ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
A benchtop brain injury model using resected donor tissue from patients with Chiari malformation

The use of live animal models for testing new therapies for brain and spinal cord repair is a controversial area. Live animal models have associated ethical issues and scientific concerns regarding the predictability of human responses. Alternative models that replicate the 3D architecture of the central nervous system have prompted the development of organotypic neural injury models. However, the lack of reliable means to access normal human neural tissue has driven reliance on pathological or post-mortem tissue which limits their biological utility. We have established a protocol to use donor cerebellar tonsillar tissue surgically resected from patients with Chiari malformation (cerebellar herniation towards the foramen magnum, with ectopic rather than diseased tissue) to develop an in vitro organotypic model of traumatic brain injury. Viable tissue was maintained for approximately 2 weeks with all the major neural cell types detected. Traumatic injuries could be introduced into the slices with some cardinal features of post-injury pathology evident. Biomaterial placement was also feasible within the in vitro lesions. Accordingly, this 'proof-of-concept' study demonstrates that the model offers potential as an alternative to the use of animal tissue for preclinical testing in neural tissue engineering. To our knowledge, this is the first demonstration that donor tissue from patients with Chiari malformation can be used to develop a benchtop model of traumatic brain injury. However, significant challenges in relation to the clinical availability of tissue were encountered, and we discuss logistical issues that must be considered for model scale-up.
Solar assisted air conditioning of buildings - an overview

Goal of this contribution is to draw a picture about some general issues for using solar thermal energy for air conditioning of buildings. The following topics are covered: A basic analysis of the thermodynamic limits for the use of heat cooling in combination with solar thermal energy is drawn; thereby fundamental insights about control needs for solar thermal driven cooling are obtained. A short overview about the state-of-the-art of available technologies, such as closed thermal driven cooling cycles (e.g., absorption, adsorption) and open cooling cycles (e.g., desiccant employing either solid or liquid sorbents) is given and needs and perspectives for future developments are described. The state-of-the-art of application of solar assisted air-conditioning in Europe is given and some example installations are presented. An overview about new developments of open and closed heat driven cooling cycles for application in combination with solar thermal collectors is given and some of these new systems are outlined more in detail. (c) 2006 Elsevier Ltd. All rights reserved.
Integration of ART-Kohonen neural network and case-based reasoning for intelligent fault diagnosis

This paper presents a new approach for integrating case-based reasoning (CBR) with an ART-Kohonen neural network (ART-KNN) to enhance fault diagnosis. When solving a new problem, the neural network is used to make hypotheses and to guide the CBR module in the search for a similar previous case that supports one of the hypotheses. The knowledge acquired by the network is interpreted and mapped into symbolic diagnosis descriptors, which are kept and used by the system to determine whether a final answer is credible, and to build explanations for the reasoning carried out. ART-KNN, synthesizing the theory of adaptive resonance theory and the learning strategy of Kohonen neural network, can solve the plasticity-stability dilemma of conventional neural networks. It can carry out 'on-line' training without forgetting previously trained patterns (stable training), and recode previously trained categories adaptive to changes in the environment and is self-organizing, which differs from most of networks that only can be carried out off-line. The proposed system has been used in the faults diagnosis of electric motor to verify the system performance. The result shows the proposed system performs better than self-organizing feature map (SOFM) based system with respect to classification rate. (C) 2003 Elsevier Ltd. All rights reserved.
Geodesics-Based Image Registration: Applications To Biological And Medical Images Depicting Concentric Ring Patterns

In many biological or medical applications, images that contain sequences of shapes are common. The existence of high inter-individual variability makes their interpretation complex. In this paper, we address the computer-assisted interpretation of such images and we investigate how we can remove or reduce these image variabilities. The proposed approach relies on the development of an efficient image registration technique. We first show the inadequacy of state-of-the-art intensity-based and feature-based registration techniques for the considered image datasets. Then, we propose a robust variational method which benefits from the geometrical information present in this type of images. In the proposed non-rigid geodesics-based registration, the successive shapes are represented by a level-set representation, which we rely on to carry out the registration. The successive level sets are regarded as elements in a shape space and the corresponding matching is that of the optimal geodesic path. The proposed registration scheme is tested on synthetic and real images. The comparison against results of state-of-the-art methods proves the relevance of the proposed method for this type of images.
Analysis of HDACi-Coupled Nanoparticles: Opportunities and Challenges

Systemic administration of histone deacetylase inhibitors (HDACi), like valproic acid (VPA), is often associated with rapid drug metabolization and untargeted tissue distribution. This requires high-dose application that can lead to unintended side effects. Hence, drug carrier systems such as nanoparticles (NPs) are developed to circumvent these disadvantages by enhancing serum half-life as well as organ specificity.This chapter gives a summary of the biological characterization of HDACi-coupled NPs in vitro, including investigation of cellular uptake, biocompatibility, as well as intracellular drug release and activity. Suitable methods, opportunities, and challenges will be discussed to provide general guidelines for the analysis of HDACi drug carrier systems with a special focus on recently developed cellulose-based VPA-coupled NPs.
Inducible deletion of raptor and mTOR from adult skeletal muscle impairs muscle contractility and relaxation

Skeletal muscle weakness has been associated with different pathological conditions, including sarcopenia and muscular dystrophy, and is accompanied by altered mammalian target of rapamycin (mTOR) signalling. We wanted to elucidate the functional role of mTOR in muscle contractility. Most loss-of-function studies for mTOR signalling have used the drug rapamycin to inhibit some of the signalling downstream of mTOR. However, given that rapamycin does not inhibit all mTOR signalling completely, we generated a double knockout for mTOR and for the scaffold protein of mTORC1, raptor, in skeletal muscle. We found that double knockout in mice results in a more severe phenotype compared with deletion of raptor or mTOR alone. Indeed, these animals display muscle weakness, increased fibre denervation and a slower muscle relaxation following tetanic stimulation. This is accompanied by a shift towards slow-twitch fibres and changes in the expression levels of calcium-related genes, such as Serca1 and Casq1. Double knockout mice show a decrease in calcium decay kinetics after tetanus in vivo, suggestive of a reduced calcium reuptake. In addition, RNA sequencing analysis revealed that many downregulated genes, such as Tcap and Fhod3, are linked to sarcomere organization. These results suggest a key role for mTOR signalling in maintaining proper fibre relaxation in skeletal muscle. KEY POINTS: Skeletal muscle wasting and weakness have been associated with different pathological conditions, including sarcopenia and muscular dystrophy, and are accompanied by altered mammalian target of rapamycin (mTOR) signalling. Mammalian target of rapamycin plays a crucial role in the maintenance of muscle mass and functionality. We found that the loss of both mTOR and raptor results in contractile abnormalities, with severe muscle weakness and delayed relaxation following tetanic stimulation. These results are associated with alterations in the expression of genes involved in sarcomere organization and calcium handling and with an impairment in calcium reuptake after contraction. Taken together, these results provide a mechanistic insight into the role of mTOR in muscle contractility.
Evaluation of Semantic Segmentation Methods for Land Use with Spectral Imaging Using Sentinel-2 and PNOA Imagery

Land use classification using aerial imagery can be complex. Characteristics such as ground sampling distance, resolution, number of bands and the information these bands convey are the keys to its accuracy. Random Forest is the most widely used approach but better and more modern alternatives do exist. In this paper, state-of-the-art methods are evaluated, consisting of semantic segmentation networks such as UNet and DeepLabV3+. In addition, two datasets based on aircraft and satellite imagery are generated as a new state of the art to test land use classification. These datasets, called UOPNOA and UOS2, are publicly available. In this work, the performance of these networks and the two datasets generated are evaluated. This paper demonstrates that ground sampling distance is the most important factor in obtaining good semantic segmentation results, but a suitable number of bands can be as important. This proves that both aircraft and satellite imagery can produce good results, although for different reasons. Finally, cost performance for an inference prototype is evaluated, comparing various Microsoft Azure architectures. The evaluation concludes that using a GPU is unnecessarily costly for deployment. A GPU need only be used for training.
Unmasking a two-faced protein

Single-molecule fluorescence spectroscopy and molecular dynamics simulations illuminate the structure and dynamics of PSD-95, a protein involved in neural plasticity.
Improved split-ubiquitin screening technique to identify surface membrane protein-protein interactions

Yeast-based methods are still the workhorse for the detection of protein-protein interactions (PPIs) in vivo. Yeast two-hybrid (Y2H) systems, however, are limited to screening for a specific group of molecules that interact in a particular cell compartment. For this reason, the split-ubiquitin system (SUS) was developed to allow screening of cDNA libraries of full-length membrane proteins for protein-protein interactions in Saccharomyces cerevisiae. Here we demonstrate that a modification of the widely used membrane SUS involving the transmembrane (TM) domain of the yeast receptor Wsc1 increases the stringency of screening and improves the selectivity for proteins localized in the plasma membrane (PM).
The economic costs of a multisectoral nutrition programme implemented through a credit platform in Bangladesh

Bangladesh struggles with undernutrition in women and young children. Nutrition-sensitive agriculture programmes can help address rural undernutrition. However, questions remain on the costs of multisectoral programmes. This study estimates the economic costs of the Targeting and Re-aligning Agriculture to Improve Nutrition (TRAIN) programme, which integrated nutrition behaviour change and agricultural extension with a credit platform to support women's income generation. We used the Strengthening Economic Evaluation for Multisectoral Strategies for Nutrition (SEEMS-Nutrition) approach. The approach aligns costs with a multisectoral nutrition typology, identifying inputs and costs along programme impact pathways. We measure and allocate costs for activities and inputs, combining expenditures and micro-costing. Quantitative and qualitative data were collected retrospectively from implementers and beneficiaries. Expenditure data and economic costs were combined to calculate incremental economic costs. The intervention was designed around a randomised control trial. Incremental costs are presented by treatment arm. The total incremental cost was $795,040.34 for a 3.5-year period. The annual incremental costs per household were US$65.37 (Arm 2), USD$114.15 (Arm 3) and $157.11 (Arm 4). Total costs were led by nutrition counselling (37%), agriculture extension (12%), supervision (12%), training (12%), monitoring and evaluation (9%) and community events (5%). Total input costs were led by personnel (68%), travel (12%) and supplies (7%). This study presents the total incremental costs of an agriculture-nutrition intervention implemented through a microcredit platform. Costs per household compare favourably with similar interventions. Our results illustrate the value of a standardised costing approach for comparison with other multisectoral nutrition interventions.
DESIGN OF A HYBRID COMPUTATIONAL FLUID DYNAMICS-MONTE CARLO RADIATION TRANSPORT METHODOLOGY FOR RADIOACTIVE PARTICULATE RESUSPENSION STUDIES

There are numerous scenarios where radioactive particulates can be displaced by external forces. For example, the detonation of a radiological dispersal device in an urban environment will result in the release of radioactive particulates that in turn can be resuspended into the breathing space by external forces such as wind flow in the vicinity of the detonation. A need exists to quantify the internal (due to inhalation) and external radiation doses that are delivered to bystanders; however, current state-of-the-art codes are unable to calculate accurately radiation doses that arise from the resuspension of radioactive particulates in complex topographies. To address this gap, a coupled computational fluid dynamics and Monte Carlo radiation transport approach has been developed. With the aid of particulate injections, the computational fluid dynamics simulation models characterize the resuspension of particulates in a complex urban geometry due to air-flow. The spatial and temporal distributions of these particulates are then used by the Monte Carlo radiation transport simulation to calculate the radiation doses delivered to various points within the simulated domain. A particular resuspension scenario has been modeled using this coupled framework, and the calculated internal (due to inhalation) and external radiation doses have been deemed reasonable. GAMBIT and FLUENT comprise the software suite used to perform the Computational Fluid Dynamics simulations, and Monte Carlo N-Particle eXtended is used to perform the Monte Carlo Radiation Transport simulations.
High-Performance Shielded Coplanar Waveguides for the Design of CMOS 60-GHz Bandpass Filters

This paper presents optimized very high performance CMOS slow-wave shielded CPW transmission lines (S-CPW TLines). They are used to realize a 60-GHz bandpass filter, with T-junctions and open stubs. Owing to a strong slow-wave effect, the longitudinal length of the S-CPW is reduced by a factor up to 2.6 compared to a classical microstrip topology in the same technology. Moreover, the quality factor of the realized S-CPWs reaches 43 at 60 GHz, which is about two times higher than the microstrip one and corresponds to the state of the art concerning S-CPW TLines with moderate width. For a proof of concept of complex passive device realization, two millimeter-wave filters working at 60 GHz based on dual-behavior-resonator filters have been designed with these S-CPWs and measured up to 110 GHz. The measured insertion loss for the first-order (respectively, second-order) filter is -2.6 dB (respectively, -4.1 dB). The comparison with a classical microstrip topology and the state-of-the-art CMOS filter results highlights the very good performance of the realized filters in terms of unloaded quality factor. It also shows the potential of S-CPW TLines for the design of high-performance complex CMOS passive devices.
Ways of preventing surgeon burnout

In surgical practice, numerous sources of stress (stressors) are unpredictable, two examples being daily workload and postoperative complications. They may help to explain surgeon burnout, of which the prevalence (34 to 53%) has been the subject of many studies. That said, even though assessments are legion, recommended solutions have been few and far between, especially insofar as by nature and training, surgeons are disinclined to interest themselves in burnout, which they are prone to consider as something experienced by "others". The objective of this attempt at clarification is to identify in the literature the strategies put forward in view of avoiding surgeon burnout, and to assess the impact of this phenomenon not only on the surgeon's professional and personal entourage, but also on patient safety. Prevention-based strategies, many of them focused on modifiable stressors, will be detailed.
Multichannel Speech Enhancement With Own Voice-Based Interfering Speech Suppression for Hearing Assistive Devices

Enhancementof a desired speech signal in the presence of competing or interfering speech remains an unsolved problem, as it can be hard to determine which of the speech signals is the one of interest. In this paper, we propose a multichannel noise reduction algorithm which uses the presence of the user's own voice signal, e.g. during conversations with the target speaker, as an asset to efficiently identify interfering speech and noise. Specifically, following the typical speech pattern in natural conversations, the presence of an own voice may indicate the absence of the target speech, hence undesired speech and noise can be identified and estimated during own voice presence. In contrast to conventional noise reduction systems, the proposed noise reduction systems use the user's own voice to identify interfering speech that otherwise could be confused with the target speech. We demonstrate the performance of the proposed noise reduction systems in a comparison against state-of-the-art noise reduction systems in terms of beamforming performance for hearing assistive devices. The results show that the proposed beamforming scheme in particular outperforms state-of-the-art methods in terms of ESTOI and PESQ in situations with a target speaker and a strong interfering speaker.
Chinese flower-bird character generation based on pencil drawings or brush drawings

Chinese flower-bird characters are gems of traditional Chinese art. It is an artistic font and the strokes of the characters are designed as beautiful patterns of flowers, birds, etc. The generation of such characters requires painters' great efforts. Imagine that if we only need to sketch the outline of the ideal flower-bird characters using a pencil, and then we can quickly obtain these artistic characters, which will be of great significance in promoting their development, allowing more people to appreciate and even create this art by computer. Recently, with the development of deep learning and the invention of generative adversarial networks (GANs), some studies on font generation have made new progress. However, there is no research on the generation of flower-bird characters. We provide a solution by designing a GAN-based architecture to generate flower-bird characters. More specifically, a generator inspired by U-Net translates pencil drawings or brush drawings to flower-bird characters, and a patch-level discriminator distinguishes whether the received image is real. In addition to adversarial loss, a valid loss term called structural similarity loss is designed to further drive the network to generate satisfactory images. The quantitative analysis and user perceptual validation show the effectiveness of our method. (C) 2019 SPIE and IS&T
Stress-Induced Diabetes: A Review

It has long been established that stress has a significant impact on metabolic function. Type 2 diabetes may be initiated by psychological and physical stress. The central and peripheral nervous systems are both involved in the neuroendocrine framework that underlies the underlying processes. The release of catecholamines and a rise in serum glucocorticoid concentrations caused by psychological stress enhance the requirement for insulin and insulin resistance. Experiencing persistent hyperglycemia in people with diabetes may be influenced by stress. Blood sugar levels may rise due to hormones being released in response to stress. Although this has adaptive significance in a healthy patient, in the long run, it can cause insulin resistance and lead to diabetes. Additionally, diabetes may cause abnormalities in the regulation of these stress hormones.
Building reflective capacity and improving well-being of early childhood professionals through an embedded cross-system model of infant early childhood mental health consultation

Infant and Early Childhood Mental Health Consultation (IECMHC) aims to improve early childhood professionals' abilities to promote children's mental health through relationship building and collaboration. Using a longitudinal, matched-comparison group design, a 3-year pilot study of a cross-system, embedded model of IECMHC assessed teachers and home visitors in intervention and comparison programs in reflective capacity, burnout, and perceptions of children's behavior. A sample of 136 staff (n = 72 intervention group; n = 64 comparison group; 21% Black; 51% White; 28% Latina/Hispanic) participated in surveys over a 21-month implementation period. A subsample of staff (n = 26) participated in interviews that included a narrative measure of reflective capacity; and a smaller subsample of teachers only (n = 21) completed assessments of children. Staff in the intervention group significantly increased reflective capacity after 21 months. For the staff interview subsample, receiving the intervention predicted lower levels of burnout at 12-15 months post-baseline. Among teachers completing child assessments, those with higher reflective capacity rated children's behaviors more positively than teachers with lower reflective capacity. We conclude that this IECMHC model successfully improved reflective capacity in staff. Future research should investigate reflective capacity as a potential mechanism of change for IECMHC.
A high-speed RSD-based flexible ECC processor for arbitrary curves over general prime field

This workpresents a novel high-speed redundant-signed-digit (RSD)-based elliptic curve cryptographic (ECC) processor for arbitrary curves over a general prime field. The proposed ECC processor works for any value of the prime number and curve parameters. It is based on a new high speed Montgomery multiplier architecture which uses different parallel computation techniques at both circuit level and architectural level. At the circuit level, RSD and carry save techniques are adopted while pre-computation logic is incorporated at the architectural level. As a result of these optimization strategies, the proposed Montgomery multiplier offers a significant reduction in computation time over the state-of-the-art. At the system level, to further enhance the overall performance of the proposed ECC processor, Montgomery ladder algorithm with (X,Y)-only common Z coordinate (co-Z) arithmetic is adopted. The proposed ECC processor is synthesized and implemented on different Xilinx Virtex (V) FPGA families for field sizes of 256 to 521 bits. On V-6 platform, it computes a single 256 to 521 bits scalar point multiplication operation in 0.65 to 2.6ms which is up to 9 times speed-up over the state-of-the-art.