ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
How to Manage Pseudomonas aeruginosa Infections

Pseudomonas aeruginosa is a pathogen frequently encountered in healthcare-associated infections and immunocompromised patients. In bacteremia, this pathogen is associated with higher mortality than other Gram-negative pathogens. This increase in mortality was also found globally for multi-resistant compared to susceptible strains. Several factors have been associated with the development of resistance: previous ICU stay, use of carbapenems, and comorbidities were identified in multivariate analysis. In the therapeutic choice, previous antibiotic treatment remains the strongest driver suggesting a potential resistant strain. These risk factors will decide whether multi-resistant strains must be considered in the empiric coverage. For susceptible strains, a single agent can be used, β-lactams are usually the first choice. Associations do not provide any advantage on mortality. Optimization of pharmacokinetic/pharmacodynamic parameters, such as prolonged infusion (for time-dependent antibiotics), increased dosage (for concentration-dependent antibiotics), and therapeutic drug monitoring, also influences the outcome. The increasing number of resistant strains led the clinician to use either recently approved new molecules but also associations. For multi-resistant strains, new molecules such as ceftolozane-tazobactam, ceftazidime-avibactam, and cefiderocol have shown an adequate activity against P. aeruginosa. Older molecules like colistin and fosfomycin are also used in this indication. The complexity of the resistance and consequences on a larger scale of antibiotic prescription will probably lead to more individualized prescriptions.
Decline of lymphatic vessel density and function in murine skin during aging

Lymphatic vessels play important roles in the pathogenesis of many conditions that have an increased prevalence in the elderly population. However, the effects of the aging process on the lymphatic system are still relatively unknown. We have applied non-invasive imaging and whole-mount staining techniques to assess the lymphatic vessel function and morphology in three different age groups of mice: 2 months (young), 7 months (middle-aged), and 18 months (aged). We first developed and validated a new method to quantify lymphatic clearance from mouse ear skin, using a lymphatic-specific near-infrared tracer. Using this method, we found that there is a prominent decrease in lymphatic vessel function during aging since the lymphatic clearance was significantly delayed in aged mice. This loss of function correlated with a decreased lymphatic vessel density and a reduced lymphatic network complexity in the skin of aged mice as compared to younger controls. The blood vascular leakage in the skin was slightly increased in the aged mice, indicating that the decreased lymphatic function was not caused by a reduced capillary filtration in aged skin. The decreased function of lymphatic vessels with aging might have implications for the pathogenesis of a number of aging-related diseases.
Secure Location of Things (SLOT): Mitigating Localization Spoofing Attacks in the Internet of Things

The rise of geo-spatial location-based applications for the Internet of Things introduces new location spoofing security risks. To overcome the threat of malicious spoofing attacks, we develop the Secure Location of Things (SLOT) framework which extends current state-of-the-art methods and is able to cope with such threats. The SLOT framework incorporates another piece of information which has not been utilized so far, the audibility information. This information indicates whether a node is able/unable to communicate with the target. By leveraging on this available information, we reformulate the location estimation problem as a stochastic censoring model and derive the maximum likelihood estimator for the node's location in two different ways: the first algorithm is based on a probabilistic mixture model and assumes knowledge of the Byzantine attack distributional model; and the second algorithm is based on a difference-time-of-arrival, which does not make any distributional assumptions regarding the attack. We show that our algorithms provide significant performance gain over current state-of-the-art algorithms, by mitigating the well-known ambiguity problem of the likelihood surface. Extensive simulations show the significant benefits that the SLOT framework provides compared to current state-of-the-art algorithms.
Detection and Segmentation of Concealed Objects in Terahertz Images

Terahertz imaging makes it possible to acquire images of objects concealed underneath clothing by measuring the radiometric temperatures of different objects on a human subject. The goal of this work is to automatically detect and segment concealed objects in broadband 0.1-1 THz images. Due to the inherent physical properties of passive terahertz imaging and associated hardware, images have poor contrast and low signal to noise ratio. Standard segmentation algorithms are unable to segment or detect concealed objects. Our approach relies on two stages. First, we remove the noise from the image using the anisotropic diffusion algorithm. We then detect the boundaries of the concealed objects. We use a mixture of Gaussian densities to model the distribution of the temperature inside the image. We then evolve curves along the isocontours of the image to identify the concealed objects. We have compared our approach with two state-of-the-art segmentation methods. Both methods fail to identify the concealed objects, while our method accurately detected the objects. In addition, our approach was more accurate than a state-of-the-art supervised image segmentation algorithm that required that the concealed objects be already identified. Our approach is completely unsupervised and could work in real-time on dedicated hardware.
The role of emotion regulation in mental health during the COVID-19 outbreak: A 10-wave longitudinal study

The COVID-19 pandemic elicited a lot of concerns among citizens, thereby potentially compromising their well-being. This study sought to examine the role of individuals' emotion regulation styles (i.e., emotional dysregulation, emotional suppression, and emotional integration) in handling these concerns and their experiences of well-being (i.e., satisfaction with life and sleep quality) and ill-being (i.e., anxiety and depressive symptoms). The study had a unique 10-wave longitudinal design (N = 986; Mage = 41.28; 76% female) and was conducted during the outbreak of the pandemic in March-May 2020. Multilevel analyses showed, first, that weekly variation in COVID-19 related concerns related negatively to weekly variation in well-being and positively to weekly variation in ill-being. Second, at the between-person level, emotional dysregulation and suppression related positively to between-person vulnerability in ill-being and lower well-being (across all waves). Third, between-person differences in emotional dysregulation amplified the strength of the within-person association between concerns and depressive complaints and lowered life satisfaction. Unexpectedly, integrative emotion regulation amplified the strength of the within-person association between concerns and anxiety. The discussion focuses on the critical role of emotion regulation in handling the uncertainty elicited by the pandemic and provides directions for further research.
Load-Oriented Order Release (LOOR) revisited: bringing it back to the state of the art

In the workload control literature, the Load-Oriented Order Release (LOOR) approach has been neglected since its robustness was questioned at the end of the 1990s. This paper revisits LOOR and evaluates whether its performance can be improved in two ways. First, an intermediate pull release mechanism is added to avoid starvation between periodic release events. This mechanism was recently shown to be effective at improving the performance of a state-of-the-art release method known as LUMS COR. Second, an integer linear programming model is used to manage the trade-off between the timing and load balancing functions of order release. The two refinements are assessed using simulations of different shop configurations, which allow us to evaluate robustness. Results demonstrate that the refinements contribute to improving the performance of LOOR such that it can even outperform LUMS COR. Perhaps counter-intuitively, putting more emphasis on load balancing than on the urgency of individual orders is shown to lead to a lower percentage of tardy orders. Overall, the improvements mean that concerns about LOOR's robustness are no longer valid - it now appears suitable for a wide range of shops found in practice.
Pharmacokinetic and Pharmacodynamic Modeling and Simulation Analysis of Prasugrel in Healthy Male Volunteers

This study evaluated the pharmacokinetics and pharmacodynamics of the antiplatelet agent prasugrel, and explored its optimal dose regimens via modeling and simulation using NONMEM. We measured platelet aggregation and the serial plasma concentrations of the inactive (R-95913) and active metabolites (R-138727) of prasugrel after a single oral dose of 10-60 mg in 20 healthy adult male volunteers. A pharmacokinetic model for R-95913 and R-138727, and a pharmacodynamic model between the concentration of R-138727 and maximal platelet aggregation measured by light transmittance were constructed. The predictability of the model for platelet aggregation was evaluated by comparing the model prediction values with the observed ones not used in the construction of the model. Pharmacokinetic data were best described by a 3-compartment models for R-95913, a 1-compartment model for R-138727 with transit compartment model for absorption delay, and first-pass metabolic conversion of R-95913 into R-138727 during absorption. The association-dissociation model between R-138727 and its receptor in platelets was applied for the inhibitory effect of prasugrel on platelet aggregation. Prasugrel rapidly inhibited platelet aggregation after oral administration, with a prolonged duration of action; however, the concentration of the active metabolite decreased rapidly, which may have been due to the slow dissociation rate of R-138727 from its target receptor in platelets. The external validation suggests that our model could be used to individualize prasugrel treatment in various clinical situations. Simulation showed rapid onset of inhibitory effect with great magnitude and consistent inhibition after therapeutic dose of prasugrel.
Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling

The spatial resolution and temporal frame-rate of dynamic magnetic resonance imaging (MRI) can be improved by reconstructing images from sparsely sampled ${k}$ -space data with mathematical modeling of the underlying spatiotemporal signals. These models include sparsity models, linear subspace models, and non-linear manifold models. This work presents a novel linear tangent space alignment (LTSA) model-based framework that exploits the intrinsic low-dimensional manifold structure of dynamic images for accelerated dynamic MRI. The performance of the proposed method was evaluated and compared to state-of-the-art methods using numerical simulation studies as well as 2D and 3D in vivo cardiac imaging experiments. The proposed method achieved the best performance in image reconstruction among all the compared methods. The proposed method could prove useful for accelerating many MRI applications, including dynamic MRI, multi-parametric MRI, and MR spectroscopic imaging.
Resilience of art cities to flood risk: A quantitative model based on depth-idleness correlation

Cultural heritage (CH) is threatened by floods; however, the understanding of exposure and vulnerability is challenging and makes risk and resilience assessment rarely practiced. CH is crucial for post-disaster resilience, especially when the local economy is based on tourism. The work presents a novel framework for evaluating flood resilience, indirect impacts, and associated risk in art cities. The exposure of CH is estimated using the number of visitors as a proxy variable for the social appreciation. A new depth-idleness vulnerability function assigning a reopening time to flood depth is developed from post-event reports. A resilience model is conceived to (i) describe the recovery dynamics, (ii) estimate the indirect impacts in terms of lost visitors to CH for different probabilistic scenarios, (iii) calculate risk, and (iv) identify mitigation actions. The application of the model to the art city of Florence (Italy), a UNESCO site visited by approximately 10 million people a year, shows that a medium recurrence interval flood requires a recovery time of 351 days and causes a loss of 10.5 million visitors. The annual average number of lost visitors is 88,000 approximately. Resilience can be increased by accelerating the reopening and by reinforcing the attractivity of the city.
Rates and Predictors of Consistent Condom-use by People Living with HIV/AIDS on Antiretroviral Treatment in Uganda

Antiretroviral treatment (ART) has been recognized as one of the methods for reducing the risk of HIV transmission, and access to this is being rapidly expanded. However, in a generalized HIV epidemic, ART could increase unprotected sex by people living with HIV/AIDS (PHAs). This paper assessed the rates and predictors of consistent condom-use by sexually-active PHAs after initiating ART. The study used cross-sectional data on sexual behaviour of 269 sexually-active ART-experienced individuals (95 males and 174 females) aged 18 years and above. The results revealed that 65% (70% of men and 61% of women) used condom consistently after initiating ART. Consistent use of condom was more likely if PHAs had secondary- or tertiary-level education and had more than one sex partner in the 12 months preceding the study. However, PHAs were less likely to have used condom consistently if they worked in the informal and formal sectors, belonged to the medium- and high-income groups, and were married. PHAs, who were on ART for less than 1 year and 1-2 year(s), had a good self-perception of health, had a sexual partner who was HIV-negative or a partner with unknown HIV status, and desired to bear children, were also less likely to have used condom consistently. The paper concluded that, although the majority of PHAs consistently used condom, there was potential for unprotected sex by PHAs on ART.
Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level

Depression is a severe psychological condition that affects millions of people worldwide. As depression has received more attention in recent years, it has become imperative to develop automatic methods for detecting depression. Although numerous machine learning methods have been proposed for estimating the levels of depression via audio, visual, and audiovisual emotion sensing, several challenges still exist. For example, it is difficult to extract long-term temporal context information from long sequences of audio and visual data, and it is also difficult to select and fuse useful multi-modal information or features effectively. In addition, how to include other information or tasks to enhance the estimation accuracy is also one of the challenges. In this study, we propose a multi-modal adaptive fusion transformer network for estimating the levels of depression. Transformer-based models have achieved state-of-the-art performance in language understanding and sequence modeling. Thus, the proposed transformer-based network is utilized to extract long-term temporal context information from uni-modal audio and visual data in our work. This is the first transformer-based approach for depression detection. We also propose an adaptive fusion method for adaptively fusing useful multi-modal features. Furthermore, inspired by current multi-task learning work, we also incorporate an auxiliary task (depression classification) to enhance the main task of depression level regression (estimation). The effectiveness of the proposed method has been validated on a public dataset (AVEC 2019 Detecting Depression with AI Sub-challenge) in terms of the PHQ-8 scores. Experimental results indicate that the proposed method achieves better performance compared with currently state-of-the-art methods. Our proposed method achieves a concordance correlation coefficient (CCC) of 0.733 on AVEC 2019 which is 6.2% higher than the accuracy (CCC = 0.696) of the state-of-the-art method.
Antibiotic allergy labels in immunocompromised populations

Antibiotic allergy labels (AALs) are commonly reported, with well-defined prevalence in the general population; several studies have now focused efforts on immunocompromised hosts. Understanding the prevalence of reported allergy labels and methods of antibiotic allergy evaluation and delabeling strategies has the potential to improve prescribing practices and clinical outcomes in this high-antibiotic use group. In this review, we will discuss the current literature on the prevalence, impact, and evaluations of AALs in immunocompromised hosts with a focus on beta-lactam (penicillin) allergy and sulfa-antibiotic (antimicrobial sulfurs) allergy labels.
Experimental DC extraction of the thermal resistance of bipolar transistors taking into account the Early effect

This paper presents three methods to experimentally extract the thermal resistance of bipolar transistors taking into account the Early effect. The approaches are improved variants of recently-proposed techniques relying on common-base DC measurements. The accuracy is numerically verified by making use of a compact model calibrated on I-V characteristics of state-of-the-art SOG BJTs and SiGe:C HBTs. (C) 2016 Elsevier Ltd. All rights reserved.
Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms

We study lossy-to-lossless compression of medical volumetric data using three-dimensional (3-D) integer wavelet transforms. To achieve good lossy coding performance, it is important to have transforms that are unitary. In addition to the lifting approach, we first introduce a general 3-D integer wavelet packet transform structure that allows implicit bit shifting of wavelet coefficients to approximate a 3-D unitary transformation. We then focus on context modeling for efficient arithmetic coding of wavelet coefficients. Two state-of-the-art 3-D wavelet video coding techniques, namely, 3-D set partitioning in hierarchical trees (Kim et al., 2000) and 3-D embedded subband coding with optimal truncation (Xu et aL, 2001), are modified and applied to compression of medical volumetric data, achieving the best performance published so far in the literature-both in terms of lossy and lossless compression.
Managing life-threatening 5-fluorouracil cardiotoxicity

5-Fluorouracil (5-FU), a known cardiotoxin, is the backbone for the treatment of colorectal cancer. It is associated with arrhythmias, myocardial infarction and sudden cardiac death. Most commonly, it is associated with coronary vasospasm secondary to direct toxic effects on vascular endothelium.A woman with metastatic colon cancer, originally treated with a 5-FU infusion as part of the FOLFIRI (Folinic acid, 5-Fluorouracil, Irinotecan) regimen, was unable to tolerate the chemotherapy due to chest pain. She was transitioned from infusional 5-FU to inferior 1-hour bolus 5-FU, in an attempt to minimise cardiotoxicity, but had disease progression. A multidisciplinary decision was made to again trial 5-FU infusion and pretreat with diltiazem. She tolerated chemotherapy without adverse events. A multidisciplinary discussion is recommended for co-management of reversible 5-FU-associated cardiotoxicity. After coronary artery disease (CAD) risk stratification and treatment, empiric treatment with calcium channel blockers and/or nitrates may allow patients with suspected coronary vasospasm, from 5-FU, to continue this vital chemotherapy.
Ratiometric fluorescent detection of miRNA-21 via pH-regulated adsorption of DNA on polymer dots and exonuclease III-assisted amplification

This work proposed a simple and sensitive method for ratiometric fluorescent detection of nucleic acids via pH-dependent adsorption of dye-labeled DNA on polymer dots. The polymer dots (Pdots) could be conveniently prepared with nanoprecipitation in water. The mixture of dye-labeled DNA and Pdots at neutral pH showed the fluorescence of Pdots, while the adsorption of dye-labeled DNA on Pdots at acidic pH led to fluorescence resonance energy transfer from the Pdots to dye, and thus the fluorescence of dye. As a result, a signal switch could be designed for the detection of nucleic acids complementary to the DNA after combining with exonuclease III-assisted digestion of DNA. Using miRNA-21 as a target model and Cy3-labeled DNA as the probe, the hybridization of DNA with miRNA-21 provided active sites for EXO III, which released the hybridized miRNA-21 for cyclic digestion of DNA, and thus decreased the adsorption of Cy3-labeled DNA on Pdots and the fluorescence of Cy3. The ratio of fluorescent intensity of Pdots to Cy3 showed linear increase upon increasing miRNA-21 concentration ranging from 0.01 to 2.5 nM. The limit of detection at 3σ was 4.0 pM. The excellent performance and good extendability of the proposed strategy demonstrated its promising application in bioanalysis.
Interviewing in virtual environments: Towards understanding the impact of rapport-building behaviours and retrieval context on eyewitness memory

Given the complexities of episodic memory and necessarily social nature of in-person face-to-face interviews, theoretical and evidence-based techniques for collecting episodic information from witnesses, victims, and survivors champion rapport-building. Rapport is believed to reduce some of the social demands of recalling an experienced event in an interview context, potentially increasing cognitive capacity for remembering. Cognitive and social benefits have also emerged in remote interview contexts with reduced anxiety and social pressure contributing to improved performance. Here, we investigated episodic memory in mock-eyewitness interviews conducted in virtual environments (VE) and in-person face-to-face (FtF), where rapport-building behaviours were either present or absent. Main effects revealed when rapport was present and where interviews were conducted in a VE participants recalled more correct event information, made fewer errors and were more accurate. Moreover, participants in the VE plus rapport-building present condition outperformed participants in all other conditions. Feedback indicated both rapport and environment were important for reducing the social demands of a recall interview, towards supporting effortful remembering. Our results add to the emerging literature on the utility of virtual environments as interview spaces and lend further support to the importance of prosocial behaviours in applied contexts.