
technique on hypergraphs, which extends the celebrated work of Karger and Stein on recursive contractions in graphs. Our techniques and results also extend to the problems of minimum hedge-cut and minimum hedge-
k
-cut on hedgegraphs, which generalize hypergraphs.
Abnormal Variations of the Key Genes in Osteoporotic Fractures
Authors: Wang Bin , Mai Caiyuan , Pan Lei
Published: October 2022

Objective. The classical osteoporotic signaling pathways include the four key genes (LRP5, Runx2, Osterix, and RANKL) influencing the regulation of osteogenesis and osteoclastogenesis. This study investigates the expression of these four genes associated with bone remodeling during fracture healing. Methods. Ovariectomized rats as an osteoporotic group were randomly divided into three groups-group A, group B, and group C. Nonosteoporotic rats as the control group were likewise divided into three groups A0, B0, and C0, using the same method. The rats were killed on the third day of fractures in groups A and A0, on the seventh day of fractures in groups B and B0, and on the fourteenth day of fractures in groups C and C0. The bone specimens were taken from the femoral fracture site, and the expression level of each gene in the bone specimens was detected using RT-qPCR, Western blotting, and immunohistochemistry. Results. LRP5, Runx2, and Osterix expressions were decreased in osteoporotic rat fractures and then increased over time. The expression of RANKL was elevated in osteoporotic rat bone specimens, which decreased after that. Conclusion. The expressions of the four genes varied with time after fracture, which could be associated with the various stages of bone repair. The four genes can inform practice in ideal interventions in the prevention and management of osteoporosis.
Existence and Stability ofα−Harmonic Maps
Authors: Kazemi Torbaghan Seyed Mehdi , Salehi Keyvan , Babayi Salman
Published: October 2022

In this paper, we first study theα−energy functional, Euler‐Lagrange operator, andα‐stress‐energy tensor. Second, it is shown that the critical points of theα−energy functional are explicitly related to harmonic maps through conformal deformation. In addition, anα−harmonic map is constructed from any smooth map between Riemannian manifolds under certain assumptions. Next, we determine the conditions under which the fibers of horizontally conformalα−harmonic maps are minimal submanifolds. Then, the stability of anyα−harmonic map on Riemannian manifold with nonpositive curvature is studied. Finally, the instability ofα−harmonic maps from a compact manifold to a standard unit sphere is investigated.
Improvement in the Gain of UWB Antenna for GPR Applications by Using Frequency-Selective Surface
Authors: Din Iftikhar Ud , Ullah Sadiq , Naqvi Syeda Iffat , Ullah Raza , Ullah Shakir , Ali Esraa Mousa , Alibakhshikenari Mohammad
Published: October 2022

In this article, high-gain ultra-wideband (UWB) monopole antenna is presented. The UWB monopole antenna is a semicircular-shaped antenna with a semicircular slot at the top side. The bottom plane consists of partial ground with triangular and rectangular slotted structures to improve the impedance bandwidth of the proposed antenna. In order to enhance gain, a

6
×
6

metallic reflector (FSS) is placed below the antenna. The performance of the offered design is validated experimentally. The simulated results show resemblance with the measured results. The antenna resonates for the UWB ranging from 3 to 11 GHz. Moreover, the integration of FSS improves the average gain by 4 dB, where peak gain obtained is 8.3 dB across the UWB. In addition, the reported unit cell having dimension of

0.11
λ
×
0.11
λ

gives wide bandwidth (7.2 GHz) from 3.3 GHz to 10.5 GHz. The performance of the proposed antenna determines its suitability for the modern day wireless UWB and GPR applications.
Review of the Pressure Swing Adsorption Process for the Production of Biofuels and Medical Oxygen: Separation and Purification Technology
Authors: Rumbo Morales Jesse Y. , Ortiz-Torres Gerardo , García Rodolfo Omar Domínguez , Cantero Carlos Alberto Torres , Rodriguez Manuela Calixto , Sarmiento-Bustos Estela , Oceguera-Contreras Edén , Hernández Alberto Arturo Flores , Cerda Julio César Rodríguez , Molina Yehoshua Aguilar , García Mario Martínez
Published: October 2022

The production of biofuels has had a great impact on climate change and the reduction of the use of fossil fuels. There are different technologies used for the separation and production of biofuels, which allow having compounds such as ethanol, methane, oxygen, and hydrogen, one of these promising technologies is the Pressure Swing Adsorption process (PSA). The objectives of this article focus on the production and purification of compounds that achieve purities of 99.5% bioethanol, 94.85% biohydrogen, 95.00% medical oxygen, and 99.99% biomethane through the PSA process; also, a significant review is contemplated to identify the different natural and synthetic adsorbents that have greater adsorption capacity, the different configurations in which a PSA operates are studied and identified, and the different mathematical models that describe the dynamic behavior of all the variables are established that interact in this PSA process, parametric studies are carried out in order to identify the variables that have the greatest effect on the purity obtained. The results obtained in this review allow facilitating the calculation of parameters, the optimization of the process, the automatic control to manipulate certain variables and to achieve the rejection of disturbances to have a recovery and production of biofuels with a high degree of purity.
Network Construction for Bearing Fault Diagnosis Based on Double Attention Mechanism
Authors: Wu QingE , Zong Tao , Cheng Wenfang , Li Yong , Li Penglei
Published: October 2022

Aiming at the difficulty of feature extraction in the case of multicomponent and strong noise in the traditional rolling bearing fault diagnosis method, this paper proposes a bearing fault diagnosis network with double attention mechanism. The original signal with noise is decomposed into a series of intrinsic mode functions (IMFs) by the Empirical Mode Decomposition method. The Pearson correlation coefficient is discussed to filter the IMFs components for signal reconstruction. The spatial features of the reconstructed signal are extracted by attention convolutional networks. Then, time series features are extracted based on the long short-term memory method. Furthermore, the importance of temporal features is measured through a temporal attention mechanism. The Softmax layer of the constructed network is used as the classifier for fault diagnosis. Comparing this method with the existing methods of experiments, the proposed method has not only better diagnosis accuracy but also stronger antiinterference ability and generalization ability, which can accurately diagnose and classify the bearing fault types. The fault diagnosis accuracy rate for each load is above 99%.
Cutting Tools Assignment and Control Using Neutrosophic Case-Based Reasoning and Best Worst Method
Authors: Kasie Fentahun Moges , Bright Glen
Published: October 2022

Cutting tools management is one of the major issues in metal cutting operations. Most of the problems in cutting tools management were mostly addressed using optimization, heuristic, and simulation techniques. This important problem was not studied using decision-based approaches. This study proposed a decision support system (DSS) that can perform part-cutting tools assignment and control decisions by integrating a neutrosophic case-based reasoning and the best-worst method (BWM) in metal cutting processes. Specifically, this study utilized the integration of case-based reasoning (CBR) and single-valued neutrosophic set (SVNS) theories in artificial intelligence (AI). Furthermore, the proposed DSS applies the BWM to determine optimal weights for case attributes from multicriteria decision-making (MCDM). The system retrieves the most similar historical cases using a neutrosophic CBR and the BWM to adapt their cutting tool requirements to the current product orders. In addition, it revises retrieved cases (tool sets) depending on attribute differences between new and retrieved cases using rule-based reasoning (RBR) from experts. This study provided new insights regarding the application of a neutrosophic CBR and its integration with the BWM. Specifically, the integration of SVNS, CBR, and BWM was not articulated in cutting tools management problems. A numerical example was illustrated in a computer-simulated environment to show the applicability of the proposed DSS using lathe machine operations.