The human patellar tendon is mechanically homogenous at its mid-substance.

The human patellar tendon contains distinct fascicle bundles across its mediolateral and anteroposterior regions. Studies have suggested region-specific behaviour during in vivo actions, but it is unclear whether such regional differences result from localized variation in composition and mechanical properties within the tendon itself. Furthermore, the viscoelastic properties of any region of the human patellar tendon have not been well described previously.

A low-cost soft sensor for sewer flow monitoring - Learning from water level measurements in manholes.

Flow meters are commonly used in manholes to monitor the flow rate for sewer operation and management. However, the large-scale deployment of flow meters in a sewer system is cost-prohibitive due to their high costs and the need for frequent maintenance. This paper proposes a soft sensor that estimates flow rates based on water level measurements in a manhole.

Causal analysis for multivariate integrated clinical and environmental exposures data.

Electronic health records (EHRs) provide a rich source of observational patient data that can be explored to infer underlying causal relationships. These causal relationships can be applied to augment medical decision-making or suggest hypotheses for healthcare research. In this study, we explored a large-scale EHR dataset on patients with asthma or related conditions (N = 14,937).

Factors associated with true-positive and false-positive diagnoses of behavioural variant frontotemporal dementia in 100 consecutive referrals from specialist physicians.

Background: The behavioural variant of frontotemporal dementia (bvFTD) is a challenging diagnosis due to overlapping symptoms with psychiatric and other neurological conditions. Accordingly, misdiagnosis is common. The present study aimed to identify clinical factors contributing to misdiagnoses of bvFTD by specialist physicians.

Assessing the impact of energy coaching with smart technology interventions to alleviate energy poverty.

Energy poverty affects 550,000 homes in the Netherlands yet policy interventions to alleviate this issue are rare. Therefore, we test two energy coaching interventions in Amsterdam: a static information group (n = 67) which received energy efficient products and one energy-use report, and a smart information group (n = 50), which also had a display providing real-time feedback on energy-use. Results across both groups, show a 75% success rate for alleviating energy poverty.

Rural Roads to cognitive Resilience (RRR): A prospective cohort study protocol.

Background: Ambient air pollution, detrimental built and social environments, social isolation (SI), low socioeconomic status (SES), and rural (versus urban) residence have been associated with cognitive decline and risk of Alzheimer's disease and related dementias (ADRD). Research is needed to investigate the influence of ambient air pollution and built and social environments on SI and cognitive decline among rural, disadvantaged, ethnic minority communities. To address this gap, this cohort study will recruit an ethnoracially diverse, rural Florida sample in geographic proximity to seasonal agricultural burning.

Selective modal excitation in a multimode nanoslit by interference of surface plasmon waves.

Interference of surface plasmons has been widely utilized in optical metrology for applications such as high-precision sensing. In this paper, we introduce a surface plasmon interferometer with the potential to be arranged in arrays for parallel multiplexing applications. The interferometer features two grating couplers that excite surface plasmon polariton (SPP) waves traveling along a gold-air interface before converging at a gold nanoslit where they interfere.

Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations.

Middle-Aged and Elderly people today face a variety of health problems as a result of their modern lifestyle, which includes increased work stress, less physical activity, and altered food habits. Because of Complications arising, diabetes has become one of the most frequent, severe, and fatal illnesses around the world. Therefore, inaccurate measurements of blood glucose levels can seriously damage vital organs.

DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations.

Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex interactions among drugs and their wide-ranging effects. To address this issue, we introduce DD-PRiSM (Decomposition of Drug-Pair Response into Synergy and Monotherapy effect), a deep-learning pipeline that predicts the effects of combination therapy.

Strategies to enhance THz harmonic generation combining multilayered, gated, and metamaterial-based architectures.

Graphene has unique properties paving the way for groundbreaking future applications. Its large optical nonlinearity and ease of integration in devices notably makes it an ideal candidate to become a key component for all-optical switching and frequency conversion applications. In the terahertz (THz) region, various approaches have been independently demonstrated to optimize the nonlinear effects in graphene, addressing a critical limitation arising from the atomically thin interaction length.

Adapting single-walled carbon nanotube-based thin-film transistors to flexible substrates with electrolyte-gated configurations using a versatile tri-layer polymer dielectric.

Flexibility has been a key selling point in the development of carbon-based electronics and sensors with the promise of further development into wearable devices. Semiconducting single-walled carbon nanotubes (SWNTs) lend themselves well to applications requiring flexibility while achieving high-performance. Our previous work has demonstrated a tri-layer polymer dielectric composed of poly(lactic acid) (PLA), poly(vinyl alcohol) with cellulose nanocrystals (PVAc), and toluene diisocyanate-terminated poly(caprolactone) (TPCL), yielding an environmentally benign and solution-processable n-type thin-film transistor (TFT).

Medications and cognitive decline in Alzheimer's disease: Cohort cluster analysis of 15,428 patients.

Background: Medications for comorbid conditions may affect cognition in Alzheimer's disease (AD).

Objective: To explore the association between common medications and cognition, measured with the Mini-Mental State Examination.

Methods: Cohort study including persons with AD from the Swedish Registry for Cognitive/Dementia Disorders (SveDem).

International multicenter validation of AI-driven ultrasound detection of ovarian cancer.

Ovarian lesions are common and often incidentally detected. A critical shortage of expert ultrasound examiners has raised concerns of unnecessary interventions and delayed cancer diagnoses. Deep learning has shown promising results in the detection of ovarian cancer in ultrasound images; however, external validation is lacking.

Automatic detection, classification, and segmentation of sagittal MR images for diagnosing prolapsed lumbar intervertebral disc.

Magnetic resonance (MR) images are commonly used to diagnose prolapsed lumbar intervertebral disc (PLID). However, for a computer-aided diagnostic (CAD) system, distinguishing between pathological abnormalities of PLID in MR images is a challenging and intricate task. Here, we propose a comprehensive model for the automatic detection and cropping of regions of interest (ROI) from sagittal MR images using the YOLOv8 framework to solve this challenge.

Jets Downstream of Collisionless Shocks: Recent Discoveries and Challenges.

Plasma flows with enhanced dynamic pressure, known as magnetosheath jets, are often found downstream of collisionless shocks. As they propagate through the magnetosheath, they interact with the surrounding plasma, shaping its properties, and potentially becoming geoeffective upon reaching the magnetopause. In recent years (since 2016), new research has produced vital results that have significantly enhanced our understanding on many aspects of jets.

Clinical and Radiographic Parameters for Early Periodontitis Diagnosis: A Comparative Study.

Early periodontitis diagnosis is challenging due to varying staging and grading systems. While clinical parameters like bleeding on probing (BoP) and pocket depth (PD) are commonly used, periapical radiographs provide valuable information about bone loss and periodontal ligament changes. However, a clear definition of early periodontitis, particularly regarding alveolar bone crest changes, remains elusive.

Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation.

Background: Human digital twins have the potential to change the practice of personalizing cognitive health diagnosis because these systems can integrate multiple sources of health information and influence into a unified model. Cognitive health is multifaceted, yet researchers and clinical professionals struggle to align diverse sources of information into a single model.

Objective: This study aims to introduce a method called HDTwin, for unifying heterogeneous data using large language models.

Photoelectric Feedback Mechanism for Acceleration of Runaway Electrons in Gas Discharges at High Overvoltages.

Energy conservation dictates that an electron with elementary charge e traversing a vacuum gap formed by electrodes maintained at potential difference U volts acquires maximum energy of eU. In many experiments electrons with energies as high as 3eU have been observed. The experimental discovery of this effect was made over 50 years ago and is still a subject of significant controversy in applications related to x-ray generation from high voltage discharges.

Computational modeling of attractor-based neural processes involved in the preparation of voluntary actions.

Volition is conceived as a set of orchestrated executive functions, which can be characterized by features, such as reason-based and goal-directedness, driven by endogenous signals. The lateral prefrontal cortex (LPFC) has long been considered to be responsible for cognitive control and executive function, and its neurodynamics appears to be central to goal-directed cognition. In order to address both associative processes (i.

MiCK: a database of gut microbial genes linked with chemoresistance in cancer patients.

Cancer remains a global health challenge, with significant morbidity and mortality rates. In 2020, cancer caused nearly 10 million deaths, making it the second leading cause of death worldwide. The emergence of chemoresistance has become a major hurdle in successfully treating cancer patients.

Two Is Better than One: How the Addition of Multiple Biodegradable Polymers Can Improve Organic Thin-Film Transistor Performance.

Developing sustainable electronics requires using materials that are either recyclable or biodegradable, without compromising on electrical performance. Here, we introduce a solution-processed biodegradable polymer blend consisting of a diketopyrrolopyrrole-based semiconducting polymer (DPP2T) and different mixtures of two biodegradable polymers, polycaprolactone (PCL) and polylactic acid (PLA). We find that controlling the ratio of components enables a reduction in semiconductor polymer loading (∼70:80% reduction) while maintaining or improving field-effect transistor performance.

Diagnostic accuracy of neonatal structural MRI scores to predict 6-year motor outcomes of children born very preterm.

Aims: This study aimed to (1) evaluate associations between Early and Term structural MRI (sMRI) brain abnormality scores and adverse motor outcomes at 6-years corrected age (CA), (2) determine their diagnostic accuracy in predicting adverse motor outcomes and cerebral palsy (CP) at 6-years CA.

Methods: Infants born < 31-weeks gestational age (GA) returning for 6-year follow-up were included. Early and Term sMRI were scored using a validated method, deriving white matter, cortical grey matter, deep grey matter, cerebellar and global brain abnormality scores (GBAS).

SHM System for Composite Material Based on Lamb Waves and Using Machine Learning on Hardware.

There is extensive use of nondestructive test (NDT) inspections on aircraft, and many techniques nowadays exist to inspect failures and cracks in their structures. Moreover, NDT inspections are part of a more general structural health monitoring (SHM) system, where cutting-edge technologies are needed as powerful resources to achieve high performance. The high-performance aspects of SHM systems are response time, power consumption, and usability, which are difficult to achieve because of the system's complexity.