bluuebunny/crossref_metadata_2025 huggingface dataset:
Computer-assisted simulated workplace-based assessment in surgery: application of the universal framework of intraoperative performance within a mixed-reality simulation
Authors: Stefan Philipp , Pfandler Michael , Kullmann Aljoscha , Eck Ulrich , Koch Amelie , Mehren Christoph , von der Heide Anna , Weidert Simon , Fürmetz Julian , Euler Ekkehard , Lazarovici Marc , Navab Nassir , Weigl Matthias
Published: January 2023

Objectives

Workplace-based assessment (WBA) is a key requirement of competency-based medical education in postgraduate surgical education. Although simulated workplace-based assessment (SWBA) has been proposed to complement WBA, it is insufficiently adopted in surgical education. In particular, approaches to criterion-referenced and automated assessment of intraoperative surgical competency in contextualized SWBA settings are missing.

Main objectives were (1) application of the universal framework of intraoperative performance and exemplary adaptation to spine surgery (vertebroplasty); (2) development of computer-assisted assessment based on criterion-referenced metrics; and (3) implementation in contextualized, team-based operating room (OR) simulation, and evaluation of validity.

Design

Multistage development and assessment study: (1) expert-based definition of performance indicators based on framework’s performance domains; (2) development of respective assessment metrics based on preoperative planning and intraoperative performance data; (3) implementation in mixed-reality OR simulation and assessment of surgeons operating in a confederate team. Statistical analyses included internal consistency and interdomain associations, correlations with experience, and technical and non-technical performances.

Setting

Surgical simulation center. Full surgical team set-up within mixed-reality OR simulation.

Participants

Eleven surgeons were recruited from two teaching hospitals. Eligibility criteria included surgical specialists in orthopedic, trauma, or neurosurgery with prior VP or kyphoplasty experience.

Main outcome measures

Computer-assisted assessment of surgeons’ intraoperative performance.

Results

Performance scores were associated with surgeons’ experience, observational assessment (Objective Structured Assessment of Technical Skill) scores and overall pass/fail ratings. Results provide strong evidence for validity of our computer-assisted SWBA approach. Diverse indicators of surgeons’ technical and non-technical performances could be quantified and captured.

Conclusions

This study is the first to investigate computer-assisted assessment based on a competency framework in authentic, contextualized team-based OR simulation. Our approach discriminates surgical competency across the domains of intraoperative performance. It advances previous automated assessment based on the use of current surgical simulators in decontextualized settings. Our findings inform future use of computer-assisted multidomain competency assessments of surgeons using SWBA approaches.
Using CT scans to determine the optimal sizes of hard armour plates to protect the torso for UK female Armed Forces personnel
Authors: Breeze John , Fryer RN , Bowley D , Gibb I , Lewis E
Published: January 2023

Introduction

Hard armour plates provide coverage to essential anatomical structures in the torso that, if injured, would likely be responsible for death before damage control surgery can be undertaken. Existing front and rear OSPREY plates in conjunction with Mark 2 plates used at the sides in current UK Armed Forces personal armour systems are provided in a single size, used by both female and male users.

Methods

CT scans of 45 female UK military personnel were analysed. Distances between anatomical structures representing threshold (absolute minimum) and objective (the maximum level of coverage beyond which there is limited further benefit) coverage of the torso were determined and compared with OSPREY and Mark 2 plate dimensions. Sample characteristics were compared with the 2006/2007 UK Armed Forces Anthropometric Survey.

Results

No statistical difference was found between sample means for stature (p=0.131) and mass (p=0.853) from those of the anthropometric survey in this sample. The height of both the front OSPREY plates exceeded the threshold coverage (suprasternal notch to lower border of the 10th rib) for all women studied. The height of the Mark 2 plate exceeds the objective coverage from the side for all women studied.

Conclusions

Based on a plate height providing threshold coverage of all women up to the 50th percentile, the height of the front and rear OSPREY plates could be reduced by 36mm and 31mm respectively. Based on a presumption that a side plate should cover up to the 95th percentile, the Mark 2 plate achieves the objective height and width for the female population studied. Strong evidence was found to support the UK Ministry of Defence requirement for procurement of new front and rear plates of multiple heights for both female and male users.
Clinical evaluation of the GeneXpert® Xpert® Xpress SARS-CoV-2/Flu/RSV PLUS combination test
Authors: Johnson Grant , Gregorchuk Branden S.J. , Zubrzycki Arek , Kolsun Kurt , Meyers Adrienne F.A. , Sandstrom Paul A. , Becker Michael G.
Published: January 2023

The GeneXpert® Xpert® Xpress SARS-CoV-2/Flu/RSV PLUS combination test (PLUS assay) received Health Canada approval in January 2022. The PLUS assay is similar to the SARS-CoV-2/Flu/RSV combination test, with modifications to improve assay robustness against circulating and emerging variants. The performance characteristics of the PLUS assay were assessed at the Lakeridge Health Oshawa Hospital Centre and the National Microbiology Laboratory of Canada. The PLUS assay was directly compared to the SARS-CoV-2/Flu/RSV combination test using SARS-CoV-2 culture from five variants and remnant clinical specimens collected across the coronavirus disease 2019 pandemic. This included 50 clinical specimens negative for all pathogens, 110 clinical specimens positive for SARS-CoV-2, influenza A, influenza B, RSVA, and(or) RSVB and an additional 11 mixed samples to screen for target interactions. The PLUS assay showed a high % agreement with the widely used SARS-CoV-2/Flu/RSV combination test. Based on these findings, the PLUS assay and the Xpert SARS-CoV-2/Flu/RSV combination test results are largely consistent with no observed difference in sensitivity, specificity, or time to result when challenged with various SARS-CoV-2 variants. The reported cycle threshold (Ct) values provided by the new PLUS assay were also unchanged, with the exception of a possible 1–2 decrease reported in Ct for RSVA across a limited sample size.
Soft gluon–quark–antiquark emission in QCD hard scattering
Authors: Catani Stefano , Cieri Leandro , Colferai Dimitri , Coradeschi Francesco
Published: January 2023

We consider the radiation of a soft gluon (g) and a soft quark–antiquark ($$q{{\bar{q}}}$$

q

q

¯

) pair in QCD hard scattering. In the soft limit the scattering amplitude has a singular behaviour that is factorized and controlled by a soft current, which has a process-independent structure in colour space. We evaluate the soft $$gq{{\bar{q}}}$$

g
q

q

¯

current at the tree level for an arbitrary multiparton scattering process. The irreducible correlation component of the current includes strictly non-abelian terms and also terms with an abelian character. Analogous abelian correlations appear for soft photon–lepton–antilepton emission in QED. The squared current for soft $$gq{{\bar{q}}}$$

g
q

q

¯

emission produces colour dipole and colour tripole interactions between the hard-scattering partons. The colour tripole interactions are odd under charge conjugation and lead to charge asymmetry effects. We consider the specific applications to processes with two and three hard partons, and we discuss the structure of the corresponding charge asymmetry contributions. We also generalize our QCD results to the cases of QED and mixed QCD $$\times $$
×
QED radiative corrections.
A $$\nu $$ approach to analyzing neutrino data in the $${\textbf{R}}$$-parity-violating MSSM
Authors: Dreiner Herbi K. , Köhler Dominik , Nangia Saurabh
Published: January 2023

The R-parity-violating Minimal Supersymmetric Standard Model (RPV-MSSM) can naturally accommodate massive neutrinos as required by the oscillation data. However, studying the phenomenology is complicated due to the large number of undetermined parameters involved. Thus, studies are usually restricted to specific submodels. In this work, we develop an approach that allows us to be less restrictive. Working in (almost) the completely general RPV-MSSM setting, we analyze the structure of the neutrino mass matrix, and identify – for the case of two massive neutrinos – only four minimal classes of structures that can solve the neutrino data; we call these Minimal Oscillation Models (MOMs). We study the general features of each MOM class, and present numerical fits to the oscillation data. Our approach allows us to study all RPV models satisfying the neutrino data in a unified manner, as long as they satisfy the MOM criteria. Through several examples, we show that this indeed holds for many interesting scenarios.
Exotic states with triple charm
Authors: Bayar M. , Martínez Torres A. , Khemchandani K. P. , Molina R. , Oset E.
Published: January 2023

In this work we investigate the possibility of the formation of states from the dynamics involved in the $$D^*D^*D^*$$

D
∗

D
∗

D
∗

system by considering that two $$D^*$$

D
∗

’s generate a $$J^P=1^+$$

J
P

=

1
+

bound state, with isospin 0, which has been predicted in an earlier theoretical work. We solve the Faddeev equations for this system within the fixed center approximation and find the existence of $$J^P=0^-$$

J
P

=

0
-

, $$1^-$$

1
-

and $$2^-$$

2
-

states with charm 3, isospin 1/2, masses $$\sim 6000$$

∼
6000

 MeV, which are manifestly exotic hadrons, i.e., with a multiquark inner structure.
The fundamental group of the complement of the Hesse configuration
Authors: Kaneko Jyoichi
Published: January 2023

This note is of supplementary nature to our previous paper [J. Kaneko, K. Matsumoto and K. Ohara, The structure of a local system associated with a hypergeometric system of rank 9, Int. J. Math. 31 (2020) 2050021]. Let [Formula: see text] be the union of the nodal cubic curve and its three inflectional tangents in the complex projective plane [Formula: see text]. Such [Formula: see text] has appeared as the singular locus of certain hypergeometric system introduced in [J. Kaneko, K. Matsumoto and K. Ohara, A system of hypergeometric differential system in two variables of rank 9,Int. J. Math. 28 (2017) 1750015], and we have given generators and defining relations of the fundamental group of [Formula: see text] [J. Kaneko, K. Matsumoto and K. Ohara, The structure of a local system associated with a hypergeometric system of rank 9, Int. J. Math. 31 (2020) 2050021]. [Formula: see text] has a 9-fold Galois covering space [Formula: see text] given by the complement of the Hesse configuration of 12 lines in [Formula: see text]. Hence one can apply the method of Reidemeister–Schreier to derive a finite presentation of [Formula: see text], which we carry out in this note.
Bufalin Inhibits Tumorigenesis and SREBP-1-Mediated Lipogenesis in Hepatocellular Carcinoma via Modulating the ATP1A1/CA2 Axis
Authors: Huang Chang-Jing , Zhang Chen-Yue , Zhao Ying-Ke , Wang Dan , Zhuang Liping , Qian Ling , Xie Lin , Zhu Ying , Meng Zhi-Qiang
Published: January 2023

Altered lipid metabolism is a hallmark of hepatocellular carcinoma (HCC), a common malignancy with a dismal prognosis against which there is a lack of effective therapeutic strategies. Bufalin, a classical Na[Formula: see text]-K[Formula: see text]-ATPase (NKA) inhibitor, shows a potent antitumor effect against HCC. However, the role of bufalin in regulating lipid metabolism-related pathways of HCC remains unclear. In this study, we examined the interaction between bufalin and its target molecule, ATP1A1/CA2, in vitro and in vivo and explored the intersected downstream pathways in silico. A multi-omics analysis of transcriptomics and metabolomics was employed to screen for potential action targets. The results were verified and correlated with the downstream lipid de novo synthesis pathway and the bufalin/ATP1A1/CA2 axis. We found that bufalin suppressed the ATP1A1/CA2 ratio in the treated HCC cells and showed a negative correlation with bufalin drug sensitivity. Functionally, ATP1A1 overexpression and CA2 down-regulation inhibited the bufalin-suppressed HCC proliferation and metastasis. Furthermore, down-regulation of CA2 induced epithelial-mesenchymal transition and bufalin resistance in HCC cells by up-regulating ATP1A1. Mechanistically, lipid metabolism-related signaling pathways were enriched in low ATP1A1 and high CA2 expression subgroups in GSEA. The multi-omics analysis also showed that bufalin was closely related to lipid metabolism. We demonstrated that bufalin inhibits lipogenesis and tumorigenesis by down-regulating SREBP-1/FASN/ACLY via modulating the ATP1A1/CA2 axis in HCC.
The effect of damping by an environment on emergence of classicality
Authors: Bracken Paul
Published: January 2023

The role of dissipation with respect to a microscopic superposition of quantum states is investigated by means of master equations. This has implications for the study of the emergence of classicality from the quantum level. In particular, it illustrates why it is difficult to observe a macroscopic quantum state. The role of the environment is assumed by the measuring apparatus. A pure state is reduced to a mixture in the pointer basis of the system by means of the interaction with the apparatus. It is the intention that this type of analysis will have applications to experiments which are designed to better understand the environmental-assisted invariance formulation of quantum mechanics.
The adsorption of CN− on B-doped carbon nanotubes: The first-principles study
Authors: Guo Peng , An Libao , Zhang Yan
Published: January 2023

The first-principles method based on density functional theory has been used to investigate the adsorption performance of cyanide ions on intrinsic and B-doped carbon nanotubes (CNTs). We first investigate the effect of B-doping on the reactivity of CNTs. It is found that B-doping enhances the reactivity of CNTs while it ensures the structure of the doped CNTs is stable. Then, we perform a comparative analysis of various indices for each adsorption system. The results show that the adsorption effect of intrinsic CNTs on cyanide ions is weak, and there exists only physical adsorption between them. After B-doping, the adsorption energy between CNTs and cyanide ions increases by 87.6–122.8%, and the adsorption distance decreases substantially. The analysis of the energy band structure, partial density of states (PDOS) and charge density shows that the [Formula: see text]-orbital electrons of both C and N atoms in [Formula: see text] are filled into the [Formula: see text]-hybrid orbital of the B atom and the effective overlap of charges of each adsorption system is greatly increased as well. Therefore, the adsorption effect of B-doped CNTs on cyanide ions is greatly enhanced, and there is chemical adsorption formed between them. In addition, through analyzing the geometric structure and PDOS of each adsorption system, it can be seen that the adsorption effect of B-doped CNTs on the C atom in [Formula: see text] is better than that on the N atom. This study shows that B-doped CNTs can be used as an effective adsorbing or sensing material for [Formula: see text] in wastewater.
Performance improvement of MF-DFA on feature extraction of skin lesion images
Authors: Wang Jian , Zhang Yudong , Wang Zhaohu , Jiang Wenjing , Yang Mengdie , Huang Menghao , Kim Junseok
Published: January 2023

In this paper, we propose an improved algorithm based on the original two-dimensional (2D) multifractal detrended fluctuation analysis (2D MF-DFA) that involves increasing the number of cumulative summations in the computational steps of 2D MF-DFA. The proposed method aims to modify the distribution of the generalized Hurst exponent to ensure that skin lesion image features are extracted based on enhanced multifractal features. We calculate the generalized Hurst exponent using 0, 1, or 2 cumulative summation processes. A support vector machine (SVM) is adopted to examine the classification performance under these three conditions. Computation shows that the process involving two cumulative summations achieves an accuracy, sensitivity, and specificity of [Formula: see text], [Formula: see text], and [Formula: see text], respectively, which indicates that its performance is much better than with 0 and 1 cumulative summations.
Development of Fragility Functions for Embankment Slopes on Liquefiable Soils
Authors: Liu Guoguo , Geng Ping , Wang Tianqiang , Gu Wenqi , Deng Lin , Ma Shiqiang
Published: January 2023

In seismically active regions, high-filled embankment slopes on liquefiable soils tend to damage after strong earthquakes. Therefore, post-seismic damages should be estimated as soon as possible to mitigate potential losses. Fragility function is an efficient tool for assessing the seismic vulnerability conditions of structures, which links the probability of exceeding different limit states to seismic intensity. An embankment slope on liquefiable soils at Yading Airport in China was selected as the study object, and a series of numerical analyses of the embankment-foundation system utilizing the finite element method were conducted. Advanced dynamic constitutive models considering liquefaction and hysteresis characteristics were also adopted to simulate the nonlinear stress–strain behavior of soils under cyclic loadings. The post-seismic stability of embankment slopes was assessed using the strength reduction method (SRM) based on the stress–strain analysis. On this basis, the permanent ground deformation (PGD) at the ground-free field conditions was selected as the intensity measure (IM), while the factor of safety (FoS) of the slopes was selected as the damage measure (DM). Then, a procedure was presented for deriving seismic fragility functions with different damage states in light of incremental dynamic analysis (IDA). This paper aims to investigate the effects of different embankment typologies, such as the thickness of liquefiable soils and slope inclination, on the post-seismic vulnerability of embankment slopes. The fragility curves constructed in this study may soon be helpful for predicting the post-seismic damage of similar high-filled embankment slopes on liquefiable soils, which enables efficient traffic control and rapid disaster response.
Graded Seismic Metamaterials with Structural Steel Sections for Low-Frequency Isolation of Surface Wave
Authors: Zhang Kai , Luo Jie , Hong Fang , Yu Jiang , Zhao Cheng , Deng Zichen
Published: January 2023

By introducing the concept of a graded structure to seismic metamaterials, a new type of graded seismic metamaterial assembled using four steel sections with different graded levels is proposed to investigate its attenuation performance for surface waves. The dispersion curves and vibration modes are obtained using the finite element method and the sound cone method. A comparative analysis of the band gap characteristics of the four graded seismic metamaterials shows that an increase of the graded level is beneficial for widening the total band gap to a much larger relative bandwidth in the range of 0.1–13.07 Hz. In addition, a detailed analysis of the vibration modes reveals that local resonance is the main mechanism for the generation and change of the three band gaps. Moreover, the filling materials in the cavities, material and geometric parameters of the structure play important roles in the distribution and relative bandwidth of the band gaps. Finally, frequency–domain analysis is carried out on a finite system, and the agreement with the bandgaps is verified. This study paves the way for the design of graded seismic metamaterials. This concept allows flexible manipulation of the surface wave propagation by adjusting the graded level, fillers, geometric parameters of the steel sections, and soil materials to achieve seismic wave attenuation in low-frequency broadband.
On the standard quantized matrix algebra Mq(n): From a constructive-computational viewpoint
Authors: Tuniyaz Rabigul
Published: January 2023

Let [Formula: see text] be the standard quantized matrix algebra introduced by Faddeev, Reshetikhin, and Takhtajan. It is shown that some structural properties of [Formula: see text] and their modules may be established and realized in a constructive-computational way.
The average conjugacy class size and the Hall π-subgroups in π-solvable groups
Authors: Dong Shuqin , Pan Hongfei
Published: January 2023

Let [Formula: see text] be a [Formula: see text]-solvable group for some set of primes [Formula: see text]. We show that if [Formula: see text] is a Hall [Formula: see text]-subgroup of [Formula: see text], then [Formula: see text], where [Formula: see text] is the number of conjugacy classes of [Formula: see text].
On generalized quasi Baer skew monoid rings
Authors: Habibi Mohammad , Paykan Kamal , Arianpoor Hassan
Published: January 2023

In this paper, we study generalized right (principally) quasi Baer skew monoid rings. Examples to illustrate and delimit the results are provided.
The influence of the expression form of solutions to related equations on SEP elements in a ring with involution
Authors: Li Anqi , Wei Junchao
Published: January 2023

In recent years, SEP elements have been studied by many authors. In this paper, we obtain many new characterizations of SEP elements by using inner inverse, group inverse and Moore–Penrose inverse. Mainly, we construct a lot of equations, study the expression forms of solution to these equations in certain given set.
Effective Implementation of the Enterprise’s Innovation Capacity
Authors: Sarsen Kassymkhan , Aliyeva Naila , Demin Sergey , Giyasova Zeynab
Published: January 2023

The study’s aim is to compare qualitative and quantitative tools used to measure the effectiveness of innovation activities in an enterprise. The techniques examined in the study are the balanced scorecard, multilevel clustering, world indices or descriptive statistics, mixed approach, and statistical method. The research found that the balanced scorecard was the most cost-effective for measuring the business efficiency within an enterprise. Multilevel clustering and world indices/descriptive statistics can be applied to developed markets and businesses with sustainable entrepreneurial orientation. The results can be used by top-level managers to assess innovation performance and make informed decisions regarding the innovation-related policy.
A Three-Layer Imperfect Production Supply Chain Model with Green Investment Under Trade Credit and Cap-Trade Policy
Authors: Narang Pankaj , Kumari Mamta , De Pijus Kanti
Published: January 2023

A three-layer supply chain model with a single supplier, manufacturer, and retailer is presented in this paper. This proposed model is analyzed under green investment along with trade credit and cap-trade policy. It is considered that the manufacturer’s production process is imperfect. Few inferior quality products are reworked, and the remaining defective items are discarded. The manufacturer makes investments in green technology to reduce carbon emissions. The product’s demand is influenced by selling price, advertisement, and green-technology level. The total average profit of the supply chain is constructed under three different scenarios of trade credit provided by the manufacturer to the retailer. The primary goal of this research is to obtain the optimal selling price, production rate, and green-technology level to maximize the system’s total average profit by using genetic algorithm. A numerical example is shown to demonstrate the model, and sensitivity analysis is carried out to analyze the impact of numerous input parameters. Managerial insights and conclusions are provided to make this model helpful for manufacturers.
A Surgical Robotic Framework for Safe and Autonomous Data-Driven Learning and Manipulation of an Unknown Deformable Tissue with an Integrated Critical Space
Authors: Murphy Braden P. , Alambeigi Farshid
Published: January 2023

Aside from reliable robotic hardware and sensing technologies, to successfully transition from teleoperation to an autonomous and safe minimally invasive robotic surgery on unknown Deformable Tissues (U-DTs), various challenges need to be simultaneously considered and tackled to ensure safety and accuracy of the procedure. These challenges mainly include but are not limited to online modeling and reliable tracking of a U-DT with integrated critical tissues as well as development of reliable and fast control algorithms to enable safe, accurate, and autonomous surgical procedures. To collectively and simultaneously address these challenges and toward performing an autonomous and safe minimally invasive robotic surgery in a confined environment, in this paper, we present a surgical robotic framework with (i) real-time vision-based detection algorithm based on a Convolutional Neural Network (CNN) architecture that enables tracking the time-varying deformation of a critical tissue located within a U-DT and (ii) a complementary data-driven adaptive constrained optimization approach that learns deformation behavior of a U-DT while autonomously manipulating it within a time-varying constrained environment defined based on the output of the CNN detection algorithm. To thoroughly evaluate the performance of the proposed framework, we used the da Vinci Research Kit (dVRK) and performed various experiments on a custom-designed U-DT phantom with an arbitrary deformable vessel embedded within the phantom’s body (serving as the U-DT’s integrated critical space). Various experiments were conducted and analyzed to demonstrate the performance of the proposed framework and ensure robustness and safety while performing an autonomous surgical procedure.
Hydrocarbon generation and retention potential of Chang 7 organic-rich shale in the Ordos Basin, China
Authors: Sayid Mohamed Awad , Yao Zhi-Gang , Li Rongxi , Saif Mohammed Maged Ahmed
Published: January 2023

This study investigates the hydrocarbon generation and retention potential of Chang 7 organic-rich shale, with an emphasis on the producibility of retained hydrocarbons, using a sample set chosen to represent a maturity spectrum of 0.54–0.9%
R
o
and organic matter of type II and mixed type II–III. Based on the present-day hydrogen index (HI
pd
), the sample sets were divided into three sections: Upper, Middle and Lower. The three sections have a high hydrocarbon generation potential, with an average original total organic carbon (TOC
o
) content of 12.27, 3.10 and 5.13 wt%, of which 49.39, 23.62 and 49.86 wt% represents generative organic carbon (GOC), and an original hydrogen index (HI
o
) of 581.27, 278.05 and 586.82 HC g
−1
rock in the Upper, Middle, and Lower sections, respectively. The bulk of the analysed samples exhibited moderate–high oil saturation, yet the oil crossover effect was only observed in two organic-rich samples, indicating organic-rich shale-oil resource systems. The sorption capacity of organic matter controls oil retention in the Chang 7 shale system, where the oil saturation index increases with increasing maturity in the oil window until a maximum retention capacity of about 82–83 mgHC g
−1
TOC is reached at a vitrinite reflectance of 0.8% and thereafter decreases with further maturity.

Supplementary material:
A detailed spreadsheet of the back-calculated original geochemical parameters using the mass-balance method of

Jarvie (2012
a
)

is available at
https://doi.org/10.6084/m9.figshare.c.6387577
An Intelligent Approach Based on Cleaning up of Inutile Contents for Extremism Detection and Classification in Social Networks
Authors: Berhoum Adel , Meftah Mohammed Charaf Eddine , Laouid Abdelkader , Hammoudeh Mohammad
Published: January 2023

Extremism is a growing threat worldwide that presents a significant danger to public safety and national security. Social networks provide extremists with spaces to spread their ideas through commentaries or tweets, often in Asian English. In this paper, we propose an intelligent approach that cleans the text’s content, analyzes its sentiment, and extracts its features after converting it to digital data for machine learning treatments. We apply 16 intelligent machine learning classifiers for extremism detection and classification. The proposed artificial intelligence methods for Asian English language data are used to extract the essential features from the text. Our evaluation of the proposed model with an extremism dataset proves its effectiveness compared to the standard classification models based on various performance metrics. The proposed model achieves 93,6% accuracy for extremism detection and 97,0% for extremism classification.
MKVSE: Multimodal Knowledge Enhanced Visual-semantic Embedding for Image-text Retrieval
Authors: Feng Duoduo , He Xiangteng , Peng Yuxin
Published: January 2023

Image-text retrieval aims to take the text (image) query to retrieve the semantically relevant images (texts), which is fundamental and critical in the search system, online shopping, and social network. Existing works have shown the effectiveness of visual-semantic embedding and unimodal knowledge exploiting (e.g., textual knowledge) in connecting the image and text. However, they neglect the implicit multimodal knowledge relations between these two modalities when the image contains information that is not directly described in the text, hindering the ability to connect the image and text with the implicit semantic relations. For instance, an image shows a person next to the “tap” but the pairing text description may only include the word “wash,” missing the washing tool “tap.” The implicit semantic relation between image object “tap” and text word “wash” can help to connect the above image and text. To sufficiently utilize the implicit multimodal knowledge relations, we propose a
M
ultimodal
K
nowledge enhanced
V
isual-
S
emantic
E
mbedding (MKVSE) approach building a multimodal knowledge graph to explicitly represent the implicit multimodal knowledge relations and injecting it to visual-semantic embedding for image-text retrieval task. The contributions in this article can be summarized as follows: (1)
M
ultimodal
K
nowledge
G
raph (MKG) is proposed to explicitly represent the implicit multimodal knowledge relations between the image and text as
intra-modal semantic relations
and
inter-modal co-occurrence relations
. Intra-modal semantic relations provide synonymy information that is implicit in the unimodal data such as the text corpus. And inter-modal co-occurrence relations characterize the co-occurrence correlations (such as temporal, causal, and logical) that are implicit in image-text pairs. These two relations help establishing reliable image-text connections in the higher-level semantic space. (2)
M
ultimodal
G
raph
C
onvolution
N
etworks (MGCN) is proposed to reason on the MKG in two steps to sufficiently utilize the implicit multimodal knowledge relations. In the first step, MGCN focuses on the intra-modal relations to distinguish other entities in the semantic space. In the second step, MGCN focuses on the inter-modal relations to connect multimodal entities based on co-occurrence correlations. The two-step reasoning manner can sufficiently utilize the implicit semantic relations between two modal entities to enhance the embeddings of the image and text. Extensive experiments are conducted on two widely used datasets, namely, Flickr30k and MSCOCO, to demonstrate the superiority of the proposed MKVSE approach in achieving state-of-the-art performances. The codes are available at
https://github.com/PKU-ICST-MIPL/MKVSE-TOMM2023
.
Fine-Grained Interaction Modeling with Multi-Relational Transformer for Knowledge Tracing
Authors: Cui Jiajun , Chen Zeyuan , Zhou Aimin , Wang Jianyong , Zhang Wei
Published: January 2023

Knowledge tracing, the goal of which is predicting students’ future performance given their past question response sequences to trace their knowledge states, is pivotal for computer-aided education and intelligent tutoring systems. Although many technical efforts have been devoted to modeling students based on their question-response sequences, fine-grained interaction modeling between question-response pairs within each sequence is underexplored. This causes question-response representations less contextualized and further limits student modeling. To address this issue, we first conduct a data analysis and reveal the existence of complex cross effects between different question-response pairs within a sequence. Consequently, we propose MRT-KT, a multi-relational transformer for knowledge tracing, to enable fine-grained interaction modeling between question-response pairs. It introduces a novel relation encoding scheme based on knowledge concepts and student performance. Comprehensive experimental results show that MRT-KT outperforms state-of-the-art knowledge tracing methods on four widely-used datasets, validating the effectiveness of considering fine-grained interaction for knowledge tracing.
Uniqueness Constraints for Object Stores
Authors: Skavantzos Philipp , Leck Uwe , Zhao Kaiqi , Link Sebastian
Published: January 2023

Object stores offer an increasingly popular choice for data management and analytics. As with every data model, managing the integrity of objects is fundamental for data quality but also important for the efficiency of update and query operations. In response to shortcomings of unique and existence constraints in object stores, we propose a new principled class of constraints that separates uniqueness from existence dimensions of data quality, and fully supports multiple labels and composite properties. We illustrate benefits of the constraints on real-world examples of property graphs where node integrity is enforced for better update and query performance. The benefits are quantified experimentally in terms of perfectly scaling the access to data through indices that result from the constraints. We establish axiomatic and algorithmic characterizations for the underlying implication problem. In addition, we fully characterize which non-redundant families of constraints attain maximum cardinality for any given finite sets of labels and properties. We exemplify further use cases of the constraints: elicitation of business rules, identification of data quality problems, and design for data quality. Finally, we propose extensions to managing the integrity of objects in object stores such as graph databases.
Sex and diet, but not exercise, alter cardiovascular ACE2 and TMPRSS2 mRNA levels in aortic banded swine
Authors: Kelly Shannon C. , Thorne Pamela K. , Leary Emily V. , Emter Craig A.
Published: January 2023

This retrospective analysis evaluated the impact of exercise, sex, and diet on ACE2 and TMPRSS2 mRNA levels in preclinical swine heart failure models. Unlike normal exercise intensities, exercise training of an intensity tolerable to a patient with heart failure had no influence on ACE2 or TMPRSS2 mRNA. In a tissue-specific manner, ACE2 mRNA levels were altered due to sex and Western diet, whereas TMPRSS2 mRNA levels were sensitive to sex, Western diet, and pig species.
In Vitro Insulin Resistance Model: A Recent Update
Authors: Yudhani Ratih D. , Sari Yulia , Nugrahaningsih Dwi A. A. , Sholikhah Eti N. , Rochmanti Maftuchah , Purba Abdul K. R. , Khotimah Husnul , Nugrahenny Dian , Mustofa Mustofa
Published: January 2023

Insulin resistance, which affects insulin-sensitive tissues, including adipose tissues, skeletal muscle, and the liver, is the central pathophysiological mechanism underlying type 2 diabetes progression. Decreased glucose uptake in insulin-sensitive tissues disrupts insulin signaling pathways, particularly the PI3K/Akt pathway. An in vitro model is appropriate for studying the cellular and molecular mechanisms underlying insulin resistance because it is easy to maintain and the results can be easily reproduced. The application of cell-based models for exploring the pathogenesis of diabetes and insulin resistance as well as for developing drugs for these conditions is well known. However, a comprehensive review of in vitro insulin resistance models is lacking. Therefore, this review was conducted to provide a comprehensive overview and summary of the latest in vitro insulin resistance models, particularly 3T3-L1 (preadipocyte), C2C12 (skeletal muscle), and HepG2 (liver) cell lines induced with palmitic acid, high glucose, or chronic exposure to insulin.
On the Heat and Wave Equations with the Sturm-Liouville Operator in Quantum Calculus
Authors: Shaimardan Serikbol , Persson Lars-Erik , Tokmagambetov Nariman
Published: January 2023

In this paper, we explore a generalised solution of the Cauchy problems for the

q

-heat and

q

-wave equations which are generated by Jackson’s and the

q

-Sturm-Liouville operators with respect to

t

and

x

, respectively. For this, we use a new method, where a crucial tool is used to represent functions in the Fourier series expansions in a Hilbert space on quantum calculus. We show that these solutions can be represented by explicit formulas generated by the

q

-Mittag-Leffler function. Moreover, we prove the unique existence and stability of the weak solutions.
Electroacupuncture Alleviates 46-Trinitrobenzene Sulfonic Acid-Induced Visceral Pain via the Glutamatergic Pathway in the Prefrontal Cortex
Authors: Jiang Hao , Li Rongrong , Zhang Fan , Zhou Feini , Lin Jiangnan , Kong Ning , Chen Haitao , Guo Lingnan , Ye Chenxiao , Li Fuhao , Xu Maosheng
Published: January 2023

Visceral pain caused by inflammatory bowel disease (IBD) greatly diminishes the quality of life in affected patients. Yet, the mechanism of how IBD causes visceral pain is currently not fully understood. Previous studies have suggested that the central nervous system (CNS) and gut-brain axis (GBA) play an important role in IBD-inducing visceral pain. As one of the treatments for IBD, electroacupuncture (EA) has been used to treat various types of pain and gastrointestinal diseases in clinical practice. However, whether EA relieves the visceral pain of IBD through the gut-brain axis has not been confirmed. To verify the relationship between visceral pain and CNS, the following experiments were conducted. 1H-NMR analysis was performed on the prefrontal cortex (PFC) tissue obtained from IBD rat models to determine the link between the metabolites and their role in EA treatment against visceral pain. Western blot assay was employed for detecting the contents of glutamate transporter excitatory amino acid transporters 2 (EAAT2) and the glutamate receptor N-methyl-D-aspartate (NMDA) to verify whether EA treatment can alleviate neurotoxic symptoms induced by abnormal increases of glutamate. Study results showed that the glutamate content was significantly increased in the PFC of TNBS-induced IBD rats. This change was reversed after EA treatment. This process was associated with increased EAAT2 expression and decreased expression of NMDA receptors in the PFC. In addition, an increase in intestinal glutamic-metabolizing bacteria was observed. In conclusion, this study suggests that EA treatment can relieve visceral pain by reducing glutamine toxicity in the PFC, and serves an alternative clinical utility.
Improvements of Logarithmic and Identric Mean Inequalities for Scalars and Operators
Authors: Burqan Aliaa , Abu-Snainah Abeer , Saadeh Rania
Published: January 2023

In this article, we provide refined inequalities for a convex Riemann’s integrable function using refinements of the classical Hermite-Hadamard inequality. The obtained results are applied on special functions to establish new improvements of inequalities on the weighted logarithmic mean and weighted identric mean. Moreover, corresponding operator inequalities are introduced based on the scalar inequalities and the monotonicity property for operators.
Ventricular Tachycardia in a Pediatric Patient with High-Risk Thrombotic Thrombocytopenia Purpura
Authors: Kratochvil Taylor J. , Robinson Jeffrey A.
Published: January 2023

An 8-year-old previously healthy male was diagnosed with thrombotic thrombocytopenic purpura (TTP) and increased serum cardiac troponin I. Telemetry recorded non-sustained ventricular tachycardia, without ST-segment changes or other abnormalities on serial electrocardiogram. This case illustrates that cardiac monitoring by telemetry should be considered in high-risk TTP with elevated cardiac troponin.
Complex Emotion Recognition via Facial Expressions with Label Noises Self‐Cure Relation Networks
Authors: Wang Xiaoqing , Wang Yaocheng , Zhang Deyu
Published: January 2023

Current deep learning‐based facial expression recognition mainly focused on the six basic human emotions and relied on large‐scale and well‐annotated data. For complex emotion recognition, such a large amount of data are not easy to obtain, and a high‐quality annotation is even more difficult. Therefore, in this paper, we regard complex emotion recognition via facial expressions as a few‐shot learning problem and introduce a metric‐based few‐shot model named self‐cure relation networks (SCRNet), which is robust to label noises and is able to classify facial images of new classes of emotions by only few examples from each. Specifically, SCRNet learns a distance metric based on deep features abstracted by convolutional neural networks and predicts a query image’s emotion category by computing relation scores between the query image and the few examples of each new class. To tackle the label noise problem, SCRNet gives corrected labels to noise data via class prototype stored in external memory during the meta‐training phase. Experimenting on public datasets as well as on synthetic noise datasets demonstrates the effectiveness of our method.
NO2 Gas Sensing Properties of Ag-Functionalized Porous ZnO Sheets
Authors: Kim Min Young , Hwang Jeong Yun , Mirzaei Ali , Choi Sun-Woo , Kim Sang-il , Kim Hyun-Sik , Kim Sun-Jae , Roh Jong Wook , Choi Myung Sik , Lee Kyu Hyoung , Lee Seung Yong , Jin Changhyun
Published: January 2023

Herein, we report a simple and scalable synthesis route to prepare Ag-functionalized porous ZnO sheets and their enhanced NO2 gas sensing properties. Porous ZnO sheets functionalized with well-dispersed submicron Ag particles were prepared by using a hydrothermal method-based one-pot synthesis route from Zn and Ag precursors. NO2 gas sensing performance (response, selectivity, response time, and recovery time) was optimized at 200°C in the gas sensor fabricated with 3 at% Ag-functionalized porous ZnO sheets. We demonstrated a response ([Formula: see text]/[Formula: see text]) of 17.18 to 10 ppm NO2 gas and also obtained a high response of 14.05 even at 60% relative humidity due to the synergetic effect of improved NO2 gas adsorption in the presence of Ag particles and increased resistance by the formation of Schottky barrier at Ag-ZnO heterojunctions.
Extracting a Novel Emotional EEG Topographic Map Based on a Stacked Autoencoder Network
Authors: Vafaei Elnaz , Nowshiravan Rahatabad Fereidoun , Setarehdan Seyed Kamaledin , Azadfallah Parviz
Published: January 2023

Emotion recognition based on brain signals has increasingly become attractive to evaluate human’s internal emotional states. Conventional emotion recognition studies focus on developing machine learning and classifiers. However, most of these methods do not provide information on the involvement of different areas of the brain in emotions. Brain mapping is considered as one of the most distinguishing methods of showing the involvement of different areas of the brain in performing an activity. Most mapping techniques rely on projection and visualization of only one of the electroencephalogram (EEG) subband features onto brain regions. The present study aims to develop a new EEG-based brain mapping, which combines several features to provide more complete and useful information on a single map instead of common maps. In this study, the optimal combination of EEG features for each channel was extracted using a stacked autoencoder (SAE) network and visualizing a topographic map. Based on the research hypothesis, autoencoders can extract optimal features for quantitative EEG (QEEG) brain mapping. The DEAP EEG database was employed to extract topographic maps. The accuracy of image classifiers using the convolutional neural network (CNN) was used as a criterion for evaluating the distinction of the obtained maps from a stacked autoencoder topographic map (SAETM) method for different emotions. The average classification accuracy was obtained 0.8173 and 0.8037 in the valence and arousal dimensions, respectively. The extracted maps were also ranked by a team of experts compared to common maps. The results of quantitative and qualitative evaluation showed that the obtained map by SAETM has more information than conventional maps.
High Expression of DLGAP5 Indicates Poor Prognosis and Immunotherapy in Lung Adenocarcinoma and Promotes Proliferation through Regulation of the Cell Cycle
Authors: Tang Xiaolong , Zhou Honghong , Liu Yongshuo
Published: January 2023

Background. Lung adenocarcinoma (LUAD) is one of the most common types of cancer in the respiratory system, with a high mortality and recurrence rate. The role of disc large-associated protein 5 (DLGAP5) in LUAD progression and tumor microenvironment (TME) remains unclear. This study is aimed at revealing the functional role of DLGAP5 in LUAD based on bioinformatics analysis and experimental validation. Methods. Differential expression analysis, protein-protein interaction (PPI) network, and Cox regression analysis were applied to screen potential prognostic biomarkers. The mRNA and protein levels of DLGAP5 were analyzed using The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA) databases. The CCK-8 and colony formation assays were performed to assess the effect of DLGAP5 on cell proliferation. RNA sequencing (RNA-seq) and enrichment analyses were utilized to explore the biological functions of DLGAP5. Furthermore, flow cytometry was used to explore the role of DLGAP5 on the cell cycle. The ssGSEA algorithm in the R package “GSVA” was applied to quantify immune infiltrating cells, and the tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict the efficacy of immunotherapy. Moreover, analyses using the cBioPortal and MethSurv databases were performed to evaluate the mutation and methylation of DLGAP5, respectively. Finally, the prognostic value of DLGAP5 was estimated using the TCGA and the Gene Expression Omnibus (GEO) databases. The nomogram model was constructed using the TCGA-LUAD cohort and evaluated by adopting calibration curves, time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Results. DLGAP5 mRNA and protein abundance were significantly elevated in LUAD, and knockdown of DLGAP5 remarkably suppressed lung cancer cell proliferation through induction of cell cycle G1 arrest. In addition, DLGAP5 expression was positively correlated with Th2 cells and negatively correlated with B cells, T follicular helper cells, and mast cells. LUAD patients with high DLGAP5 expression may be resistant to immunotherapy. Hypermethylation levels of the cg23678254 site of DLGAP5 or its enhanced expression were unfavorable for the survival of LUAD patients. Meanwhile, DLGAP5 expression was associated with TNM stages, tumor status, and therapy outcome. Notably, the prognostic model constructed based on DLGAP5 expression exhibited great predictive capability, which was promising for clinical applications. Conclusion. DLGAP5 promotes lung cancer cell proliferation through regulation of the cell cycle and is associated with multiple immune infiltrating cells. Furthermore, DLGAP5 predicts poor prognosis and response to immunotherapy in lung adenocarcinoma.