ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
ARTS: A Framework for AI-Rooted IoT System Design Automation

IoT systems are used for performing a variety of essential tasks in wide-ranging sectors, such as healthcare, smart cities, agriculture, and industrial automation. Most of these systems incorporate smartness for intelligent decision making using artificial intelligence (AI) approaches. To reduce the network bandwidth usage and load on the cloud server, there is a push to relegate most of these AI-related computations to edge IoT devices/systems. Hence, to ensure good performance, the edge devices must be systematically designed with an emphasis on the respective AI requirements from exploration to deployment. State-of-the-art IoT device and system design practices place little importance on the AI specifications during the early stages of the system development resulting in systems, which are unable to meet the AI specifications without additional redesigning and optimization efforts. In this letter, we propose an automated framework for AI-rooted IoT system design approach, where the AI specifications play a vital role in deciding the system components, design, and implementation from a very early stage of the design life cycle. The proposed framework employs an expert system and a machine-readable knowledge-base to automate the design process. Using a set of case studies, we demonstrate the benefits of the proposed framework.
Energy-aware strategy for collaborative target-detection in wireless multimedia sensor network

Energy-efficiency in visual surveillance is the most important issue for wireless multimedia sensor network (WMSN) due to its energy-constraints. This paper addresses the trade-off between detection-accuracy and power-consumption by presenting an energy-aware scheme for detecting moving target based on clustered WMSN. The contributions of this paper are as follows; 1- An adaptive clustering and nodes activation approach is proposed based on residual energy of detecting nodes and the location of the object at the camera's field of view (FoV). 2- An effective cooperative features-pyramid construction method for collaborative target identification with low communication cost. 3- An in-network collaboration mechanism for cooperative detection of the target is proposed. The performance of this scheme is evaluated using both standard datasets and personal recorded videos in terms of detection-accuracy and power-consumption. Compared with state-of-the-art methods, our proposed strategy greatly reduces energy-consumption and saves more than 65% of the network-energy. Detection-accuracy rate of our strategy is 11% better than other recent works. We have increased the Precision of classification up to 49% and 65% and the Recall of classification up to 53% and 71% for specific-target and object-type respectively. These results demonstrate the superiority of our scheme over the recent state-of-the-art works.
The Effect of Long-Term Iron Chelator Therapy on Serum Levels of Hepcidin and Ferritin in Patients with Thalassemia Major and Intermediate

Serum hepcidin is a good predictor of iron overload compared with serum ferritin. However, serum hepcidin levels may change under different conditions. The current study aims to determine the role of long-term iron chelator therapy on serum levels of hepcidin and ferritin in patients with thalassemia major (TM) and intermediate (TI). In this cross-sectional study 91 patients with thalassemia TM and TI, who referred to the thalassemia center were chosen. The serum levels of hepcidin and ferritin were measured after two years of iron chelator therapy by ELISA and ECL methods, respectively. The patients' demographic information was extracted from their records. After treatment with iron chelator, ferritin levels decreased in 44 patients (48.4%), and increased in 47 patients (%51.6). Median serum levels of hepcidin decreased in all patients (%100). Also, there was a significant association between serum levels of hepcidin and ferritin (p value = 0.034). Furthermore, while a significant difference was observed between ferritin changes (p = 0.01), no difference was found between changes in hepcidin based on the type of iron chelator (p value = 0.94). Increased levels of hepcidin and ferritin in β-thalassemia patients are significantly ameliorated by iron chelator.
Towards Finite File Packetizations in Wireless Device-to-Device Caching Networks

We consider wireless device-to-device (D2D) caching networks with single-hop transmissions. Previous work has demonstrated that caching and coded multicasting can significantly increase per user throughput. However, the state-of-the-art coded caching schemes for D2D networks are generally impractical because content files are partitioned into an exponential number of packets with respect to the number of users if both library and memory sizes are fixed. In this paper, we present two combinatorial approaches of D2D coded caching network design with reduced packetizations and desired throughput gain compared to the conventional uncoded unicasting. The first approach uses a "hypercube" design, where each user caches a "hyperplane" in this hypercube and the intersections of "hyperplanes" represent coded multicasting codewords. In addition, we extend the hypercube approach to a decentralized design. The second approach uses the Ruzsa-Szemeredi graph to define the cache placement. Disjoint matchings on this graph represent coded multicasting codewords. Both approaches yield an exponential reduction of packetizations while providing a per-user throughput that is comparable to the state-of-the-art designs in the literature. Furthermore, we apply spatial reuse to the new D2D network designs to further reduce the required packetizations and significantly improve per user throughput for some parameter regimes.
Role of C-terminal domain of Mycobacterium tuberculosis PE6 (Rv0335c) protein in host mitochondrial stress and macrophage apoptosis

PE/PPE proteins of Mycobacterium tuberculosis (Mtb) target the host organelles to dictate the outcome of infection. This study investigated the significance of PE6/Rv0335c protein's unique C-terminal in causing host mitochondrial perturbations and apoptosis. In-silico analysis revealed that similar to eukaryotic apoptotic Bcl2 proteins, Rv0335c had disordered, hydrophobic C-terminal and two BH3-like motifs in which one was located at C-terminal. Also, Rv0335c's N terminal had mitochondrial targeting sequence. Since, C-terminal of Bcl2 proteins are crucial for mitochondria targeting and apoptosis; it became relevant to evaluate the role of Rv0335c's C-terminal domain in modulating host mitochondrial functions and apoptosis. To confirm this, in-vitro experiments were conducted with Rv0335c whole protein and Rv0335c∆Cterm (C-terminal domain deleted Rv0335c) protein. Rv0335c∆Cterm caused significant reduction in mitochondrial perturbations and Caspase-mediated apoptosis of THP1 macrophages in comparison to Rv0335c. However, the deletion of C-terminal domain didn't affect Rv0335c's ability to localize to mitochondria. Nine Ca2+ binding residues were predicted within Rv0335c and four of them were at the C-terminal. In-vitro studies confirmed that Rv0335c caused significant increase in intracellular calcium influx whereas Rv0335c∆Cterm had insignificant effect on Ca2+ influx. Rv0335c has been reported to be a TLR4 agonist and, we observed a significant reduction in the expression of TLR4-HLA-DR-TNF-α in response to Rv0335c∆Cterm protein also suggesting the role of Rv0335c's C-terminal domain in host-pathogen interaction. These findings indicate the possibility of Rv0335c as a molecular mimic of eukaryotic Bcl2 proteins which equips it to cause host mitochondrial perturbations and apoptosis that may facilitate pathogen persistence.
An Examination of Predictors of Prejudice against Transgender Individuals

We examined associations between prejudice toward transgender people, aggression proneness, history of family violence, contact and closeness with transgender people, and education about issues that impact transgender individuals. We also examined the moderating effects of contact, education, and closeness on the relations between aggression and history of family violence with prejudice. There were 360 participants (M age = 31.34, SD = 12.47, range 18-75) who completed the survey online. Participants were recruited through social media, websites, and MTurk. Higher levels of aggression proneness were related to higher levels of prejudice. Higher levels of education about issues that impact transgender people and prior contact with a transgender person were associated with less prejudice. In a multiple regression analysis, the strongest predictor of prejudice was education about transgender people and topics. Moderation analyses revealed that prior contact may buffer the effects of aggression proneness on prejudiced beliefs.
More Than Meets the Eyes: Bringing Attention to the Eyes Increases First Impressions of Warmth and Competence

The present research examined how face masks alter first impressions of warmth and competence for different racial groups. Participants were randomly assigned to view photographs of White, Black, and Asian targets with or without masks. Across four separate studies (total N = 1,012), masked targets were rated significantly higher in warmth and competence compared with unmasked targets, regardless of their race. However, Asian targets benefited the least from being seen masked compared with Black or White targets. Studies 3 and 4 demonstrate how the positive effect of masks is likely due to these clothing garments re-directing attention toward the eyes of the wearer. Participants viewing faces cropped to the eyes (Study 3), or instructed to gaze into the eyes of faces (Study 4), rated these targets similarly to masked targets, and higher than unmasked targets. Neither political affiliation, belief in mask effectiveness, nor explicit racial prejudice moderated any hypothesized effects.
An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA.
Segmentation-Based Background-Inference and Small-Person Pose Estimation

Despite encouraging results have been achieved in human pose estimation in recent years, it remains challenging problems. When the background is similar to the human body parts, and there are small persons with low-resolution in the image, the performance may degrade dramatically. This paper addresses problems in background-inference and small-person pose estimation. To achieve this, a novel pose estimation algorithm is proposed on the basis of person semantic segmentation deep neural network. Different from most previous methods with a single pose estimation model, we generate mixture models with pose estimation and semantic segmentation. We introduce novel generative adversarial model and auxiliary model to realize the semantic segmentation network, which can handle the confusion of the similar regions in the background. In addition, to address the problem of the scale differences between big and small persons' keypoints, we add additional position and channel attention modules to the first two stages of OpenPose. We conduct extensive experiments on COCO and VOC datasets. And we compare the proposed method with the most popular state-of-the-art human pose estimation and semantic segmentation frameworks, including MultiPoseNet, Deterton2 and DeepLab V3. Our experimental results show that the proposed method is more accurate than the state-of-the-art algorithms and performs effectively in tackling the complex situations.
Probing the importance of lipid diversity in cell membranes via molecular simulation

Lipid membranes in prokaryotes and eukaryotes have a wide array of lipids that are necessary for proper membrane structure and function. In this paper, an introduction to lipid diversity in biology and a mini-review on how molecular simulations have been used to model biological membranes (primarily limited to one to three lipid types in most simulation-based models) is provided, which motivates the use of all-atom molecular dynamics (MD) simulations to study the effect of lipid diversity on properties of realistic membrane models of prokaryotes and eukaryotes. As an example, cytoplasmic membrane models of Escherichia coli were developed at different stages of the colony growth cycle (early-log, mid-log, stationary and overnight). The main difference between lipid compositions at each stage was the concentration of a cyclopropane-containing moiety on the sn-2 lipid acyl chain (cyC17:0). Triplicate MD simulations for each stage were run for 300 ns to study the influence of lipid diversity on the surface area per lipid, area compressibility modulus, deuterium order parameters, and electron density profiles. The overnight stage (also known as the death stage) had the highest average surface area per lipid, highest rigidity, and lowest bilayer thickness compare to other stages of E. coli cytoplasmic membrane. Although bilayer thickness did depend on the growth stage, the changes between these were small suggesting that the hydrophobic core of transmembrane proteins fit well with the membrane in all growth stages. Although it is still common practise in MD simulations of membrane proteins to use simple one- or two-component membranes, it can be important to use diverse lipid model membranes when membrane protein structure and function are influenced by changes in lipid membrane composition.
Recommendations from the association for professionals in infection control and epidemiology health inequalities & disparities task force

In June 2021, a task force commissioned by the Board of Directors of the Association for Professionals in Infection Prevention and Epidemiology (APIC) evaluated the landscape of health inequity and health disparities as they apply to infection prevention in health care settings. This task force, consisting of infection preventionists across the country, convened to evaluate current literature, identify relevant issues and make recommendations to the APIC Board of Directors for action steps to be taken.
Selections from the history of environmental pollution, with special attention to air pollution. Part 2: From medieval times to the 19th century

Several comprehensive publications have been issued recently on the environmental pollution of past times, especially from medieval times (e.g. Brimblecombe, 1987a; Goldstein, 1988; Brimblecombe and Pfister, 1990; Hughes, 1993; Markham, 1994; Brimblecombe, 1995). The aim of this paper is to give an over-view of information on the subject-mainly related to the period between medieval times and the 19th century.
Effect of queen cell numbers on royal jelly production and quality

Royal jelly (RJ) is a popular functional food with a wealth of health-promoting effects. Over 90% of the global RJ is produced in China mainly by a high RJ-producing honeybee (RJB) strain that can accept and feed a great number of queen larvae for RJ production. To elucidate RJ changes due to queen cell numbers (QCNs), we compared the yield, larval acceptance rate, metabolic and proteomic profiles, and antioxidant activities of RJ from 1 to 5 strips of queen cells (64 per strip) in RJB colonies. As QCNs increased, the larval acceptance rate was not found to vary (p = 0.269) whereas the RJ weight per cell began to significantly decline in the 5-strip colonies (p < 0.05). Increased QCNs had a profound impact on RJ metabolic profiles and mainly reduced fatty acid levels. Remarkably, the 10-hydroxy-2-decenoic acid (10-HDA) content, a most important indicator of RJ quality, declined gradually from 2.01% in the 1-strip colonies to 1.52% in the 5-strip colonies (p < 0.001). RJ proteomic profiles were minimally altered and antioxidant activities were not significantly changed by QCNs. Collectively, the metabolomics and proteomics data and the antioxidant activity test represent a global evaluation of the quality of RJ produced with different QCNs. Our findings gain new insights into higher-quality RJ production using the high-yielding RJBs.
Erosion rates and weathering history of rock surfaces associated with Aboriginal rock art engravings (petroglyphs) on Burrup Peninsula, Western Australia, from cosmogenic nuclide measurements

The Burrup Peninsula and surrounding Dampier Archipelago, in Western Australia, contain the world's largest known gallery of rock art engravings (petroglyphs), estimated to number up to 1 million images. The peninsula is also the site of major industrial development and there are concerns that industrial emissions may adversely affect the stability and longevity of the rock art. We have studied the natural processes and rates of weathering and erosion, including the effects of fire, that affect the stability of rock surfaces and hence the longevity of the rock art, using cosmogenic nuclides. The concentration of Be-10 in quartz yields erosion rates in the range 0.15-0.48 mm/1000 years on horizontal rock surfaces and 0.34-2.30 mm/1000 years on vertical rock faces. The former, largely caused by mm-scale surface flaking, are amongst the lowest erosion rates measured by cosmogenic nuclides anywhere in the world. The latter are inferred to represent a combination of mm-scale flaking and very rare centimetre-to metre-scale block falls, controlled by failure along joint planes. Such low erosion rates result from a combination of resistant rocks, low relief and low rainfall, favouring long-term preservation of the petroglyphs - long enough to encompass the known period of human settlement in Australia. (c) 2013 Elsevier Ltd. All rights reserved.
A Cross-Domain Metal Trace Restoring Network for Reducing X-Ray CT Metal Artifacts

Metal artifacts commonly appear in computed tomography (CT) images of the patient body with metal implants and can affect disease diagnosis. Known deep learning and traditional metal trace restoring methods did not effectively restore details and sinogram consistency information in X-ray CT sinograms, hence often causing considerable secondary artifacts in CT images. In this paper, we propose a new cross-domain metal trace restoring network which promotes sinogram consistency while reducing metal artifacts and recovering tissue details in CT images. Our new approach includes a cross-domain procedure that ensures information exchange between the image domain and the sinogram domain in order to help them promote and complement each other. Under this cross-domain structure, we develop a hierarchical analytic network (HAN) to recover fine details of metal trace, and utilize the perceptual loss to guide HAN to concentrate on the absorption of sinogram consistency information of metal trace. To allow our entire cross-domain network to be trained end-to-end efficiently and reduce the graphic memory usage and time cost, we propose effective and differentiable forward projection (FP) and filtered back-projection (FBP) layers based on FP and FBP algorithms. We use both simulated and clinical datasets in three different clinical scenarios to evaluate our proposed network's practicality and universality. Both quantitative and qualitative evaluation results show that our new network outperforms state-of-the-art metal artifact reduction methods. In addition, the elapsed time analysis shows that our proposed method meets the clinical time requirement.
Does Pacemaker Implantation After Surgical Aortic Valve Replacement Impact Long-Term Morbidity and Mortality? A Focused Review

Permanent pacing remains a serious complication that can occur in the postoperative period of surgical aortic valve replacement. The reported incidence is variable, and there are many perioperative factors that have been linked with a greater need for permanent pacing. Permanent pacing can also be associated with late lead-related and cardiac complications that can affect late outcome. However, the degree of late dependence on pacemakers is varied, and some studies have shown that a substantial proportion of patients do not need long-term pacing. Some groups have found that permanent pacing was associated with a negative impact on long-term survival in these patients. A common finding among these studies is that the groups of patients with pacemakers had higher preoperative surgical risk and comorbidity status. This makes it difficult to establish whether permanent pacing on its own represents a risk factor for late mortality or whether it is simply a marker that reflects the higher complexity and comorbidities in this group of patients.
Chordae Tendineae Approximation Technique for Severe Tricuspid Regurgitation with Severe Leaflet Tethering Using a Totally Endoscopic Beating-Heart Strategy: A Case Report

Untreated severe tricuspid regurgitation (TR) is associated with poor outcomes. Functional TR occurs secondary to dilatation of the annulus and tethering of the leaflets. Ring annuloplasty alone can correct most cases, but is insufficient in cases of severe annular dilatation due to severe leaflet tethering. In such cases, a tricuspid edge-to-edge technique may be an option. However, stitching of the leaflet tips alone is likely to result in tearing of the leaflets. Approximation of the durable chordae tendineae is considered helpful for this problem. Herein, we present the case of a 39-year-old man who had undergone openheart surgery for acute type A aortic dissection 13 months earlier. A right mini-thoracotomy approach with a beating-heart strategy was used, which did not require unnecessary pericardial adhesiolysis and dissection. This technique had the advantage of reducing the operation time and the risk of bleeding. To summarize, we present a case of tricuspid valve repair in a high-risk patient with severe leaflet tethering that was successfully managed using these methods.