Miracle-dz/UniFAR-FTUs huggingface dataset:
STEMI and CVA in Hypercoagulable State with Ostium Secundum Defect

Atrial septal defect (ASD) is a risk factor for multiple vascular thrombotic events, which can occur either sequentially or simultaneously. In this report we present a case of ST-elevation myocardial infarction (STEMI) and cerebrovascular accident (CVA). The severity of adverse cardiovascular or cerebrovascular events can be increased by the presence of specific type of ASD, such as a patent foramen ovale (PFO) or osteum secundum defect. This case report discusses a unique presentation of a 48-year old male on warfarin therapy for a history of cerebral venous thrombosis (CVT) who subsequently presented with simultaneous STEMI with CVA, and who was incidentally found to have an ostium secundum defect on echocardiography. He was emergently taken for cardiac catheterization, which revealed significant proximal LAD occlusion. There has been a long standing debate within the international scientific communities regarding the therapeutic benefit of PFO closure for long-term secondary prevention of recurrence CVA. We discuss the different points of view regarding PFO closure for secondary prevention of CVA with a review of the literature on this rather controversial topic.
Reliability of an isometric and isokinetic strength testing protocol of the knee and ankle in young adults

1 Sport and Exercise Medicine Division, Department of Medicine, University of Padova, Italy 2 Laboratorio de Fisiologia e Bioquimica Experimental, Centro de Educacao Fisica e Deportos, Universidade Federal do Espirito Santo (UFES), Vitoria, Brasil 3 Department of Medicine and Sciences of Aging, G. d’Annunzio University of Chieti-Pescara, Italy 4 Department of Medical Sciences, University of Cagliari, Italy 5 Escola Superior de Educação Física, Universidade Federal de Pelotas, Brasil 6 Department of Neuroscience, University, University of Padova, Italy
Simulação da camada física do protocolo IEEE 802.11AC utilizando a ferramenta Matlab

This work has as purpose the simulation and analysis of wireless transmissions in Matlab of the new standard IEEE 802.11ac, also known as VHT (Very High Throughput), approved in December 2013. Many of the features of the previous versions, specially IEEE 802.11n, have been maintained on the new one, but the main gains on the physical layer enable transmissions with high data rate, reaching almost 7 Gbps on its maximum operation capability (bandwidth of 160 MHz, 256-QAM modulation with code rate of 5/6, eight spatial streams and short guard interval between ODFM symbols). In the simulator used, it was already possible to simulate transmissions with IEEE 802.11a and IEEE 802.11n standards. The main goal of this work was to include some of the new features of the physical layer of the standard IEEE 802.11ac and to make sure coexistence with IEEE 802.11a and IEEE 802.11n. Some of them are the new format of the preamble to IEEE 802.11ac networks, the mapper and demapper of the new 256-QAM order of modulation and transmissions with 80 MHz and 160 MHz.
Efficacy of Antioxidant Supplementation on Conventional and Advanced Sperm Function Tests in Patients with Idiopathic Male Infertility

Antioxidants are used in the empirical treatment of infertile men. The aim of this study was to evaluate the effects of antioxidant therapy on conventional semen parameters and advanced sperm function tests in men seeking fertility treatment. A total of 148 infertile men of unknown etiology were divided into idiopathic (n = 119) and unexplained male infertility (UMI; n = 29). All participants were treated with the antioxidant supplement ‘FH PRO for Men’ for a period of three months. Compared with pretreatment results, there was a significant improvement in conventional semen parameters including sperm concentration, total and progressive motility and normal morphology, and seminal oxidation reduction potential (ORP), and sperm DNA fragmentation (SDF) in idiopathic infertile men. The changes were more prominent in idiopathic infertile men positive for ORP and SDF. UMI patients showed an improvement in progressive motility, ORP, and SDF after antioxidant treatment. Statistical analysis revealed that the efficacy of FH PRO for Men was significant in idiopathic male infertility compared with UMI. Treatment of idiopathic male infertility patients with the FH PRO for Men antioxidant regimen for three months resulted in a significant improvement in conventional semen parameters and sperm function. Therefore, FH PRO for Men offers promise for the medical treatment of idiopathic male infertility.
Optimization of Intelligent Spectrum Sensing Techniques for Cognitive Radio Networks

— Spectrum sensing is a key function of cognitive radio to prevent the harmful interference with licensed users and identify the available spectrum for improving the spectrum’s utilization. However, detection performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been introduced to be an effective method to improve the detection performance by exploiting spatial diversity. Cooperative sensing is the most sophisticated approach in spectrum sensing depends on base of sharing information to eliminate error in spectrum sensing mechanism. While cooperative gain such as improved detection performance and relaxed sensitivity requirement can be obtained, cooperative sensing can incur cooperation overhead. The overhead refers to any extra sensing time, delay, energy, and operations devoted to cooperative sensing and any performance degradation caused by cooperative sensing. In this paper, the state of-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead. Specifically, the cooperation method is analyzed by the fundamental components called the elements of cooperative sensing, including cooperation models, sensing techniques, hypothesis testing, data fusion, control channel and user selection, and knowledge base. The open research challenges related to each issue in cooperative sensing are also discussed. In this review paper, we have discussed the Cooperative sensing approach, different optimization techniques for spectrum searching and sharing features in cognitive radio.
A system biology study of the molecular mechanism of Metformin on breast cancer

Breast cancer is a complicated, heterogeneous and diversified disease that comprises of a mixture of various subtypes. The emergence of high throughout technologies such as gene expression profiling and DNA copy number analysis has allowed a profound awareness of this complex disease. Breast cancer molecular classification began with ER, PR and HER2 based stratification of patients, and further classified into various intrinsic subtypes such as Luminal A, Luminal B, Her-2 enriched, Basal-like, and Claudin-low. These subtypes were proven to have significant divergences in amplified and mutated genes, survival rates, prognosis and response to therapy. The anti-diabetic drug Metformin has been prescribed to treat type 2 diabetes patients since 1957 with a well-established side effects and safety profile. Additionally, cancer researchers have studied the anti-tumour effects of this drug since 2005 and have determined Metformin benefit in the reduction of cancers incidence. Thus, Metformin has been suggested as an ideal candidate to treat and prevent diverse types of cancers, including breast carcinoma. The purpose of this study is to elucidate the biological and molecular effects of Metformin on breast cancer cell lines such as BT-474, MCF-7, MDA-MB-231, MDA-MB-468, and SkBr3. Interestingly, Metformin treatments reduced the viability and proliferation of examined breast cancer cell lines, while induced cells apoptosis. Basal-like (MDA-MB-468) was the most sensitive phenotype to Metformin treatments, whereas HER2 (SkBr3) was the least sensitive subtype. We performed Gene Expression Microarray and NanoString analysis of Metformin treated MDAMB- 468 and SkBr3 cells and found that the upregulated Protein Tyrosine Kinase 2 Beta (PTK2B) was predominantly involved in cell proliferation, cell survival, cell migration and cell invasion. We found that PTK2B promotes invasion and migration, while prevents the proliferation of breast cancer cells. It is also, playing a vital role in Autocrine Somatotropin signalling pathway in breast cancer. Additionally, Mass Spectrometry (MS) analyses and pathways enrichment analysis that has emphasised the role of PTK2B in breast cancer invasion and metastasis. Additionally, the combined action of both selected markers and Metformin treatment on fundamental biological functions in breast cancer were also assessed. These data showed that Metformin promotes Her-2 enriched breast cancer invasion through mechanisms involving PYK2, and that future treatments should consider potential complications resulting from metformin-based therapies.
Anatomy of Threats to the Internet of Things

The world is resorting to the Internet of Things (IoT) for ease of control and monitoring of smart devices. The ubiquitous use of IoT ranges from industrial control systems (ICS) to e-Health, e-Commerce, smart cities, supply chain management, smart cars, cyber physical systems (CPS), and a lot more. Such reliance on IoT is resulting in a significant amount of data to be generated, collected, processed, and analyzed. The big data analytics is no doubt beneficial for business development. However, at the same time, numerous threats to the availability and privacy of the user data, message, and device integrity, the vulnerability of IoT devices to malware attacks and the risk of physical compromise of devices pose a significant danger to the sustenance of IoT. This paper thus endeavors to highlight most of the known threats at various layers of the IoT architecture with a focus on the anatomy of malware attacks. We present a detailed attack methodology adopted by some of the most successful malware attacks on IoT, including ICS and CPS. We also deduce an attack strategy of a distributed denial of service attack through IoT botnet followed by requisite security measures. In the end, we propose a composite guideline for the development of an IoT security framework based on industry best practices and also highlight lessons learned, pitfalls and some open research challenges.
Ensuring Data Quality for Environmental Fatigue: INCEFA-PLUS Testing Procedure and Data Evaluation

INCEFA-PLUS stands for INcreasing safety in nuclear power plants by Covering gaps in Environmental Fatigue Assessment. It is a five year project supported by the European Commission HORIZON2020 program that commenced in mid-2015 and in which sixteen organizations from across Europe participate. Specifically, the effects of mean strain/stress, hold time, strain amplitude and surface finish on fatigue life of austenitic stainless steels in light water reactor environments are being studied, these being issues of common interest to all participants. The project will develop proposals for improvements to methods for environmental fatigue assessment of nuclear plant components. Therefore, extensive testing capacity is being solicited in various laboratories across Europe in order to add to the existing amount of published data on environmentally assisted fatigue. Since there currently is no standard on environmental fatigue testing, it was imperative to come up with and agree upon a testing procedure within the consortium to minimize lab-to-lab variations in test results. This was done prior to the first phase of testing, but an update of the procedure was required after review of initial results, when additional potential lab-to-lab differences were identified. The current status of the so-called test protocol, and the key areas of difference found between different testing facilities, will be discussed. Due to the large test matrix within INCEFA-PLUS, distributed amongst various test laboratories, it has been necessary to develop a method to assign a data quality level to each test result, and a minimum data quality requirement for results that will be included in the project’s datasets used for analysis. Furthermore, the project has triggered international interest in facilitating mutual data access, and this requires data is gathered in a common database with data quality ratings applied. Ways to address the evaluation of data quality will be discussed. In a way, both activities, on a test protocol and on data review, jointly contribute to data quality by, respectively, ensuring a pre-test, common test procedure and a post-test, harmonized data evaluation. The large number of participants in the INCEFA-PLUS project presents a unique opportunity to gain consensus on light water reactor environment fatigue testing procedures and data quality assessment from experts working in a range of different organizations. The test protocol and data quality ratings developed within the INCEFA-PLUS project could be adopted by other organizations, or possibly used as the basis for future testing standards documents to harmonize approaches across the nuclear industry.
The necessity, efficacy and safety of biologics in juvenile idiopathic arthritis

OBJECTIVE: Juvenile idiopathic arthritis (JIA) is the most common cause of chronic arthritis in children. Biologics have changed the faith of children with rheumatic diseases. The main objective of this study was to demonstrate the rate of usage, efficacy and safety of biologics in JIA subtypes. METHODS: This retrospective observational cohort study was conducted between May 2010 and September 2017. All children with the diagnosis of JIA and children under a biological agent treatment were recorded into the local registry system. Age, gender, JIA subtype, medications used, the clinical status of the patient, tuberculosis screening results, and side effects observed under biologics were retrieved from the registry. RESULTS: There were 405 patients with the diagnosis of JIA in the cohort. Biologics were used in 123 (30.3%) JIA patients. Subtype frequencies of JIA patients were as follows: persistent oligoarticular JIA (33.6%), enthesitis-related arthritis (29.2%), systemic JIA (13%), rheumatoid factor (RF)-negative polyarticular JIA (13%), extended oligoarticular JIA (4.2%), RF-positive polyarticular JIA (3.4%), psoriatic arthritis (1.8%) and unclassified arthritis (1.8%). The rate of biologic use was high in extended oligoarticular JIA (64.7% of the cases), RF-positive polyarticular JIA (57.1%), psoriatic arthritis (57.1%), RF-negative polyarticular JIA (41.5%), and in systemic JIA (39.6%). Enthesitis-related arthritis (27.1%), persistent oligoarticular JIA (17.6%) and unclassified arthritis (16.6%) patients were the cases that needed a biologic agent in the last order. At the last control, 78.9% of the cases were in remission, while 21.1% of them were active despite biologic treatment. Isoniazid prophylaxis was used in 30.8% of the patients. None of the patients developed active tuberculosis infection under prophylaxis. Adverse events were observed in 18.6% of patients under biologics as recurrent uncomplicated upper respiratory tract infections being the most common. CONCLUSION: Biologics are safe and effective treatment options in children with JIA. Most of the JIA patients with polyarticular involvement require biologics earlier in the disease course. The risk of tuberculosis infection seems not to be increased after appropriate screening and prophylaxis.
3D Forensic Facial Reconstruction: A Review of the Traditional Sculpting Methods and Recent Computerised Developments

Forensic facial reconstruction aims at achieving a likeness of the facial outlook of the deceased based on the underlying skull for the purpose of recognition and identification. On encountering a greatly decomposed, mutilated, or skeletonized body, facial reconstruction can be used as a last resort technique to identify the unknown skeletal remains, when the usual methods of investigation fail. This paper focuses mainly on the three-dimensional aspect of facial reconstruction, giving an overview of both the traditional and the computerized techniques. Traditional methods involve physically modeling the clay onto the skull replica to sculpt the face, which tends to be subjective and time-taking. However, with the recent advancement in technology, newer, more rapid and flexible computer-based techniques are underway. Nevertheless, all reconstruction techniques are based on the relationship between the skull and the overlying tissues and thus, the evolution of the various techniques for facial soft tissue depth measurements along with their limitations have also been summarised. One of the major challenges it has to face in the coming future will be to fully explore this relationship between the hard and soft tissues and furthermore increase the accuracy and reliability of the various techniques.
Prevalence and outcome of central airway obstruction in patients with lung cancer

Introduction Central airway obstruction (CAO) is a life-threatening complication of lung cancer. The prevalence of CAO in lung cancer patients is unknown. We audited CAO burden to inform our local cancer service. Methods This is a cohort review of all new lung cancer diagnoses between 1 November 2014 and 30 November 2015. CAO was defined by CT appearance. CT scans and routine patient records were followed up to 30 November 2018 to determine the prevalence of CAO at diagnosis; the characteristics of patients with prevalent CAO; mortality (using survival analysis); and incident CAO over follow-up. Results Of 342 new lung cancer diagnoses, CAO prevalence was 13% (95% CI 10% to 17%; n=45/342). Dedicated CT scan review identified missed CAO in 14/45 (31%) cases. In patients with prevalent CAO, 27/44 (61%) had a performance status of ≤2, 23/45 (51%) were diagnosed during an acute admission and 36/44 (82%) reported symptoms. Treatments were offered to 32/45 (71%); therapeutic bronchoscopy was performed in only 8/31 (26%) eligible patients. Median survival of patients with prevalent CAO was 94 (IQR 33–274) days. Multivariate analysis, adjusting for age, gender and disease stage, found CAO on index CT scan was independently associated with an increased hazard of death (adjusted HR 1.78 (95% CI 1.27 to 2.48); p=0.001). In total, 15/297 (5%) developed CAO during follow-up (median onset 340 (IQR 114–551) days). Over the audit period, 60/342 (18%; 95% CI 14% to 22%) had or developed CAO. Discussions This is the first description of CAO prevalence in 40 years. Patients with prevalent CAO had a higher mortality. Our data provide a benchmark for service planning.
Automatically Correcting Semantic Errors in Programming Assignments

MOOCs allow thousands of students to be taught how to program at scale and, using automatic error correction, personalized feedback can also be provided at scale. Current NLP techniques have been used to correct errors in programming assignments, however, these mainly focus on syntactic errors and do not take advantage of NLU techniques to understand the desired semantics. By understanding semantics, there is a potential that the accuracy of error corrections can be vastly improved as focus shifts to correcting errors speciﬁc to the desired problem, rather than errors common across all programs. Each step of the process also gives an opportunity to do surrounding work on NLU techniques applied to source code.
DEVELOPMENT OF WEBGIS BASED REAL TIME ROAD TRAFFIC INFORMATION SYSTEM

Abstract. Rapid increase in road traffic density results into a serious problem of Traffic Congestion (TC) in cities. During peaks hours TC is very high and hence public search least congested path for their journeys in order to minimize ravel time and hence transportation cost. In this study, a new empirical model was developed to estimate congestion levels using real time road Traffic Parameters (TPs) such as vehicle density, speed, class and vehicle-to-vehicle (V2V) gap. These real time road TPs were collected using latest generation Inductive Loop Detector (ILD) technology. Further, a WebGIS based Road Traffic Information System (RTIS) for Dehradun city was developed for real time TD analyses and visualisation. This RTIS is very useful for public and user departments for planning and decision making processes. No other such system is available in India, which handles multiple traffic parameters simultaneously to provide solution of day-to-day problems.
Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks

Even though computational intelligence techniques have been extensively utilized in financial trading systems, almost all developed models use the time series data for price prediction or identifying buy-sell points. However, in this study we decided to use 2-D stock bar chart images directly without introducing any additional time series associated with the underlying stock. We propose a novel algorithmic trading model CNN-BI (Convolutional Neural Network with Bar Images) using a 2-D Convolutional Neural Network. We generated 2-D images of sliding windows of 30-day bar charts for Dow 30 stocks and trained a deep Convolutional Neural Network (CNN) model for our algorithmic trading model. We tested our model separately between 2007-2012 and 2012-2017 for representing different market conditions. The results indicate that the model was able to outperform Buy and Hold strategy, especially in trendless or bear markets. Since this is a preliminary study and probably one of the first attempts using such an unconventional approach, there is always potential for improvement. Overall, the results are promising and the model might be integrated as part of an ensemble trading model combined with different strategies.
A Comprehensive survey on deep future frame video prediction

El present projecte planteja l'estudi comprensiu i extens per a la tasca de prediccio de fotogrames donada una sequencia de video. Mitjancant l'analisi de l'estat de l'art en generacio d'imatges, xarxes convolucionals i adversaries l'objectiu es establir les forces i utilitats d'aquesta tasca.
Cooperative Inverse Reinforcement Learning - Cooperation and learning in an asymmetric information setting with a suboptimal teacher

There exists many different scenarios where an artificial intelligence (AI) may have to learn from a human. One such scenario is when they both have to cooperate but only the human knows what the goal is. This is the study of cooperative inverse reinforcement learning (CIRL). The purpose of this report is to analyze CIRL when the human is not behaving fully optimally and may make mistakes. The effect of different behaviours by the human is investigated and two frameworks are developed, one for when there is a finite set of possible goals and one for the general case where the set of possible goals is infinite. Two benchmark problems are designed to compare the learning performance. The experiments show that the AI learns, but also that the humans behaviour has a large affect on learning. Also highlighted by the experiments, is the difficulty of differentiating between the actual goal and other possible goals that are similar in some aspects.