bluuebunny/crossref_metadata_2025 huggingface dataset:
Endometriosis and uterine fibroids and risk of premature mortality: prospective cohort study
Authors: Wang Yi-Xin , Farland Leslie V , Gaskins Audrey J , Wang Siwen , Terry Kathryn L , Rexrode Kathryn M , Rich-Edwards Janet W , Tamimi Rulla , Chavarro Jorge E , Missmer Stacey A
Published: November 2024

Objective

To prospectively assess the effect of endometriosis and uterine fibroids on the long term risk of premature mortality (younger than 70 years).

Design

Prospective cohort study

Setting

The Nurses’ Health Study II, United States (1989-2019).

Participants

110 091 women aged 25-42 years in 1989 without a history of hysterectomy before endometriosis or fibroids diagnosis, cardiovascular diseases, or cancer.

Main outcome measures

Hazard ratios (estimated by Cox proportional hazards models) for total and cause specific premature mortality according to laparoscopically confirmed endometriosis or ultrasound or hysterectomy confirmed uterine fibroids reported in biennial questionnaires.

Results

4356 premature deaths were recorded during 2 994 354 person years of follow-up (27.2 years per person), including 1459 from cancer, 304 from cardiovascular diseases, and 90 from respiratory diseases. The crude incidence of all cause premature mortality for women with and without laparoscopically confirmed endometriosis was 2.01 and 1.40 per 1000 person years, respectively. In age adjusted models, laparoscopically confirmed endometriosis was associated with a hazard ratio of 1.19 (95% confidence interval 1.09 to 1.30) for premature death; these models were strengthened after also adjusting for potential confounders including behavioral factors (1.31, 1.20 to 1.44). Cause specific mortality analyses showed that the association was largely driven by mortality from senility and ill-defined diseases (1.80, 1.19 to 2.73), non-malignant respiratory diseases (1.95, 1.11 to 3.41), diseases of the nervous system and sense organs (2.50, 1.40 to 4.44), and malignant neoplasm of gynecological organs (2.76, 1.79 to 4.26). Ultrasound or hysterectomy confirmed uterine fibroids were not associated with all cause premature mortality (1.03, 0.95 to 1.11), but were associated with a greater risk of mortality from malignant neoplasm of gynecological organs (2.32, 1.59 to 3.40) in cause specific mortality analyses. The risk of mortality caused by cardiovascular and respiratory diseases varied according to joint categories of endometriosis and uterine fibroids, with an increased risk of all cause premature mortality among women reporting both endometriosis and uterine fibroids.

Conclusion

Women with a history of endometriosis and uterine fibroids might have an increased long term risk of premature mortality extending beyond their reproductive lifespan. These conditions were also associated with an increased risk of death due to gynecological cancers. Endometriosis was associated with a greater risk of non-cancer mortality. These findings highlight the importance for primary care providers to consider these gynecological disorders in their assessment of women's health.
Efficacy and safety of hyperbaric oxygen therapy for Parkinson’s disease with cognitive dysfunction: protocol for a systematic review and meta-analysis
Authors: Tan Weiqiang , Pan Zhaoquan , Xie Fengxi
Published: November 2024

Introduction

The presence of cognitive dysfunction notably affects the quality of life in individuals diagnosed with Parkinson’s disease (PD) and is often recognised as a non-motor symptom. Comprehensive studies have shown the possible advantages of hyperbaric oxygen therapy (HBOT) in alleviating cognitive deficits in these individuals. This systematic review aims to investigate the practicality of incorporating HBOT within a more extensive therapeutic framework for PD, with a specific focus on cognitive symptoms.

Methods and analysis

A comprehensive literature review will be conducted utilising various databases such as PubMed and Cochrane Library and so on. The duration of the search will encompass the entire timeline from the initiation of each database up to 1 April 2024. This investigation seeks to uncover randomised controlled trials that explore the efficacy and safety of HBOT in patients with PD who are facing cognitive impairments. The authors' autonomous screening and extraction of data will facilitate the attainment of impartial results. The assessment of possible biases will be conducted using the Cochrane risk-of-bias tool, while statistical analyses will be executed with RevMan V.5.3 and Stata V.15.0.

Ethics and dissemination

As this review synthesises and evaluates previously conducted studies, the requirement for ethical approval is not applicable. The findings from this review will be shared via academic publications, comprehensive reports and presentations at pertinent conferences.

PROSPERO registration number

CRD42024504763
Adolescents’ Daily Lives (ADL) project: an intensive longitudinal design study protocol examining the associations between physical literacy, movement behaviours, emotion regulation and mental health
Authors: Ames Megan , Srinivasa Gopalan Sharan , Sihoe C Emmett , Craig Stephanie G , Garcia-Barrera Mauricio , Liu Sam , Rhodes Ryan , Rush Jonathan , Buckler E Jean
Published: November 2024

Introduction

Adolescence represents a critical developmental period, with changes in emotional regulation capacities influencing physical and mental health. With less than 6% of Canadian youth currently meeting the 24-hour movement guidelines for physical activity, sleep and sedentary behaviour, there is an urgent need to understand the potential association between movement behaviours, physical literacy, emotional regulation and mental health during adolescence. Additionally, there is a need to better understand these associations among equity-deserving groups. We developed the Adolescents’ Daily Lives (ADL) project to identify how, when, under what contexts and to whom to promote healthy engagement in movement behaviours to optimise youth mental health.

Methods and analysis

For the ADL project, we will employ a 14-day intensive longitudinal design to investigate the associations between physical literacy, movement behaviours, emotion regulation and mental health among a diverse sample of 120 adolescents (ages 13–17 years) living in the Greater Victoria Area, British Columbia, Canada. A comprehensive baseline survey and movement competence test, assessing physical and mental well-being, 24-hour movement behaviours (ie, physical activity, sleep and sedentary behaviours) and physical literacy, will be accompanied by daily diary surveys and accelerometer-based movement tracking (ie, Fitbit Inspire 3) to assess daily fluctuations in movement behaviour, emotional regulation and mood. Multivariate analyses, including multilevel modelling, multilevel structural equation modelling and Bayesian hierarchical continuous-time SEM, will be used to model the repeated measures data and understand the simultaneous variations in daily movement behaviours, emotion regulation and mental health.

Ethics and dissemination

The ADL project received ethical approval from the University of Victoria Behavioural Research Ethics Board (protocol #22-0262). Study participation is voluntary, and data collection will be anonymised to protect participant privacy and confidentiality. Research findings will be shared through academic publications and conference proceedings. Through knowledge mobilisation resources, cocreated with the youth community advisory board, relevant findings will be shared directly with the wider community of adolescents.
Preoperative risk factors for blood transfusion in women requiring surgical management of ectopic pregnancy: a retrospective cohort study
Authors: Cullifer Rachel , Johnson Christina , Huynh Terri , Yeonjoo Yi , Pacis Michelle , Hoffman Matthew , Swartz Sarah , Makai Gretchen
Published: November 2024

Objective

This study identifies preoperative risk factors associated with blood transfusion in women undergoing surgery for ectopic pregnancy. A retrospective chart review of 252 cases was performed at a single academic-affiliated community hospital system between January 2014 and October 2017. Univariate analysis was performed using non-parametric testing where appropriate, and significant variables were incorporated in multivariate modelling.

Methods

In this cohort of 252 women, the overall transfusion rate was 8.7% (n=22). Increasing age (OR 1.12, 95% CI 1.03 to 1.22), lower systolic blood pressure (SBP) on presentation (OR 0.96, 95% CI 0.93 to 1.00), lower minimum systolic and diastolic blood pressure (DBP) (OR 0.92, 95% CI 0.89 to 1.95 and OR 0.9, 95% CI 0.84 to 0.93) and lower preoperative haemoglobin (g/L) (OR 0.46, 95% CI 0.33 to 0.62) were associated with higher rates of blood transfusion. Women who had prior care in their current pregnancy and women treated in a women’s specific emergency room (compared with a general emergency room) were less likely to be transfused (OR 0.16, 95% CI 0.05 to 0.51 and OR 0.09, 95% CI 0.03 to 0.30, respectively). Our study used a model in which variance in transfusion can reliably be explained by location of presentation to care, pain alone as a presenting complaint and haemoglobin level (Area under the curve (AUC) =0.87).

Conclusion

History of caesarean section and a presenting complaint of pain alone are newly identified indicators for women at higher risk of transfusion at the time of surgical management of ectopic pregnancy. Additionally, care provided in women’s specific emergency rooms may decrease the risk of blood transfusion in this population.
Phase I dose escalation study of IO-108, an anti-LILRB2 antibody, in patients with advanced solid tumors
Authors: Taylor Matthew H , Naing Aung , Powderly John , Woodard Paul , Chung Luke , Lin Wen Hong , Tian Hongyu , Siemers Nathan , Xiang Hong , Deng Rong , Hong Kyu , Valencia Donna , Huang Tao , Zhu Ying , Liao X Charlene , Schebye Xiao Min , Patel Manish R
Published: November 2024

Purpose

In this first-in-human dose escalation study, the safety and efficacy of IO-108, a fully human monoclonal antibody targeting leukocyte immunoglobulin-like receptor B2 (LILRB2), was investigated in patients with advanced solid tumors as monotherapy and in combination with pembrolizumab, an anti-programmed cell death protein 1 (PD-1) antibody.

Methods

The study included patients with histologically or cytologically confirmed advanced and relapsed solid tumors, with measurable disease by Response Evaluation Criteria In Solid Tumors (RECIST) V.1.1. Patients were treated with escalating doses of IO-108 every 3 weeks (Q3W) as monotherapy and in combination with pembrolizumab. Safety and tolerability were the primary objectives. Secondary and exploratory objectives included: pharmacokinetics, clinical efficacy, immunogenicity and biomarkers.

Results

Of 25 patients enrolled, 12 were treated with IO-108 monotherapy and 13 received combination therapy. IO-108 was well-tolerated up to the maximally administered dose of 1,800 mg every 3 weeks (Q3W) as monotherapy and in combination with pembrolizumab. No dose-limiting toxicity was observed, and a maximum tolerated dose was not reached. Treatment-related adverse events (TRAEs) occurred in 6 (50.0%) patients treated with IO-108 monotherapy and 6 (46.2%) patients treated with IO-108+pembrolizumab. All TRAEs were mild or moderate (Grade 1 or 2), and no TRAEs led to treatment discontinuation or death. IO-108 exhibited a dose-proportional increase in exposure. Full receptor occupancy (RO) in peripheral blood was achieved at doses ≥600 mg. The overall response rate was 9% (1/11) in the monotherapy and 23% (3/13) in the combination therapy. A patient with treatment-refractory Merkel cell carcinoma treated with IO-108 monotherapy achieved a durable complete response (CR) for more than 2 years. Pharmacodynamic gene expression changes reflecting increased tumor infiltration of T cells were associated with clinical benefits in both monotherapy and combination therapy. Additionally, baseline tumor inflammation gene signature (TIS) scores correlated with clinical benefit.

Conclusion

IO-108 is well tolerated and has led to objective response as monotherapy and in combination with pembrolizumab. The complete response and the pharmacodynamic changes in the monotherapy cohort demonstrate single agent activity of IO-108 and provide proof of concept that targeting myeloid-suppressive pathways through LILRB2 inhibition may potentiate the clinical efficacy of anti-PD-1 immune checkpoint inhibitors.

Trial registration number

NCT05054348.
Development of a predictive model for systemic lupus erythematosus incidence risk based on environmental exposure factors
Authors: Zhang Ying , Zhao Cheng , Lei Yu , Li Qilin , Jin Hui , Lu Qianjin
Published: November 2024

Objective

Systemic lupus erythematosus (SLE) is an autoimmune disease characterised by a loss of immune tolerance, affecting multiple organs and significantly impairing patients’ health and quality of life. While hereditary elements are essential in the onset of SLE, external environmental influences are also significant. Currently, there are few predictive models for SLE that takes into account the impact of occupational and living environmental exposures. Therefore, we collected basic information, occupational background and living environmental exposure data from patients with SLE to construct a predictive model that facilitates easier intervention.

Methods

We conducted a study comparing 316 individuals diagnosed with SLE and 851 healthy volunteers in a case–control design, collecting their basic information, occupational exposure history and environmental exposure data. Subjects were randomly allocated into training and validation groups using a 70/30 split. Using three-feature selection methods, we constructed four predictive models with multivariate logistic regression. Model performance and clinical utility were evaluated via receiver operating characteristic, calibration and decision curves. Leave-one-out cross-validation further validated the models. The best model was used to create a dynamic nomogram, visually representing the predicted relative risk of SLE onset.

Results

The ForestMDG model demonstrated strong predictive ability, with an area under the curve of 0.903 (95% CI 0.880 to 0.925) in the training set and 0.851 (95% CI 0.809 to 0.894) in the validation set, as indicated by model performance evaluation. Calibration and decision curves demonstrated accurate results along with practical clinical value. Leave-one-out cross-validation confirmed that the ForestMDG model had the best accuracy (0.8338). Finally, we developed a dynamic nomogram for practical use, which is accessible via the following link:https://yingzhang99321.shinyapps.io/dynnomapp/.

Conclusion

We created a user-friendly dynamic nomogram for predicting the relative risk of SLE onset based on occupational and living environmental exposures.

Trial registration number

ChiCTR2000038187.
Beyond the fingertips: imagining haptic technologies for a deafblind future
Authors: Palmer Russ , Lahtinen Riitta , Holt Raymond
Published: November 2024

In this paper, we imagine how future technologies could support people who have severe hearing and visual impairment or a deafblind condition. Much effort has gone into assistive technologies to improve access for people with visual or hearing impairments, and while some of these systems will work for people with dual sensory loss, this is not always the case. Fewer systems have been developed specifically for this group. To this end, we imagine what technologies might look like in the future if they were designed specifically for people with dual sensory impairment, based on the experiences of two of the authors in accessing various displays and events related to space and astronomy. Dual sensory loss can cover a very wide range of situations, and the precise history of each individual will have a strong effect on how they use residual senses and technologies. We therefore start by reviewing literature on deafblindness, looking at current efforts to make museums accessible to people with vision and hearing impairments and social-haptic communication, a method of augmenting vision and hearing with touch signals that has developed from the deafblind community. We move on to consider three case studies, each representing a different situation: the Rocket Garden at Kennedy Space Centre; visits to observatories to view constellations and planets and engagement with the livestreamed launch of the Mars 2020 mission. For each case study, we consider the challenges faced, and the way existing technologies have been adapted or new strategies improvised to provide access to these situations. We finish by considering where these technologies might usefully go in the future—we set out some desired characteristics for future technologies, imagine some technologies for the future and how these might have been applied to the three case studies.
A study of stable wormhole solution with non-commutative geometry in the framework of linear $$f(R,{\mathcal {L}}_m, T)$$ gravity
Authors: Loewer Niklas , Tayde Moreshwar , Sahoo P. K.
Published: November 2024

This research delves into the potential existence of traversable wormholes (WHs) within the framework of modified, curvature based gravity. The modification includes linear perturbations of the matter Lagrangian and the trace of the energy-momentum tensor with specific coupling strengths $$\alpha $$
α
and $$\beta $$
β
and can thus be viewed as a special case of linear f(R, T)-gravity with a variable matter coupling or as the simplest additively separable $$f(R,{\mathcal {L}}_m,T)$$

f
(
R
,

L
m

,
T
)

-model. A thorough examination of static WH solutions is undertaken using a constant redshift function; therefore, our work can be regarded as the first-order approximation of WH theories in $$f(R,{\mathcal {L}}_m,T)$$

f
(
R
,

L
m

,
T
)

. The analysis involves deriving WH shape functions based on non-commutative geometry, with a particular focus on Gaussian and Lorentzian matter distributions $$\rho $$
ρ
. Constraints on the coupling parameters are developed so that the shape function satisfies both the flaring-out and asymptotic flatness conditions. Moreover, for positive coupling parameters, violating the null energy condition (NEC) at the WH throat $$r_0$$

r
0

demands the presence of exotic matter. For negative couplings, however, we find that exotic matter can be avoided by establishing the upper bound $$\beta +\alpha /2<-\frac{1}{\rho r_0^2}-8\pi $$

β
+
α
/
2
<
-

1

ρ

r
0
2

-
8
π

. Additionally, the effects of gravitational lensing are explored, revealing the repulsive force of our modified gravity for large negative couplings. Lastly, the stability of the derived WH solutions is verified using the Tolman–Oppenheimer–Volkoff (TOV) formalism.
Exploring research trends in modern machine learning through a statistical mechanics lens: An Ising-inspired modeling perspective
Authors: Marullo Chiara , Buonaiuto Giuseppe , Ciani Daniele , Gargiulo Francesco , Esposito Massimo
Published: November 2024

Artificial intelligence has become ubiquitous in our society, profoundly influencing various aspects of our daily lives. However, despite its widespread adoption, artificial intelligence remains largely a “black box” with internal mechanisms that are not fully understood. Statistical mechanics offers a potential avenue to unlock this black box, treating neural networks as a complex system composed of many individual components that are too intricate to be directly and explicitly solved at a microscopic level at all times. The Ising spin model can conceptualize how neurons interact and influence each other within the nervous system. We will explore how Ising’s model is the fundamental starting point for investigating neural network models as they have been developed, starting with the pioneering work of McCulloch and Pitts and moving through the Hopfield model to the most recent deep learning architectures.
SYMMETRY SCHEME OF THE TIME FRACTIONAL (3 + 1)-DIMENSIONAL MODIFIED EXTENDED ZAKHAROV–KUZNETSOV EQUATION IN PLASMA PHYSICS
Authors: LIU JIAN-GEN , FENG BIN-LU , ZHANG YU-FENG
Published: November 2024

Higher-dimensional nonlinear models can describe more complex evolutionary mechanisms. In this paper, we considered the time fractional [Formula: see text]-dimensional modified extended Zakharov–Kuznetsov equation with the sense of the Riemann–Liouville fractional derivative in plasma physics. In the first place, the existence of symmetry of this studied equation through the symmetry scheme was proved. Then, the optimal system to the time fractional [Formula: see text]-dimensional modified extended Zakharov–Kuznetsov equation was also constructed. Subsequently, the time fractional higher-dimensional equation was reduced into the lower-dimensional fractional differential equation with the help of the Erdélyi–Kober fractional operators. Last, some conservation laws by using a new conservation theorem were also given. These novel results provide a window for us to discover this high-dimensional nonlinear equation.
Energy–momentum-squared gravity model-ℱ(ℛ,𝒯2) coupled with perfect fluid admitting solitonic-type symmetries
Authors: Siddiqi Mohd Danish
Published: November 2024

In this research paper, we discuss the energy–momentum-squared gravity model [Formula: see text] coupled with perfect fluid. We obtain the equation of state for the perfect fluid in [Formula: see text]-gravity model. Furthermore, we deal with the energy–momentum-squared gravity model [Formula: see text] coupled with perfect fluid, which admits the Ricci solitons with a conformal vector field. We provide a clue in this series to determine the density and pressure in the radiation and phantom barrier periods, respectively. In addition, we investigate the different energy conditions, black holes and singularity conditions for perfect fluid attached to [Formula: see text]-gravity in terms of Ricci soliton. Finally, we derive the Schrödinger equation for energy–momentum-squared gravity model [Formula: see text] coupled with perfect fluid.
Unraveling new exact solutions to relativistic compact objects via the segre classification approach
Authors: Iram Aneela , Afzal Wardah Aroosh , Siddiqui Azad A.
Published: November 2024

This paper is the continuation of the groundwork laid in [A. Iram, A. A. Siddiqui and T. Feroze, Int. J. Mod. Phys. D 31(11) (2022) 2240006], where the Segre classification scheme was applied to categorize spherically symmetric static spacetime metrics into four possible Segre types [Formula: see text] [Formula: see text] [Formula: see text] or [Formula: see text]. The solution for type [Formula: see text] leads to the Schwarzschild de-Sitter/anti de-Sitter metrics. The eigenvalue degeneracy in Segre types identifies the kind of matter distribution in space and aid in the consideration of novel solutions for the corresponding energy momentum tensor. We deal with an anisotropic distribution of matter correlated with electric field intensity for types [Formula: see text] and [Formula: see text]. The type [Formula: see text] refers to ideal fluid characterized by uniformly distributed pressure. A comprehensive examination is conducted in scenarios where all physical and stability criteria are satisfied. Nevertheless, for type [Formula: see text], the strong energy and causality prerequisites are breached due to negative pressure, suggesting the existence of dark energy where the attributes of standard matter cannot be met. Furthermore, the numerical test for models is conducted for the compact objects [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]. Each star’s density, pressure, and compactness factor are observed, showing the regularity at the origin. These observations impart that the discover models are plausible since they accurately represent the observable system.
Entropy relations and GUP corrections of Ernst black hole
Authors: Mondal Debojyoti , Debnath Ujjal
Published: November 2024

Bekenstein bound provides a universal bound on entropy for a black hole that is independent of mass. The universal nature of Entropy and area product of multi-horizon black holes ensure the existence of dual in 2D CFT. So, studying various sums and product relations of thermodynamic quantities, such as entropy. area, Komar energy, etc., for black holes having multiple horizons, has become a trend in quantum gravity. In this paper, we studied the thermodynamic relations of the Ernst black hole. First, we calculated temperature, area, entropy and Komar energies. Then, we derived their sums and products and found that they are not universal except for area. Lastly, we studied thermodynamics with the Generalized Uncertainty Principle (GUP) to verify the effect of the dispersion of space-time on the stability and other behavior of the Ernst black hole.
Circular motion and chaos-bound violation for dyonic global monopole spacetime surrounded by a perfect fluid
Authors: Targema Terkaa Victor , Babar Rimsha , Atif Muhammad , El-Meligy Mohammed , Tiecheng Xia , Ali Riasat
Published: November 2024

In this paper, we investigate the circular motion and chaotic behavior of charged particles in the dyonic global monopole spacetime surrounded by a perfect fluid. We classified the black hole into three special regimes: dark matter, dust, and radiation. We precisely calculated the Lyapunov exponent for each regime as an eigenvalue of the Jacobian matrix. We examine, through numerical and graphical analysis, the circular motion and chaos bound violation across all the regimes. In the dark matter regime, stable orbits conform to the chaos bound. Even though the bound brings orbits with small charges and those far from the event horizon closer, they never violate it. In the dust regime, there can be more than one orbit for a fixed mass, charge, topological defect, and fluid parameter, especially when the angular momentum is small. At this point, the orbits are unstable, and those that are closer to the event horizon violate the bound. Similarly, in the radiation regime, orbits that are closer to the event horizon are unstable and chaotic, especially with greater angular momentum. In fact, regardless of the charge, topological defect, and fluid parameter, all orbits, whether they are far from or close to the horizon, become unstable and violate the bound when the angular momentum is significantly large.
Developing an Innovative Network Security Attack Detection Model Through Artificial Intelligence and Edge Computing
Authors: Zhuang Yuan
Published: November 2024

Securing a network at its edge, that is, the location where a user creates and stores data within a larger network is defined as edge security. It is essential to have this type of perimeter security in edge computing (EC) settings. One of the biggest challenges in EC is establishing and sustaining dependable network connectivity at the edge. This study presents an innovative strategy to improve network security by combining EC and artificial intelligence (AI). With the explosion of Internet of Things (IoT) devices and the developing complexity of cyber threats, conventional security assessments are becoming insufficient. In this study, we suggested a novel water wave-optimized flexible recurrent neural network (WWO-FRNN) for security attack detection on EC. The HTTP DATASET CSIC 2010 was gathered for this study and used for intrusion detection. The data were preprocessed utilizing min–max normalization to transmogrify numeric data into a communal scale. Next, the feature is extracted for dimensional reduction using principle component analysis (PLA). The proposed method is implemented using Python software. WWO-FRNN is compared to the other traditional algorithms. The result shows the proposed methods achieved high accuracy, precision, recall, and F1-score. The study demonstrates its effectiveness against different types of attacks, improving edge network security for IoT applications.
Early publications on the stratigraphy of the northern Pennines at the turn of the nineteenth century and the first long stratigraphic sections
Authors: Smith R. D. A.
Published: November 2024

Detailed stratigraphic sections recorded by the mining industry in Great Britain were first published during the eighteenth century. In the northern Pennines, Forster presented the first representative long composite stratigraphic section in 1809. It encompassed the entire known Carboniferous (as it was later named) succession, with the portion representing the lead mining district summarizing ‘a sequence worked out during many centuries of lead mining’. Three other shorter sections, also compiled from mining industry data and dating to between 1785 and 1800, had been published previously, with limited circulation. While the lateral continuity of the geology results in a broad similarity across all of the early sections, same-scale comparison combined with contemporary accounts constrains locations of the source data. A recent assertion that an unpublished composite section presented by Walton in 1793 to the Literary and Philosophical Society of Newcastle upon Tyne was the first ‘stratigraphical section of the lead mining districts’ with ‘Hutchinson, Millar and then Forster later using his work without acknowledgement’ is shown to be incorrect. The interest of Sir Joseph Banks in the emergence of stratigraphic geology in this period suggests that he may have been the enigmatic ‘A Constant Reader’ who corresponded on the topic of these early sections in the Philosophical Magazine. Forster's 1809 publication was the first concise synthesis of the Pennines Carboniferous, making ‘the miners' succession’ more widely accessible and providing a basis for later work.
Geothermal potential in the Croatian Part of Pannonian Basin: mapping geothermal plays
Authors: Novak Zelenika Kristina , Gluhak Popović Barbara , Pleić Marija , Durn Tatjana
Published: November 2024

The Croatian part of the Pannonian Basin System (CPBS) represents the southwestern margin of the Pannonian Basin, characterized by a high geothermal gradient (4.9°C/100 m). There is a rich tradition of using geothermal aquifers for balneological, recreational and medicinal purposes. The estimation of geothermal potential is crucial at a time when Europe is increasingly turning to renewable energy sources.

There are three main geothermal plays in the CPBS: pre-rift, syn-rift and post-rift play. Temperature maps were created for each geothermal play. Temperature measurements in a total of 75 wells were used as input data. A correlation between depth and temperature was established and the assumption that the highest temperatures are to be expected in the deepest parts of the basins for all three geothermal plays was confirmed.

Temperature maps of the pre-rift, syn-rift and post-rift geothermal plays were created by applying the depth-temperature functions on the depth maps. The highest temperatures of the pre-rift, syn-rift and post-rift plays are expected in the deepest parts of the Drava and Sava basins.
GoalTrack: Supporting Personalized Goal-Setting in Stroke Rehabilitation with Multimodal Activity Journaling
Authors: Lee Jong Ho , Lee Sunghoon Ivan , Choe Eun Kyoung
Published: November 2024

Stroke is the leading cause of disability among adults, with motor impairments being the most significant complication. Stroke rehabilitation is critical for stroke survivors to regain independence in their daily activities. Central to this rehabilitation process is patient-centered goal-setting, a crucial philosophy underpinning personalized programs. However, mismatched expectations between stroke survivors and clinicians often lead to limited engagement from patients, which detracts from patient-centeredness. We envision that stroke survivors who engage in journaling activities can empower themselves to be more proactive, thereby enhancing the goal-setting process. To this end, we iteratively designed and developed GoalTrack, an activity journaling app utilizing voice and touch to support stroke survivors in articulating their rehabilitation goals. Using GoalTrack as a probe, we conducted an in-lab user study with thirteen stroke survivor participants. We present findings on how stroke survivors utilize multimodal input for different data formats, and their perspectives on its accessibility. We also report on how stroke survivors envision activity journaling in the goal-setting process, where our findings suggest that journaling supports articulating personalized rehabilitation goals and fosters enhanced engagement with therapists. We also discuss future avenues of research for designing multimodal interfaces for stroke survivors, and share lessons learned from conducting in-lab studies.
GOAT: A Generalized Cross-Dataset Activity Recognition Framework with Natural Language Supervision
Authors: Miao Shenghuan , Chen Ling
Published: November 2024

Wearable human activity recognition faces challenges in cross-dataset generalization due to variations in device configurations and activity types across datasets. We present GOAT, a Generalized crOss-dataset Activity recogniTion framework that leverages learning with natural language supervision to address these challenges. GOAT utilizes textual attributes from activity labels and device on-body positions to enable multimodal pre-training, aligning wearable activity representations with corresponding textual representations. This approach enables GOAT to adapt to diverse device configurations and activity label spaces in downstream tasks. Our method incorporates a novel device position encoding technique, a Transformer-based activity encoder, and a cosine similarity loss function to enhance feature extraction and generalization capabilities. Extensive evaluations demonstrate GOAT's effectiveness across various scenarios, including comparisons with state-of-the-art baselines, component analysis, and zero-shot activity recognition. GOAT shows promise for advancing cross-dataset activity recognition, offering a flexible and scalable solution for diverse wearable sensing applications.
ContrastSense: Domain-invariant Contrastive Learning for In-the-Wild Wearable Sensing
Authors: Dai Gaole , Xu Huatao , Yoon Hyungjun , Li Mo , Tan Rui , Lee Sung-Ju
Published: November 2024

Existing wearable sensing models often struggle with domain shifts and class label scarcity. Contrastive learning is a promising technique to address class label scarcity, which however captures domain-related features and suffers from low-quality negatives. To address both problems, we propose ContrastSense, a domain-invariant contrastive learning scheme for a realistic wearable sensing scenario where domain shifts and class label scarcity are presented simultaneously. To capture domain-invariant information, ContrastSense exploits unlabeled data and domain labels specifying user IDs or devices to minimize the discrepancy across domains. To improve the quality of negatives, time and domain labels are leveraged to select samples and refine negatives. In addition, ContrastSense designs a parameter-wise penalty to preserve domaininvariant knowledge during fine-tuning to further maintain model robustness. Extensive experiments show that ContrastSense outperforms the state-of-the-art baselines by 8.9% on human activity recognition with inertial measurement units and 5.6% on gesture recognition with electromyography when presented with domain shifts across users. Besides, when presented with different kinds of domain shifts across devices, on-body positions, and datasets, ContrastSense achieves consistent improvements compared with the best baselines.
HCR-Auth: Reliable Bone Conduction Earphone Authentication with Head Contact Response
Authors: He Zhixiang , Chen Jing , Wu Cong , He Kun , Du Ruiying , Jia Ju , Gu Yangyang , Sun Xiping
Published: November 2024

Earables, or ear wearables, are increasingly being used for a variety of personal applications, prompting the development of authentication schemes to safeguard user privacy. Existing authentications are designed for traditional in-ear earphones, relying on a closed ear canal environment, which is not suited for bone conduction earphones that feature an open-ear design. In this paper, we propose HCR-Auth, a new authentication approach for bone conduction earphones based on head biometrics. It employs a modulated chirp signal, emitted by the earphone speaker, to actively sense the user's head structure, and captures the response through the earphone's accelerometer. It operates implicitly, eliminating additional efforts from the user to perform authentication. Through extensive experiments involving 60 subjects, we determine that HCR-Auth achieves a commendable balanced accuracy of 96.55% using only 10 registration samples, proving its efficacy and resilience against potential threats. Our dataset and source codes are available at https://anonymous.4open.science/r/HCR-Auth-D43B/.
Frailty Assessment Using a Floor Panel-Type Device by Measuring Center of Pressure
Authors: Ozaki Ryota , Shinzaki Yoshio , Kodama Kana , Ito Kodai , Kamihori Mai , Takeda Toshihiro , Itoh Yuichi
Published: November 2024

In Japan, the demographic shift towards an older population presents significant challenges, particularly in elderly care. Early detection of frality---a precursor to more severe dependency---is essential for maintaining health in older adults. This study introduces a novel floor panel-type device that measures both weight and center of pressure oscillations, facilitating the early identification of frailty through routine activities like standing up, sitting down, and walking. Unlike video or audio monitoring, this method minimizes privacy concerns, making it more suitable for assessing activities of daily living. We evaluated these metrics in a cohort of 28 individuals aged between 64 and 89 years and utilized the k-nearest neighbor algorithm to correlate these measurements with frailty, defined by the revised J-CHS criteria. Our analysis achieved a predictive accuracy of approximately 72.6 % for frailty detection during sitting down actions. These findings underscore the utility of continuous monitoring of weight and center of pressure in daily environments such as bathrooms and hallways for predicting health deterioration.
Tool Learning with Foundation Models
Authors: Qin Yujia , Hu Shengding , Lin Yankai , Chen Weize , Ding Ning , Cui Ganqu , Zeng Zheni , Zhou Xuanhe , Huang Yufei , Xiao Chaojun , Han Chi , Fung Yi Ren , Su Yusheng , Wang Huadong , Qian Cheng , Tian Runchu , Zhu Kunlun , Liang Shihao , Shen Xingyu , Xu Bokai , Zhang Zhen , Ye Yining , Li Bowen , Tang Ziwei , Yi Jing , Zhu Yuzhang , Dai Zhenning , Yan Lan , Cong Xin , Lu Yaxi , Zhao Weilin , Huang Yuxiang , Yan Junxi , Han Xu , Sun Xian , Li Dahai , Phang Jason , Yang Cheng , Wu Tongshuang , Ji Heng , Li Guoliang , Liu Zhiyuan , Sun Maosong
Published: November 2024

Humans possess an extraordinary ability to create and utilize tools. With the advent of foundation models, artificial intelligence systems have the potential to be equally adept in tool use as humans. This paradigm, which is dubbed as
tool learning with foundation models
, combines the strengths of tools and foundation models to achieve enhanced accuracy, efficiency, and automation in problem-solving. This article presents a systematic investigation and comprehensive review of tool learning. We first introduce the background of tool learning, including its cognitive origins, the paradigm shift of foundation models, and the complementary roles of tools and models. Then we recapitulate existing tool learning research and formulate a general framework: starting from understanding the user instruction, models should learn to decompose a complex task into several subtasks, dynamically adjust their plan through reasoning, and effectively conquer each sub-task by selecting appropriate tools. We also discuss how to train models for improved tool-use capabilities and facilitate generalization in tool learning. Finally, we discuss several open problems that require further investigation, such as ensuring trustworthy tool use, enabling tool creation with foundation models, and addressing personalization challenges. Overall, we hope this article could inspire future research in integrating tools with foundation models.
Masquerade: Verifiable Multi-Party Aggregation with Secure Multiplicative Commitments
Authors: Mouris Dimitris , Tsoutsos Nektarios Georgios
Published: November 2024

In crowd-sourced data aggregation over the Internet, participants share their data points with curators. However, a lack of strong privacy guarantees may discourage participation, which motivates the need for privacy-preserving aggregation protocols. Moreover, existing solutions remain limited with respect to public auditing without revealing the participants’ data. In realistic applications, however, there is an increasing need for public verifiability (i.e., verifying the protocol correctness) while preserving the privacy of the participants’ inputs, since the participants do not always trust the data curators. At the same time, while publicly distributed ledgers may provide public auditing, these schemes are not designed to protect sensitive information.

In this work, we introduce two protocols, dubbed Masquerade and zk-Masquerade, for computing private statistics, such as sum, average, and histograms, without revealing anything about participants’ data. We propose a tailored multiplicative commitment scheme to ensure the integrity of data aggregations and publish all the participants’ commitments on a ledger to provide public verifiability. zk-Masquerade detects malicious participants who attempt to poison the aggregation results by adopting two zero-knowledge proof protocols that ensure the validity of shared data points before being aggregated and enable a broad range of numerical and categorical studies. In our experiments, we use homomorphic ciphertexts and commitments for a variable number of participants and evaluate the runtime and the communication cost of our protocols.
Circulating Tumor DNA: A Pan-Cancer Biomarker in Solid Tumors with Prognostic and Predictive Value
Authors: Hitchen Nadia , Shahnam Adel , Tie Jeanne
Published: November 2024

Circulating tumor DNA (ctDNA), often referred to as a liquid biopsy, represents a promising biomarker in the management of both localized and advanced solid tumors. It has garnered significant attention due to its potential to inform prognosis and guide therapeutic decisions. The clinical utility of ctDNA spans early cancer detection, minimal residual disease identification, recurrence surveillance, treatment monitoring, and precision oncology treatment decision-making in the advanced setting. Unlike conventional radiological assessments, the short half-life of ctDNA allows for more timely insights into disease dynamics. Several technological approaches are available to measure ctDNA, including next-generation sequencing and droplet digital polymerase chain reaction, although their clinical accuracy depends on multiple biological and technical factors. This review evaluates current evidence surrounding ctDNA's utility in early and advanced solid tumors.
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models
Authors: Suh Namjoon , Cheng Guang
Published: November 2024

In this article, we review the literature on statistical theories of neural networks from three perspectives: approximation, training dynamics, and generative models. In the first part, results on excess risks for neural networks are reviewed in the nonparametric framework of regression. These results rely on explicit constructions of neural networks, leading to fast convergence rates of excess risks. Nonetheless, their underlying analysis only applies to the global minimizer in the highly nonconvex landscape of deep neural networks. This motivates us to review the training dynamics of neural networks in the second part. Specifically, we review articles that attempt to answer the question of how a neural network trained via gradient-based methods finds a solution that can generalize well on unseen data. In particular, two well-known paradigms are reviewed: the neural tangent kernel and mean-field paradigms. Last, we review the most recent theoretical advancements in generative models, including generative adversarial networks, diffusion models, and in-context learning in large language models from two of the same perspectives, approximation and training dynamics.
Fabrication of MOSCAP and VARICAP Based Soil Sensors Using Low-Cost Solution Processing
Authors: Pranjale Gopal S. , Srikanth Kola , Rayudu Gosa Pedda , Patil Ganesh C.
Published: November 2024

In this work, for the first time metal-oxide semiconductor capacitor (MOSCAP) and variable capacitor diode (VARICAP) sensors are fabricated for the detection of soil macronutrients such as nitrate (N), phosphate (P) and the potash (K). The thin-film MOSCAP is fabricated by using the zinc oxide (ZnO) as semiconducting layer and the silicon dioxide (SiO2) as the dielectric layer whereas the thin film VARICAP is comprised of FTO-coated glass as anode and chemically synthesized aluminium doped zinc oxide (AZO) as the semiconducting layer. The anode and the cathode electrodes for both the devices are formed by using the low-cost screen-printing technique. Although the fabricated sensors are not characterised, the steps to characterise both MOSCAP and the VARICAP soil sensors for detecting N, P and K are also proposed. The necessary ionophores found for the detection of N, P and K are tetradodecylammonium nitrate (TDDAN), tributyltin chloride and valinomycin respectively. Thus, this paper presents a comprehensive study on fabricating solid state capacitive sensors for the detection of N, P and K soil micronutrients by using low-cost solution processing.
Subcomponent analysis of the directional sensitivity of dynamic cerebral autoregulation
Authors: Panerai Ronney B. , Davies Aaron , Alshehri Abdulaziz , Beishon Lucy C. , Minhas Jatinder S.
Published: November 2024

The directional sensitivity of the cerebral blood velocity response to a sudden change in mean arterial blood pressure (MAP) is mediated by the resistance-area product, without involvement from the cerebral critical closing pressure. The reduced amplitude of MAP spontaneous fluctuations at rest suggests that it is less likely that directional sensitivity has origins in the sympathetic control of cerebral blood vessels, thus generating the need to consider other alternatives.
An Interval Integrated Optimization to Air‐Cargo Hub Network Design and Airline Fleet Planning
Authors: Wang Yu , Zhu Tao , Yuan Kaibo , Zhang Peiwen , Liang Zhe , Zhu Jinfu
Published: November 2024

The objective of this study is to minimize the overall transportation cost through the joint decision‐making for air‐cargo hub network design and fleet planning under the uncertain environment. This joint decision‐making considers various factors, including hub location, node connectivity, fleet size, and flight frequency. It takes into account several uncertain parameters such as air‐cargo demand and transportation cost in a realistic setting. We propose a mixed‐integer programming model tailored to the characteristics of such problem, which utilizes interval numbers to address these challenges. This model aims to provide a robust scheme for the joint hub network design and the fleet planning in the uncertain environment. An improved probability‐based interval ranking method is proposed to solve the model. This transformation converts the proposed model into an equivalent real‐number one, simplifying the solving process. Then a hybrid heuristic algorithm, combining the advantages of Memory‐Based Genetic Algorithm (MBGA) and Greedy Heuristic Procedure (GHP), is introduced to enhance the solving speed. Finally, the performance of our proposed model and algorithm is verified using real‐world data from the Australian postal dataset. The results show that the proposed model reduces hub construction costs by 1.37% and fleet operational costs by 7.60%, respectively, as opposed to the use of traditional approaches. The computational time of the proposed algorithm is reduced by 28.4% and 36.5%, respectively, when compared to the use of Genetic Algorithm (GA) and Variable Neighborhood Search (VNS) algorithm.