bluuebunny/crossref_metadata_2025_split huggingface dataset:
Parameter Estimation in Brain Dynamics Models from Resting-State fMRI Data using Physics-Informed Neural Networks
Authors: Sotero Roberto C. , Sanchez-Bornot Jose M. , Shaharabi-Farahani Iman 
Published: February 2024

AbstractConventional modeling of the Blood-Oxygen-Level-Dependent (BOLD) signal in resting-state functional Magnetic Resonance Imaging (rsfMRI) struggle with parameter estimation due to the complexity of brain dynamics. This study introduces a novel brain dynamics model (BDM) that directly captures BOLD signal variations through differential equations. Unlike dynamic causal models or neural mass models, we integrate hemodynamic responses into the signal dynamics, considering both direct and network-mediated neuronal activity effects. We utilize Physics-Informed Neural Networks (PINNs) to estimate the parameters of this BDM, leveraging their ability to embed physical laws into the learning process. This approach simplifies computational demands and increases robustness against data noise, providing a comprehensive tool for analyzing rsfMRI data. Leveraging the functional connectivity matrices scaled by the estimated parameters, we apply a state-of-the-art community detection method to elucidate the network structure. Our analysis reveals significant differences in the participation coefficients of specific brain regions when comparing neurotypical individuals to those with Autism Spectrum Disorder (ASD), with distinct patterns observed between male and female cohorts. These differences are consistent with regions implicated in previous studies, reinforcing the role of these areas in ASD. By integrating PINNs with advanced network analysis, we demonstrate a robust approach for dissecting the complex neural signatures of ASD, providing a promising direction for future research in neuroimaging and the broader field of computational neuroscience.
A Real-time Multi-Subject Three Dimensional Pose Tracking System for Analyzing Social Behaviors of Non-human Primates
Authors: Cheng Chaoqun , Huang Zijian , Zhang Ruiming , Huang Guozheng , Wang Han , Tang Likai , Wang Xiaoqin 
Published: February 2024

AbstractThe ability to track positions and poses (body parts) of multiple monkeys in a 3D space in real time is highly desired by non-human primate (NHP) researchers in behavioral and systems neuroscience because it allows both analyzing social behaviors among multiple NHPs and performing close-loop experiments (e.g., delivering sensory or optogenetics stimulation during a particular behavior). While a number of animal pose tracking systems have been reported, nearly all published work lacks the real-time analysis capacity. Existing methods for tracking freely moving animals have been developed primarily for rodents which typically move on a 2D space. In contrast, NHPs roam in a 3D space and move at a much faster speed than rodents. We have designed a real-time 3D pose tracking system (MarmoPose) based on deep learning to capture and quantify social behaviors in natural environment of a highly social NHP species, the common marmosets (Callithrix jacchus) which has risen to be an important NHP model in neuroscience research in recent years. This system has minimum hardware requirement and can accurately track the 3D poses (16 body locations) of multiple marmosets freely roaming in their homecage. It employs a marmoset skeleton model to optimize the 3D poses and estimate invisible body locations. Furthermore, it achieves high inference speed and provides an online processing module for real-time closed-loop experimental control based on the 3D poses of marmosets. While this system is optimized for marmosets, it can also be adapted for other large animal species in a typical housing environment with minimal modifications.
Dysregulation of macrophage lipid metabolism underlies intracellular bacterial neuroinvasion
Authors: Sha Zhou , Yang Kun , Fu Shoupeng , Tong Xiaoyong , Yang Hui , Fang Huiling , He Qianqian , Li Ning , Shu Xinyu , Liu Qi , Du Yongliang , Fu Beibei , Xiong Yan , Guo Dong , Liu Jin , Li Qian , Zeng Hao , Zhang Xiaokai , Yao Rui , Zhang Xushuo , Guo Wenjin , Mao Xuhu , Long Mian , Lin Xiaoyuan , Zou Quanming , Wu Haibo 
Published: February 2024

SummaryAcute infection of the central nervous system is one of the deadliest diseases, but the mechanisms by which intracellular bacteria infiltrate the brain remain poorly understood. Phagocytic cells are usually recognized as the battlefield on which war is waged against intracellular bacteria; however, little is known about how the intracellular bacteria take advantage of infected phagocytes to access the brain. In this study, we find that a novel CD36+Fabp4+Pparg+macrophage subpopulation (CD36+macrophage) participates in penetration of the brain by intracellular bacteria without disruption of the brain-blood barrier. Biomechanical analysis reveals that abundant protrusions and adhesion molecules on CD36+macrophages confer significant resistance to the mechanical stress of blood flow, thereby providing more opportunities for these macrophages to adhere to the vascular endothelial surface. Through metabolomics analysis, we find that macrophage lipid metabolism is dysregulated during bacterial neuroinvasion, and that β-hydroxybutyrate promotes the formation and survival of CD36+macrophages. Importantly, ketogenesis exacerbates symptoms during bacterial neuroinvasion, which could be alleviated by supplementing with physiological level of glucose. Taken together, our findings uncover a pathway by which intracellular bacteria hijack macrophages to invade the brain, suggesting that lipid metabolism might play a role in the prevention or resolution of bacterial neuroinvasion.Graphic Abstract
Bicyclic pyrrolidine inhibitors ofToxoplasma gondiiphenylalanine t-RNA synthetase with antiparasitic potencyin vitroand brain exposure
Authors: Ence Chloe C. , Uddin Taher , Borrel Julien , Mittal Payal , Xie Han , Zoller Jochen , Sharma Amit , Comer Eamon , Schreiber Stuart L. , Melillo Bruno , Sibley L. David , Chatterjee Arnab K. 
Published: February 2024

AbstractPrevious studies have shown that bicyclic azetidines are potent and selective inhibitors of apicomplexan phenylalanine tRNA synthetase (PheRS), leading to parasite growth inhibitionin vitroandin vivo, including in models ofToxoplasmainfection. Despite these useful properties, additional optimization is required for the development of efficacious treatments of toxoplasmosis from this inhibitor series, in particular to achieve sufficient exposure in the brain. Here, we describe a series of PheRS inhibitors built on a new bicyclic pyrrolidine core scaffold designed to retain the exit-vector geometry of the isomeric bicyclic azetidine core scaffold while offering avenues to sample diverse chemical space. Relative to the parent series, bicyclic pyrrolidines retain reasonable potency and target selectivity for parasite PheRS vs. host. Further structure-activity relationship studies revealed that the introduction of aliphatic groups improved potency, ADME and PK properties, including brain exposure. The identification of this new scaffold provides potential opportunities to extend the analog series to further improve selectivity and potency and ultimately deliver a novel, efficacious treatment of toxoplasmosis.Lay abstractThe inhibition of protein synthesis in parasites has emerged as an attractive strategy to target parasitic diseases such as malaria, cryptosporidiosis, and toxoplasmosis. In this study, we report a new series of small molecules that inhibit the enzyme responsible for loading the amino acid phenylalanine onto its cognate tRNA in the parasite speciesToxoplasma, directly upstream of protein synthesis. We show that small molecules in this new series inhibitToxoplasmaparasite growth at low concentrations, and that, orally administered to mice, these molecules achieve high concentrations in the brain, which hold promise for the treatment of forms of toxoplasmosis that result from parasitic brain infection.
Quantifying the Relative Importance of Genetics and Environment on the Comorbidity between Mental- and Cardiometabolic Disorders: A Comprehensive Analysis of National Register Data from 17 million Scandinavians
Authors: Meijsen Joeri , Hu Kejia , Krebs Morten Dybdahl , Athanasiadis Georgios , Washbrook Sarah , Zetterberg Richard , e Silva Raquel Nogueira Avelar , Shorter John R. , Gådin Jesper R. , Bergstedt Jacob , Howard David M. , Ye Weimin ,   The iPSYCH Consortium, Lu Yi , Valdimarsdóttir Unnur A. , Ingason Andrés , Mikkelsen Dorte Helenius , Plana-Ripoll Oleguer , McGrath John J. , Micali Nadia , Andreassen Ole A. , Werge Thomas M. , Fang Fang , Buil Alfonso 
Published: February 2024

AbstractMental disorders (MDs) are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders (CMDs). Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and complete genealogies of Denmark and Sweden (n=17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six MDs and 14 CMDs. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with CMDs, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with CMDs was mainly or fully driven by environmental factors. These findings provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.
Shedding light on charmonium
Authors: Wang Zhiguo , Li Meijian , Li Yang , Vary James P. 
Published: February 2024

We investigate E1 radiative transitions within charmonium in a relativistic approach based on light-front QCD. In quantum field theory, two sets of processes are pure E1: χc0→J/ψγ (ψ→χc0γ) and hc→ηcγ (ηc′→hcγ), both involving the P-wave charmonia. We compute the E1 radiative decay widths as well as the corresponding transition form factors of various processes including those involving 2P states. These observables provide an access to the microscopic structures of the P-wave charmonium. We show that our parameter-free predictions are in excellent agreement with the experimental measurements as well as lattice simulations whenever available.

Published by the American Physical Society
2024
Variational sparse diffusion and its application in mesh processing
Authors: Xue Yongjiang , Wang Wei , Song Qingzeng 
Published: February 2024

PurposeThe primary objective of this study is to tackle the enduring challenge of preserving feature integrity during the manipulation of geometric data in computer graphics. Our work aims to introduce and validate a variational sparse diffusion model that enhances the capability to maintain the definition of sharp features within meshes throughout complex processing tasks such as segmentation and repair.Design/methodology/approachWe developed a variational sparse diffusion model that integrates a high-order L1 regularization framework with Dirichlet boundary constraints, specifically designed to preserve edge definition. This model employs an innovative vertex updating strategy that optimizes the quality of mesh repairs. We leverage the augmented Lagrangian method to address the computational challenges inherent in this approach, enabling effective management of the trade-off between diffusion strength and feature preservation. Our methodology involves a detailed analysis of segmentation and repair processes, focusing on maintaining the acuity of features on triangulated surfaces.FindingsOur findings indicate that the proposed variational sparse diffusion model significantly outperforms traditional smooth diffusion methods in preserving sharp features during mesh processing. The model ensures the delineation of clear boundaries in mesh segmentation and achieves high-fidelity restoration of deteriorated meshes in repair tasks. The innovative vertex updating strategy within the model contributes to enhanced mesh quality post-repair. Empirical evaluations demonstrate that our approach maintains the integrity of original, sharp features more effectively, especially in complex geometries with intricate detail.Originality/valueThe originality of this research lies in the novel application of a high-order L1 regularization framework to the field of mesh processing, a method not conventionally applied in this context. The value of our work is in providing a robust solution to the problem of feature degradation during the mesh manipulation process. Our model’s unique vertex updating strategy and the use of the augmented Lagrangian method for optimization are distinctive contributions that enhance the state-of-the-art in geometry processing. The empirical success of our model in preserving features during mesh segmentation and repair presents an advancement in computer graphics, offering practical benefits to both academic research and industry applications.
Tito’s Goa: deciding the growth strategy for India?
Authors: Mehdi Mokhalles Mohammad , Kumar Nitesh , Srivastava Manish , Akoijam Sunildro L.S. , Sarma Tridib Ranjan 
Published: February 2024

Learning outcomes
The case study aims to provide students with an understanding of the challenges a business faces when operating in India. In conclusion of this study, students should be able to know why franchising is such a common way of delivering services to end users, describe the “place” decisions of physical channels, and be familiar with the strategic and tactical location considerations and devise a growth strategy to expand the business.

Case overview/synopsis
Situated at Tito’s Lane in North Goa, Tito’s was the discotheque founded by Tito Henry D’Souza in 1971. The company offered restaurant, concert space and nightclub services to music and party lovers from diverse locations. Ricardo D’Souza and David D’Souza (both brothers) spearheaded the business. Ricardo understood the growth of markets and the factors driving the growth in India. The key factors driving the Tito’s and pub, bar, café and lounge business in India were rising disposable incomes among Indians, nightlife parties by young individuals and preference for quality food and alcoholic beverages among the customers. By seeing the opportunities in 2022, Ricardo considered expanding its business across India. How should Ricardo move to expand its business and offerings? What strategies should they devise for the growth of the business?

Complexity academic level
This case study is designed for use in undergraduate programs like Bachelor of Business Administration. It is ideal for strategy and services marketing. Theoretical frameworks like the Ansoff matrix are suitable for analyzing the case study to understand the growth of the business.

Supplementary materials
Teaching notes are available for educators only.

Subject code
CSS 8: Marketing.
Adjoined ISPH method and artificial intelligence for thermal radiation on double diffusion inside a porous L-shaped cavity with fins
Authors: Elshehabey Hillal M. , Çolak Andaç Batur , Aly Abdelraheem 
Published: February 2024

Purpose
The purpose of this study is to adapt the incompressible smoothed particle hydrodynamics (ISPH) method with artificial intelligence to manage the physical problem of double diffusion inside a porous L-shaped cavity including two fins.

Design/methodology/approach
The ISPH method solves the nondimensional governing equations of a physical model. The ISPH simulations are attained at different Frank–Kamenetskii number, Darcy number, coupled Soret/Dufour numbers, coupled Cattaneo–Christov heat/mass fluxes, thermal radiation parameter and nanoparticle parameter. An artificial neural network (ANN) is developed using a total of 243 data sets. The data set is optimized as 171 of the data sets were used for training the model, 36 for validation and 36 for the testing phase. The network model was trained using the Levenberg–Marquardt training algorithm.

Findings
The resulting simulations show how thermal radiation declines the temperature distribution and changes the contour of a heat capacity ratio. The temperature distribution is improved, and the velocity field is decreased by 36.77% when the coupled heat Cattaneo–Christov heat/mass fluxes are increased from 0 to 0.8. The temperature distribution is supported, and the concentration distribution is declined by an increase in Soret–Dufour numbers. A rise in Soret–Dufour numbers corresponds to a decreasing velocity field. The Frank–Kamenetskii number is useful for enhancing the velocity field and temperature distribution. A reduction in Darcy number causes a high porous struggle, which reduces nanofluid velocity and improves temperature and concentration distribution. An increase in nanoparticle concentration causes a high fluid suspension viscosity, which reduces the suspension’s velocity. With the help of the ANN, the obtained model accurately predicts the values of the Nusselt and Sherwood numbers.

Originality/value
A novel integration between the ISPH method and the ANN is adapted to handle the heat and mass transfer within a new L-shaped geometry with fins in the presence of several physical effects.
A robot motion skills method with explicit environmental constraints
Authors: Huang Yonghua , Li Tuanjie , Ning Yuming , Zhang Yan 
Published: February 2024

Purpose
This paper aims to solve the problem of the inability to apply learning methods for robot motion skills based on dynamic movement primitives (DMPs) in tasks with explicit environmental constraints, while ensuring the reliability of the robot system.

Design/methodology/approach
The authors propose a novel DMP that takes into account environmental constraints to enhance the generality of the robot motion skill learning method. First, based on the real-time state of the robot and environmental constraints, the task space is divided into different regions and different control strategies are used in each region. Second, to ensure the effectiveness of the generalized skills (trajectories), the control barrier function is extended to DMP to enforce constraint conditions. Finally, a skill modeling and learning algorithm flow is proposed that takes into account environmental constraints within DMPs.

Findings
By designing numerical simulation and prototype demonstration experiments to study skill learning and generalization under constrained environments. The experimental results demonstrate that the proposed method is capable of generating motion skills that satisfy environmental constraints. It ensures that robots remain in a safe position throughout the execution of generation skills, thereby avoiding any adverse impact on the surrounding environment.

Originality/value
This paper explores further applications of generalized motion skill learning methods on robots, enhancing the efficiency of robot operations in constrained environments, particularly in non-point-constrained environments. The improved methods are applicable to different types of robots.
Considering leadership pedagogy in creative arts education
Authors: Walzer Daniel 
Published: February 2024

PurposeIn the following theoretical article, the author generates a theory of Leadership Pedagogy and its connection to Creative Arts Education.Design/methodology/approachThe article analyzes Leadership Theory across three pillars: Socio-relational, Cognitive and Creative, and how these areas underscore thoughtful and caring pedagogy and inclusive teaching in undergraduate education.FindingsDrawing on the Scholarship of Teaching and Learning (SoTL), the article advocates for a flexible, multifaceted approach to curricular design rooted in theoretical pluralism, prioritizing interdisciplinary methods to bridge theory and practice in Creative Arts Education.Originality/valueThe article concludes with implications for future research and collaboration connecting Leadership Studies and the Arts.
The effect of discount discrepancy on purchase intention: the moderation of justification
Authors: Zuniga Huertas Melby Karina , Ferreira Lepre Thais Rubia , Torres Urdan André 
Published: February 2024

Purpose
This paper aims to clarify the effect of discount discrepancy (DD) on consumers’ purchase intention (PI). The authors propose, test and provide evidence and explanations about the moderation of justification in the relation between consumers’ perceived DD and PI.

Design/methodology/approach
The authors conducted three experimental studies with a 2 × 2 factorial design, focusing on consumers’ processing of price discounts. Participants were informed that this study aimed to gather opinions on fashion, clothing and retail sales promotions. They accessed the questionnaire via Qualtrics. Each participant took part in only one study. The experimental conditions were manipulated through scenarios.

Findings
Study 1 tested and supported the moderation of justification on the effect of DD on PI. Study 2 tested and supported the moderation of the type of justification for the effect of DD on PI. Study 3 confirmed the findings in Study 2 and revealed the more effective type of justification.

Research limitations/implications
The authors focused on a typically hedonic product category (fashion clothing). Further research should include a wider variety of goods and services, which could lead to different explanations or generalizations.

Practical implications
Sales promotions must refrain from generating DD between the initial price discount and the subsequent smaller discounts. Practitioners must evaluate the gains of an initial, more considerable percentage discount to attract consumers to the store and sell them other products versus the cost of losing sales because of DD. Management should recognize the importance of giving the correct justification for perceived DD, aligning the firm’s justification with the consumer’s motivation to buy the product.

Social implications
The authors offer subsidies for effective consumer protection policies.

Originality/value
By studying the influence of justification on the effect of DD on PI, the authors propose a mechanism that would reduce the negative effect of DD on consumers’ PI.
Study on the mechanism underlying Trichosanthis peel injection‐induced improvements in myocardial fibrosis markers in patients with chronic heart failure
Authors: He Yue , Gu Xinsheng , Yang Zhou , Wang Hao , Liu Ping 
Published: February 2024

AbstractIn this research, we aimed to observe the changes in myocardial fibrosis indices in patients with chronic heart failure before and after treatment and to evaluate the anti‐chronic heart failure and ventricular remodelling effects of Trichosanthis peel (TP) injection. This study was a single‐center, open, single‐blind, randomized controlled study with an optimal efficacy design. Patients were consecutively and randomly divided into two groups, with 36 patients in the TP injection group and 36 patients in the conventional treatment group. ELISA was used to measure changes in myocardial fibrosis indices before and after discharge, including transforming growth factor β (TGF‐β), serum hyaluronic acid (HA), type I procollagen (PCI), laminin (LN) and type III procollagen (PCIII). There was no significant difference between the two groups in clinical data or baseline level of myocardial fibrosis before treatment. After treatment, compared with the conventional treatment group, the myocardial fibrosis index was significantly decreased following TP injection. Our findings indicate that TP injection combined with conventional medicine can attenuate myocardial fibrosis by reducing angiotensin II, aldosterone, TGFβ, HA, PCI, metallomatrix proteinase 2, connective tissue growth factor and LN and promote ventricular remodelling in patients with chronic heart failure.