ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
A Rare Case of HIV-Induced Neutropenia Resulting in Haemophilus influenzae Septic Oligoarthritis: A Case-Based Literature Review

Septic arthritis is a medical emergency that rarely occurs without direct trauma to a joint, compromise or trauma to the synovium, or internal hematogenous seeding from bacteremia. Infection of a single joint space is a cause for concern, and infection of multiple joints is even more rare and concerning. Human immunodeficiency virus (HIV) renders patients particularly susceptible to encapsulated bacteria as it compromises opsonization, humoral immunity, as well as neutrophil function. Neutrophils play an important role in preventing and fighting off infections of the synovium, and it is well documented that compromised neutrophil function can result in this peculiar infection. HIV is popularly acknowledged for its suppression of the lymphoid division of the immune system, particularly CD4 T-cells suppression. However, HIV's effects on myeloid cells are largely overlooked in medical academia, specifically with respect to neutrophil dysfunction. We will explore a case where compromised neutrophil function results in rare infiltration of Haemophilus influenzae resulting in polyarticular septic arthritis.
Seismic Considerations for the Art Deco Interwar Reinforced-Concrete Buildings of Napier, New Zealand

Following the devastating 1931 Hawke's Bay earthquake, buildings in Napier and surrounding areas in the Hawke's Bay region were rebuilt in a comparatively homogenous structural and architectural style comprising the region's famous Art Deco stock. These interwar buildings are most often composed of reinforced concrete two-way space frames, and although they have comparatively ductile detailing for their date of construction, are often expected to be brittle, earthquake-prone buildings in preliminary seismic assessments. Furthermore, the likelihood of global collapse of an RC building during a design-level earthquake became an issue warranting particular attention following the collapse of multiple RC buildings in the February 22, 2011 Christchurch earthquake. Those who value the architectural heritage and future use of these iconic Art Deco buildings-including building owners, tenants, and city officials, among others-must consider how they can be best preserved and utilized functionally given the especially pressing implications of relevant safety, regulatory, and economic factors. This study was intended to provide information on the seismic hazard, geometric weaknesses, collapse hazards, material properties, structural detailing, empirically based vulnerability, and recommended analysis approaches particular to Art Deco buildings in Hawke's Bay as a resource for professional structural engineers tasked with seismic assessments and retrofit designs for these buildings. The observed satisfactory performance of similar low-rise, ostensibly brittle RC buildings in other earthquakes and the examination of the structural redundancy and expected column drift capacities in these buildings, led to the conclusion that the seismic capacity of these buildings is generally underrated in simple, force-based assessments. (C) 2014 American Society of Civil Engineers.
A Comprehensive State-of-the-Art Survey on the Transmission Network Expansion Planning Optimization Algorithms

Long term planning in power transmission network expansion provides a well ordered and profitable extension of power equipment and facilities to meet the expected electric energy demand with an allowable degree of reliability. However, high quality and improved reliability in energy supply have to be balanced with the available funds. The need to expand transmission network can never be over emphasized. Transmission Network Expansion Planning (TNEP) is a periodical measure that must be carried out due to dynamic societies that attract extra energy demands. It is highly important to minimize the network reinforcement and operational costs while satisfying the increase in demand imposed by technical and economic conditions over the planning horizon. Several optimization algorithms for TNEP problems have been developed and applied over the past decades. This paper presents a comprehensive state-of-the-art survey on the TNEP optimization algorithms. The approach of this paper is in the area of highlights of the various available TNEP algorithms, their applications, viability, computational complexities and drawbacks, which can aid in the identifications of the proper methods that can yield an optimal solution to TNEP problem.
Dynamic Complexity Measures for Use in Complexity-Based System Design

Difficulty predicting system behaviors introduces a certain level of complexity to a system design. The INCOSE systems engineering handbook indicates that system complexity is one of the seven key challenges influencing development when engineering a system of systems. The scope of this paper is first to survey systems engineering relevant definitions of complexity for latter application to the complexity evaluation framework. The literature search also includes state-of-the-art works on system complexity measurement. Before proposing new techniques, the current complexity-based system, and interface measurement and design techniques are explored. As the state-of-the-art only includes static/ structural complexity quantification, entropy-based measures for dynamic complexity quantification are proposed. A sample system is evaluated using the proposed dynamic complexity measures and the results are discussed. The methods proposed herein provide a first step in the path to an enhanced system/ interface complexity evaluation framework using dynamic complexity measures.
Design Optimization Considering Guiding Template Feasibility and Redundant Via Insertion for Directed Self-Assembly

While multiple patterning lithography suffers from considerable and increasing mask manufacturing cost, next generation lithography technologies are urgently required for sub-10 nm technology nodes, where directed self-assembly (DSA) is one of the most promising candidates for contact/via layer fabrication. In addition, redundant via insertion is regarded as an important step in the circuit design flow to improve circuit reliability and yield. In this paper, we propose to adopt wire perturbation to further enhance via manufacturability and redundant via insertion rates. In addition, an improved DSA-compliant and redundant via-aware routing graph model is proposed and a systematic via graph update approach is developed to facilitate the implementation of the router. Experimental results demonstrate that compared with a state-of-the-art work, our wire perturbation approach can averagely increase inserted redundant vias by 6% and reduce unmanufacturable vias by 23% with only 0.9% wirelength overhead, and our routing graph model achieves the same performance as the one proposed in a state-of-the-art work and is much more efficient.
Collaborative Convolution Operators for Real-Time Coarse-to-Fine Tracking

Discriminative correlation filter (DCF) has attracted enormous popularity among the tracking community. Standard DCF based trackers easily achieve real-time tracking speed but significantly suffer from the boundary effects. Recently, spatially regularized or constrained correlation filters tackle the problem of boundary effects at the sacrifice of the closed-form element-wise solution. In this paper, we cope with boundary effects from a novel perspective and present a coarse-to-fine tracking (CTFT) framework which breaks the task of visual tracking into two stages. In the first stage, CTFT locates the target coarsely with a deep convolution operator in a large search area. In the second stage, CTFT performs a fine-grained search of the target with a shallow convolution operator around the initial location in the first stage. With this two-stage tracking framework, CTFT holds a large target search area and maintains the efficient element-wise solution of standard DCF. Compared with state-of-the-art deep trackers, CTFT makes a good balance between computational efficiency and accuracy. Extensive experimental results on OTB2013 and OTB2015 demonstrate that CTFT maintains real-time performance at an average tracking speed of 35.8 fps and achieves favorable performance against state-of-the-art trackers.
Improvement of Stability for Small Molecule Organic Solar Cells by Suppressing the Trap Mediated Recombination

To understand the degradation mechanism of organic solar cells (OSCs), the charge dynamics of conventional and inverted planar heterojunction OSCs based on boron subthalocyanine chloride (SubPc) and fullerene (C60) with identical buffers during the air exposure were investigated. The results of light intensity dependent open circuit voltage show that the bimolecular recombination is dominated in the fresh devices, regardless of the device structure. The appearance of transient peak in photocurrent after turn-on and the light intensity independent turn-off traces in transient photocurrent suggest that the rapid degradation of conventional device is due to the energy loss originated from the aggravated trap mediated recombination. In contrast, the half-lifetime of inverted device is ∼25 times longer than the conventional one. The improvement of stability is ascribed to the decrease of the trap generation possibility and the suppression of trap mediated recombination in the case of inverted structure, where the penetration of oxygen and water through buffer layer is avoided.
Domain Transformation-Based Efficient Cost Aggregation for Local Stereo Matching

Binocular stereo matching is one of the most important algorithms in the field of computer vision. Adaptive support-weight approaches, the current state-of-the-art local methods, produce results comparable to those generated by global methods. However, excessive time consumption is the main problem of these algorithms since the computational complexity is proportionally related to the support window size. In this paper, we present a novel cost aggregation method inspired by domain transformation, a recently proposed dimensionality reduction technique. This transformation enables the aggregation of 2-D cost data to be performed using a sequence of 1-D filters, which lowers computation and memory costs compared to conventional 2-D filters. Experiments show that the proposed method outperforms the state-of-the-art local methods in terms of computational performance, since its computational complexity is independent of the input parameters. Furthermore, according to the experimental results with the Middlebury dataset and real-world images, our algorithm is currently one of the most accurate and efficient local algorithms.
Advances in hydrostatic leveling with the NPH6, and suggestions for further enhancements

This paper reviews the state-of-the-art of hydrostatic leveling and tilt measurement, with an emphasis on the Pellissier H5, and the National Radio Astronomy Observatory NPH6. Details of the NPH6 design are described, experimental results are discussed, suggestions are made for further enhancements, and additional potential applications are offered. (c) 2004 Elsevier Inc. All rights reserved.
The Effect of Obstructive Sleep Apnea on Sleep-dependent Emotional Memory Consolidation

Rationale: A growing body of evidence suggests that sleep is critical for the adaptive processing and consolidation of emotional information into long-term memory. Previous research has indicated that emotional components of scenes particularly benefit from sleep in healthy groups, yet sleep-dependent emotional memory processes remain unexplored in clinical cohorts, including those with obstructive sleep apnea (OSA). This line of research is important as it will add to the understanding of how disrupted sleep in OSA contributes to both impaired cognition and emotion dysregulation. Objectives: To test the hypothesis that individuals with OSA will have impaired sleep-dependent memory consolidation, with the greatest impact being on memory for emotional content. Methods: In this study, a group of newly diagnosed patients with OSA (n = 26; 10 female; average age, 42.5 years) and a matched group of healthy control subjects (n = 24; 13 female; average age, 37 years) were enrolled in the study at Beth Israel Deaconess Medical Center. Participants encoded scenes with negative or neutral foreground objects placed on neutral backgrounds before a night of polysomnographically recorded sleep. In the morning, they completed a recognition test in which old and new scene objects and backgrounds, presented separately and one at a time, were judged as old, new, or similar compared with what had been previously viewed. Results: Patients with OSA had a deficit in recognition memory for the scenes. Overall recognition (the ability to recognize old items as either old or similar) was impaired across all scene elements, both negative and neutral objects and backgrounds, whereas specific recognition (correctly identifying old items as old) was impaired only for negative objects. Across all participants, successful overall recognition correlated positively with sleep efficiency and rapid eye movement (REM) sleep, whereas successful specific memory recognition correlated only with REM sleep. Conclusions: Our findings indicate that fragmented sleep and reduced REM sleep, both hallmarks of OSA, are associated with disruptions in general memory impairment and veridical memory for emotional content, which could alter emotional regulation and contribute to comorbid emotional distress in OSA.
Implementation of Tele-Intensive Care Unit Services During the COVID-19 Pandemic: A Systematic Literature Review and Updated Experience from Shandong Province

Background: While the use of telemedicine had been expanding before the initial outbreak of COVID-19, the pandemic has dramatically accelerated its implementation and expanded its usage in many hospitals. Tele-intensive care unit (ICU) is a specialized type of telemedicine that adapts available technologies to the unique needs of critically ill patients. We published an editorial in 2020 describing our initial experiences of Tele-ICU application in Shandong Province. Here, we update our insights gained over the past 2 years, and we provide a systematic review of the literature to compare our perspectives with those from other institutions. Methods: We performed a systematic literature review of publications describing the use of telemedicine in an ICU setting during COVID-19. The PubMed database was searched for studies published after January 1, 2020, which offered detailed descriptions of tele-ICU usage. Extracted data included details regarding tele-ICU technologies, descriptions of the institution, usage cases, assessments of tele-ICU effectiveness, and site-reported opinions (e.g., advantages, disadvantages). Results: We screened 162 studies resulting from the PubMed literature search, along with one expert recommendation. Of the 112 full-text articles retrieved, 11 were selected for inclusion in this qualitative summary. All were retrospective descriptions of tele-ICU experiences at a single site. Some pairs of included articles reported results from the same institution, with seven unique sites being described. Three sites employed centralized models of tele-ICU, while four allowed staff to participate from distant locations. Five sites collected user-reported feedback regarding tele-ICU. While the advantages and disadvantages described rarely overlapped directly between sites, many reported positive opinions of tele-ICU use overall. Conclusions: The potential applications of tele-ICU technologies vary widely, making them highly adaptable to the needs of individual institutions. Tele-ICU has proven invaluable to some hospitals during COVID-19 due to its effectiveness at aiding patient care while mitigating risk to health care workers.
A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation

In an inhomogeneously illuminated photoacoustic image, important information like vascular geometry is not readily available, when only the initial pressure is reconstructed. To obtain the desired information, algorithms for image segmentation are often applied as a post-processing step. In this article, we propose to jointly acquire the photoacoustic reconstruction and segmentation, by modifying a recently developed partially learned algorithm based on a convolutional neural network. We investigate the stability of the algorithm against changes in initial pressures and photoacoustic system settings. These insights are used to develop an algorithm that is robust to input and system settings. Our approach can easily be applied to other imaging modalities and can be modified to perform other high-level tasks different from segmentation. The method is validated on challenging synthetic and experimental photoacoustic tomography data in limited angle and limited view scenarios. It is computationally less expensive than classical iterative methods and enables higher quality reconstructions and segmentations than the state-of-the-art learned and non-learned methods.
Antibiotics administration alleviates the high fat diet-induced obesity through altering the lipid metabolism in young mice

Currently, there is a global trend of rapid increase in obesity, especially among adolescents. The antibiotics cocktails (ABX) therapy is commonly used as an adjunctive treatment for gut microbiota related diseases, including obesity. However, the effects of broad-spectrum antibiotics alone on young obese hosts have rarely been reported. In the present study, the 3-week-old C57BL/6J male mice fed a high-fat diet (HFD) were intragastric administration with ampicillin, vancomycin, metronidazole or neomycin for 30 days. The lipid metabolites in plasma were assessed by biochemical assay kits, and genes related to lipid metabolite in the white adipose were assessed by qPCR. To further analyze the underlying mechanisms, the expression of genes related to lipid metabolism, inflammatory reactions and oxidative stress in the liver were determined by qPCR assay. In addition, the expression of oxidative damage-associated proteins in the liver were detected by western blot. The results showed that oral antibiotics exposure could reduce body weight and fat index in HFD-fed mice, concurrent with the increase of white adipose lipolysis genes and the decrease of hepatic lipogenic genes. Furthermore, antibiotics treatment could clearly reverse the HFD-induced elevation of oxidative damage-related proteins in the liver. Together, these findings will provide valuable clues into the effects of antibiotics on obesity.
Host-microbiota interactions play a crucial role in oyster adaptation to rising seawater temperature in summer

Climate change, represented by rising and fluctuating temperature, induces systematic changes in marine organisms and in their bacterial symbionts. However, the role of host-microbiota interactions in the host's response to rising temperature and the underlying mechanisms are incompletely understood in marine organisms. Here, the symbiotic intestinal microbiota and transcriptional responses between diploid and triploid oysters that displayed susceptible and resistant performance under the stress of rising temperature during a summer mortality event were compared to investigate the host-microbiota interactions. The rising and fluctuating temperatures triggered an earlier onset and higher mortality in susceptible oysters (46.7%) than in resistant oysters (17.3%). Correlation analysis between microbial properties and environmental factors showed temperature was strongly correlated with indices of α-diversity and the abundance of top 10 phyla, indicating that temperature significantly shaped the intestinal microbiota of oysters. The microbiota structure of resistant oysters exhibited more rapid changes in composition and diversity compared to susceptible oysters before peak mortality, indicating that resistant oysters possessed a stronger ability to regulate their symbiotic microbiota. Meanwhile, linear discriminant analysis effect size (LefSe) analysis found that the probiotics Verrucomicrobiales and Clostridiales were highly enriched in resistant oysters, and that potential pathogens Betaproteobacteriales and Acidobacteriales were enriched in susceptible oysters. These results implied that the symbiotic microbiota played a significant role in the oysters' adaptation to rising temperature. Accompanying the decrease in unfavorable bacteria before peak mortality, genes related to phagocytosis and lysozymes were upregulated and the xenobiotics elimination pathway was exclusively expressed in resistant oysters, demonstrating the validity of these immunological functions in controlling proliferation of pathogens driven by rising temperature. Compromised immunological functions might lead to proliferation of pathogens in susceptible oysters. This study might uncover a conserved mechanism of adaptation to rising temperature in marine invertebrates from the perspective of interactions between host and symbiotic microbiota.
Fully Connected Generative Adversarial Network for Human Activity Recognition

Conditional Generative Adversarial Networks (CGAN) have shown great promise in generating synthetic data for sensor-based activity recognition. However, one key issue concerning existing CGAN is the design of the network architecture that affects sample quality. This study proposes an effective CGAN architecture that synthesizes higher quality samples than state-of-the-art CGAN architectures. This is achieved by combining convolutional layers with multiple fully connected networks in the generator's input and discriminator's output of the CGAN. We show the effectiveness of the proposed approach using elderly data for sensor-based activity recognition. Visual evaluation, similarity measure, and usability evaluation are used to assess the quality of generated samples by the proposed approach and validate its performance in activity recognition. In comparison to the state-of-the-art CGAN, the visual evaluation and similarity measure demonstrate that the proposed models' synthetic data more accurately represents actual data and creates more variations in each synthetic data than the state-of-the-art approach respectively. The experimental stages of the usability evaluation, on the other hand, show a performance gain of 2.5%, 2.5%, 3.1%, and 4.4% over the state-of-the-art CGAN when using synthetic samples by the proposed architecture.
A survey on secure multipath routing protocols in WSNs

Routing protocols in wireless sensor networks (WSN) have been substantially investigated by researches. Most state-of-the-art surveys have focused on reviewing the different routing schemes that have been proposed for WSN and classifying them based on the network's type and protocol's operation. Security aspects in routing protocols have not been given enough attention, since most of the routing protocols in WSNs have not been designed with security requirements in mind. However, taking into consideration that WSN applications need to support critical infrastructures (i.e., military, healthcare, environmental, etc.), security becomes an issue. And since these infrastructures are highly depended on the availability of resources, focus has especially been given to support a secure, resilient and reliable environment, with multipath routing being one of the added functionalities. The need for security in sensitive WSN application has lead researchers to design secure multipath routing protocols from the beginning or design security extensions for existing protocols. This paper surveys the current state-of-the-art of secure multipath routing protocols in WSNs, classifies the protocols in categories according to their security-related operational objectives, defines a new threat model in the routing procedure and identifies open research issues in the area. (C) 2010 Elsevier B.V. All rights reserved.