Miracle-dz/UniFAR-FTUs huggingface dataset:
The Importance of Arterial Stiffness Assessment in Patients with Familial Hypercholesterolemia

Cardiovascular diseases are still the leading cause of mortality due to increased atherosclerosis worldwide. In the background of accelerated atherosclerosis, the most important risk factors include hypertension, age, male gender, hereditary predisposition, diabetes, obesity, smoking and lipid metabolism disorder. Arterial stiffness is a firmly established, independent predictor of cardiovascular risk. Patients with familial hypercholesterolemia are at very high cardiovascular risk. Non-invasive measurement of arterial stiffness is suitable for screening vascular dysfunction at subclinical stage in this severe inherited disorder. Some former studies found stiffer arteries in patients with familial hypercholesterolemia compared to healthy controls, while statin treatment has a beneficial effect on it. If conventional drug therapy fails in patients with severe familial hypercholesterolemia, PCSK9 inhibitor therapy should be administered; if these agents are not available, performing selective LDL apheresis could be considered. The impact of recent therapeutic approaches on vascular stiffness is not widely studied yet, even though the degree of accelerated athero and arteriosclerosis correlates with cardiovascular risk. The authors provide an overview of the diagnosis of familial hypercholesterolemia and the findings of studies on arterial dysfunction in patients with familial hypercholesterolemia, in addition to presenting the latest therapeutic options and their effects on arterial elasticity parameters.
Detection of endo-epicardial atrial low-voltage areas using unipolar and omnipolar voltage mapping

Background: Low-voltage areas (LVA) can be located exclusively at either the endocardium or epicardium. This has only been demonstrated for bipolar voltages, but the value of unipolar and omnipolar voltages recorded from either the endocardium and epicardium in predicting LVAs at the opposite layer remains unknown. The goal of this study was therefore to compare simultaneously recorded endo-epicardial unipolar and omnipolar potentials and to determine whether their voltage characteristics are predictive for opposite LVAs. Methods: Intra-operative simultaneous endo-epicardial mapping (256 electrodes, interelectrode distances 2 mm) was performed during sinus rhythm at the right atrium in 93 patients (67 ± 9 years, 73 male). Cliques of four electrodes (2 × 2 mm) were used to define maximal omnipolar (Vomni,max) and unipolar (Vuni,max) voltages. LVAs were defined as Vomni,max ≤0.5 mV or Vuni,max ≤1.0 mV. Results: The majority of both unipolar and omnipolar LVAs were located at only the endocardium (74.2% and 82.0% respectively) or epicardium (52.7% and 47.6% respectively). Of the endocardial unipolar LVAs, 25.8% were also located at the opposite layer and 47.3% vice-versa. In omnipolar LVAs, 18.0% of the endocardial LVAs were also located at the epicardium and 52.4% vice-versa. The combination of epicardial Vuni,max and Vomni,max was most accurate in identifying dual-layer LVAs (50.4%). Conclusion: Unipolar and omnipolar LVAs are frequently located exclusively at either the endocardium or epicardium. Endo-epicardial LVAs are most accurately identified using combined epicardial unipolar and omnipolar voltages. Therefore, a combined endo-epicardial unipolar and omnipolar mapping approach is favoured as it may be more indicative of possible arrhythmogenic substrates.
Multiresolution Aggregation Transformer UNet Based on Multiscale Input and Coordinate Attention for Medical Image Segmentation

The latest medical image segmentation methods uses UNet and transformer structures with great success. Multiscale feature fusion is one of the important factors affecting the accuracy of medical image segmentation. Existing transformer-based UNet methods do not comprehensively explore multiscale feature fusion, and there is still much room for improvement. In this paper, we propose a novel multiresolution aggregation transformer UNet (MRA-TUNet) based on multiscale input and coordinate attention for medical image segmentation. It realizes multiresolution aggregation from the following two aspects: (1) On the input side, a multiresolution aggregation module is used to fuse the input image information of different resolutions, which enhances the input features of the network. (2) On the output side, an output feature selection module is used to fuse the output information of different scales to better extract coarse-grained information and fine-grained information. We try to introduce a coordinate attention structure for the first time to further improve the segmentation performance. We compare with state-of-the-art medical image segmentation methods on the automated cardiac diagnosis challenge and the 2018 atrial segmentation challenge. Our method achieved average dice score of 0.911 for right ventricle (RV), 0.890 for myocardium (Myo), 0.961 for left ventricle (LV), and 0.923 for left atrium (LA). The experimental results on two datasets show that our method outperforms eight state-of-the-art medical image segmentation methods in dice score, precision, and recall.
Functional Characterization and Whole-Genome Analysis of an Aflatoxin-Degrading Rhodococcus pyridinivorans Strain

Simple Summary The microbiological degradation of AFB1 has been a promising approach to control AFB1 contamination. Here, we characterize a Rhodococcus pyridinivorans strain that can efficiently degrade AFB1. The AFB1-degrading capacity of this bacterial strain was characterized, and the completed genome was sequenced and analyzed. Further proteomic analyses of this strain identified a total of 723 proteins in an extracellular component that showed the strongest capacity to degrade AFB1 (degradation rate 83.7%). Multiple potential AFB1-degrading enzymes, and enzymes that are reported to respond to AFB1 treatment, have been identified accordingly. These findings provide a genomic, proteomic, and experimental approach for characterizing an efficient AFB1-degrading bacterial strain with great potential for use in the remediation of AFB1 contamination. Abstract Aflatoxin B1 (AFB1) is one of the most toxic, naturally occurring carcinogen compounds and is produced by specific strains of fungi. Crop contamination with AFB1 can cause huge economic losses and serious health problems. Many studies have examined the microbiological degradation of AFB1, especially the use of efficient AFB1-degrading microorganisms, to control AFB1 contamination. Here, we reported the identification of a new Rhodococcus pyridinivorans strain (4-4) that can efficiently degrade AFB1 (degradation rate 84.9%). The extracellular component of this strain showed the strongest capacity to degrade AFB1 (degradation rate 83.7%). The effects of proteinase K, SDS, temperature, pH, incubation time, and AFB1 concentration on the AFB1 degradation ability of the extracellular component were investigated. We sequenced the complete genome of this strain, encoding 5246 protein-coding genes and 169 RNA genes on a circular chromosome and two plasmids. Comparative genomic analysis revealed high homology with other Rhodococcus strains with high AFB1-degradation ability. Further proteomic analyses of this strain identified a total of 723 proteins in the extracellular component, including multiple potential AFB1-degrading enzymes, along with enzymes that are reported to response to AFB1 treatment. Overall, the results demonstrate that R. pyridinivorans 4-4 would be an excellent candidate for the biodegradation and detoxification of AFB1 contamination.
Development of Low‐Gain Avalanche Detectors in the Frame of the Acceptor Removal Phenomenon

Low‐gain avalanche detectors (LGAD) suffer from an acceptor removal phenomenon due to irradiation. This acceptor removal phenomenon is investigated in boron, gallium, and indium implanted samples by 4‐point‐probe (4pp) measurements, low‐temperature photoluminescence spectroscopy (LTPL), and secondary ion mass spectrometry (SIMS) before and after irradiation with electrons and protons. Different co‐implantation species are evaluated with respect to their ability to reduce the acceptor removal phenomenon. In case of boron, the beneficial effect is found to be most pronounced for the low‐dose fluorine and high‐dose nitrogen co‐implantation. In case of gallium, the low‐dose implantations of carbon and oxygen are found to be beneficial. For indium, the different co‐implantation species have no beneficial effect. SIMS boron concentration depth profiles measured before and after irradiation show no indication of a fast movement of boron at room temperature. Hence, the discussed BSi–Sii‐defect explanation approach of the acceptor removal phenomenon seems to be more likely than the other discussed Bi–Oi‐defect explanation approach.
TECHNOLOGY SECURITY ISSUES, ATTACKS AND CHALLENGES IN WIRELESS SENSOR NETWORK

Wireless Sensor Networks (WSN) is an emerging technology now-a-days and has a wide range of applications such as battlefield surveillance, traffic surveillance, forest fire detection, flood detection etc. But wireless sensor networks are susceptible to a variety of potential attacks which obstructs the normal operation of the network. The wireless sensor network nature of communication is unprotected and unsafe because of deployment in hostile environment, limited resources, an automated nature and untrusted broadcast transmission media. The most of security techniques are not sufficient in WSN network and security is a vital requirement for network. The intent of this paper is to investigate the security related issues, attacks and Challenges. The introductory sectio n gives brief information on the WSN components and its architecture. Then it deals with some of the major security issues and challenges over wireless sensor networks (WSNs).
Unknown Future, Repeated Present: A Narrative-Centered Analysis of Long-Term AI Discourse

Recent narratives and debates surrounding long-term AI concerns—the prospect of artificial general intelligence in particular—are fraught with hidden assumptions, priorities, and values. This paper employs a humanistic, narrative-centered approach to analyze the works of two vocal, and opposing, thinkers in the field—Luciano Floridi and Nick Bostrom—to ask how the representational, descriptive differences in their works reveal the high stakes of narrative choices for how we form ideas about humanity, urgency, risk, harm, and possibility in relation to AI. This paper closely reads Floridi and Bostrom using different representational models and historical narratives from works in the environmental humanities, literary theory, bioethics, and the history of technology to uncover the imaginative terrain of recent long-term AI discourse and reveal the complexity and limitations of the messaging underlying the works of different authors.
An evaluation of the impact of IT on multi-disciplinary team working

This paper describes feedback from a series of experimental student projects in multi- disciplinary team-working using information technology. The TIME-IT Project, (Team-working in Multi-disciplinary Environments using Information Technology) was devised by Jaki Howes (architect) and set up with help from Gerard Wood (QS) and staff from Civil Engineering and Construction Management. AutoDesk and Dell Computers provided equipment for a dedicated IT lab. Projects were planned by Abbey Holford Rowe (architects), Chapman Taylor (architects), Citex (project management and QS), Halifax plc, and Willmott Dixon (contractors) The project is now in its third year. Four teams of students, each team consisting of a final year degree level architect, civil engineer, construction manager and quantity surveyor, work competitively on ‘real’ projects that have been or will be carried out by one of the six industrial collaborators. Teams are expected to produce a PowerPoint presentation that included spatial arrangement and appearance, a full cost plan, a design and construction programme, a safety report and appropriate calculations. IT is used as much as possible. Students were assessed later on a critical evaluation of the process and their experience. Student summative evaluation forms are analysed, for the first time, in this paper.
Evaluating Active Transport Benefits and Costs

This report describes methods for evaluating the benefits and costs of active transport (walking, cycling, and their variants, also called non-motorized and human-powered travel). It describes various types of benefits, costs and methods for measuring them. These include direct benefits to users from improved active transport conditions, various benefits to society from increased walking and cycling activity, reduced motor vehicle travel, and more compact and multi-modal community development. It discusses active transport demands and ways to increase walking and cycling activity. This analysis indicates that many active transport benefits tend to be overlooked or undervalued in conventional transport economic evaluation.
Affective Computing Model With Impulse Control in Internet of Things Based on Affective Robotics

The combination of Internet of Things (IoT) and artificial intelligence (AI) technology plays an important role in many fields, especially in the field of psychology and medical treatment. This work is mainly to study an affective robotics that can serve humans emotionally based on the IoT and AI technology. The design of affective robotics is important to understand the underlying mechanisms of human behaviors in real life. These mechanisms mainly include human nonverbal behaviors and affective states, which are important but difficult to be precisely modeled. To address this challenge, we introduce a human–robot interaction (HRI) architecture, including emotion recognition, affective computing, emotion diagnosis, and emotion control. First, we propose a system model based on HRI between affective robotics and human, in order to enhance the emotional service. Then, we develop a dynamical model with affective computing and control, where we provide a mathematical formulation method based on stochastic differential equations to quantify the emotional state. Furthermore, we perform the dynamic behavior analysis of the existence, boundedness, and stability of the model solution comprehensively. Numerical results are provided to demonstrate the validity and feasibility of the proposed design techniques.
COVID-19: Reshaping Medical Tourism through Artificial Intelligence (AI) and Robotics

The tourism and travel sector is a large and thriving industry, with almost 5 billion international tourist arrivals recorded in 2019, with an annual growth of 4% on the previous year. Yet it suffered a major downturn, globally due to Covid 19. Since the concept of healthcare has existed, humans have been willing to travel to access it. From the spas of the ancient Sumerians, Greeks, and Romans, to the supposed curative properties of alpine and seaside health resorts in early modern Europe, the idea of traveling long distances for health reasons, and marketing destinations for that purpose, is certainly nothing new However, lately, medical tourism has been growing due to the low-cost treatment, Specialization of medical agencies, hospitals, and medical professionals in the host countries. This type of tourism was valued at USD 16.761 million in 2018, and it is expected to reach USD 27,247.6 million by 2024. However, the appearance of COVID 19 has completely changed the tourism sector, where a loss of USD 910 billion to USD 1.2 trillion from export revenues from tourism was reported Moreover, the different types of Tourism and travel industry are taking advantage of Artificial intelligence (AI) in order to perform a variety of administrative and customer service tasks. For medical tourism the development of these technologies (AI, robotic, and so on) play a key role in supporting the medical agencies in connecting physicians and prospective medical tourists. In addition to make it more feasible and credible option for patients, respond to questions and provide valuable information to customers, and allows to reduce the time would be impossible for humans. Furthermore, international remote surgeries will allow various clinical centers to pool their expertise and offer remote surgeries from a central operating theatre that is convenient to access for patients and persuade patients to invest in the local economy. Keywords: Medical Tourism, COVID-19, AI, Robotics.
Wind Atlas Analysis and Application Program: WAsP 11 Help Facility

(02/10/2019) Wind Atlas Analysis and Application Program: WAsP 11 Help Facility The Wind Atlas Analysis and Application Program (WAsP) is a PC-program for horizontal and vertical extrapolation of wind climates. The program contains a complete set of models to calculate the effects on the wind of sheltering obstacles, surface roughness changes and terrain height variations. The analysis part consists of a transformation of an observed wind climate (wind speed and direction distributions) to a generalised wind climate (wind atlas data set). The generalised wind climate can subsequently be applied for estimation of the wind climate and wind power potential, as well as for siting of specific wind turbines and wind farms. The WAsP Help Facility includes a Quick Start Tutorial, a User's Guide and a Technical Reference. It further includes descriptions of the Observed Wind Climate Wizard, the WAsP Climate Analyst, the WAsP Map Editor tool, the WAsP Turbine Editor tool, the Air Density Calculator and various other tools and scripts.
Effect of micronutrients on yield and economics of gynoecious cucumber (Cucumis sativus L) var Kian under naturally-ventilated polyhouse

The economic analysis was conducted for cultivation of gynoecious cucumber var Kian under naturally-ventilated polyhouse during Kharif season of 2014-2015. The experiment consisting of twenty seven treatments was laid out in factorial randomized block design with three replications. The common cost of cultivation for growing cucumber under naturally-ventilated polyhouse was Rs 131.5/m2. The maximum yield per plant (5.62 kg), net income of Rs 498.17/m2 with highest B-C ratio of 3.71 was obtained with foliar application of treatment B2Zn2Fe2(boron at 40 ppm + zinc at 40 ppm + iron at 80 ppm) and it was found significantly superior over control.
How Do Populists Visually Represent ‘The People’? A Systematic Comparative Visual Content Analysis of Donald Trump and Bernie Sanders’ Instagram Accounts

How do populists visually represent “the people”? While the literature on populism has tended to focus on text- and language-based documents, such as speeches, policies, and party documents to consider how populists characterize “the people,” in this article I undertake a systematic visual content analysis to consider how populist leaders on either side of the ideological spectrum visually represent “the people” in images from their official Instagram accounts (N = 432). Comparing the cases of Donald Trump on the populist right and Bernie Sanders on the populist left, I code for the majority gender, race, and age of “the people” in each image, and supplement this with a discussion of the depictions of these categories. I find that Trump’s images of “the people” are significantly more homogenous across all categories—specifically more white, more masculine, and with less young people—than Sanders’, and situate these findings in the context of the literature on the differences between left and right populism. This article contributes to the study of populist communication by highlighting the role of images in representing “the people”; analyzing how left and right populists do this differently; and developing a method for measuring the demographic characteristics of “the people” in populists’ images that can be used in future studies. In doing so, it seeks to push the literature forward by highlighting that images are not something “extra” to be studied in populist communication, but rather are a central battleground for the construction of populist identities.
ADA2b and GCN5 Affect Cytokinin Signaling by Modulating Histone Acetylation and Gene Expression during Root Growth of Arabidopsis thaliana

In Arabidopsis thaliana, the histone acetyltransferase GCN5 and the associated coactivator ADA2b regulate root growth and affect gene expression. The cytokinin signaling reporter TCS::GFP was introduced into gcn5-1, ada2b-1, and ada2a-2, as well as the ada2a-2ada2b-1 mutants. The early root growth (4 to 7 days post-germination) was analyzed using cellular and molecular approaches. TCS signal accumulated from the fourth to seventh days of root growth in the wild-type columella cells. In contrast, ada2b-1 and gcn5-1 and ada2a-2ada2b-1 double mutants displayed reduced TCS expression relative to wild type. Gene expression analysis showed that genes associated with cytokinin homeostasis were downregulated in the roots of gcn5-1 and ada2b-1 mutants compared to wild-type plants. H3K14 acetylation was affected in the promoters of cytokinin synthesis and catabolism genes during root growth of Arabidopsis. Therefore, GCN5 and ADA2b are positive regulators of cytokinin signaling during root growth by modulating histone acetylation and the expression of genes involved in cytokinin synthesis and catabolism. Auxin application in the roots of wild-type seedlings increased TCS::GFP expression. In contrast, ada2b and ada2ada2b mutant plants do not show the auxin-induced TCS signal, suggesting that GCN5 and ADA2b are required for the auxin-induced cytokinin signaling in early root growth.
A Computer Vision-based Assistive Mobile Application for the Visually Impaired

People with visual disabilities suffer environmentally, socially, and technologically. Navigating through places and recognizing objects are already a big challenge for them who require assistance. This study aimed to develop an android-based assistive application for the visually impaired. Specifically, the study aimed to create a system that could aid visually impaired individuals performs significant tasks through object recognition and identifying locations through GPS and Google Maps. In this study, the researchers used an android phone allowing a visually impaired individual to go from one place to another with the aid of the application. Google Maps is integrated to utilize GPS in identifying locations and giving distance directions and the system has a cloud server used for storing pinned locations. Furthermore, Haar-like features were used in object recognition.