ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
A Global Spatial Similarity Optimization Scheme to Track Large Numbers of Dendritic Spines in Time-Lapse Confocal Microscopy

Dendritic spines form postsynaptic contact sites in the central nervous system. The rapid and spontaneous morphology changes of spines have been widely observed by neurobiologists. Determining the relationship between dendritic spine morphology change and its functional properties such as memory learning is a fundamental yet challenging problem in neurobiology research. In this paper, we propose a novel algorithm to track the morphology change of multiple spines simultaneously in time-lapse neuronal images based on nonrigid registration and integer programming. We also propose a robust scheme to link disappearing-and-reappearing spines. Performance comparisons with other state-of-the-art cell and spine tracking algorithms, and the ground truth show that our approach is more accurate and robust, and it is capable of tracking a large number of neuronal spines in time-lapse confocal microscopy images.
Ultra-Widefield OCT Angiography

Optical Coherence Tomography Angiography (OCTA), a functional extension of OCT, has the potential to replace most invasive fluorescein angiography (FA) exams in ophthalmology. So far, OCTA's field of view is however still lacking behind fluorescence fundus photography techniques. This is problematic, because many retinal diseases manifest at an early stage by changes of the peripheral retinal capillary network. It is therefore desirable to expand OCTA's field of view to match that of ultra-widefield fundus cameras. We present a custom developed clinical high-speed swept-source OCT (SS-OCT) system operating at an acquisition rate 8-16 times faster than today's state-of-the-art commercially available OCTA devices. Its speed allows us to capture ultra-wide fields of view of up to 90 degrees with an unprecedented sampling density and hence extraordinary resolution by merging two single shot scans with 60 degrees in diameter. To further enhance the visual appearance of the angiograms, we developed for the first time a three-dimensional deep learning based algorithm for denoising volumetric OCTA data sets. We showcase its imaging performance and clinical usability by presenting images of patients suffering from diabetic retinopathy.
Modelling unsaturated soils with the Material Point Method. A discussion of the state-of-the-art

Many natural hazards involve large deformations of unsaturated soils, e.g. rainfall-induced landslides, embankment collapses due to wetting, seepage-induced instabilities of dams and levees, etc. The study of these phenomena requires accounting for the complex hydro-mechanical interactions between solid skeleton and pore fluids and modelling large deformations to predict the post-failure behaviour, which poses significant computational challenges. In recent years, several hydro-mechanical coupled MPM formulations were developed to model saturated and unsaturated soils. These approaches are slightly different in terms of governing equations, integration schemes and have been implemented in different MPM software; thus, they benefit from various computational features. The purpose of this paper is to present an overview of the available MPM approaches to model unsaturated soils discussing differences and similarities of the formulations and their impact on the results under different conditions in a range of geotechnical applications. In addition, the effect of partially saturated conditions on the critical time step in explicit numerical integration schemes is studied for the first time. Different analytical expressions are derived and compared with the numerical results.Published by Elsevier Ltd.
The animated assessment of theory of mind for people with schizophrenia (AToMS): development and psychometric evaluation

Theory of mind (ToM) deficits in people with schizophrenia have been reported and associated with impaired social interactions. Thus, ToM deficits may negatively impact social functioning and warrant consideration in treatment development. However, extant ToM measures may place excessive cognitive demands on people with schizophrenia. Therefore, the study aimed to develop a comprehensible Assessment of ToM for people with Schizophrenia (AToMS) and evaluate its psychometric properties. The AToMs was developed in 5 stages, including item formation, expert review, content validity evaluation, animation production, and cognitive interviews of 25 people with schizophrenia. The psychometric properties of the 16-item AToMS (including reliability and validity) were then tested on 59 people with schizophrenia. The newly developed animated AToMS assesses 8 ToM concepts in the cognitive and affective dimensions while placing minimal neurocognitive demands on people with schizophrenia. The AToMS presented satisfactory psychometric properties, with adequate content validity (content validity index = 0.91); mostly moderate item difficulty (item difficulty index = 0.339-0.966); good discrimination (coefficients = 0.379-0.786), internal consistency (Cronbach's α = 0.850), and reliability (intraclass correlation coefficient = 0.901 for test-retest, 0.997 for inter-rater); and satisfactory convergent and divergent validity. The AToMS is reliable and valid for evaluating ToM characteristics in people with schizophrenia. Future studies are warranted to examine the AToMS in other populations (e.g., people with affective disorders) to cross-validate and extend its utility and psychometric evidence.
Convergence studies on iterative algorithms for image reconstruction

We introduce a general iterative scheme for image reconstruction based on Landweber's method. In our configuration, a sequential block-iterative (SeqBI) version can be readily formulated from a simultaneous block-iterative (SimBI) version, and vice versa. This provides a mechanism to derive new algorithms from known ones. It is shown that some widely used iterative algorithms, such as the algebraic reconstruction technique (ART), simultaneous ART (SART), Cimmino's, and the recently designed diagonal weighting and component averaging algorithms, are special examples of the general scheme. We prove convergence of the general scheme under conditions more general than assumed in earlier studies, for its SeqBI and SimBI versions in the consistent and inconsistent cases, respectively. Our results suggest automatic relaxation strategies for the SeqBI and SimBI versions and characterize the dependence of the limit image on the initial guess. It is found that in all cases the limit is the sum of the minimum norm solution of a weighted least-squares problem and an oblique projection of the initial image onto the null space of the system matrix.
Apply MIKE 11 model to study impacts of climate change on water resources and develop adaptation plan in the Mekong Delta, Vietnam: a case of Can Tho city

Can Tho city in the Mekong Delta is in the top ten areas affected by climate change. Therefore, assessing climate change impacts, social and economic activities require proposed solutions to respond to climate change. This study aims to (i) apply the MIKE 11 model (Hydrodynamic module and Advection-Dispersion module) to simulate the impacts of climate change scenarios on water resources in Can Tho city; (ii) calculate water balance in Can Tho city; and (iii) suggest climate change adaptation plan for sustainable social-economic activities of the city. The results show that when the rainfall changes due to climate change, the flow rate tends to decrease at high tide and increase at low tide. When the sea level rises due to climate change, the flow rate tends to increase at high tide and decrease at low tide. For 2030, the flow will decrease up to 15.6% and 14.3% at the low tide period for RCP 2.6 and RCP 8.5 compared to the present, respectively. The flow will increase up to 63.5% and 58.9% at the high tide period for RCP 2.6 and RCP 8.5 compared to the present, respectively. The water demand evaluation shows that the water resource reserve in Can Tho city meets water demands in current and future scenarios under climate change. While rainwater and groundwater can provide enough water in the rainy season, the city has to use surface water during the dry season due to a lack of rainwater. Of these, agriculture contributes the most water demands (85%). Eight adaptation measures to climate change for Can Tho city are developed from 2021 to 2050.
Texture Regulation of Metal-Organic Frameworks, Microwave Absorption Mechanism-Oriented Structural Optimization and Design Perspectives

Texture regulation of metal-organic frameworks (MOFs) is essential for controlling their electromagnetic wave (EMW) absorption properties. This review systematically summarizes the recent advancements in texture regulation strategies for MOFs, including etching and exchange of central ions, etching and exchange of ligands, chemically induced self-assembly, and MOF-on-MOF heterostructure design. Additionally, the EMW absorption mechanisms in approaches based on structure-function dependencies, including nano-micro topological engineering, defect engineering, interface engineering, and hybrid engineering, are comprehensively explored. Finally, current challenges and future research orientation are proposed. This review aims to provide new perspectives for designing MOF-derived EMW-absorption materials to achieve essential breakthroughs in mechanistic investigations in this promising field.
Building urban community resilience through university extension: community engagement and the politics of knowledge

Many land-grant universities are examining approaches to community engagement to better align with the US land-grant mission of knowledge democratization. With a growing majority of the United States' population living in urbanized spaces, it is a societal imperative for university engagement initiatives to devise strategies for engaging people on the complexity of urban issues central to individual and community wellbeing. Effective urban engagement demands collaboration and strong relationships with urban organizations and residents to co-create approaches to urban concerns. Through narrative-based inquiry, we explore urban engagements within Penn State Extension (PSE) across the Commonwealth of Pennsylvania (USA). PSE, located administratively in the College of Agricultural Sciences, is charged with carrying out Penn State's land-grant commitment to serve Pennsylvania's citizens through community engagement and nonformal education in the agricultural and food, human, and social sciences. We examine extension educator and faculty practices, program development, community engagements, and experiences, and those of community stakeholders. This work draws upon democratic methods to uncover the undergirding philosophies of engagement within PSE and how communities experience those engagements. This project offers an entry-point to longer-term applied research to develop a broadly applicable theory and praxis of translational research, engagement, and change privileging urban community resilience.
Eosinophilic granulomatosis with polyangiitis

This review aims to describe the epidemiology, pathogenesis, clinical manifestations, diagnosis, treatment, and prognosis of eosinophilic granulomatosis with polyangiitis (EGPA). Eosinophilic granulomatosis with polyangiitis is a small to medium vessel necrotizing vasculitis, typically classified with granulomatosis with polyangiitis (GPA) and microscopic polyangitis (MPA) as antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). However, less than 50% of patients with EGPA have a positive ANCA test. Among all the vasculitides, asthma and eosinophilia are unique features of EGPA. Eosinophilic granulomatosis with polyangiitis is very rare and the diagnosis may be missed as the disease evolves over time. Polyneuropathies are common and may be severe, requiring aggressive immunosuppressive therapy. Heart involvement is the most common cause of death in EGPA. Biopsy of involved tissue supports a clinically suspected diagnosis but is not always feasible. Treatment of EGPA is primarily dictated by the severity of disease and prognostic factors. More severe disease frequently requires the use of aggressive therapy such as cyclophosphamide. Once treatment is initiated, patients can achieve good control of symptoms; unfortunately, disease relapses are common and prolonged treatment with corticosteroids is often necessary for asthma management. A better understanding of the disease heterogeneity is needed for the development of better therapies.
Emotional Creativity in Art Education: An Exploratory Analysis and Research Trends

The emotions that human beings experience have a key role in the environments in which they operate. In art education, creative processes are influenced by the emotions and experiences lived by the individual, enabling a more emotional and creative design to make life more pleasant. The aim was to examine the research during the period 1917-2020 on the development of emotional creativity in art education. Mathematical and statistical techniques were applied to 984 articles carried from Elsevier's Scopus database. The findings yielded data on the scientific productivity of the journal, authors, research institutions, and countries/territories that promoted this field. The data showed an exponential trend, mostly in the last decade. Five lines of research stand out: emotion, higher education, education, art, and leadership. Moreover, five future research directions related to visual art education, affective paradigm, metacompetency, expressive arts therapy group, and cognitive empathy were detected. This study establishes the link between psychology, neuroscience, and artistic education to constitute the decision-making of the promoters of this topic of research. The analysis of international research allowed us to focus the future publications of academics and researchers, in addition to guaranteeing an adequate approach to the objectives of the institutions and funding centers.
Boundary Objects: Engaging and Bridging Needs of People in Participatory Research by Arts-Based Methods

Background: Participatory health research (PHR) is a research approach in which people, including hidden populations, share lived experiences about health inequities to improve their situation through collective action. Boundary objects are produced, using arts-based methods, to be heard by stakeholders. These can bring about dialogue, connection, and involvement in a mission for social justice. This study aims to gain insight into the value and ethical issues of boundary objects that address health inequalities. A qualitative evaluation is conducted on three different boundary objects, created in different participatory studies with marginalized populations (mothers in poverty, psychiatric patients, and unemployed people). A successful boundary object evokes emotions among those who created the objects and those encountering these objects. Such objects move people and create an impulse for change. The more provocative the object, the more people feel triggered to foster change. Boundary objects may cross personal boundaries and could provoke feelings of discomfort and ignorance. Therefore, it is necessary to pay attention to ethics work. Boundary objects that are made by people from hidden populations may spur actions and create influence by improving the understanding of the needs of hidden populations. A dialogue about these needs is an essential step towards social justice.
Enhanced Acidic Water Oxidation by Dynamic Migration of Oxygen Species at the Ir/Nb2 O5-x Catalyst/Support Interfaces

Catalyst/support interaction plays a vital role in catalysis towards acidic oxygen evolution (OER), and the performance reinforcement is currently interpreted by either strain or electron donation effect. We herein report that these views are insufficient, where the dynamic evolution of the interface under potential bias must be considered. Taking Nb2 O5-x supported iridium (Ir/Nb2 O5-x ) as a model catalyst, we uncovered the dynamic migration of oxygen species between IrOx and Nb2 O5-x during OER. Direct spectroscopic evidence combined with theoretical computation suggests these migrations not only regulate the in situ Ir structure towards boosted activity, but also suppress its over-oxidation via spontaneously delivering excessive oxygen from IrOx to Nb2 O5-x . The optimized Ir/Nb2 O5-x thus demonstrated exceptional performance in scalable water electrolyzers, i.e., only need 1.839 V to attain 3 A cm-2 (surpassing the DOE 2025 target), and no activity decay during a 2000 h test at 2 A cm-2 .
Periodontal Management of Gummy Smile Due to Altered Passive Eruption: A Case Report

Today's population is expanding quickly, and there is a growing desire for aesthetics. Smiles and other friendly facial expressions communicate joy and assurance. They are the essential elements of nonverbal communication and play a significant part in establishing a person's first impression. The altered passive eruption, which results in the excessive gingival display (EGD) when the gingival edge is situated incisal to the cervical convexity of the crown, is one of the factors affecting aesthetics. It has an impact on the patient's appearance and grin. The management of EGD becomes crucial. The following case study covers the control of EGD with a crown lengthening operation.
Automated Multi-Sensor 3D Reconstruction for the Web

The Internet has become a major dissemination and sharing platform for 3D content. The utilization of 3D measurement methods can drastically increase the production efficiency of 3D content in an increasing number of use cases where 3D documentation of real-life objects or environments is required. We demonstrated a developed, highly automated and integrated content creation process of providing reality-based photorealistic 3D models for the web. Close-range photogrammetry, terrestrial laser scanning (TLS) and their combination are compared using available state-of-the-art tools in a real-life project setting with real-life limitations. Integrating photogrammetry and TLS is a good compromise for both geometric and texture quality. Compared to approaches using only photogrammetry or TLS, it is slower and more resource-heavy but combines complementary advantages of each method, such as direct scale determination from TLS or superior image quality typically used in photogrammetry. The integration is not only beneficial, but clearly productionally possible using available state-of-the-art tools that have become increasingly available also for non-expert users. Despite the high degree of automation, some manual editing steps are still required in practice to achieve satisfactory results in terms of adequate visual quality. This is mainly due to the current limitations of WebGL technology.
A Hybrid CMOS-Memristor Neuromorphic Synapse

Although data processing technology continues to advance at an astonishing rate, computers with brain-like processing capabilities still elude us. It is envisioned that such computers may be achieved by the fusion of neuroscience and nano-electronics to realize a brain-inspired platform. This paper proposes a high-performance nano-scale Complementary Metal Oxide Semiconductor (CMOS)-memristive circuit, which mimics a number of essential learning properties of biological synapses. The proposed synaptic circuit that is composed of memristors and CMOS transistors, alters its memristance in response to timing differences among its pre- and post-synaptic action potentials, giving rise to a family of Spike Timing Dependent Plasticity (STDP). The presented design advances preceding memristive synapse designs with regards to the ability to replicate essential behaviours characterised in a number of electrophysiological experiments performed in the animal brain, which involve higher order spike interactions. Furthermore, the proposed hybrid device CMOS area is estimated as 600 mu m(2) in a 0.35 mu m process-this represents a factor of ten reduction in area with respect to prior CMOS art. The new design is integrated with silicon neurons in a crossbar array structure amenable to large-scale neuromorphic architectures and may pave the way for future neuromorphic systems with spike timing-dependent learning features. These systems are emerging for deployment in various applications ranging from basic neuroscience research, to pattern recognition, to Brain-Machine-Interfaces.
Robust Learning-Based Parsing and Annotation of Medical Radiographs

In this paper, we propose a learning-based algorithm for automatic medical image annotation based on robust aggregation of learned local appearance cues, achieving high accuracy and robustness against severe diseases, imaging artifacts, occlusion, or missing data. The algorithm starts with a number of landmark detectors to collect local appearance cues throughout the image, which are subsequently verified by a group of learned sparse spatial configuration models. In most cases, a decision could already be made at this stage by simply aggregating the verified detections. For the remaining cases, an additional global appearance filtering step is employed to provide complementary information to make the final decision. This approach is evaluated on a large-scale chest radiograph view identification task, demonstrating a very high accuracy (> 99.9%) for a posteroanterior/anteroposterior (PA-AP) and lateral view position identification task, compared with the recently reported large-scale result of only 98.2% (Luo, et al., 2006). Our approach also achieved the best accuracies for a three-class and a multiclass radiograph annotation task, when compared with other state of the art algorithms. Our algorithm was used to enhance advanced image visualization workflows by enabling content-sensitive hanging-protocols and auto-invocation of a computer aided detection algorithm for identified PA-AP chest images. Finally, we show that the same methodology could be utilized for several image parsing applications including anatomy/organ region of interest prediction and optimized image visualization.
An Exploration of Dance Learning Stress Sources of Elementary School Dance Class Students with Artistic Abilities: The Influences of Psychological Capital and Self-Concept

The purpose of this study is to explore the factors which may cause the increase of students' stress in dance class in elementary school. In this study, students' demographic variables, psychological capital (which includes four sub-constructs), and self-concept (which includes five sub-constructs) were used as predicting variables to estimate their influences on dance class students' stress level. A structured questionnaire was distributed to 450 elementary art talent class students with 412 valid responses. Structural equation modeling was used to test the relationships proposed by the study. As for demographic variables, the results show that the grade, gender, and the dance class hours per week had no significant influences on stress, while the seniority level had a negative influence, which indicated that junior dance students had more stress than senior students. As for psychological capital, self-efficacy and optimism had negative influences on stress, while the other two sub-constructs, hope and resilience, did not have a significant influence on stress. As for physical self-concept, the worry of overweight had positive influences on their stress, while appearance, physical ability performance, health status, and satisfaction of body parts had no significant influence on stress. Based on the research findings, suggestions were made to reduce students' pressure in learning dance.