bluuebunny/crossref_metadata_2025_split huggingface dataset:
A randomized controlled experiment testing the use of virtual reality to trigger cigarette craving in people who smoke
Authors: Rovira Aitor , Lambe Sinéad , Beckwith Helen , Ahmed Memoona , Hudson Felicity , Haynes Phoebe , Yu Chun-Jou , Williams Kira , Saidel Simone , Iredale Ellen , McBride Sapphira , Waite Felicity , Pan Xueni , Freeman Daniel 
Published: August 2024

AbstractAutomated delivery of therapy in virtual reality (VR) has the potential to be used for smoking cessation. Most obviously, it could be used to practise and establish alternative reactions to smoking cues. The first step in treatment development is to show that VR environments can trigger sufficient cravings in smokers. We evaluated a new VR public house outdoor scenario with 100 individuals who smoked daily. Participants were randomly assigned to the VR scenario with smoking cues or a neutral experience in VR. The VR experiences were presented in a standalone VR headset. Before and after VR, we collected self-reported craving scores for cigarettes and alcohol using the Tobacco Craving Questionnaire (TCQ) and visual analogue scales (VAS). Physiological data were also collected. Compared to the neutral condition, exposure to the smoking cues led to a large increase in craving for a cigarette (TCQ β = 11.44, p < 0.0001, Cohen’s d = 1.10) and also a moderate increase in craving for alcohol $$(\upbeta =0.7,\text{ p}=0.017,\text{ d}=0.50)$$

(
β
=
0.7
,

p
=
0.017
,

d
=
0.50
)

. There were no significant physiological differences between the two conditions. These results provide good evidence that VR experiences can elicit strong craving for cigarettes. The programming can be part of developing a new VR cognitive therapy to help people reduce smoking.
Targeting Nrf2/PHKG2 axis to enhance radiosensitivity in NSCLC
Authors: Han Fushi , Chen Shuzhen , Zhang Kangwei , Zhang Kunming , Wang Meng , Wang Peijun 
Published: August 2024

AbstractWhile ferroptosis shows promise in anti-cancer strategy, the molecular mechanisms behind this process remain poorly understood. Our research aims to highlight the regulation of radiotherapy-induced ferroptosis in non-small cell lung cancer (NSCLC) via the NRF2/PHKG2 axis-mediated mechanism. To identify ferroptosis-associated genes associated with radioresistance in NSCLC, this study employed high-throughput transcriptome sequencing and Lasso risk regression analysis. Clinical samples were analyzed to confirm PHKG2 expression changes before and after radiotherapy. The study further examined ferritinophagy-related factors, intracellular iron levels, mitochondrial function, and ferroptosis in NSCLC cells undergoing radiation exposure to explore the effect of PHKG2 on radiosensitivity or radioresistance. The research also demonstrated the transcriptional inhibition of PHKG2 by NRF2 and created in situ transplantation tumor models of NSCLC to examine the role of NRF2/PHKG2 axis in NSCLC radiosensitivity and resistance in vivo. The Lasso risk regression model that incorporated ferroptosis-associated genes effectively predicted the prognosis of patients with NSCLC. Radiotherapy-sensitive tissues exhibited an increased expression of PHKG2. Overexpression of PHKG2 led to elevated intracellular iron levels by promoting ferritinophagy and increased mitochondrial stress-dependent ferroptosis induced by radiotherapy. PHKG2 transcription repression was achieved through NRF2. The FAGs-Lasso risk regression model can accurately predict the prognosis of NSCLC patients. Targeting Nrf2 upregulates the expression of PHKG2 and reverses radiotherapy resistance in NSCLC by promoting iron autophagy and inducing mitochondrial dysfunction, thereby increasing radiotherapy sensitivity.
Predicting 1, 2 and 3 year emergent referable diabetic retinopathy and maculopathy using deep learning
Authors: Nderitu Paul , Nunez do Rio Joan M. , Webster Laura , Mann Samantha , Cardoso M. Jorge , Modat Marc , Hopkins David , Bergeles Christos , Jackson Timothy L. 
Published: August 2024

Abstract
Background
Predicting diabetic retinopathy (DR) progression could enable individualised screening with prompt referral for high-risk individuals for sight-saving treatment, whilst reducing screening burden for low-risk individuals. We developed and validated deep learning systems (DLS) that predict 1, 2 and 3 year emergent referable DR and maculopathy using risk factor characteristics (tabular DLS), colour fundal photographs (image DLS) or both (multimodal DLS).

Methods
From 162,339 development-set eyes from south-east London (UK) diabetic eye screening programme (DESP), 110,837 had eligible longitudinal data, with the remaining 51,502 used for pretraining. Internal and external (Birmingham DESP, UK) test datasets included 27,996, and 6928 eyes respectively.

Results
Internal multimodal DLS emergent referable DR, maculopathy or either area-under-the receiver operating characteristic (AUROC) were 0.95 (95% CI: 0.92–0.98), 0.84 (0.82–0.86), 0.85 (0.83–0.87) for 1 year, 0.92 (0.87–0.96), 0.84 (0.82–0.87), 0.85 (0.82–0.87) for 2 years, and 0.85 (0.80–0.90), 0.79 (0.76–0.82), 0.79 (0.76–0.82) for 3 years. External multimodal DLS emergent referable DR, maculopathy or either AUROC were 0.93 (0.88–0.97), 0.85 (0.80–0.89), 0.85 (0.76–0.85) for 1 year, 0.93 (0.89–0.97), 0.79 (0.74–0.84), 0.80 (0.76–0.85) for 2 years, and 0.91 (0.84–0.98), 0.79 (0.74–0.83), 0.79 (0.74–0.84) for 3 years.

Conclusions
Multimodal and image DLS performance is significantly better than tabular DLS at all intervals. DLS accurately predict 1, 2 and 3 year emergent referable DR and referable maculopathy using colour fundal photographs, with additional risk factor characteristics conferring improvements in prognostic performance. Proposed DLS are a step towards individualised risk-based screening, whereby AI-assistance allows high-risk individuals to be closely monitored while reducing screening burden for low-risk individuals.
Hydrodynamical shear mixing in subsonic boundary layers and its role in the thermonuclear explosion of classical novae
Authors: Bellomo Marco , Shore Steven N. , José Jordi 
Published: August 2024

Context. The transition zone between the white dwarf (WD) envelope and a circumstellar accretion disk in classical novae, the boundary layer, is a region of strong dissipation and intense vorticity. In this strongly sheared layer, the hydrogen-rich accreted gas is expected to mix with the underlying WD outermost layers so the conditions for the onset of the thermonuclear runaway (TNR) in classical nova will be different from the standard treatment of the onset and subsequent mixing.
Aims. We applied the critical layer instability (CLI) to the boundary between a disk-accreted H/He zone and the C/O- or O/Ne – rich outer layers of a mass-accreting WD in a cataclysmic binary and then used the resulting structure as input to one-dimensional nuclear-hydrodynamic simulations of the nova outburst.
Methods. We simulated the subsonic mixing process in two dimensions for conditions appropriate for the inner disk and a CO 0.8 M⊙ and CO and ONe 1.25 M⊙ WDs using the compressible hydrodynamics code PLUTO. The resulting compositional profile was then imported into the one-dimensional nuclear-hydrodynamics code SHIVA to simulate the triggering and growth rate for the TNR and subsequent envelope ejection.
Results. We find that the deep shear driven mixing changes the triggering and development of the TNR. In particular, the time to reach peak temperature is significantly shorter, and the ejected mass and maximum velocity of the ejecta substantially greater, than the current treatment. The 7Li yield is reduced by about an order of magnitude relative to the current treatments.
Artificial Intelligence Prediction Model of Occurrence of Cerebral Vasospasms Based on Machine Learning
Authors: Lintas Konstantinos , Rohde Stefan , Mpoukouvala Anna , El Hamalawi Boris , Sarge Robert , Mueller Oliver Marcus 
Published: August 2024

Abstract
Background Symptomatic cerebral vasospasms are deleterious complication of the rupture of a cerebral aneurysm and potentially lethal. The existing scales used to classify the initial presentation of a subarachnoid hemorrhage (SAH) offer a blink of the outcome and the possibility of occurrence of symptomatic cerebral vasospasms. Altogether, neither are they sufficient to predict outcome or occurrence of events reliably nor do they offer a united front. This study tests the common grading scales and factors that otherwise affect the outcome, in an artificial intelligence (AI) based algorithm to create a reliable prediction model for the occurrence of cerebral vasospasms.
Methods Applying the R environment, an easy-to-operate command line was programmed to prognosticate the occurrence of vasospasms. Eighty-seven patients with aneurysmal SAH during a 24-month period of time were included for study purposes. The holdout and cross-validation methods were used to evaluate the algorithm (65 patients constituted the validation set and 22 patients constituted the test set). The Support Vector Machines (ksvm) classification method provided a high accuracy. The medical dataset included demographic data, the Hunt and Hess scale (H&H), Fisher grade, Barrow Neurological Institute (BNI) scale, length of intervention for aneurysmal repair, etc.
Results Our prediction model based on the AI algorithm demonstrated an accuracy of 61 to 86% for the event of symptomatic vasospasms. For subgroup analysis, 28.8% (n = 13) patients in the surgical cohort developed symptomatic vasospasm. Of these, 50% (n = 7) were admitted with Fisher scale grade 4, 37.5% (n = 5) with H&H 5, and 28.5% (n = 4) with BNI 5. In the endovascular cohort, vasospasms occurred in 31.8% (n = 14) patients. Of these, 69% (n = 9) patients were admitted with Fisher grade 4, 23% (n = 3) patients with H&H 5, and 7% (n = 1) patients with BNI 5.
Conclusion From our data, we may believe that the algorithm presented can help in identifying patients with SAH who are at “high” or “low” risk of developing symptomatic vasospasms. This risk balancing might further allow the treating physician to go for an earlier intervention trying to prevent permanent sequelae. Certainly, accuracy will improve with a higher caseload and more statistical coefficients.
Time Trends and Excess Mortality Compared to Population Controls after a First-Time Pulmonary Embolism or Deep Vein Thrombosis
Authors: Glise Sandblad Katarina , Svensson Carl Johan , Svennerholm Kristina , Philipson Jacob , Pivodic Aldina , Schulman Sam , Tavoly Mazdak 
Published: August 2024

Background Recent data on temporal trends in excess mortality for patients with pulmonary embolism (PE) and deep vein thrombosis (DVT) compared with the general population are scarce.
Methods A nationwide Swedish register study conducted from 2006 to 2018 including 68,960 PE and 70,949 DVT cases matched with population controls. Poisson regression determined relative risk (RR) for 30-day and 1-year mortality trends while Cox regression determined adjusted hazard ratios (aHRs). A significance level of 0.001 was applied.
Results In PE cases, both 30-day mortality (12.5% in 2006 to 7.8% in 2018, RR: 0.95 [95% CI: 0.95–0.96], p < 0.0001) and 1-year mortality (26.5 to 22.1%, RR: 0.98 [0.97–0.98], p < 0.0001) decreased during the study period. Compared with controls, no significant change was seen in 30-day (aHR: 33.08 [95% CI: 25.12–43.55] to 24.64 [95% CI: 18.81–32.27], p = 0.0015 for interaction with calendar year) or 1-year (aHR: 5.85 [95% CI: 5.31–6.45] to 7.07 [95% CI: 6.43–7.78], p = 0.038) excess mortality. The 30-day excess mortality decreased significantly (aHR: 39.93 [95% CI: 28.47–56.00) to 24.63 [95% CI: 17.94–33.83], p = 0.0009) in patients with PE without known cancer before baseline, while the excess 1-year mortality increased (aHR: 3.55 [95% CI: 3.16–3.99] to 5.38 [95% CI: 4.85–5.98], p < 0.0001) in PE cases surviving to fill a prescription of anticoagulation. In DVT cases, 30-day and 1-year mortality declined, while excess mortality compared with controls remained stable.
Conclusion In general, the improved mortality following PE and DVT paralleled population trends. However, PE cases without cancer had decreasing excess 30-day mortality, whereas those surviving to fill a prescription for anticoagulant medication showed increasing excess 1-year mortality.
15 Years POEM: The Current and Future State of Submucosal Endoscopy
Authors: Strong Andrew T. 
Published: August 2024

AbstractThe submucosal plane has become an increasingly utilized space to endoscopically approach and treat several diseases of the gastrointestinal tract. Submucosal tunneling was introduced as a concept jointly by both endoscopic submucosal dissection and per-oral endoscopic myotomy or (POEM). The enthusiasm for the latter technique has not only revolutionized the treatment of achalasia over the past two decades but also spurred the development of several procedural derivatives to treat a variety of diseases. This review will survey literature concerning submucosal tunneling endoscopy from 2008, when the first POEM was reported, to today.
Modified fungal diversity in dense clay subsoils after deep-banding organic substrate
Authors: Vido Joshua J. , Jin Jian , Hayden Helen L. , Celestina Corinne , Sale Peter W. G. , Armstrong Roger , Tang Caixian , Wood Jennifer L. , Franks Ashley E. 
Published: August 2024

Context Deep-banded nutrient rich amendments can overcome crop productivity constraints of Australian dense clay subsoils. However, knowledge on essential microbial community in field trials is limited. Methods We examined subsoils that had been deep-ripped 2 years earlier with various types of amendments (organic, a blend of organic and inorganic, and purely inorganic). Subsoil samples (15–25 cm) were collected encompassing the amendment band (0 cm), as well as at increasing distances from it (14 and 28 cm). Bacterial 16S rRNA, fungal ITS amplicon sequencing, and SOM/TOC measurements on amendment band samples were done to assess microbial communities. Key results While no variations were detected in bacterial communities across treatments, soils enriched with organic substrates diverged significantly in fungal diversity compared to the control, concentrated primarily within the amendment bands. Fungal response to these organic amendments was primarily dominated by an enrichment of filamentous saprotrophic fungi. Conclusion Changes in fungal diversity and the enrichment of saprotrophic fungi is primarily attributed to the introduction of organic substrates into the subsoil. However, despite the absence of SOM/TOC differences between treatments, SOM/TOC levels were initially expected to rise in response to organic amendments. Consequently, variations in fungal communities may have initially arisen from heightened SOM/TOC levels but persisted even as these levels returned to baseline, suggesting a lasting legacy effect. Implications A single application of deep-banded organic amendments was effective in enriching agriculturally significant fungi within dense clay subsoils after 2 years. This can further aid crop productivity by fostering soil structural improvements and optimising nutrient cycling, even after the organic amendments are undetectable.
Circular motion of a charged particle on the inner surface of a frictionless cone under the influence of an electric field due to an electric dipole
Authors: Yusmantoro Yusmantoro 
Published: August 2024

Abstract
A common problem provided in elementary physics textbooks is the analysis of the circular motion of a point-like particle affected by a gravitational field on the frictionless inner surface of an inverted cone. In this research, we study the motion of a charged particle on the same surface subject to an electric field generated by an electric dipole placed at the bottom of the cone. We study negatively and positively charged particles and analyse the dynamics of both. We calculate the physical quantities such as speed, angular velocity, angular momentum, and mechanical energy. Furthermore, we determine all possible distances travelled by the particles measured from the dipole. We also discuss the stability of the circular orbit using the effective potential. Finally, we consider the particle’s motion on a generic surface formed by the revolution of the curve

ρ

z

around the vertical axis. We determine the differential equation of

ρ

z

, in which the kinematic variables including speed

v
,

angular velocity

ω
,

and angular momentum

L

are constant.
A highly accurate analytical method for determination of the vibrational frequency of N/MEMS with electrostatic and van der Waals interaction forces
Authors: Nhu Hieu Nguyen , Chung Pham Ngoc 
Published: August 2024

Abstract
In this study, a novel approach based on the elliptic balance method (EBM) is proposed for the first time to find the approximate frequency of nano/micro-electromechanical systems modeled as Euler–Bernoulli beams under the effects of electrostatic and van der Waals interaction forces. Firstly, the governing equation of the beam is reduced to the single-mode vibration equation using the Galerkin method. A nonlinear differential equation for the time-dependent beam deflection is obtained. We present the approximate solution as an elliptic cosine function, which considers the free term contributing to the solution. This free term is relevant for vibrations with a non-zero mean in time, in which the beam is affected by a relatively large applied voltage. Via some manipulations, the obtained result is an algebraic equation with only one unknown in three unknowns: the free and vibration coefficient terms, and the modulus quantity of the elliptic cosine function. This nonlinear equation is solved using the Newton–Raphson method. The numerical results from the EBM show that the accuracy of the solution responses in time and approximate frequency is relatively accurate, almost coinciding with the results obtained from the numerical solution method using the Runge–Kutta algorithm. Our results also agree well with previously published experimental and simulation results. The results are meaningful when determining the frequency of the vibrating beam with high accuracy for micro/nano systems.
Fault detection method for transmission line components based on lightweight GMPPD-YOLO
Authors: Wu Dong , Yang Weijiang , Li Jiechang 
Published: August 2024

Abstract
This paper designs a lightweight high-precision transmission line component detection model, named grouped dense, monotonic self-regularized, and partial faster convolution, pruning, and distillation optimized—you only look once (GMPPD-YOLO), in transmission line inspection. It addresses the issue of low detection accuracy of target detection algorithms due to the complex background, large differences in target shape, location, texture, etc, as well as diversified and smaller defects in insulator and vibration hammer images taken by unmanned aerial vehicles from multiple angles. To enhance the model’s feature extraction capabilities in complex backgrounds and across different scales, the grouped dense C3 dense feature extraction module was designed, enabling the model to more effectively handle diverse defect forms. Simultaneously, the monotonic self-regularized pyramid pooling–fast (MSPPF) module is proposed to enhance the model’s capability to process multi-scale information. Additionally, the partial-faster C3 feature awareness module is designed to improve feature fusion performance, enhancing the model’s ability to perceive features at different scales. Finally, channel pruning was used to reduce redundant parameters, and knowledge distillation was employed to compensate for the accuracy loss caused by pruning. This approach further compressed the model size while ensuring its detection performance. The experimental results demonstrate that compared to the original YOLOv5s algorithm, the proposed GMPPD-YOLO algorithm achieves a reduction in parameters by 68.4%, a decrease in Giga floating-point operations per second by 58.2%, and a reduction in the model size by 66.4%, while achieving an increase in precision by 1%, mAP50 by 1.1%, and mAP95 by 0.4%. This confirms the significant potential of the GMPPD-YOLO algorithm for deployment in real-time drone-based power transmission line inspections.
A novel DNFS control strategy for vehicle semi-active suspension system
Authors: Ji Guanggang , Li Shaohua , Feng Guizhen , Li Zhengchuan , Liu Xiaofan 
Published: August 2024

Abstract
Due to the fact that the traditional fuzzy controller of the suspension system expressively depends on expert experience, and the fact that the control strategy and damper model of the suspension system are verified separately, we put forward a novel control strategy for semi-active suspension systems based on deep neural fuzzy system (DNFS). The dynamic model of semi-active suspension systems is established, and by using adaptive neuro fuzzy inference system (ANFIS), a variable universe Takagi–Sugeno (T–S) fuzzy controller is designed. Then, combining the bench experimental data and ANFIS, a non-parametric model of continuous damping control (CDC) damper is first proposed. Finally, a semi-active suspension controller based on DNFS is constructed by using serial ideas. The effectiveness of the proposed DNFS control strategy is verified by simulation experiments under different working conditions. The results show that the proposed DNFS control strategy has strong adaptability to various working conditions, which can effectively improve the ride comfort and handling stability of vehicles.
Linear and fractional response for nonlinear dissipative SPDEs
Authors: Carigi Giulia , Kuna Tobias , Bröcker Jochen 
Published: August 2024

Abstract
A framework to establish response theory for a class of nonlinear stochastic partial differential equations (SPDEs) is provided. More specifically, it is shown that for a certain class of observables, the averages of those observables against the stationary measure of the SPDE are differentiable (linear response) or, under weaker conditions, locally Hölder continuous (fractional response) as functions of a deterministic additive forcing. The method allows to consider observables that are not necessarily differentiable. For such observables, spectral gap results for the Markov semigroup associated with the SPDE have recently been established that are fairly accessible. This is important here as spectral gaps are a major ingredient for establishing linear response. The results are applied to the 2D stochastic Navier–Stokes equation and the stochastic two–layer quasi–geostrophic model, an intermediate complexity model popular in the geosciences to study atmosphere and ocean dynamics. The physical motivation for studying the response to perturbations in the forcings for models in geophysical fluid dynamics comes from climate change and relate to the question as to whether statistical properties of the dynamics derived under current conditions will be valid under different forcing scenarios.