Phosphorus-based heterojunction tunnel field-effect transistors: from atomic insights to circuit renovations.

Tunnel field-effect transistors (TFETs) are gaining interest for low-power applications, but challenges like poor drive current, delayed saturation, and ambipolarity can hinder their performance. This work proposes a dopingless heterojunction TFET (DL-HTDET) utilizing advanced materials, all based on phosphorus, to address these issues. Our approach involves a comprehensive and accurate analysis of the DL-HTDET's behavior.

The MARVIN Hypothesis: Linking Unhealthy Lifestyles to Intracranial Aneurysm Rupture Risk and Clinical Prognosis.

: The rising incidence of modifiable lifestyle risk factors and cardiovascular diseases, driven by poor diet, inactivity, excessive alcohol use, and smoking, may influence the development and rupture of intracranial aneurysms (IA). This study aimed to examine the impact of lifestyle-related and cardiovascular risk factors on IA rupture and patient outcomes. : We developed the "MARVIN" (Metabolic and Adverse Risk Factors and Vices Influencing Intracranial Aneurysms) model and conducted a retrospective analysis of 303 patients with 517 IAs, treated between 2007 and 2020.

Development and Assessment of a High-Fidelity Simulator for the Microsurgical Dissection of the Sylvian Fissure.

Background: The dissection of the Sylvian fissure (SF) is a crucial technique requiring considerable expertise and skills traditionally acquired through years of experience. The continuous decline in surgical case-load necessitates the development of efficient alternative training opportunities. However, building a realistic and effective training simulator for the microsurgical dissection of the SF as an integral part of the neurosurgical curriculum remains a challenging endeavor.

Sex Differences in Intracranial Aneurysms: A Matched Cohort Study.

Aneurysmal subarachnoid hemorrhage (SAH) predominantly affects women, accounting for 65% of cases. Women have a 1.3 times higher relative risk than men, with the incidence rising particularly in women aged 55-85 years.

Intracranial Aneurysms and Cerebral Small Vessel Disease: Is There an Association between Large- and Small-Artery Diseases?

: Intracranial aneurysms (IAs) may be connected to interactions between large and small intracranial vessels. We aimed to investigate the association between IAs and cerebral small-vessel disease (CSVD) and assess CSVD impact on IA patient management. : This retrospective study analyzed clinical data and MRI features of CSVD in 192 subarachnoid hemorrhage (SAH) patients: 136 with incidental IA, 147 with severe CSVD without SAH/IA, and 50 controls without SAH, IA, or severe CSVD.

Anterior interhemispheric vs. pterional approach in the microsurgical management of anterior communicating artery aneurysms: a comparative analysis employing a novel multidimensional matching-tool.

The surgical management of anterior communicating artery aneurysms (AcomA) is challenging due to their deep midline position and proximity to complex skull base anatomy. This study compares the pterional craniotomy with the interhemispheric approach based on the specific aneurysm angulation. A total of 129 AcomA cases were analyzed, with 50 undergoing microsurgical clipping via either the pterional or interhemispheric approach.

Pterional vs. lateral supraorbital approach in the management of middle cerebral artery aneurysms: insights from a phantom model study.

The pterional approach has traditionally been employed for managing middle cerebral artery (MCA) aneurysms. With potential benefits like reduced surgical morbidity and improved postoperative recovery, the lateral supraorbital approach (LSO) should be considered individually based on aneurysm morphology, location and patient-specific variations of the MCA anatomy, which requires considerable technical expertise traditionally acquired through years of experience. The goal of this study was the development and evaluation of a novel phantom simulator in the context of clinical decision-making in the managmement of MCA aneurysms.

Virtual Reality vs Phantom Model: Benefits and Drawbacks of Simulation Training in Neurosurgery.

Background And Objectives: Traditional neurosurgical education has relied heavily on the Halstedian "see one, do one, teach one" approach which is increasingly perceived as inefficient in contemporary settings marked by a steady decline in surgical caseload. In recent years, simulation training has emerged as an effective and accessible training alternative. To date, however, there is no standardized criterion pertaining to the quality and implementation of simulators in neurosurgical education and training.

Enlarged tumefactive perivascular, or Virchow-Robin, spaces and hydrocephalus: do we need to treat? Illustrative cases.

Background: Perivascular spaces (PVSs) are spaces in brain parenchyma filled with interstitial fluid surrounding small cerebral vessels. Massive enlargements of PVSs are referred to as "giant tumefactive perivascular spaces" (GTPVSs), which can be classified into three types depending on their localization. These lesions are rare, predominantly asymptomatic, and often initially misinterpreted as cystic tumor formations.

Unveiling rupture risk and clinical outcomes in midline aneurysms: A matched cohort analysis investigating the impact of localization within the anterior or posterior circulation.

Intracranial aneurysms (IAs) located in the anterior and posterior circulations of the Circle of Willis present differential rupture risks. This study aimed to compare the rupture risk and clinical outcomes of anterior communicating artery aneurysms (AcomA) and basilar tip aneurysms (BAs); two IA types located along the midline within the Circle of Willis. We retrospectively collected data from 1026 patients presenting with saccular IAs.

Artificial intelligence in cardiac computed tomography.

Artificial Intelligence (AI) is a broad discipline of computer science and engineering. Modern application of AI encompasses intelligent models and algorithms for automated data analysis and processing, data generation, and prediction with applications in visual perception, speech understanding, and language translation. AI in healthcare uses machine learning (ML) and other predictive analytical techniques to help sort through vast amounts of data and generate outputs that aid in diagnosis, clinical decision support, workflow automation, and prognostication.

4Dflow-VP-Net: A deep convolutional neural network for noninvasive estimation of relative pressures in stenotic flows from 4D flow MRI.

Purpose: To estimate relative transvalvular pressure gradient (TVPG) noninvasively from 4D flow MRI.

Methods: A novel deep learning-based approach is proposed to estimate pressure gradient across stenosis from four-dimensional flow MRI (4D flow MRI) velocities. A deep neural network 4D flow Velocity-to-Presure Network (4Dflow-VP-Net) was trained to learn the spatiotemporal relationship between velocities and pressure in stenotic vessels.

Probiotics in vaginal health.

Bacterial vaginosis, a type of vaginal inflammation, can be considered the main reason for abnormal discharges of the vagina and vaginal dysbiosis during reproductive years. Epidemiological investigations of females suffering from vaginitis demonstrated that at least 30% to 50% of all women had Bacterial vaginosis (BV). One of the fields of treatment is the use of probiotics, probiotics are commonly defined as viable microorganisms (yeasts or bacteria) that can positively affect the health of their hosts.

The association between penile cancer and HIV infection: A literature review.

Penile cancer is a rare malignancy which HIV infection appears to increase the risk of. The magnitude of this risk and the pathogenesis remain unclear. A comprehensive review of the literature was undertaken using conventional search strategies.

Rural vulnerability to water scarcity in Iran: an integrative methodology for evaluating exposure, sensitivity and adaptive capacity.

Unlabelled: The water crisis is the main stress in arid and semi-arid areas, especially in rural areas where agriculture is the main livelihood. This study assessed vulnerability to water scarcity in six rural regions of Isfahan, Iran. These areas have lost their primary water source of agriculture, the Zayandeh Rud River, since 2006.

Overcoming Barriers in Neurosurgical Education: A Novel Approach to Practical Ventriculostomy Simulation.

Background: In the high-risk, high-stakes specialty of neurosurgery, traditional teaching methods often fail to provide young residents with the proficiency needed to perform complex procedures in stressful situations, with direct effects on patient outcomes. Physical simulators provide the freedom of focused, hands-on training in a more controlled environment. However, the adoption of simulators in neurosurgical training remains a challenge because of high acquisition costs, complex production processes, and lack of realism.

FlowRAU-Net: Accelerated 4D Flow MRI of Aortic Valvular Flows With a Deep 2D Residual Attention Network.

In this work, we propose a novel deep learning reconstruction framework for rapid and accurate reconstruction of 4D flow MRI data. Reconstruction is performed on a slice-by-slice basis by reducing artifacts in zero-filled reconstructed complex images obtained from undersampled k-space. A deep residual attention network FlowRAU-Net is proposed, trained separately for each encoding direction with 2D complex image slices extracted from complex 4D images at each temporal frame and slice position.

Relative pressure estimation from 4D flow MRI using generalized Bernoulli equation in a phantom model of arterial stenosis.

Objective: Arterial stenosis is a significant cardiovascular disease requiring accurate estimation of the pressure gradients for determining hemodynamic significance. In this paper, we propose Generalized Bernoulli Equation (GBE) utilizing interpolated-based method to estimate relative pressures using streamlines and pathlines from 4D Flow MRI.

Methods: 4D Flow MRI data in a stenotic phantom model and computational fluid dynamics simulated velocities generated under identical flow conditions were processed by Generalized Bernoulli Equation (GBE), Reduced Bernoulli Equations (RBE), as well as the Simple Bernoulli Equation (SBE) which is clinically prevalent.

VR-based training of craniotomy for intracranial aneurysm surgery.

Purpose: Intracranial aneurysms can be treated micro-surgically. This procedure involves an appropriate head position of the patient and a proper craniotomy. These steps enable a proper access, facilitating the subsequent steps.

Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge.

Lung cancer is by far the leading cause of cancer death in the US. Recent studies have demonstrated the effectiveness of screening using low dose CT (LDCT) in reducing lung cancer related mortality. While lung nodules are detected with a high rate of sensitivity, this exam has a low specificity rate and it is still difficult to separate benign and malignant lesions.

Chamberless NDIR CO Sensor Robust against Environmental Fluctuations.

Accuracy of CO measurement is affected by ambient air fluctuations, making the compensation of such variations in drift-like sensor response essential for concentration level assessment. Here, a series of experiments were carried out with a chamberless approach in a nondispersive infrared (NDIR) gas sensor to examine the combined effect of environmental temperature and relative humidity fluctuations on sensor responses at different concentrations of CO. To eliminate the drift-like terms caused by environmental fluctuations, the behavior of the sensor was modeled to include ambient temperature, relative humidity, the measured responses as the inputs, and the concentration level as the output.

A Unified Optimization for Resilient Dynamic Event-Triggering Consensus Under Denial of Service.

This article proposes a resilient framework for optimized consensus using a dynamic event-triggering (DET) scheme, where the multiagent system (MAS) is subject to denial-of-service (DoS) attacks. When initiated by an adversary, DoS blocks the local and neighboring communication channels in the network. A distributed DET scheme is utilized to limit transmissions between the neighboring agents.

Lung Nodule Malignancy Prediction From Longitudinal CT Scans With Siamese Convolutional Attention Networks.

We propose a convolutional attention-based network that allows for use of pre-trained 2-D convolutional feature extractors and is extendable to multi-time-point classification in a Siamese structure. Our proposed framework is evaluated for single- and multi-time-point classification to explore the value that temporal information, such as nodule growth, adds to malignancy prediction. Our results show that the proposed method outperforms a comparable 3-D network with less than half the parameters on single-time-point classification and further achieves performance gains on multi-time-point classification.