bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of past HIV interventions and diagnosis gaps on new HIV acquisitions, transmissions, and HIV-related deaths in Côte d’Ivoire, Mali, and Senegal
Authors: Silhol Romain , Maheu-Giroux Mathieu , Soni Nirali , Fotso Arlette Simo , Rouveau Nicolas , Vautier Anthony , Doumenc-Aïdara Clémence , Geoffroy Olivier , N’Guessan Kouassi Noël , Sidibé Younoussa , Kabemba Odé Kanku , Gueye Papa Alioune , Ndeye Pauline Dama , Mukandavire Christinah , Vickerman Peter , Keita Abdelaye , Ndour Cheikh Tidiane , Ehui Eboi , Larmarange Joseph , Boily Marie-Claude ,   for the ATLAS Team∗
Published: July 2024

Objectives:
To estimate the epidemiological impact of past HIV interventions and the magnitude and contribution of undiagnosed HIV among different risk groups on new HIV acquisitions in Côte d’Ivoire, Mali and Senegal.

Design:
HIV transmission dynamic models among the overall population and key populations [female sex workers (FSW), their clients, and MSM].

Methods:
Models were independently parameterized and calibrated for each set of country-specific demographic, behavioural, and epidemiological data. We estimated the fraction of new HIV infections over 2012–2021 averted by condom use and antiretroviral therapy (ART) uptake among key populations and non-key populations, the direct and indirect contribution of specific groups to new infections [transmission population-attributable fraction (tPAF)] over 2012–2021 due to prevention gaps, and the distribution of undiagnosed people with HIV (PWH) by risk group in January 2022 and their tPAF over 2022–2031.

Results:
Condom use and ART may have averted 81–88% of new HIV infections over 2012–2021 across countries, mostly due to condom use by key population. The tPAF of all key populations combined over 2012–2021 varied between 27% (Côte d’Ivoire) and 79% (Senegal). Male key populations (clients of FSW and MSM) contributed most to new infections (>60% in Mali and Senegal) owing to their higher HIV prevalence and larger prevention gaps. In 2022, men represented 56% of all PWH with an undiagnosed infection in Côte d’Ivoire (male key populations = 15%), 46% in Mali (male key populations = 23%), and 69% in Senegal (male key populations = 55%). If HIV testing and ART initiation rates remain at current levels, 20% of new HIV infections could be due to undiagnosed key populations living with HIV in Côte d’Ivoire over 2022–2031, 53% in Mali, and 65% in Senegal.

Conclusion:
Substantial HIV diagnosis gaps remain in Western Africa, especially among male key populations. Addressing these gaps is key to impacting the HIV epidemics in the region and achieving the goal of ending AIDS by 2030.
Collagen modification remodels the sarcoma tumor microenvironment and promotes resistance to immune checkpoint inhibition
Authors: Pan Hehai , Liu Ying , Fuller Ashley M. , Williams Erik F. , Fraietta Joseph A. , Eisinger T.S. Karin 
Published: July 2024

AbstractMolecular mechanisms underlying immune checkpoint inhibitor (ICI) response heterogeneity in solid tumors, including soft tissue sarcomas (STS), remain poorly understood. Herein, we demonstrate that the collagen-modifying enzyme, procollagen-lysine,2-oxoglutarate 5-dioxygenase 2 (Plod2), which is over-expressed in many tumors relative to normal tissues, promotes immune evasion in undifferentiated pleomorphic sarcoma (UPS), a relatively common and aggressive STS subtype. This finding is consistent with our earlier observation that Plod2 promotes tumor metastasis in UPS, and its enzymatic target, collagen type VI (ColVI), enhances CD8+ T cell dysfunction. We determined that genetic and pharmacologic inhibition of Plod2 with the pan-Plod transcriptional inhibitor minoxidil, reduces UPS growth in an immune competent syngeneic transplant system and enhances the efficacy of anti-Pd1 therapy. These findings suggest that PLOD2 is an actionable cancer target and its modulation could augment immunotherapy responses in patients with UPS, and potentially other sarcomas and carcinomas.
Local chromatin decompaction shapes mitotic chromosome landscape
Authors: Tashiro Sanki , Tanizawa Hideki , Noma Ken-ichi 
Published: July 2024

ABSTRACTUnregulated activation of transcription on mitotic chromosomal arms can be detrimental to faithful chromosome segregation1–3, although a subset of genes are up-regulated during mitosis4, raising the question as to how gene activation is coordinated in the context of mitotic chromosome reorganization. Here we investigate the fine structure of mitotic chromosomes in fission yeastSchizosaccharomyces pombeand reveal that intense decompaction of local chromatin upon mitotic gene activation helps shape the mitotic chromosome landscape. More specifically, we show that binding of mitosis-specific transcription factors, Ace2 and MluI binding factor (MBF)5,6, to gene promoters followed by transcriptional elongation can locally induce chromatin decompaction during mitosis. Interestingly, local decompaction-competent genes can establish chromatin boundaries that demarcate long-range contact domains, indicating tight coupling between local and global genome organizations. Furthermore, efficient local decompaction requires enough transcriptional elongation distance and histone removal, providing a mechanistic insight into the decompaction-associated domain boundary formation. Given that the demarcation of large, self-associating domains is critical for faithful chromosome segregation7, we propose that decompaction-competent genes can be a key determinant of mitotic chromosome configuration, thereby underpinning the maintenance of genome integrity over generations, and thus their distribution along chromosomes can be subject to evolutionary selection.
Leadership during crisis: a multi-sector exploration of perceptions of leadership in Australia
Authors: Samad Ataus , Muchiri Michael K. 
Published: July 2024

Purpose
This paper aims to extend our understanding of the concept of crisis leadership based on perceptions of 48 Australian leaders drawn from various sectors including Australian politics, higher education, not-for-profit and corporate sectors.

Design/methodology/approach
This qualitative study employed semi-structured virtual interviews of 48 leaders from Australian politics, higher education, not-for-profit and corporate sectors during the COVID-19 pandemic. The Leximancer text analytics program was used for data analysis.

Findings
Participants perceived effective leadership during a crisis as encompassing four macro themes: leadership as power, leadership as emanating from people, leadership as management and leadership as specific to the organization. While these findings reinforced extant literature on facets of effective leadership, leaders from different sectors differed on the relative importance of some leadership themes and their relevance to specific sectors.

Research limitations/implications
While the data were collected from a convenient sample, our findings from multiple sectors in Australia extend our knowledge on crisis leadership by revealing differences in sectorial perspectives of crisis leadership. Further, these findings help refine the extant traditional explanations of leadership and especially offer an enhanced understanding of leadership during a crisis. Consequently, our findings support future research that could help identify specific attributes of leaders navigating organizational crises. Such future research could subsequently help develop a theory on crisis leadership based on a valid and reliable measurement for assessing crisis leadership effectiveness in diverse organizational settings.

Originality/value
Our study is based on multi-sector data and consequently lays a solid foundation for extending the conceptualization of leadership during crisis, and the need to reconceptualize effective leader attributes useful in crisis contexts. Theoretically, the current study extended recent research on crisis leadership, by examining the conceptualizations of crisis leadership within specific Australian sectors.
Rotor pole and stator tooth shaping in FSPM machines for torque performance optimization
Authors: Cetin Emrah , Zhu Z.Q. 
Published: July 2024

Purpose
This study aims to obtain the minimum torque ripple at the maximum average torque for Flux-switching permanent magnet (FSPM) machines.

Design/methodology/approach
This paper is about torque performance optimization of the FSPM machines. To achieve that, finite element analysis and genetic algorithm (GA) are used. Five different designs are simulated, optimized and compared on their air gap flux density, back electromotive force, cogging torque, average torque, torque density and torque ripple.

Findings
After the thousands of iterations, its proved that all proposed shaping techniques have potential for reducing torque ripple and cogging torque, with slightly reduced average torque. The best design is the joint stator and rotor shaping, Design V, which results in the lowest torque ripple and cogging torque. The techniques should be applicable to FSPMs with other stator slot/rotor pole number combinations.

Originality/value
In this paper, rotor pole shaping by notching, chamfering and generic shaping, stator tooth shaping and joint shaping techniques are investigated for 12 s/10p FSPM machines. Rotor and stator flanks are optimized separately and jointly, by using finite element analysis and GA for optimization to achieve maximum average torque and minimum torque ripple. Five different design is implemented and compared, respectively.
Improved design-oriented analytical modelling of flux switching PM machines
Authors: Abdelkefi Anis , Souissi Amal , Abdennadher Imen 
Published: July 2024

Purpose
This paper aims at the analytical formulation of the electromagnetic features of flux switching permanent magnet (PM) machines with emphasis on the PM air gap flux density and armature magnetic reaction.

Design/methodology/approach
The PM air gap flux density is formulated considering three different analytical models. These differ by the incorporation of the air gap magnetic saliency level from the stator side. In addition, the armature magnetic reaction is investigated based on a simplified magnetic reluctance circuit that considers the flux switching permanent magnet machines magnetic circuit geometry specification. Then, the no- and on-load torque is predicted based on the two air gap flux densities.

Findings
It has been found that the PM air gap flux density considering the stator saliencies with trapezoidal magnetomotive force waveform presents the highest accuracy. Despite the simplicity of the magnetic equivalent circuit-based approach, the predicted air gap armature magnetic reaction is in good agreement with the finite element analysis (FEA) one. These lead to the analytical predictions of the no- and on-load torque which is characterized by an acceptable accuracy.

Research limitations/implications
This work should be extended to experimental validation of the FEA results regarding the torque production generation.

Originality/value
The paper proposes an improved design-oriented analytical approach with emphasis on the PM air gap flux density and the armature magnetic reaction of flux switching PM machines.
Dynamic community detection algorithm based on hyperbolic graph convolution
Authors: Wu Weijiang , Tan Heping , Zheng Yifeng 
Published: July 2024

PurposeCommunity detection is a key factor in analyzing the structural features of complex networks. However, traditional dynamic community detection methods often fail to effectively solve the problems of deep network information loss and computational complexity in hyperbolic space. To address this challenge, a hyperbolic space-based dynamic graph neural network community detection model (HSDCDM) is proposed.Design/methodology/approachHSDCDM first projects the node features into the hyperbolic space and then utilizes the hyperbolic graph convolution module on the Poincaré and Lorentz models to realize feature fusion and information transfer. In addition, the parallel optimized temporal memory module ensures fast and accurate capture of time domain information over extended periods. Finally, the community clustering module divides the community structure by combining the node characteristics of the space domain and the time domain. To evaluate the performance of HSDCDM, experiments are conducted on both artificial and real datasets.FindingsExperimental results on complex networks demonstrate that HSDCDM significantly enhances the quality of community detection in hierarchical networks. It shows an average improvement of 7.29% in NMI and a 9.07% increase in ARI across datasets compared to traditional methods. For complex networks with non-Euclidean geometric structures, the HSDCDM model incorporating hyperbolic geometry can better handle the discontinuity of the metric space, provides a more compact embedding that preserves the data structure, and offers advantages over methods based on Euclidean geometry methods.Originality/valueThis model aggregates the potential information of nodes in space through manifold-preserving distribution mapping and hyperbolic graph topology modules. Moreover, it optimizes the Simple Recurrent Unit (SRU) on the hyperbolic space Lorentz model to effectively extract time series data in hyperbolic space, thereby enhancing computing efficiency by eliminating the reliance on tangent space.
Beyond the monolith: a taxonomy of relationship banking models and segmentation levels in SMEs
Authors: Boulanouar Zakaria 
Published: July 2024

Purpose
This study aims to investigate the reality of relationship banking (RB) in the small and medium enterprise (SME) context, specifically how banks organize activities, define SMEs and manage the SME–banking relationship.

Design/methodology/approach
Using qualitative methods, this study uses a case study approach, conducting in-depth interviews with relationship managers from major New Zealand banks. The data are analyzed using thematic analysis with a process- and mechanism-oriented lens.

Findings
The study identifies bank criteria for defining SMEs, considering factors such as business complexity, owner/manager ethnicity and business lending. Banks divide their activities into personal and business banking, with the latter further classified as micro-, small- and medium-sized businesses based on borrowing amounts. Three types of RB emerge, namely, micro-business (online/many-to-many) relationship model (RM), small-business RM (one-to-many) and medium-sized business (one-to-one) RM. This study presents a taxonomy of business banking relationship management models that capture the structure and dynamics of the three RB levels.

Research limitations/implications
Interviews may introduce biases or limited perspectives. Findings specific to New Zealand may not universally apply. Future research could explore different regions and assess the impact of these RB models on SMEs’ financial outcomes and satisfaction with banking services.

Practical implications
Findings assist banks in organizing activities and managing SME relationships. Taxonomy aids in categorizing companies and determining appropriate management models. Consequently, tailored services can be provided based on SME needs, offering customized financial packages.

Social implications
RB models prioritizing ethnicity consideration and personalized services contribute to enhanced financial inclusion for SMEs, thereby fostering broader socioeconomic growth and development, partly through the provision of tailored financial packages. Additionally, relationship managers specializing in specific industries can offer valuable insights and assistance to SMEs, fostering mutual trust and collaboration.

Originality/value
To the best of the author’s knowledge, this is the first study to hypothesize, investigate, identify and provide evidence for three RB levels in SMEs. The presented taxonomy contributes to the literature on the SME–bank relationship by providing a structured framework for effective SME relationship management. Insights can help banks develop strategies and practices for serving SMEs, ultimately contributing to their growth and success.
Prediction of effective parameters for 3D printing of poly lactic acid-carbon fibre composites using intelligent frameworks based on mechanical response
Authors: Marappan Karthikeyan , Jenarthanan M.P. , Begum K Ghousiya , Moorthy Venkatesan 
Published: July 2024

Purpose
This paper aims to find the effective 3D printing process parameters based on mechanical characteristics such as tensile strength and hardness of poly lactic acid (PLA)/carbon fibre composites (CF-PLA) by implementing intelligent frameworks.

Design/methodology/approach
The experiment trials are conducted based on design of experiments (DoE) using Taguchi L9 orthogonal array with three factors (speed, infill % and pattern type) and three levels. The factors have been optimized by solving the regression equation which is obtained from analysis of variance (ANOVA). The contour plots are generated by response surface methodology (RSM). The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness.

Findings
The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness. The results obtained from RSM are also confirmed by implementing the machine learning classifiers, such as logistic regression, ridge classifier, random forest, K nearest neighbour and support vector classifier (SVC). The results show that the SVC can predict the optimized process parameters with an accuracy of 95.65%.

Originality/value
3D printing parameters which are considered in this work such as pattern types for PLA/CF-PLA composites based on intelligent frameworks has not been attempted previously.
Additive manufacturing of duplex stainless steel by DED-LB/M and PBF-LB/M – process-material-property relationships
Authors: Maier Andreas , Rühr Manuel , Tangermann-Gerk Katja , Stephan Marcel , Roth Stephan , Schmidt Michael 
Published: July 2024

Purpose
Additive manufacturing (AM) of duplex stainless steels (DSS) is still challenging in terms of simultaneously generating structures with high build quality and adequate functional properties. This study aims to investigate comprehensive process-material-property relationships resulting from both laser-directed energy deposition (DED-LB/M) and laser powder bed fusion (PBF-LB/M) of DSS 1.4462 in as-built (AB) and subsequent heat-treated (HT) states.

Design/methodology/approach
Cuboid specimens made of DSS 1.4462 were generated using both AM processes. Porosity and microstructure analyses, magnetic-inductive ferrite and Vickers hardness measurements, tensile and Charpy impacts tests, fracture analysis, critical pitting corrosion temperature measurements and Huey tests were performed on specimens in the AB and HT states.

Findings
Correlations between the microstructural aspects and the resulting functional properties (mechanical properties and corrosion resistance) were demonstrated and compared. The mechanical properties of DED-LB/M specimens in both material conditions fulfilled the alloy specifications of 1.4462. Owing to the low ductility and toughness of PBF-LB/M specimens in the AB state, a post-process heat treatment was required to exceed the minimum alloy specification limits. Furthermore, the homogenization heat treatment significantly improved the corrosion resistance of DED- and PBF-processed 1.4462.

Originality/value
This study fulfills the need to investigate the complex relationships between process characteristics and the resulting material properties of additively manufactured DSS.
Determinants in the phage life cycle: The dynamic nature of ssDNA phage FLiP and host interactions under varying environmental conditions and growth phases
Authors: Mäkelä Kati , Laanto Elina , Sundberg Lotta‐Riina 
Published: July 2024

AbstractThe influence of environmental factors on the interactions between phages and bacteria, particularly single‐stranded DNA (ssDNA) phages, has been largely unexplored. In this study, we used Finnlakevirus FLiP, the first known ssDNA phage species with a lipid membrane, as our model phage. We examined the infectivity of FLiP with three Flavobacterium host strains, B330, B167 and B114. We discovered that FLiP infection is contingent on the host strain and conditions such as temperature and bacterial growth phase. FLiP can infect its hosts across a wide temperature range, but optimal phage replication varies with each host. We uncovered some unique aspects of phage infectivity: FLiP has limited infectivity in liquid‐suspended cells, but it improves when cells are surface‐attached. Moreover, FLiP infects stationary phase B167 and B114 cells more rapidly and efficiently than exponentially growing cells, a pattern not observed with the B330 host. We also present the first experimental evidence of endolysin function in ssDNA phages. The activity of FLiP's lytic enzymes was found to be condition‐dependent. Our findings underscore the importance of studying phage ecology in contexts that are relevant to the environment, as both the host and the surrounding conditions can significantly alter the outcome of phage–host interactions.
Effect of leader gender on countries' performance: Evidence from four COVID‐19 waves
Authors: FREUND AMIR , SHOMER YAEL 
Published: July 2024

AbstractDoes a leader's gender affect a country's performance during a health crisis, and through what mechanisms? This study finds a clear, substantial negative correlation between having a female leader in democracies and their COVID‐19 infections and mortality rates, rejecting multiple spurious claims. The research is the first to analyse four pandemic waves covering 2 years while performing inter‐wave analysis. The gendered performance gap continuously grew during the first three waves, moderated by vaccinations in the fourth wave. We found that trust and effectiveness mechanisms impacted the growth of the performance gap. As new variants of COVID‐19 continue to spread and new threats related to the climate crisis are threatening globally, understanding the impact of gender in leadership roles, particularly during global crises, can provide valuable insights for policy makers and national leaders.
Accounting for observation noise in equation‐free forecasting: The hidden‐Markov S‐map
Authors: Esguerra Dylan , Munch Stephan B. 
Published: July 2024

Abstract

Ecosystems contain numerous species interacting with each other and the environment. However, data on all relevant state variables is rarely available, hampering inference and prediction. Empirical dynamic modelling (EDM) is a valuable tool for prediction, inference and control in such partially observed systems.

However, EDM typically assumes that the available time series are observed without error. Failing to account for observation noise strongly biases estimates of Lyapunov exponents and reduces forecast accuracy. To address this limitation, we propose incorporating EDM into a hidden Markov framework and using an iterative scheme based on the expectation maximization (EM) algorithm to obtain filtered state and parameter estimates.

We evaluate the performance of this approach on several simulated dynamical systems with a range of additive noise levels, as well as on insect population time series.

Accounting for observation noise improved accuracy of population forecasts and estimates of Lyapunov exponents (LE) over a wide range of noise levels relevant to ecological time series.