bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hardware-Free Testing for Antimicrobial Resistance Using Artificial Intelligence
Authors: Chakraborty Purbali , Doganay Mert Tunca , Tozluyurt Abdullah , Hujer Andrea M. , Bonomo Robert A. , Draz Mohamed S. 
Published: July 2024

ABSTRACTAntimicrobial resistance (AMR) is one of the most challenging public health problems, and implementation of effective and accessible testing solutions is an ever-increasing unmet need. Artificial intelligence (AI) offers a promising avenue for enhanced testing performance and accuracy. We introduce an AI system specifically designed for rapid AMR testing, eliminating the requirement for bulky hardware and extensive automation. Our system incorporates a novel approach for nanotechnology-empowered intelligent diagnostics (NEIDx), leveraging nanoparticles to enable novel AI-based advanced systems for detection. We employ catalytic nanoparticle-based NEIDx coupled with magnetic separation to facilitate the direct detection of AMR-associated enzymes from blood samples. This is achieved through the formation of easily visible and detectable large bubbles, a process streamlined by AI running on a cellphone. We evaluated the performance of our AI system using two clinically relevant AMR enzymes: Klebsiella pneumoniae carbapenemase-2 (KPC-2) and Sulfhydryl variable-1 (SHV-1) β-lactamases. The system demonstrated qualitative detection with a sensitivity of 82.61% (CI of 79.7 - 85.5%) and a specificity of 92.31% (CI of 90.3 - 94.3%) in blood samples, respectively. This innovative approach holds significant promise for advancing point-of-care diagnostics and addressing the urgent need for rapid and accessible AMR testing in diverse healthcare settings.
Psilocybin mushrooms and public health in Brazil: a low-risk adverse event profile calls for evidence-based regulatory discussions
Authors: Nogueira Marcel , García-Hernández Solimary , Roberto Gleicy Sotéro , Marques Leonardo Zanella 
Published: July 2024

AbstractBackgroundCurrent drug policy classifies psilocybin, a substance produced by psychoactive mushrooms, as having a high potential for abuse, neglecting its therapeutic properties. We aimed to investigate if psilocybin mushrooms pose a risk to Brazilian public health compared to other toxic agents and whether evidence-based regulatory discussions are needed.MethodsA retrospective cross-sectional study was conducted following STROBE guidelines. Data were obtained from the Sistema de Agravos de Notificação (SINAN) on adverse events reported from 2007 to 2022. Participants were categorized into three groups: drug abuse, psilocybin mushrooms, and unknown mushrooms. Clinical outcomes assessed included non-hospitalization, hospitalization, and death. Associations between variables were analyzed using the Chi-square test.ResultsA total of 112,451 individuals sought medical attention for drug abuse-related adverse events. Among them, men constituted the majority (n = 79,514; 70.7%), followed by whites (n = 37,565; 33.4%) and those aged 26-35 (n = 29,163; 25.9%) (p < 0.001). Alcohol was the primary toxic agent (n = 71,824; 49.2%) (p < 0.001). The psilocybin mushroom group reported 13 adverse events, and the unknown mushroom group recorded 51 adverse events. Hospitalization rates were 19.5% (n = 21,923) for drug abuse, 46.2% (n = 6) for psilocybin mushrooms (0.02% of all hospitalizations) (99% CI: 10.6% - 81.6%), and 23.5% (n = 12) for unknown mushrooms (0.04% of hospitalizations) (99% CI: 8.3% - 38.7%). The mortality rate was 1.8% (n = 2035) for drug abuse, with no fatalities in the psilocybin or unknown mushroom groups. Most hospitalizations involved alcohol (45.0%), and deaths were mainly associated with cocaine (33.3%).ConclusionOur findings suggest that psilocybin mushrooms have a low-risk profile for adverse events, although underreporting may be a factor. This study highlights the need for evidence-based regulatory discussions to prevent arbitrary arrests and ensure safe access to psilocybin for clinical and ceremonial use.
First-born twin has a higher risk of acute leukemia in a population-based assessment of cancer in twins in California, and lower than anticipated rate of twin concordance
Authors: Nickels Eric M , Zhou Naying , Wiemels Joseph L 
Published: July 2024

ABSTRACTWe assessed cancer concordance, cancer incidence in the healthy twin of cancer probands, and cancer risk in relation to birth order in pediatric and adolescent/young adult twins via a population-based study in California from 1982-2022. Twin subjects born in California between 1982-2017 who were diagnosed with leukemia from 0-39 years of age were identified through linked birth and California Cancer Registry (1988-2022) data. Two concordant-twin leukemias cases were identified across 255 total twin pairs with leukemia for an overall rate of leukemia concordance of 0.9%. One concordant twin pair was identified among 199 pairs with lymphoid leukemia (0.5%) and one within 34 pairs with acute myeloid leukemia (2.9%). A significant association was identified between twin plurality birth order and development of leukemia (OR 1.18, 95% CI 1-1.39, P=0.049), an effect which was strongest in lymphoid leukemias (2.21, 1.44-3.39, P=1.65e-4). Assessment of DNA methylation markers associated with birth order showed significantly reduced methylation in first-born twin cases compared to second-born (P=8.53e-12) in a subset of 41 twins discordant for lymphoid leukemia. Overall cancer concordance in twins was comparable to the lower range of previous estimates from different world regions. Concordance in lymphoid leukemias was quite lower than expected, indicating concordant leukemia is rarer than previously appreciated. We identified a strong association between twin plurality birth order and development of pediatric cancer. While the underlying cause of this finding is uncertain, we identified significant differences in DNA methylation at previously described sites associated with birth order, suggesting a similar biological mechanism.
mBRSET: A Portable Retina Fundus Photos Benchmark Dataset for Clinical and Demographic Prediction
Authors: Wu Chenwei , Restrepo David , Nakayama Luis Filipe , Ribeiro Lucas Zago , Shuai Zitao , Barboza Nathan Santos , Vieira Sousa Maria Luiza , Fitterman Raul Dias , Alves Pereira Alexandre Durao , Saito Regatieri Caio Vinicius , Stuchi Jose Augusto , Malerbi Fernando Korn , Andrade Rafael E. 
Published: July 2024

AbstractThis paper introduces mBRSET, the first publicly available retina dataset captured using handheld retinal cameras in real-life, high-burden scenarios, comprising 5,164 images from 1,291 patients of diverse backgrounds. This dataset addresses the lack of ophthalmological data in low- and middle-income countries (LMICs) by providing a cost-effective and accessible solution for ocular screening and management. Portable retinal cameras enable applications outside traditional hospital settings, such as community health screenings and telemedicine consultations, thereby democratizing healthcare. Extensive metadata that are typically unavailable in other datasets, including age, sex, diabetes duration, treatments, and comorbidities, are also recorded. To validate the utility of mBRSET, state-of-the-art deep models, including ConvNeXt V2, Dino V2, and SwinV2, were trained for benchmarking, achieving high accuracy in clinical tasks diagnosing diabetic retinopathy, and macular edema; and in fairness tasks predicting education and insurance status. The mBRSET dataset serves as a resource for developing AI algorithms and investigating real-world applications, enhancing ophthalmological care in resource-constrained environments.
Unveiling the Structural Proteome of an Alzheimer’s Disease Rat Brain Model
Authors: Samani Elnaz Khalili , Naimul Hasan S.M. , Waas Matthew , Keszei Alexander F. A. , Xu Xiaoxiao , Heydari Mahtab , Hill Mary Elizabeth , McLaurin JoAnne , Kislinger Thomas , Mazhab-Jafari Mohammad T. 
Published: July 2024

AbstractStudying native protein structures at near-atomic resolution in crowded environment presents a challenge. Consequently, understanding the structural intricacies of proteins within pathologically affected tissues often relies on mass spectrometry and proteomic analysis. In this study, we utilized electron cryomicroscopy (cryo-EM) and a specific method of analysis called Build and Retrieve (BaR) to investigate structural characteristics of protein complexes such as post-translational modification, active site occupancy, and arrested conformational state in Alzheimer’s Disease (AD) using brain lysate from a rat model (TgF344-AD) of the disease. Our findings reveal novel insights into the architecture of these complexes, which we corroborate through mass spectrometry analysis. Interestingly, it has been shown that the dysfunction of these protein complexes extends beyond AD, implicating them in cancer, as well as other neurodegenerative disorders such as Parkinson’s disease, Huntington’s disease, and Schizophrenia. By elucidating the structural details of these complexes, our work not only enhances our understanding of disease pathology but also suggests new avenues for future approaches in therapeutic intervention.
Immunometabolic Blood Biomarkers of Developmental Trajectories of Depressive Symptoms: Findings From the ALSPAC Birth Cohort
Authors: Tsang Ruby S. M. , Stow Daniel , Kwong Alex S. F. , Donnelly Nicholas A. , Fraser Holly , Barroso Inês A. , Holmans Peter A. , Owen Michael J. , Wood Megan L. ,   LINC Consortium, van den Bree Marianne B. M. , Timpson Nicholas J. , Khandaker Golam M. 
Published: July 2024

AbstractStudies of longitudinal trends of depressive symptoms in young people could provide insight into aetiologic mechanism, heterogeneity and origin of common cardiometabolic comorbidities for depression. Depression is associated with immunological and metabolic alterations, but immunometabolic characteristics of developmental trajectories of depressive symptoms remain unclear. Using depressive symptoms scores measured on 10 occasions between ages 10 and 25 years in the Avon Longitudinal Study of Parents and Children (n=7302), we identified four distinct trajectories: low-stable (70% of the sample), adolescent-limited (13%), adulthood-onset (10%) and adolescent-persistent (7%). We examined associations of these trajectories with: i) anthropometric, cardiometabolic and psychiatric phenotypes using multivariable regression (n=1709-3410); ii) 67 blood immunological proteins and 57 metabolomic features using empirical Bayes moderated linear models (n=2059 and n=2240 respectively); and iii) 28 blood cell counts and biochemical measures using multivariable regression (n=2256). Relative to the low-stable group, risk of depression and anxiety in adulthood was higher for all other groups, especially in the adolescent-persistent (ORdepression=22.80, 95% CI 15.25-34.37; ORGAD=19.32, 95% CI 12.86-29.22) and adulthood-onset (ORdepression=7.68, 95% CI 5.31-11.17; ORGAD=5.39, 95% CI 3.65-7.94) groups. The three depression-related trajectories vary in their immunometabolic profile, with evidence of little or no alterations in the adolescent-limited group. The adulthood-onset group shows widespread classical immunometabolic changes (e.g., increased immune cell counts and insulin resistance), while the adolescent-persistent group is characterised by higher BMI both in childhood and adulthood with few other immunometabolic changes. These findings point to distinct mechanisms and intervention opportunities for adverse cardiometabolic profile in different groups of young people with depression.
Wavelength scaling and multicolor operation of a plasma-driven attosecond x-ray source via harmonic generation
Authors: Hessami Rafi , Morgan Jenny , Robles River , Larsen Kirk A. , Marinelli Agostino , Emma Claudio 
Published: July 2024

The generation of high-power coherent soft x-ray pulses of sub-100 as duration and 10 nm wavelength using beams from a GeV energy plasma wakefield accelerator has been recently investigated in Emma []. As a future upgrade to this concept, this contribution investigates scaling to shorter x-ray wavelengths by cascading undulators tuned to higher harmonics of the fundamental. We present two simulation studies for plasma-driven attosecond harmonic generation schemes with final photon wavelengths of 2 and 0.40 nm. We demonstrate in these schemes that using undulators with retuned fundamental frequencies can produce GW-scale pulses of sub-nm radiation with tens of attosecond-scale pulse lengths, an order of magnitude shorter than current state-of-the-art attosecond x-ray free electron lasers (XFELs). This multipulse multicolor operation will be broadly applicable to attosecond pump-probe experiments.

Published by the American Physical Society
2024
Direct evidence from high-field magnetotransport for a dramatic change of quasiparticle character in van der Waals ferromagnet
Fe3−xGeTe2
Authors: Vaidya S. , Coak M. J. , Mayoh D. A. , Lees M. R. , Balakrishnan G. , Singleton J. , Goddard P. A. 
Published: July 2024

Magnetometry and magnetoresistance (MR) data taken on the van der Waals ferromagnet Fe3−xGeTe2 (FGT) reveal three distinct contributions to the MR: a linear negative component, a contribution from closed Fermi-surface orbits, and an enhancement proportional to the square of the applied magnetic field which is linked to a noncoplanar spin arrangement. Contrary to earlier studies on FGT, by accounting for the field dependence of the anomalous Hall effect, we find that the ordinary Hall coefficient decreases markedly below 80 K, indicating a significant change in character of the electrons and holes on the Fermi-surface at this temperature. The resulting altered ground state eventually causes the Hall coefficient to reverse sign at 35 K. Our Hall data support the proposal that Kondo-lattice behavior develops in this d-electron material below 80 K. Additional evidence comes from the negative linear component of the MR, which arises from electron-magnon scattering with an atypical temperature dependence attributable to the onset of Kondo screening.

Published by the American Physical Society
2024
IPO underpricing: a comparative analysis of risk factor disclosures in the financial and non-financial sectors
Authors: Bhullar Pritpal Singh , Grover Krishan Lal , Tiwari Ranjit 
Published: July 2024

Purpose
This study aims to identify mutually exclusive risk categories and determine whether these categories effectively capture the potential impact of risk disclosures on the initial returns of initial public offerings (IPOs) in the financial and non-financial sectors.

Design/methodology/approach
Data were collected from 131 Indian IPO prospectuses (104 non-financial and 27 financial) issued between 2015 and 2021. Content analysis was performed to identify mutually exclusive risk categories, and the effects of these categories on initial IPO returns were assessed by regression analysis

Findings
The findings revealed that risk factor disclosures have a significant impact on underpricing, but not all risk factors are relevant. In the current study, in the financial sector, IPO underpricing was mostly driven by technological and competitive risk factors. In the non-financial sector, underpricing was predominantly influenced by operating risk and compliance risk factors.

Research limitations/implications
The limitations of this study include the use of sentence-based context analysis, which does not assess the quality of risk disclosures. The statistical data reduction technique used to generate mutually exclusive risk categories may also be a limitation.

Practical implications
This research has the potential to assist companies in standardizing the disclosure of risks within IPO prospectuses. The insights gained can inform market regulators in designing policies aimed at aiding investors in formulating investment strategies, ultimately enhancing transparency and clarity regarding information disclosure. Moreover, the findings offer valuable guidance to investors in selecting IPOs aligned with their risk tolerance levels.

Social implications
From a societal perspective, this study represents advancements by guiding regulators towards developing and regulating standardized, mutually exclusive risk factors. Such measures can aid investors in enhancing their decision-making perspectives regarding IPOs, promoting a more informed and confident investment environment.

Originality/value
This study is a pioneering attempt to address knowledge gaps by identifying distinct categories of risk disclosures in IPO prospectuses and examining their potential influence on IPO underpricing in the financial and non-financial sectors in India.
A study of rare-earth magnet profiles for torque ripple improvement of axial flux permanent magnet machine
Authors: Ali Salman , Qadeer Neelam , Ciprini Luca , Marignetti Fabrizio 
Published: July 2024

Purpose
The purpose of this study is to reduce the cogging torque in axial flux permanent magnet (AFPM) machine using optimal magnet shape.

Design/methodology/approach
This study analyzes different magnet shapes for AFPM machine performance enhancement. Three-dimensional (3D) finite element analysis is performed to see the effects of pole shaping on the cogging torque of the AFPM machine.

Findings
The magnetic pole shape has a significant effect on cogging torque and overall efficiency. The conventional model has the highest torque whereas the conventional skewing affected cogging torque positively and significantly reduced the cogging torque. The combination of skewing the pole along with face curving is more effective and decreases the cogging torque from 3.88 Nm to 1.5 Nm.

Originality/value
Rare-earth magnets are the most expensive and important part of AFPM machines. Shape and volume optimization of rare-earth magnets is crucial for the performance of AFPM machines. The research aims to analyze the different permanent magnet designs for performance improvement of the AFPM machine. Conventional flat top trapezoidal, curved-top and skewed-magnet shapes are analyzed and the performance of the AFPM machine is compared with different magnet shapes. Curved-top shape and skewed magnet significantly reduce the cogging torque. Furthermore, a combination of curved-top shape and skew magnet shape is proposed to reduce the cogging torque further and improve the AFPM machine’s overall performance. Newly proposed magnet profile gives skewed curve magnet shapes which reduce the cogging torque further. 3D finite element analysis has been used to analyze the single-sided AFPM with all four different magnet shapes. The research focuses on single-sided AFPM machines, but the results are also valid for double-sided AFPM machines and can be extended to other topologies of AFPM machines.
An adaptive multi-output Gaussian process surrogate model for large-scale parameter estimation problems
Authors: Lyu Xiaolong , Huang Dan , Wu Liwei , Chen Ding 
Published: July 2024

PurposeParameter estimation in complex engineering structures typically necessitates repeated calculations using simulation models, leading to significant computational costs. This paper aims to introduce an adaptive multi-output Gaussian process (MOGP) surrogate model for parameter estimation in time-consuming models.Design/methodology/approachThe MOGP surrogate model is established to replace the computationally expensive finite element method (FEM) analysis during the estimation process. We propose a novel adaptive sampling method for MOGP inspired by the traditional expected improvement (EI) method, aiming to reduce the number of required sample points for building the surrogate model. Two mathematical examples and an application in the back analysis of a concrete arch dam are tested to demonstrate the effectiveness of the proposed method.FindingsThe numerical results show that the proposed method requires a relatively small number of sample points to achieve accurate estimates. The proposed adaptive sampling method combined with the MOGP surrogate model shows an obvious advantage in parameter estimation problems involving expensive-to-evaluate models, particularly those with high-dimensional output.Originality/valueA novel adaptive sampling method for establishing the MOGP surrogate model is proposed to accelerate the procedure of solving large-scale parameter estimation problems. This modified adaptive sampling method, based on the traditional EI method, is better suited for multi-output problems, making it highly valuable for numerous practical engineering applications.
Exploring the critical success factors of virtual reality adoption in the hotel industry
Authors: Lodhi Rab Nawaz , Asif Muhammad , Del Gesso Carla , Cobanoglu Cihan 
Published: July 2024

Purpose
This qualitative study aims to investigate the critical success factors (CSFs) driving the adoption of virtual reality (VR) in the hospitality industry, shedding light on key determinants for successful implementation.

Design/methodology/approach
Drawing on a diverse set of interviews conducted in Italy, Pakistan, the USA and Turkey, this study uses thematic analysis facilitated by NVivo 12 to comprehensively explore and identify the CSFs influencing VR adoption within the global hospitality industry.

Findings
This study identifies distinct CSFs at various phases of VR adoption in the hospitality industry. Preimplementation emphasizes budget planning and stakeholder engagement, implementation highlights safety training and feedback mechanisms and postimplementation underscores the importance of innovation, feedback utilization and maintenance for sustained success. These findings offer a strategic roadmap for VR integration in hospitality.

Practical implications
The study informs hospitality industry stakeholders of crucial success factors for VR adoption, thereby guiding strategic decision-making. Sustained VR integration success is ensured by emphasizing budget planning, stakeholder engagement, safety training, feedback mechanisms and postimplementation innovation.

Originality/value
To the best of the authors’ knowledge, this groundbreaking research is the first in-depth investigation into CSFs for the adoption of VR in the hospitality industry. This research advances our understanding of and provides fresh guidance for effective VR integration by revealing novel insights into the key variables at various deployment phases.