bluuebunny/crossref_metadata_2025 huggingface dataset:
PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration
Authors: Wieder Cecilia , Cooke Juliette , Frainay Clement , Poupin Nathalie , Bowler Russell , Jourdan Fabien , Kechris Katerina J. , Lai Rachel PJ , Ebbels Timothy
Published: January 2024

As terabytes of multi-omics data are being generated, there is an ever-increasing need for methods facilitating the integration and interpretation of such data. Current multi-omics integration methods typically output lists, clusters, or subnetworks of molecules related to an outcome. Even with expert domain knowledge, discerning the biological processes involved is a time-consuming activity. Here we propose PathIntegrate, a method for integrating multi-omics datasets based on pathways, designed to exploit knowledge of biological systems and thus provide interpretable models for such studies. PathIntegrate employs single-sample pathway analysis to transform multi-omics datasets from the molecular to the pathway-level, and applies a predictive single-view or multi-view model to integrate the data. Model outputs include multi-omics pathways ranked by their contribution to the outcome prediction, the contribution of each omics layer, and the importance of each molecule in a pathway. Using semi-synthetic data we demonstrate the benefit of grouping molecules into pathways to detect signals in low signal-to-noise scenarios, as well as the ability of PathIntegrate to precisely identify important pathways at low effect sizes. Finally, using COPD and COVID-19 data we showcase how PathIntegrate enables convenient integration and interpretation of complex high-dimensional multi-omics datasets. The PathIntegrate Python package is available athttps://github.com/cwieder/PathIntegrate.

Author summary

Omics data, which provides a readout of the levels of molecules such as genes, proteins, and metabolites in a sample, is frequently generated to study biological processes and perturbations within an organism. Combining multiple omics data types can provide a more comprehensive understanding of the underlying biology, making it possible to piece together how different molecules interact. There exist many software packages designed to integrate multi-omics data, but interpreting the resulting outputs remains a challenge. Placing molecules into the context of biological pathways enables us to better understand their collective functions and understand how they may contribute to the condition under study. We have developed PathIntegrate, a pathway-based multi-omics integration tool which helps integrate and interpret multi-omics data in a single step using machine learning. By integrating data at the pathway rather than the molecular level, the relationships between molecules in pathways can be strengthened and more readily identified. PathIntegrate is demonstrated on Chronic Obstructive Pulmonary Disease and COVID-19 metabolomics, proteomics, and transcriptomics datasets, showcasing its ability to efficiently extract perturbed multi-omics pathways from large-scale datasets.
Peptidoglycan fragment release and NOD activation by commensalNeisseriaspecies from humans and other animals
Authors: Harris-Jones Tiffany N. , Chan Jia Mun , Hackett Kathleen T. , Weyand Nathan J. , Schaub Ryan E. , Dillard Joseph P.
Published: January 2024

Neisseria gonorrhoeae, a human restricted pathogen, releases inflammatory peptidoglycan (PG) fragments that contribute to the pathophysiology of pelvic inflammatory disease. The genusNeisseriais also home to multiple species of human- or animal-associatedNeisseriathat form part of the normal microbiota. Here we characterized PG release from the human-associated nonpathogenic speciesN. lactamicaandN. mucosaand animal-associatedNeisseriafrom macaques and wild mice. AnN. mucosastrain and anN. lactamicastrain were found to release limited amounts of the pro-inflammatory monomeric PG fragments. However, a single amino acid difference in the PG fragment permease AmpG resulted in increased PG fragment release in a secondN. lactamicastrain examined.Neisseriaisolated from macaques also showed significant release of PG monomers. The mouse colonizerN. musculiexhibited PG fragment release similar to that seen inN. gonorrhoeaewith PG monomers being the predominant fragments released. All the human-associated species were able to stimulate NOD1 and NOD2 responses.N. musculiwas a poor inducer of mouse NOD1, butldcAmutation increased this response. The ability to genetically manipulateN. musculiand examine effects of different PG fragments or differing amounts of PG fragments during mouse colonization will lead to a better understanding of the roles of PG inNeisseriainfections. Overall, we found that only some nonpathogenicNeisseriahave diminished release of pro-inflammatory PG fragments, and there are differences even within a species as to types and amounts of PG fragments released.
Growth-induced collective bending and kinetic trapping of cytoskeletal filaments
Authors: Banerjee Deb Sankar , Freedman Simon L. , Murrell Michael P. , Banerjee Shiladitya
Published: January 2024

Growth and turnover of actin filaments play a crucial role in the construction and maintenance of actin networks within cells. Actin filament growth occurs within limited space and finite subunit resources in the actin cortex. To understand how filament growth shapes the emergent architecture of actin networks, we developed a minimal agent-based model coupling filament mechanics and growth in a limiting subunit pool. We find that rapid filament growth induces kinetic trapping of highly bent actin filaments. Such collective bending patterns are long-lived, organized around nematic defects, and arises from competition between filament polymerization and bending elasticity. The stability of nematic defects and the extent of kinetic trapping are amplified by an increase in the abundance of the actin pool and by crosslinking the network. These findings suggest that kinetic trapping is a robust consequence of growth in crowded environments, providing a route to program shape memory in actin networks.
A new role for IFRD1 in regulation of ER stress in bladder epithelial homeostasis
Authors: Fashemi Bisiayo E. , Rougeau Amala K. , Salazar Arnold M. , Bark Steven J. , Chappidi Rayvanth , Brown Jeffrey W. , Cho Charles J. , Mills Jason C. , Mysorekar Indira U.
Published: January 2024

A healthy bladder requires the homeostatic maintenance of and rapid regeneration of urothelium upon stress/injury/infection. Several factors have been identified to play important roles in urothelial development, injury and disease response, however, little is known about urothelial regulation at homeostasis. Here, we identify a new role for IFRD1, a stress-induced gene that has recently been demonstrated to play a critical role in adult tissue proliferation and regeneration, in maintenance of urothelial function/ homeostasis in a mouse model. We show that the mouse bladder expresses IFRD1 at homeostasis and its loss alters the global transcriptome of the bladder with significant accumulation of cellular organelles including multivesicular bodies with undigested cargo, lysosomes and mitochondria. We demonstrate that IFRD1 interacts with several mRNA-translation-regulating factors in human urothelial cells and that the urothelium ofIfrd1−/−mice reveal decreased global translation and enhanced endoplasmic reticulum (ER) stress response.Ifrd1−/−bladders have activation of the unfolded protein response (UPR) pathway, specifically the PERK arm, with a concomitant increase in oxidative stress and spontaneous exfoliation of urothelial cells. Further, we show that such increase in cell shedding is associated with a compensatory proliferation of the basal cells but impaired regeneration of superficial cells. Finally, we show that upon loss of IFRD1, mice display aberrant voiding behavior. Thus, we propose that IFRD1 is at the center of many crucial cellular pathways that work together to maintain urothelial homeostasis, highlighting its importance as a target for diagnosis and/or therapy in bladder conditions.
MRI-Targeted Prostate Biopsy Introduces Grade Inflation and Overtreatment
Authors: Batouche Abderrahim Oussama , Czeizler Eugen , Lehto Timo-Pekka , Erickson Andrew , Shadbahr Tolou , Laajala Teemu Daniel , Pohjonen Joona , Vickers Andrew Julian , Mirtti Tuomas , Rannikko Antti Sakari
Published: January 2024

Purpose

The use of MRI-targeted biopsies has led to lower detection of Gleason Grade Group 1 (GG1) prostate cancer and increased detection of GG2 disease. Although this finding is generally attributed to improved sensitivity and specificity of MRI for aggressive cancers, it might also be explained by grade inflation. Our objective was to determine the likelihood of definitive treatment and risk of post-treatment recurrence for patients with GG2 cancer diagnosed using targeted biopsies relative to men with GG1 cancer diagnosed using systematic biopsies.

Methods

We performed a retrospective study on a large tertiary centre registry (HUS Acamedic Datalake) to retrieve data on prostate cancer diagnosis, treatment, and cancer recurrence. We included patients with either GG1 with systematic biopsies (3317 men) or GG2 with targeted biopsies (554 men) from 1993 to 2019. We assessed the risk of curative treatment and recurrence after treatment. Kaplan-Meier survival curves were computed to assess treatment- and recurrence-free survival. Cox proportional hazards regression analysis was performed to assess the risk of posttreatment recurrence.

Results

Patients with systematic biopsy detected GG1 cancer had a significantly longer median time-to-treatment (31 months) than those with targeted biopsy detected GG2 cancer (4 months, p<0.0001). The risk of recurrence after curative treatment was similar between groups with the upper bound of 95% CI, excluding an important difference (HR: 0.94, 95% CI [0.71-1.25], p=0.7).

Conclusion

GG2 cancers detected by MRI-targeted biopsy are treated more aggressively than GG1 cancers detected by systematic biopsy, despite having similar oncologic risk. To prevent further overtreatment related to the MRI pathway, treatment guidelines from the pre-MRI era need to be updated to consider changes in the diagnostic pathway.
PD-L1+diffuse large B-cell lymphoma with extremely high mutational burden and microsatellite instability due to acquiredPMS2mutation
Authors: Allbee Andrew W. , Gerson James , Yang Guang , Bagg Adam
Published: January 2024

We present a unique case of a single patient presenting with two mutationally distinct, PD-L1+diffuse large B-cell lymphomas (DLBCLs). One of these DLBCLs demonstrated exceptionally high mutational burden (eight disease-associated variants and 41 variants of undetermined significance) with microsatellite instability (MSI) and an acquiredPMS2mutation with loss of PMS2 protein expression, detected postchemotherapy. This report, while highlighting the extent of possible tumor heterogeneity across separate clonal expansions as well as possible syndromic B-cell neoplasia, supports the notion that, although rare, PD-L1 expression and associated states permissive of high mutational burden (such as mismatch repair gene loss of function/MSI) should be more routinely considered in DLBCLs. Appropriate testing may be predictive of outcome and inform the utility of targeted therapy in these genetically diverse and historically treatment-refractory malignancies.
The diagnostic odyssey of a patient with dihydropyrimidinase deficiency: a case report and review of the literature
Authors: Albokhari Daniah , Alharbi Ohood , Blesson Alyssa , Jain Mahim
Published: January 2024

Dihydropyrimidinase (DHP) deficiency is an autosomal recessive metabolic disorder caused by biallelic pathogenic variants ofDPYS. Patients with DHP deficiency exhibit a broad spectrum of phenotypes, ranging from severe neurological and gastrointestinal involvement to cases with no apparent symptoms. The biochemical diagnosis of DHP deficiency is based on the detection of a significant amount of dihydropyrimidines in urine, plasma, and cerebrospinal fluid samples. Molecular genetic testing, specifically the identification of biallelic pathogenic variants inDPYS, has proven instrumental in confirming the diagnosis and facilitating family studies. This case study documents the diagnostic journey of an 18-yr-old patient with DHP deficiency, highlighting features at the severe end of the clinical spectrum. Notably, our patient exhibited previously unreported skeletal features that positively responded to bisphosphonate treatment, contributing valuable insights to the clinical characterization of DHP deficiency. Additionally, a novelDPYSvariant was identified and confirmed pathogenicity through metabolic testing, further expanding the variant spectrum of the gene. Our case emphasizes the importance of a comprehensive diagnostic approach using genetic sequencing and metabolic testing for accurate diagnosis.
Constraining MeV-scale axionlike particles with Fermi-LAT observations of SN 2023ixf
Authors: Ravensburg Eike , Carenza Pierluca , Eckner Christopher , Goobar Ariel
Published: January 2024

The Fermi-LAT observations of SN 2023ixf, a type II supernova in the nearby Pinwheel Galaxy, Messier 101 (M101), presents us with an excellent opportunity to constrain MeV-scale axionlike particles (ALPs). By examining the photon decay signature from heavy ALPs that could be produced in the explosion, the existing constraints on the ALP-photon coupling can be improved, under optimistic assumptions, by up to a factor of ∼2 for masses ma≲3  MeV. Under very conservative assumptions, we find a bound that is slightly weaker than the existing ones for ma≲0.5  MeV. The exact reach of these searches depends mostly on properties of the SN progenitor. This study demonstrates the relevance of core-collapse supernovae, also beyond the Magellanic Clouds, as probes of fundamental physics.

Published by the American Physical Society
2024
Intermediate defect groups, polarization pairs, and noninvertible duality defects
Authors: Lawrie Craig , Yu Xingyang , Zhang Hao Y.
Published: January 2024

Within the framework of relative and absolute quantum field theories (QFTs), we present a general formalism for understanding polarizations of the intermediate defect group and constructing noninvertible duality defects in theories in 2k spacetime dimensions with self-dual gauge fields. We introduce the polarization pair, which fully specifies absolute QFTs as far as their (k−1)-form defect groups are concerned, including their (k−1)-form symmetries, global structures (including discrete θ-angle), and local counterterms. Using the associated symmetry topological field theory (TFT), we show that the polarization pair is capable of succinctly describing topological manipulations, e.g., gauging (k−1)-form global symmetries and stacking counterterms, of absolute QFTs. Furthermore, automorphisms of the (k−1)-form charge lattice naturally act on polarization pairs via their action on the defect group; they can be viewed as dualities between absolute QFTs descending from the same relative QFT. Using this formalism, we present a prescription for building noninvertible symmetries of absolute QFTs. A large class of known examples, e.g., noninvertible defects in 4D N=4 super-Yang-Mills, can be reformulated via this prescription. As another class of examples, we identify and investigate in detail a family of noninvertible duality defects in 6D superconformal field theories (SCFTs), including from the perspective of the symmetry TFT derived from type IIB string theory.

Published by the American Physical Society
2024
Coarse-graining of perplexity for the spatial distribution of molecules
Authors: Xu Lili , Zhang Chi , Oyama Soho , Machida Manabu , Kahyo Tomoaki , Setou Mitsutoshi
Published: January 2024

Biological tissue consists of various molecules. Instead of focusing on a particular molecule, we consider the Shannon entropy which is calculated from the abundance of different molecules at each spot in the tissue. The spatial distribution of the Shannon entropy is of interest. In this paper, we first obtain the heat map of perplexity, whose logarithm is the entropy. To characterize the spatial variety of molecules, we propose a scalar k that is concerned with the coarse-graining of the perplexity heat map. To verify the usefulness of the number, experiments with mass spectrometry imaging were performed for mouse kidneys. We found that k has large values in the renal pelvis area, cortex area, veins, and arteries in the mouse kidney, whereas fractal dimensions fail to distinguish those regions.

Published by the American Physical Society
2024
Realizing Symmetry-Breaking Architectures in Soap Films
Authors: Kaul Nidhi , Bergamasco Luca , Song Hongwei , Varkevisser Thijs , Amati Agnese , Falciani Gabriele , van Rijn Cees J. M. , Chiavazzo Eliodoro , Sen Indraneel , Bonnet Sylvestre , Hammarström Leif
Published: January 2024

We show here that soap films—typically expected to host symmetric molecular arrangements—can be constructed with differing opposite surfaces, breaking their symmetry, and making them reminiscent of functional biological motifs found in nature. Using fluorescent molecular probes as dopants on different sides of the film, resonance energy transfer could be employed to confirm the lack of symmetry, which was found to persist on timescales of several minutes. Further, a theoretical analysis of the main transport phenomena involved yielded good agreement with the experimental observations.

Published by the American Physical Society
2024
Ensemble-learning error mitigation for variational quantum shallow-circuit classifiers
Authors: Li Qingyu , Huang Yuhan , Hou Xiaokai , Li Ying , Wang Xiaoting , Bayat Abolfazl
Published: January 2024

Classification is one of the main applications of supervised learning. Recent advancements in developing quantum computers have opened a new possibility for machine learning on such machines. Due to the noisy performance of near-term quantum computers, error mitigation techniques are essential for extracting meaningful data from noisy raw experimental measurements. Here, we propose two ensemble-learning error mitigation methods, namely, bootstrap aggregating and adaptive boosting, which can significantly enhance the performance of variational quantum classifiers for both classical and quantum datasets. The idea is to combine several weak classifiers, each implemented on a shallow noisy quantum circuit, to make a strong one with high accuracy. While both of our protocols substantially outperform error-mitigated primitive classifiers, the adaptive boosting shows better performance than the bootstrap aggregating. The protocols have been exemplified for classical handwriting digits as well as quantum phase discrimination of a symmetry-protected topological Hamiltonian, in which we observe a significant improvement in accuracy. Our ensemble-learning methods provide a systematic way of utilizing shallow circuits to solve complex classification problems.

Published by the American Physical Society
2024
Classical shadows for quantum process tomography on near-term quantum computers
Authors: Levy Ryan , Luo Di , Clark Bryan K.
Published: January 2024

Quantum process tomography is a powerful tool for understanding quantum channels and characterizing the properties of quantum devices. Inspired by recent advances using classical shadows in quantum state tomography [H.-Y. Huang, R. Kueng, and J. Preskill, .], we have developed ShadowQPT, a classical shadow method for quantum process tomography. We introduce two related formulations with and without ancilla qubits. ShadowQPT stochastically reconstructs the Choi matrix of the device allowing for an classical evaluation of the device on arbitrary inputs with respect to arbitrary outputs. Using shadows, we then show how to compute overlaps, generate all k-weight reduced processes, and perform reconstruction via Hamiltonian learning. These latter two tasks are efficient for large systems as the number of quantum measurements needed scales only logarithmically with the number of qubits. A number of additional approximations and improvements are developed, including the use of a pair-factorized Clifford shadow and a series of postprocessing techniques that significantly enhance the accuracy for recovering the quantum channel. We have implemented ShadowQPT using both Pauli and Clifford measurements on the IonQ trapped ion quantum computer for quantum processes up to n=4 qubits, and we achieved good performance.

Published by the American Physical Society
2024
Quantum simulation of the one-dimensional Fermi-Hubbard model as a
Z2
lattice-gauge theory
Authors: Khodaeva Uliana E. , Kovrizhin Dmitry L. , Knolle Johannes
Published: January 2024

The Fermi-Hubbard model is one of the central paradigms in the physics of strongly correlated quantum many-body systems. Here we propose a quantum circuit algorithm based on the Z2 lattice gauge theory (LGT) representation of the one-dimensional Fermi-Hubbard model, which is suitable for implementation on current NISQ quantum computers. Within the LGT description there is an extensive number of local conserved quantities commuting with the Hamiltonian. We show how these conservation laws can be used to implement an efficient error-mitigation scheme. The latter is based on a postselection of states for noisy quantum simulators. While the LGT description requires a deeper quantum-circuit compared to a Jordan-Wigner (JW) based approach, remarkably, we find that our error-correction protocol leads to results being on par with a standard JW implementation on quantum simulators.

Published by the American Physical Society
2024
Stability of dissipatively-prepared Mott insulators of photons
Authors: Scarlatella Orazio , Clerk Aashish A. , Schirò Marco
Published: January 2024

Reservoir engineering is a powerful approach for using controlled driven-dissipative dynamics to prepare target quantum states and phases. In this work, we study a paradigmatic model that can realize a Mott insulator of photons in its steady state. We show that, while in some regimes its steady state approximates a Mott-insulating ground state, this phase can become unstable through a transition towards a coherent yet nonclassical limit-cycle phase, driven by doublon excitations. This instability is completely distinct from the ground-state Mott-insulator to superfluid transition. This difference has dramatic observable consequences and leads to an intrinsic fragility of the steady-state Mott phase: a fast pump compared to losses is required to sustain the phase, but also determines a small critical hopping. We identify unique features of the steady-state Mott phase and its instability that distinguish them from their ground-state counterpart and can be measured in experiments.

Published by the American Physical Society
2024
Valley-Coherent Quantum Anomalous Hall State in AB-Stacked
MoTe2/WSe2
Bilayers
Authors: Tao Zui , Shen Bowen , Jiang Shengwei , Li Tingxin , Li Lizhong , Ma Liguo , Zhao Wenjin , Hu Jenny , Pistunova Kateryna , Watanabe Kenji , Taniguchi Takashi , Heinz Tony F. , Mak Kin Fai , Shan Jie
Published: January 2024

Moiré materials provide fertile ground for the correlated and topological quantum phenomena. Among them, the quantum anomalous Hall (QAH) effect, in which the Hall resistance is quantized even under zero magnetic field, is a direct manifestation of the intrinsic topological properties of a material and an appealing attribute for low-power electronics applications. The QAH effect has been observed in both graphene and transition metal dichalcogenide (TMD) moiré materials. It is thought to arise from the interaction-driven valley polarization of the narrow moiré bands. Here, we show that the newly discovered QAH state in AB-stacked MoTe2/WSe2 moiré bilayers is not valley polarized but valley coherent. The layer- and helicity-resolved optical spectroscopy measurement reveals that the QAH ground state possesses spontaneous spin (valley) polarization aligned (antialigned) in two TMD layers. In addition, saturation of the out-of-plane spin polarization in both layers occurs only under high magnetic fields, supporting a canted spin texture. Our results call for a new mechanism for the QAH effect and highlight the potential of TMD moiré materials with strong electronic correlations and spin-orbit interactions for exotic topological states.

Published by the American Physical Society
2024
Risk and performance of Islamic and conventional banks under COVID-19 pandemic: Evidence from MENA region
Authors: Ghenimi Ameni , Chaibi Hasna , Omri Mohamed Ali
Published: January 2024

Purpose

The aim of this study is to conduct a comparative analysis between Islamic and conventional banks in terms of whether Islamic banks was more or less resilient/risky than conventional counterparts to the pandemic shock. It also examines the role of capital in improving the performance and stability within the two banking systems.

Design/methodology/approach

This study uses 82 banks from MENA (Middle East and North Africa) region for periods across 2011–2020, and employs a dynamic panel data approach to examine the resilience within both banking systems during the Covid-19 pandemic.

Findings

The results show that the Covid-19 pandemic has a negative impact on conventional banks' stability. However, Islamic banks performed better and were less risky than conventional ones. Banks with high-quality capital are more effective at controlling their risks and improving their performance during the pandemic.

Practical implications

The results offer important financial observations and policy implications to many stakeholders engaging with banks. Actually, the findings of this study facilitate to the stakeholders and bankers to have an alluded picture about determinants of risk and performance. The results can be used by bankers’ policy decision-makers to improve and enhance their consideration for risk management, taking into consideration the type of banking systems.

Originality/value

Compared to the various studies on the stability of Islamic and conventional banks, researchers have not sufficiently addressed the effect of the Covid-19 pandemic on risk and performance. Moreover, none of these studies has examined if Islamic banks was more or less resilient/risky than conventional counterparts to the pandemic shock. This leads the authors to identify the similarities and differences between two types of banks in the MENA region in a pandemic shock context.
What facilitates the emergence of shared leadership? The predictive role of team personality composition
Authors: Ge Xiaolin , Liu Siyuan , Zhang Qing , Yu Haibo , Du Xiaoyu , Song Shanghao , Shi Yunsheng
Published: January 2024

Purpose

This study aims to investigate the predictive role of team personality composition in facilitating shared leadership through team member exchange (TMX), while also to examine the moderating effect of organizational culture.

Design/methodology/approach

The authors conducted a two-stage online survey and selected the customer service teams, claims teams and financial teams of 26 Chinese insurance companies as the research samples. The authors finally obtained validated questionnaires from 107 teams with 457 members. The hypothesized relationships were tested using SPSS 25.0 and Mplus.

Findings

The results indicate that both team relationship-oriented and task-oriented personality composition have significant positive effects on shared leadership with team-member exchange serving as a full mediator for both paths. As a boundary condition, organizational culture (i.e. including internal integration values and external adaptation values) has a moderating effect on the influence of TMX on shared leadership.

Originality/value

The study investigates the predictive role of team personality composition on shared leadership, which complements the empirical studies of shared leadership antecedents in the literature. Drawing on social exchange perspective, the authors find out that TMX serves as a mediator between team personality composition and shared leadership. The authors also identify the moderating effect of organizational culture on the emergence of shared leadership. The research emphasizes the contextual boundary condition in this process.
Delineating wine tourism experiences in Ningxia, China: a supply–demand perspective
Authors: Zhan Xiaohai , Shi Xiaolin (Crystal)
Published: January 2024

Purpose

The purpose of this paper is to examine the relationship between wine tourism experiences (i.e. winescape, winery service quality, winery brand differentiation and tourist motivation) and tourist behavioral intentions (satisfaction, loyalty and revisit intention) from both demand and supply perspectives in Ningxia, China, by using the SERVQUAL model and the self-determination theory.

Design/methodology/approach

The research comprises two studies with an exploratory sequential mixed-methods approach. Study 1 adopted semi-structured interviews with winery owners and managers to explore the factors related to wine tourism experiences that influence tourists’ tourism experience. The results from the Study 1 leads to Study 2, which used a survey to explore wine tourist experiences and their behavioral intentions

Findings

This study provided important information regarding the factors that influence wine tourists experience in Ningxia wine region from the perspectives of supply and demands sides. Frist, this study confirmed the various factors influence wine tourism experiences in Ningxia based on the results from Study 1 (supply perspectives). Second, by further investigation in the Study 1, this study integrates the SERVQUAL model and the self-determination theory as fundamental theoretical frameworks in Study 2 to analysis the tourist perspectives. Third, as results, the authors finally confirmed the theoretical frameworks of wine tourism in Ningxia based on dual supply-demand perspectives.

Originality/value

The integration of multiple research approaches enriches the research findings and provides a more robust understanding of the wine tourism experiences in Ningxia.
Improving the picking efficiency of a cold warehouse to avoid temperature abuse
Authors: Benaglia Marco Fabio , Chen Mei-Hui , Lu Shih-Hao , Tsai Kune-Muh , Hung Shih-Han
Published: January 2024

Purpose

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

Design/methodology/approach

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

Findings

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

Research limitations/implications

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

Practical implications

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Originality/value

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.
Experimental analysis of vibration and noise characteristics of helical gears with nano-lubricant additives
Authors: Xu Kai , Xiao Ying , Cheng Xudong
Published: January 2024

Purpose

The purpose of this study is to investigate the effects of nanoadditive lubricants on the vibration and noise characteristics of helical gears compared with conventional lubricants. The experiment aims to analyze whether nanoadditive lubricants can effectively reduce gear vibration and noise under different speeds and loads. It also analyzes the sensitivity of the vibration reduction to load and speed changes. In addition, it compares the axial and radial vibration reduction effects. The goal is to explore the application of nanolubricants for vibration damping and noise reduction in gear transmissions. The results provide a basis for further research on nanolubricant effects under high-speed conditions.

Design/methodology/approach

Helical gears of 20CrMnTi were lubricated with conventional oil and nanoadditive oils. An open helical gearbox with spray lubrication was tested under different speeds (200–500 rpm) and loads (20–100 N·m). Gear noise was measured by a sound level meter. Axial and radial vibrations were detected using an M+P VibRunner system and fast Fourier transform analysis. Vibration spectrums under conventional and nanolubrication were compared. Gear tooth surfaces were observed after testing. The experiment aimed to analyze the noise and vibration reduction effects of nanoadditive lubricants on helical gears and the sensitivity to load and speed.

Findings

The key findings are that nanoadditive lubricants significantly reduce the axial and radial vibrations of helical gears under low-speed conditions compared with conventional lubricants, with a more pronounced effect on axial vibrations. The vibration reduction is more sensitive to rotational speed than load. At the same load and speed, nanolubrication reduces noise by 2%–5% versus conventional lubrication. Nanoparticles change the friction from sliding to rolling and compensate for meshing errors, leading to smoother vibrations. The nanolubricants alter the gear tooth surfaces and optimize the microtopography. The results provide a basis for exploring nanolubricant effects under high speeds.

Originality/value

The originality and value of this work is the experimental analysis of the effects of nanoadditive lubricants on the vibration and noise characteristics of hard tooth surface helical gears, which has rarely been studied before. The comparative results under different speeds and loads provide new insights into the vibration damping capabilities of nanolubricants in gear transmissions. The findings reveal the higher sensitivity to rotational speed versus load and the differences in axial and radial vibration reduction. The exploration of nanolubricant effects on gear tribological performance and surface interactions provides a valuable reference for further research, especially under higher speed conditions closer to real applications.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0220/
Exploring the application of college student role models in service-learning pedagogy
Authors: Ifinedo Eloho , Burt Diane
Published: January 2024

Purpose

Service-learning (SL) is a widely accepted pedagogy that can enrich the learning experience for students in higher education while they apply their skills in a meaningful community service. This research is part of a larger project that aimed to motivate educational achievement among youths living in a priority neighborhood through SL. Toward this goal, this study investigated the impact of SL on the college students from a college information technology programmer-analyst (ITPA) program, who were deployed as role models to youths in a priority neighborhood on the east coast of Canada.

Design/methodology/approach

The overall project used the design-based methodology. Seven college students were deployed in two phases to a community center as role models for the delivery of science, technology, engineering, art and mathematics (or STEAM) programs to youths living in a priority neighborhood. Data were collected using open-ended survey, journal entries and focus groups and was qualitatively analyzed by drawing on two frameworks: the experiential-learning framework by Kolb (1984) and the conceptual SL framework by Ash and Clayton (2009).

Findings

The findings describe the outcome of the college students' experiences in SL with respect to the development of skills and capacities needed by employers. Specifically, their experiences mirrored all aspects of the two frameworks applied. Therefore, the study validates the use of SL pedagogy in higher education. In addition, the study identified the role of SL as an integration strategy for international students. While the research contributes to the wider SL conversation for policymakers, faculty and administrators of higher education, it also promotes development opportunities for college students.

Originality/value

The integration of SL pedagogy is widespread among programs in higher education. However, there are no common SL frameworks used in literature. The study is novel in that it combines two theoretical frameworks – Kolb (1984) and Ash and Clayton (2009) in explaining the outcomes. In addition, it uses two high-impact educational practices – SL and role modeling to improve educational attainment for college students.
Measuring the multiplier effect of regional tourism and its spatial distribution in Indonesia before and after the COVID-19
Authors: Sastri Ray , Li Fanglin , Setiyawan Arbi , Monika Anugerah Karta
Published: January 2024

Purpose

The tourism multiplier effect (TME) is the total economic impact of tourism demand, representing the linkages between tourism and other businesses in an area. However, study about it is limited in Indonesia, especially at the provincial level and after the COVID-19 crisis. This study aims to estimate the TME in all provinces of Indonesia, test its differences in priority and non-priority areas before and after the COVID-19 crisis, analyze its spatial distribution and examine the determinant factor of TME

Design/methodology/approach

This study applies an input-output model to measure the TME of all provinces in Indonesia, an independent sample t-test to examine the similarity of TME in priority and nonpriority areas, a paired sample t-test to examine the similarity of it before and after the COVID-19 crisis, and spatial analysis to check its spatial relationship.

Findings

The result shows that regional TME ranges from 1.25 to 2.05 in 2019, which changed slightly over time. The empirical result shows the TME difference before and after the COVID-19 crisis, and there is a spatial correlation in terms of TME with the hot spots are clustered in the eastern region of Indonesia, However, there was a slight change in the position of hot spots during the COVID-19 crisis. Moreover, the spatial model shows that value-added and employment in agriculture, manufacturing, trade and transportation affect the size of TME.

Originality/value

This study contributes to the academic literature by providing the first estimate of the TME at the provincial level in Indonesia, comparing the it in priority and non-priority areas before and after the COVID-19 crisis, and mapping its spatial distribution.
Unveiling the contextual effects of total quality management to enhance sustainable performance
Authors: Mohsin Muhammad , Shamsudin Mad Nasir , Jaffri Nasif Raza , Idrees Muhammad , Jamil Khalid
Published: January 2024

Purpose

The current study focuses on the relationship between total quality management (TQM) and sustainable performance (SP) and examines how TQM practices can facilitate firms' achievement of sustainable performance. Knowledge management (KM), with its four dimensions, i.e. knowledge creation (KCR), knowledge acquisition (KAC), knowledge sharing (KSH) and knowledge application (KAP), is also an essential factor for organizations. Therefore, this study also focuses on the mediating role of KM in the relationship between TQM and sustainable performance.

Design/methodology/approach

This study used a survey method to collect data from the managers of 485 manufacturing SMEs working in five major industrial cities in Pakistan. Collected data were analyzed through PLS-SEM with the help of smart-PLS.

Findings

The study's findings reveal that TQM practices positively influence the environmental and economic sustainability of the firm. At the same time, there is no evidence that TQM practices positively affect the social sustainability of the firm. Results further elaborate that TQM practices significantly affect all four dimensions of KM. Moreover, KM positively affects the two dimensions of SP, i.e. economic and social sustainability, but surprisingly, the impact of KM on environmental sustainability is not found. Finally, results indicate the significant mediating role of KM between TQM and SP.

Originality/value

This study contributes to bridging research gaps in the literature and advances how TQM, directly and indirectly, helps firms improve sustainable performance via the mediating role of KM.
An exploration of operational excellence methodologies implementation in the logistics sectors: a global study
Authors: Trakulsunti Yaifa , Antony Jiju , Garza-Reyes Jose Arturo , Tortorella Guilherme Luz , Chuayjan Witsarut , Foster Monika
Published: January 2024

Purpose

The aim of this study reported in this paper was to explore the application of operational excellence methodologies in a global context.

Design/methodology/approach

A qualitative interview approach was used to understand the current state, benefits, challenges, success factors, tools and techniques of operational excellence methodology implementation with relevance to logistics companies worldwide. About 16 interviews were undertaken with practitioners working in leading companies and with leading academics in Asia, Europe, Africa, North America, South America and Australia.

Findings

The findings show that operational excellence methodologies including Lean, Six Sigma, Lean Six Sigma and Agile can apply in logistics firms to improve operations and productivity and save costs. Top management support and involvement play an important role in the success of operational excellence projects in the logistics service.

Research limitations/implications

The findings will be of interest to top and middle managers and logistics practitioners, with a dual aim of improving logistics performance and saving costs.

Originality/value

The present study has been one of the first global study attempts to explore the implementation of operational excellence methodologies in the logistics sectors.
Climatic gradients and forest composition shape bat communities in Eastern Mediterranean pine plantations
Authors: ALLEGRINI Claudia , KORINE Carmi , KRASNOV Boris R.
Published: January 2024

Biotic and abiotic factors can act as filters for determining the species composition of biological communities. We aimed to identify abiotic factors driving the assembly of bat communities in Eastern Mediterranean pine plantations along a north–south climatic gradient, as they are crucial forest habitats for the assessment and conservation of these communities. We expected that bat communities are predominantly shaped by environmental filtering. We conducted acoustic sampling in 35 pine plantations in Israel and analyzed recordings for species identification. We used the ESLTP analysis, an extension of the three‐table ordination (RLQ analysis), to explore relationships between environmental characteristics, species occurrences, and functional traits of species while accounting for phylogenetic relationships between species and spatial distribution of the communities. Communities showed phylogenetic and trait clustering. Climatic conditions and forest vegetation composition shaped communities of bats, affecting the distribution of traits related to foraging behaviors, vegetation clutter, and the ability of bats to maneuver in it. Maneuverable species were associated with the northern Mediterranean climatic zone, with a scarce cover of drought‐tolerant small shrubs and grassland. Fast flyers were associated with the center‐south semi‐arid area, with abundant drought‐tolerant small shrubs and grassland. These forces might have a predominant role in the assembly of these communities, presumably due to the stressful climatic conditions of the study area. The ESLTP approach can be extended to other taxa and environments to predict species responses to disturbance and environmental changes and give insights into environmental management.
Brain size mediates the choice of breeding strategy in the red‐backed shrike Lanius collurio
Authors: BIALAS Joanna T. , DYLEWSKI Łukasz , TOBOLKA Marcin
Published: January 2024

The brain size of vertebrates represents a trade‐off between natural selection for enhanced cognitive abilities and the energetic constraints of brain tissue production. Processing information efficiently can confer benefits, but it also entails time costs. Breeding strategies, encompassing timing of breeding onset and nest‐site selection, may be related to brain size. In this study, we aim to elucidate the relationship between brain size, breeding timing, nest‐site choice, and breeding success in the red‐backed shrike Lanius collurio. Our findings revealed that the timing of the first egg‐laying date was associated with female head size, with larger‐headed females tending to lay eggs later in the breeding season. Additionally, we observed that breeding success was positively correlated with increased nest concealment. However, this relationship was stronger in males with smaller heads. In turn, nest concealment was not related to head size but primarily influenced breeding onset. These results suggest that the choice of breeding strategy may be moderated by brain size, with differences between sexes. Larger‐headed females may invest more time in selecting nesting sites, leading to delayed breeding onset, while larger‐headed males may compensate for suboptimal nest concealment. Our study sheds light on the intricate interplay between brain size, breeding timing, nest‐site preferences, and breeding success in passerine birds, underscoring the potential role of cognitive capacity in shaping individual decision‐making processes.