ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Hyper-glycemia and insulinemia induce morphological changes and modulate secretion of S100B, S100A8, amyloid β 1-40 and amyloid β 1-42, in a model of human dopaminergic neurons

Glucose metabolism in neuronal tissue declines during neurodegenerative disorders in a progressive, region-specific, and disease-specific manner. Studies have shown that extracellular hyper-glycemia affects the functioning of adenosine triphosphate (ATP) sensitive potassium channels located in neurons and astrocytes. Also, hyper-insulinemia contributes to the formation and progression of Alzheimer's disease (AD) via competition with amyloid β (Aβ) for insulin-degrading enzyme. Aβ disruption is phosphatidylinositol 3-kinase pathway dependent, and increased circulatory insulin concentrations lead to Aβ accumulation. In 2008, based on assessment of brain glucose utilization disorders and insulin signaling disruptions, it was proposed that AD could be called "type III diabetes". Proteins from the S100 family are actively secreted during metabolic and oxidative stress, but their role in neuronal cells has yet to be clarified. However, it has been demonstrated that they act in a dose-dependent manner, which may be crucial in the modulation of glucose and insulin metabolism in the brain. The goal of this paper was to elucidate the association between high glucose and insulin concentrations with extra- and intracellular S100B and S100A8 proteins levels as well as the correlation with toxic (Aβ42) and physiologic (Aβ40) forms of Aβ. Medium and high glucose concentrations mimicking pre-diabetic and diabetic state, caused statistically significant discharge of S100b and S100A8 protein to the extracellular compartment. Similar effect was observed after 50 nM insulin incubation. Furthermore, the correlation coefficient patterns between those proteins shows similar associations which highlights possible effective and modulating role of S100 family in the metabolic disturbances occurring in neuropathological disorders.
Chipless RFID Printing Technologies: A State of the Art

Recently, the field of flexible electronics has received significant research attention, primarily in response to the growing market for lightweight and compact devices. The low-cost mass fabrication of these flexible-electronic printed products, such as RF identification (RFID) tags, wireless sensors, conductive tags and readers, touchpads for keyboards, and display applications, all require knowledge of additive production techniques and appropriate substrates.
The Sustainability of Rock Art: Preservation and Research

Rock art is a widespread cultural heritage, representing an immovable element of the material culture created on natural rocky supports. Paintings and petroglyphs can be found within caves and rock shelters or in open-air contexts and for that reason they are not isolated from the processes acting at the Earth surface. Consequently, rock art represents a sort of ecosystem because it is part of the complex and multidirectional interplay between the host rock, pigments, environmental parameters, and microbial communities. Such complexity results in several processes affecting rock art; some of them contribute to its destruction, others to its preservation. To understand the effects of such processes an interdisciplinary scientific approach is needed. In this contribution, we discuss the many processes acting at the rock interface-where rock art is present-and the multifaceted possibilities of scientific investigations-non-invasive or invasive-offered by the STEM disciplines. Finally, we suggest a sustainable approach to investigating rock art allowing to understand its production as well as its preservation and eventually suggest strategies to mitigate the risks threatening its stability.
Tree-Based Kernel for Graphs With Continuous Attributes

The availability of graph data with node attributes that can be either discrete or real-valued is constantly increasing. While existing Kernel methods are effective techniques for dealing with graphs having discrete node labels, their adaptation to nondiscrete or continuous node attributes has been limited, mainly for computational issues. Recently, a few kernels especially tailored for this domain, and that trade predictive performance for computational efficiency, have been proposed. In this brief, we propose a graph kernel for complex and continuous nodes' attributes, whose features are tree structures extracted from specific graph visits. The kernel manages to keep the same complexity of the state-of-the-art kernels while implicitly using a larger feature space. We further present an approximated variant of the kernel, which reduces its complexity significantly. Experimental results obtained on six real-world data sets show that the kernel is the best performing one on most of them. Moreover, in most cases, the approximated version reaches comparable performances to the current state-of-the-art kernels in terms of classification accuracy while greatly shortening the running times.
Situational Strength as a Lens to Understand the Strain Implications of Extra-Normative Work

Employees must often perform work outside of the time and/or space requirements that typically define their job role (e.g., working after-hours, teleworking), especially during the COVID-19 pandemic. We introduce the concept of extra-normative work to capture this idea and draw on situational strength theory to test the seemingly paradoxical hypotheses that (1) the effects of extra-normative work are more harmful to employee strain when this work represents a stronger situation (i.e., one that unambiguously prescribes expected behavior), relative to when this work represents a weaker situation (i.e., one that allows for greater personal choice and behavioral latitude), but that (2) this strain is diminished when situational strength is achieved by maximizing the clarity and consistency of extra-normative work, while this strain is enhanced when situational strength is achieved by imposing greater constraints and consequences surrounding extra-normative work. These predictions were supported in an experimental vignette study, a survey focused on after-hours work experiences, and an investigation of telework in response to COVID-19. We discuss the theoretical implications of viewing extra-normative work through the lens of situational strength, while also outlining how our findings inform best practices surrounding how to communicate about and frame extra-normative work to employees.
Emergence in Interactive Artistic Visualization

This research draws on theories of emergence to inform the creation of an artistic and direct visualization. This is an interactive artwork and drawing tool for creative participant experiences. Emergence is characteristically creative and many different models of emergence exist. It is therefore possible to effect creativity through the application of emergence mechanisms from these different disciplines. A review of theories of emergence and examples of visualization in the arts, is provided. An art project led by the author is then discussed in this context. This project, Iterative Intersections, is a collaboration with community artists from Cerebral Palsy League. It has resulted in a number of creative outcomes including the interactive art application, Of me with me. Analytical discussion of this work shows how its construction draws on aspects of experience design, fractal and emergent theory to effect perceptual emergence and creative experience as well as to facilitate self-efficacy.
Freehand scanning photoacoustic microscopy with simultaneous localization and mapping

Optical-resolution photoacoustic microscopy offers high-resolution, label-free hemodynamic and functional imaging to many biomedical applications. However, long-standing technical barriers, such as limited field of view, bulky scanning probes, and slow imaging speed, have limited the application of optical-resolution photoacoustic microscopy. Here, we present freehand scanning photoacoustic microscopy (FS-PAM) that can flexibly image various anatomical sites. We develop a compact handheld photoacoustic probe to acquire 3D images with high speed, and great flexibility. The high scanning speed not only enables video camera mode imaging but also allows for the first implementation of simultaneous localization and mapping (SLAM) in photoacoustic microscopy. We demonstrate fast in vivo imaging of some mouse organs, and human oral mucosa. The high imaging speed greatly reduces motion artifacts and distortions from tissue moving, breathing, and unintended handshaking. We demonstrate small-lesion localization in a large region of the brain. FS-PAM offers a flexible high-speed imaging tool with an extendable field of view, enabling more biomedical imaging applications.
Multiple Beamforming with Perfect Coding

Perfect Space-Time Block Codes (PSTBCs) achieve full diversity, full rate, nonvanishing constant minimum determinant, uniform average transmitted energy per antenna, and good shaping. However, the high decoding complexity is a critical issue for practice. When the Channel State Information (CSI) is available at both the transmitter and the receiver, Singular Value Decomposition (SVD) is commonly applied for a Multiple-Input Multiple-Output (MIMO) system to enhance the throughput or the performance. In this paper, two novel techniques, Perfect Coded Multiple Beamforming (PCMB) and Bit-Interleaved Coded Multiple Beamforming with Perfect Coding (BICMB-PC), are proposed, employing both PSTBCs and SVD with and without channel coding, respectively. With CSI at the transmitter (CSIT), the decoding complexity of PCMB is substantially reduced compared to a MIMO system employing PSTBC, providing a new prospect of CSIT. Especially, because of the special property of the generation matrices, PCMB provides much lower decoding complexity than the state-of-the-art SVD-based uncoded technique in dimensions 2 and 4. Similarly, the decoding complexity of BICMB-PC is much lower than the state-of-the-art SVD-based coded technique in these two dimensions, and the complexity gain is greater than the uncoded case. Moreover, these aforementioned complexity reductions are achieved with only negligible or modest loss in performance.
High-resolution cortical MAP-MRI reveals areal borders and laminar substructures observed with histological staining

The variations in cellular composition and tissue architecture measured with histology provide the biological basis for partitioning the brain into distinct cytoarchitectonic areas and for characterizing neuropathological tissue alterations. Clearly, there is an urgent need to develop whole-brain neuroradiological methods that can assess cortical cyto- and myeloarchitectonic features non-invasively. Mean apparent propagator (MAP) MRI is a clinically feasible diffusion MRI method that quantifies efficiently and comprehensively the net microscopic displacements of water molecules diffusing in tissues. We investigate the sensitivity of high-resolution MAP-MRI to detecting areal and laminar variations in cortical cytoarchitecture and compare our results with observations from corresponding histological sections in the entire brain of a rhesus macaque monkey. High-resolution images of MAP-derived parameters, in particular the propagator anisotropy (PA), non-gaussianity (NG), and the return-to-axis probability (RTAP) reveal cortical area-specific lamination patterns in good agreement with the corresponding histological stained sections. In a few regions, the MAP parameters provide superior contrast to the five histological stains used in this study, delineating more clearly boundaries and transition regions between cortical areas and laminar substructures. Throughout the cortex, various MAP parameters can be used to delineate transition regions between specific cortical areas observed with histology and to refine areal boundaries estimated using atlas registration-based cortical parcellation. Using surface-based analysis of MAP parameters we quantify the cortical depth dependence of diffusion propagators in multiple regions-of-interest in a consistent and rigorous manner that is largely independent of the cortical folding geometry. The ability to assess cortical cytoarchitectonic features efficiently and non-invasively, its clinical feasibility, and translatability make high-resolution MAP-MRI a promising 3D imaging tool for studying whole-brain cortical organization, characterizing abnormal cortical development, improving early diagnosis of neurodegenerative diseases, identifying targets for biopsies, and complementing neuropathological investigations.
A Novel Approach for Bi-Level Segmentation of Tuberculosis Bacilli Based on Meta-Heuristic Algorithms

Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.
Update on the use of ultrasound in the diagnosis and monitoring of the critical patient

Hemodynamic and respiratory complications are the main causes of morbidity and mortality in in critical care units (CCU). Imaging techniques are a key tool in differential diagnosis and treatment. In the last decade, ultrasound has shown great potential for bedside diagnosis of respiratory disease, as well as for the hemodynamic assessment of critically ill patients. Ultrasound has proven to be a useful guide for identifying the type of shock, estimating cardiac output, guiding fluid therapy and vasoactive drugs, providing security in the performance of percutaneous techniques (thoracentesis, pericardiocentesis, evacuation of abscesses/hematomas), detecting dynamically in real time pulmonary atelectasis and its response to alveolar recruitment maneuvers, and predicting weaning failure from mechanical ventilation. Due to its dynamic nature, simple learning curve and absence of ionizing radiation, it has been incorporated as an essential tool in daily clinical practice in CCUs. The objective of this review is to offer a global vision of the role of ultrasound and its applications in the critically ill patient.
Fast near-maximum likelihood phase estimation of X-ray pulsars

This letter addresses the problem of X-ray pulsar radiation phase estimation, encountered in research works concerning autonomous deep space navigation systems. Autonomous navigation systems represent an intriguing solution to be employed when Earth-assisted navigation is not viable for long range missions. In such applications. X-ray pulsars, as well as other celestial objects, may be employed as peculiar beacons to allow the spacecrafts to adjust their own route. State of the art techniques for estimation of X-ray pulsar radiation phase involve maximization of generally nonconvex objective functions, thus resulting in computationally onerous procedures. Here, we show how the problem of pulsar phase estimation can be recast as a cyclic shift parameter estimation problem under multinomial distributed observations, whose maximum likelihood solution can be implemented by means of a fast, Discrete Fourier Transform based procedure. Numerical results show how the herein described fast, near maximum likelihood, estimator favorably compares with selected state of the art estimators, while presenting a significantly reduced computational complexity. (C) 2012 Elsevier B.V. All rights reserved.
Chroma binary similarity and local alignment applied to cover song identification

We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the music: information retrieval (MIR) community along in the past, as it provides a direct and objective. way to evaluate music similarity algorithms. This paper first presents a series of experiments carried out with two state-of-the-art methods for cover song identification. We have studied several components of these (such as chroma resolution and similarity, transposition, beat tracking or dynamic time warping constraints), in order to discover which characteristics would be desirable for a competitive cover song identifier. After analyzing many cross-validated results, the importance of these. characteristics is discussed, and the best performing ones are finally applied to the newly proposed method. Multiple evaluations of this one confirm a large increase in identification accuracy when comparing it with alternative state-of-the-art approaches.
Validation of Flow Cytometry and Magnetic Bead-Based Methods to Enrich CNS Single Cell Suspensions for Quiescent Microglia

Microglia are resident mononuclear phagocytes within the CNS parenchyma that intimately interact with neurons and astrocytes to remodel synapses and extracellular matrix. We briefly review studies elucidating the molecular pathways that underlie microglial surveillance, activation, chemotaxis, and phagocytosis; we additionally place these studies in a clinical context. We describe and validate an inexpensive and simple approach to obtain enriched single cell suspensions of quiescent parenchymal and perivascular microglia from the mouse cerebellum and hypothalamus. Following preparation of regional CNS single cell suspensions, we remove myelin debris, and then perform two serial enrichment steps for cells expressing surface CD11b. Myelin depletion and CD11b enrichment are both accomplished using antigen-specific magnetic beads in an automated cell separation system. Flow cytometry of the resultant suspensions shows a significant enrichment for CD11b(+)/CD45(+) cells (perivascular microglia) and CD11b(+)/CD45(-) cells (parenchymal microglia) compared to starting suspensions. Of note, cells from these enriched suspensions minimally express Aif1 (aka Iba1), suggesting that the enrichment process does not evoke significant microglial activation. However, these cells readily respond to a functional challenge (LPS) with significant changes in the expression of molecules specifically associated with microglia. We conclude that methods employing a combination of magnetic-bead based sorting and flow cytometry produce suspensions highly enriched for microglia that are appropriate for a variety of molecular and cellular assays.
Effects of fluids on the surface generation in material removal processes - Molecular dynamics simulation

Molecular dynamics (MD) simulation has been attractive in order to gain deeper understanding of microscopic material behavior and have been applied to study various materials properties and phenomena. Most of the MD material removal process simulations were focusing on the material removal mechanisms, chip and surface generation. The state-of-the-art in MD grinding, scratching, cutting or indentation simulation did not consider fluids or an atmosphere (neither gas nor liquid). Hence, the environment represents high vacuum with no heat convection. In this contribution we will describe an extension of the state-of-the-art MD material removal process modeling to consider fluids like coolants and elaborate on its impact on the surface generation and the tribological contact conditions on basis of MD simulation results.
Can changes in 3D genome architecture create new regulatory landscapes that contribute to phenotypic evolution?

Animal genomes are compartmentalized into insulated regulatory units named topology-associated domains (TADs). TADs insulate gene promoters from enhancers that occupy neighboring TADs. Chromosomal rearrangements that disrupt TAD structure can generate new regulatory interactions between enhancers and promoters that were once separated into different TADs, which might lead to new gene expression patterns. On the one hand, TAD rearrangements are known to cause deleterious phenotypes, but, on the other hand, rearrangements can also create novel expression patterns that may be selected during evolution because they generate advantageous phenotypes. Here, we review recent studies that explore the effects of chromosomal rearrangements and genetic perturbations on TAD structure and gene regulation in the context of development and evolution. We discuss the possible contribution of evolutionary breakpoints (EBRs) that affect TAD structure to the evolution of gene regulation and the phenotype.
The deposition mapping of polycyclic aromatic hydrocarbons in megacity Shanghai, China

The deposition of polycyclic aromatic hydrocarbon (PAHs) has far-reaching impacts on Earth's surface system and human health. However, a comprehensive understanding of PAHs' deposition in a high urbanized area is still lacking because of limited field measurements data and rough resolution of current models. In this research, a deposition map of PAHs with a resolution of 2 × 2 km in megacity Shanghai, China was established. Gridded annual total deposition of PAHs from July 2020 to June 2021 ranged from 385 to 10,631 ng/(m2·d), with a mean value of 2,611 ng/(m2·d). The highest PAHs deposition was found over the downtown Shanghai, which received 4.3 times the deposition flux of outlying areas. About 77 % of area in Shanghai was dominated by wet deposition which accounted for 62 % of total deposition in Shanghai. The total deposition showed a trend of summer>fall>spring>winter, which was similar to that of the amount of rain. Source apportionment and geographically weighted regression analysis showed that built-up land and human activities are key driving factors of PAHs' deposition in Shanghai. Our results suggest that intensive human activities could alter the PAHs deposition distribution in Shanghai, and improve the understanding of PAHs' environmental behavior in high urbanized area.