bluuebunny/crossref_metadata_2025 huggingface dataset:
What mechanisms underlie phonetic and phonological learning ability in monolingual and bilingual populations? A closer look at the connection with cognitive and sensory functions
Authors: Spinu Laura , Muscalu Laura M. , Vasilita Mariana , Gilbert Crystal , Wallace Julia
Published: May 2022

Despite considerable controversy surrounding the “bilingual advantage” phenomenon, recent meta-analyses reveal a majority of studies on the topic have reported that bilinguals outperform monolinguals on tasks related to executive functioning, such as mental flexibility and inhibitory mechanisms. A more recent line of investigation also shows that bilinguals typically score higher than monolinguals on tasks involving phonetic and phonological learning as well as auditory sensory memory. In this study, we aim to gain insight into how these different functions are related by exploring the correlations between four cognitive tasks in 30 bilinguals and 30 monolinguals. The tasks were designed to test: (1) inhibition; (2) mental flexibility; (3) phonetic and phonological learning (PPL); and (4) auditory sensory memory (ASM). All the participants were tested and data analysis is currently underway. Based on existing literature, we hypothesize enhanced bilingual performance on all of these tasks, as well as a connection between PPL and ASM. While the literature does not allow for a straightforward prediction, we will also investigate whether executive functions play a role in PPL and are correlated with ASM. Our study will thus lead to better understanding of the coupling between sensory and cognitive functions.
Evaluating contributions of relative vocabulary size and demand for use on masked-speech recognition for bilingual children with normal hearing
Authors: Cowan Tiana , Leibold Lori , Calandruccio Lauren , McCreery Ryan , Rodriguez Barbara , Buss Emily
Published: May 2022

The Children’s English and Spanish Speech Recognition Test (ChEgSS) is a tool for assessing masked-speech recognition. An audiologist could test a bilingual child’s speech recognition in both English and Spanish, but if time is limited, which language should they choose? We evaluated how two different measures of language dominance, relative demand for use and relative vocabulary size impacted word identification in noise and in a two-talker speech masker for 82 bilingual children (4–17 years) with normal hearing. The participants were exposed to Spanish from birth and varied in their initial exposure to English. Each child completed ChEgSS in English and Spanish using a 4AFC procedure. We measured vocabulary using standardized tests and demand for use using questionnaires. We created language dominance variables by standardizing values then subtracting Spanish scores from English ones. Linear regression evaluated how age and the interaction between length of exposure, relative vocabulary size, and relative language use predicted performance. Relative vocabulary size impacted thresholds, and this effect was larger for children with less exposure in the test language. Results suggest relative vocabulary size and length of exposure should inform the test language(s) used to assess clinical speech recognition.
Effects of age and musical expertise on speech-on-speech perception in adults
Authors: Rachman Laura , Harding Eleanor , Gray Ryan , Smeenk Stefan , Sarampalis Anastasios , Gaudrain Etienne , Baskent Deniz
Published: May 2022

Speech-on-speech (SoS) perception relies on perceptual mechanisms, such as discriminating mean fundamental frequency (F0) and vocal-tract length (VTL), and cognitive mechanisms, such as selective attention and working memory. Older adults may be less sensitive to F0 differences, possibly affecting their ability to perceive different speakers. Age-related cognitive changes may lead to difficulties in attention direction and inhibition. Compared to non-musicians, musicians are reported to possess enhanced processing of acoustic features such as F0, as well as enhanced cognitive abilities such as auditory attention skills and working memory. While this intuitively could lead to a musician advantage for SoS perception, reports of musicians outperforming non-musicians on SoS tasks are inconsistent across both younger and older adults. Differences in SoS paradigms across the literature have made it difficult to directly compare musicianship advantages in SoS perception in younger and older adults, or to clarify related underlying mechanisms. In this study, we investigated the extent to which older compared to younger adults benefit from voice differences in an SoS perception task, by manipulating differences in F0 and VTL cues between target and masker speakers. Furthermore, we investigated the effect of musical expertise in younger and older adults within the same SoS task.
Antibodies induced by an ancestral SARS-CoV-2 strain that cross-neutralize variants from Alpha to Omicron BA.1
Authors: Windsor Ian W. , Tong Pei , Lavidor Olivia , Moghaddam Ali Sanjari , McKay Lindsay G.A. , Gautam Avneesh , Chen Yuezhou , MacDonald Elizabeth A. , Yoo Duck Kyun , Griffths Anthony , Wesemann Duane R. , Harrison Stephen C.
Published: May 2022

Neutralizing antibodies that recognize the SARS-CoV-2 spike glycoprotein are the principal host defense against viral invasion. Variants of SARS-CoV-2 bear mutations that allow escape from neutralization by many human antibodies, especially those in widely distributed (“public”) classes. Identifying antibodies that neutralize these variants of concern and determining their prevalence are important goals for understanding immune protection. To determine the Delta and Omicron BA.1 variant specificity of B cell repertoires established by an initial Wuhan strain infection, we measured neutralization potencies of 73 antibodies from an unbiased survey of the early memory B cell response. Antibodies recognizing each of three previously defined epitopic regions on the spike receptor binding domain (RBD) varied in neutralization potency and variant-escape resistance. The ACE2 binding surface (“RBD-2”) harbored the binding sites of neutralizing antibodies with the highest potency but with the greatest sensitivity to viral escape; two other epitopic regions on the RBD (“RBD-1” and “RBD-3”) bound antibodies of more modest potency but greater breadth. The structures of several Fab:spike complexes that neutralized all five variants of concern tested, including one Fab each from the RBD-1, -2, and -3 clusters, illustrated the determinants of broad neutralization and showed that B cell repertoires can have specificities that avoid immune escape driven by public antibodies. The structure of the RBD-2 binding, broad neutralizer shows why it retains neutralizing activity for Omicron BA.1, unlike most others in the same public class. Our results correlate with real-world data on vaccine efficacy, which indicate mitigation of disease caused by Omicron BA.1.
Cleaved to keep dying cells alive
Authors: Ferrarelli Leslie K.
Published: May 2022

Upon DNA damage, caspase-3 sends the kinase AMPK to the nucleus to prevent apoptotic progression.
Human Metapneumovirus Phosphoprotein Independently Drives Phase Separation and Recruits Nucleoprotein to Liquid-Like Bodies
Authors: Boggs Kerri Beth , Edmonds Kearstin , Cifuentes-Munoz Nicolas , El Najjar Farah , Ossandón Conny , Roe McKenna , Wu Chao , Moncman Carole L. , Creamer Trevor P. , Amarasinghe Gaya K. , Leung Daisy W. , Dutch Rebecca Ellis
Published: May 2022

Human metapneumovirus (HMPV) is a leading cause of respiratory disease among children, immunocompromised individuals, and the elderly. Currently, no vaccines or antivirals are available for the treatment of HMPV infections.
A World of Viruses Nested within Parasites: Unraveling Viral Diversity within Parasitic Flatworms (Platyhelminthes)
Authors: Dheilly Nolwenn M. , Lucas Pierrick , Blanchard Yannick , Rosario Karyna
Published: May 2022

Little is known about the diversity of parasite-associated viruses and how these viruses may impact parasite fitness, parasite-host interactions, and virus evolution. The discovery of over a hundred viruses associated with a range of free-living and parasitic flatworms, including parasites of economic and clinical relevance, allowed us to compare the viromes of flatworms with contrasting lifestyles.
Prevalence, Antimicrobial Resistance, and Molecular Characterization of
Campylobacter
Isolated from Broilers and Broiler Meat Raised without Antibiotics
Authors: Poudel Sabin , Li Tianmin , Chen Saijuan , Zhang Xue , Cheng Wen-Hsing , Sukumaran Anuraj T. , Kiess Aaron S. , Zhang Li
Published: May 2022

Campylobacter
is one of the main bacterial pathogens that cause campylobacteriosis in the United States. Poultry is considered a major reservoir for the transmission of
Campylobacter
to humans.
Comparative Genomics Revealed Wide Intra-Species Genetic Heterogeneity and Lineage-Specific Genes of
Akkermansia muciniphila
Authors: Li Weicheng , Sun Jiaqi , Jing Yongjian , Zhao Jie , Wu Qiong , Liu Jiaqi , Kwok Lai-Yu , Zhang Wenguang , Sun Zhihong , Zhong Zhi , Liu Wenjun
Published: May 2022

Akkermansia muciniphila
has been widely accepted as part of the next generation of probiotics. However, most current studies on
A. muciniphila
have focused on the application of type strain BAA835
T
in the treatment of diseases, while few studies have reported on the genomic specificity, population structure, and functional characteristics of
A. muciniphila
species.
Synthesis of Fluorine-Containing Analogues of Purine Deoxynucleosides: Optimization of Enzymatic Transglycosylation Conditions
Authors: Drenichev M. S. , Dorinova E. O. , Varizhuk I. V. , Oslovsky V. E. , Varga M. A. , Esipov R. S. , Lykoshin D. D. , Alexeev C. S.
Published: May 2022

In this work, a comparative analysis of the conditions of transglycosylation reactions catalyzed by E. coli nucleoside phosphorylases was carried out, and the optimal conditions for the formation of various nucleosides were determined. Under the optimized conditions of transglycosylation reaction, fluorine-containing derivatives of N6-benzyl-2'-deoxyadenosine, potential inhibitors of replication of enteroviruses in a cell, were obtained starting from the corresponding ribonucleosides.
Positive impact on 10-year outcome of the window of opportunity for conventional synthetic DMARDs in rheumatoid arthritis: results from the ESPOIR cohort
Authors: Kedra Joanna , Lafourcade Alexandre , Combe Bernard , Dougados Maxime , Hajage David , Fautrel Bruno
Published: May 2022

Objective

This study aimed to assess the impact of disease-modifying antirheumatic drugs (DMARDs) on 10-year outcomes in rheumatoid arthritis (RA).

Methods

Patients with RA from the ESPOIR cohort with complete data on Disease Activity Score in 28 Joints (DAS28) and Health Assessment Questionnaire (HAQ) at 10 years (n=418) and complete radiographic data at baseline and 10 years (n=343) were included in this study. Outcomes were favourable outcome (FavOut) at 10 years, defined as DAS28 of <2.6 and HAQ score of <0.5 at 10 years, and absence of structural damage progression (AbsSDP) at 10 years, defined as change in Sharp-van der Heijde Score less than the smallest detectable change at 10 years (11.5 points). Three multivariate logistic regression models predicting 10-year outcome were built, considering (1) baseline variables only, (2) baseline variables and DMARD exposure (ever exposed, yes/no) and (3) baseline variables and DMARD exposure as weighted cumulative exposure (WCE) variables.

Results

Overall, 196/418 (46.9%) patients showed FavOut and 252/343 (73.5%) AbsSDP. WCE models had the best predictive performance, with area under the curve=0.80 (95% CI 0.74 to 0.87) for FavOut and 0.87 (95% CI 0.83 to 0.92) for AbsSDP. In the WCE model, the odds of FavOut and AbsSDP were reduced with conventional synthetic disease-modifying antirheumatic drug (csDMARD) initiation at 12 months versus at baseline (OR 0.78, 95% CI 0.65 to 0.94, and OR 0.89, 95% CI 0.76 to 0.98, respectively). Early biologics initiation was not significantly associated with either outcome.

Conclusions

WCE models can identify and quantify the long-term benefit of early csDMARD initiation on 10-year functional and structural outcomes in patients with RA.
Disseminating and assessing implementation of the EULAR recommendations for patient education in inflammatory arthritis: a mixed-methods study with patients’ perspectives
Authors: Jones Bethan , Bennett Sarah , Larsson Ingrid , Zangi Heidi , Boström Carina , Van der Elst Kristien , Fayet Françoise , Fusama Mie , Herrero Manso María del Carmen , Hoeper Juliana Rachel , Kukkurainen Marja Leena , Kwok Suet Kei , Frãzao-Mateus Elsa , Minnock Patricia , Nava Tiziana , Pavic Nikolic Milena , Primdahl Jette , Rawat Roopa , Schoenfelder Mareen , Sierakowska Matylda , Voshaar Marieke , Wammervold Edgar , van Tubergen Astrid , Ndosi Mwidimi
Published: May 2022

Objectives

To explore patients’ agreement and reasons for agreement or disagreement with the EULAR recommendations for patient education (PE) for people with inflammatory arthritis (IA).

Methods

This mixed-method survey collected data using snowball sampling. The survey had been translated into 20 languages by local healthcare professionals, researchers and patient research partners. It explored the degree to which patients with IA agreed with each recommendation for PE (0=do not agree at all and 10=agree completely) and their rationale for their agreement level in free text questions. Descriptive statistics summarised participants’ demographics and agreement levels. Qualitative content analysis was used to analyse the free text data. Sixteen subcategories were developed, describing the reasons for agreement or disagreement with the recommendations, which constituted the categories.

Results

The sample comprised 2779 participants (79% female), with a mean (SD) age 55.1 (13.1) years and disease duration 17.1 (13.3) years. Participants strongly agreed with most recommendations (median 10 (IQR: 9–10) for most recommendations). Reasons for agreement with the recommendations included the benefit of using PE to facilitate collaborative care and shared decision making, the value of flexible and tailored PE, and the value of gaining support from other patients. Reasons for disagreement included lack of resources for PE, not wanting information to be tailored by healthcare professionals and a reluctance to use telephone-based PE.

Conclusion

The EULAR recommendations for PE have been disseminated among patients with IA. Overall, agreement levels were very high, suggesting that they reflect patients’ preferences for engaging in collaborative clinical care and using PE to facilitate and supplement their own understanding of IA. Reasons for not completely agreeing with the recommendations can inform implementation strategies and education of healthcare professionals.
Impact of charge on gravastars in f(ℜ,𝒯2) gravity
Authors: Sharif M. , Naz Saba
Published: May 2022

This paper studies the influence of charge on a compact stellar structure also regarded as vacuum condensate star in the background of [Formula: see text] gravity. This object is considered the alternate of black hole whose structure involves three distinct regions, i.e. interior, exterior and thin-shell. We analyze these domains of a gravastar for a particular model of this modified theory. In the inner region of a gravastar, the considered equation of state defines that energy density is equal to negative pressure which is the cause of repulsive force on the spherical shell. In the intermediate shell, pressure and energy density are equal and contain ultra-relativistic fluid. The inward-directed gravitational pull of thin-shell counterbalances the force exerted by the inner region of a gravastar allowing the formation of a singularity-free object. The Reissner–Nordström metric presents the outer vacuum spherical domain. Moreover, we discuss the impact of the charge on physical attributes of a gravastar such as the equation of state parameter, entropy, proper length and energy. We conclude that singularity-free solutions of charged gravastar are physically consistent in this modified theory.
Effect of RuO2 crystallinity and particle size on electrical property of LTCC resistors
Authors: Wei Hong , Wang Zhen , Wang Fenglin , Zhang Weijun
Published: May 2022

The crystallization and sintering process of RuO[Formula: see text]xH2O nanoparticles have been investigated in this paper. The effect of RuO2 crystallinity and particle size on the sheet resistance of RuO2-based resistor paste after being co-fired with CaO–B2O3–SiO2 green tapes has been reported. The results show that the nanoparticles are not fully crystallized below 600[Formula: see text]C, and the effect of high-density defects, such as grain boundaries and dislocations on the residual resistance ([Formula: see text] of RuO2 particles, is significant. So, the sheet resistance decreases with the increase of crystallinity and the weakening of electron wave scattering. Above 600[Formula: see text]C, the effect of crystal imperfections on [Formula: see text] is greatly weakened. However, the number of conductive chains formed in co-fired resistor decreases with the increase of particle size, thus the sheet resistance gradually raises. When the dwelling time is increased to 3 h, the RuO2 is mostly crystallized and the effect of crystal imperfections on [Formula: see text] is negligible, and the sheet resistance mainly depends on particle size of RuO2. Using RuO2 particles with low crystallinity, small size and narrow particle-size distribution as conductive phase is expected to solve the problem of poor sheet resistance uniformity in high resistance paste for LTCC application.
Design and Implementation of Time-Frequency Distributions for Real-Time Applications Using Field Programmable Gate Array
Authors: Krishna B. Murali , Krishna B. T. , Babulu K.
Published: May 2022

In this paper, time-frequency distributions (TFDs) and their hardware implementation on FPGA are presented. TFDs are evolved due to disadvantage of Fourier Transform (FT), which cannot provide time information in spectrum representation. Time-Frequency Representations (TFRs) are helpful in providing simultaneous information about spectral contents of a signal with respect to time period axis. The major problem associated with hardware implementation of TFDs is limited on-board memory. Forward and backward register allocation method (FBRA) is employed to obtain the optimum register occupation. A register of length 32-bit is considered for the input signal representation. The stored register values are applied to the proposed TFDs and computed using real-time hardware. FBRA is implemented during the computation of FFT in all TFDs. All the transforms are modeled using Verilog code and implemented on SPARTA-6 FPGA. A real-time ECG, earthquake and a quad chirp signals are taken as input to test the designed TFDs. Finally, a comparison of different hardware resources utilized on FPGA with earlier conventional methods for better real-time applications was made.
The Effect of Service Quality on Spectators’ Behavioral Intensions in Professional Football: The Role of Value and Satisfaction
Authors: Nikolaos Papadopoulos G. , Theodoros Kargidis
Published: May 2022

The importance of quality for an organization has been highlighted by many researchers. The service quality of sports organizations is conceptualized by the dimensions of technical (outcome) and functional (process-related) qualities as a significant element of sport product. The purpose of this study is to investigate the level of service quality provided by Greek professional sports clubs, through the satisfaction of spectators, the perceived value and the ability to predict their intentions of behavior. The survey included 940 fans of Greek Super Leagues’ team ARIS THESSALONIKI FC. The results provided support of the service quality models used.
Propositions for R&D Governance Regimes: A Behavioral Perspective
Authors: Sinha Kanhaiya Kumar , Osiyevskyy Oleksiy , Radnejad Amir Bahman
Published: May 2022

Purpose: Our paper intends to bring systematic attention to the transaction costs and corresponding governance structures in the corporate R&D contexts. Design/methodology/approach: The current conversation on the governance of R&D has addressed topics related to investments, resource allocation, knowledge sharing, or managing intellectual property rights. While these are important aspects of innovation cost and benefit, they do not address an equally important issue of transaction cost arising out of human behavior. We adopt a systematic synthesis of 16 qualitative teaching case studies to validate the existence of human behavior-related transaction cost issues in the context of R&D and identify firms’ governance responses to mitigate or eliminate their effect. Findings: Our findings suggest that transaction costs issues can be mitigated by appropriate governance models ranging from centralized R&D to open innovation. While structure mitigates the transaction cost some ex-ante and ex-post controls may also be required. Practical implications: For management practice, the insights of our study provide evidence-based advice for R&D managers regarding the practical, effective ways of limiting and controlling the transaction costs associated with R&D activity. Originality/value: This paper uses teaching-case studies to analyze a variety of transaction cost dilemmas in the R&D context and brings in a new perspective to R&D governance.
On small fractional parts of perturbed polynomials
Authors: Minelli Paolo
Published: May 2022

Questions concerning small fractional parts of polynomials and pseudo-polynomials have a long history in analytic number theory. In this paper, we improve on the earlier work by Madritsch and Tichy. In particular, let [Formula: see text] where P is a polynomial of degree k and [Formula: see text] is a linear combination of functions of shape [Formula: see text], [Formula: see text], [Formula: see text]. We prove that for any given irrational [Formula: see text] we have [Formula: see text] for P belonging to a certain class of polynomials and with [Formula: see text] being an explicitly given rational function in k.
The Hasse principle for finite Galois modules allowing exceptional sets of positive density
Authors: Ishitsuka Yasuhiro , Ito Tetsushi
Published: May 2022

We study a variant of the Hasse principle for finite Galois modules, allowing exceptional sets of positive density. For a Galois module whose underlying abelian group is isomorphic to [Formula: see text] ([Formula: see text]), we show that the product of the restriction maps for places in a set of places [Formula: see text] is injective if the Dirichlet density of [Formula: see text] is strictly larger than [Formula: see text]. We give applications to the local–global divisibility problem for elliptic curves and the Hasse principle for flexes on plane cubic curves.
On the Statherian–Calymmian palaeogeography of northwestern Laurentia
Authors: Rainbird R. H. , Davis W. J.
Published: May 2022

The
c.
1.75 to 1.27 Ga Hornby Bay intracontinental basin, exposed in northwestern Canada, NE of Great Bear Lake, includes the Big Bear, Mountain Lake and Dismal Lakes groups. The Big Bear group comprises mainly immature clastic rocks deposited by high-energy rivers in restricted fault-bounded basins formed during the late-stage assembly of supercontinent Nuna. Detrital zircon analysis of the Big Bear group suggests provenance from a combination of local sources including recycling of sedimentary rocks, which were originally derived from sources further east, such as the Thelon orogen. The overlying Mountain Lake group was deposited by westerly flowing rivers over a much broader region, with less evidence for syndepositional faulting, suggesting thermal subsidence. It displays provenance via recycling of strata from the proximal Coronation Supergroup and the more distal and correlative Goulburn Supergroup of Kilohigok Basin. Following tectonic uplift and erosion, basal clastic rocks of the Dismal Lakes Group were deposited in fluvial and then shallow-marine to paralic environments. Detrital zircon from these strata displays prominent late Archean peaks demonstrating provenance from adjacent rocks of the Slave craton and recycling of the Mountain Lake group. Detrital zircon geochronology of sandstones from the Hornby Bay Basin supports stratigraphic correlation with the Wernecke Supergroup in the Wernecke Mountains and the Muskwa assemblage, located further southward along the ancient western margin of Laurentia. Our data, along with Nd and C isotopes from corresponding shale and carbonate units, provide robust evidence for a palaeogeographical model whereby these successions represent the terrestrial and marine components of a west-facing, passive-margin clastic wedge, considered the westward extension of an Amazon-scale, braided fluvial system that originated in the foreland of the Trans-Hudson orogen, to the east. Elements of this system have been identified from inliers in northeastern Australia, which was attached to northwestern Laurentia prior to the break-up of supercontinent Nuna.

Supplementary material:
U–Pb and Hf results, and Hf isotopic compositions of reference zircons are available at
https://doi.org/10.6084/m9.figshare.c.5980940
Exploitation for Multimedia Asian Information Processing and Artificial Intelligence-based Art Design and Teaching in Colleges
Authors: Xu Bo , Jiang Jing
Published: May 2022

Artificial intelligence has been widely used in art education and learning due to its quick progress.  Any creation made with the help of artificial intelligence is referred to as art design. It covers works generated independently by AI systems and works created in collaboration with humans and AI systems. The objective of directing the invention of environmental art design thinking is to stimulate students' learning and innovation abilities and teach students how to put design ideas into effect. Despite the progress of smart technologies, there are several challenges in increasing the teaching capabilities of technical art design courses, such as the influence of different variables, the absence of quantitative research, and the imperfection in the index system. In this paper, the
Artificial intelligence-based Art design and teaching (AI-ADT)
method in colleges increases the capacity to adapt to AI-oriented art education, establish intelligent teaching methods, and improve AI-oriented art teaching art knowledge and environments. The widespread application of artificial intelligence in design education has become a trend in development. Self-Learning Systems are software that incorporates machine learning techniques to allow computers to learn from and make judgments based on data without the need for explicit programming instructions. The art design profession should confirm and actively adapt to this development trend. Modify the original teaching mode, invent their teaching methods, continually enrich the teaching methods, enhance the quality of teaching, and constantly foster high-quality art design talents in the new age. AI-ADT investigates the optimization of the art design curriculum system in higher education institutions in the context of artificial intelligence. The experimental results show that the proposed method develops smart teaching (98.1%), flexibility (96.5%), performance (93.6%), participation (94.9%), and interaction (95.1%).
Testing Feedforward Neural Networks Training Programs
Authors: Ben Braiek Houssem , Khomh Foutse
Published: May 2022

At present, we are witnessing an increasing effort to improve the performance and trustworthiness of Deep Neural Networks (DNNs), with the aim to enable their adoption in safety critical systems such as self-driving cars or aircraft collision-avoidance systems. Multiple testing techniques are proposed to generate test cases that can expose inconsistencies in the behavior of DNN models. These techniques assume implicitly that the training program is bug-free and appropriately configured. However, satisfying this assumption for a novel problem requires significant engineering work to prepare the data, design the DNN, implement the training program, and tune the hyperparameters to produce the model for which current automated test data generators search for corner-case behaviors. All these model training steps can be error prone. Therefore, it is crucial to detect and correct errors throughout all the engineering steps of DNN-based software systems and not only on the resulting DNN model.

In this article, we gather a catalog of training issues and based on their symptoms and their effects on the behavior of the training program, we propose practical verification routines to detect the aforementioned issues, automatically, by continuously validating that some important properties of the learning dynamics hold during the training. Then, we design
TheDeepChecker
, an end-to-end property-based debugging approach for DNN training programs and implement it as a TensorFlow-based library. As an empirical evaluation, we conduct a case study to assess the effectiveness of
TheDeepChecker
on synthetic and real-world buggy DL programs and compare its performance to that of the Amazon SageMaker Debugger (
SMD
). Results show that
TheDeepChecker
’s on-execution validation of DNN-based program’s properties through three sequential phases (pre-, on-, and post-fitting) succeeds in revealing several coding bugs and system misconfigurations errors early on and at a low cost. Moreover, our property-based approach outperforms the
SMD
’s offline rules verification on training logs in terms of detection accuracy for unstable learning issues and coverage of additional DL bugs.
HIFIR: Hybrid Incomplete Factorization with Iterative Refinement for Preconditioning Ill-Conditioned and Singular Systems
Authors: Chen Qiao , Jiao Xiangmin
Published: May 2022

We introduce a software package called
Hybrid Incomplete Factorization with Iterative Refinement (HIFIR)
for preconditioning sparse, unsymmetric, ill-conditioned, and potentially singular systems. HIFIR computes a
hybrid incomplete factorization
(HIF)
, which combines multilevel incomplete LU factorization with a truncated, rank-revealing QR (RRQR) factorization on the final Schur complement. This novel hybridization is based on the new theory of
ϵ-accurate approximate generalized inverse (AGI)
. It enables near-optimal preconditioners for consistent systems and enables flexible GMRES to solve inconsistent systems when coupled with iterative refinement. In this article, we focus on some practical algorithmic and software issues of HIFIR. In particular, we introduce a new inverse-based rook pivoting (IBRP) into ILU, which improves the robustness and the overall efficiency for some ill-conditioned systems by significantly reducing the size of the final Schur complement for some systems. We also describe the software design of HIFIR in terms of its efficient data structures for supporting rook pivoting in a multilevel setting, its template-based generic programming interfaces for mixed-precision real and complex values in C++, and its user-friendly high-level interfaces in MATLAB and Python. We demonstrate the effectiveness of HIFIR for ill-conditioned or singular systems arising from several applications, including the Helmholtz equation, linear elasticity, stationary incompressible Navier–Stokes (INS) equations, and time-dependent advection-diffusion equation.
Neuroplasticity, the Prefrontal Cortex, and Psychopathology-Related Deviations in Cognitive Control
Authors: Luciana Monica , Collins Paul F.
Published: May 2022

A basic survival need is the ability to respond to, and persevere in the midst of, experiential challenges. Mechanisms of neuroplasticity permit this responsivity via functional adaptations (flexibility), as well as more substantial structural modifications following chronic stress or injury. This review focuses on prefrontally based flexibility, expressed throughout large-scale neuronal networks through the actions of excitatory and inhibitory neurotransmitters and neuromodulators. With substance use disorders and stress-related internalizing disorders as exemplars, we review human behavioral and neuroimaging data, considering whether executive control, particularly cognitive flexibility, is impaired premorbidly, enduringly compromised with illness progression, or both. We conclude that deviations in control processes are consistently expressed in the context of active illness but operate through different mechanisms and with distinct longitudinal patterns in externalizing versus internalizing conditions.
Diversity, Evolution, and Function of Pseudomonas syringae Effectoromes
Authors: Bundalovic-Torma Cedoljub , Lonjon Fabien , Desveaux Darrell , Guttman David S.
Published: May 2022

Pseudomonas syringae is an evolutionarily diverse bacterial species complex and a preeminent model for the study of plant–pathogen interactions due in part to its remarkably broad host range. A critical feature of P. syringae virulence is the employment of suites of type III secreted effector (T3SE) proteins, which vary widely in composition and function. These effectors act on a variety of plant intracellular targets to promote pathogenesis but can also be avirulence factors when detected by host immune complexes. In this review, we survey the phylogenetic diversity (PD) of the P. syringae effectorome, comprising 70 distinct T3SE families identified to date, and highlight how avoidance of host immune detection has shaped effectorome diversity through functional redundancy, diversification, and horizontal transfer. We present emerging avenues for research and novel insights that can be gained via future investigations of plant–pathogen interactions through the fusion of large-scale interaction screens and phylogenomic approaches.
Understanding the Performance Increase of Catalysts Supported on N-Functionalized Carbon in PEMFC Catalyst Layers
Authors: Ott Sebastian , Du Fengmin , Luna Mauricio Lopez , Dao Tuan Anh , Cuenya Beatriz Roldan , Orfanidi Alin , Strasser Peter
Published: May 2022

Applying nitrogen-modified carbon support in PEMFCs has been attracting arising interest due to the resulting performance enhancement. In the present study, we attempt to uncover the origin and gain a deeper understanding of the different N-modification processes, whose influences are responsible for the performance improvement. By utilizing chemically modified Ketjenblack supports comprising altered fraction of N-functionalities, we investigate the underlying mechanism of the drastically reduced voltage losses under fuel cell operation conditions. In all, we demonstrate the key role of support modification induced by ammonia in strengthened support/ionomer interactions and alter physico-chemical properties of the carbon support contributing towards enhanced MEA performance. With the use of X-ray photoelectron spectroscopy (XPS), we show unambiguous evidences that not all N modified surfaces yield the desired performance increase. Rather, the latter depends on a complex interplay between different electrochemical parameter and catalyst properties. We want to emphasize the ionomer/support interaction as one important factor for enhanced ionomer distribution and present a prove of a direct interaction between the ionomers´ sidechains and N-functional groups of the support.
A Study on the Translation of Cultural Classics Based on Deep Learning Methods
Authors: Zhang Yanqing , Lou Jianying , Cheng Zhiqi
Published: May 2022

China’s cultural classics have high artistic and ideological values in the world, which implies China’s historical heritage and the inheritance of the cultural situation of the Chinese nation for thousands of years. At present, with the rapid development of China’s economy, especially in the development environment of cultural globalization, China’s traditional cultural classics have attracted worldwide attention along with historical and cultural treasures. In fact, other countries need to translate cultural classics out of their love for China’s cultural classics or academic research. However, there are a large number of cultural classics in China. According to relevant data, there are approximately 35,000 kinds of cultural classics, out of which only 0.2% are translated into foreign languages. In order to make China’s excellent cultural classics known to the world and let more people in other countries understand Chinese culture, this paper studies the translation of cultural classics through in-depth learning. Firstly, this paper introduces the basic concept of deep learning and proposes an algorithm that deeply studies the convolution layer and pool layer. Secondly, the algorithm establishes a deep learning model that calculates and counts the text information of ancient books through explicit intertextuality. Thirdly, the model carries out automatic text translation and lists the analysis process of cultural classics translation based on intertextuality, so as to study cultural classics translation. The obtained results can promote the development of cultural classics translation in China. For the translation of complex cultural classics, the effects of the three models are tested experimentally, of which the sequence model (seq) is the best. This model is fast and simple to extract the text of literary classics.
Neuropsychiatric Symptoms in Clinically Defined Parkinson’s Disease: An Updated Review of Literature
Authors: Macías-García Paloma , Rashid-López Raúl , Cruz-Gómez Álvaro J. , Lozano-Soto Elena , Sanmartino Florencia , Espinosa-Rosso Raúl , González-Rosa Javier J.
Published: May 2022

Background. Neuropsychiatric symptoms (NPS) are a common and potentially serious manifestation of Parkinson’s disease (PD) but are frequently overlooked in favor of a focus on motor symptomatology. Here, we conducted a literature review of the prevalence and type of NPS experienced by PD patients with a clinically defined course of their illness. Methods. We identified reports of NPS in patients with PD and mean disease duration over 3 years. Three databases—PubMed, Scopus, and Dialnet—were searched for relevant literature published between 2010 and 2020. Predefined exclusion criteria were applied prior to a descriptive analysis of the literature base. Results. In all, 87 unique reports were identified and 30 met inclusion and exclusion criteria. These included 7142 patients with PD (male: 67.3%; mean age: 66.2 years; mean disease duration: 6.7 years). The most frequent NPS were mood disorders (apathy, depression, and anxiety), psychosis, and impulse control disorders (ICD). Treatment with dopamine agonists was identified as an important risk factor for ICD. Co-occurrence of NPS and cognitive dysfunction was also evidenced in a number of studies. Patients with more significant cognitive deficits and higher levels of NPS appeared to be of older age with a longer disease duration and to have more severe motor symptoms. Conclusions. NPS, most commonly mood disorders (apathy, depression, and anxiety), psychosis, and ICDs are frequent manifestations of PD. The results of this review reflect the need to develop unified validated assessment protocols for NPS in PD, as well as to improve their management in clinical practice.
Performance Evaluation of Knowledge Sharing in an Industry-University-Research Alliance Based on PSO-BPNN
Authors: Wang Lin
Published: May 2022

Knowledge sharing performance is very important to evaluate the interests of industry university research alliance. Firstly, this paper puts forward the index system of knowledge sharing performance evaluation of industry university research alliance. A BP neural network (BPNN) and a PSO-improved BP neural network (PSO-BPNN) are used to establish the evaluation model, and the accuracy of the model is evaluated. The prediction accuracy is evaluated by comparing the predicted value with the target value. Through comparative analysis, it is found that the performance evaluation model based on PSO-BP neural network has high accuracy and applicability, and is an effective method of alliance knowledge sharing performance evaluation.
Power Intelligent Terminal Intrusion Detection Based on Deep Learning and Cloud Computing
Authors: Li Tong , Zhao Hai , Tao Yaodong , Huang Donghua , Yang Chao , Xu Shuheng
Published: May 2022

Numerous internal and external intrusion attacks have appeared one after another, which has become a major problem affecting the normal operation of the power system. The power system is the infrastructure of the national economy, ensuring that the information security of its network not only is an aspect of computer information security but also must consider high-standard security requirements. This paper analyzes the intrusion threat brought by the power information network and conducts in-depth research and investigation combined with the intrusion detection technology of the power information network. It analyzes the structure of the power knowledge network and cloud computing through deep learning-based methods and provides a network interference detection model. The model combines the methods of abuse detection and anomaly detection, which solves the problem that the abuse analysis model does not detect new attack variants. At the same time, for big data network data retrieval, it retrieves and analyzes data flow quickly and accurately with the help of deep learning of data components. It uses a fuzzy integral method to optimize the accuracy of power information network intrusion prediction, and the accuracy reaches 98.11%, with an increase of 0.6%.
Research on Dance Teaching Based on Motion Capture System
Authors: Peng Yuan
Published: May 2022

Ethnic dance is a part of minority culture and an important chapter of intangible cultural heritage. Because the art of dance does not exist in a certain physical form in a certain environment, it is difficult to record and preserve dance. In traditional recording work, dancers' dance movements are mostly recorded through text, photos, videos, etc. However, these methods can only record and preserve dance movements in a two-dimensional manner from a limited number of angles and cannot achieve accurate and comprehensive record protection of dance poses. Moreover, data preserved by traditional methods can only be simply copied and transferred, and cannot be exploited, developed, or innovated. Therefore, motion capture technology can be applied to the protection of ethnic dance art, and motion capture technology can be used to obtain 3D gestures of ethnic minority dance spaces, restore and optimize digital movements, such as establishing a national dance art movement technology database, and combine the protection of the original ecological cultural atmosphere. It can accurately and comprehensively preserve the essence of ethnic minority dance art and provide effective reference for many ethnic minority dances with ethnic characteristics, digital protection of sports, and the future.
Pole Extraction of Radar Target in Resonant Region Based on Sliding-Window Matrix Pencil Method
Authors: Deng Zhian , Zhang Tianbao , Li Na , Zhang Chunjie , Si Weijian
Published: May 2022

In the complex battlefield environment, stealth radar target recognition has been paid increasing attentions. Previous studies have demonstrated that the stealth target can be identified well by pole extraction based on matrix pencil method (MPM). However, MPM suffers from the difficulty in setting model order and the time-domain resonant response aliasing problem. This paper proposes a new sliding-window matrix pencil method (SW-MPM) based on dynamic order setting and sliding window. Dynamic order setting scheme is used to overcome the difficulty of setting the order in matrix pencil method, while sliding window can avoid the aliasing problem of time-domain resonant response to some extent. The time-domain scattering data used in SW-MPM are obtained by inverse Fourier transform of the frequency domain scattering data in the resonance region. Taking typical stealth aircraft identification as example, the simulation results verify that the proposed method may extract more number of poles with better azimuth consistency, which is beneficial to improve the accuracy of pole-based target identification.
The Cultivation and Training Effect of the Subconscious Mind in Physical Education and Training by Intelligent Internet of Things Network Computing
Authors: Xu Qing , Jia Qixia
Published: May 2022

With the deep integration of the Internet of Things and artificial intelligence, the intelligent Internet of Things is becoming a cutting-edge technology with broad application prospects. The intelligent Internet of Things can realize the interconnection, interaction, perception, and calculation of human, machine, object, environment, and other elements, thereby realizing the intelligent space function with self-organization, self-learning, self-adaptation, and continuous evolution. Based on the intelligent Internet of things, this paper analyzes the cultivation and training effect of network computing on the subconscious in physical education training. An experimental study of its influence on the learning of shooting techniques in the compulsory basketball course of the physical education class of the high school affiliated to Jiangxi Normal University in 2020 was conducted. It is concluded that the average score of students’ learning motivation in the intelligent Internet of Things network computing group is 4.06, and the average score of learning interest is 3.9. After the experiment, the pass rate of students’ shooting was 92%, and the excellent rate was 74%. The use of intelligent Internet of Things network computing technology can significantly improve students’ learning motivation, learning interest, and training effect.
The Curative Effect of Pregabalin in the Treatment of Postherpetic Neuralgia Analyzed by Deep Learning‐Based Brain Resting‐State Functional Magnetic Resonance Images
Authors: Zheng Shumao , Lei Mingjun , Bai Fan , Tian Zan , Wang Hua
Published: May 2022

This work aimed to investigate the brain resting‐state functional magnetic resonance imaging (fMRI) technology based on the depth autoencoders algorithm and to evaluate the clinically curative effect of pregabalin in the treatment of postherpetic neuralgia (PHN). In this study, 40 patients with PHN were selected and rolled randomly into a treatment group and a control group (20 cases in each group). Then, a depth autoencoders algorithm was constructed and applied in the brain resting‐state fMRI technology. The brains of 40 patients with PHN treated with pregabalin were scanned, and the time curve extracted from MRI images was convolved by linear drift removal bandpass filtering to reduce low‐frequency drift and high‐frequency noise, so the low‐frequency amplitude was calculated. Based on the low‐frequency amplitude method, the calculated low‐frequency signal energy was eventually divided by the total power of the entire frequency band to obtain the low‐frequency amplitude rate value. The amplitude of low‐frequency fluctuation (ALFF) and fractional ALFF (f‐ALFF) before and after treatment were compared between the treatment group and the control group, and the visual analog scale (VAS) after treatment was also observed. After 4 weeks of taking the drug, the VAS scores of patients from the treatment group in the first week (6.5 ± 0.8 points), the second week (6.5 ± 0.8 points), the third week (3.1 ± 0.3 points), and the fourth week (2.3 ± 0.4 points) after treatment were lower steeply than the scores before treatment (8.3 ± 1.1 points) (P < 0.05). Resting‐state fMRI images showed that the f-ALFF of the 4 brain areas in the treatment group was higher than that of the control group, mainly including the bilateral frontal lobes, bilateral parietal lobes, left parietal lobes, and right posterior cerebellar lobes. Besides, the f‐ALFF of the 6 brain areas in the treatment group was lower than that of the control group, mainly including the right frontal lobe, right parietal lobe, right middle frontal gyrus, precuneus, left frontal lobe, and superior frontal gyrus. In conclusion, the resting‐state fMRI technology based on the depth autoencoders algorithm could efficiently display the brain area characteristic changes of patients with PHN before and after treatment, thereby providing a reference for the diagnosis of the patient’s condition.