bluuebunny/crossref_metadata_2025 huggingface dataset:
ChatGPT takes the FCPS exam in Internal Medicine
Authors: Qazi Hina , Ali Syed Ahsan , Irfan Muhammad , Siddiqui M. A. Rehman
Published: June 2024

Large language models (LLMs) have exhibited remarkable proficiency in clinical knowledge, encompassing diagnostic medicine, and have been tested on questions related to medical licensing examinations. ChatGPT has recently gained popularity because of its ability to generate human-like responses when presented with exam questions. It has been tested on multiple undergraduate and subspecialty exams and the results have been mixed. We aim to test ChatGPT on questions mirroring the standards of the FCPS exam, the highest medical qualification in Pakistan.

We used 111 randomly chosen MCQs of internal medicine of FCPS level in the form of a text prompt, thrice on 3 consecutive days. The average of the three answers was taken as the final response. The responses were recorded and compared to the answers given by subject experts. Agreement between the two was assessed using the Chi-square test and Cohen’s Kappa with 0.75 Kappa as an acceptable agreement. Univariate regression analysis was done for the effect of subspeciality, word count, and case scenarios in the success of ChatGPT.. Post-risk stratification chi-square and kappa statistics were applied.

ChatGPT 4.0 scored 73% (69%-74%). Although close to the passing criteria, it could not clear the FCPS exam. Question characteristics and subspecialties did not affect the ChatGPT responses statistically. ChatGPT shows a high concordance between its responses indicating sound knowledge and a high reliability.

This study’s findings underline the necessity for caution in over-reliance on AI for critical clinical decisions without human oversight. Creating specialized models tailored for medical education could provide a viable solution to this problem.

Author Summary

Artificial intelligence is the future of the world. Since the launch of ChatGPT in 2014, it become one of the most widely used application for people in all fields of life. A wave of excitement was felt among the medical community when the chatbot was announced to have cleared the USMLE exams. Here, we have tested ChatGPT on MCQs mirroring the standard of FCPS exam questions. The FCPS is the highest medical qualification in Pakistan. We found that with a vast data base, ChatGPT could not clear the exam in all of the three attempts taken by it. ChatGPT, however, scored a near passing score indicating a relatively sound knowledge.

We found ChatGPT to be a consistent LLM for complex medical scenarios faced by doctors in their daily lives irrespective of the subspecialty, length or word count of the questions. Although ChatGPT did not pass the FCPS exam, its answers displayed a high level of consistency, indicating a solid understanding of internal medicine. This demonstrates the potential of AI to support and improve medical education and healthcare services in near future.
Prediction of binding sites of GPCRs based on 3D convolutional neural networks
Authors: Yu Junfeng , Zhang Ying , Lv Jun
Published: June 2024

G protein-coupled receptors are a class of receptor proteins located on the cell membrane, regulating the perception and response of cells to various external signals. Identifying the binding sites of G protein-coupled receptors plays a crucial role in understanding their allosteric modulation mechanisms. However, obtaining the crystal structure of the complex through experimental means and subsequently identifying the binding sites require substantial resources. With the development of computer-aided computation, deep learning can effectively predict the binding sites between proteins and ligands. This study predicted the binding sites of G protein-coupled receptors based on 3D convolutional neural network. A total of 108 G protein-coupled receptors recorded in the scPDB database were collected for this study, and a 3D convolutional neural network model was established based on these three-dimensional structures. Firstly, the PDB file of the protein is voxelized and segmented into different channels according to the type of atoms in a certain region. Then, 3D convolutional neural network is employed to predict the binding site through traversal, and the optimal voxel box size and model parameters are determined based on performance evaluation metrics. The established 3D convolutional neural network accurately predicts the binding site of G protein-coupled receptors, with an accuracy as high as 0.942, precision of 0.678, and recall rate of 0.532. Additionally, using the backpropagation algorithm, the gradients of the input data are calculated, and the importance of input elements on the final classification result is analyzed.
Gradient matching accelerates mixed-effects inference for biochemical networks
Authors: van Oppen Yulan B. , Milias-Argeitis Andreas
Published: June 2024

Single-cell time series data frequently display considerable variability across a cell population. The current gold standard for inferring parameter distributions across cell populations is the Global Two Stage (GTS) approach for nonlinear mixed-effects (NLME) models. However, this method is computationally intensive, as it makes repeated use of non-convex optimization that in turn requires numerical integration of the underlying system. Here, we propose the Gradient Matching GTS (GMGTS) method as an efficient alternative to GTS. Gradient matching offers an integration-free approach to parameter estimation that is particularly powerful for dynamical systems that are linear in the unknown parameters, such as biochemical networks modeled by mass action kinetics. Here, we harness the power of gradient matching by integrating it into the GTS framework. To this end, we significantly expand the capabilities of gradient matching via uncertainty propagation calculations and the development of an iterative estimation scheme for partially observed systems. Through comparisons of GMGTS with GTS in different inference setups, we demonstrate that our method provides a significant computational advantage, thereby facilitating the use of complex NLME models in systems biology applications.
Endogenous LRRK2 and PINK1 function in a convergent neuroprotective ciliogenesis pathway in the brain
Authors: Bagnoli Enrico , Lin Yu-En , Burel Sophie , Jaimon Ebsy , Antico Odetta , Themistokleous Christos , Nikoloff Jonas M. , Morella Ilaria , Watzlawik Jens O. , Fiesel Fabienne C. , Springer Wolfdieter , Tonelli Francesca , Brooks Simon P. , Dunnett Stephen B. , Brambilla Riccardo , Alessi Dario R. , Pfeffer Suzanne R. , Muqit Miratul M. K.
Published: June 2024

Mutations in LRRK2 and PINK1 are associated with familial Parkinson’s disease (PD). LRRK2 phosphorylates Rab GTPases within the Switch II domain whilst PINK1 directly phosphorylates Parkin and ubiquitin and indirectly induces phosphorylation of a subset of Rab GTPases. Herein we have crossed LRRK2 [R1441C] mutant knock-in mice with PINK1 knock-out (KO) mice and report that loss of PINK1 does not impact endogenous LRRK2-mediated Rab phosphorylation nor do we see significant effect of mutant LRRK2 on PINK1-mediated Rab and ubiquitin phosphorylation. In addition, we observe that a pool of the Rab-specific, PPM1H phosphatase, is transcriptionally up-regulated and recruited to damaged mitochondria, independent of PINK1 or LRRK2 activity. Parallel signalling of LRRK2 and PINK1 pathways is supported by assessment of motor behavioural studies that show no evidence of genetic interaction in crossed mouse lines. Previously we showed loss of cilia in LRRK2 R1441C mice and herein we show that PINK1 KO mice exhibit a ciliogenesis defect in striatal cholinergic interneurons and astrocytes that interferes with Hedgehog induction of glial derived-neurotrophic factor (GDNF) transcription. This is not exacerbated in double mutant LRRK2 and PINK1 mice. Overall, our analysis indicates that LRRK2 activation and/or loss of PINK1 function along parallel pathways to impair ciliogenesis, suggesting a convergent mechanism towards PD. Our data suggests that reversal of defects downstream of ciliogenesis offers a common therapeutic strategy for LRRK2 or PINK1 PD patients whereas LRRK2 inhibitors that are currently in clinical trials are unlikely to benefit PINK1 PD patients.
Decoding Protein Aggregation through Computational Approach: Identification and Scoring of Aggregation-Prone Regions in Protein Sequences
Authors: Kaushik Rahul , Launey Thomas
Published: June 2024

Protein aggregation is a critical phenomenon associated with numerous neurodegenerative and systemic diseases. Understanding the propensity of proteins to aggregate is essential for unraveling the molecular basis of these disorders and for design and engineering of novel proteins or modulating the activity/stability of enzymatic proteins. Here, we present APR-Score, a novel machine-learning based computational method designed to identify aggregation-prone regions within protein sequences. ARP-Score leverages a combination of sequence-based features to predict regions of proteins that are prone to aggregate. The APR-Score harnessed the information ingrained in the compiled sequence and structural features to provide state-of-the-art accuracy. The APR-Score is assessed by conducting rigorous cross-validation experiments on the training dataset and further validated on an independent test dataset. The APR-Score prediction models demonstrated robustness and reliability in discriminating aggregation-prone regions from non-aggregating ones on an independent dataset, achieving Mathew’s correlation coefficient (MCC) 0.81, precision 0.89, and F1-Score 0.91. The APR-Score offers a valuable tool for researchers investigating protein aggregation-related diseases, as it can expedite the identification of aggregation-prone regions, aiding in the development of targeted therapies and diagnostic tools. The computational protein design and engineering regimes can be facilitated through APR-Score based identification and screening of aggregation prone protein sequences.
SETD8 inhibition targets cancer cells with increased rates of ribosome biogenesis
Authors: Murga Matilde , Lopez-Pernas Gema , Soliva Robert , Fueyo-Marcos Elena , Amor Corina , Faustino Ignacio , Serna Marina , Serrano Alicia G. , Díaz Lucía , Martínez Sonia , Blanco-Aparicio Carmen , Antón Marta Elena , Seashore-Ludlow Brinton , Pastor Joaquín , Jafari Rozbeh , Lafarga Miguel , Llorca Oscar , Orozco Modesto , Fernández-Capetillo Oscar
Published: June 2024

SETD8 is a methyltransferase that is overexpressed in several cancers, which monomethylates H4K20 as well as other non-histone targets such as PCNA or p53. We here report novel SETD8 inhibitors, which were discovered while trying to identify chemicals that prevent 53BP1 foci formation, an event mediated by H4K20 methylation. Consistent with previous reports, SETD8 inhibitors induce p53 expression, although they are equally toxic for p53-deficient cells. Thermal stability proteomics revealed that the compounds had a particular impact on nucleoli, which was confirmed by fluorescent and electron microscopy. Similarly,Setd8deletion generated nucleolar stress and impaired ribosome biogenesis, confirming that this was an on-target effect of SETD8 inhibitors. Furthermore, a genome-wide CRISPR screen identified an enrichment of nucleolar factors among those modulating the toxicity of SETD8 inhibitors. Accordingly, the toxicity of SETD8 inhibitors correlated with MYC or mTOR activity, key regulators of ribosome biogenesis. Together, our study provides a new class of SETD8 inhibitors and a novel biomarker to identify tumors most likely to respond to this therapy.
Modulation of beta oscillatory dynamics in motor and frontal areas during physical fatigue
Authors: Matta Pierre-Marie , Baurès Robin , Duclay Julien , Alamia Andrea
Published: June 2024

Beta-band oscillations have been suggested to promote the maintenance of the current motor (or cognitive) set, thus signaling the ‘status quo’ of the system. While this hypothesis has been reliably demonstrated in many studies, it fails to explain changes in beta-band activity due to the accumulation of physical fatigue. In the current study, we aimed to reconcile the functional role of beta oscillations during physical fatigue within the status quo theory. Using an innovative EEG design, we identified two distinct beta-band power dynamics in the motor areas as fatigue rises: (i) an enhancement at rest, supposedly promoting the resting state, and (ii) a decrease during contraction, thought to reflect the increase in motor cortex activation necessary to cope with the muscular fatigue. We then conducted effective connectivity analyses, which revealed that the modulations during contractions were driven by frontal areas. Finally, we implement a biologically plausible model to replicate and characterize our results mechanistically. Together, our findings anchor the physical fatigue paradigm within the status quo theory, thus shedding light on the functional role of beta oscillations in physical fatigue. We further discuss a unified interpretation that might explain the conflicting evidence previously encountered in the physical fatigue literature.
A feedforward mechanism for human-like contour integration
Authors: Doshi Fenil R. , Konkle Talia , Alvarez George A.
Published: June 2024

Deep neural network models provide a powerful experimental platform for exploring core mechanisms underlying human visual perception, such as perceptual grouping and contour integration — the process of linking local edge elements to arrive at a unified perceptual representation of a complete contour. Here, we demonstrate that feedforward, nonlinear convolutional neural networks (CNNs) can emulate this aspect of human vision without relying on mechanisms proposed in prior work, such as lateral connections, recurrence, or top-down feedback. We identify two key inductive biases that give rise to human-like contour integration in purely feedforward CNNs: a gradual progression of receptive field sizes with increasing layer depth, and a bias towards relatively straight (gradually curved) contours. While lateral connections, recurrence, and feedback are ubiquitous and important visual processing mechanisms, these results provide a computational existence proof that a feedforward hierarchy is sufficient to implement gestalt “good continuation” mechanisms that detect extended contours in a manner that is consistent with human perception.
Endothelial cell Piezo1 promotes vascular smooth muscle cell differentiation on large arteries
Authors: Abello Javier , Yin Ying , Zhao Yonghui , Maurer Josh , Lee Jihui , Bodell Cherokee , Clevenger Abigail J. , Burton Zarek , Goeckel Megan E. , Lin Michelle , Grainger Stephanie , Halabi Carmen M. , Raghavan Shreya A. , Sah Rajan , Stratman Amber N.
Published: June 2024

Vascular stabilization is a mechanosensitive process, in part driven by blood flow. Here, we demonstrate the involvement of the mechanosensitive ion channel, Piezo1, in promoting arterial accumulation of vascular smooth muscle cells (vSMCs) during zebrafish development. Using a series of small molecule antagonists or agonists to temporally regulate Piezo1 activity, we identified a role for the Piezo1 channel in regulatingklf2alevels and altered targeting of vSMCs between arteries and veins. Increasing Piezo1 activity suppressedklf2aand increased vSMC association with the cardinal vein, while inhibition of Piezo1 activity increasedklf2alevels and decreased vSMC association with arteries. We supported the small molecule data within vivogenetic suppression ofpiezo1and2in zebrafish, resulting in loss oftransgelin+vSMCs on the dorsal aorta. Further, endothelial cell (EC)-specificPiezo1knockout in mice was sufficient to decrease vSMC accumulation along the descending dorsal aorta during development, thus phenocopying our zebrafish data, and supporting functional conservation of Piezo1 in mammals. To determine mechanism, we usedin vitromodeling assays to demonstrate that differential sensing of pulsatile versus laminar flow forces across endothelial cells changes the expression of mural cell differentiation genes. Together, our findings suggest a crucial role for EC Piezo1 in sensing force within large arteries to mediate mural cell differentiation and stabilization of the arterial vasculature.
Brain Age Prediction: Deep Models Need a Hand to Generalize
Authors: Rajabli Reza , Soltaninejad Mahdie , Fonov Vladimir S. , Bzdok Danilo , Collins D. Louis
Published: June 2024

Predicting brain age from T1-weighted MRI is a promising marker for understanding brain aging and its associated conditions. While deep learning models have shown success in reducing the Mean Absolute Error (MAE) of predicted brain age, concerns about robust and accurate generalization in new data limit their clinical applicability. The large number of trainable parameters, combined with limited medical imaging training data, contribute to this challenge, often resulting in a generalization gap where there is a significant discrepancy between model performance on training data versus unseen data.

In this study, we assess a deep model, SFCN-reg, based on the VGG-16 architecture, and address the generalization gap through comprehensive preprocessing, extensive data augmentation, and model regularization. Using training data from the UK Biobank, we demonstrate substantial improvements in model performance. Specifically, our approach reduces the generalization MAE by 44% (from 5.25 to 2.96 years) in the Alzheimer’s Disease Neuroimaging Initiative dataset and by 22% (from 4.35 to 3.40 years) in the Australian Imaging, Biomarker and Lifestyle dataset. Furthermore, we achieve a 29% reduction in scan-rescan error (from 0.86 to 0.61 years) while enhancing the model’s robustness to registration errors. Feature importance maps highlight anatomical regions used to predict age.

These results highlight the critical role of high-quality preprocessing and robust training techniques in improving accuracy and narrowing the generalization gap, both necessary steps towards the clinical use of brain age prediction models. Our study makes valuable contributions to neuroimaging research by offering a potential pathway to improve the clinical applicability of deep learning models.
Feasibility of Stereo EEG Based Brain Computer Interfacing in An Adult and Pediatric Cohort
Authors: Jensen Michael A , Schalk Gerwin , Ince Nuri , Hermes Dora , Brunner Peter , Miller Kai J
Published: June 2024

Introduction

Stereoelectroencephalography (sEEG) is a mesoscale intracranial monitoring method which records from the brain volumetrically with depth electrodes. Implementation of sEEG in BCI has not been well-described across a diverse patient cohort.

Methods

Across eighteen subjects, channels with high frequency broadband (HFB, 65-115Hz) power increases during hand, tongue, or foot movements during a motor screening task were provided real-time feedback based on these HFB power changes to control a cursor on a screen.

Results

Seventeen subjects established successful control of the overt motor BCI, but only nine were able to control imagery BCI with≥80% accuracy. In successful imagery BCI, HFB power in the two target conditions separated into distinct subpopulations, which appear to engage unique subnetworks of the motor cortex compared to cued movement or imagery alone.

Conclusion

sEEG-based motor BCI utilizing overt movement and kinesthetic imagery is robust across patient ages and cortical regions with substantial differences in learning proficiency between real or imagined movement.
DrosophilaLate Embryonic through Late Larval Stage Body Wall Dissection: Dissection Tools and Techniques
Authors: Ashley James , Carrillo Robert A.
Published: June 2024

One of the challenges of studying synaptic structure and function is accessibility. Some of the earliest readily identifiable and accessible synapses were from the frog and various arthropods. To address questions regarding mechanisms that underlie synaptic development and function, genetically tractable systems were required, and researchers turned to theDrosophila melanogasterembryonic/larval neuromuscular preparation.Drosophilaembryos are transparent and can be labeled with antibodies or probes and imaged in whole-mount preparation for structural analysis. Embryos can also be dissected to visualize the entire body wall musculature as well as finer details including live protein trafficking and protein–protein interactions. Whereas younger dissected embryos can be mounted directly onto charged slides, more mature embryos and larvae develop a cuticle that impedes this adherence, so different techniques must be applied. In this protocol, we detail how to manufacture dissection tools and collect embryos, and discuss the individual steps of dissecting late-stage embryos, early first-instar larvae, and late-stage third-instar larvae.
Immunohistochemistry and Morphometric Analysis ofDrosophilaLarval Body Wall Neuromuscular Junction Preparations
Authors: Ashley James , Carrillo Robert A.
Published: June 2024

TheDrosophilaneuromuscular junction (NMJ) is an excellent model for studying vertebrate glutamatergic synapses. Researchers have uncovered fundamental mechanisms at the fly NMJ that are conserved in higher-order organisms. To gain molecular and structural insight into these and other structures, immunolabeling is invaluable. In this protocol, we describe how to use immunolabeling to visualize embryonic/larval presynaptic and postsynaptic structures at the NMJ. We also include details about amplification of weak immunohistochemistry signals and how to use these signals to quantify synaptic growth via bouton counting. Boutons are bead-like structures at motor axon terminals that house synapses, and the number of boutons reflects the size of the NMJ. We also describe how to identify the different bouton types.
Few-body bound topological and flat-band states in a Creutz ladder
Authors: Pelegrí G. , Flannigan S. , Daley A. J.
Published: June 2024

We investigate the properties of a few interacting bosons in a Creutz ladder, which has become a standard model for topological systems, and which can be realized in experiments with cold atoms in optical lattices. At the single-particle level, this system may exhibit a completely flat energy landscape with nontrivial topological properties. In this scenario, we identify topological two-body edge states resulting from the bonding of single-particle edge and flat-band states. We also explore the formation of two- and three-body bound states in the strongly interacting limit, and we show how these quasiparticles can be engineered to replicate the flat-band and topological features of the original single-particle model. Furthermore, we show that in this geometry perfect Aharonov-Bohm caging of two-body bound states may occur for arbitrary interaction strengths, and we provide numerical evidence that the main features of this effect are preserved in an interacting many-body scenario resulting in many-body Aharonov-Bohm caging.

Published by the American Physical Society
2024
Ultrahigh resolution x-ray Thomson scattering measurements at the European X-ray Free Electron Laser
Authors: Gawne Thomas , Moldabekov Zhandos A. , Humphries Oliver S. , Appel Karen , Baehtz Carsten , Bouffetier Victorien , Brambrink Erik , Cangi Attila , Göde Sebastian , Konôpková Zuzana , Makita Mikako , Mishchenko Mikhail , Nakatsutsumi Motoaki , Ramakrishna Kushal , Randolph Lisa , Schwalbe Sebastian , Vorberger Jan , Wollenweber Lennart , Zastrau Ulf , Dornheim Tobias , Preston Thomas R.
Published: June 2024

Using an ultrahigh resolution (ΔE∼0.1eV) setup to measure electronic features in x-ray Thomson scattering (XRTS) experiments at the European XFEL in Germany, we have studied the collective plasmon excitation in aluminium at ambient conditions, which we can measure very accurately even at low momentum transfers. As a result, we can resolve previously reported discrepancies between time-dependent density functional theory simulations and experimental observations. The demonstrated capability for high-resolution XRTS measurements will be a game changer for the diagnosis of experiments with matter under extreme densities, temperatures, and pressures, and unlock the full potential of state-of-the-art x-ray free electron laser (XFEL) facilities to study planetary interior conditions, to understand inertial confinement fusion applications, and for material science and discovery.

Published by the American Physical Society
2024
Emulating
ab initio
computations of infinite nucleonic matter
Authors: Jiang W. G. , Forssén C. , Djärv T. , Hagen G.
Published: June 2024

We construct efficient emulators for the computation of the infinite nuclear matter equation of state. These emulators are based on the subspace-projected coupled-cluster method for which we here develop a new algorithm called small-batch voting to eliminate spurious states that might appear when emulating quantum many-body methods based on a non-Hermitian Hamiltonian. The efficiency and accuracy of these emulators facilitate a rigorous statistical analysis within which we explore nuclear matter predictions for >106 different parametrizations of a chiral interaction model with explicit Δ-isobars at next-to-next-to leading order. Constrained by nucleon-nucleon scattering phase shifts and bound-state observables of light nuclei up to He4, we use history matching to identify nonimplausible domains for the low-energy coupling constants of the chiral interaction. Within these domains we perform a Bayesian analysis using sampling and importance resampling with different likelihood calibrations and study correlations between interaction parameters, calibration observables in light nuclei, and nuclear matter saturation properties.

Published by the American Physical Society
2024
Bottomonium suppression from the three-loop QCD potential
Authors: Brambilla Nora , Magorsch Tom , Strickland Michael , Vairo Antonio , Vander Griend Peter
Published: June 2024

We compute the suppression of bottomonium in the quark-gluon plasma using the three-loop QCD static potential. The potential describes the spin-averaged bottomonium spectrum below threshold with a less than 1% error. Within potential nonrelativistic quantum chromodynamics and an open quantum systems framework, we compute the evolution of the bottomonium density matrix. The values of the quarkonium transport coefficients are obtained from lattice QCD measurements of the bottomonium in-medium width and thermal mass shift; we additionally include for the first time a vacuum contribution to the dispersive coefficient γ. Using the three-loop potential and the values of the heavy quarkonium transport coefficients, we find that the resulting bottomonium nuclear modification factor is consistent with experimental observations, while at the same time reproducing the lattice measurements of the in-medium width.

Published by the American Physical Society
2024
On
Higgs+jet
production at next-to-leading power accuracy
Authors: Pal Sourav , Seth Satyajit
Published: June 2024

We present computation of the next-to-leading power corrections for Higgs plus one jet production in a hadron collider via gluon fusion channel. Shifting of spinors in the helicity amplitudes without additional radiation captures the leading next-to-soft radiative behavior and makes the calculation tractable. We establish the connection between the shifted dipole spinors and the color ordered radiative amplitudes. We find that next-to-maximal helicity violating amplitudes do not play a role in this correction. Compact analytic expressions of next-to-leading power leading logarithms coming from different helicity configurations are shown.

Published by the American Physical Society
2024
Probing bosonic overdensities with optomechanical sensing
Authors: Slattery Katherine , Wijewardhana Rohana , Eby Joshua , Street Lauren
Published: June 2024

Previous work has shown that optomechanical force sensing can be used for efficient detection of ultralight (sub-eV) dark matter candidates. We propose to extend the reach of this method to the search for ultralight dark matter in gravitationally bound configurations in the Milky Way. We consider three scenarios, each strongly motivated by previous studies: boson stars traveling in the galaxy with virial velocity; a bosonic halo centered around the Sun (a “solar halo”); and a bosonic halo centered around the Earth. For each case, we consider bound states composed of either scalar particles with a Yukawa coupling, or vector particles coupled to baryon minus lepton number charge. Accounting for all experimental constraints on coupling strength, we estimate the sensitivity reach of an optomechanical sensor search. We conclude that, although boson star encounters with Earth would be too infrequent to be detected in the relevant parameter space, current optomechanical force sensing technologies provide promising search capabilities for solar or Earth-bound halos.

Published by the American Physical Society
2024
Λb→Pℓ
factorization in QCD
Authors: Li Lei-Yi , Lü Cai-Dian , Wang Jin , Wei Yan-Bing
Published: June 2024

We calculate the form factors for the baryon number violation processes of a heavy-flavor baryon decaying into a pseudoscalar meson and a lepton. In the framework of the Standard Model effective field theory, the leptoquark operators at the bottom quark scale, whose matrix elements define the form factors, are derived by integrating out the high energy physics. Under the quantum chromodynamics (QCD) factorization approach, the form factors of the baryon number violation processes at leading power can be factorized into the convolution of the long-distance hadron wave functions as well as the short-distance hard and jet functions representing the hard scale and hard-collinear scale effects, separately. Based on measurements of the baryon number violation processes by LHCb, we further impose constraints on the new physics constants of leptoquark operators.

Published by the American Physical Society
2024
A composite indicator-based energy-efficiency benchmarking for residential buildings
Authors: Gupta Gyanesh , Mathur Sanjay , Mathur Jyotirmay
Published: June 2024

Purpose

Buildings require significant energy, and meeting energy demands is becoming exceedingly challenging. Energy demand reduction goals are now prioritised as the demand is rising. Energy-saving improvements and opportunities can be provided if enough information is provided through building energy benchmarking. The study focuses on developing a framework for benchmarking the energy efficiency of residential buildings.

Design/methodology/approach

This study applied multiple linear regression analysis to analyse the energy use of residential buildings and establish energy benchmarks. Over 2000 data from Jaipur city were surveyed, and regression analysis was done on 1527 datasets after fundamental statistical analysis. The research considered the significant energy used by household appliances and placed a greater emphasis on end-use appliances.

Findings

The comparison of the developed framework with the standard rating plan was carried out to evaluate the accuracy of the benchmarks. The validation of the model determines the gap between the predicted and actual value of the building energy. The recommendations were made for organisations and policymakers to employ multiple or combinations of methods to assess the reliability of the developed benchmark framework.

Practical implications

Policymakers may promote awareness campaigns encouraging homeowners to consume less energy and make buildings more energy efficient. This technique may be applied worldwide with the proper and suitable adjustments and information provided.

Originality/value

To our knowledge, India needs residential building energy benchmarking framework studies. In addition, a new framework based on Composite Indicators was implemented to overcome the scepticism of the EPI/BPI or floor-based approach held by several academics and to offer energy benchmarking for residential buildings.
“Nudging towards excellence: Harnessing behavioral insights for organizational learning”
Authors: Arya Jyoti , Hindolia Anand
Published: June 2024

Purpose

In dynamic business environments, organizations must constantly adapt and learn. Nudging, a concept from behavioral economics, offers a novel approach to influence organizational behavior and learning. This article explores the integration of nudging within organizational learning, drawing from Thaler and Sunstein’s work and organizational learning theories. Also, To investigate nudging’s role in organizational learning and propose a practical nudging framework, while addressing ethical considerations.

Design/methodology/approach

The article combines theoretical insights from behavioral economics (Thaler and Sunstein; Kahneman) with organizational learning theories (Argyris and Schön). It discusses real-world nudging applications, like Google's health initiatives, and examines the ethical aspects of workplace nudging.

Findings

Nudging effectively influences organizational decisions and strategies by targeting rapid cognitive processes. It finds application in training, performance management, and decision-making, with a critical focus on ethical implications, especially regarding autonomy and non-manipulation.

Research limitations/implications

This study highlights the potential of behavioral economics in reshaping organizational learning, emphasizing the importance of ethical application in developing adaptive, learning-focused organizational cultures.

Originality/value

Nudging offers a promising method for enhancing organizational learning. Applied ethically, it can improve workforce engagement, performance, and adaptability. Future research should focus on nudging's long-term organizational impacts and ethical boundaries.
Tensions in data use for mission: academic data within holistic education
Authors: Jones Mary F. , Dallavis Julie
Published: June 2024

Purpose

Research shows data-informed leadership matters for school improvement and student achievement, but less is known about what motivates leaders’ data use toward such outcomes, particularly in the Catholic school context.

Design/methodology/approach

This qualitative interview study uses interview (n = 23) data from a sample of Catholic school leaders to unpack how they conceptualize data, the motivations encouraging their data use and the challenges inhibiting data routines.

Findings

Catholic school leaders largely shared a narrow definition of data as quantitative, standardized achievement data, were motivated by a moral imperative to meet students’ needs and faced several common challenges, including time constraints, uncertainty in measurement, limited capacity and resources and issues of turnover at the classroom and school levels.

Practical implications

School leaders can assuage tension around data by broadening the scope of measures and appealing to teachers’ sense of personal responsibility and commitment to students.

Originality/value

These findings extend the research in three ways. They bring to light an important tension between data-informed practice and a whole child approach to education, highlight the possibility of motivating data use through conscience rather than compliance and provide insight into data perceptions in private schools, an understudied context in the literature.
Social media’s sway: how social comparison on social media stimulates impulse travelling; serial mediation study on Indian millennials tourists
Authors: Kumar Satinder , Kumar Sandeep
Published: June 2024

Purpose

The study explores the impact of social media-induced social comparison on impulse travelling, drawing upon social comparison theory. It thoroughly examines the intermediary functions of fear of missing out (FoMO) and compulsive use of social media, alongside exploring the moderating impacts of self-esteem and self-control within this dynamic process.

Design/methodology/approach

To meet the objective, we conducted a survey of 382 social media users among Indian millennial tourists. The analysis has been done using SPSS (AMOS 24) and Process macro (model 1) for moderation effect. Purposive and snowball sampling techniques have been employed for data collection.

Findings

The results indicate a positive influence of social comparison on impulsive travel. Additionally, the findings suggest that FoMO and the compulsive use of social media serve as serial mediations on the link between social comparison and impulse travelling. Moreover, self-esteem has shown a negatively significant relationship between social comparison and FoMO. Furthermore, self-control has also been found to have a negatively significant effect on the relationship between FoMO and the compulsive use of social media.

Practical implications

The study’s findings offer valuable guidance for destination administrators. It suggests that administrators should refrain from engaging in aggressive and overly tailored marketing tactics. Instead, they should focus on sharing real and authentic stories that resonate with travellers, and administrators can mitigate the effects of social comparison and discourage impulsive travelling.

Originality/value

This study delves into an unexplored realm in digital marketing literature, shedding light on how social comparison on social media influences the impulsive travelling of Indian millennial tourists. This study is an inaugural attempt to formulate a theoretical framework within the scope of the tourism sector.
The role of AI agents in fostering inclusivity for HEIs’ students with special needs against backdrops of the accreditation trend
Authors: Chedrawi Charbel , Kazoun Nahil , Kokkinaki Angelika
Published: June 2024

Purpose

This paper aims to study the role of artificial intelligence (AI) agents in creating a climate of inclusion for people with special needs in the higher education sector (HES).

Design/methodology/approach

A qualitative methodology is used in this research that is mainly based on semistructured interviews conducted with the top ten universities in Lebanon with deans, information technology managers, professors and administrative officers.

Findings

This paper highlights findings related to the current status of the higher education institutions (HEIs) in Lebanon vis-à-vis their accreditation and quality assurance processes in accommodating and creating a climate of inclusion for people with special needs. The results show the important role of AI agents in aiding HEI in creating such a climate of inclusion for people with special needs.

Originality/value

The study sheds light on existing gaps in the literature related to creating a climate of inclusion for people with special needs in HEI. Additionally, there is yet a lack of research that focuses on the role of AI technology in general and AI agents in particular in fostering a climate of inclusion for people with special needs within the HES.
The mediatory role of the environmental performance function within the lean-green manufacturing sustainability complex
Authors: Machingura Tinotenda , Adetunji Olufemi , Maware Catherine
Published: June 2024

Purpose

The objective of the study is to explore the mediatory role of the environmental performance of organisations on their economic and social performances. It demonstrates that implementing environmental management techniques should not only be done to comply with environmental regulations, but also as a means of improving social and economic performance.

Design/methodology/approach

The data were gathered from the manufacturing industry of Zimbabwe, and 302 useable responses were received. Data analysis was performed through structural equation modelling (SEM) using SMART PLS 3.

Findings

Improvement in environmental performance led to improvements in both social and economic performances. Also, environmental performance contributes the greatest total effect; hence, it deserves attention, not only for compliance but also for economic reasons.

Originality/value

Our goal is to quantify the extent to which environmental performance might improve the social and, more importantly, the economic performance of organisations. The study also explores the relative importance and performance of lean manufacturing (LM), green manufacturing (GM), social performance and environmental performance for purposes of prioritisation of organisational improvement initiatives.
Big rodents disperse small seeds and spores in Neotropical wetlands
Authors: Hoffmann Pedro Henrique de Oliveira , Adolfo Andressa , Green Andy J. , Stenert Cristina , Silva Giliandro Gonçalves , Weber Vinicius , Maltchik Leonardo
Published: June 2024

The role of large frugivores in the dispersal of tropical trees has been well‐studied, whereas the importance of the world's largest rodents for plant dispersal has previously been ignored. We studied plant dispersal by gut passage (endozoochory) in Neotropical wetlands by the largest extant rodent, the capybara Hydrochoerus hydrochaeris. We compared it with another of the world's 10 largest rodents, the nutria or coypu Myocastor coypus.

We collected 96 faecal samples (50 capybara, 46 nutria) from 10 sites within the Taim Ramsar site in southern Brazil, and extracted intact propagules from 10 g subsamples. Propagules from 27 plant taxa (24 angiosperms, and three aquatic ferns) were recovered, representing 13 plant families. Whole Spirodela (duckweed) plants were dispersed. Seeds from 14 angiosperm taxa were germinated in the laboratory.

Taxonomic composition of propagules was significantly different for the two mammals, but propagule size was not. Capybara dispersed more terrestrial propagules per sample, and nutrias more aquatic propagules. When total faecal production was taken into account, an estimated 1025 propagules (including 133 fern spores) were dispersed by each capybara per day, compared with 691 propagules for nutrias (including 566 fern spores). Capybaras have larger home ranges and likely dispersed plants over a greater distance.

Synthesis: This is the first demonstration that rodents disperse aquatic pteridophytes as well as flowering plants. Our results suggest that capybaras and nutrias play important, complementary roles in dispersing a variety of aquatic and terrestrial plant species within Neotropical wetlands. Our study indicates that the role of herbivorous mammals as vectors of plants with small seeds and non‐fleshy fruits has been overlooked in the neotropics and that defaunation of large herbivores can have negative consequences, in a manner similar to that previously highlighted for frugivores.
Isolation and characterization of a phage collection against Pseudomonas putida
Authors: Brauer Age , Rosendahl Sirli , Kängsep Anu , Lewańczyk Alicja Cecylia , Rikberg Roger , Hõrak Rita , Tamman Hedvig
Published: June 2024

The environmental bacterium, Pseudomonas putida, possesses a broad spectrum of metabolic pathways. This makes it highly promising for use in biotechnological production as a cell factory, as well as in bioremediation strategies to degrade various aromatic pollutants. For P. putida to flourish in its environment, it must withstand the continuous threats posed by bacteriophages. Interestingly, until now, only a handful of phages have been isolated for the commonly used laboratory strain, P. putida KT2440, and no phage defence mechanisms have been characterized. In this study, we present a new Collection of Environmental P. putida Phages from Estonia, or CEPEST. This collection comprises 67 double‐stranded DNA phages, which belong to 22 phage species and 9 phage genera. Our findings reveal that most phages in the CEPEST collection are more infectious at lower temperatures, have a narrow host range, and require an intact lipopolysaccharide for P. putida infection. Furthermore, we show that cryptic prophages present in the P. putida chromosome provide strong protection against the infection of many phages. However, the chromosomal toxin–antitoxin systems do not play a role in the phage defence of P. putida. This research provides valuable insights into the interactions between P. putida and bacteriophages, which could have significant implications for biotechnological and environmental applications.
The Case for a Scottish Clarity Act
Authors: Coulter Steph
Published: June 2024

The recent political difficulties faced by the Scottish National Party have made the prospect of a future Scottish independence referendum less salient in both Westminster and Holyrood. However, whilst the short‐term prospects for the independence movement look challenging, the long‐term question of Scotland's future within the UK remains an important area of analysis for constitutional policy makers and scholars alike. This article seeks to add to the debate on the future of the UK's territorial constitution by arguing for the passage of a ‘Scottish Clarity Act’ by the UK government, which would outline the rules about when and how a future Scottish independence referendum should be conducted. Using the Canadian Clarity Act 2000 as an international example of the constitutionalising of secession, it argues that there are numerous benefits associated with providing greater clarity on Scotland's constitutional future, including the dampening of polarisation, the mitigation of constitutional crisis, the improvement of governance and the bolstering of democracy in the UK.
Proliferation of probiotics and antioxidant effects of functional oligosaccharides added in fermented dairy product
Authors: Liu Lingxiao , Yang Daqiao , Liu Hualan , Guo Wenzhu , Jiang Zhumao , Han Qingdian , Liu Yunguo
Published: June 2024

To obtain functional fermented dairy products with strong probiotic proliferation and high antioxidant ability, the proliferation ability of oligosaccharides on probiotics and their DPPH radical scavenging ability were studied. Key functional oligosaccharides (galactooligosaccharide and galactomannan oligosaccharide) and probiotics (Bifidobacterium bifidum and Lactobacillus acidophilus) were selected. The orthogonal experimental design of L9(34) was employed to study the optimal process, which was adding 5 g/L galactomannan oligosaccharide and 5 g/L galactooligosaccharide in reconstituted milk, inoculating 1% Streptococcus thermophilus, 1% Lactobacillus bulgaricus and 1% probiotics (B. bifidum and L. acidophilus = 2:1) and fermenting for 6 h. This work is important for preparing functional fermented dairy products with a high content of probiotics and strong antioxidant capacity.