ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Generative-Discriminative Basis Learning for Medical Imaging

This paper presents a novel dimensionality reduction method for classification in medical imaging. The goal is to transform very high-dimensional input (typically, millions of voxels) to a low-dimensional representation (small number of constructed features) that preserves discriminative signal and is clinically interpretable. We formulate the task as a constrained optimization problem that combines generative and discriminative objectives and show how to extend it to the semi-supervised learning (SSL) setting. We propose a novel large-scale algorithm to solve the resulting optimization problem. In the fully supervised case, we demonstrate accuracy rates that are better than or comparable to state-of-the-art algorithms on several datasets while producing a representation of the group difference that is consistent with prior clinical reports. Effectiveness of the proposed algorithm for SSL is evaluated with both benchmark and medical imaging datasets. In the benchmark datasets, the results are better than or comparable to the state-of-the-art methods for SSL. For evaluation of the SSL setting in medical datasets, we use images of subjects with mild cognitive impairment (MCI), which is believed to be a precursor to Alzheimer's disease (AD), as unlabeled data. AD subjects and normal control (NC) subjects are used as labeled data, and we try to predict conversion from MCI to AD on follow-up. The semi-supervised extension of this method not only improves the generalization accuracy for the labeled data (AD/NC) slightly but is also able to predict subjects which are likely to converge to AD.
Engineering a thermostable biosensor based on biomimetic mineralization HRP@Fe-MOF for Alzheimer's disease

The development of disease detection by biosensors represents one of the key components of medical science. However, millions of people are still misdiagnosed each year due to the poor efficacy and thermal instability of biosensors. Using horseradish peroxidase (HRP) as a paradigm, we offer a rational design strategy to optimize the thermostability and activity of biosensors by biomimetic mineralization. To overcome the weak thermostability of the biosensor, the mineralization of Fe-MOF forms an armor on HRP that protects against high temperature. Additionally, the biomimetic mineralization HRP@Fe-MOF can double-catalyze the TMB/H2O2 chromogenic system for color development. The biosensor can also be recycled through simple heat treatment due to the thermally stable aptamer and biomimetic mineralization HRP@Fe-MOF. The optical biosensor based on this sensitive spectral transformation was successfully developed for the measurement of AβO with an outstanding linear range (0.0001-10 nM) and a low limit of detection (LOD) of 0.03 pM. This promising platform will open up new avenues for the detection of AβO in the early diagnosis of Alzheimer's disease (AD).
Preparation and properties of nano silica-based bioactive glass/apatite/sodium alginate composite hydrogel

In this paper, given the lack of osteogenic activity of sodium alginate (SA) hydrogel and to simulate the composition of natural bone, ionic-crosslinking NBG/n-HA/SA hydrogel scaffolds were prepared by using nano bioactive glass (NBG) and nano hydroxyapatite (n-HA) with high bioactivity as composite calcium sources and reinforcement phases, and D-gluconic acid δ-lactone (GDL) as the coagulant. The results showed that the mixture of the precursor forming the network had good injectability and plasticity. When the dosage of GDL was 0.75 g, the gelling time of the composite hydrogel could be regulated within 4-8 min, and the hydrogel had high compressive strength (170-220 kPa), as well. When the mass ratio of calcium source to SA was 1:1, the crosslinking network was relatively uniform with a considerable number of large pores around 40 μm in the structure. In the immersion experiment in vitro, it was found that the composite hydrogel could promote the deposition of bone-like apatite on the material's surface. Meanwhile, the cell experiments in vitro verified that the NBG/n-HA/SA composite hydrogel had good cytocompatibility without cytotoxicity. Moreover, the composite hydrogel could enhance the activity of ALP of mouse bone marrow mesenchymal stem cells, and thus, it had good osteogenic activity.
Sustainable operation of membrane distillation for hypersaline applications: Roles of brine salinity, membrane permeability and hydrodynamics

This study aims to explore the role of brine salinity in achieving sustainable operation of membrane distillation (MD), particularly in hypersaline applications where highly concentrated or saturated solutions are treated. Given the state-of-the-art MD modeling work mainly focused on the mass and heat transfer phenomena for dilute systems, our simulation work predicts the trends of permeation flux in direct contact MD (DCMD) with elevated feed concentrations up to saturation, by a newly-developed exponential decay function. Also, a semi-empirical equation of the solute transport coefficient Sherwood number (Sh) is derived as Sh = (alpha(1)omega(F) + alpha(2)) Re-beta Sc-0.33, which for the first time incorporates the influence of feed concentration into the concentration polarization calculation in MD. Numerical analysis on the supersaturation ratio, concentration factor and concentration polarization effect showed that low to modest membrane permeability, reasonably high feed temperature and modest hydrodynamics (500 < Re < 2000) may help to prevent supersaturation and potentially reduce membrane scaling in hypersaline applications.
Advanced Ferromagnetic Materials in Power Electronic Converters: A State of the Art

Currently, the design of power electronic converters (PECs) is in a stage which looks increasing its efficiency and reducing its dimensions from basic topologies through precise analysis of losses in each device that conforms. Although there have been important advances to improve the active components of PECs, passive components, particularly inductors, have changed very little since several decades ago, and those begin a limiting factor, when a high efficiency at very high power and switching frequency, are required. It is for the foregoing that this paper reviews new ferromagnetic materials to construct inductors and achieve a substantial increasing in efficiency through magnetic permeability and hysteresis improvements. Therefore, the main objective of this work is to position the reader in the state of the art of advanced ferromagnetic materials used in PECs. Details about how they are constructed and qualitative comparison of their dynamic behavior are provided. Also, estimation methods of energy losses, applications for different types of material, and its influence on the performance of some basic PECs are presented.
Aberrant mesolimbic dopamine-opiate interaction in obesity

Dopamine and opioid neurotransmitter systems share many functions such as regulation of reward and pleasure. μ-Opioid receptors (MOR) modulate the mesolimbic dopamine system in ventral tegmental area and striatum, key areas implicated in reward. We hypothesized that dopamine and opioid receptor availabilities correlate in vivo and that this correlation is altered in obesity, a disease with altered reward processing. Twenty lean females (mean BMI 22) and 25 non-binge eating morbidly obese females (mean BMI 41) underwent two positron emission tomography scans with [(11)C]carfentanil and [(11)C]raclopride to measure the MOR and dopamine D2 receptor (DRD2) availability, respectively. In lean subjects, the MOR and DRD2 availabilities were positively associated in the ventral striatum (r=0.62, p=0.003) and dorsal caudate nucleus (r=0.62, p=0.004). Moreover, DRD2 availability in the ventral striatum was associated with MOR availability in other regions of the reward circuitry, particularly in the ventral tegmental area. In morbidly obese subjects, this receptor interaction was significantly weaker in ventral striatum but unaltered in the caudate nucleus. Finally, the association between DRD2 availability in the ventral striatum and MOR availability in the ventral tegmental area was abolished in the morbidly obese. The study demonstrates a link between DRD2 and MOR availabilities in living human brain. This interaction is selectively disrupted in mesolimbic dopamine system in morbid obesity. We propose that interaction between the dopamine and opioid systems is a prerequisite for normal reward processing and that disrupted cross-talk may underlie altered reward processing in obesity.
A survey of object-oriented Petri nets and analysis methods

Petri nets are a well-known graphical and modeling tool for concurrent and distributed systems, and there have been many results on the theory, and also on practical applications. In the last decade, various Object-Oriented Petri nets (OO-nets) are proposed. As object orientation was adopted for programming languages, extension to OO-nets inspired from object-oriented programming is a natural flow. This article presents state-of-the-art on OO-nets.
Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs non linear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing highspeed, neuromorphic, and massively parallel pattern recognition and classification tasks.
Nanoneedles Induce Targeted siRNA Silencing of p16 in the Human Corneal Endothelium

Nanoneedles can target nucleic acid transfection to primary cells at tissue interfaces with high efficiency and minimal perturbation. The corneal endothelium is an ideal target for nanoneedle-mediated RNA interference therapy aimed at enhancing its proliferative capacity, necessary for tissue regeneration. This work develops a strategy for siRNA nanoninjection to the human corneal endothelium. Nanoneedles can deliver p16-targeting siRNA to primary human corneal endothelial cells in vitro without toxicity. The nanoinjection of siRNA induces p16 silencing and increases cell proliferation, as monitored by ki67 expression. Furthermore, siRNA nanoinjection targeting the human corneal endothelium is nontoxic ex vivo, and silences p16 in transfected cells. These data indicate that nanoinjection can support targeted RNA interference therapy for the treatment of endothelial corneal dysfunction.
Series Resonator Mode Switching for Area-Efficient Octave Tuning-Range CMOS LC Oscillators

Integrated oscillators with octave frequency tuning range (FTR) are desirable for wireless transceivers supporting multiple frequency bands. In this paper, we describe a wide-FTR CMOS voltage-controlled oscillator (VCO) based on a novel area-efficient series resonator mode-switching scheme that preserves resonator quality factor Q across the entire octave tuning range. This allows the CMOS VCO to simultaneously achieving wide FTR, area efficiency, and low phase noise, demonstrating state-of-the-art figure of merit (FoM) for >10-GHz octave-tuning range VCOs. We also analyze the relationship between Q and FTR across common resonator band-switching schemes, quantifying performance limits and highlighting the benefits of using mode-switching for wide-FTR VCOs. The proposed approach is demonstrated through a 6.4-14-GHz (74.6% FTR) VCO implemented in 65-nm CMOS that achieves 186-188-dB VCO FoM, demonstrating good FoM across the entire FTR. The scalability of this approach toward achieving even larger FTR is also demonstrated by a triple-mode 2.2-8.7-GHz (119% FTR) CMOS VCO. Area efficiency of the proposed mode-switching scheme is demonstrated by the state-of-the-art 197-dB FoM area achieved by the 14-GHz VCO.
Hyper-Redundant Manipulators for Operations in Confined Space: Typical Applications, Key Technologies, and Grand Challenges

In this article, we review the state of the art in hyper-redundant manipulators for applications in confined space such as ON-orbit services. With their multiple degrees of freedom and slender links, hyper-redundant manipulators can offer superior dexterity and excellent operability. They can traverse freely, manipulate objects flexibly, and conform to curvilinear paths accurately in confined spaces. The by-design separation of the mechanical and electrical parts in these manipulators also offers inherent structural compliance and miniaturization. Due to the elastic characteristics of driving cables, hyper-redundant manipulators have both stiffness and flexibility. In this article, the overviews of the current state of the art in this field are provided from the perspectives of both typical applications and key technologies. We detailed the relevant studies on the configuration, obstacle avoidance, path planning, and control technologies for hyper-redundant manipulators and highlight the use of these studies in the development of practical applications. Furthermore, we propose several aspects that need to be further studied, namely efficient inverse kinematics solution, strong coupled dynamics modeling, variable stiffness control, and multiobjective trajectory optimization. Breakthroughs in these areas will provide valuable solutions for complex path planning and control of hyper-redundant manipulators.(1)
Hybrid Ageing Patterns for face age estimation

Wrinkles can be embedded in several image-based applications as a descriptor for human skin. However, wrinkle-based age estimation research has not been widely addressed. In this paper, we introduce a Multi scale Wrinkle Patterns (MWP) representation, investigate the effect of wrinkles on face age estimation and propose Hybrid Ageing Patterns (HAP) for face age estimation. To define the wrinkle regions more precisely, a template consisting of 10 regions constructed relatively to a set of automatically located facial landmarks is used. We extract the multi-scale wrinkles in each region and encode them into MWP. We use Support Vector Regression to estimate age from the combination of such patterns. The performance of the algorithms is assessed by using Mean Absolute Error (MAE) on three state-of-the-art datasets-FG-NET, FERET and MORPH. We observe that MWP produces a comparable MAE of 4.16 on FERET to the state of the art. Finally we propose HAP, which combines the features from MWP and the facial appearance model (FAM), and demonstrate improved performance on FERET and MORPH with MAE of 3.02 (2.92) and 3.68 (2.98), respectively. Therefore, we conclude that MWP is an important complementary feature for face age estimation. (C) 2017 Elsevier B.V. All rights reserved.
Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging

Compressed sensing (CS) has exhibited great potential for accelerating magnetic resonance imaging (MRI). In CS-MRI, we want to reconstruct a high-quality image from very few samples in a short time. In this paper, we propose a fast algorithm, called projected iterative soft-thresholding algorithm (pISTA), and its acceleration pFISTA for CS-MRI image reconstruction. The proposed algorithms exploit sparsity of the magnetic resonance (MR) images under the redundant representation of tight frames. We prove that pISTA and pFISTA converge to a minimizer of a convex function with a balanced tight frame sparsity formulation. The pFISTA introduces only one adjustable parameter, the step size, and we provide an explicit rule to set this parameter. Numerical experiment results demonstrate that pFISTA leads to faster convergence speeds than the state-of-art counterpart does, while achieving comparable reconstruction errors. Moreover, reconstruction errors incurred by pFISTA appear insensitive to the step size.
Concentrations, Compound Profiles, and Possible Sources of Organic UV Filters in Human Milk in China

Ultraviolet (UV) filters are of great concern due to their wide occurrence, bioaccumulation, and toxicity. Little is known about human exposure to UV filters. A total of 3467 individual human milk samples from 24 Chinese provinces were collected during 2017-2019. The concentrations of 12 UV filters in 100 pooled milk samples were determined. The total UV filter concentration was 78-846 (mean 235 ± 120) ng/g lipid weight. The highest and lowest total mean concentrations were for samples from Qinghai and Sichuan provinces, respectively. A significant positive correlation was found between UV radiation levels and UV concentrations in the samples. The dominant UV filters were 2-(2-hydroxy-5-methylphenyl) benzotriazole (UV-P) and ethylhexyl methoxycinnamate (EHMC), which contributed means of 32 and 22%, respectively, to the total concentrations. Plastic products and sunscreens were probably the sources of UV-P and EHMC in the human milk from China, respectively. The mean 2-(3,5-di-tert-amyl-2-hydroxyphenyl) benzotriazole (UV-328) concentration was 2.6 ± 2.6 ng/g lipid weight. The UV filter profiles were similar to profiles for samples from Japan, the Philippines, and Switzerland but not for samples from Korea and Vietnam. The estimated daily UV filter intake for breastfed infants was below the corresponding reference dose. This was the first large-scale study of UV filters in human milk and will help assess the risks posed.
TanDEM-X Forest Mapping Using Convolutional Neural Networks

In this work, we face the problem of forest mapping from TanDEM-X data by means of Convolutional Neural Networks (CNNs). Our study aims to highlight the relevance of domain-related features for the extraction of the information of interest thanks to their joint nonlinear processing through CNN. In particular, we focus on the main InSAR features as the backscatter, coherence, and volume decorrelation, as well as the acquisition geometry through the local incidence angle. By using different state-of-the-art CNN architectures, our experiments consistently demonstrate the great potential of deep learning in data fusion for information extraction in the context of synthetic aperture radar signal processing and specifically for the task of forest mapping from TanDEM-X images. We compare three state-of-the-art CNN architectures, such as ResNet, DenseNet, and U-Net, obtaining a large performance gain over the baseline approach for all of them, with the U-Net solution being the most effective one.
Inflammation and plaque vulnerability

Atherosclerosis is a maladaptive, nonresolving chronic inflammatory disease that occurs at sites of blood flow disturbance. The disease usually remains silent until a breakdown of integrity at the arterial surface triggers the formation of a thrombus. By occluding the lumen, the thrombus or emboli detaching from it elicits ischaemic symptoms that may be life-threatening. Two types of surface damage can cause atherothrombosis: plaque rupture and endothelial erosion. Plaque rupture is thought to be caused by loss of mechanical stability, often due to reduced tensile strength of the collagen cap surrounding the plaque. Therefore, plaques with reduced collagen content are thought to be more vulnerable than those with a thick collagen cap. Endothelial erosion, on the other hand, may occur after injurious insults to the endothelium instigated by metabolic disturbance or immune insults. This review discusses the molecular mechanisms involved in plaque vulnerability and the development of atherothrombosis.
Scrotal Abdomen: Case Report and Management Principles

Hernias extending beyond the midpoint of the inner thigh in the standing position are called giant inguinal hernias or scrotal abdomen. They are rarely seen in common surgical practice. Huge inguinal hernias occur after years of neglect by the patient or in areas that are inaccessible to surgical services. Two cases of giant inguinal hernias which were managed successfully are presented here. Case 1: 80-year-old male patient presented with left giant scrotal abdomen for the past 12 years. Preoperatively, the pulmonary function test was found to be normal for his age. He was given incentive spirometry for a week. Perioperatively, the sac contained the entire small bowel, sigmoid colon, and omentum with inter bowel loop adhesions. Adhesions were released and it was repaired by hernioplasty with left orchidectomy. In the postoperative period, the patient was put on non-invasive ventilation for two days and then later was weaned off. Case 2: 42 years male patient presented with right-sided giant inguinoscrotal swelling for the past 15 years. The swelling was extending below midthigh. All the preoperative investigations were normal. Perioperatively, the sac contained omentum and small bowel and it was repaired by right hernioplasty. The postoperative period was uneventful and the patient recovered well. These are interesting cases of giant inguinal hernias. The occurrence of such potentially dangerous surgical problems is more common in low-to-middle income countries owing to the unavailability of surgical services. The management involves specific measures to prepare the patient adequately preoperatively especially to prevent respiratory complications in the postoperative period. Giant inguinal hernias can be comfortably managed if the patients are prepared adequately in the preoperative period. Their postoperative period will be uneventful if their pulmonary functions are normal.
Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts

The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.