bluuebunny/crossref_metadata_2025 huggingface dataset:
Speaking in the presence of noise: Consistency of acoustic properties in clear-Lombard speech over time
Authors: Shen Chen , Cooke Martin , Janse Esther
Published: April 2023

Individual speakers are often able to modify their speech to facilitate communication in challenging conditions, such as speaking in a noisy environment. Such vocal “enrichments” might include reductions in speech rate or increases in acoustic contrasts. However, it is unclear how consistently speakers enrich their speech over time. This study examined inter-speaker variability in the speech enrichment modifications applied by speakers. The study compared a baseline habitual speaking style to a clear-Lombard style and measured changes in acoustic differences between the two styles over sentence trials. Seventy-eight young adult participants read out sentences in the habitual and clear-Lombard speaking styles. Acoustic differences between speaking styles generally increased nonlinearly over trials, suggesting that speakers require practice before realizing their full speech enrichment potential when speaking clearly in noise with reduced auditory feedback. Using a recent objective intelligibility metric based on glimpses, the study also found that predicted intelligibility increased over trials, highlighting that communicative benefits of the clear-Lombard style are not static. These findings underline the dynamic nature of speaking styles.
Perceptions of Self-Care and Work–Life Balance Among Secondary School Athletic Trainers
Authors: Singe Stephanie M. , Cairns Alexandrya H. , Eason Christianne M.
Published: April 2023

The athletic training research agenda identifies a need for exploration on strategies for improved work–life balance. One unexplored area is self-care practices used to maintain work–life balance. Fourteen (six males, eight females) athletic trainers employed in the secondary school setting participated in a qualitative research study. All interviews were recorded, transcribed, and analyzed using an inductive approach as prescribed by phenomenological approach. Data saturation guided recruitment and peer review and intercoder reliability was used for credibility. Secondary school athletic trainers are engaging in self-care practices regularly and connect those activities to their work–life balance. Self-care practices are designed to create “me time” and are geared toward physical and social self-care activities. In addition, our results address the interchangeable thoughts of self-care practices, stress relief, and work–life balance.
Work–Family Conflict: Understanding Workplace Relationships for Collegiate Athletic Trainers
Authors: Singe Stephanie M. , Tannebaum Chloe , Cairns Alexandrya H.
Published: April 2023

Role congruence has been suggested to be a facilitator for work–life balance for the athletic trainer, but to date, it has only been superficially explored. Conceptually, role congruence is based on relationships and roles within the organization; thus, the purpose of the study was to further investigate professional relationships between coaches and athletic trainers related to work–life balance. To accomplish this, 28 credentialed athletic trainers were interviewed via the Zoom platform. Three identifiable themes were found within the data. The first them role congruence reduces stress for the athletic trainer and was supported by two themes: (a) role congruence facilitates a positive work environment and (b) incongruence facilitates a stressful work environment. The second theme, peak season expectations and job demands limit work–life balance, was defined by (a) hours worked, (b) coaches’ expectations, and (c) sport is demanding, which impacts work–life balance.
Design of a minimal di-nickel hydrogenase peptide
Authors: Timm Jennifer , Pike Douglas H. , Mancini Joshua A. , Tyryshkin Alexei M. , Poudel Saroj , Siess Jan A. , Molinaro Paul M. , McCann James J. , Waldie Kate M. , Koder Ronald L. , Falkowski Paul G. , Nanda Vikas
Published: April 2023

Ancestral metabolic processes involve the reversible oxidation of molecular hydrogen by hydrogenase. Extant hydrogenase enzymes are complex, comprising hundreds of amino acids and multiple cofactors. We designed a 13–amino acid nickel-binding peptide capable of robustly producing molecular hydrogen from protons under a wide variety of conditions. The peptide forms a di-nickel cluster structurally analogous to a Ni-Fe cluster in [NiFe] hydrogenase and the Ni-Ni cluster in acetyl-CoA synthase, two ancient, extant proteins central to metabolism. These experimental results demonstrate that modern enzymes, despite their enormous complexity, likely evolved from simple peptide precursors on early Earth.
Fishing through the cracks: The unregulated nature of global squid fisheries
Authors: Seto Katherine L. , Miller Nathan A. , Kroodsma David , Hanich Quentin , Miyahara Masanori , Saito Rui , Boerder Kristina , Tsuda Masaki , Oozeki Yoshioki , Urrutia S. Osvaldo
Published: April 2023

While most research has focused on the legality of global industrial fishing, unregulated fishing has largely escaped scrutiny. Here, we evaluate the unregulated nature of global squid fisheries using AIS data and nighttime imagery of the globalized fleet of light-luring squid vessels. We find that this fishery is extensive, fishing 149,000 to 251,000 vessel days annually, and that effort increased 68% over the study period 2017–2020. Most vessels are highly mobile and fish in multiple regions, largely (86%) in unregulated areas. While scientists and policymakers express concerns over the declining abundance of squid stocks globally and regionally, we find a net increase in vessels fishing squid globally and spatial expansion of effort to novel areas. Since fishing effort is static in areas with increasing management, and rising in unmanaged areas, we suggest actors may take advantage of fragmented regulations to maximize resource extraction. Our findings highlight a profitable, but largely unregulated fishery, with strong potential for improved management.
How the mechanobiology orchestrates the iterative and reciprocal ECM-cell cross-talk that drives microtissue growth
Authors: Benn Mario C. , Pot Simon A. , Moeller Jens , Yamashita Tadahiro , Fonta Charlotte M. , Orend Gertraud , Kollmannsberger Philip , Vogel Viola
Published: April 2023

Controlled tissue growth is essential for multicellular life and requires tight spatiotemporal control over cell proliferation and differentiation until reaching homeostasis. As cells synthesize and remodel extracellular matrix, tissue growth processes can only be understood if the reciprocal feedback between cells and their environment is revealed. Using de novo–grown microtissues, we identified crucial actors of the mechanoregulated events, which iteratively orchestrate a sharp transition from tissue growth to maturation, requiring a myofibroblast-to-fibroblast transition. Cellular decision-making occurs when fibronectin fiber tension switches from highly stretched to relaxed, and it requires the transiently up-regulated appearance of tenascin-C and tissue transglutaminase, matrix metalloprotease activity, as well as a switch from α5β1 to α2β1 integrin engagement and epidermal growth factor receptor signaling. As myofibroblasts are associated with wound healing and inflammatory or fibrotic diseases, crucial knowledge needed to advance regenerative strategies or to counter fibrosis and cancer progression has been gained.
mRNA translational specialization by RBPMS presets the competence for cardiac commitment in hESCs
Authors: Bartsch Deniz , Kalamkar Kaustubh , Ahuja Gaurav , Lackmann Jan-Wilm , Hescheler Jürgen , Weber Timm , Bazzi Hisham , Clamer Massimiliano , Mendjan Sasha , Papantonis Argyris , Kurian Leo
Published: April 2023

The blueprints of developing organs are preset at the early stages of embryogenesis. Transcriptional and epigenetic mechanisms are proposed to preset developmental trajectories. However, we reveal that the competence for the future cardiac fate of human embryonic stem cells (hESCs) is preset in pluripotency by a specialized mRNA translation circuit controlled by RBPMS. RBPMS is recruited to active ribosomes in hESCs to control the translation of essential factors needed for cardiac commitment program, including Wingless/Integrated (WNT) signaling. Consequently, RBPMS loss specifically and severely impedes cardiac mesoderm specification, leading to patterning and morphogenetic defects in human cardiac organoids. Mechanistically, RBPMS specializes mRNA translation, selectively via 3′UTR binding and globally by promoting translation initiation. Accordingly, RBPMS loss causes translation initiation defects highlighted by aberrant retention of the EIF3 complex and depletion of EIF5A from mRNAs, thereby abrogating ribosome recruitment. We demonstrate how future fate trajectories are programmed during embryogenesis by specialized mRNA translation.
The super elongation complex drives transcriptional addiction in
MYCN
-amplified neuroblastoma
Authors: Wang Donghai , Yin Zhinang , Wang Honghong , Wang Liyuan , Li Tianyu , Xiao Ruijing , Xie Ting , Han Ruyi , Dong Rui , Liu Hudan , Liang Kaiwei , Qing Guoliang
Published: April 2023

MYCN
amplification in neuroblastoma leads to aberrant expression of MYCN oncoprotein, which binds active genes promoting transcriptional amplification. Yet, how MYCN coordinates transcription elongation to meet productive transcriptional amplification and which elongation machinery represents MYCN-driven vulnerability remain to be identified. We conducted a targeted screen of transcription elongation factors and identified the super elongation complex (SEC) as a unique vulnerability in
MYCN
-amplified neuroblastomas. MYCN directly binds EAF1 and recruits SEC to enhance processive transcription elongation. Depletion of EAF1 or AFF1/AFF4, another core subunit of SEC, leads to a global reduction in transcription elongation and elicits selective apoptosis of
MYCN
-amplified neuroblastoma cells. A combination screen reveals SEC inhibition synergistically potentiates the therapeutic efficacies of FDA-approved BCL-2 antagonist ABT-199, in part due to suppression of MCL1 expression, both in
MYCN
-amplified neuroblastoma cells and in patient-derived xenografts. These findings identify disruption of the MYCN-SEC regulatory axis as a promising therapeutic strategy in neuroblastoma.
Hemagglutinin destabilization in H3N2 vaccine reference viruses skews antigenicity and prevents airborne transmission in ferrets
Authors: Hu Meng , Kackos Christina , Banoth Balaji , Ojha Chet Raj , Jones Jeremy C. , Lei Shaohua , Li Lei , Kercher Lisa , Webby Richard J. , Russell Charles J.
Published: April 2023

During influenza virus entry, the hemagglutinin (HA) protein binds receptors and causes membrane fusion after endosomal acid activation. To improve vaccine efficiency and pandemic risk assessment for currently-dominant H3N2 influenza viruses, we investigated HA stability of 6 vaccine reference viruses and 42 circulating viruses. Recent vaccine reference viruses had destabilized HA proteins due to egg-adaptive mutation HA1-L194P. Virus growth in cell culture was independent of HA stability. In ferrets, the vaccine reference viruses and circulating viruses required a relatively stable HA (activation and inactivation pH < 5.5) for airborne transmissibility. The recent vaccine reference viruses with destabilized HA proteins had reduced infectivity, had no airborne transmissibility unless reversion to HA1-P194L occurred, and had skewed antigenicity away from the studied viruses and circulating H3N2 viruses. Other vaccine reference viruses with stabilized HAs retained infectivity, transmissibility, and antigenicity. Therefore, HA stabilization should be prioritized over destabilization in vaccine reference virus selection to reduce mismatches between vaccine and circulating viruses.
Active recruitment of anti–PD-1–conjugated platelets through tumor-selective thrombosis for enhanced anticancer immunotherapy
Authors: Wang Yixin , Li Wen , Li Zhaoting , Mo Fanyi , Chen Yu , Iida Mari , Wheeler Deric L , Hu Quanyin
Published: April 2023

Immune checkpoint inhibitors (ICIs) can reinvigorate T cells to eradicate tumor cells, showing great potential in combating various types of tumors. We propose a delivery strategy to enhance tumor-selective ICI accumulation, which leverages the responsiveness of platelets and platelet-derivatives to coagulation cascade signals. A fused protein tTF-RGD targets tumor angiogenic blood vessel endothelial cells and initiates the coagulation locoregionally at the tumor site, forming a “cellular hive” to recruit anti–PD-1 antibody (aPD-1)–conjugated platelets to the tumor site and subsequently activating platelets to release aPD-1 antibody to reactivate T cells for improved immunotherapy. Moreover, on a patient-derived xenograft breast cancer model, the platelet membrane–coated nanoparticles can also respond to the coagulation signals initiated by tTF-RGD, thus enhancing the accumulation and antitumor efficacy of the loaded chemotherapeutics. Our study illustrates a versatile platform technology to enhance the local accumulation of ICIs and chemodrugs by taking advantage of the responsiveness of platelets and platelet derivatives to thrombosis.
Mechanism of sphingolipid homeostasis revealed by structural analysis of
Arabidopsis
SPT-ORM1 complex
Authors: Liu Peng , Xie Tian , Wu Xinyue , Han Gongshe , Gupta Sita D. , Zhang Zike , Yue Jian , Dong Feitong , Gable Kenneth , Niranjanakumari Somashekarappa , Li Wanyuan , Wang Lin , Liu Wenchen , Yao Ruifeng , Cahoon Edgar B. , Dunn Teresa M. , Gong Xin
Published: April 2023

The serine palmitoyltransferase (SPT) complex catalyzes the first and rate-limiting step in sphingolipid biosynthesis in all eukaryotes. ORM/ORMDL proteins are negative regulators of SPT that respond to cellular sphingolipid levels. However, the molecular basis underlying ORM/ORMDL-dependent homeostatic regulation of SPT is not well understood. We determined the cryo–electron microscopy structure of
Arabidopsis
SPT-ORM1 complex, composed of LCB1, LCB2a, SPTssa, and ORM1, in an inhibited state. A ceramide molecule is sandwiched between ORM1 and LCB2a in the cytosolic membrane leaflet. Ceramide binding is critical for the ORM1-dependent SPT repression, and dihydroceramides and phytoceramides differentially affect this repression. A hybrid β sheet, formed by the amino termini of ORM1 and LCB2a and induced by ceramide binding, stabilizes the amino terminus of ORM1 in an inhibitory conformation. Our findings provide mechanistic insights into sphingolipid homeostatic regulation via the binding of ceramide to the SPT-ORM/ORMDL complex that may have implications for plant-specific processes such as the hypersensitive response for microbial pathogen resistance.
A movable unshielded magnetocardiography system
Authors: Xiao Wei , Sun Chenxi , Shen Liang , Feng Yulong , Liu Meng , Wu Yulong , Liu Xiyu , Wu Teng , Peng Xiang , Guo Hong
Published: April 2023

Magnetocardiography (MCG), which uses high-sensitivity magnetometers to record magnetic field signals generated by electrical activity in the heart, is a noninvasive method for evaluating heart diseases such as arrhythmia and ischemia. The MCG measurements usually require the participant keeping still in a magnetically shielded room due to the immovable sensor and noisy external environments. These requirements limit MCG applications, such as exercise MCG tests and long-term MCG observations, which are useful for early detections of heart diseases. Here, we introduce a movable MCG system that can clearly record MCG signals of freely behaving participants in an unshielded environment. On the basis of optically pumped magnetometers with a sensitivity of 140 fT/Hz1/2, we successfully demonstrated the resting MCG and the exercise MCG tests. Our method is promising to realize a practical movable multichannel unshielded MCG system that nearly sets no limits to participants and brings another kind of insight into the medical diagnosis of heart disease.
Molecular origin of the two-step mechanism of gellan aggregation
Authors: Tavagnacco Letizia , Chiessi Ester , Severini Leonardo , Franco Silvia , Buratti Elena , Capocefalo Angela , Brasili Francesco , Mosca Conte Adriano , Missori Mauro , Angelini Roberta , Sennato Simona , Mazzuca Claudia , Zaccarelli Emanuela
Published: April 2023

Among hydrocolloids, gellan is one of the most studied polysaccharides due to its ability to form mechanically stable gels. Despite its long-standing use, the gellan aggregation mechanism is still not understood because of the lack of atomistic information. Here, we fill this gap by developing a new gellan force field. Our simulations offer the first microscopic overview of gellan aggregation, detecting the coil to single-helix transition at dilute conditions and the formation of higher-order aggregates at high concentration through a two-step process: first, the formation of double helices and then their assembly into superstructures. For both steps, we also assess the role of monovalent and divalent cations, complementing simulations with rheology and atomic force microscopy experiments and highlighting the leading role of divalent cations. These results pave the way for future use of gellan-based systems in a variety of applications, from food science to art restoration.
A Second Role for the Second Messenger Cyclic-di-GMP in E. coli: Arresting Cell Growth by Altering Metabolic Flow
Authors: Hwang YuneSahng , Harshey Rasika M.
Published: April 2023

The c-di-GMP signaling network in bacteria not only controls a variety of cellular processes such as motility, biofilms, cell development, and virulence, but does so by a dizzying array of mechanisms. The DGC YfiN singularly represents the versatility of this network in that it not only inhibits motility and promotes biofilms, but also arrests growth in
Escherichia coli
by relocating to the mid-cell and blocking cell division.
Environmental Stability of Enveloped Viruses Is Impacted by Initial Volume and Evaporation Kinetics of Droplets
Authors: French Andrea J. , Longest Alexandra K. , Pan Jin , Vikesland Peter J. , Duggal Nisha K. , Marr Linsey C. , Lakdawala Seema S.
Published: April 2023

During the COVID-19 pandemic, policy decisions were being driven by virus stability experiments with SARS-CoV-2 in different droplet volumes under various humidity conditions. Our study, the first of its kind, provides a model for the decay of multiple enveloped RNA viruses in cell culture medium deposited in 50-, 5-, and 1-μL droplets at 40%, 65%, and 85% RH over time.
Unravelling Strain-Specific Modifications of Toxoplasma gondii tRNA and sncRNA Using LC-MS/MS
Authors: Wang Wei , Yang Yi , Guo Huanping , Li Ming-Han , Chen Xiao-Qing , Wei Xin-Yu , Chen Yu , Elsheikha Hany M. , Zhang Xiao-Xuan
Published: April 2023

Although RNA modifications play roles in many cellular and developmental processes in various domains of life, knowledge about the patterns and functions of RNA modifications in
T. gondii
is limited. Here, a quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach was used to study global RNA modifications in
T. gondii
strains of distinct virulence backgrounds.
Efficient Autotransporter-Mediated Extracellular Secretion of a Heterologous Recombinant Protein by Escherichia coli
Authors: Beriotto Irene , Icke Christopher , Sevastsyanovich Yanina R. , Rossiter Amanda E. , Romagnoli Giacomo , Savino Silvana , Hodges Freya J. , Cole Jeffrey A. , Saul Allan , MacLennan Calman A. , Cunningham Adam F. , Micoli Francesca , Henderson Ian R.
Published: April 2023

Recombinant protein production is an essential component of the biotechnology sector. Here, we show that the autotransporter platform is a viable method for the recombinant production, secretion, and purification of a “difficult” to produce protein on an industrially relevant scale. Use of the autotransporter platform could reduce the number of downstream processing operations required, thus accelerating the development time and reducing costs for recombinant protein production.
Long Noncoding RNA AROD Inhibits Host Antiviral Innate Immunity via the miR-324-5p–CUEDC2 Axis
Authors: Zhang Zixiao , Yu Tianqi , Li Haimin , Du Liuyang , Jin Zian , Peng Xiran , Yan Yan , Zhou Jiyong , Gu Jinyan
Published: April 2023

lnc-AROD is a potential diagnostic and discriminative biomarker for different cancers. However, so far the mechanisms of lnc-AROD regulating virus replication are not well understood.
Magnetic Anisotropy of Single-Ion Magnet (PPh4)2 [ReF6]·2H2O
Authors: Taran L. S. , Elfimova V. Y. , Streltsov S. V.
Published: April 2023

Studying of single-molecule magnets has sprung many surprises such as, e.g., quantum tunneling of the magnetization, which is strongly related to the presence of a magnetic anisotropy. Electron spin resonance and inelastic neutron scattering measurements of (PPh4)2[ReF6]⋅2H2O complex evidence an unprecedented large single-site magnetic anisotropy of $$D \sim 35$$ K in this material. Using state-of-the-art ab initio calculations we found that the single-ion anisotropy is indeed very large (but does not exceed 12 K) and revealed the physical mechanism lying behind this phenomenon.
Determinants of recreational screen time behavior following the COVID-19 pandemic among Canadian adults
Authors: Liu Sam , Coulter Rebecca , Sui Wuyou , Nuss Kayla , Rhodes Ryan E.
Published: April 2023

The objectives of our study were to examine recreational screen time behavior before and 2 years following the COVID-19 pandemic lockdown, and explore whether components of the capability–opportunity–motivation–behavior (COM-B) model would predict changes in this recreational screen time behavior profile over the 2-year period. This cross-sectional, retrospective study was conducted in March 2022. Canadian adults ( n = 977) completed an online survey that collected demographic information, current screen time behavior, screen time behavior prior to the pandemic, and beliefs about capability, opportunities, and motivation for limiting screen time based on the COM-B model. We found that post-pandemic recreational screen time (3.91 ± 2.85 h/day) was significantly higher than pre-pandemic levels (3.47 ± 2.50 h/day, p < 0.01). Three recreational screen time behavior profiles were identified based on the Canadian 24-Hour Movement Guidelines: (1) always met screen time guidelines (≤3 h/day) (47.8%; n = 454); (2) increased screen time (10.1%; n = 96); and (3) never met screen time guidelines (42%; n = 399). The overall discriminant function was found to be significant among the groups (Wilks’ λ = 0.90; canonical r = 0.31, χ2 = (14) = 95.81, p < 0.001). The group that always met screen time guidelines had the highest levels of automatic motivation, reflective motivation, social opportunity, and psychological capabilities to limit screen time compared to other screen time profile groups. In conclusion, recreational screen time remains elevated post-pandemic. Addressing motivation (automatic and reflective), psychological capabilities, and social opportunities may be critical for future interventions aiming to limit recreational screen time.
Facial Expression Recognition with Contrastive Learning and Uncertainty-Guided Relabeling
Authors: Yang Yujie , Hu Lin , Zu Chen , Zhou Qizheng , Wu Xi , Zhou Jiliu , Wang Yan
Published: April 2023

Facial expression recognition (FER) plays a vital role in the field of human-computer interaction. To achieve automatic FER, various approaches based on deep learning (DL) have been presented. However, most of them lack for the extraction of discriminative expression semantic information and suffer from the problem of annotation ambiguity. In this paper, we propose an elaborately designed end-to-end recognition network with contrastive learning and uncertainty-guided relabeling, to recognize facial expressions efficiently and accurately, as well as to alleviate the impact of annotation ambiguity. Specifically, a supervised contrastive loss (SCL) is introduced to promote inter-class separability and intra-class compactness, thus helping the network extract fine-grained discriminative expression features. As for the annotation ambiguity problem, we present an uncertainty estimation-based relabeling module (UERM) to estimate the uncertainty of each sample and relabel the unreliable ones. In addition, to deal with the padding erosion problem, we embed an amending representation module (ARM) into the recognition network. Experimental results on three public benchmarks demonstrate that our proposed method facilitates the recognition performance remarkably with 90.91% on RAF-DB, 88.59% on FERPlus and 61.00% on AffectNet, outperforming current state-of-the-art (SOTA) FER methods. Code will be available at http//github.com/xiaohu-run/fer_supCon .
Abnormal Traffic Detection Method of Internet of Things Based on Deep Learning in Edge Computing Environment
Authors: Qiu Lingcong , Wang Lei
Published: April 2023

In this paper, a method based on deep learning to detect abnormal traffic of IoTs in edge computing environment is proposed. Firstly, the data are preprocessed by data cleaning, normalization, oversampling and undersampling, and data set segmentation to obtain a data set with balanced data distribution. Secondly, a method of calculating feature information based on data increment is adopted, which can accurately extract feature information from the dynamic data flow. Finally, the convolution neural network (CNN) is used to extract the local features of the data, and the bi-directional gated loop unit (BiGRU) is used to extract the long sequence correlation of the data. The two networks work together to extract data features. The self-focus mechanism is introduced to deal with redundant data. Experiments show that the accuracy, recall and [Formula: see text]1 value of the proposed method are 97.36%, 98.38% and 97.16%, respectively, in the normal class, which are higher than the comparison algorithm.
A Methodology to Analyze and Estimate the Software Development Process Using Machine Learning Techniques
Authors: Lalitha R. , Sreelekha P.
Published: April 2023

Analyzing the software development process and estimating the effort required for its completion is an essential task. In the case of Agile methodology, the values of the parameters used for estimation vary frequently as the scope of the project changes with changes in the requirements of the clients. Hence, the estimation done at the initial phase will not be appropriate until the completion of the project. Therefore, to overcome this issue, a methodology is proposed to estimate the duration of a project by applying machine learning techniques. The use-case point method is used for estimating the duration. Information about the number of use cases and values for environmental and technical factors is stored in a repository. Few values may be uncertain, and to estimate the effort for a new project with few unknown or uncertain values, the machine learning algorithm Gaussian Process Regression (GPR) is used. The repository information is taken as the training dataset, and the new project data is taken as the test dataset. The estimated value shows the accurate duration for the new project. The result is validated with a popular dataset.
Enhancing Answer Selection via Ad-Hoc Knowledge Extraction from Unstructured Web Texts
Authors: Gu Shengwei , Luo Xiangfeng , Wang Hao
Published: April 2023

Answer selection aims to identify the most relevant answers to a given question from a set of candidates. It is the fundamental component of intelligent question answering system. To improve performance, it gradually becomes an effective strategy to integrate external structured knowledge bases (KBs) into the answer selection model. Due to expensive cost of construction and maintenance of such KBs, these models are suffering from domain barriers and information incompleteness. In this paper, we propose a two-stage extraction–comprehension answer selection model, which can extract ad-hoc knowledge from unstructured web texts to enhance the performance of answer selection. For the extraction, two types of snippets are extracted from unstructured web pages and utilized as the source of ad-hoc knowledge. For the comprehension, a selective attention mechanism is employed to extract and integrate ad-hoc knowledge from multiple text snippets obtained in the first stage, which can enrich the representation of question–answer pairs and more accurately identify the correct answers. By incorporating ad-hoc knowledge extracted from both types of snippets, the proposed model achieves state-of-the-art results on two public available benchmark datasets. In particular, on WikiQA, in terms of the two evaluation metrics (mean average precision and mean reciprocal rank), it achieves 9.9[Formula: see text] and 8.4[Formula: see text] higher than the previous non-pretraining-based models, and 3.4[Formula: see text] and 3.2[Formula: see text] higher than the pretraining-based models.
HIGHER-ORDER SLIP FLOW OF MAXWELL FLUIDS CONTAINING GYROTACTIC MICROORGANISMS PAST A HORIZONTAL EXTENDING SURFACE: ANALYSIS WITH CONVECTIVE CONDITIONS
Authors: LONE SHOWKAT AHMAD , ANWAR SADIA , RAIZAH ZEHBA , ALMUSAWA MUSAWA YAHYA , SAEED ANWAR
Published: April 2023

This paper explores the bioconvective Maxwell fluid flow over a horizontal stretching sheet. The Maxwell fluid flow is considered in the presence of gyrotactic microorganisms. The velocity slips and convection conditions are used in this investigation. Additionally, the Cattaneo–Christov heat and mass flux model, Brownian motion, thermophoresis, and activation energy are employed in the flow problem. The model formulation has been transferred to a dimension-free format using similarity variables and solved by the homotopy analysis approach. Figures have been sketched to depict the HAM convergence. The consequences of this study are that the velocity of Maxwell fluid flow reduces for higher Hartmann number, buoyancy ratio factor, and bioconvective Rayleigh number, whereas the increasing behavior in velocity profile is seen against Deborah number. The thermal characteristics of the Maxwell fluid flow diminish with developing values of the thermal relaxation factor and Prandtl number, while augmenting with the increasing Brownian motion, thermal and concentration Biot numbers and thermophoresis factor. The rate of thermal transmission of the Maxwell fluid flow enhances with the increasing Prandtl number, and mixed convective factor, while diminishing with the increasing buoyancy ratio factor, thermophoresis factor and Brownian motion factor.
MODELING AND OPTIMIZATION OF PROCESS PARAMETERS OF THE PISTON ALLOY-BASED COMPOSITE PRODUCED BY FSP USING RESPONSE SURFACE METHODOLOGY
Authors: AKBARI M. , ASADI P. , ALIHA M. R. M. , BERTO F.
Published: April 2023

In this paper, A356/B4C composites were fabricated using the friction stir processing (FSP) method. The process’s input parameters, including rotational and transverse speed, were optimized using the response surface methodology (RSM). Three factors and three levels with nine experimental runs made up the design of the experiments. An analysis of variance (ANOVA) was employed to determine whether the constructed model was adequate at a 95% confidence level. This study found that transverse speed was the most critical variable affecting the composites’ silicon (Si) particle size, UTS, and force. The findings demonstrate that the Si particle size of the parent material and the dispersion quality of B4C particles in the aluminum matrix are considerably influenced by the FSP factors, such as rotating speed and transverse speed. Second, tests for tensile strength were conducted to examine the composites’ mechanical properties. Then, using a specially designed fixture to measure force during the process, the forces on the tool, which play a decisive role in determining the tool’s life, were measured in different input parameters. The findings demonstrate that FSP transforms the mechanism of the fracture from brittle to extremely ductile in composites from the as-received metal.
Dynamic Force Reconstruction for Structural Support Platforms Based on the Combined Strategy of Experiment and Simulation
Authors: Yang Hongji , Jiang Jinhui , Chen Guoping , Bao Huanying , Lu Fan
Published: April 2023

Dynamic force reconstruction theory has been developed for many years, generating numerous effective methods. However, the applications of engineering structures are relatively rare, owing to the difficult experiment, low accuracy and noise disturbance, among others. Aiming at the support platform structure commonly used in engineering, we propose the complete dynamic force reconstruction process based on the direct inversion method in frequency domain. The dynamic calibration methods of experiment and simulation are both analyzed in this case. In order to improve identification accuracy, the Tikhonov regularization is introduced. The results validate the reliability of our proposed method in real scenarios and the necessity of regularization method. Moreover, dynamic load identification method of structural variable stiffness is derived by the four-terminal parameter method. This work provides engineering application–a reference for the engineering of dynamic load identification technology.
Transient PDF Solution of Nonlinear Stochastic Oscillator Subjected to Modulated Gaussian White Noise
Authors: Luo Jie , Er Guo-Kang , Iu Vai Pan , Lam Chi Chiu
Published: April 2023

In this paper, an extended exponential-polynomial-closure (EPC) procedure is presented to investigate the transient probability density function (PDF) of stochastic oscillator under the stimulation being modulated white noise based on the conventional EPC approach. By the presented EPC procedure, an evolutionary exponential–polynomial function is defined as the PDF solution and a set of evolutionary independent base functions are introduced to span a [Formula: see text] space. By integrating the residual error with those evolutionary functions spanning the [Formula: see text] space, a group of ordinary differential equations can then be formulated. Three nonlinear oscillators are analyzed numerically and the results comparisons of various techniques validate the presented EPC procedure in solution efficiency and accuracy, particularly in the PDF solution tails which play a crucial role in reliability analysis. The transient PDF solutions acquired by the presented EPC procedure match well with Monte Carlo simulation even in the PDF solution tails, whereas the solutions obtained by the equivalent linearization are deemed to be unacceptable for the strongly nonlinear oscillators subjected to modulated stimulation. Notably, the presented EPC procedure can highly increase the computational efficiency by about 1[Formula: see text]000 times in all the presented numerical examples in comparison to Monte Carlo simulation.
Semisimplicity of affine cellular algebras
Authors: Li Yanbo , Sun Bowen
Published: April 2023

In this paper, we prove that an affine cellular algebra [Formula: see text] is semisimple if and only if the scheme associated to [Formula: see text] is reduced and 0-dimensional, and the bilinear forms with respect to all layers of [Formula: see text] are invertible. Moreover, if the ground ring is a perfect field, then [Formula: see text] is semisimple if and only if it is separable. We also give a sufficient condition for an affine cellular algebra being Jacobson semisimple.
The structure of Jordan contractible Banach algebras
Authors: Valaei Mohammad , Haddadi Mohammad Reza
Published: April 2023

In this paper, we define the Jordan notions of contractibility and biprojectivity of Banach algebras and comparing to the classical notions of contractibility and biprojectivity. Also, we introduce the notion of Jordan diagonal and find relations between these Jordan notions. As a main result, we show that the Banach algebra [Formula: see text] is unital and Jordan contractible if and only if it has a Jordan diagonal if and only if [Formula: see text] is unital and Jordan biprojective, whenever [Formula: see text] is a Banach [Formula: see text]-bimodule.
The opposite of projectivity by proper classes
Authors: Durğun Yılmaz
Published: April 2023

In the last decade, two new approaches have been introduced for the analysis of the projectivity of modules. In this paper, the projectivity of modules has been studied with a new approach by using projectively generated proper classes. As an opposite to projectivity, a module [Formula: see text] is said to be [Formula: see text]-indigent if the projectively generated proper class by [Formula: see text] is consisting of exactly the split short exact sequences. We consider rings over which every (finitely generated, finitely presented, cyclic, simple) right [Formula: see text]-modules are either projective or [Formula: see text]-indigent.
A Deep Learning Algorithm for Evaluating the Quality of English Teaching
Authors: Li Nan
Published: April 2023

Universities play a huge role in the cultivation of talents. Especially in the context of internationalization, the teaching of English as a common language is becoming more and more important. This paper introduced the traditional methods for evaluating the quality of English teaching, established a deep learning algorithm for evaluating the quality of English teaching with the evaluation indicators of the traditional methods combined with the convolutional neural network (CNN) algorithm, conducted simulation experiments on the CNN algorithm, and compared it with the support vector machine (SVM) algorithm. The results showed that the scores obtained by the CNN algorithm had some errors with the actual scores but were much lower than the scores obtained by the SVM algorithm, and the CNN algorithm consumed a shorter time in computing. This paper used the CNN algorithm combined with evaluation indexes constructed by the analytic hierarchy process (AHP) method to evaluate the quality of English teaching and verified the effectiveness of the CNN algorithm through a comparison with the SVM algorithm, which provides an effective reference for intelligent evaluation of English teaching quality.
Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market
Authors: Muhammad Tashreef , Aftab Anika Bintee , Ibrahim Muhammad , Ahsan Md. Mainul , Muhu Maishameem Meherin , Khan Shahidul Islam , Alam Mohammad Shafiul
Published: April 2023

In the modern capital market, the price of a stock is often considered to be highly volatile and unpredictable because of various social, financial, political and other dynamic factors. With calculated and thoughtful investment, stock market can ensure a handsome profit with minimal capital investment, while incorrect prediction can easily bring catastrophic financial loss to the investors. This paper introduces the application of a recently introduced machine learning model — the transformer model, to predict the future price of stocks of Dhaka Stock Exchange (DSE), the leading stock exchange in Bangladesh. The transformer model has been widely leveraged for natural language processing and computer vision tasks, but, to the best of our knowledge, has never been used for stock price prediction task task using DSE data. Recently, the introduction of time2vec encoding to represent the time series features has made it possible to employ the transformer model for the stock price prediction. This paper aims to leverage these two effective techniques to discover forecasting ability on the volatile stock market of DSE. We deal with the historical daily and weekly data of eight specific stocks listed in DSE. Our experiments demonstrate promising results and acceptable root-mean-squared error on most of the stocks. We also compare the performance of our model with that of a well-known benchmark stock forecasting model called ARIMA and report satisfactory results.
China’s COVID-19 Vaccine Cooperation with Southeast Asia: A Boost for the Health Silk Road Initiative
Authors: Zhao Wanyi , Li Mingjiang
Published: April 2023

The severe impact of the COVID-19 pandemic highlighted the importance of public health management for the economy and society in every country. It also proved the necessity of international cooperation in the health sector to deal with global health challenges and realize sustainable development. As one of the major players in global health governance, China has made significant contributions to anti-COVID cooperation through the Health Silk Road, a key component of the Belt and Road Initiative (BRI). Beijing’s vaccine cooperation was particularly noteworthy in Southeast Asia, a very important region in China’s BRI design. The bilateral vaccine collaboration between China and regional states has provided good experiences for regional health cooperation and paved the way for the further promotion of the Health Silk Road in the post-pandemic era.
Adaptive Collaborative Soft Label Learning for Unsupervised Multi-View Feature Selection
Authors: Shi Dan , Zhu Lei , Dong Xiao , Song Xuemeng , Li Jingjing , Cheng Zhiyong
Published: April 2023

Unsupervised multi-view feature selection aims to select informative features with multi-view features and unsupervised learning. It is a challenging problem due to the absence of explicit semantic supervision. Recently, graph theory and hard pseudo-label learning have been adopted to solve multi-view feature selection problems under the unsupervised learning paradigm. However, graph-based methods are difficult to support large-scale real scenarios due to the high computational complexity of graph construction. Moreover, existing methods based on hard pseudo-label learning generally result in significant information loss. In this article, we propose an Adaptive Collaborative Soft Label Learning (ACSLL) model for unsupervised multi-view feature selection. In this model, collaborative soft label learning and multi-view feature selection are integrated into a unified framework. Specifically, we learn the pseudo soft labels from each view feature by a simple and efficient method and fuse them with an adaptive weighting strategy into a joint soft label matrix. This matrix is further used for guiding the feature selection process to identify valuable features. An effective optimization strategy guaranteed with proven convergence is derived to iteratively solve this problem. Experiments demonstrate the superiority of the proposed method in both feature selection accuracy and efficiency.
Optimization-Aware Compiler-Level Event Profiling
Authors: Basso Matteo , Prokopec Aleksandar , Rosà Andrea , Binder Walter
Published: April 2023

Tracking specific events in a program’s execution, such as object allocation or lock acquisition, is at the heart of dynamic analysis. Despite the apparent simplicity of this task, quantifying these events is challenging due to the presence of compiler optimizations. Profiling perturbs the optimizations that the compiler would normally do—a profiled program usually behaves differently than the original one.

In this article, we propose a novel technique for quantifying compiler-internal events in the optimized code, reducing the profiling perturbation on compiler optimizations. Our technique achieves this by instrumenting the program from within the compiler, and by delaying the instrumentation until the point in the compilation pipeline after which no subsequent optimizations can remove the events. We propose two different implementation strategies of our technique based on path-profiling, and a modification to the standard path-profiling algorithm that facilitates the use of the proposed strategies in a modernjust-in-time (JIT)compiler. We use our technique to analyze the behaviour of the optimizations in Graal, a state-of-the-art compiler for the Java Virtual Machine, identifying the reasons behind a performance improvement of a specific optimization, and the causes behind an unexpected slowdown of another. Finally, our evaluation results show that the two proposed implementations result in a significantly lower execution-time overhead w.r.t. a naive implementation.
A Hypothesis Testing-based Framework for Software Cross-modal Retrieval in Heterogeneous Semantic Spaces
Authors: Wei Hongwei , Su Xiaohong , Gao Cuiyun , Zheng Weining , Tao Wenxin
Published: April 2023

Software cross-modal retrieval is a popular yet challenging direction, such as bug localization and code search. Previous studies generally map natural language texts and codes into a homogeneous semantic space for similarity measurement. However, it is not easy to accurately capture their similar semantics in a homogeneous semantic space due to the semantic gap. Therefore, we propose to map the multi-modal data into heterogeneous semantic spaces to capture their unique semantics. Specifically, we propose a novel software cross-modal retrieval framework named Deep Hypothesis Testing (DeepHT). In DeepHT, to capture the unique semantics of the code’s control flow structure, all control flow paths (CFPs) in the control flow graph are mapped to a CFP sample set in the sample space. Meanwhile, the text is mapped to a CFP correlation distribution in the distribution space to model its correlation with different CFPs. The matching score is calculated according to how well the sample set obeys the distribution using hypothesis testing. The experimental results on two text-to-code retrieval tasks (i.e., bug localization and code search) and two code-to-text retrieval tasks (i.e., vulnerability knowledge retrieval and historical patch retrieval) show that DeepHT outperforms the baseline methods.
Chronopotentiometric Analysis of the Anode Dissolution Process in Dimethyl Sulfone–Aluminum Chloride Electrolytic Solution
Authors: Matsuda Junichi , Okamoto Atsushi , Akahoshi Haruo , Shironita Sayoko , Umeda Minoru
Published: April 2023

Toward the commercialization of aluminum electrodeposition, unveiling the anode dissolution process in a sustainable electrolyte is essential. Herein, to gain more insight into the anode dissolution process in dimethyl sulfone (DMSO2)–aluminum chloride (AlCl3) electrolyte solution, we performed chronopotentiometry measurements using Pt disk electrodes. In this system, the anode dissolution reaction exhibits two-wave behavior with a positive potential shift of +1.0 V. The Coulombic efficiency, reaction potential, and multiple reverse chronopotentiometry measurements show that the second-stage anode dissolution reaction is a three-electron-transfer process from Al0 and AlCl4
− to Al2Cl7
−. The transition of the anode dissolution reaction from the first to the second-stage occurs because Al (DMSO2)3
3+ is not stably formed owing to DMSO2 depletion near the electrode during the anode dissolution reaction.
Highly Stable and Reusable 3D Graphene-Quinizarin Voltammetric pH Sensor
Authors: Siddiqui Mohd Salman , Aslam M.
Published: April 2023

A simple pH sensor has been developed employing a 3D porous graphene framework blended with quinizarin. The performance of the fabricated sensor is tested via the square wave voltammetry technique by applying different buffer solutions and real samples. The peak potential of the designed electrode varies with the change in pH of solutions due to 2e−/2H+ transfer process of pH-dependent quinone/hydroquinone redox couple. For varying pH (1–13), the designed sensor has a sensitivity of 65.6 ± 0.4 mV/pH at 25 °C. Soil pH sensing is performed for different types of soil samples prepared using 1M KCl and 0.01M CaCl2 solutions with a potential shift of 63.5 ± 0.9 mV/pH and 57.9 ± 0.3 mV/pH, respectively. The 3D graphene-quinizarin pH sensing probe demonstrates negligible hysteresis (± 0.3 pH) and long-term stability (six months and more). In comparison to the commercial pH meter, the fabricated sensor shows a relative inaccuracy of less than 5%. Moreover, a single electrode could be used to detect the pH of multiple environments by mild rinsing with deionized water and is reusable for more than 500 cycles without significant potential drift. These low-cost and reusable pH-sensitive electrodes with linear Nernstian response are promising candidates for diverse pH-sensing applications.